ACTA BIOLOGICA SLOVENICA VOL. 65 ŠT. 2 LJUBLJANA 2022 ISSN 1854-3073 UDK 57(497.4) izdajatelj/publisher Društvo biologov Slovenije prej/formerly BIOLOŠKI VESTNIK VOL. 65 ŠT. 2 LJUBLJANA 2022 ACTA BIOLOGICA SLOVENICA prej/formerly BIOLOŠKI VESTNIK ISSN 1854-3073 izdajatelj/publisher UDK 57(497.4) Društvo biologov Slovenije ACTA BIOLOGICA SLOVENICA LJUBLJANA 2022 Vol. 65, Št. 2: 1–118 Acta Biologica Slovenica Glasilo Društva biologov Slovenije – Journal of Biological Society of Slovenia Izdaja – Published by Društvo biologov Slovenije – Biological Society of Slovenia Glavna in odgovorna urednica – Editor in Chief Jasna Dolenc Koce, e-mail: jasna.dolenc.koce@bf.uni-lj.si Tehnična urednica – Managing Editor Anita Jemec Kokalj, e-mail: anita.jemec@bf.uni-lj.si Uredniški odbor – Editorial Board Franc Batič (SLO), Gregor Belušič (SLO), Tina Eleršek (SLO), Alenka Gaberščik (SLO), Georg A. 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Naslov uredništva – Address of Editorial Office Acta Biologica Slovenica, Večna pot 111, SI-1001 Ljubljana, Slovenija http://bijh.zrc-sazu.si/abs/ Zasnova oblikovanja – Design Žare Vrezec ISSN 1854-3073 (Spletna izdaja - Web edition) UDK 57(497.4) Grafična priprava: Tisk Žnidarič d.o.o., Kranj Cena letnika (dve številki): 15 € za posameznike, 42 € za ustanove Številka poslovnega računa pri Ljubljanski banki: 02083-142508/30 Publikacijo je sofinancirala Javna agencija za raziskovalno dejavnost Republike Slovenije Acta Biologica Slovenica je indeksirana v – is indexed in: CAB Abstracts, Web of Science Clarivate PREGLEDNA ČLANKA – REVIEW PAPERS: Adrijana LEONARDI Masna spektrometrija v raziskavah kačjih strupov / Mass spectrometry in snake venom research...........................................................................................................................................5 Alenka GABERŠČIK, Matej HOLCAR, Mateja GRAŠIČ Optical properties of different structures of some herbaceous understorey plant species from temperate deciduous forests / Optične lastnosti različnih struktur pri nekaterih zelnatih rastlinskih vrstah v podrasti zmernega listopadnega gozda..........................................................26 ZNANSTVENA ČLANKA – SCIENTIFIC ARTICLES: Martina TURK, Vesna PODGRAJŠEK, Cene GOSTINČAR, Nina GUNDE-CIMERMAN Aerobic bacteria in holy water from Catholic churches in Slovenia / Aerobne bakterije v blagoslovljeni vodi iz katoliških cerkva v Sloveniji......................................................................42 Bahareh NOWRUZI Phylogenetic study of Aliinostoc species (Cyanobacteria) using pc-igs, nifH and mcy as markers for investigation of horizontal gene transfer / Filogenetska študija vrst Aliinostoc (Cyanobacteria) z uporabo označevalcev pc-igs, nifH in mcy za ugotavljanje horizontalnega genskega prenosa.........................................................................................................................104 NOVICA – NEWS: Špela BAEBLER Plants in changing evironment – mednarodna konferenca Slovenskega društva za biologijo rastlin / Plants in changing evironment – International conference of Slovene society of plant biology.........................................................................................................................................116 Acta Biologica Slovenica, 2022, 65 (2) Masna spektrometrija v raziskavah kačjih strupov Mass spectrometry in snake venom research Adrijana Leonardi Institut »Jožef Stefan«, Odsek za molekularne in biomedicinske znanosti, Jamova 39, 1000 Ljubljana, Slovenija Korespondenca: adrijana.leonardi@ijs.si Izvleček: Masna spektrometrija omogoča hitro in zanesljivo identifikacijo in karakterizacijo proteinov in peptidov v kačjih strupih. Z vse večjo dostopnostjo tran- skiptomskih in genomskih podatkov se veča podatkovna baza proteinskih zaporedij, ki je ključna za identifikacijo proteinov. Kačje strupe analiziramo z večdimenzionalnim proteomskim pristopom, poimenovanim »venomika«. Proteine najprej med seboj ločimo z eno- ali dvo-dimenzionalno gelsko elektroforezo ali s hitro tekočinsko kromatografijo na obrnjenih fazah. Posamezne proteinske lise oziroma frakcije encimsko razgradimo in dobljene peptide analiziramo z masnim spektrometrom. Proteine identificiramo s primerjavo masnih spektrov peptidov s spektri v podatkovni bazi. Visoko zmogljivi masni spektrometri omogočajo analizo strupov tudi brez predhodnega ločevanja meša- nice proteinov v strupu. Analizirali smo proteinski sestavi (proteoma) dveh evropskih, medicinsko najbolj zanimiv kačjih strupov, modrasovega (Vipera a. ammodytes) in ga- dovega (Vipera b. berus). Modras je najbolj strupena evropska kača. Njen ugriz je sicer redko smrten, pogosto pa zahteva bolnišnično opazovanje in zdravljenje s protistrupom. Gad je najbolj razširjena evropska strupenjača, katere ugriz v večini primerov izzove blažje simptome kot ugriz modrasa. S proteomsko raziskavo smo na molekulskem nivoju razložili opažene razlike v delovanju obeh strupov. Poleg tega smo analizirali tudi proteom strupa malega gada (Vipera ursinii ssp.), najbolj ogrožene evropske kačje vrste. Za človeka ne predstavlja nobene nevarnosti. V naravi se prehranjuje pretežno z insekti, medtem ko jih v ujetništvu hranijo z mišmi. Primerjava proteomske analize strupa kač iz naravnega okolja in strupa kač iz ujetništva je pokazala očitne razlike. Sestava kačjega strupa je torej pogojena z dieto. Masna spektrometrija je zelo uporab- no orodje tudi pri karakterizaciji protistrupov (antivenomika), za določanje njihove specifičnosti in nevtralizacijske moči. Ključne besede: antivenomika, kačji strup, mali gad, masna spektrometrija, modras, navadni gad, proteomika, venomika, Vipera a. ammodytes, Vipera b. berus, Vipera ursinii Abstract: Mass spectrometry allows rapid and reliable identification and charac- terisation of proteins and peptides in snake venoms. With the increasing availability of transcriptomic and genomic data, there is a growing database of protein sequences that is essential for protein identification. Snake venoms are analysed using a multi- ACTA BIOLOGICA SLOVENICA LJUBLJANA 2022 Vol. 65, Št. 2: 5–25 6Acta Biologica Slovenica, 2022, 65 (2), 5–25 dimensional proteomic approach known as ‚venomics‘. Proteins are first separated by one- or two-dimensional gel electrophoresis or reversed-phase liquid chromatography. The individual protein spots or fractions are digested enzymatically and the resulting peptides are analysed by mass spectrometry. The proteins are identified by comparing the mass spectra of the peptides with those in the database. High-performance mass spectrometers allow the analysis of venoms even without prior separation of the protein mixture. We have analysed the protein composition (proteome) of two European snake venoms of greatest medical interest, the nose-horned viper (Vipera a. ammodytes) and the common adder (Vipera b. berus). The nose-horned viper is the most venomous European snake. Although its bite is rarely fatal, a human wictim often needs to be observed in hospital and treated with an antivenom. The adder is the most widespread European venomous snake and its bite causes milder symptoms than the bite of the nose-horned viper in most cases. To explain the observed differences in the effects of the two venoms at the molecular level, a proteomic study was performed. We also analysed the proteome of the venom of the meadow viper (Vipera ursinii), the most threatened snake species in Europe. It does not pose a threat to humans. In the wild, it feeds mainly on insects, while in captivity it is fed on mice. A comparison of the proteome of the venom of snakes in the wild and snakes in captivity showed clear differences. Thus, the composition of snake venom is diet-dependent. Mass spectrometry is also a very useful tool in the characterisation of antivenoms (antivenomics) to determine their specificity and neutralising power. Keywords: antivenomics, common adder, mass spectrometry, meadow viper, nose-horned viper, proteomics, snake venom, venomics, Vipera s. ammodytes, Vipera b. berus, (Vipera ursinii) Uvod Strupene kače so skozi evolucijo razvile enega najbolj izpopolnjenih orožij v naravi. Njihov strup lahko povzroči prizadetost ali celo smrt, zato so se jih ljudje skozi zgodovino bali, jih častili in jim pripisovali nadnaravne moči. Raziskave kačjega strupa so v sodobnem času usmerjene predvsem v obvladovanje kačjih ugrizov, v razvoj diagnostike in protistrupov (antidotov) ter novih pristopov zdravljenja. Kačji strupi so zanimivi tudi kot potencialni vir visoko specifičnih farmakološko aktivnih snovi in spojin vodnic za razvoj inovativnih zdravil. Opisanih je že več kot 3000 vrst kač, od katerih je le ena petina strupenih (Uetz in sod. 2022). Slednje razvrščamo v štiri družine: Colubridae (goži), Elapidae (strupeni goži), Atractaspidae (zemeljski gadi) in Viperidae (gadi). Približno deset odstotkov vseh kač (376 vrst) pripada družini Viperidae. Ta se naprej deli na tri poddružine: Azemiopinae in Crotalinae (jamičarke) ter Viperinae (pravi gadi). Evolucijski izvor poddružine Viperinae (trenutno obsega 100 vrst) je še vedno nejasen, vendar sega v srednji Okrajšave: 1DE, enodimenzionalna gelska elektroforeza; 2DE, dvodimenzionalna gelska elektroforeza; cDNA, komplementarna deoksiribonukleinska kislina; CRISP, s cisteinom bogati sekretorni proteini; CTL, lektini tipa C; DIS, disintegrini; DNA, deoksiribonukleinska kislina; ELISA, encimsko-imunski test; ESI, elektrosprej ionizacija (ang. electrospay ionization); LC, tekočinska kromatografija (ang. liquid chromatography); KUN, peptidi Kunitzovega tipa; LAO, L-aminokislinske oksidaze; MALDI, ionizacija z lasersko desorbcijo ob pomoči matrice (ang. matrix- -assisted laser desorption/ionization); MPKS, metaloproteinaze iz kačjih strupov; MS, masna spektrometrija; MS/ MS, tandemska masna spektrometrija; NaDS-PAGE, poliakrilamidna gelska elektroforeza v prisotnosti natrijevega dodecil sulfata; NCBI, Nacionalni center za biotehnološke informacije (ang. National Center for Biotechnology Information); RNA, ribonukleinska kislina; RP-HPLC, visokotlačna tekočinska kromatografija na obrnjenih fazah; sPLA2, sekretorne fosfolipaze A2; SPKS, serinske proteaze iz kačjih strupov; TOF, čas preleta ionov (ang. time of flight); WHO, Svetovna zdravstvena organizacija (ang. World Health Organization). 7Leonardi: Venomika in antivenomika kačjih strupov eocen in zgodnji miocen (42 do 34 milijonov let nazaj) (Alencar in sod. 2016). Najstarejši znani fosil, Vipera antiqua, pa so našli v srednji Evropi in je datiran v zgodnji miocen, pred približno 22,5 milijoni let (Šmíd in Tolley 2019). Odtlej so se Viperinae razvile v več linij in osvojile “Stari svet”. Ob Evropi (z izjemo Irske in nekaj sredo- zemskih otokov), te kače najdemo na Bližnjem vzhodu, v Afriki (z izjemo Madagaskarja) in v Aziji, celo na skrajno vzhodnih otokih, Tajvanu in Sahalinu. V Sloveniji lahko srečamo modrasa (Vipera ammodytes ammodytes), navadnega gada (Vipera berus berus) in laškega gada (Vipera aspis, podvrsta francisciredi). Prvi je najbolj strupena, drugi pa najbolj razširjena evropska strupenjača. Strupene kače so za onesposobitev ali celo usmrtitev plena razvile zelo zapleten strupni aparat (Mebs 2002). Na obeh straneh zgornje čeljusti se nahajajo posebne strupne žleze, ki razvojno izha- jajo iz žlez slinavk in proizvajajo strupen izloček oziroma strup. Tega ob ugrizu kače vbrizgajo v plen skozi ostre strupnike, različno dolge votle zobe z majhno odprtinico na konici. Pri velikih kačah iz družine gadov, npr. puhnici (Bitis arietans), so strupniki daljši od 3 cm, pri slovenskih strupenja- čah pa niso daljši od enega centimetra. Količino iztisnjenega strupa kača regulira s pritiskom mišic na žlezo. Tako v primeru obrambnega ugriza včasih celo ne pride do izločanja strupa. Takemu ugrizu pravimo suhi ugriz. Kače svoj plen pogoltnejo v celoti, zato mora strup hitro in učinkovito prizadeti vitalne telesne funkcije žrtve, npr. blokirati krčenje mišic ali pretok krvi. Delovanje strupa je odvisno od njegove sestave, ki je značilna za vsako kačjo družino. Strupi gožev in gadov najbolj zmotijo strjevanje krvi (hemotoksičnost), strupi zemeljskih gadov delovanje srca (kardiotoksičnost), strupi strupenih gožev pa poleg delovanja srca tudi delovanje živčevja (nevrotoksičnost). Izvor in sestava kačjih strupov Kačji strupi vsebujejo mešanico biološko aktivnih proteinov in peptidov (približno 90- 95 % mase strupa) ter drugih neproteinskih sestavin, vključno z ogljikovimi hidrati, lipidi, amini in anorganskimi solmi (Villar-Briones in Aird 2018; Mebs 2002). Proteinske komponente izvirajo iz genov, ki sicer nosijo zapis za telesne proteine, po navadi tiste, ki sodelujejo v ključnih fizioloških procesih v telesu (npr. v hemostazi, prenosu živčnega signala …). V evoluciji je prišlo do podvajanja teh genov, prenosa ene od kopij v strupno žlezo in njenega razvoja v strupni žlezi, kjer je v procesu neofunkcionalizacije razvila nove funkcije za učinkovito delovanje strupne žleze (Barua in Mikheyev 2020). Da bi bili učinkoviti pri lovljenju plena in obrambi pred plenilci, se geni za toksine, v primerjavi z geni za netoksične proteine, razvijajo precej hitreje (Kini 2018). Predlaganih je bilo več različnih mehanizmov za razlago tega zanimivega pojava, kot so pogostejše mutacije v eksonih (delih gena, ki nosijo zapis za protein) v primerjavi z introni (delih gena, ki ne nosijo zapisa za protein) in nesinonimne zamenjave v eksonih (zamenjava nukleotida v DNA, ki pov- zroči spremembo v aminokislinskem zaporedju), visoka pogostost točkovnih mutacij, spremembe na meji med intronom in eksonom, izbris eksona in izguba/pridobitev domen z rekombinacijo ter hitro kopičenje mutacij, ki povzročajo spremembe na površini proteinske molekule. V multigenskih družinah toksinov se ohrani osnovno molekulsko ogrodje izvornega proteina (tridimenzionalna struktura), spreminjajo pa se aminokislinski ostanki izven ogrodnih, ki so ključni za funkcijo. Tako skozi evolucijo nastajajo izooblike osnovne molekule z novimi aktivnostmi (Fry in sod. 2009). Dejavniki, ki vplivajo na neofunkcionalizacijo so številni, nekateri še neznani, povzročajo pa variacije v sestavi strupa. Na krajši rok pa so za sestavo strupa pomembni dejavniki, ki vplivajo na izražanje strupnih genov. Tako sestava strupa variira glede na vrsto in geografsko podvrsto kače, njen spol, starost in velikost kot tudi prehrano in letni čas (Chippaux in sod. 1991; Lang Balija in sod. 2005). Venomika kačjih strupov V novem tisočletju je masna spektrometrija (MS) postala glavna analitska metoda v proteomiki, masovno in hitropretočno identifikacijo in karak- terizacijo kompleksnih proteinskih zmesi, kakršne so tudi kačji strupi. Skokovit tehnični napredek na področju MS in proteomike vzporedno z nekaterimi 8Acta Biologica Slovenica, 2022, 65 (2), 5–25 drugimi »omik«-tehnologijami, transkriptomiko in genomiko, toksinologom omogočajo bolj in bolj poglobljeno kvalitativno in kvantitativno analizo živalskih strupov, tako imenovano venomiko (Calvete in sod. 2007; Calvete in sod. 2009). Masna spektrometrija–Proteomika MS temelji na analizi ionov v plinastem stanju. Ti se v magnetnem polju ločijo glede na razmerje njihove mase in naboja (m/z). Glede na način ionizacije (npr. elektrosprej (ang. electrospay ionization, ESI); ionizacija z lasersko desorbcijo ob pomoči matrice (ang. matrix-assisted laser desorption/ionization, MALDI) in masnega ana- lizatorja (npr. kvadrupolni, na ionsko past, na čas preleta ionov ( ang. time of flight, TOF) ločimo več vrst masnih spektrometrov. Za določanje mase celih proteinskih molekul se uporablja kombinacija MALDI- ali ESI-TOF, medtem ko je kombinacija ESI in analizatorja z ionsko pastjo ali trojnega kvadrupolnega (ang. quadrupole, Q) analizatorja primerna za generiranje sekundarnih ionskih spektrov in s tem za »de novo« sekven- ciranje peptidov. Identifikacijo proteinov z MS najpogosteje izvajamo s pristopoma »od spodaj navzgor« (ang. bottom-up) in »od zgoraj navzdol« (ang. top-down) (Sl. 1). Proteomika »od spodaj navzgor« temelji na MS in MS/MS analizi peptidov, dobljenih z encimsko ali kemično razgradnjo proteinov. Peptidni oziroma prekurzorski ion ujamemo v kolizijski celici in izzovemo njegovo delno fragmentacijo. Tako se v prekurzorskem ionu delno cepijo le vezi v osnovni peptidni verigi, da nastanejo fragmenti - produktni ioni, ki se med seboj razlikujejo le za en aminoki- slinski ostanek. Produktne ione analiziramo, da dobimo MS/MS spekter, ki je specifičen za vsak peptid oziroma njegov prekurzorski ion. Odvisen je od njegovega aminokislinskega zaporedja in predstavlja njegov »prstni odtis«. Peptide identi- ficiramo z bioinformatskimi analizami MS in MS/ MS spektrov, ki uporabljajo različne algoritme za iskanje po podatkovnih bazah (npr. Mascot in Sequest) (Chen in sod. 2020). Slednje temelji na matematični primerjavi prekrivanja masnih spektrov analiziranih peptidov z bazo podatkov, v kateri so eksperimentalno določeni ali/in teoretično generirani peptidni MS spektri proteinov. Rezultat računalniške analize je najverjetnejša identiteta analiziranega proteina. Pri proteomskem pristopu »od zgoraj nav- zdol« (Sl. 1) analiziramo cele proteinske mole- kule (Schaffer in sod. 2019). Z ESI ali MALDI ionizacijo se v plinski fazi pripravijo ioni celih proteinov, ki jih potem analiziramo s TOF analizatorjem. Prednost te metode je, da lahko med seboj ločimo vse oblike, v katerih določeni protein obstaja (proteoforme) - so sicer produkt istega gena, a rezultat specifičnih genetskih vari- acij, alternativnega spajanja in posttranslacijskih modifikacij. Proteinski ioni lahko fragmentirajo z disociacijo, povzročeno s trki, ali z metodama »mehke« disociacije z zajemanjem elektronov ali prenosom elektronov v masnem spektrometru. Pri tem razberemo molekulsko maso proteinskega iona in mase njegovih fragmentov - peptidov (»prstni odtis« proteina). Če je za identifikacijo potrebno, lahko večje peptide dodatno fragmen- tiramo in produkte analiziramo s tandemsko MS (MS/MS). V primeru MS analize čistih proteinov lahko določimo njihovo celotno primarno strukturo vključno s post-translacijskimi modifikacijami. Fragmentacija ionov celih proteinov z visoko molekulsko maso (večjo od 50-70 kDa) v plinski fazi je težavna, zato je za razločevanje razlik med velikimi molekularnimi ioni podobnih mas potreben instrument zelo visoke ločljivosti. Glavni izzivi, s katerimi se trenutno sooča proteomika »od zgoraj navzdol«, so še posebej omejena to- pnost proteinov, dinamično območje proteomov, kompleksnost proteomov in analiza kompleksnih podatkov (Melby in sod. 2021). Glede na dopolnjujočo se naravo informacij, ki jih zagotavljata oba pristopa masne analize proteinov, se bosta v proteomiki še naprej upora- bljala oba. Različne statistične metode in metode strojnega učenja, ki so bile razvite za izvajanje poglobljene analize v proteomskih študijah, pa nam omogočajo, da kvalitativne in kvantitativne podatke o proteinih uporabimo pri rekonstrukciji proteinskih interakcij in signalnih omrežij. 9Leonardi: Venomika in antivenomika kačjih strupov Slika 1: Pristopi v proteomiki, ki temeljijo na masni spektrometriji. S proteomiko »od spodaj navzgor« (ang. bot- tom-up) analiziramo manjše proteinske fragmente (peptide), pridobljene z encimsko (najpogosteje se uporablja tripsin) ali kemično razgradnjo proteinov. Posamezni peptidni ion v masnem spektrometru fragmentiramo, da dobimo tandemski masni spekter (MS/MS spekter), ki je značilen za vsak peptid oziroma njegov prekurzorski ion (»prstni odtis« peptida) posebej. Z uporabo računalniških algoritmov primerjamo izmerjene mase peptidnih ionov in/ali njihovih fragmentov z bazo podatkov, v kateri so teoretično generirani peptidni masni spektri (MS in MS/MS) proteinov. Rezultat te analize je najver- jetnejša identiteta analiziranega proteina. S proteomiko »od zgoraj navzdol« (ang. top-down) dobimo informacijo o masi celih, intaktnih proteinskih molekul, vključno z njihovimi post-translacijskimi mo- difikacijami. Za identifikacijo cele proteine fragmentiramo v masnem spektrometru, da dobimo masno lestvico fragmentov, značilno za vsak protein (t.i. »prstni odtis« proteina). Figure 1: Mass spectrometry-based approaches in proteomics. Bottom-up proteomics is used to analyse small protein fragments (peptides) obtained by enzymatic (usually trypsin) or chemical degradation of pro- teins. A single peptide ion is fragmented inside mass spectrometer to obtain a tandem mass spectrum (MS/MS spectrum), characteristic for each peptide i.e. its precursor ion (the peptide‘s »fingerprint«). Computer algorithms are used to compare the acquired masses of the peptide ions and/or their fragments with a database containing theoretically generated peptide mass spectra (MS and MS/MS) of proteins. The result of this analysis is the most probable identity of the analysed protein. Top-down proteomics provides information on the mass of whole, intact protein molecules, including their post-translational modifications. For identification, the proteins are fragmented in the mass spectrometer to obtain a ladder of fragment masses, characteristic for each protein (the protein‘s »fingerprint«). 10Acta Biologica Slovenica, 2022, 65 (2), 5–25 Proteomski pristopi v venomiki Ena sama analitična metoda ne zadostuje za razkritje kompleksnosti kačjega strupa, vsak pristop pa ima svoje prednosti in omejitve. Postopek se začne z odvzemom strupa, ki je preprost, vendar ključen korak, ki ima velik vpliv na nadaljnjo analizo in razlago podatkov. Pred tem morajo raziskovalci pridobiti uradna dovoljenja za te- rensko delo, ki so odvisna od kraja zbiranja in statusa ohranjenosti ciljne vrste. V Sloveniji so vse strupene kače razglašene za ogrožene vrste (Uradni list RS, 1993). Ročno odvzemanje strupa z »molžo« je daleč najpogostejša metoda za pri- dobivanje kačjega strupa. Pri tem žival ugrizne v s tanko membrano prekrito čisto stekleno posodo in vanjo sprosti strup. Tako zbrani strup lahko desetletja hranimo zamrznjenega pri temperaturah od -20 do -80 oC. Večinoma se strup hrani v liofi- lizirani obliki. Tako zagotovimo še dolgotrajnejšo stabilnost proteinskih komponent. Calvete in sod. (2007) so predlagali postopek za analizo kačjih strupov, ki temelji na proteomiki »od spodaj navzgor« in je do danes ostal zlati standard venomike. Po ločevanju surovega strupa z visokotlačno tekočinsko kromatografijo na obr- njenih fazah (RP-HPLC) sledi analiza proteinskih frakcij z enodimenzionalno poliakrilamidno gelsko elektroforezo v prisotnosti detergenta natrijevega dodecil sulfata (1D NaDS-PAGE; 1DE). Odvisno od količine, proteine v gelu vizualiziramo z različnimi z MS kompatibilnimi barvili, kot npr. Coomassie modrim, Ponceau rdečim in koloi- dnim srebrom (Miller in sod. 2006). Obarvane proteinske lise izrežemo iz gela, proteine v gelu reduciramo, alkiliramo njihove proste SH-skupine (npr. karbamidometiliramo) in jih razgradimo s tripsinom. Nastale peptide ekstrahiramo iz gela, nato pa analiziramo in identificiramo s tandemsko MS. Relativno količino proteina lahko ocenimo glede na njegovo UV absorbcijo (površino vrha pri RP-HPLC analizi), intenzivnost proteinske lise na gelu ali glede na relativno intenzivnost MS spektrov treh najbolj intenzivnih ionov. V nekaterih proteomskih študijah so metodo RP- HPLC uspešno zamenjali z gelsko filtracijo, kom- binacijo RP-HPLC/1DE pa z dvodimenzionalno gelsko elektroforezo (2DE) (Abd El-Aziz in sod. 2020). Slednja omogoča natančnejši vpogled v makromolekulsko organizacijo in v število pro- teoform posameznih toksinov v strupu. Opisani pristop ima tudi nekaj pomanjkljivosti. Zahteva večje količine strupa ter dolgotrajnejšo manipulacijo vzorcev, kar povečuje možnost nji- hove kontaminacije. Poleg tega razgradnja vzorca s tripsinom pogosto preprečuje jasno identifikacijo številnih različic posameznih toksinov, izooblik ali kompleksnih multimernih struktur. Isti peptid po- gosto identificiramo v več različnih proteoformah, kar vnaša dvom pri določanju identitete toksinov, posledično pa otežuje določanje skupnega števila in relativne vsebnosti proteoform, prisotnih v strupu. Tem omejitvam se lahko izognemo tako, da nativne strupne proteine analiziramo s tandemsko MS v okviru proteomskega pristopa »od zgoraj navzdol« (Melani in sod. 2016; Ghezellou in sod. 2019). Surove vzorce strupa injiciramo v MS instrument neposredno preko sistema za tekočinsko kromatografijo, kar bistveno zmanjša potrebno količino strupa in skrajša operativni čas. Ta proteomski pristop pa zahteva tehnološko bolj zahtevne pristope, ki vključujejo visokoresolu- cijske MS instrumente z ustrezno računalniško in programsko podporo, ti pa so na voljo le v specializiranih laboratorijih (Melby in sod. 2021). Poleg tega kačji strupi pogosto vsebujejo veliko proteinov z visoko molekulsko maso, katerih ana- liza je, kot je omenjeno zgoraj, še vedno zahtevna in manj uspešna. Ne glede na izbiro pristopa k analizi kačjega strupa je uspešnost identifikacije proteinov v največji meri odvisna od baze podatkov oziroma poznavanja proteoma, transkriptoma in geno- ma določene vrste kače. V proteinski knjižnici Nacionalnega centra za biotehnološke informacije (»National Center for Biotechnology Information«; NCBI) za taksonomsko skupino kače (Serpentes) najdemo že pol milijona vnosov, od tega za dru- žino Viperidae 118.685 in poddružino Viperinae 6.550 vnosov. Raznolikost in številčnost toksinov v proteomih kačjih strupov Tasoulis in Isbister sta v svojem članku iz leta 2017 zbrala podatke o vseh 132 do takrat objavlje- nih proteomskih raziskavah kačjih strupov. V samo 11Leonardi: Venomika in antivenomika kačjih strupov štirih naslednjih letih je bilo analiziranih še dodatnih 79 novih proteomov (Tasoulis in sod. 2021). Ta trend se nadaljuje in v bazi Pubmed (https://pub- med.ncbi.nlm.nih.gov/) v zadnjem letu najdemo že 32 novih objav proteomov kačjih strupov. To je nedvomno spodbudila Svetovna zdravstvena organizacija (World Health Organization, WHO), ko je l. 2017 zastrupitvam s kačjimi strupi ponovno podelila status zanemarjene tropske bolezni, ki na vseh celinah povzroča ogromno trpljenja zaradi invalidnosti in prezgodnjih smrti (Chippaux 2017). Skupno so v proteomskih raziskavah odkrili toksine iz 63 encimskih in neencimskih družin proteinov in peptidov (Tasoulis in Isbister, 2017; Tasoulis in sod. 2021). Med njimi so tudi družine z majhnim številom proteinov, katerih funkcija ali biološki pomen ni znan. Encimske komponente so večinoma hidrolaze in L-aminokislinske oksidaze (LAO), ki sodelujejo pri usmrtitvi plena in pomagajo pri njegovi prebavi (Mebs, 2002). Med neencimskimi komponentami najdemo toksine, ki prizadenejo živčni sistem in celične membrane ter peptide z različnimi znanimi (npr. encimski inhibitorji) ali še neznanimi funkcijami. Glede na dosedanje proteomske raziskave so posamezni kačji strupi sestavljeni iz toksinov, ki jih lahko uvrstimo v le tri pa do celo 20 različnih proteinskih družin. V povprečju večino kačjih strupov sestavljajo toksini iz štirih proteinskih družin: triprstni proteini, se- kretorne fosfolipaze A2 (sPLA2), serinske proteaze iz kačjih strupov (SPKS) in metaloproteinaze iz kačjih strupov (MPKS). Prvi dve družini prevla- dujeta pri strupenih gožih, zadnje tri pa pri gadih, v katerih so triprstni proteini zelo redko prisotni. Večina preostalih proteinov v kačjih strupih sodi med s cisteinom bogate sekretorne proteine (CRISP), peptide Kunitzovega tipa (KUN), LAO, natriuretične peptide, lektine tipa C (CTL) in disintegrine (DIS). Skoraj dve tretjini vseh proteomskih raziskav se nanaša na strupe gadov. Njihovi strupi imajo bolj kompleksno sestavo od strupov strupenih gožev glede na število proteinskih družin, ki jih sestavljajo. Čeprav so strupi strupenih gožev se- stavljeni iz manjšega števila proteinskih družin, pa je raznolikost toksinov znotraj njih zelo velika. Primer takega strupa je strup trakaste egiptovske kobre (Naja annulifera), ki ga povečini sestavljajo toksini iz ene same proteinske družine, to je triprstni proteini (78 %), vendar je znotraj te družine pri- sotnih 18 različnih izooblik (Tan in sod. 2020). V strupu vzhodne zelene mambe (Dendroaspis polylepis) so zabeležili celo 80 različnih triprstnih proteinov (Ainsworth in sod. 2018). Proteomska slika strupov kač iz poddružine Viperinae Celovito zbirko podatkov o proteomih strupov poddružine Viperinae, analitičnih metodah in po- stopkih najdemo v nedavno objavljenem članku Damm in sod. (2021), ki obravnava 54 objavljenih proteomskih študij, v katerih je bilo analiziranih 89 strupov iz 37 različnih vrst kač, ki pripadajo 11 rodovom. Primerjave njihovih proteomov so pokazale izjemne razlike na znotrajvrstni in medvrstni ravni med rodovi s poudarkom na re- gionalnih razlikah. Največ raziskav je posvečenih medicinsko najbolj pomembnim vrstam iz rodov Bitis, Echis, in Daboia, ki povzročijo največ smrti v ruralnih predelih Afrike, Indije in Srednjega Vzhoda (Gutiérrez in sod. 2010; Amr in sod. 2020; Pintor in sod. 2021). Veliko raziskav se po drugi strani posveča tudi medicinsko pomembnim evropskim strupenjačam iz rodu Vipera (Di Nicola in sod. 2021). V večini raziskav je bila uporabljena proteomika »od spodaj navzgor«, proteini v strupih pa so bili predhodno ločeni z eno izmed tekočin- skih (gelska filtracija, ionsko-izmenjevalna, RP- HPLC) in/ali gelskih kromatografij (1DE, 2DE). Le v šestih raziskavah so uporabili proteomiko »od zgoraj navzdol«, od tega v štirih primerih za analizo strupov kač iz rodu Vipera (V. ammodytes, V. anatolica, V. kaznakovi in V. transcaucasiana) (Göçmen in sod. 2015; Hempel in sod. 2018; Petras in sod. 2019; Gopcevic in sod. 2021). V strupih kač poddružine Viperinae pre- vladujejo štiri glavne družine toksinov, MPKS, sPLA2, SPKS in CTL, ki predstavljajo 60 do 90 % celotnega strupa; pet sekundarnih družin toksinov (DIS, LAO, CRISP, KUN in žilni endotelijski rastni dejavniki F ) predstavlja 6 do 15 % strupa; šest manj pomembnih družin toksinov, živčni rastni dejavnik, 5’ nukleotidaze, fosfodiesteraze, hialuronidaze, fosfolipaze B in cistatin iz rodu Bitis, so določili v manj kot polovici proteomov s skupnim povprečnim deležem 13 %; več redkih 12Acta Biologica Slovenica, 2022, 65 (2), 5–25 družin toksinov pa je prisotnih v povprečnem 1 % deležu: glutaminil ciklotransferaza, aspartana proteaza, različne proteaze in triprstni proteini. Izmed peptidov prevladujejo inhibitorji MPKS, natriuretični peptidi in peptidi, ki potencirajo bradikinin. Rod Vipera šteje 21 različnih vrst in številne podvrste. Taksonomska raznolikost se odraža tudi v sestavi njihovega strupa. Med vsemi kačami iz družine Viperidae imajo tiste iz rodu Vipera v svojem strupu največ CRISP (5–30 %) in najmanj DIS (le nekaj 1 %). Izjema je strup stepskega gada (V. renardi) iz Rusije, pri katerem toksini iz družine DIS predstavljajo četrtino strupa (Kovalchuk in sod. 2016). V strupih V. ursini (Hrvaška), V. b. berus (Slovaška), V. nikolskii (Rusija) ter V. a. montadoni in V. transcaucasiana (Turčija) pa DIS niso odkrili (Bocian in sod. 2016; Kovalchuk in sod. 2016; Hempel in sod. 2018; Lang Balija in sod. 2020). Medtem ko imajo nekateri strupi kač iz rodu Vipera visoko vsebnost MPKS (npr. 40–50 % pri V. ursini in V. anatolica), so drugi bogati s sPLA2 (npr. 45–52 % pri V. a. montandoni in V. transcaucasiana) ali SPKS (npr. 20–30 % pri V. b. berus, V. nikolskii in V. orlovi iz Rusije) (Göçmen in sod. 2015; Kovalchuk in sod. 2016; Latinović in sod. 2016; Hempel in sod. 2020). Zanimivo je opažanje, da sta količini MPKS in sPLA2 v strupih obratno sorazmerni. V nadaljevanju bom bolj podrobno opisala venomiko treh kač, modrasa (Sl. 2), gada in travniškega gada, ki je bila tema naših raziskav (Latinović in sod. 2016; Leonardi in sod. 2019; Lang Balija in sod. 2020) V vseh primerih smo uporabili proteomiko »od spodaj navzgor«. Naše rezultate bom primerjala z rezultati drugih raziskovalcev. Slika 2: Modras (Vipera a. ammodytes). Njegov prepoznavni znak je rožiček na nosu, od koder izvira tudi njegovo angleško ime nose-horned viper ali long-nosed viper. Na hrbtu svetlo rjave, rdečkasto rjave ali sive barve ima cikcak vzorec temnejše barve (foto: Neven Vrbanić). Figure 2: The nose-horned viper (Vipera ammodytes ammodytes). Its distinct feature is a single “horn” on the snout, hence its English name nose-horned or long-nosed viper. It has a dark zigzag pattern on its pale brown, reddish brown, or grey back (photo: Neven Vrbanić). 13Leonardi: Venomika in antivenomika kačjih strupov Venomika modrasovega strupa Proteom in peptidom modrasovega strupa hrva- škega izvora smo analizirali s kombinacijo metod 2DE/LC-MS/MS in gelska filtracija/RP-HPLC/ LC-MS/MS. Ključnega pomena za identifikacijo proteinov je bila transkriptomska analiza strupne žleze modrasa, s pomočjo katere smo zgradili cDNA knjižnico strupne žleze, ki je vsebovala prepise za prekurzorje 45 različnih proteinov in peptidov. Proteine iz surovega strupa z molekul- sko maso večjo od 10 kDa smo ločili z 2DE in jih nato identificirali z MS. Za boljšo ločbo proteinov smo optimizirali vsak korak v 2DE metodi. V prvi dimenziji smo proteine ločili na poliakrilamidnih trakovih z imobiliziranim pH gradientom (IPG) v območju pH 3–11. Uspešnost analize je odvisna predvsem od priprave vzorca, to je njegove topnosti v pogojih izoelektričnega fokusiranja. Zato smo sestavo pufra za popolno raztapljanje vzorca in rehidracijo IPG trakov optimizirali z modificirano Taguchijevo metodo, ki omogoča enostavno in hitro optimizacijo večkomponentnih sistemov (Ahmad in Sharma, 2009). Pufer je vseboval standardne komponente, denaturante ureo in tioureo, ki smo jim za boljšo topnost proteinov dodali detergenta (CHAPS in ASB-14) in amfolite v optimalnih koncentracijah (Sl. 3). Proteine v IPG trakovih, fokusirane pri pH svojih izoelektričnih točk, smo reducirali in alkilirali pred analizo v drugi dimenziji. Slednja je potekala v 10 % (m/v) poliakrilamidnem gelu v puferskem sistemu Tris/tavrin (Sl. 3) (Tastet in sod. 2003). Ta puferski sistem ima v proteomiki prednost pred klasičnim NaDS-PAGE puferskim sistemom Tris/glicin, ker za ločbo proteinov v ši- rokem masnem območju (5-250 kDa) potrebujemo manj zamrežene gele (le 9-11,5 % (m/v) namesto klasičnih 7,5-15 % (m/v)). Razgradnja proteinov, predvsem tistih z višjo maso, in ekstrakcija peptidov za MS analizo je bolj uspešna v manj zamreženih gelih. Pod temi pogoji smo strup modrasa z 2DE ločili na 208 proteinskih lis, ki smo jih vizualizirali z občutljivim reverznim barvanjem v prisotnosti imidazola in Zn2+ (Castellanos-Serra in sod. 2001). Gel se obarva motno belo, medtem ko kompleksi protein-NaDS-imidazol ostanejo prozorni. Prednost te metode pred barvanjem s koloidnim srebrom ali barvilom Coomassie modro je, da je zelo hitra in ne zahteva fiksacije proteinov v gelu, pri čemer lahko nastanejo netopni agregati. Proteinske lise smo izrezali iz gela, jih razgradili s tripsinom in analizirali s tandemsko MS. Slika 3: Optimizirana 1DE (A) in 2DE (B) analiza modrasovega strupa. Strup smo analizirali z 1DE v 10 % (m/v) gelu v puferskem sistemu Tris/tavrin. Pri 2DE smo prvo dimenzijo (izoelektrično fokusiranje) izvedli na 7 cm IPG trakovih v optimiziranem rehidracijskem pufru, ki je vseboval detergenta 2,5 % (m/v) CHAPS in 0,25 % (m/v) ASB-14 ter 1 % (v/v) amfolitov. Pogoji v drugi dimeziji so bili enaki kot pri 1DE. Gele smo pobarvali s koloidnim srebrom. Figure 3: Optimized 1DE (A) and 2DE (B) analysis of V. a. ammodytes venom. (A) - the venom was analysed in a 10% (w/v) gel in a Tris/Taurine buffer system. For 2DE, the first dimension (isoelectric focusing) was performed on 7 cm IPG strips in an optimised rehydration buffer containing detrgents 2.5% (w/v) CHAPS and 0.25% (w/v) ASB-14, and 1% (v/v) ampholytes. The conditions in the second dimension were the same as for 1DE. The gels were stained with colloidal silver. 14Acta Biologica Slovenica, 2022, 65 (2), 5–25 Za identifikacijo proteinov smo masne spektre primerjali s podatkovno bazo neredundantnih proteinskih zaporedij NCBI, ki smo jo dopolnili z zaporedji prepisov iz naše cDNA knjižnice. V 176 proteinskih lisah smo identificirali 57 protei- nov iz 16 različnih proteinskih/toksinskih družin, med katerimi so najštevilčnejši SPKS, MPKS, CTL in sPLA2 (Tab. 1). Pomemben dosežek naše proteomske študije je bilo odkritje novega P-IIIe podrazreda MPKS, ki je nastal tekom evolucije s podvajanjem predniškega gena in izgubo celotne proteinazne domene (Požek in sod. 2022). MPKS predstavljajo izjemen primer evolucije večgenskih proteinskih družin, katerih zgodovino so zaznamo- vale številne epizode izgube domen (katalitičnih in nekatalitičnih), posttranslacijske modifikacije in pospešena evolucija s pozitivno selekcijo, kar je povzročilo pogoste spremembe strukturnega ogrodja (Casewell in sod. 2011). Polipeptide in peptide iz modrasovega strupa z molekulsko maso pod 10 kDa smo najprej ločili z gelsko filtracijo celotnega strupa, ki ji je sledila RP-HPLC analiza nizkomolekulskih frakcij. V njih smo z MS in Edmanovim sekvenciranjem določili proteine DIS, KUN in žilni endotelijski rastni dejavnik F, izmed peptidov pa natriuretič- ne peptide, peptide, ki potencirajo bradikinin in inhibitorje MPKS. V podobni proteomski študiji so strup bol- garskega modrasa ločili z 2DE na le 139 prote- inskih lis (Georgieva in sod. 2008). Proteine so uspešno identificirali le v eni tretjini lis, skupno 38 proteinov iz 9 proteinskih družin, kar je lahko posledica manjše sekvenčne identitete proteinov modrasovega strupa s proteini v takrat dostopnih podatkovnih bankah. Primerjava dveh omenjenih proteomskih študij poudarja pomen optimizacije protokola za predhodno ločevanje proteinov iz strupa in uporabo vrstno specifičnega referenčnega transkriptoma za njihovo MS identifikacijo. V nedavno objavljeni kvalitativni analizi strupa modrasa iz Srbije so uporabili proteomski pristop »od spodaj navzgor«, ki temelji na MS/ MS analizi tripsinskega hidrolizata celotnega strupa (Gopcevic in sod. 2021). Identificirali so 99 proteinov iz 9 proteinskih družin in s tem dobro pokrili visokomolekulski del proteoma. Ta pristop omogoča zelo hitro analizo celotnih kompleksnih nefrakcioniranih proteomov, vendar zahteva visokoločljive nanoLC-MS/MS sisteme. Zato je bil do sedaj uporabljen le v osmih proteomskih študijah strupov iz poddružine Viperinae, od tega pet iz rodu Vipera (Damm in sod. 2021). Omejitev uporabljenega pristopa je slabša identifikacija nizkomolekulskih proteinov in peptidov. Po podatkih WHO (2017) je modras uvrščen na seznam vrst strupenih kač največjega medicin- skega pomena v Evropi. Modrasov strup na majhne živali (mali glodavci, ptiči, kuščarji), ki so njegov naravni plen, deluje predvsem nevrotoksično zaradi delovanja nevrotoksičnih sPLA2, amoditoksinov (Križaj, 2011). Ob zastrupitvi človeka pa so najbolj izraženi lokalna in sistemska hemoragija, lokalna poškodba tkiva in motnje strjevanja krvi, v manjši meri nevrotoksičnost, poročila o smrtnih izidih pa so zelo redka (Luksić in sod. 2006; Karabuva in sod. 2016a). Skladno s to zelo zapleteno klinično sliko je proteomska analiza strupa modrasa potrdila njegovo izredno kompleksno sestavo. Posamezne komponente smo povezali s patofiziološkim delo- vanjem strupa tako, da smo z različnimi metodami tekočinske kromatografije postopoma načrtno ločevali sestavine strupa in testirali njihov vpliv na srčno-žilni sistem (Sajevic in sod. 2014; Karabuva in sod. 2016b; Karabuva in sod. 2017). Na ta način smo pokazali, da so toksini iz štirih najštevilčnejših in najbolj raznolikih družin, SPKS, sPLA2, CTL in MPKS, ki predstavljajo 80 % vseh proteinov strupa, odgovorni za glavne toksične učinke strupa, vključno s krvavitvami, koagulopatijo, zaviranjem agregacije trombocitov, kardiološkimi in nevro- loškimi motnjami. Protein iz novega podrazreda MPKS, sestavljen le iz nekatalitskih domen, zavira agregacijo trombocitov. 15Leonardi: Venomika in antivenomika kačjih strupov Tabela 1: Sestava in relativni deleži identificiranih družin proteinov/toksinov v strupu modrasa, navadnega gada in malega gada. Table 1: Composition and relative abundances of the identified protein/toxin families in the venom of Vipera a. ammodytes, Vipera b. berus in Vipera ursinii ssp. Proteinska/toksinska družina Masni delež v strupu (%) modras (V. a. ammodytes) navadni gad (V. b. berus) mali gad (V. ursinii ssp.) Encimi serinske proteaze (SPKS) 25 31 6,3 fosfolipaze (PLA2) 21,5 10 11,5 metaloproteinaze (MPKS) 14,4 19 55,2 oksidaze L-aminokislin (LAO) 2,9 1,6 ni zaznan aspartatne proteaze < 1 < 1 ni zaznan glutaminil ciklotransferaza < 1 ni zaznan ni zaznan 5’ nukleotidaza < 1 ni zaznan ni zaznan Brez encimske aktivnosti lektini tipa C (CTL) 19,3 1,6 1,8 s cisteini bogati sekretorni proteini (CRISP) 7,7 8,2 12,2 disintegrini (DIS) 2 < 1 ni zaznan žilni endotelijski rastni faktor < 1 ni zaznan ni zaznan živčni rastni dejavnik < 1 ni zaznan < 1 Venomika gadovega strupa Navadni gad (V. b. berus, Sl. 4) je druga nevarna strupenjača, ki jo lahko srečamo v naravi v Sloveniji in je zaradi razširjenosti in zato večje pogostosti srečevanja z ljudmi medicinsko najbolj pomembna kača v Evropi. V naši venomski študiji smo anali- zirali strup ruskega izvora (moskovska regija) in ga primerjali s strupom modrasa iz prej opisane raziskave (Latinović in sod. 2016). Kvalitativni primerjalni analizi obeh strupov z RP-HPLC in 2DE sta razkrili manjšo kompleksnost gadovega strupa. Zaradi tega in manjše količine razpolo- žljivega strupa smo za strukturno in kvantitativno analizo gadovega strupa izbrali klasični proteomski pristop Calveteja in sod. (2007) RP-HPLC/1DE/ MS. Surovi strup smo najprej ločili v 14 frakcij z RP-HPLC, ki smo jih naprej analizirali z 1DE pod ne-reducirajočimi pogoji. Na gelu smo zaznali 30 diskretnih proteinskih lis z masami v razponu od 15 do 150 kDa. V njih smo s tandemsko MS določili 31 različnih proteinov, predstavnike 7 glavnih proteinskih družin iz strupov gadov, SPKS, MPKS, sPLA2, CRISP, LAO, CTL in DIS (Tab. 1). Prvič smo na proteinskem nivoju v nekem kačjem strupu identificirali tudi aspartatno proteazo. Komponente z nizko molekulsko maso v frakcijah RP-HPLC smo analizirali neposredno z uporabo razgradnje po Edmanu ali ESI-QTOF-MS/MS in identificirali inhibitorje MPKS, natriuretične peptide in KUN. Bistvene razlike v sestavi strupov navadnega gada in modrasa, ki lahko na molekularni ravni razložijo razlike v kliničnih slikah po zastrupitvah s temi strupi, so naslednje: i) delež SPKS in MPKS sta večja v strupu gada, deleži sPLA2, LAO, CTL in DIS pa manjši, ii) nevrotoksičnih sPLA2, amo- ditoksinov, v gadovem strupu ni, iii) prav tako ne proteinov CTL. Slednje smo v strupu gada identi- ficirali le kot kovalentno vezane podenote MPKS in ne pa tudi kot proste proteine v strupu (Tab. 1). Njihov delež v strupu modrasa pa je 10 % in lahko povzročijo življenjsko nevarno trombocitopenijo, 16Acta Biologica Slovenica, 2022, 65 (2), 5–25 t.j. znižanje števila trombocitov v krvi. V skladu z odsotnostjo amoditoksinov v gadovem strupu so poročila o nevrotoksičnih učinkih po zastrupitvi z njegovim strupom zelo redka. Nasprotno pa so se nevrotoksični znaki (npr. pareza ali paraliza kra- nialnih živcev) pojavili v približno 6 % pacientov zastrupljenih z modrasovim strupom. Ti zahtevajo nujno medicinsko pomoč, saj lahko napredujejo od ptoze (povešenost zgornjih vek) do močne mišične oslabelosti, ki lahko traja celo več ur (Luksić in sod. 2006). Najbolj učinkovita terapija po zastrupitvah s kačjimi strupi je imunoterapija s protistrupi. Naša raziskava imunološke navzkrižne reaktivnosti obeh strupov je pokazala, da protistrupi proti modrasovem strupu lahko nudijo popolno zaščito v primeru zdravljenja po strupenem ugrizu gada. Po drugi strani pa ne moremo pričakovati, da antiserum proti strupu gada nudi zadostno zaščito v primeru zastrupitve po ugrizu modrasa, še zlasti ne v primeru resne zastrupitve z močno izraženimi nevrološkimi učinki in trombocitopenijo. Tako kot modrasov je tudi strup navadnega gada bil predmet še dveh proteomskih raziskav, ki so lepo pokazale, kako je sestava strupov iz iste vrste kač odvisna od geografskega porekla. Al-Shekhadat in sod. (2019) so uporabili enak standardni venomski pristop kot smo ga uporabili mi za analizo prav tako strupa ruskega izvora, toda iz regij Tver in Novosibirsk. Tudi ta strup vsebuje kompleksen nabor toksinov, saj so določili 80 različnih proteinov in peptidov iz 13 družin. Za razliko od gadovega strupa iz moskovske regije je imel gadov strup iz Sibirije dvakrat več sPLA2, dvainpolkrat več LAO, a dvakrat manj SPKS in CRISP. Delež ostalih komponent, MPKS, DIS, CTL (le kot podenote MPKS), KUN in natriure- tičnih peptidov je bil primerljiv. Od peptidov so poleg natriuretičnih peptidov za razliko od nas določili tudi peptide, ki potencirajo bradikinin in sicer v 9,5 % deležu. Ker so za analizo uporabili večjo količino strupa, so lahko identificirali tudi komponente, ki so v strupih navadno prisotne v zelo majhnih količinah (pod 1 %), kot so hialuro- nidaza, 5’ nukleotidaza, glutaminil ciklotransfe- raza, fosfodiesteraza in živčni rastni dejavnik. Z izjemo hialuronidaze smo jih lahko določili tudi v strupu modrasa. Bocian in sod. (2016) so s proteomskim pristopom »od spodaj navzgor« in kombinacijo metod 2DE/MALDI TOF/TOF MS analizirali strup navadnega gada iz Slovaške. 2DE analiza v širokem območju pH 3–10 je pokazala, da se večina proteinskih lis nahaja v ožjem območju pH 5–8. Zato so za boljšo ločbo različnih izooblik proteinov strup analizirali tudi v tem ožjem območju, izrezali vse lise iz obeh gelov in proteine identificirali s tandemsko MS. Slovaški strup se je od ruskega razlikoval na kvalitativni in kvantitativni ravni. V njem so določili manjše število različnih proteinov, 25 iz 6 toksinskih družin, izmed peptidov pa le peptide, ki potencirajo bradikinin. Poleg tega, da niso našli proteinov iz družine DIS, je vsebnost proteinov iz družine CTL le 6 %. Presenetljivo pa so več kot polovico strupa sestavljale sPLA2, med njimi tudi nevrotoksične, sledili so jim SPKS, LAO in CRISP ter MPKS, ki jim je pa pripadel le nekaj odstotni delež. Do sedaj so poročali o primerih nevrotoksičnega učinka strupa navadnega gada po ugrizih v Romuniji in na Madžarskem, različni surovi strupi modrasa po poreklu iz Madžarske pa so povzročili paralizo izoliranih živčno-mišičnih preparatov iz piščanca (Malina in sod. 2017). Opaženi znaki paralize pri človeku in popolna ohromelost pri miših, ki so jim vbrizgali ma- džarski strup so tudi značilni za delovanje sPLA2 nevrotoksinov. Čeprav so te strupe analizirali le z 1DE, pa so iz intenzitet lis z maso 13-15 kDa, kar ustreza masi sPLA2, lahko sklepali, da so to dominantne komponente. Pričakujemo lahko torej, da je sestava strupov navadnega gada iz nekaterih regij Madžarske in Romunije bolj podobna sestavi slovaškega kot pa ruskega strupa. 17Leonardi: Venomika in antivenomika kačjih strupov Slika 4: Navadni gad (Vipera berus berus). Telo mu krasi neprekinjena temna cikcakasta proga vzdolž hrbta, ki se začne za ovalno glavo. Navadno je sivkaste ali rjavkaste barve, čeprav je lahko tudi popolnoma črn (foto: Neven Vrbanić). Figure 4: Common or European adder (Vipera berus berus). Its body is decorated with a continuous dark zigzag stripe along the back, starting behind the oval head. It is usually greyish or brownish in colour, although it could be also completely black (photo: Neven Vrbanić). Venomika strupa malega gada Mali gad (V. ursinii) je ogrožena vrsta evropske kače. Zaradi nevarnosti izumrtja je Svet Evrope leta 2005 sprejel načrt za njegovo zaščito. V Sloveniji te kače ni, na Hrvaškem pa najdemo njeno podvrsto V. ursinii ssp. (Sl. 5). Poseljuje visokogorske suhe travnate predele na jugu in jugovzhodu države. Je medicinsko manj pomembna kot druge kače iz vrste Vipera zaradi redkih srečanj s človekom in zelo majhne količine strupa, ki ga lahko injicira s svojimi le nekaj milimetrov dolgimi strupniki. V svojem naravnem okolju se večinoma prehranjuje z žuželkami. Strup hrvaškega malega gada je dosti manj kompleksen od prej opisanih strupov modrasa in gada (Lang Balija in sod. 2020). Surovi strup kač iz naravnega okolja, smo ločili z 1DE na le sedem in z 2DE na le 50 proteinskih lis. V izrezanih proteinskih lisah smo s tandemsko MS identi- ficirali 25 proteinov, uvrščenih v sedem družin, MPKS, SPKS, sPLA2, CRISP, CTL in KUN in živčni rastni dejavnik (Tab. 1). Dobro polovico strupa sestavljajo visokomolekulske MPKS, ki so večinoma homologi modrasovih hemoragičnih MPKS. Skladno s tem sta oba strupa, strup malega gada in strup modrasa, v testu v podganah pokazala primerljivo visoko hemoragično aktivnost. sPLA2 iz strupa malega gada so encimi brez nevrotoksične aktivnosti, zato je strup za podgano precej manj toksičen kot strup modrasa. Po drugi strani je bil strup modrasa bistveno manj toksičen za čričke kot strup malega gada. To je lepa demonstracija naravne prilagoditve, saj so črički naravna hrana malega gada, ne pa tudi modrasa. Za namene ohranjanja in raziskav nekatere primerke malega gada gojijo tudi v ujetništvu, kjer imajo drugačen režim prehranjevanja kot v naravi; 18Acta Biologica Slovenica, 2022, 65 (2), 5–25 hranijo jih namreč z mišmi namesto z žuželkami. Sprememba sestave strupa zaradi spremembe pre- hrane je bila že opisana pri drugih kačah (Barlow in sod. 2009; Gibbs in sod. 2013; Amazonas in sod. 2019). Da bi ugotovili, kako različna prehrana v primeru malega gada vpliva na sestavo strupa, smo strupe, zbrane od kač v ujetništvu, in strupe, pridobljene od divjih živali, primerjalno analizirali z metodo 2DE. Opažene spremembe v sestavi strupa kač v ujetništvu v primerjavi s tistimi, ki živijo v naravi, so predvsem večja količina sPLA2 ter manjša količina MPKS in CRISP. Ta ugotovitev podpira hipotezo, da pridobitev različnih izooblik sPLA2 v strupu s pospešeno evolucijo (Ogawa in sod. 1996) predstavlja močno selektivno prednost, npr. za hitro prilagajanje razpoložljivemu plenu s spremembo v izražanju genov (Aird in sod. 2015). Slika 5: Mali ali Ursinijev gad (Vipera ursinii ssp.). Ime je dobil po italijanskem naravoslovcu Antoniu Orsiniju (1788-1870). Ima majhno srčasto oblikovano glavo, telo je pa kratko in čokato. Je sive ali oker barve s črno obrobljeno temno rjavo cikcakasto progo na hrbtu (foto: Neven Vrbanić). Figure 5: Meadow or Ursini‘s viper (Vipera ursinii ssp.). It is named after the Italian naturalist Antonio Orsini (1788–1870). It has a small, heart-shaped head and a short, stocky body, which is grey or ochre in colour and has a black-edged, dark brown zigzag stripe on the back (photo: Neven Vrbanić). Antivenomika Po podatkih WHO (2019) strupene kače vsak dan ugriznejo skoraj 7400 ljudi na vseh kontinen- tih, od posledic ugriza pa jih umre 220 do 380. To pomeni približno 2,7 milijona primerov zastrupitev in 81.000 do 138.000 smrtnih primerov na leto. Problematika najbolj prizadeva države v razvoju z velikim številom ruralnega prebivalstva. Zato je WHO pripravila celovito strategijo za zmanjšanje umrljivosti in invalidnosti zaradi zastrupitev po kačjih ugrizih za 50 % do leta 2030. Pri tem je proizvodnja in dostopnost učinkovitih proti- strupov eden glavnih ukrepov za obvladovanje kačjih ugrizov. Protistrupi so zaenkrat edino res učinkovito specifično zdravilo proti sistemskim 19Leonardi: Venomika in antivenomika kačjih strupov učinkom zastrupitev s kačjimi strupi (Gutiérrez in sod. 2017). Sam izraz antivenomika opisuje proteomski proces identifikacije tistih polipeptidov v strupu, ki imajo epitope, ki jih protistrup slabo ali pa sploh ne prepozna (Calvete in sod. 2009). Vzrok za slabši zaščitni učinek protistrupa, pridoblje- nega z imunizacijo živali s celotnim strupom, je lahko tvorba protiteles z nizko afiniteto ali pa sploh izostanek tvorbe protiteles proti določenim toksičnim komponentam v strupu. Antivenomika dopolnjuje in vitro in in vivo teste nevtralizacije aktivnosti strupa ter tradicionalne imunološke me- tode, kot so analize ELISA in prenos po Westernu, za predklinično oceno nevtralizacijskega spektra protistrupov. Predstavlja alternativni pristop testiranju na živalih za določanje učinkovitosti zaščite protistrupov pred letalno nevarnostjo, ki jo povzroča strup. Prva generacija antivenomike, ki je temeljila na imunoprecipitaciji kompleksov antigen-protitelo v raztopini in ji je sledila kro- matografska kvantifikacija prostega antigena v supenatantu, je bila primerna le za protistrupe, ki so vsebovali celotne IgG (Núñez in sod. 2009; Lingam in sod. 2020). Ta pristop je bil pozneje preoblikovan tako, da je bil primeren tudi za proti- strupe, ki jih sestavljajo F(ab’)2 fragmenti. Ključna posodobitev v anivenomiki druge generacije je priprava imunoafinitetne kolone z vezavo molekul protistrupa na kromatografski nosilec (Villalta in sod. 2012; Lomonte in Calvete, 2017; Patra in sod. 2017; Pla in sod. 2017a). S kombinacijo imuno- afinitetne kromatografije in proteomske analize sestavin strupa v nevezanih in vezanih frakcijah takšen pristop zagotavlja kvalitativne in tudi kvan- titativne informacije o obeh skupinah proteinov strupa, tistih, ki jih protistrup dobro prepozna, in tistih, ki jih ne (imajo slabšo imunoreaktivnost). Ob predpostavki, da je stopnja imunoprecipitacije toksičnih sestavin v strupu s protistrupom in vitro enaka stopnji nevtralizacije toksičnih učinkov teh sestavin in vivo, rezultati antivenomike zagotavljajo podatke o tem, s katerimi sestavinami strupa je treba dodatno obogatiti imunizacijsko mešanico ali katerim sestavinam strupa je treba z določenimi postopki izboljšati imunogenost, da dobimo visoko učinkovit antiserum. Antivenomika tretje generacije nadgrajuje predhodni pristop z določitvijo največje kapacitete vezave različnih toksinov iz strupa s protistrupom in kvantifikacijo celotnega deleža protiteles v protistrupu, ki imajo imunoafiniteto do toksinov iz strupa – terapevtska protitelesa (Pla in sod. 2017b). Dejansko so pri skoraj vseh obstoječih protistrupih najpogostejše molekule protitelesa proti antigenom, ki niso strup (60-90 %) (Sanny, 2011). Ta pristop se uporablja tudi v molekularnih študijah navzkrižne reaktivnosti protistrupov in heterolognih strupov (Gutiérrez in sod. 2009). Protitelesa bodo verjetno navzkrižno nevtralizirala toksine znotraj iste družine toksinov v različnih kačjih strupih. Zaključki Venomika je orodje, ki nam omogoča boljše razumevanje kačjih strupov z evolucijskega, bi- ološkega in kliničnega vidika. Izjemen pospešek raziskavam živalskih strupov je omogočil razvoj proteomskih, transkriptomskih in genomskih platform, ki jih podpirajo visoko zmogljive teh- nologije sekvenciranja proteinov/peptidov, RNA in DNA. Tako se skokovito bogatijo baze amino- kislinskih zaporedij, ki jih z analizo s pomočjo vse zmogljivejših bioinformatskih orodij prevajamo v vse bogatejše baze znanja. Proteomika strupov temelji predvsem na masni spektrometriji, s katero določamo i) kvalitativno in kvantitativno sestavo proteoma na nivoju proteinskih družin, ii) delna ali celotna zaporedja izoliranih proteinov/peptidov, in iii) njihove točne mase, kar omogoča identifikacijo različnih proteoform. Informacije o sestavi strupa so bistvene za določitev obsega medvrstnih in znotrajvrstnih razlik ter vpliva ekologije in pre- hrane na evolucijo strupa. Podprta z genomiko in transkriptomiko nam torej proteomika zagotavlja veliko informacij o procesih, ki uravnavajo izra- žanje genov, o alternativnem spajanju in drugih molekularnih mehanizmih, odgovornih za izražanje fenotipskih razlik. Primerjalni podatki o sestavi strupa so koristni tudi za nadaljnje raziskave na področju molekularne biologije, kot so regulacija, izguba in podvajanje genov. Izjemen potencial v prihodnosti leži v povezavi proteomike z napre- dnimi slikovnimi tehnologijami, tako imenovana prostorska venomika – kartiranje proteinskih toksinov in njihove aktivnosti neposredno v tkivu 20Acta Biologica Slovenica, 2022, 65 (2), 5–25 strupne žleze – ki odstira pogled v morfološke in funkcionalne značilnosti strupnega sistema. Natančno poznavanje sestave strupov je izje- mno pomembno tudi za razumevanje patofiziologije zastrupitev in za razvoj ustreznih strategij zdravlje- nja zastrupitev s kačjimi strupi in pa za razvoj pro- tistrupov. Zastrupitve s kačjimi strupi predstavljajo velik zdravstveni in ekonomski problem še posebej v večjem delu sveta v razvoju. To problematiko je prepoznala tudi WHO, ki je protistrupe uvrstila med ključna zdravila. Specifičnost in učinkovitost teh zdravil – večinoma antiserumov – sta neločljivo povezani s sestavo strupov, ki se uporabljajo za imunizacijo, variabilnost toksinov pa povzroča slabše prepoznavanje in nevtralizacijo toksinov iz različnih strupov. S pomočjo antivenomike lahko s proteomskimi orodji kvalitativno in kvantitativno ovrednotimo interakcijo (nevtralizacijo) strupov s protistrupi in vitro. S tem bistveno zmanjšamo potrebo po testiranju protistrupov v laboratorijskih živalih. Antivenomika nam torej pomaga nadzo- rovati kakovost in načrtovati najboljše mešanice strupov za imunizacijo živali za proizvodnjo učinkovitih protistrupov. S ciljem povečanja njihove učinkovitosti bi bil namesto imunizacije živali s celotnim strupom bolj primeren pristop s proizvodnjo protistrupa le proti najbolj nevarnim toksinom v strupu. Prihodnost torej leži v pripravi rekombinantnih toksinov – antigenov za imuni- zacijo. Ti v eni molekuli vsebujejo več ključnih epitopov, sicer prisotnih na različnih toksinih ali proteoformah toksinov (celo iz različnih rodov in vrst kač). Tako proizvedena protitelesa naj bi imela široko nevtralizacijsko moč proti podobnim toksinom v različnih kačjih strupih. Summary Snake venoms are complex mixtures of biologi- cally active proteins and peptides that have evolved over the course of evolution to become one of the deadliest natural weapons. The pathological effect of the venom on the organism depends on its com- position, which is specific to each venomous snake family and even to a single snake. Indeed, snake venom may vary depending on the age, sex, diet or geographical distribution of a snake. Proteomics of snake venoms, snake venomics, is primarily based on mass spectrometry, which allows us to determine i) the qualitative and quantitative composition of the proteome at the protein family level, ii) the partial or complete sequences of venom proteins/ peptides, and iii) their exact masses, allowing the identification of the different proteoforms. The most commonly used approach to snake venom analysis is bottom-up proteomics. In this approach, the venom is first separated using liquid and/or gel- based chromatographic methods. The proteins are enzymatically degraded and the resulting peptides are analyzed using liquid chromatography-tandem mass spectrometry. Bioinformatics tools are then used to identify the proteins and find the best match between the experimental peptide tandem mass spectra and the theoretically generated spectra of proteins in sequence databases. The proteomes of snake venoms are increasingly being studied. Undoubtedly, snake venom research received an additional boost in 2017 when the World Health Organisation reclassified snakebite envenomation into the Category A of the Neglected Tropical Diseases, recognising that it is a major cause of suffering, disability and premature death in many developing countries. To date, venomics studies have identified numerous toxins classified into 63 enzymatic and non-enzymatic families of proteins and peptides. The medically important European vipers belong to the genus Vipera. Three of these snakes live in Slovenia, the nose-horned viper (Vipera a. ammodytes), the common adder (Vipera b. berus) and the asp viper (Vipera aspis, subspecies francisciredi). The nose-horned viper is the most venomous of the European venomous snakes, while the adder is the most widespread. We have studied their venoms using bottom-up proteomics and found characteristic differences in the composition and relative abundance of certain venom protein/toxin families. The most important difference, which is also reflected in the markedly different pharmacological effects of these two venoms, is the absence of the neurotoxic sPLA2s and CTLs in the venom of V. b. berus. These two groups of toxins are the reason for the neurotoxic- ity and thrombocytopenia (a decrease in platelet count) in a victim intoxicated by the venom of V. a. ammodytes. We also conducted a venom study on the most endangered snake species in Europe, the meadow viper (Vipera ursinii). This medically 21Leonardi: Venomika in antivenomika kačjih strupov insignificant viper species produces only a small amount of venom and feeds mainly on insects. It was no surprise that its venom is much less complex than that of the nose-horned viper and the adder. We found that it consists of many fewer toxin families, which are also less diverse. By comparing the venoms of V. ursinii snakes from the wild with those in captivity fed on mice instead of insects, we were able to confirm that diet strongly influ- ences the composition of the venom. Currently, antivenoms are the only effective treatment for the systemic effects of snakebite envenomation. In antivenomics, proteomics is used to identify the venom components that carry epitopes that are recognised by the antivenom weekly or not at all. The maximum binding capacity of different toxins by the antivenom and the proportion of antibodies in the antivenom that have immunoaffinity for the venom toxins to the total antibodies in the antivenom, e.g. the ratio of therapeutic antibodies in the antivenom, are determined by antivenom- ics. This is an effective alternative approach to animal testing to predict the protective efficacy of an antivenom in the case of snake envenomation. 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Optical properties of different structures of some herbaceous understorey plant species from temperate deciduous forests Optične lastnosti različnih struktur pri nekaterih zelnatih rastlinskih vrstah v podrasti zmernega listopadnega gozda Alenka Gaberščika*, Matej Holcara, Mateja Grašičb a Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, 1000 Ljubljana, Slovenia b Agricultural Institute of Slovenia, Hacquetova ulica 17, 1000 Ljubljana, Slovenia *Correspondence: alenka.gaberscik@bf.uni-lj.si Abstract: This contribution discusses the optical properties of different structures of some herbaceous understorey plant species from temperate deciduous and mixed forests. These forests are marked by annual dynamics of radiation level that is related to the vegetation cycle of forest trees. During winter and early spring, the understorey is exposed to full solar radiation, while later in the growing season radiation is limited due to the closing of the tree storey. The plasticity of optical properties of photosynthetic structures of understorey plants is directly related to their structural and biochemical phenotypic plasticity that optimises harvesting and use of energy. The optimisation of energy harvesting is also achieved by specific adaptations of green leaves, such as variegation (Pulmonaria officinalis, Cyclamen sp.), anthocyanic lower epidermis (Cyclamen sp.), and by using structures other than green leaves for photosynthesis, such as bracts (Hacquetia epipactis) and sepals (Helleborus sp.). The optical proper- ties of these structures are similar to those of green leaves. The understanding of optical responses of different structures contributes to the understanding of the forest understorey functioning. Keywords: bracts, leaves, light conditions, optical properties, sepals, temperate deciduous forest, understorey plants Izvleček: Prispevek povzema optične lastnosti različnih struktur nekaterih zelnatih rastlinskih vrst v podrasti listnatega in mešanega gozda zmernega pasu. Te gozdove za- znamuje letna dinamika ravni sevanja, ki je povezana z vegetacijskim ciklom gozdnega drevja. Pozimi in zgodaj spomladi je podrast izpostavljena polnemu sončnemu sevanju, kasneje pa je sevanje omejeno zaradi olistanja krošenj. Plastičnost optičnih lastnosti fotosinteznih struktur rastlin v podrasti je neposredno povezana z njihovo strukturno in biokemijsko plastičnostjo, ki optimizira privzem in rabo energije. Optimizacijo pri- dobivanja energije rastline dosežejo tudi s posebnimi prilagoditvami zelenih listov, kot sta pisanost (Pulmonaria officinalis, Cyclamen sp.) in antocianska spodnja povrhnjica (Cyclamen sp.) ter z uporabo drugih struktur poleg zelenih listov za fotosintezo, kot so podporni (Hacquetia epipactis) in čašni listi (Helleborus sp.). Optične lastnosti teh ACTA BIOLOGICA SLOVENICA LJUBLJANA 2022 Vol. 65, Št. 2: 26–41 27Gaberščik et al.: Optical properties of understorey plant species struktur so podobne optičnim lastnostim zelenih listov. Razumevanje optičnih odzivov različnih struktur prispeva k razumevanju delovanja rastlin v podrasti. Ključne besede: čašni listi, listi, optične lastnosti, podporni listi, podrast, svetlobne razmere, zmerni listopadni gozd Introduction Temperate deciduous and mixed forests are marked by annual dynamics of radiation regime that is related to the vegetation cycle of forest trees (Klančnik et al. 2015). The amount of radiation at the forest floor in a certain time of the year is a consequence of canopy structure, especially leaf area index (Larcher 2003). During winter and early spring, the understorey is exposed to full solar radiation, while later in the growing season radiation is limited due to the closing of the tree storey (Rothstein et al. 2001, Klančnik et al. 2015). In a fully foliated forest, light enters the system via gaps in the canopy forming sun flecks that provide up to 80% of solar energy for understorey species (Larcher 2003). However, these sun flecks are very variable regarding their quality, intensity, and duration (Chazdon et al. 1991, Lambers et al. 1998, Leakey 2004). The radiation conditions in the understorey layer during the vegetation period define the functional traits of photosynthetic organs, including their optical properties (Esteban et al. 2008, Grašič et al. 2020), which enable efficient light use (Reich et al. 2003, Yoshimura et al. 2010). Such traits are leaf tissue thickness and density, spotted and variegated leaves (Klančnik et al. 2016), and the production of additional pigments, such as antho- cyanins (Smillie et al. 1999). Optical properties depend on plant tissue structure and may thus be species-specific (Marín et al. 2016). However, they can vary significantly during tissue ontogenetic development (Grašič et al. 2021 a,b) and due to species phenotypic plasticity, which is related to environmental changes in the habitat (Liew et al. 2008, Klančnik et al. 2016, Klančnik et al. 2014 a). Herbaceous understorey species exhibit dif- ferent life histories that are related to variable radiation environments during specific phenologi- cal phases. The first group of plants develops all organs before the full foliation of trees. These organs are based on storage accumulated in un- derground organs (Larcher 2003) and possess a variety of traits that support quick development in the period with abundant light (Kim et al. 2015). The second group develops leaves prior to tree foliation and reproductive organs after the closure of the canopy (Gilliam 2014). The third group consists of, for example, the genus Vinca (Darcy et al. 2002) and some Helleborus species (Bavcon et al. 2012). These species have evergreen leaves that enable photosynthesis throughout the whole year, especially during high-light conditions in late winter and early spring. Some species within these groups increase their carbon and energy budget through additional photosynthetic organs, such as sepals and bracts (Grašič et al. 2020, Aschan et al. 2003), and in some species, the colour of sepals turns green after pollination, as shown for H. orientalis cv. Olympicus (Shahri et al. 2011). Photosynthetic organs optimise light harvest- ing by various adaptations of their biophysical structure (Ustin et al. 2001). Optical properties that comprise light reflectance, absorbance, and transmittance (Woolley 1971) vary among dif- ferent ecological groups of plants (Klančnik et al. 2012, Klančnik et al. 2014 b, Klančnik and Gaberščik 2016). In addition, they can be tissue- or species-specific, or they can vary due to tissue ontogenetic development and species phenotypic plasticity in relation to environmental changes in the habitat (Liew et al. 2008, Klančnik et al. 2012). Therefore, they also vary among different understorey species and their organs in time and space. The reflectance spectra of photosynthetic organs are a very useful parameter since they reflect specific organ traits, such as biochemical structure (Carter et al. 2002, Gitelson et al. 2002, Castro et al. 2008, Kováč et al. 2013, Roelofsen et al. 2014, Klančnik and Gaberščik 2016), and content of nutrients and hydration (Baltzer et al. 2005, Lukeš et al. 2013, Roelofsen et al. 2014). They also provide information about energy 28Acta Biologica Slovenica, 2022, 65 (2), 26–41 balance (Noda et al. 2013, Ullah et al. 2012), the potential presence of stress, and contribute to the understanding of photosynthetic performance (Coops et al. 2005). In some studies, it was shown that reflectance spectra act as a “plant signature”, enabling the identification of different plant groups (Klančnik and Gaberščik 2016), or even species classification (Castro-Esau et al. 2006). The present article presents the optical prop- erties of different structures of some understorey plant species in temperate deciduous forests. The insight into these optical properties and the traits supporting them contributes to the understanding of the forest ecosystem and enables the maintenance of some of these plants in man-made environments, which usually differ significantly from those of the floor of deciduous forests. Leaf traits and their optical properties Phenotypic plasticity Plant traits are a result of the evolutionary process, which favours a variety of adaptations that enable an optimal response to specific environ- mental conditions (Šraj Kržič et al. 2005, Rascio et al. 1999, Boeger et al. 2003). The persistence of these traits in plant species is related to the stability of conditions in the habitat. However, species phenotypic plasticity enables the ac- climation of specific traits to current conditions (Larcher 2003). Therefore, phenotypic plasticity presents the potential of an organism to produce various phenotypes when exposed to different environmental conditions (Sommer 2020). The highest level of phenotypic plasticity is found in environments with pronounced environmental changes. Environmental conditions in the forest understorey may be very heterogeneous in time and space, as is the case in temperate deciduous and mixed forests (Valladares 2003). This highly heterogeneous environment differs in multiple fac- tors. Besides variable light conditions, understorey plants are subjected to changes in temperature, soil moisture, and fertility. However, these factors usually co-vary in nonlinear ways (Valladares et al. 2007). The adaptation to light depends on a trade-off with plant responses to other factors (Larcher 2003). Different species in the forest understorey exhibit different levels of phenotypic plasticity, as shown for Asarum arifolium and Hepatica nobilis, the latter showing a higher level of plasticity (Warren et al. 2013). Plasticity may be expressed in different organs and at different levels of plant structure and function, and it also differs among different environments, as is the case in Hacquetia epipactis (Grašič et al. 2021 a). The plasticity of understorey plants in response to light is relatively low in shade-tolerant woody species in the tropics, where the environment is rather stable (Valladares et al. 2000). Warren et al. (2013) reported an ecological convergence in trait values along environmental gradients be- tween ecologically similar, but phylogenetically different evergreen understorey herbs. The plastic response of plant structural traits due to different environmental conditions results in undisturbed functioning, including the processing of avail- able energy. Thus, the plasticity of leaf optical properties is directly related to their structural and biochemical phenotypic plasticity (Klančnik et al. 2014 a, Grašič et al. 2021 a,b). Differences in species responses to variable light environments affect the success of understorey species in forest dynamics (Santos et al. 2021). In the case of fern Phyllitis scolopendrium, light along with other environmental factors significantly affected the frond biochemical structure, and consequently also their optical properties (Fig. 1). However, the photochemical efficiency of PS II remained the same (Grašič et al. 2020). Thus, photosynthetic acclimation to specific light conditions, which also includes pigment levels, is one of the most important plant abilities (Popović et al. 2006). Changes in biochemical leaf traits and their op- tical properties during the growing season were observed in Cyclamen purpurascens, where the contents of carotenoids and anthocyanins de- creased between February and April, and affected optical properties (Klančnik et al. 2016). This is also a consequence of lower levels of radiation that reached their habitat due to canopy closing (Rothstein et al. 2001). Besides anthocyanins, changes in carotenoid contents are also important since they can present accessory pigments under light limitation (Demmig-Adams et al. 1996). 29Gaberščik et al.: Optical properties of understorey plant species Figure 1: Mean reflectance of radiation in Phyllitis scolopendrium fronds in different spectral regions from locations with various light regimes at different times of the year. Locations along the light gradient: up - upper (high light level), mid – in the middle (middle light level), low - lower (low light level). Slika 1: Povprečna odbojnost sevanja pri listih vrste Phyllitis scolopendrium v različnih območjih sevanja z lokacij z različnimi svetlobnimi režimi v različnih delih sezone. Lokacije vzdolž svetlobnega gradienta: up - zgoraj (visoka raven svetlobe), mid - sredina (srednja raven svetlobe), low - spodaj (nizka raven svetlobe). The optical properties of understorey species are shaped by leaf structure and thickness, which are represented by specific leaf area (SLA). SLA of understorey species may vary from 0.66 to 0.01 cm2/mg (Prado et al. 2015), which results in different light capture efficiency (Reich et al. 2003). Lower SLA increases light backscattering, which positively affects light absorbance, reduces sieving effects, and prolongs the path of photons within the tissue (Lee et al. 2000). It determines photosynthetic efficiency per leaf mass, which increases with increasing SLA (Evans et al. 2001). Correlations between SLA and light reflectance spectra were observed by Asner et al. (2008), who studied the optical properties of tropical forest canopy species. Leaf colouration Plant biochemical and morphological structure is determined by organ-specific interactions with the environment (Bongers et al. 2019), which also includes light conditions. Many studies have revealed an important role of pigments in shaping leaf optical properties (Slaton et al. 2001, Gitelson et al. 2002, Baltzer et al. 2005, Levizou et al. 2005, Castro et al. 2008, Klančnik, et al. 2014 a, Klančnik et al. 2016). The contents of chlorophylls, which are the main light-harvesting pigments, usually negatively affect the reflectance spectra (Klančnik et al. 2014 a). This effect may be altered in plants with different structures at the leaf surface, e.g., in many understorey species. For example, the pres- ence of trichomes as the first target of light may significantly affect leaf optical properties (Baldini et al. 1997, Klančnik et al. 2012). 30Acta Biologica Slovenica, 2022, 65 (2), 26–41 Anthocyanins play an important role in the adaptive strategy of plants to their radiation environment, including in forest understorey species. Anthocyanins mitigate or prevent plant stress, as they function as sunscreens, antioxidants, and chelating substances (Landi et al. 2015). Anthocyanins in leaves of understorey plants filter high-intensity radiation during sun flecks (Gould et al. 1995, Gould 2004). In vivo anthocyanins exhibit an absorption peak around 550 nm, and this peak magnitude is related to anthocyanin content (Gitelson et al. 2022). In general, anthocyanins ac- cumulate in upper leaf layers (Chalker-Scott 1999, Lev-Yadun 2002, la Rocca et al. 2014). However, some understorey plant species accumulate them in their abaxial epidermis as well (Hughes et al. 2008, Lee et al. 1979, Lee et al. 2001), as is the case in the genus Cyclamen (Klančnik et al. 2016) (Fig. 2). Figure 2: The red abaxial epidermis in Cyclamen purpurascens may vary in colour intensity and homogeneity. Slika 2: Rdeča spodnja povrhnjica vrste Cyclamen purpurascens se lahko razlikuje po intenzivnosti in homoge- nosti barve. Some researchers suggest that the reduction of light transmission through the leaf due to an- thocyanins might negatively affect competitors, especially in spring before the development of the canopy. A study of leaves of tropical trees at the beginning of the last century showed that red abaxial epidermis contributes to enhanced leaf temperatures, however, this was not confirmed in later studies (Gould et al. 1995, Lee et al. 1979). Klančnik et al. (2016) showed significant dif- ferences in transmittance in the visible and NIR regions between the leaves with and without the red abaxial epidermis. The visible region is used for photosynthesis but also has a thermal effect, while the effect of NIR is mainly thermal (Ross 1981). In addition, lower transmittance in the green and yellow regions was measured for the red-coloured lower epidermis in comparison to the epidermis with fewer anthocyanins. The study of Begonia heracleifolia revealed that the red anthocyanic lower epidermis did not affect the reflectance of red light in the mesophyll (Hughes et al. 2008). The study of Colocasia esculenta leaves with dif- ferent anthocyanin contents showed no differences in CO2 uptake under shade conditions between the studied leaf types (Hughes et al. 2014). Erytronium dens-canis red patches are due to a single layer of cells in the upper parenchyma that accumulate anthocyanins and have lower photochemical efficiency in comparison to the green sections (Esteban et al. 2008). 31Gaberščik et al.: Optical properties of understorey plant species Variegated leaves Plant leaves are usually uniformly coloured. However, some understorey plants develop leaves in such a way that they have different colour pat- terns at their surface, optimising the use of both high and low light levels in the forest understorey (Tsukaya et al. 2004). These coloured patterns are very popular, therefore, such species can be used as ornamental plants (e.g., Aglaonema, Begonia, Cyclamen). Pulmonaria officinalis, a perennial forest herb that grows in biodiverse, mixed, and open forests, has variable light green spots at the green leaf surface (Fig. 3). Variegation patterns are mainly not related to pigments, but rather to the differences in the palisade mesophyll (Konoplyova et al. 2008). Light green spots in P. officinalis are caused by the presence of loosely arranged cells instead of a well-established layer of packed cells in the palisade parenchyma (Esteban et al. 2008). SLA in light green parts was higher in comparison to dark green parts (3.16 and 2.75 dm2/g DM, respectively). Consequently, dark green parts had somewhat higher contents of all pigments, however, the differences were not significant. All these aspects affected plant optical properties, as shown in Figure 4. Light green parts reflected and transmitted more light in the green, yellow, and red regions, while shorter wavelengths and NIR showed a similar pattern in both light green and dark parts of the leaf. In addition, chlorophyll fluorescence imaging revealed a decrease in photochemical efficiency for light green spots in comparison to the green sections (Esteban et al. 2008). Under higher levels of UV radiation that are found in more open habitats, the light green spots become less transparent to visible light (Gaberščik et al. 2001). Figure 3: Pulmonaria officinalis leaves with light green spots. Slika 3: Listi vrste Pulmonaria officinalis s svetlozelenimi pikami. 32Acta Biologica Slovenica, 2022, 65 (2), 26–41 Figure 4: Mean radiation reflectance (area below the lower curves), light transmittance (area above the upper curves), and absorbance (area between the upper and lower curves) measured on the dark (dark green curves) and light green (light green curves) parts of the Pulmonaria officinalis leaves. Slika 4: Povprečna odbojnost sevanja (površina pod spodnjimi krivuljami), prepustnost sevanja (površina nad zgornjimi krivuljami) in absorbanca (površina med zgornjo in spodnjo krivuljo), izmerjene na temnih (temnozelene krivulje) in svetlozelenih (svetlozelene krivulje) delih listov vrste Pulmonaria officinalis. In Cyclamen purpurascens leaves, more evi- dent differences in light reflectance of dark and light green parts were obtained in comparison to P. officinalis (Figs. 5 and 6). These differences were negligible in the UV region, but very pronounced in VIS, and then again less pronounced in NIR. The light green leaf parts also transmitted more radiation than the dark green leaf parts, wherein the most differences in transmission were seen for the green region (Klančnik et al. 2016). In spite of the differences in light management, the light green parts of the variegated leaves perform photosyn- thetic activities similar to those of the dark green leaf parts or of fully green leaves (Konoplyova et al. 2008, la Rocca et al. 2011, Sheue et al. 2012, la Rocca et al. 2014). 33Gaberščik et al.: Optical properties of understorey plant species Figure 5: The light green pattern at the upper leaf surface of Cyclamen purpurascens may vary in intensity and shape. Slika 5: Svetlozelen vzorec na zgornji površini listov vrste Cyclamen purpurascens se lahko razlikuje po jakosti in obliki. Figure 6: Reflectance of radiation measured on the dark green (dark green curve) and light green (light green curve) parts of the Cyclamen purpurascens leaves. Slika 6: Odbojnost sevanja, izmerjena na temnozelenih (temnozelena krivulja) in svetlozelenih (svetlozelena krivulja) delih listov vrste Cyclamen purpurascens. 34Acta Biologica Slovenica, 2022, 65 (2), 26–41 The higher reflectance in the light green leaf parts is mainly a consequence of the morphological differences. The mesophyll below the light green leaf parts shows a polygonal light reflection pat- tern, composed of white polygons formed around the epidermal cell edges (Zhang et al. 2009, Sheue et al. 2012, Klančnik et al. 2016). This pattern is associated with air spaces between the epidermal and mesophyll cells (Zhang et al. 2009), and thus the light green colouration is also a consequence of leaf mesophyll structure (Sheue et al. 2012). The palisade mesophyll cells of these leaf parts are larger and loosely arranged, therefore hav- ing a greater volume of intercellular air spaces (Konoplyova et al. 2008, Sheue et al. 2012, la Rocca et al. 2011), which increase light reflection and the scattering of light (Esteban et al. 2008). In C. purpurascens the differences in tissue den- sity between the light and dark green leaf parts were most pronounced in April under high light conditions, when tissue density was significantly higher in the dark green leaf sections (Klančnik et al. 2016). This additionally supports the im- portance of variegation for light management. This increased light reflectance of the light green leaf parts may serve as photoprotection and may prevent damage caused by high light during sun flecks (Holmes et al. 2002, Esteban et al. 2008). However, the dark green leaf parts are protected against excessive radiation by carotenoids (Filella et al. 1999, Schulze et al. 2005), as their carotenoid contents were higher when the canopies were not yet closed (Klančnik et al. 2016). In the case of Actinidia kolomikta leaf colour was also related to leaf structure and leaf pigment contents (Wang et al. 2015), and the reflectance of white leaves was significantly higher than that of green leaves (Wang et al. 2020). Structures other than leaves Some species in the understorey of mixed and deciduous forests may use structures other than leaves, such as bracts and sepals, for harvesting energy in the early period with abundant light. Sepals may function as petals, as they at- tract pollinators, protect flowers, and regulate flower temperature, however, they can also serve as photosynthetic organs (Grašič et al. 2021 b, Herrera 2005). This is also the case in the genus Helleborus, which comprises 22 species of herba- ceous or evergreen perennials originating in Europe and Asia (Bavcon et al. 2012, Fassou et al. 2020, Grašič et al. 2021 b). In some species, the colour of flowers changes during flower development. In H. orientalis cv. Olympicus, creamy white sepals turned green at later developmental stages (Shahri et al. 2011) and sepals of pollinated flowers contained more chlorophyll in comparison to non- pollinated and senescent flowers (Schmitzer et al. 2013). In some Helleborus species with coloured sepals, the evolutionary selection in sepals was not directed to floral function, but rather to the development of sepals into photosynthetic organs (Salopek-Sondi 2002, Salopek-Sondi et al. 2000). This was confirmed by the presence of stomata in the sepals (Grašič et al. 2021 b), even though their density is relatively low in comparison to leaves (Aschan et al. 2005). In H. odorus with green-coloured sepals, photochemical efficiency is permanently high, whereas this is not the case in H. niger with initially white sepals (Grašič et al. 2021 b). However, the photochemical efficiency of H. niger sepals increases during flower develop- ment, as they turn green since their chlorophyll content increases (Grašič et al. 2021 b). Along with chlorophylls, sepal carotenoid, anthocyanin, and UV-B–absorbing substances contents were also gradually increasing (Grašič et al. 2021 b). A study of H. niger showed an increase in the contents of total anthocyanins, but not flavonols, which absorb in the UV region (Schmitzer et al. 2013). The reflectance and transmittance spectra of the green sepals in H. odorus and H. niger (Grašič et al. 2021 b) had similar shapes as those of green leaves (Klančnik et al. 2012). Sepal reflectance in VIS and NIR regions was in a negative rela- tionship with chlorophylls and anthocyanins in all phases of flower development. In the case of transmittance, negative relationship between the visible regions (with the exception of green) and anthocyanins and chlorophyll a and b was obtained in the developing phase, while UV-B–absorbing substances were more important in the flowering phase (Grašič et al. 2021 b). 35Gaberščik et al.: Optical properties of understorey plant species Figure 7: Mean reflectance of radiation in Helleborus odorus and H. niger sepals in the different spectral regions at different phases of flower development. Slika 7: Povprečna odbojnost sevanja čašnih listov vrst Helleborus odorus in H. niger v različnih spektralnih območjih v različnih fazah razvoja cvetov. In some genera, floral bracts serve as a protec- tive structure and replace the lacking perianth by enclosing floral organs (von Balthazar et al. 1999). Their photosynthetic ability presumably increases the importance of bracts early in the season. Bracts are also extremely important for the attraction of pollinators in some species (Gagliardi et al. 2018) since in 25% of angiosperm flowers, the reflection of ultraviolet light represents important visual information for pollinators (Klomberg et al. 2019). An example of such plant species is Hacquetia epipactis, which develops leaves, flowers, and fruits before the canopy layer closes (Gilliam 2014). It has a narrow ecological range and it is sensitive to changes in light conditions and water availability (Ellenberg 1996). H. epipactis has umbels that are supported by green bracts (von Balthazar et al. 1999). The shape of the spectral curves of bract reflectance reveals spectra typical of green leaves with peaks in the green and NIR regions, and with low reflectance in the shorter wavelengths (Klančnik et al. 2012). During umbel development, the traits of these bracts change along with changes of the basal leaves, wherein the most evident difference in the reflectance spectra was observed in the UV range (Fig. 8), which increased with age for bracts, while it decreased with age for basal leaves (Grašič et al. 2021 a). Some similarity was observed for bracts of immature and flowering umbels, which may be of relevance for pollinators (Arnold et al. 2010). 36Acta Biologica Slovenica, 2022, 65 (2), 26–41 Figure 8: Mean reflectance of radiation in Hacquetia epipactis basal leaves and bracts in the different spectral regions. Slika 8: Povprečna odbojnost sevanja bazalnih in podpornih listov Hacquetia epipactis v različnih območjih spektra. Summary Temperate deciduous and mixed forests are marked by annual dynamics of radiation level that is related to the vegetation cycle of forest trees. The amount of radiation on the forest floor at a certain time of the year is a consequence of the canopy structure. During winter and early spring, the understorey is exposed to full solar radiation, while later in the growing season radiation is limited due to the closing of the tree storey. In a fully foliated forest, light enters the system via gaps in the canopy forming sun flecks that are very variable regarding their quality, intensity, and duration. The radiation conditions in the understorey layer during the vegetation period define the functional traits of photosynthetic organs, including their optical properties, which support efficient light use. The present article presents the optical properties of different structures in some understorey plants species in temperate deciduous forests. The understanding of the functioning of these optical responses and the traits supporting them contributes to the understanding of the for- est ecosystem and enables the maintenance of some of these plants in man-made environments, which usually differ significantly from those of the floor of deciduous forests. Plant traits are a result of the evolutionary process, which favours a variety of adaptations that enable an optimal response to specific environmental conditions. The adaptation to light depends on a trade-off in plant responses to other factors. However, plant plasticity that enables the development of specific traits may also enhance light harvesting. Different species in the forest understorey exhibit different levels of phenotypic plasticity. Plasticity may be expressed in different organs and at different levels of plant structure and function, and it also differs among different environments. The plasticity of leaf optical properties is directly related to their structural and biochemical phenotypic plasticity. Plant biochemical and morphological structure, including photosynthetic pigments and antho- cyanins, plays an important role in the adaptive strategy of plants to the radiation environment in the forest understorey. Plant leaves are usually uniformly coloured. However, some understorey plants develop leaves in such a way that they have different colour patterns at their surface, optimis- ing the use of both high and low light levels in the forest understorey. The higher light reflectance in 37Gaberščik et al.: Optical properties of understorey plant species the light green leaf parts is mainly a consequence of the morphological differences and to a lesser extent of pigment contents. Some species may use structures other than leaves, such as bracts and sepals, for efficient energy harvesting. Povzetek Za zmerne listnate in mešane gozdove je zna- čilna letna dinamika ravni sevanja, ki je povezana z vegetacijskim ciklom gozdnega drevja. Količina sevanja v gozdnih tleh skozi čas je posledica strukture krošnje. Pozimi in zgodaj spomladi je podrast izpostavljena polnemu sončnemu sevanju, kasneje v rastni dobi pa je sevanje omejeno zaradi zaprtja drevesnih krošenj. Sevanje v podrasti med vegetacijskim obdobjem vpliva na funkcionalne poteze fotosinteznih organov, med drugim tudi na njihove optične lastnosti, ki podpirajo učinkovito rabo svetlobe. Pričujoči članek predstavlja optične lastnosti različnih struktur nekaterih vrst rastlin podrasti v zmernem listnatem gozdu. Poznavanje optičnih odzivov in funkcionalnih potez, ki jih podpirajo, prispeva k razumevanju gozdnega eko- sistema in omogoča ohranjanje določenih tovrstnih rastlin v umetnih okoljih, ki se običajno bistveno razlikujejo od razmer v gozdu. Funkcionalne poteze rastlin so rezultat procesa evolucije, ki daje prednost različnim prilagoditvam, ki omo- gočajo optimalen odziv na specifične okoljske razmere. Prilagajanje na svetlobo je kompromis med odzivom rastlin na vse dejavnike, medtem ko fenotipska plastičnost rastlin, ki omogoča razvoj specifičnih lastnosti, lahko izboljša tudi prestrezanje svetlobe. Različne vrste podrasti kažejo različno stopnjo fenotipske plastičnosti. Plastičnost se lahko izraža v različnih organih in na različnih ravneh zgradbe in delovanja rastline, razlikuje pa se tudi med različnimi okolji. Plastičnost optičnih lastnosti listov je neposredno povezana z njihovo strukturno in biokemijsko fenotipsko plastičnostjo. Biokemijska in morfološka zgradba rastlin, vključ- no s fotosinteznimi pigmenti in antocianini, ima pomembno vlogo v strategiji prilagajanja rastlin na sevalno okolje v gozdni podrasti. Listi rastlin so običajno enakomerno obarvani, vendar imajo nekatere rastline liste z različnimi barvnimi vzorci na površini, kar optimizira rabo tako visoke kot tudi nizke ravni svetlobe v podrasti. Večji odboj svetlobe v svetlozelenih delih listov je predvsem posledica morfoloških razlik in v manjši meri vsebnosti pigmentov. Nekatere vrste lahko za povečanje učinkovitosti prestrezanja svetlobe poleg listov uporabljajo tudi druge strukture, kot so podporni in čašni listi. Acknowledgements This work was supported by the Ministry of Education, Science and Sport, Republic of Slovenia, through the programme “Biology of plants” (P1-0212). References Arnold, S.E.J., Faruq, S., Savolainen, V., McOwan, P.W., Chittka, L., 2010. FReD: The floral reflectance database - A web portal for analyses of flower colour. PLoS ONE, 5, 12, e14287. Aschan, G., Pfanz, H., 2003. Non-foliar photosynthesis - a strategy of additional carbon acquisition. 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But it is also considered a source of potential pathogens, such as Pseudomonas aeruginosa, Acinetobacter baumanii and enterobacteria. To estimate the potential risk, we studied the composition and antimi- crobial resistance of bacteria in holy water from fonts and reservoirs of ten selected Catholic churches in Ljubljana, Slovenia. Bacterial contamination of holy water from fonts was moderate (102 - 105 CFU ml-1), but one to two orders of magnitude higher than in reservoirs, probably due to frequent immersion of fingers in the water. Some genera/species occurred only in fonts (Acinetobacter beijerinckii, A. haemolyticus, Brevundimonas aurantiaca, B. mediterranea, Delftia, Kocuria, Sphingobacterium, Staphylococcus warneri), while few fecal indicator bacteria were isolated. Isolated bacteria have relatively low pathogenic potential, some of them are skin commensals. Bacterial strains isolated in this study were susceptible to antibiotics. While according to our results, the potential of holy water for spreading bacterial infections is mod- est, to further limit the risks, water should be changed regularly, the fonts cleaned thoroughly, and the water should not be brought in contact with the eyes, ingested or aerosolized and inhaled. Keywords: antibiotic resistance, bacteria, fonts, holy water, NaCl, Roman Catholic churches, pathogens Izvleček: Blagoslovljena voda ima pomembno vlogo v različnih religijah. Uporablja se pri svetem krstu, za blagoslov ljudi, krajev in predmetov. V katoliških cerkvah se običajno nahaja v kropilnikih ob vhodu v cerkev. Lahko pa predstavlja tudi vir opor- tunističnih patogenov, kot so Pseudomonas aeruginosa, Acinetobacter baumanii in enterobakterije. Da bi bolje razumeli to tveganje, smo proučili sestavo in protimikrobno odpornost bakterij v blagoslovljeni vodi kropilnikov in rezervarjev desetih izbranih katoliških cerkva v Ljubljani (Slovenija). Bakterijska kontaminacija blagoslovljene vode iz krstilnikov je bila zmerna (102 - 105 CFU ml-1), a za red velikosti do dva višja kot v rezervarjih, verjetno zaradi pogostega pomakanja prstov vernikov v vodo kropilnika ob vstopu in izstopu iz cerkve. Nekateri bakterijski rodovi/vrste so se pojavili le v kropilnikih (Acinetobacter beijerinckii, A. haemolyticus, Brevundimonas aurantiaca, B. mediterranea, Delftia, Kocuria, Sphingobacterium, Staphylococcus warneri), izoliranih ACTA BIOLOGICA SLOVENICA LJUBLJANA 2022 Vol. 65, Št. 2: 42–103 43Turk et al.: Aerobic bacteria in holy water from Catholic churches pa je bilo le nekaj fekalnih indikatorskih bakterij. Izolirane bakterije imajo razmeroma nizek patogeni potencial, nekatere med njimi so kožni komenzali. Bakterijski sevi v tej študiji so bili občutljivi proti antibiotikom. Čeprav je potencial blagoslovljene vode za širjenje bakterijskih okužb glede na naše rezultate majhen, lahko tveganja dodatno zmanjšamo z redno menjavo vode, s temeljitim čiščenjem kropilnikov in s prepreče- vanjem vnosa vode v oči, njenega zaužitja ter aerosolizacije in vdihavanja. Ključne besede: bakterije, blagoslovljena voda, kropilniki, NaCl, odpornost proti antibiotikom, patogeni, rimskokatoliške cerkve Introduction Water is considered a sign of cleanliness and purification and has been used in many ancient and modern religious traditions (Oestigaard 2017). Holy water is water that has been blessed by a priest or comes from a well or spring considered sacred. In the Roman Catholic tradition, holy water is used as a sacrament for baptisms, to bless people, places, and objects, or to protect against evil and danger (Kirschner et al. 2012). It is commonly used to wash away sins (Flemming 2011). The Roman Catholic Church recommends adding an unregulated amount of blessed salt (sodium chloride) to the water during the blessing, which also results in varying salt concentrations of the holy water (Kirschner et al. 2012). Holy water is usually made only once a year at Easter, when tap water is blessed and then stored in metal reser- voirs (tanks) located in the church. Holy water is offered in the holy water fonts at the entrance of the church (or sometimes at a separate location, the baptistery). Smaller vessels, called stoups, are usually placed on the walls of church entrances for people to bless themselves with as they enter the church. They may be larger or smaller and made of stone, marble, glass, metal, or porcelain. When the faithful enter and leave the church, they dip the fingers of their right hand into the holy water and make the sign of the cross on their forehead, lips and chest. Holy water can also be used to bless food, objects, places, or people by sprinkling them (Jurado et al. 2002, Kirschner et al. 2012). However, it is well known that water is both a reservoir and source of pathogens that can lead to transmission of infectious diseases (Denham et al. 2013). Holy water has also been identified as a potential source of microbial and viral infections, including COVID-19 (Gajurel and Deresinski 2021). As early as the late 19th century, bacteriolo- gist L. Vincenzi found large numbers of microbes - staphylococci, streptococci, coli bacilli, Klebs- Loeffler bacillus (Corynebacterium diphtheriae), and other bacteria - in samples of holy water from a church in Sassari, Italy (Leffmann 1898). In a study from 1998, coliforms, staphylococci, yeasts, and molds were cultured from holy water from County Clare, Ireland (Payne, 2001). An examination of holy water fonts from churches in Seville, Spain, revealed heavy contamination with bacterial pathogens. The number of coliforms in the fonts exceeded 103 per 100 ml of water. The presence of potential pathogens was dem- onstrated by the identification of Acinetobacter, Aeromonas, Haemophilus, Neisseria, Salmonella, and Staphylococcus species. The most com- mon genera in holy water were Pseudomonas and Bacillus, followed by Staphylococcus, Sphingobacterium, and Delftia. However, spe- cies diversity varied greatly from one church to another. According to the authors, the presence of the genera Staphylococcus, Streptococcus, Acinetobacter, Pseudomonas, and several others in holy water was associated with hand contamina- tion and human skin transmission (Jurado et al. 2002). Contamination of holy water fonts has also been reported in Vienna, Austria. All holy water samples from churches and hospital chapels had extremely high concentrations of heterotrophic plate counts, up to 107 colony-forming units (CFU) ml-1; while fecal indicators such as enterococci and E. coli, as well as Pseudomonas aeruginosa and Staphylococcus aureus, were found only in the most frequently visited churches (Kirschner et al. 2012). A similar study was conducted in the Villingen-Schwenningen area, Germany. Colony 44Acta Biologica Slovenica, 2022, 65 (2), 42–103 counts revealed an average aerobic microbial load of 5.85±3.98 × 103 CFU ml-1. Urban churches had significantly higher bacterial contamination levels than rural churches, likely due to a higher number of visitors. The majority of the bacteria identified were typical human skin commensals, mainly belonging to the genus Staphylococcus. Fifty percent of the identified species were clas- sified as potential pathogens: Staphylococcus (S. aureus, S. epidermidis, S. homini, S. pettenkoferi, S. pasteuri), Bacillus cereus, Actinomyces oris, Acinetobacter johnsonii, and Enterobacter hor- maechei (König et al. 2017). Water that comes from Christian shrines and churches around the world is often used by hos- pital patients. Holy water is often administered by sprinkling, but can also be ingested, dripped into the eyes, or used to bathe affected body parts. There have been some reports of hospital patients experiencing serious complications after contact with holy water during hospital treatment. A case of hospital-acquired infection by Acinetobacter baumanii in a patient with burns after contact with holy water (sprinkling) has been described (Rees and Allen 1996). Based on the analysis of the holy water used (from Lourdes, Walsingham, and River Jordan), the majority of organisms isolated from the holy water samples were Gram-negative bacilli, including opportunistic pathogens such as Pseudomonas aeruginosa, Escherichia coli, Enterobacter spp., and Stenotrophomonas malt- ophilia (Rees and Allen 1996). A case has also been reported in which an adult male contracted Pseudomonas aeruginosa pneumonia while recov- ering from several injuries. His aunt was observed sprinkling holy water on the patient, and this water was confirmed as a source of the pathogen (Greaves and Porter 1992). Similarly, an 11-year-old boy with recurrent epilepsy requiring mechanical ventilation was found to have recurrent multidrug-resistant Acinetobacter baumannii pneumonia. The patient’s mother had regularly sprinkled him with holy water over several months. Microbiological examination of this holy water detected the multidrug-resistant Acinetobacter baumanii strain previously isolated from the patient (Michel et al. 2013). Because holy water may pose a risk for in- fection with pathogenic microorganisms through inoculation by hands, in this study we investigated the quantity and diversity of the cultivable bacterial community from holy water fonts and reservoirs located in some of the most visited Roman Catholic churches of Ljubljana, Slovenia. The bacterial isolates were identified and their resistance to selected antibiotics was analyzed to assess the potential health risk. Materials and methods Sampling and water analyses The sampling of holy water was carried out in ten churches in different parts of Ljubljana and the city area. In order to preserve anonymity, the names of the churches are not listed, but are labelled here with two-letter codes. Sampling took place three times at three-week intervals (the first sampling on March 11 and 12, 2019, the second on April 1 and 2, 2019, and the third on April 23 and 24, 2019). The third (final) sampling took place after Easter holiday, when churches are the most crowded. Samples were collected in sterile containers in the morning hours, before, during, or after morning Mass from the same fonts at the entrance and from the holy water reservoirs. We also collected a sample from tap water in church DC. Within two hours of collection, samples were inoculated onto culture media and incubated. The remaining water samples were stored at 4 °C until chemical analysis. During the final sampling, the temperature and pH of the holy water in the wells and reservoirs were measured. The water activity of the water samples from the first sampling was measured using the AquaLab 3TE instrument (Meter, Germany) according to manufacturer’s instructions. Sodium concentration of selected water samples from the first sampling was meas- ured using a Varian AA240 atomic absorption spectrophotometer. Bacterial isolation and identification Within two hours of collection, 10 µl and 100 µl of the collected water samples were inoculated onto blood agar (BA, Fluka) and onto UriSelect 45Turk et al.: Aerobic bacteria in holy water from Catholic churches 4 agar (URI, Bio-Rad) and incubated aerobically at 37 °C. After three days of incubation, colonies were counted, and all morphologically different colonies were selected and isolated in pure culture on Brain Heart Infusion (BHI) agar plates (Biolife). DNA was extracted from the isolated pure cultures using PrepMan Ultra reagent (Applied Biosystems) according to the manufacturer’s instructions. The 16S rRNA gene was amplified using primers 27f- CM (5’- AGAGTTTGATCMTGGCTCAG -3’) (Frank et al. 2008) and 1492R (5’- GGTTACCTTGTTACGACTT -3’) (Turner et al. 1999). The 16S rDNA gene amplicons were sequenced by Microsynth AG (Switzerland) using Sanger sequencing. The resulting sequences were analyzed using MUSCLE software (Edgar, 2004) implemented in the MEGA7 package (Kumar et al., 2016) and compared against the GenBank data- base (16S ribosomal RNA (Bacteria and Archaea) database) using BLASTN software (available at: https://blast.ncbi.nlm.nih.gov/Blast.cgi). All isolated strains from this study were deposited in the Ex Culture Collection of the Infrastructural Centre Mycosmo (MRIC UL) at the Department of Biology, Biotechnical Faculty, University of Ljubljana, Slovenia. Antibiotic susceptibility testing For antimicrobial susceptibility testing, the isolated bacterial strains were cultured on LB agar plates (Biolife) with 8 different commonly used antibiotics (Sigma) and incubated at 37 °C. The results were observed after 3 days. The fol- lowing antibiotics and concentrations were used: Ampicillin (AMP) 100 mg/l; Chloramphenicol (CHL) 25 mg/l; Cefotaxime (CTX) 2 mg/l; Colistin (COL) 3.5 mg/l; Enrofloxacin (ENR) 0.5 mg/l; Erythromycin (ERY) 15 mg/l; Imipenem (IPM) 4 mg/l; Kanamycin (KAN) 50 mg/l); Tetracycline (TET) 10 mg/l. Wild-type Escherichia coli strains EXB L-4239 A5 and EXB L-4240 A6 isolated from poultry with known resistance profiles were used as positive controls (recovered from Ex Culture Collection of the Infrastructural Centre Mycosmo (MRIC UL), University of Ljubljana). Community analyses using machine learning To analyze the obtained data and discover the connections between them, machine learning meth- ods were used. All data analyses were performed using the R statistical programming language and environment and Microsoft Excel 2016. The hier- archical clustering method was used to determine the similarity between samples, using the function “hclust()” from the package stats v3.6.1 (Müllner 2013). The R package randomForest was used to find how well the presence of individual bacterial species predicts the various characteristics of the sample (e.g. material of vessels) using a random forests approach. We calculated 10001 trees for each condition studied and determined from the calculated models the bacterial species whose presence best predicted each characteristic of the sample (Tang et al. 2014). Results The holy water is located in the churches in holy water fonts and containers, which can be made of different materials. The fonts in the studied churches were made of stone, porcelain, glass or metal, while the reservoirs in all the studied churches were made of metal - stainless steel (Fig. 1). 46Acta Biologica Slovenica, 2022, 65 (2), 42–103 Figure 1: Examples of holy water fonts made of different materials in the studied churches (top left metal, top right stone, bottom left glass, and bottom right porcelain). Slika 1: Primeri kropilnikov za blagoslovljeno vodo iz različnih materialov v proučevanih cerkvah (zgoraj levo kovinski, zgoraj desno kamnit, spodaj levo steklen in spodaj desno porcelanast). Physico-chemical parameters of holy water samples The values of selected physicochemical pa- rameters such as temperature, pH, water activity (aw), and sodium mass concentration in the holy water were measured (Tab. 1). These parameters were monitored with the aim of determining their influence on the growth of the cultivable aerobic bacterial community in fonts and reservoirs. 47Turk et al.: Aerobic bacteria in holy water from Catholic churches Table 1: Results of measurements of temperature, pH, water activity (aw) and sodium (Na+) mass concentration in holy water from various churches in Ljubljana and its surroundings. Tabela 1: Rezultati merjenja temperature, pH, vodne aktivnosti (aw) in masne koncentracije natrija (Na+) v blagoslovljeni vodi, vzorčeni v različnih cerkvah v Ljubljani in okolici. Church Sampling site Material of container Water T [°C] Water pH Water acitvity aW Na+ [mg/l] FC Font Glass 18 7.30 0.998 11.53 Reservoir Metal 21 7.84 0.997 8.56 SC Font Porcelain 18 7.76 0.998 - Reservoir Metal 19 7.83 0.998 - UC Font Glass 18 7.49 0.999 - Reservoir Metal 17 7.79 0.999 5.72 VC Font Glass 19 7.49 0.998 - Reservoir Metal 18 7.93 0.998 - TC Font Stone 15 7.99 0.979 14958.00 Reservoir - - - - - RC Font Metal 20 7.45 0.998 - Reservoir Metal 17 7.81 0.998 - BC Font Glass 17 7.67 0.998 - Reservoir Metal - 7.74 0.998 - SI Font Stone 20 7.70 0.997 - Reservoir Metal 18 7.79 0.997 4.72 KC Font Stone 18 7.38 0.997 - Reservoir Metal 17 7.80 - - DC Font Glass 16 7.68 0.995 2044.80 Reservoir Metal 16 7.83 0.991 4109.00 Tap water (W) - - 17 7.26 0.999 6.17 The temperature of the holy water was measured during the last, third sampling on April 23 and 24, 2019, it ranged from 15 °C to 21 °C. The pH of holy water samples from all three samplings was measured, and the average pH ranged from 7.30 to 7.99. In all sampled churches, the average pH of the holy water in the reservoir was slightly higher than in the font. The pH of the tap water (W) was 7.26. The water activity (aw) of the samples from the first sampling was also determined and ranged from 0.979 to 0.999, with the lowest aw value in the font of the church TC (0.979) and in the reservoir (0.991) and font (0.995) of the church DC. We also measured the sodium mass concentration of the selected samples. Holy water from the font of the church TC had the highest measured mass concentration of sodium (14.96 g/l), followed by holy water from the reservoir (4.11 g/l) and from the font (2.04 g/l) of the church DC. Sodium concentration in most samples of holy water from churches was 0.005-0.012 g/l, which is in the range of Na+ concentration in tap water (Tab. 1). 48Acta Biologica Slovenica, 2022, 65 (2), 42–103 Load of cultivable aerobic bacteria in holy water samples The number of cultivable aerobic bacteria in holy water samples was determined by the plate count method on blood agar after incubation at 37 °C. The colony counts of the samples from fonts (Fig. 2) spanned four orders of magnitude (102 – 105 colony-forming units (CFU) ml-1). For one third of the samples no value could be determined because of confluent overgrowth (too numerous to count – TNTC). The colony counts of samples from reservoirs spanned three orders of magnitude (101 – 103 CFU ml-1; Fig. 3). Comparing CFU numbers between samples from the font and the reservoir for a single church, the CFU count in the font was higher than in the reservoir in almost all cases. In some cases, it was not possible to obtain samples of holy water from reservoirs (BC, KC, RC, and especially TC; Fig. 3). There were also considerable differences in the number of CFUs in each church between samplings. Figure 2: Aerobic colony counts (CFU ml-1) in holy water samples from fonts in ten churches in different parts of Ljubljana and the city area. Values represent mean counts. TNTC – confluent overgrowth. Slika 2: Štetje aerobnih kolonijskih enot (CFU ml-1) v vzorcih blagoslovljene vode iz kropilnikov desetih cerkva v različnih predelih Ljubljane in njeni okolici. Vrednosti predstavljajo povprečja vzorčenj. TNTC – konfluentna rast. 49Turk et al.: Aerobic bacteria in holy water from Catholic churches Figure 3: Aerobic colony counts (CFU ml-1) in tap water and holy water samples from reservoirs in nine churches in different parts of Ljubljana and the city area. Values represent mean counts. TNTC – confluent growth. Slika 3: Štetje aerobnih kolonijskih enot (CFU ml-1) v pitni vodi in v vzorcih blagoslovljene vode iz rezervarjev devetih cerkva v različnih predelih Ljubljane in njeni okolici. Vrednosti predstavljajo povprečja vzorčenj. TNTC – konfluentna rast. Bacterial identification From 56 samples, one of which was tap water, 585 bacterial strains were isolated and identified. The results of the identification of the bacterial strains are given in the supplementary material (S1). Identification was performed by searching for homologous sequences of the 16S rRNA gene for our isolates in the GenBank database. Most of the identified strains were classified into the classes Gammaproteobacteria and Actinomycetes. The cultivable aerobic bacterial community differs from church to church, as not all taxa are present in all churches (Fig. 4). In addition, different bacterial taxa are present in the font and reservoir of each church. The highest number of species (21 and 22) was found in the holy water of the church RC from the font and reservoir (Fig. 4). Otherwise, the studied churches differed in the number of species isolated from the fonts compared to the reservoirs. In the four studied churches, the number of dif- ferent species was similar in fonts and reservoirs (DC, RC, UC, VC), in FC the species diversity in the holy water from the reservoir was higher (22) than in the font (14), and in four churches (BC, KC, SC and SI) the number of species in the water samples from the fonts was higher. 50Acta Biologica Slovenica, 2022, 65 (2), 42–103 Figure 4: The number of identified species of cultivable aerobic bacteria isolated from the holy water fonts and reservoirs of the studied churches, grouped by classes. Slika 4: Prikaz števila identificiranih vrst kultivabilnih aerobnih bakterij, izoliranih iz blagoslovljene vode kro- pilnikov in rezervarjev vzorčenih cerkva, združenih v razrede. Bacterial isolates were assigned to 52 genera. Genera whose species appeared in at least two samples were compared for their occurrence in holy water fonts and reservoirs (Fig. 5). Some genera occurred only in fonts (Delftia, Kocuria, Sphingobacterium, Staphylococcus), and only spe- cies of two genera (Acinetobacter, Pseudomonas) were found in all three sample groups. These two genera were also the most represented. Figure 5: Venn diagram (Heberle et al. 2015) of the occurrence of the identified bacterial genera in samples of holy water from fonts and reservoirs and from tap water. Slika 5: Vennov diagram (Heberle s sod. 2015) prisotnosti identificiranih bakterijskih rodov v vzorcih blagoslovljene vode kropilnikov in rezervarjev ter pitne vode. fonts reservoirs tap water 51Turk et al.: Aerobic bacteria in holy water from Catholic churches Bacterial community analysis using machine learning Machine learning methods were used to analyze the data obtained (bacterial species at different sampling sites) and to investigate the presence of bacterial species as a function of sampling site. We were interested in whether the presence of any of the species could be associated with the type of sample (font, reservoir). Certain bacterial species (Acinetobacter beijerinckii, Acinetobacter haemolyticus, Brevundimonas auran- tiaca, Brevundimonas mediterranea, Staphylococcus warneri) were present only in holy water fonts (Fig. 6). Similarly, some species were more abundant in fonts than in reservoirs (Acinetobacter johnso- nii, Aquincola tertiaricarbonis, Rothia amarae, Sphingobium hydrophobicum). The opposite phenomenon was observed for Microbacterium maritypicum, which was more abundant in holy water reservoirs (in seven of nine sampled reser- voirs) than in fonts (in three of ten sampled fonts). Figure 6: Occurrence of selected bacterial species depending on the container with holy water. Slika 6: Pojavnost izbranih bakterijskih vrst v odvisnosti od posode z blagoslovljeno vodo. The hierarchical clustering method was used to investigate the similarity between sampling sites (fonts and reservoirs) based on the matrix of the presence of different bacterial species. The more similar the bacterial communities of the sampling sites, the closer they are in the clustering tree (Fig. 7). Some reservoirs (churches DC, KC and BC) cluster together with tap water. In most cases, there is no grouping by church (font and reservoir of each church). 52Acta Biologica Slovenica, 2022, 65 (2), 42–103 Figure 7: Display of hierarchical clustering of sample sites into groups based on the bacterial species occurrence matrix. Color marks: blue - reservoirs, red - fonts, green - tap water (W). Slika 7: Prikaz hierarhičnega združevanja vzorčnih mest v skupine na osnovi matrice pojavljanja bakterijskih vrst. Barvne oznake: modra - rezervarji, rdeča – kropilniki, zelena - vodovodna voda (W). A connection between the container material and the occurrence of bacterial species was also tested (not shown). Acinetobacter beijerinckii, Brevundimonas mediterranea, Brevundimonas aurantiaca, Kocuria uropygioeca, and Sphingobacterium multivorum were isolated only from nonmetallic fonts. However, no association was found between a single bacterial species and a metal vessel, nor with other materials (glass, stone, porcelain). Resistance of bacterial isolates to selected antibiotics The effects of nine antibiotics on 83 selected bacterial strains isolated from the holy water fonts and reservoirs was investigated, namely ampicillin (AMP, 100 mg/l), tetracycline (TET, 12.5 mg/l), imipenem (IPM, 4 mg/l ), erythromycin (ERY, 15 mg/l), chloramphenicol (CHL, 25 mg/l), kanamycin (KAN, 50 mg/l), cefotaxime (CTX, 2 mg/l), enro- floxacin (ENR, 0.5 mg /l) and colistin (COL, 3.5 mg/l). Results are shown in the supplemental mate- rial (S2). Most strains were sensitive to tetracycline (12.5 mg/l) and chloramphenicol (25 mg/l) (Fig. 8), and more than half of the strains were resistant to colistin (3.5 mg/l) and cefotaxime (2 mg/l). 53Turk et al.: Aerobic bacteria in holy water from Catholic churches Figure 8: Summary of results for antimicrobial susceptibility for the 83 isolates tested, presented are percentages of isolates that are resistant. Ampicillin (AMP) 100 mg/l; chloramphenicol (CHL) 25 mg/l; cefotaxime (CTX) 2 mg/l; colistin (COL) 3.5 mg/l; enrofloxacin (ENR) 0.5 mg/l; erythromycin (ERY) 15 mg/l; imipenem (IPM) 4 mg/l; kanamycin (KAN) 50 mg/l); tetracycline (TET) 10 mg/l. Slika 8: Povzetek rezultatov občutljivosti proti antibiotikom za 83 testiranih izolatov, predstavljen je odstotek izolatov, ki so odporni. Ampicilin (AMP) 100 mg/l; kloramfenikol (CHL) 25 mg/l; cefotaksim (CTX) 2 mg/l; kolistin (COL) 3.5 mg/l; enrofloksacin (ENR) 0.5 mg/l; eritromicin (ERY) 15 mg/l; imipenem (IPM) 4 mg/l; kanamicin (KAN) 50 mg/l); tetraciklin (TET) 10 mg/l. Resistance profiles for individual species of the same genus are similar. Among bacterial species potentially pathogenic to humans and vertebrates, Pseudomonas aeruginosa (resistant to 7 antibiotics tested at selected concentrations) and Stenotrophomonas maltophilia (resistant to 4 antibiotics tested) were the most resistant to studied antibiotics. Discussion In Slovenia, 57.8% of the population declared themselves Roman Catholic, according to the last census in 2002 (Črnič et al. 2013). As in other Christian religions, for Catholics, holy water is water that has been blessed by a priest and is used for baptism and to bless people, churches, homes, and objects of devotion (Jurado et al. 2002, Kirschner et al. 2012). Some studies have presented holy water as a potential source of infec- tion with pathogenic organisms (Rees and Allen 1996, Greaves and Porter 1992, Michel et al. 2013, Gajurel and Deresinski 2021). Due to COVID -19 concern, many churches emptied their holy water fonts and, in some churches, a non-contact holy water dispenser was installed (Pullella 2020; Drogo 2022). In this study, we investigated the microbiological quality of holy water in the fonts and reservoirs of ten selected Roman Catholic churches in Ljubljana and its surroundings, focusing on bacteria. In order to assess the potential health risk of the bacterial strains isolated from the holy water, they were identified and their resistance to selected antibiotics was analyzed. The aerobic bacterial load of the holy water was determined by the plate count method. In most of the churches studied, the number of CFU ml-1 was higher in the holy water from fonts (102 - 105 CFU ml-1; Fig. 2) than in the reservoirs (101 - 103 CFU ml-1; Fig. 3), which is to be expected since the church visitors have direct daily contact with the holy water from the fonts. The bacterial load varied among the different churches and also among the sampling of a single church. This relatively moderate bacterial contamination of holy water from fonts is consistent with previous studies from churches in Vienna, Austria (Kirschner et al. 2012) and in the Villingen-Schwenningen area, Germany (König et al. 2017), where similar cultivation con- ditions (rich medium, incubation at 37 °C) were used. In Vienna, all holy water samples from the investigated churches and hospital chapels had high concentrations of heterotrophic microbial counts at 37 °C, up to 3 × 107 CFU ml-1, higher than in our study, while in Villingen-Schwenningen 9,6 % 2,4 % 9,6 % 3,6 % 25,3 % 16,9 % 59,0 % 63,9 % 21,7 % 54Acta Biologica Slovenica, 2022, 65 (2), 42–103 (Germany) the colony count showed an average aerobic microbial load of 5.85±3.98 × 103 CFU ml-1. In a study of holy water fonts from churches in Seville, Spain, total aerobic bacteria and coliforms in certain churches were ‘too numer- ous to count’ (Jurado et al. 2002). Bacterial load is certainly influenced by the number of visitors and the frequency of cleaning and replacement of water from fonts (König et al. 2017, Jurado et al. 2002). This type of data would help us under- stand the differences between the bacterial load of the sampled churches in Ljubljana, but these data were not available. Nevertheless, our results confirm that the frequent immersion of fingers in holy water fonts is probably the main reason for the higher bacterial load in the fonts compared to the reservoirs. In this way, microbes – and also nutrients for their growth – are transferred from the skin to the holy water (Kirschner et al. 2012). The Roman Catholic Church recommends adding blessed salt (NaCl) to the water during the blessing (Kirschner et al. 2012). Salt was found only in holy water samples from two churches and its concentration was low, ranging from 0.2 to 1.5% NaCl (m/v) (Tab.1). In most churches, the sodium concentration was of the same order of magnitude as the concentration in tap water. In a study from Spain, the viability of selected bacterial species was measured as a function of different NaCl concentrations. At NaCl concentrations of 20% or more, both pathogenic and nonpathogenic bacteria lysed (Jurado et al. 2002). This process, called plasmolysis, occurs due to water efflux leading to a decrease in cytoplasmic volume. This can lead to retraction of cell walls, detachment and wrinkling of the plasmalema, and disruption of protein assemblies that extend across the cell wall (Wood 2011). In a study by Hrenovic and Ivankovic (2009) testing the survival of E. coli and Acinetobacter junii at different NaCl concentra- tions, complete death of E. coli was achieved after 72 hours at concentrations of 20% NaCl. Thus, to prevent contamination of the holy water, larger amounts of NaCl would have to be added than was detected in our samples because only then would the growth of most microorganisms be completely inhibited. However, high NaCl concentrations can damage the fonts, so the use of NaCl should be carefully balanced with protection of cultural heritage (Jurado et al. 2002). An alternative is to change the holy water daily and to clean the holy water fonts regularly. From 56 samples of holy water, 585 bacterial isolates were obtained and identified based on the homologous sequences of the 16S rRNA gene in the GenBank database. The aerobic cultivable commu- nity of the holy water consisted mainly of bacterial species from the classes Gammaproteobacteria and Actinomycetes (Fig. 4). The bacterial com- munity differed between churches as well as between the font and the reservoir of each church. Some genera were present only in the holy water from fonts (Delftia, Kocuria, Sphingobacterium, Staphylococcus), and only species of two genera (Acinetobacter, Pseudomonas) were found in the holy water from fonts, reservoirs, and tap water (Fig. 5). It is likely that some of the identified bacteria in holy water fonts originated from the skin of church visitors. In the microbiota of human hands studied by amplicon sequencing, species from the phyla Pseudomonadota, Actinomycetota, and Bacillota were found, accounting for 94% of all identified bacterial species, with the most abundant genera Cutibacterium (31.6% of all se- quences; Actinomycetota), Streptococcus (17.2%; Bacillota), Staphylococcus (8.3%; Bacillota), Corynebacterium (4.3%; Actinomycetota), and Lactobacillus (3.1%; Bacillota) (Egert and Simmering 2016, Byrd et al. 2018, Carmona-Cruz et al. 2022). In agreement with previous studies (Rees and Allen 1996, Jurado et al. 2002, Kirschner et al. 2012, König et al. 2017), we also detected bacteria of probable fecal origin, i.e., enterococci and enterobacteria, albeit in very low abundance. The representative of fecal indicator bacteria, Enterococcus sp., was found in only one sample of holy water from the reservoir, while Citrobacter freundii and Enterobacter cloacae were detected in two samples from fonts. Using machine learning methods, we aimed to investigate the occurrence of bacterial spe- cies as a function of sampling location (font or reservoir). Some bacterial species occurred only in holy water from fonts (Acinetobacter beijer- inckii, Acinetobacter haemolyticus, Brevundimonas aurantiaca, Brevundimonas mediterranea, Staphylococcus warneri), while others, such as Microbacterium maritypicum, were more abundant 55Turk et al.: Aerobic bacteria in holy water from Catholic churches in holy water reservoirs (Fig. 6). These bacteria have relatively low pathogenic potential, and some of them are considered to be skin commensals. The genus Acinetobacter (Pseudomonadota) is generally found in aqueous environments, with the majority of species being non-pathogenic. The most common species causing infections is A. bauman- nii, followed by species also found on human skin, such as A. calcoaceticus and A. lwoffii, which has also been isolated from our holy water samples. These are largely opportunistic pathogens that cause infections, especially in immunocompromised patients. Other species, including A. haemolyticus, A. johnsonii, A. junii, A. nosocomialis, A. pittii, A. schindleri, and A. ursingii, have occasionally been reported as pathogens (Wong et al. 2017). Brevundimonas spp. (Pseudomonadota) are a genus of non-fermenting Gram-negative bacteria and, particularly Brevundimonas diminuta and Brevundimonas vesicularis, are considered to be of minor clinical importance (Ryan and Pembroke 2018). Microbacterium species (Actinomycetota), non-spore-forming, Gram-positive rods, have also rarely been associated with human disease. However, increasing amount of literature shows that Microbacterium species are opportunistic human pathogens, causing, for example, infec- tive endocarditis associated with Microbacterium maritypicum bacteremia (Yeung et al. 2020). But Staphylococcus warneri, a coagulase-negative staphylococcus (CNS) commonly found in the microbiota of human and animal epithelia and mucosa, is considered an opportunistic pathogen that causes serious infections in humans and animals (Liu et al. 2020). The hierarchical clustering was used to deter- mine the similarity between sampling sites (fonts and reservoirs) based on the matrix of occurrence of different bacterial species. Some of the reservoirs were clustered together with the tap water, indicat- ing that an important part of bacterial community in these reservoirs originated from the tap water (Fig. 7). However, this is not true for all sampled churches. Perhaps unexpectedly, we also did not observe clustering of samples from the reservoirs and fonts from the same church. Since the fonts in the sampled churches were made of stone, porcelain, glass, and metal, we tested whether there was a relationship between the font material and the presence of bacterial species. Although certain bacterial species were isolated only from non-metallic fonts, unfortunately no correlation was found between the material of the vessel (metal, stone, glass, porcelain) and the presence of certain bacterial species. The choice of the material of the vessel containing the holy water affects the growth of microorganisms through the smoothness of its surface. Rougher surfaces provide a better substrate for microbial attachment and biofilm formation. Microorganisms adhere more quickly to hydrophobic and nonpolar materials (plastic) than to hydrophilic materials (glass or metal) (Donlan 2002). To reduce contamination of the holy water, it would be better to use fonts made of glass or metal than fonts made of stone, for example. Testing of the selected bacterial isolates for antibiotic resistance to nine antibiotics showed that the majority of the strains tested were sensi- tive to tetracycline (12.5 mg/l) and chloram- phenicol (25 mg/l) and resistant to cefotaxime (2 mg/l) and colistin (3.5 mg/l) (Fig. 8). The use of colistin has increased recently mainly because of the emergence of multidrug-resistant Gram-negative bacteria. It is used as a last resort antibiotic against most Enterobacterales species and non-fermenting Gram-negative bacteria such as Acinetobacter baumannii and Pseudomonas aeruginosa. Conversely, colistin is not active against Gram-positive bacteria, Gram-negative cocci, and anaerobic bacteria (Torres et al. 2021). However, such a high level of resistance (63,9% of bacterial isolates) could be alarming. The European Committee on Antimicrobial Susceptibility Testing (EUCAST) minimal inhibitory concentration (MIC) breakpoints for colistin (EUCAST 2022) for interpretation are for Acinetobacter spp. and Enterobacterales ≤ 2 mg l-1 susceptible (S), > 2 mg l-1 resistant (R), while for Pseudomonas spp. ≤ 4 mg l-1 susceptible, > 4 mg l-1 resistant. However, the Clinical and Laboratory Standards Institute (CLSI) recommends higher susceptibility breakpoints for P. aeruginosa (S ≤ 2 mg l-1, R ≥ 8 mg l-1) and for Enterobacterales and Acinetobacter spp. (S ≤ 2 mg l-1, R ≥ 4 mg l-1) (CLSI 2020). According to CLSI recommendations, the colistin concentration in the culture medium was too low to correctly assess susceptibility to colistin. The same may be 56Acta Biologica Slovenica, 2022, 65 (2), 42–103 true for cefotaxime, where the EUCAST recom- mendations are for Enterobacterales and other non-species related (S ≤ 1 mg l-1, R ≥ 2 mg l-1) (EUCAST 2022), whereas the CLSI breakpoint recommendations are for aerobic bacteria (S ≤ 1 mg l-1, R ≥ 4 mg l-1) (Humphries et al. 2019). The observed high resistance in Pseudomonas aerugi- nosa and Stenotrophomonas maltophilia strains, both of which are most commonly associated with respiratory infections in humans, is somewhat expected and consistent with the literature, as these multidrug-resistant species are intrinsically resistant to a variety of antibiotics (Brooke 2012, Luczkiewicz et al. 2015). According to our results, the risk of bacterial infection from holy water is modest, especially if only applied to unbroken skin. Many of the isolated bacteria from holy water may actually have been introduced by churchgoers. This is especially true for those bacteria that are considered part of skin microbiota and are not normally associated with aqueous environments. However, the unpredict- ability of contamination source of holy water means that the water may sporadically contain more problematic species than the ones identified in this study, or strains of the species found here, but with higher resistance to antibiotics. Therefore, sprinkling or other actions that can lead to inhalation or ingestion of the holy water or its introduction into eyes is not recommended, particularly for immunocompromised individuals, the elderly, neonates, and patients with severe burns, trauma, postoperative wounds, or intravenous access. Conclusions Holy water may pose a risk of infection with pathogenic microorganisms. Adding salt (NaCl) to holy water is an accepted practice in Catholic churches, but the concentrations required to limit most microbial growth (20% w/v or more) are often incompatible with the protection of fonts as part of the cultural heritage. Since the complete removal of water from fonts would likely be poorly accepted for religious reasons, the recommended practice to limit the transmission of potentially pathogenic microorganisms is regular and rigorous cleaning of the fonts, use of vessels with easy-to-clean surfaces and regular replacement, e.g., after sev- eral days during non-holiday period, and daily after attending Mass in churches during church holidays. The public, especially individuals with increased susceptibility for infection, can protect themselves by avoiding the contact of the holy water with eyes, nose, mouth, ears and broken skin, and by practising good hand hygiene. Povzetek V Sloveniji se je po zadnjem popisu prebival- stva iz leta 2002 za katoličane opredelilo 57,8 % prebivalcev (Črnič in sod. 2013). Tako kot v drugih krščanskih religijah je za katoličane blagoslovlje- na voda tista, ki jo je blagoslovil duhovnik in se uporablja pri svetem krstu ter za blagoslov ljudi, živali, cerkva, domov in predmetov (Jurado in sod. 2002, Kirschner in sod. 2012). Nekatere študije so blagoslovljeno vodo prepoznale kot potencialni vir okužbe s patogenimi organizmi (Rees in Allen 1996, Greaves in Porter 1992, Michel in sod. 2013, Gajurel in Deresinski 2021). Zaradi zaskrbljenosti zaradi COVID-19 so številne cerkve izpraznile kropilnike za blagoslovljeno vodo, v nekaterih cer- kvah so celo namestili brezkontaktne razdelilnike blagoslovljene vode (Pullella 2020, Drogo 2022). V tej raziskavi smo preučevali mikrobiološko kakovost blagoslovljene vode, s poudarkom na bakterijah, v kropilnikih in rezervarjih desetih izbranih rimskokatoliških cerkva v Ljubljani in njeni okolici. Da bi ocenili potencialno tveganje za zdravje, smo bakterijske seve, izolirane iz bla- goslovljene vode, identificirali in preučili njihovo odpornost proti izbranim antibiotikom. Obremenitev blagoslovljene vode z aerobnimi bakterijami smo določili z metodo štetja na plo- ščah. V večini proučevanih cerkva je bilo število kolonijskih enot (CFU) na ml vzorca večje v bla- goslovljeni vodi iz kropilnikov (102 - 105 CFU ml-1; sl. 2) kot v rezervoarjih (101 - 103 CFU ml-1; sl. 3), kar je pričakovano, saj imajo obiskovalci cerkve neposreden vsakodnevni stik s blagoslovljeno vodo iz kropilnikov. Obremenitev z bakterijami se je razlikovala med različnimi cerkvami in tudi med različnimi vzorčenji ene same cerkve. Ugotovljena relativno zmerna bakterijska konta- minacija blagoslovljene vode iz kropilnikov je 57Turk et al.: Aerobic bacteria in holy water from Catholic churches skladna s prejšnjimi študijami iz cerkva na Dunaju v Avstriji (Kirschner in sod. 2012) in na območju Villingen-Schwenningen v Nemčiji (König in sod. 2017), kjer so uporabili podobne pogoje gojenja (bogato gojišče, inkubacija pri 37 °C). Na Dunaju so imeli vsi vzorci blagoslovljene vode iz preisko- vanih cerkva in bolnišničnih kapelic visoko število heterotrofnih mikrobov pri 37 °C, do 3 × 107 CFU ml-1, več kot v naši študiji, medtem ko je bila na območju Villingen-Schwenningena (Nemčija) povprečna mikrobna obremenitev blagoslovljene vode z aerobi 5,85±3,98 × 103 CFU ml-1. V študiji blagoslovljene vode iz kropilnikov cerkva v Sevilli v Španiji je bilo število aerobnih ter koliformnih bakterij v nekaterih cerkvah previsoko, da bi jih lahko prešteli (»too numerous too count«, TNTC) (Jurado in sod. 2002). Na obremenitev z bakterijami zagotovo vpliva število obiskovalcev ter pogostost čiščenja in menjave vode v kropilnikih (König in sod. 2017, Jurado in sod. 2002). Tovrstni podatki bi nam pomagali razumeti razlike med bakterijsko obremenitvijo blagoslovljene vode iz kropilnikov preučevanih cerkva v Ljubljani, vendar ti podatki niso bili na voljo. Kljub temu naši rezultati potr- jujejo, da je pogosto pomakanje prstov vernikov v vodo kropilnika ob vstopu in izstopu iz cerkve verjetno glavni razlog za večjo bakterijsko obre- menitev v kropilnikih v primerjavi z rezervoarji. Na ta način se mikrobi – in tudi hranila za njihovo rast – prenesejo s kože v blagoslovljeno vodo (Kirschner in sod. 2012). Rimskokatoliška cerkev priporoča dodajanje blagoslovljene soli (NaCl) vodi ob blagoslovu (Kirschner in sod. 2012). Sol smo določili le v vzorcih blagoslovljene vode iz dveh cerkva, njena koncentracija pa je bila nizka in se je gibala od 0,2 do 1,5 % NaCl (m/v) (Tab.1). V večini cerkva je bila koncentracija natrija enakega reda velikosti kot v vodovodni vodi. V študiji iz Španije so merili sposobnost preživetja izbranih bakterijskih vrst kot funkcijo različnih koncentracij NaCl. Pri koncen- traciji NaCl 20 % ali več naj bi tako patogene kot nepatogene bakterije lizirale (Jurado in sod. 2002). Do tega procesa, imenovanega plazmoliza, pride zaradi izhajanja vode, ki povzroči zmanjšanje volumna citoplazme. To lahko privede do umika celične stene, odcepitve in gubanja plazmaleme ter prekinitev proteinskih kompleksov, ki segajo čez celično steno (Wood 2011). V študiji Hrenovic in Ivankovic (2009), kjer so testirali preživetje E. coli in Acinetobacter junii pri različnih koncen- tracijah NaCl, je bilo popolno uničenje E. coli pri koncentraciji 20 % NaCl doseženo po 72 urah. Da bi preprečili kontaminacijo blagoslovljene vode, bi tako morali dodati večje količine NaCl, kot smo jih zaznali v naših vzorcih, saj bi le tako popolnoma zavrli rast večine mikroorganizmov. Visoke koncentracije NaCl pa lahko poškodujejo kropilnike, zato moramo uporabo NaCl skrbno uravnotežiti z varovanjem kulturne dediščine (Jurado in sod. 2002). Druga alternativa je, da blagoslovljeno vodo dnevno menjamo in redno čistimo kropilnike. Iz 56 vzorcev blagoslovljene vode smo osamili 585 bakterijskih izolatov, ter jih identificirali na podlagi homolognih zaporedij gena za 16S rRNA v podatkovni zbirki GenBank. Združbo aerobnih gojljivih bakterij iz blagoslovljene vode so se- stavljale predvsem bakterijske vrste iz razredov Gammaproteobacteria in Actinomycetes (slika 4). Sestava bakterijske združbe se je razlikovala med cerkvami, pa tudi med kropilnikom in rezervoarjem posamezne cerkve. Nekateri rodovi so bili prisotni samo v blagoslovljeni vodi iz kropilnikov (Delftia, Kocuria, Sphingobacterium, Staphylococcus), v blagoslovljeni vodi iz kropilnikov, rezervoarjev in vodovodne vode pa smo identificirali vrste le dveh rodov (Acinetobacter, Pseudomonas) (sl. 5). Verjetno so nekatere od identificiranih bakterij iz kropilnikov izvirale s kože obiskovalcev cerkve. V mikrobioti kože človeških rok, ki so jo preu- čevali s sekvenciranjem pomnožkov, so bile naj- dene vrste iz bakterijskih debel Pseudomonadota, Actinomycetota in Bacillota, ki so predstavljale 94 % vseh identificiranih bakterijskih vrst, z najbolj razširjenimi rodovi Cutibacterium (31,6 % vseh zaporedij; Actinomycetota), Streptococcus (17,2 %; Bacillota), Staphylococcus (8,3 %; Bacillota), Corynebacterium (4,3 %; Actinomycetota) in Lactobacillus (3,1 %; Bacillota) (Egert in Simmering 2016, Byrd in sod. 2018, Carmona- Cruz in sod. 2022). V skladu s predhodnimi študijami (Rees in Allen 1996, Jurado in sod. 2002, Kirschner in sod. 2012, König in sod. 2017) smo odkrili tudi bakterije fekalnega izvora, to so enterokoki in enterobakterije, čeprav v zelo nizkem številu. Tako je bil predstavnik fekalnih indikatorskih bakterij Enterococcus sp. najden le 58Acta Biologica Slovenica, 2022, 65 (2), 42–103 v enem vzorcu blagoslovljene vode iz rezervoarja, Citrobacter freundii in Enterobacter cloacae pa v dveh vzorcih vode iz kropilnikov. Z uporabo metod strojnega učenja smo želeli raziskati pojavljanje bakterijskih vrst kot funk- cijo lokacije vzorčenja (kropilnik ali rezervoar). Nekatere bakterijske vrste so se pojavljale le v blagoslovljeni vodi iz kropilnikov (Acinetobacter beijerinckii, Acinetobacter haemolyticus, Brevundimonas aurantiaca, Brevundimonas me- diterranea, Staphylococcus warneri), medtem ko so bile druge, kot je Microbacterium maritypicum, bolj pogoste v rezervoarjih blagoslovljene vode (sl. 6). Večina teh bakterij ima razmeroma nizek pato- geni potencial in nekatere od njih veljajo za kožne komensale. Rod Acinetobacter (Pseudomonadota) se običajno nahaja v vodnem okolju, pri čemer je večina vrst nepatogenih. Najpogostejša vrsta, ki povzroča okužbe, je A. baumannii, sledijo pa ji vrste, ki jih najdemo tudi na človeški koži, kot sta A. calcoaceticus in A. lwoffii, ki je bil prav tako izoliran iz naših vzorcev blagoslovljene vode. To so večinoma oportunistični patogeni, ki pov- zročajo okužbe, zlasti pri bolnikih z oslabljenim imunskim sistemom. Druge vrste, vključno z A. haemolyticus, A. johnsonii, A. junii, A. nosocomi- alis, A. pittii, A. schindleri in A. ursingii, naj bi le redko povzročale okužbe (Wong in sod. 2017). Brevundimonas spp. (Pseudomonadota) so rod nefermentirajočih gramnegativnih bakterij in so, zlasti Brevundimonas diminuta in Brevundimonas vesicularis, le malo klinično pomembne (Ryan in Pembroke 2018). Vrste rodu Microbacterium (Actinomycetota), ki so grampozitivne paličice in ne tvorijo spor, so prav tako redko povezovali z okužbami pri ljudeh. Vse več raziskav pa kaže, da so vrste rodu Microbacterium oportunistični človeški patogeni, ki lahko na primer povzročijo infektivni endokarditis, povezan z bakteriemijo, povzročeno z Microbacterium maritypicum (Yeung in sod. 2020). Po drugi strani pa Staphylococcus warneri, koagulazno negativni stafilokok (CNS), ki ga pogosto najdemo v mikrobioti človeških in živalskih epitelijev in sluznic, velja za oportuni- stičnega patogena, ki povzroča resne okužbe pri ljudeh in živalih (Liu in sod. 2020). Hierarhično združevanje smo uporabili za ugotavljanje podobnosti med mesti vzorčenja (kropilniki in rezervoarji) na podlagi matrike pojavljanja različnih bakterijskih vrst. Nekateri rezervoarji so se združevali skupaj z vodovodno vodo, kar kaže, da pomemben del bakterijske združbe v teh rezervoarjih izvira iz vodovodne vode (sl. 7). Vendar to ne velja za vse vzorče- ne cerkve. Morda nepričakovano tudi nismo opazili združevanja vzorcev iz rezervoarjev in kropilnikov posamezne cerkve. Ker so bili kro- pilniki v preučevanih cerkvah izdelani iz kamna, porcelana, stekla in kovine, smo ugotavljali, ali obstaja povezava med materialom kropilnika in prisotnostjo posameznih bakterijskih vrst. Čeprav so bile določene bakterijske vrste izolirane samo iz nekovinskih kropilnikov, žal nismo ugotovili povezave med materialom posode (kovina, ka- men, steklo, porcelan) in prisotnostjo določenih bakterijskih vrst. Material posode z blagoslovljeno vodo vpliva na rast mikroorganizmov z gladkostjo površine. Bolj grobe površine zagotavljajo boljšo podlago za pritrditev mikrobov in tvorbo biofilma. Mikroorganizmi se hitreje prilepijo na hidrofobne in nepolarne materiale (plastika) kot na hidrofilne materiale (steklo ali kovina) (Donlan 2002). Da bi zmanjšali onesnaženje blagoslovljene vode, bi bilo bolje uporabiti kropilnike na primer iz stekla ali kovine kot iz kamna. Protimikrobno testiranje izbranih bakterijskih izolatov proti devetim antibiotikom je pokazalo, da je večina testiranih sevov občutljivih proti tetraciklinu (12,5 mg/l) in kloramfenikolu (25 mg/l) ter odpornih proti cefotaksimu (2 mg/l) in kolistinu (3,5 mg/l) (sl. 8). Uporaba kolistina se je v zadnjem času povečala predvsem zaradi pojava gramnegativnih bakterij, odpornih proti več antibiotikom. Uporablja se kot antibiotik zadnje obrambne linije proti večini vrst reda Enterobacterales in nefermentirajočih gramnega- tivnih bakterij, kot sta Acinetobacter baumannii in Pseudomonas aeruginosa. Nasprotno pa kolistin ne deluje proti grampozitivnim bakterijam, gra- mnegativnim kokom in anaerobnim bakterijam (Torres in sod. 2021). Zato bi lahko bila tako visoka stopnja odpornosti (63,9 % bakterijskih izolatov) zaskrbljujoča. Smernice mejnih vrednosti minimalne inhibitorne koncentracije (MIC) za kolistin (EUCAST 2022) po EUCAST (European Committee on Antimicrobial Susceptibility Testing) so za Acinetobacter spp. in Enterobacterales ≤ 2 mg l-1 občutljiv (S), > 2 mg l-1 odporen (R), 59Turk et al.: Aerobic bacteria in holy water from Catholic churches medtem ko za Pseudomonas spp. velja ≤ 4 mg l-1 občutljiv, > 4 mg l-1 odporen. Vendar Inštitut za klinične in laboratorijske standarde (CLSI) priporoča višje mejne vrednosti občutljivosti za P. aeruginosa (S ≤ 2 mg l-1, R ≥ 8 mg l-1) ter za Enterobacterales in Acinetobacter spp. (S ≤ 2 mg l-1, R ≥ 4 mg l-1) (CLSI 2020). Glede na smernice CLSI je bila koncentracija kolistina v gojišču prenizka za pravilno oceno občutljivosti proti kolistinu. Enako bi lahko veljalo za cefotaksim, kjer so smernice EUCAST za Enterobacterales in druge nesorodne vrste (S ≤ 1 mg l-1, R ≥ 2 mg l-1) (EUCAST 2022), medtem ko so smernice CLSI za mejne vrednosti za aerobne bakterije (S ≤ 1 mg l-1, R ≥ 4 mg l-1) (Humphries in sod. 2019). Opažena visoka odpornost sevov vrst Pseudomonas aeruginosa in Stenotrophomonas maltophilia, ki sta najpogosteje povezani z okužbami dihal pri ljudeh, je pričakovana in skladna z objavami, saj sta ti vrsti intrinzično odporni proti več antibio- tikom (Brooke 2012, Luczkiewicz in sod. 2015). Glede na naše rezultate je tveganje za bakte- rijsko okužbo z blagoslovljeno vodo majhno, še posebej, če se jo nanaša samo na nepoškodovano kožo. Precej izoliranih bakterij iz blagoslovljene vode so najbrž vanjo vnesli obiskovalci cerkve. To še posebej velja za tiste bakterije, ki so prepoznane kot del mikrobiote kože in običajno niso povezane z vodnim okoljem. Vendar pa nepredvidljivost vira kontaminacije blagoslovljene vode pomeni, da lahko voda občasno vsebuje več problematičnih vrst od tistih, opredeljenih v tej študiji, ali sevov vrst, ki jih najdemo tukaj, vendar z večjo odpornostjo proti antibiotikom. Zato načini uporabe blagoslovljene vode, ki bi lahko vodili do vdihavanja, zaužitja vode ali njenega vnosa v oči ali druga tkiva, niso priporočljivi, zlasti za imunsko oslabljene posameznike, starejše, novorojenčke in bolnike s hudimi opeklinami, poškodbami, pooperativnimi ranami ali z vzpostavljeno periferno vensko potjo. Blagoslovljena voda tako lahko predstavlja nevarnost okužbe s patogenimi mikroorganizmi. Ker bi bila popolna odstranitev vode iz kropilnikov verjetno slabo sprejeta zaradi verskih razlogov, je priporočena praksa za omejitev prenosa po- tencialno patogenih mikroorganizmov redno in temeljito čiščenje kropilnikov, uporaba posod s površinami, ki jih je enostavno čistiti, in redna oziroma vsakodnevna zamenjava vode, zlasti po povečanem obisku cerkva (npr. ob cerkvenih praznikih). Javnost, zlasti posamezniki s povečano dovzetnostjo za okužbe, se lahko zaščitijo tako, da se izogibajo stiku blagoslovljene vode z očmi, nosom, usti, ušesi in poškodovano kožo ter z vzdrževanjem dobre higiene rok. Acknowledgements We acknowledge the financial support from the state budget of the Slovenian Research Agency (grants P1-0198, P4-0432, I0-0022 MRIC UL IC Mycosmo). The authors are grateful to Ms Barbara Kastelic Bokal for her technical assistance. Supplementary material Table S1: List of identified bacterial isolates from holy water of fonts and reservoirs. 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Mycosmo culture collection no. (exb) Genbank Identity Risk group Phylum, class, order, family Sample Medium and growth temperature L-5025 Kocuria salsicia 99.72 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae FC_1 blood agar, 37 °C L-5026 Brevundimonas aurantiaca 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_1 blood agar, 37 °C L-5027 Brevundimonas vesicularis/ Brevundimonas nasdae 99.9 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_1 blood agar, 37 °C L-5028 Staphylococcus lugdunensis 100 2 Bacillota, Bacilli, Bacillales, Staphylococcaceae FC_1 blood agar, 37 °C L-5029 Kocuria arsenatis/Kocuria rhizophila 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae FC_1 blood agar, 37 °C L-5030 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_1 blood agar, 37 °C L-5031 Brevundimonas vesicularis/ Brevundimonas nasdae 99.9 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_1 UriSelect4 agar, 37 °C L-5032 Brevundimonas aurantiaca 99.91 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_1 UriSelect4 agar, 37 °C L-5033 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 blood agar, 37 °C L-5034 Ralstonia pickettii 99.7 2 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae FC_R1 blood agar, 37 °C L-5035 Pseudomonas alcaliphila/ Pseudomonas oleovorans 99.89 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 blood agar, 37 °C 63Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5036 Pseudomonas chloritidismutans/ Pseudomonas knackmussii 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 UriSelect4 agar, 37 °C L-5037 Ralstonia pickettii 99.82 2 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae FC_R1 UriSelect4 agar, 37 °C L-5038 Microbacterium invictum 98.42 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R1 blood agar, 37 °C L-5039 Pseudomonas chloritidismutans/ Pseudomonas knackmussii 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 blood agar, 37 °C L-5040 Brevibacterium sanguinis 100 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R1 blood agar, 37 °C L-5041 Ralstonia pickettii 99.79 2 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae FC_R1 blood agar, 37 °C L-5042 Microbacterium maritypicum 99.82 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R1 blood agar, 37 °C L-5043 Microbacterium maritypicum 99.8 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R1 UriSelect4 agar, 37 °C L-5044 Pseudomonas chloritidismutans/ Pseudomonas knackmussii 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 UriSelect4 agar, 37 °C L-5045 Pseudomonas chengduensis 99.82 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 UriSelect4 agar, 37 °C L-5046 Pseudomonas chengduensis 99.89 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 UriSelect4 agar, 37 °C L-5047 Microbacterium invictum 98.35 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R1 UriSelect4 agar, 37 °C L-5048 Pseudomonas chengduensis 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R1 UriSelect4 agar, 37 °C L-5049 Rothia kristinae 99.56 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae FC_2 blood agar, 37 °C L-5050 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_2 blood agar, 37 °C L-5051 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_2 UriSelect4 agar, 37 °C 64Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5052 Sphingomonas hankookensis 99.41 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_2 UriSelect4 agar, 37 °C L-5053 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae FC_2 UriSelect4 agar, 37 °C L-5054 Actinomyces haliotis 99.97 1 Actinomycetota, Actinomycetes, Micrococcales, Actinomycetaceae FC_2 UriSelect4 agar, 37 °C L-5055 Rothia amarae 97.88 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae FC_2 UriSelect4 agar, 37 °C L-5056 Rothia terrae 98.96 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae FC_2 blood agar, 37 °C L-5057 Staphylococcus haemolyticus 99.82 2 Bacillota, Bacilli, Bacillales, Staphylococcaceae FC_2 blood agar, 37 °C L-5058 Rothia kristinae 99.63 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae FC_2 blood agar, 37 °C L-5059 Brevundimonas aurantiaca 99.9 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_2 blood agar, 37 °C L-5060 Brevundimonas aurantiaca 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_2 UriSelect4 agar, 37 °C L-5061 Staphylococcus haemolyticus 99.91 2 Bacillota, Bacilli, Bacillales, Staphylococcaceae FC_2 UriSelect4 agar, 37 °C L-5062 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_2 UriSelect4 agar, 37 °C L-5063 Rothia kristinae 99.63 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae FC_2 UriSelect4 agar, 37 °C L-5064 Rothia kristinae 99.63 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae FC_2 UriSelect4 agar, 37 °C L-5067 Microbacterium testaceum 99.05 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R2 blood agar, 37 °C L-5068 Brevibacterium sanguinis 99.72 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R2 blood agar, 37 °C L-5069 Brevibacterium sanguinis 99.72 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R2 UriSelect4 agar, 37 °C L-5070 Brevundimonas vesicularis/ Brevundimonas nasdae 99.79 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae FC_R2 blood agar, 37 °C L-5071 Chryseobacterium shandongense 99.91 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae FC_R2 UriSelect4 agar, 37 °C L-5072 Brevibacterium casei 99.22 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R2 UriSelect4 agar, 37 °C 65Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5073 Sphingobacterium daejeonense 99.63 1 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae FC_R2 UriSelect4 agar, 37 °C L-5074 Pseudomonas rhodesiae 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R2 UriSelect4 agar, 37 °C L-5075 Pseudomonas chloritidismutans/ Pseudomonas knackmussii 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R2 UriSelect4 agar, 37 °C L-5076 Stenotrophomonas maltophilia 99.35 2 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae FC_R2 UriSelect4 agar, 37 °C L-5077 Microbacterium saccharophilum 99.14 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R2 UriSelect4 agar, 37 °C L-5078 Pseudomonas chengduensis 99.8 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R2 UriSelect4 agar, 37 °C L-5079 Pseudomonas chloritidismutans/ Pseudomonas knackmussii 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R2 UriSelect4 agar, 37 °C L-5080 Acinetobacter haemolyticus 99.2 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_1 blood agar, 37 °C L-5081 Brevundimonas mediterranea 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_1 blood agar, 37 °C L-5082 Acinetobacter johnsonii 99.61 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_1 blood agar, 37 °C L-5083 Brevundimonas vesicularis/ Brevundimonas nasdae 99.61 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_1 blood agar, 37 °C L-5084 Sphingomonas hankookensis 99.42 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_1 blood agar, 37 °C L-5085 Sphingomonas hankookensis 99.42 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_1 blood agar, 37 °C L-5086 Sphingomonas hankookensis 99.42 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_1 blood agar, 37 °C 66Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5087 Sphingomonas hankookensis 99.42 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_1 blood agar, 37 °C L-5089 Sphingomonas hankookensis 98.87 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_1 UriSelect4 agar, 37 °C L-5090 Staphylococcus vitulinus 99.91 1 Bacillota, Bacilli,Bacillales, Staphylococcaceae SC_1 UriSelect4 agar, 37 °C L-5091 Acinetobacter haemolyticus 99.14 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_1 UriSelect4 agar, 37 °C L-5092 Sphingomonas hankookensis 99.51 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_1 UriSelect4 agar, 37 °C L-5093 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_1 UriSelect4 agar, 37 °C L-5094 Acinetobacter johnsonii 99.57 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_1 UriSelect4 agar, 37 °C L-5095 Staphylococcus vitulinus 99.9 1 Bacillota, Bacilli, Bacillales, Staphylococcaceae SC_1 UriSelect4 agar, 37 °C L-5097 Pseudomonas peli 99.63 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SC_R1 blood agar, 37 °C L-5098 Bacillus drentensis/Bacillus infantis 99.7 1 Bacillota, Bacilli, Bacillales, Bacillaceae UC_1 blood agar, 37 °C L-5099 Microbacterium testaceum 99.12 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_1 blood agar, 37 °C L-5100 Aquincola tertiaricarbonis 98.25 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_1 blood agar, 37 °C L-5101 Aquincola tertiaricarbonis 98.4 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_1 blood agar, 37 °C L-5102 Microbacterium testaceum 99.15 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_1 UriSelect4 agar, 37 °C L-5103 Aquincola tertiaricarbonis 98.18 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_1 UriSelect4 agar, 37 °C 67Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5104 Aquincola tertiaricarbonis 98.24 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_R1 blood agar, 37 °C L-5105 Microbacterium lacus 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R1 blood agar, 37 °C L-5107 Aquincola tertiaricarbonis 98.29 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_R1 UriSelect4 agar, 37 °C L-5108 Enterococcus ureilyticus 99.9 1 Bacillota, Bacilli, Lactobacillales, Enterococcaceae UC_R1 UriSelect4 agar, 37 °C L-5109 Cellulosimicrobium funkei 99.72 1 Actinomycetota, Actinomycetes, Micrococcales, Promicromonosporaceae UC_R1 UriSelect4 agar, 37 °C L-5110 Microbacterium maritypicum 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R1 UriSelect4 agar, 37 °C L-5111 Microbacterium saccharophilum 98.28 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R1 UriSelect4 agar, 37 °C L-5112 Aquincola tertiaricarbonis 98.38 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_R1 UriSelect4 agar, 37 °C L-5113 Microbacterium maritypicum 99.8 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R1 UriSelect4 agar, 37 °C L-5114 Kocuria carniphila 99.72 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae UC_R1 UriSelect4 agar, 37 °C L-5115 Acinetobacter johnsonii 99.78 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_R1 UriSelect4 agar, 37 °C L-5116 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R1 UriSelect4 agar, 37 °C L-5117 Pseudomonas koreensis 99.65 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_R1 UriSelect4 agar, 37 °C L-5120 Janibacter indicus 99.09 1 Actinomycetota, Actinomycetes, Micrococcales, Intrasporangiaceae UC_R1 UriSelect4 agar, 37 °C L-5121 Rothia amarae 98.04 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae UC_R1 UriSelect4 agar, 37 °C L-5122 Acinetobacter beijerinckii 98.93 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_1 blood agar, 37 °C L-5123 Acinetobacter johnsonii 99.9 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_1 blood agar, 37 °C 68Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5124 Acinetobacter johnsonii 98.76 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_1 blood agar, 37 °C L-5125 Acinetobacter johnsonii 99 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_1 blood agar, 37 °C L-5126 Acinetobacter johnsonii 99.9 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_1 UriSelect4 agar, 37 °C L-5127 Chryseobacterium hispalense 99.79 1 Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae VC_1 UriSelect4 agar, 37 °C L-5128 Microbacterium maritypicum 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_1 UriSelect4 agar, 37 °C L-5129 Kocuria carniphila 99.71 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae VC_1 UriSelect4 agar, 37 °C L-5130 Pseudomonas koreensis 99.62 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae VC_1 UriSelect4 agar, 37 °C L-5131 Acinetobacter johnsonii 99.89 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_1 UriSelect4 agar, 37 °C L-5132 Pseudomonas rhodesiae 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae VC_1 UriSelect4 agar, 37 °C L-5133 Acinetobacter johnsonii 99.89 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_1 UriSelect4 agar, 37 °C L-5134 Barrientosiimonas humi 99.9 1 Actinomycetota, Actinomycetes, Micrococcales, Dermacoccaceae VC_R1 blood agar, 37 °C L-5136 Novosphingobium aquaticum/ Novosphingobium subterraneum/ Novosphingobium lentum 97.82 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Erythrobacteraceae VC_R1 blood agar, 37 °C L-5137 Ponticoccus gilvus 100 1 Pseudomonadota, Alphaproteobacteria, Rhodobacterales, Rhodobacteraceae VC_R1 blood agar, 37 °C L-5139 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R1 blood agar, 37 °C L-5140 Bacillus aerius 99.68 1 Bacillota, Bacilli, Bacillales, Bacillaceae VC_R1 UriSelect4 agar, 37 °C L-5141 Microbacterium chocolatum 98.6 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R1 UriSelect4 agar, 37 °C L-5142 Microbacterium chocolatum 98.6 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R1 UriSelect4 agar, 37 °C 69Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5143 Acinetobacter johnsonii 98.82 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_R1 UriSelect4 agar, 37 °C L-5144 Cellulosimicrobium funkei 99.53 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R1 UriSelect4 agar, 37 °C L-5145 Microbacterium maritypicum 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R1 UriSelect4 agar, 37 °C L-5146 Brevundimonas vesicularis/ Brevundimonas nasdae 99.9 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae VC_R1 UriSelect4 agar, 37 °C L-5147 Rothia amarae 99.89 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R1 UriSelect4 agar, 37 °C L-5149 Naumannella halotolerans 100 1 Actinomycetota, Actinomycetes, Propionibacteriales, Propionibacteriaceae VC_R1 UriSelect4 agar, 37 °C L-5150 Sphingomonas panaciterrae 99.8 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae VC_R1 UriSelect4 agar, 37 °C L-5151 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_1 blood agar, 37 °C L-5153 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_1 UriSelect4 agar, 37 °C L-5154 Pseudomonas rhodesiae 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_1 UriSelect4 agar, 37 °C L-5155 Staphylococcus epidermidis 99.89 2 Firmicutes, Bacilli, Bacillales, Staphylococcaceae TC_1 UriSelect4 agar, 37 °C L-5156 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_1 UriSelect4 agar, 37 °C L-5157 Acinetobacter johnsonii 99.6 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_1 blood agar, 37 °C L-5158 Acinetobacter johnsonii 98.98 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_1 blood agar, 37 °C L-5159 Microbacterium testaceum 99.04 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_1 blood agar, 37 °C L-5160 Brevundimonas aurantiaca 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae KC_1 blood agar, 37 °C 70Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5161 Acidovorax facilis 99.44 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae KC_1 blood agar, 37 °C L-5162 Chryseobacterium shandongense 99.36 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae KC_1 blood agar, 37 °C L-5163 Acinetobacter beijerinckii 99.41 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_1 blood agar, 37 °C L-5164 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_1 UriSelect4 agar, 37 °C L-5165 Acinetobacter johnsonii 99.45 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_1 UriSelect4 agar, 37 °C L-5166 Acinetobacter johnsonii 99.32 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_1 UriSelect4 agar, 37 °C L-5167 Microbacterium testaceum 98.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_1 UriSelect4 agar, 37 °C L-5168 Brevundimonas aurantiaca 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae KC_1 UriSelect4 agar, 37 °C L-5169 Acidovorax facilis 99.42 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae KC_1 UriSelect4 agar, 37 °C L-5170 Kocuria uropygioeca/Kocuria uropygialis 100 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae KC_1 UriSelect4 agar, 37 °C L-5171 Acinetobacter beijerinckii 99.45 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae BC_1 blood agar, 37 °C L-5173 Acinetobacter beijerinckii 99.61 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae BC_1 UriSelect4 agar, 37 °C L-5174 Sphingobium hydrophobicum 99.5 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae BC_1 UriSelect4 agar, 37 °C L-5177 Sphingomonas paucimobilis 100 2 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae BC_R1 UriSelect4 agar, 37 °C L-5178 Microbacterium testaceum 99.13 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_1 blood agar, 37 °C L-5179 Brevundimonas mediterranea 99.72 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae DC_1 blood agar, 37 °C 71Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5180 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_1 blood agar, 37 °C L-5181 Kocuria uropygioeca 100 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae DC_1 blood agar, 37 °C L-5182 Brevundimonas vesicularis/ Brevundimonas nasdae 97.7 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae DC_1 blood agar, 37 °C L-5183 Acinetobacter johnsonii 99.73 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae DC_1 UriSelect4 agar, 37 °C L-5184 Microbacterium testaceum 98.24 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_1 UriSelect4 agar, 37 °C L-5185 Microbacterium testaceum 99.15 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_1 UriSelect4 agar, 37 °C L-5186 Microbacterium testaceum 99.1 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_1 UriSelect4 agar, 37 °C L-5187 Stenotrophomonas rhizophila 99.61 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae DC_R1 blood agar, 37 °C L-5188 Sphingobium hydrophobicum 99.9 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae DC_R1 blood agar, 37 °C L-5189 Stenotrophomonas chelatiphaga 99.55 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae DC_R1 blood agar, 37 °C L-5190 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R1 UriSelect4 agar, 37 °C L-5191 Sphingobium hydrophobicum 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae DC_R1 UriSelect4 agar, 37 °C L-5192 Microbacterium testaceum 99.08 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_R1 UriSelect4 agar, 37 °C L-5193 Stenotrophomonas rhizophila 99.61 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae DC_R1 UriSelect4 agar, 37 °C L-5194 Stenotrophomonas rhizophila 99.67 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae DC_R1 UriSelect4 agar, 37 °C L-5195 Microbacterium testaceum 99.17 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_R1 UriSelect4 agar, 37 °C 72Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5196 Acidovorax facilis 99.34 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R1 UriSelect4 agar, 37 °C L-5197 Sphingobium hydrophobicum 99.81 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SI_1 blood agar, 37 °C L-5198 Sphingobium hydrophobicum 99.9 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SI_1 blood agar, 37 °C L-5200 Sphingobium hydrophobicum 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SI_1 UriSelect4 agar, 37 °C L-5201 Chryseobacterium sediminis 98.17 1 Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae SI_1 blood agar, 37 °C L-5202 Rothia aeria 99.63 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae SI_1 blood agar, 37 °C L-5203 Staphylococcus warneri 99.91 1 Bacillota, Bacilli, Bacillales, Staphylococcaceae SI_1 UriSelect4 agar, 37 °C L-5204 Rothia amarae 97.99 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae SI_1 UriSelect4 agar, 37 °C L-5205 Microbacterium paraoxydans 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_1 UriSelect4 agar, 37 °C L-5207 Staphylococcus haemolyticus 99.91 2 Bacillota, Bacilli, Bacillales, Staphylococcaceae SI_1 UriSelect4 agar, 37 °C L-5208 Pseudomonas koreensis 99.63 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R1 blood agar, 37 °C L-5209 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R1 blood agar, 37 °C L-5210 Aerococcus urinaeequi 99.91 1 Bacillota, Bacilli, Bacillales, Aerococcaceae SI_R1 blood agar, 37 °C L-5211 Sphingomonas olei/ Sphingomonas panaciterrae 100 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SI_R1 blood agar, 37 °C L-5212 Pseudomonas koreensis 99.54 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R1 UriSelect4 agar, 37 °C L-5213 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R1 UriSelect4 agar, 37 °C L-5214 Brachybacterium paraconglomeratum 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Dermabacteraceae SI_R1 UriSelect4 agar, 37 °C 73Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5215 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R1 UriSelect4 agar, 37 °C L-5216 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R1 UriSelect4 agar, 37 °C L-5217 Acinetobacter johnsonii 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_1 blood agar, 37 °C L-5218 Pseudomonas koreensis 99.9 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_1 blood agar, 37 °C L-5220 Acinetobacter johnsonii 99.13 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_1 blood agar, 37 °C L-5221 Rothia amarae 98.04 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae RC_1 blood agar, 37 °C L-5222 Acinetobacter haemolyticus 99.86 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_1 blood agar, 37 °C L-5223 Microbacterium lacus 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_1 blood agar, 37 °C L-5224 Pseudomonas koreensis 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_1 UriSelect4 agar, 37 °C L-5225 Acinetobacter johnsonii 99.42 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_1 UriSelect4 agar, 37 °C L-5226 Brevundimonas diminuta 99.53 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae RC_1 UriSelect4 agar, 37 °C L-5227 Delftia lacustris 100 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_1 UriSelect4 agar, 37 °C L-5228 Acinetobacter johnsonii 99.45 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_1 UriSelect4 agar, 37 °C L-5229 Stenotrophomonas bentonitica 99.91 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae RC_1 UriSelect4 agar, 37 °C L-5230 Pseudomonas koreensis 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_1 UriSelect4 agar, 37 °C L-5231 Pseudomonas helmanticensis 99.82 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_R1 blood agar, 37 °C 74Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5232 Acinetobacter johnsonii 99.73 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R1 blood agar, 37 °C L-5234 Microbacterium paraoxydans 99.82 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R1 blood agar, 37 °C L-5235 Pseudomonas turukhanskensis 99.62 - Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_R1 blood agar, 37 °C L-5236 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R1 blood agar, 37 °C L-5238 Sphingomonas panaciterrae 99.9 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae RC_R1 blood agar, 37 °C L-5239 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R1 blood agar, 37 °C L-5240 Pseudomonas turukhanskensis 99.62 - Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_R1 blood agar, 37 °C L-5241 Tsukamurella pulmonis 100 2 Actinomycetota, Actinomycetes, Mycobacteriales, Tsukamurellaceae RC_R1 blood agar, 37 °C L-5242 Pseudomonas putida 99.2 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_R1 blood agar, 37 °C L-5243 Pseudomonas chloritidismutans 99.73 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_R1 blood agar, 37 °C L-5244 Acinetobacter johnsonii 99.72 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R1 UriSelect4 agar, 37 °C L-5245 Acinetobacter johnsonii 99.72 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R1 UriSelect4 agar, 37 °C L-5246 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R1 UriSelect4 agar, 37 °C L-5247 Acinetobacter johnsonii 99.81 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R1 UriSelect4 agar, 37 °C L-5248 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae RC_R1 UriSelect4 agar, 37 °C 75Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5249 Pseudomonas koreensis 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_R1 UriSelect4 agar, 37 °C L-5250 Stenotrophomonas maltophilia 99.54 2 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae RC_R1 UriSelect4 agar, 37 °C L-5251 Sphingomonas olei 99.81 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae RC_R1 UriSelect4 agar, 37 °C L-5252 Acinetobacter johnsonii 99.6 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R1 UriSelect4 agar, 37 °C L-5253 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae RC_R1 UriSelect4 agar, 37 °C L-5254 Brachybacterium conglomeratum 99.8 1 Actinomycetota, Actinomycetes, Actinomycetales, Dermabacteraceae RC_R1 UriSelect4 agar, 37 °C L-5255 Microbacterium paraoxydans 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R1 UriSelect4 agar, 37 °C L-5256 Acinetobacter haemolyticus 99.11 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_2 blood agar, 37 °C L-5257 Acinetobacter johnsonii 99.6 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_2 blood agar, 37 °C L-5258 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_2 blood agar, 37 °C L-5259 Stenotrophomonas maltophilia/ Pseudomonas hibiscicola 98.96 2 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae SC_2 UriSelect4 agar, 37 °C L-5260 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_2 blood agar, 37 °C L-5261 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_2 blood agar, 37 °C L-5262 Brevundimonas aurantiaca 99.91 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_2 blood agar, 37 °C L-5263 Curtobacterium oceanosedimentum 99.63 - Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SC_2 UriSelect4 agar, 37 °C L-5264 Asticcacaulis excentricus 99.62 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_2 UriSelect4 agar, 37 °C 76Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5265 Acinetobacter haemolyticus 99.26 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_2 UriSelect4 agar, 37 °C L-5266 Brevundimonas aurantiaca 99.9 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_2 UriSelect4 agar, 37 °C L-5267 Sphingomonas hankookensis 99.13 1 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae SC_2 UriSelect4 agar, 37 °C L-5268 Pantoea dispersa 99.17 1 Pseudomonadota, Gammaproteobacteria, Enterobacteriales, Erwiniaceae SC_R2 blood agar, 37 °C L-5269 Stenotrophomonas pavanii/ Stenotrophomonas maltophilia/ Pseudomonas geniculata 99.79 2 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae SC_R2 blood agar, 37 °C L-5270 Curtobacterium oceanosedimentum 99.73 - Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SC_R2 blood agar, 37 °C L-5271 Curtobacterium oceanosedimentum 99.81 - Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SC_R2 blood agar, 37 °C L-5272 Cellulomonas pakistanensis 99.89 1 Actinomycetota, Actinomycetes, Actinomycetales, Cellulomonadaceae SC_R2 blood agar, 37 °C L-5273 Pantoea dispersa 99.19 1 Pseudomonadota, Gammaproteobacteria, Enterobacteriales, Erwiniaceae SC_R2 UriSelect4 agar, 37 °C L-5274 Pantoea dispersa 99.02 1 Pseudomonadota, Gammaproteobacteria, Enterobacteriales, Erwiniaceae SC_R2 UriSelect4 agar, 37 °C L-5275 Pseudomonas oryzihabitans 99.54 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SC_R2 UriSelect4 agar, 37 °C L-5276 Curtobacterium citreum 99.43 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SC_R2 UriSelect4 agar, 37 °C L-5278 Microbacterium foliorum 99.44 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SC_R2 UriSelect4 agar, 37 °C L-5279 Acinetobacter haemolyticus 99.17 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 blood agar, 37 °C L-5280 Delftia acidovorans 99.91 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae FC_3 blood agar, 37 °C L-5281 Delftia acidovorans 99.91 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae FC_3 blood agar, 37 °C 77Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5282 Acinetobacter haemolyticus 99.23 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 blood agar, 37 °C L-5283 Acinetobacter johnsonii 99.54 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 blood agar, 37 °C L-5284 Acinetobacter haemolyticus 99.25 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 UriSelect4 agar, 37 °C L-5285 Acinetobacter johnsonii 99.72 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 UriSelect4 agar, 37 °C L-5286 Acinetobacter johnsonii 99.82 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 UriSelect4 agar, 37 °C L-5288 Microbacterium testaceum 98.99 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R3 blood agar, 37 °C L-5289 Microbacterium zeae/ Microbacterium proteolyticum 98.48 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R3 blood agar, 37 °C L-5290 Microbacterium zeae/ Microbacterium proteolyticum 98.42 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R3 blood agar, 37 °C L-5291 Brevibacterium sanguinis 99.9 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R3 blood agar, 37 °C L-5292 Pseudomonas aeruginosa 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 blood agar, 37 °C L-5293 Pseudomonas chloritidismutans 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 blood agar, 37 °C L-5294 Microbacterium zeae/ Microbacterium proteolyticum 98.42 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R3 blood agar, 37 °C L-5295 Sphingomonas koreensis 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 UriSelect4 agar, 37 °C L-5296 Acinetobacter johnsonii 99.9 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_R3 UriSelect4 agar, 37 °C L-5297 Brevibacterium sanguinis 99.72 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R3 UriSelect4 agar, 37 °C L-5298 Microbacterium zeae/ Microbacterium proteolyticum 98.61 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R3 UriSelect4 agar, 37 °C 78Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5299 Aquincola tertiaricarbonis 98.23 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_2 blood agar, 37 °C L-5300 Aquincola tertiaricarbonis 98.23 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_2 blood agar, 37 °C L-5301 Microbacterium lacus 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_2 blood agar, 37 °C L-5302 Aquincola tertiaricarbonis 98.27 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_2 UriSelect4 agar, 37 °C L-5303 Aquincola tertiaricarbonis 98.22 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_2 UriSelect4 agar, 37 °C L-5304 Aquincola tertiaricarbonis 98.23 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_2 blood agar, 37 °C L-5305 Acinetobacter johnsonii 99.81 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_2 blood agar, 37 °C L-5306 Limnobacter thiooxidans 99.53 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae UC_2 blood agar, 37 °C L-5307 Aquincola tertiaricarbonis 98.19 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_2 blood agar, 37 °C L-5308 Aquincola tertiaricarbonis 98.25 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_2 UriSelect4 agar, 37 °C L-5313 Aquincola tertiaricarbonis 98.21 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_R2 blood agar, 37 °C L-5314 Microbacterium paraoxydans 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R2 blood agar, 37 °C L-5317 Aquincola tertiaricarbonis 98.21 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_R2 blood agar, 37 °C 79Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5318 Aquincola tertiaricarbonis 98.1 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis UC_R2 UriSelect4 agar, 37 °C L-5319 Kocuria arsenatis/Kocuria rhizophila 99.71 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcaceae UC_R2 UriSelect4 agar, 37 °C L-5320 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R2 UriSelect4 agar, 37 °C L-5321 Chryseobacterium echinoideorum 99.54 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae VC_2 blood agar, 37 °C L-5322 Sphingobacterium faecium 99.11 1 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae VC_2 blood agar, 37 °C L-5323 Acinetobacter johnsonii 99.71 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_2 blood agar, 37 °C L-5324 Sphingomonas panni 100 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae VC_2 blood agar, 37 °C L-5325 Chryseobacterium hominis 99.63 2 Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae VC_2 blood agar, 37 °C L-5327 Chryseobacterium echinoideorum 99.53 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae VC_2 UriSelect4 agar, 37 °C L-5328 Chryseobacterium hominis 98.32 2 Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae VC_2 UriSelect4 agar, 37 °C L-5329 Sphingobacterium faecium 99.62 1 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae VC_2 UriSelect4 agar, 37 °C L-5330 Brevundimonas bullata 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae VC_2 UriSelect4 agar, 37 °C L-5331 Pelomonas aquatica 98.99 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae VC_2 UriSelect4 agar, 37 °C L-5332 Acinetobacter johnsonii 99.81 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_2 UriSelect4 agar, 37 °C L-5333 Microbacterium aurum 99.8 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R2 blood agar, 37 °C L-5334 Limnobacter thiooxidans 99.68 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae VC_R2 blood agar, 37 °C L-5335 Pelomonas puraquae 99.34 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae VC_R2 blood agar, 37 °C 80Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5336 Pelomonas aquatica 99.18 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae VC_R2 blood agar, 37 °C L-5337 Novosphingobium lentum 99.86 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Erythrobacteraceae VC_R2 blood agar, 37 °C L-5338 Pelomonas aquatica 99.15 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae VC_R2 blood agar, 37 °C L-5339 Pelomonas aquatica 99.01 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae VC_R2 UriSelect4 agar, 37 °C L-5340 Pelomonas aquatica 99.16 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae TC_2 blood agar, 37 °C L-5341 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 blood agar, 37 °C L-5342 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 blood agar, 37 °C L-5343 Pseudomonas xanthomarina 98.97 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 blood agar, 37 °C L-5344 Pseudomonas chloritidismutans 99.9 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 UriSelect4 agar, 37 °C L-5345 Pseudomonas xanthomarina 98.97 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 UriSelect4 agar, 37 °C L-5346 Pseudomonas rhodesiae 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 UriSelect4 agar, 37 °C L-5347 Staphylococcus hominis 99.9 2 Bacillota, Bacilli, Bacillales, Staphylococcaceae TC_2 UriSelect4 agar, 37 °C L-5348 Pseudomonas chloritidismutans 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 UriSelect4 agar, 37 °C 81Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5349 Pseudomonas zhaodongensis 99.48 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 blood agar, 37 °C L-5350 Pseudomonas knackmussii 99.9 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 blood agar, 37 °C L-5351 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 blood agar, 37 °C L-5352 Pelomonas aquatica 99.16 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae TC_2 blood agar, 37 °C L-5353 Pelomonas aquatica 96.94 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae TC_2 UriSelect4 agar, 37 °C L-5354 Pseudomonas xanthomarina 98.97 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_2 UriSelect4 agar, 37 °C L-5355 Microbacterium testaceum 98.98 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_2 blood agar, 37 °C L-5356 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_2 blood agar, 37 °C L-5357 Pelomonas aquatica 99.07 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_2 blood agar, 37 °C L-5358 Microbacterium testaceum 99.08 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_2 blood agar, 37 °C L-5359 Pelomonas aquatica 99.15 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_2 UriSelect4 agar, 37 °C L-5360 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_2 UriSelect4 agar, 37 °C L-5361 Sphingobium hydrophobicum 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae DC_2 UriSelect4 agar, 37 °C L-5362 Microbacterium testaceum 99.11 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_2 UriSelect4 agar, 37 °C L-5363 Staphylococcus warneri 100 1 Bacillota, Bacilli, Bacillales, Staphylococcaceae DC_2 blood agar, 37 °C 82Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5364 Citrobacter freundii 99.24 2 Pseudomonadota, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae DC_2 blood agar, 37 °C L-5365 Pelomonas aquatica 99.15 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_2 blood agar, 37 °C L-5366 Pelomonas aquatica 99.08 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_2 UriSelect4 agar, 37 °C L-5367 Microbacterium testaceum 99.08 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_2 UriSelect4 agar, 37 °C L-5368 Acinetobacter johnsonii 99.81 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae DC_2 UriSelect4 agar, 37 °C L-5369 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R2 blood agar, 37 °C L-5370 Sphingobium hydrophobicum 100 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae DC_R2 blood agar, 37 °C L-5371 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R2 UriSelect4 agar, 37 °C L-5372 Sphingobium hydrophobicum 99.9 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae DC_R2 UriSelect4 agar, 37 °C L-5373 Sphingobium hydrophobicum 99.81 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae DC_R2 UriSelect4 agar, 37 °C L-5374 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_R2 blood agar, 37 °C L-5375 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R2 blood agar, 37 °C L-5376 Microbacterium maritypicum 99.9 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_R2 blood agar, 37 °C L-5377 Pelomonas aquatica 99.23 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R2 blood agar, 37 °C L-5378 Acidovorax facilis 99.44 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R2 blood agar, 37 °C 83Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5379 Pelomonas aquatica 99.08 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R2 blood agar, 37 °C L-5380 Stenotrophomonas rhizophila 99.62 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae DC_R2 blood agar, 37 °C L-5381 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R2 blood agar, 37 °C L-5382 Pelomonas aquatica 99.04 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R2 UriSelect4 agar, 37 °C L-5383 Pelomonas aquatica 99.15 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R2 UriSelect4 agar, 37 °C L-5384 Stenotrophomonas rhizophila 99.63 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae DC_R2 UriSelect4 agar, 37 °C L-5386 Pelomonas puraquae 99.26 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R2 UriSelect4 agar, 37 °C L-5387 Pseudomonas rhodesiae 99.82 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_2 blood agar, 37 °C L-5388 Pseudomonas koreensis 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_2 blood agar, 37 °C L-5390 Pseudomonas oryzihabitans 99.45 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_2 blood agar, 37 °C L-5391 Acinetobacter johnsonii 99.45 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_2 blood agar, 37 °C L-5392 Pelomonas puraquae 98.46 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae KC_2 UriSelect4 agar, 37 °C L-5393 Pelomonas aquatica 99.17 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae KC_2 UriSelect4 agar, 37 °C L-5394 Pseudomonas koreensis 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_2 UriSelect4 agar, 37 °C 84Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5395 Pelomonas aquatica 97.36 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae KC_2 UriSelect4 agar, 37 °C L-5396 Pelomonas puraquae 99.21 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae KC_2 blood agar, 37 °C L-5397 Acinetobacter lwoffii 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_2 UriSelect4 agar, 37 °C L-5398 Chryseobacterium shandongense 99.36 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae KC_R2 UriSelect4 agar, 37 °C L-5399 Chryseobacterium shandongense 99.36 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae KC_R2 UriSelect4 agar, 37 °C L-5400 Chryseobacterium shandongense 99.38 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae KC_R2 blood agar, 37 °C L-5401 Acinetobacter lwoffii 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_R2 blood agar, 37 °C L-5402 Pelomonas aquatica 98.89 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae KC_R2 blood agar, 37 °C L-5403 Microbacterium maritypicum 99.71 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_R2 UriSelect4 agar, 37 °C L-5404 Microbacterium hominis 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_2 blood agar, 37 °C L-5405 Acinetobacter johnsonii 99.73 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_2 blood agar, 37 °C L-5408 Pelomonas aquatica 99.01 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_2 blood agar, 37 °C L-5409 Pelomonas aquatica 98.77 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_2 UriSelect4 agar, 37 °C L-5411 Pseudomonas koreensis 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_2 UriSelect4 agar, 37 °C L-5412 Staphylococcus lentus 100 1 Bacillota, Bacilli, Bacillales, Staphylococcaceae RC_2 UriSelect4 agar, 37 °C L-5413 Pelomonas aquatica 99.17 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_2 UriSelect4 agar, 37 °C L-5414 Staphylococcus warneri 99.91 1 Bacillota, Bacilli, Bacillales, Staphylococcaceae RC_2 UriSelect4 agar, 37 °C L-5416 Pelomonas puraquae 99.23 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_2 UriSelect4 agar, 37 °C 85Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5417 Acinetobacter johnsonii 99.9 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_2 UriSelect4 agar, 37 °C L-5418 Sphingomonas panni 99.81 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SI_2 blood agar, 37 °C L-5419 Pseudomonas koreensis 99.62 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_2 blood agar, 37 °C L-5421 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SI_2 UriSelect4 agar, 37 °C L-5422 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SI_2 UriSelect4 agar, 37 °C L-5423 Microbacterium maritypicum 99.73 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R2 blood agar, 37 °C L-5424 Pseudomonas koreensis 99.8 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R2 UriSelect4 agar, 37 °C L-5425 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R2 UriSelect4 agar, 37 °C L-5426 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R2 blood agar, 37 °C L-5427 Pseudomonas baetica 99.35 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R2 blood agar, 37 °C L-5428 Microbacterium maritypicum 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R2 blood agar, 37 °C L-5429 Pseudomonas baetica 99.42 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R2 blood agar, 37 °C L-5430 Microbacterium maritypicum 99.63 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R2 blood agar, 37 °C L-5431 Pseudomonas koreensis 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R2 UriSelect4 agar, 37 °C L-5432 Microbacterium maritypicum 99.79 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R2 UriSelect4 agar, 37 °C L-5433 Microbacterium maritypicum 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R2 UriSelect4 agar, 37 °C 86Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5434 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae BC_2 blood agar, 37 °C L-5435 Brevundimonas mediterranea 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae BC_2 blood agar, 37 °C L-5436 Staphylococcus warneri 100 1 Bacillota, Bacilli, Bacillales, Staphylococcaceae BC_2 UriSelect4 agar, 37 °C L-5437 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae BC_2 UriSelect4 agar, 37 °C L-5438 Streptococcus mitis 88.36 2 Bacillota, Bacilli, Lactobacillales, Streptococcaceae BC_2 blood agar, 37 °C L-5439 Rothia mucilaginosa 99.27 2 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae BC_2 UriSelect4 agar, 37 °C L-5440 Acinetobacter parvus 99.63 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae Tap water blood agar, 37 °C L-5441 Methylorubrum populi/ Methylorubrum thiocyanatum 99.81 1 Pseudomonadota, Alphaproteobacteria, Hyphomicrobiales, Methylobacteriaceae Tap water blood agar, 37 °C L-5442 Sphingopyxis alaskensis 100 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae Tap water blood agar, 37 °C L-5443 Ottowia shaoguanensis 96.96 - Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae Tap water blood agar, 37 °C L-5444 Pseudomonas peli 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae Tap water blood agar, 37 °C L-5445 Sphingopyxis alaskensis 100 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae Tap water blood agar, 37 °C L-5446 Methylorubrum populi/ Methylorubrum thiocyanatum 99.79 1 Pseudomonadota, Alphaproteobacteria, Rhizobiales, Methylobacteriaceae Tap water UriSelect4 agar, 37 °C L-5464 Massilia varians 99.72 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae VC_3 blood agar, 37 °C L-5465 Acinetobacter johnsonii 99.35 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_3 blood agar, 37 °C 87Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5466 Acinetobacter johnsonii 99.29 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_3 blood agar, 37 °C L-5467 Pseudomonas oryzihabitans 99.45 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae VC_3 blood agar, 37 °C L-5469 Sphingobacterium multivorum 99.9 2 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae VC_3 UriSelect4 agar, 37 °C L-5470 Acinetobacter johnsonii 99.53 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_3 UriSelect4 agar, 37 °C L-5471 Sphingobacterium multivorum 99.91 2 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae VC_3 UriSelect4 agar, 37 °C L-5472 Massilia varians 99.73 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae VC_3 UriSelect4 agar, 37 °C L-5473 Acinetobacter johnsonii 98.26 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_3 UriSelect4 agar, 37 °C L-5474 Pseudomonas putida 99.91 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae VC_3 UriSelect4 agar, 37 °C L-5475 Acinetobacter johnsonii 99.46 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_3 UriSelect4 agar, 37 °C L-5476 Sphingomonas olei 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae VC_3 blood agar, 37 °C L-5477 Sphingobacterium hotanense 99.9 1 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae VC_3 UriSelect4 agar, 37 °C L-5478 Pseudomonas plecoglossicida 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae VC_3 UriSelect4 agar, 37 °C L-5479 Limnobacter thiooxidans 99.72 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae VC_R3 blood agar, 37 °C L-5480 Limnobacter thiooxidans 99.61 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae VC_R3 blood agar, 37 °C L-5481 Barrientosiimonas humi 99.9 1 Actinomycetota, Actinomycetes, Actinomycetales, Dermacoccaceae VC_R3 blood agar, 37 °C 88Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5482 Cellulosimicrobium funkei 99.51 1 Actinomycetota, Actinomycetes, Micrococcales, Promicromonosporaceae VC_R3 blood agar, 37 °C L-5483 Microbacterium paraoxydans 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae VC_R3 UriSelect4 agar, 37 °C L-5484 Cellulosimicrobium funkei 99.9 1 Actinomycetota, Actinomycetes, Micrococcales, Promicromonosporaceae VC_R3 UriSelect4 agar, 37 °C L-5485 Epidermidibacterium keratini 100 - Actinomycetota, Actinomycetes, Geodermatophilales, Antricoccaceae VC_R3 UriSelect4 agar, 37 °C L-5486 Pseudomonas chloritidismutans 99.9 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_3 UriSelect4 agar, 37 °C L-5487 Sphingobacterium cellulitidis 100 1 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae TC_3 UriSelect4 agar, 37 °C L-5488 Sphingobacterium multivorum 100 2 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae TC_3 UriSelect4 agar, 37 °C L-5489 Pseudoxanthomonas japonensis 100 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae TC_3 UriSelect4 agar, 37 °C L-5490 Acinetobacter johnsonii 99.73 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae TC_3 UriSelect4 agar, 37 °C L-5491 Pseudomonas chloritidismutans 99.82 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_3 UriSelect4 agar, 37 °C L-5492 Brevundimonas olei 100 - Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae TC_3 UriSelect4 agar, 37 °C L-5493 Pseudomonas chloritidismutans 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_3 blood agar, 37 °C L-5494 Enterobacter cloacae 100 2 Pseudomonadota, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae TC_3 blood agar, 37 °C L-5495 Tsukamurella tyrosinosolvens 100 2 Actinomycetota, Actinomycetes, Mycobacteriales, Tsukamurellaceae TC_3 blood agar, 37 °C L-5496 Pseudomonas chloritidismutans 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_3 blood agar, 37 °C 89Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5497 Brachybacterium paraconglomeratum 99.89 1 Actinomycetota, Actinomycetes, Micrococcales, Dermabacteraceae TC_3 blood agar, 37 °C L-5498 Sphingobacterium cellulitidis 100 1 Bacteroidota, Sphingobacteriia, Sphingobacteriales, Sphingobacteriaceae TC_3 blood agar, 37 °C L-5500 Pseudomonas chloritidismutans 99.81 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae TC_3 UriSelect4 agar, 37 °C L-5501 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_3 UriSelect4 agar, 37 °C L-5502 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_3 UriSelect4 agar, 37 °C L-5503 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_3 blood agar, 37 °C L-5504 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_3 blood agar, 37 °C L-5505 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R3 blood agar, 37 °C L-5506 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R3 blood agar, 37 °C L-5507 Acidovorax temperans 99.64 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae DC_R3 blood agar, 37 °C L-5508 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_R3 blood agar, 37 °C L-5509 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R3 UriSelect4 agar, 37 °C L-5510 Microbacterium maritypicum 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae DC_R3 UriSelect4 agar, 37 °C L-5511 Pseudomonas baetica 99.28 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae DC_R3 UriSelect4 agar, 37 °C 90Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5513 Brevundimonas aurantiaca 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae KC_3 blood agar, 37 °C L-5514 Microbacterium testaceum 99.14 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_3 blood agar, 37 °C L-5515 Microbacterium hatanonis 99.44 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_3 blood agar, 37 °C L-5516 Microbacterium chocolatum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_3 blood agar, 37 °C L-5517 Microbacterium chocolatum 99.9 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_3 blood agar, 37 °C L-5518 Microbacterium testaceum 99.17 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_3 UriSelect4 agar, 37 °C L-5519 Acinetobacter lwoffii 99.71 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_3 UriSelect4 agar, 37 °C L-5520 Brevundimonas bullata 100 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae KC_3 UriSelect4 agar, 37 °C L-5521 Pseudomonas chloritidismutans 99.8 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_3 blood agar, 37 °C L-5522 Acinetobacter lwoffii 99.9 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_3 blood agar, 37 °C L-5523 Acinetobacter johnsonii 99.54 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_3 blood agar, 37 °C L-5525 Pseudomonas rhodesiae 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_3 blood agar, 37 °C L-5526 Acinetobacter johnsonii 99.48 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae KC_3 UriSelect4 agar, 37 °C L-5527 Pseudomonas koreensis 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae KC_3 UriSelect4 agar, 37 °C L-5528 Chryseobacterium shandongense 99.36 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae KC_R3 blood agar, 37 °C L-5530 Micrococcus aloeverae 99.79 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae KC_R3 blood agar, 37 °C L-5531 Staphylococcus epidermidis 99.82 2 Bacillota, Bacilli, Bacillales, Staphylococcaceae KC_R3 blood agar, 37 °C L-5532 Chryseobacterium shandongense 99.36 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae KC_R3 UriSelect4 agar, 37 °C 91Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5533 Micrococcus yunnanensis 99.68 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae KC_R3 UriSelect4 agar, 37 °C L-5534 Acinetobacter haemolyticus 99.04 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_3 blood agar, 37 °C L-5535 Sphingomonas panni 100 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_3 blood agar, 37 °C L-5537 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_3 blood agar, 37 °C L-5538 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_3 UriSelect4 agar, 37 °C L-5539 Acinetobacter haemolyticus 99.18 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_3 UriSelect4 agar, 37 °C L-5540 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_3 UriSelect4 agar, 37 °C L-5541 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_3 UriSelect4 agar, 37 °C L-5542 Sphingomonas hankookensis 99.42 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_3 UriSelect4 agar, 37 °C L-5543 Acinetobacter haemolyticus 99.12 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_3 UriSelect4 agar, 37 °C L-5544 Staphylococcus warneri 99.91 1 Bacillota, Bacilli, Bacillales, Staphylococcaceae SC_3 blood agar, 37 °C L-5545 Acinetobacter haemolyticus 99.27 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SC_3 blood agar, 37 °C L-5547 Sphingomonas panni 99.82 1 Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SC_R3 blood agar, 37 °C L-5548 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_R3 blood agar, 37 °C L-5550 Acidovorax temperans 99.65 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae SC_R3 UriSelect4 agar, 37 °C 92Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5551 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae SC_R3 UriSelect4 agar, 37 °C L-5552 Acinetobacter haemolyticus 99.26 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 blood agar, 37 °C L-5553 Rothia kristinae 99.63 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_3 blood agar, 37 °C L-5554 Acinetobacter johnsonii 99.9 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 blood agar, 37 °C L-5556 Acinetobacter haemolyticus 99.2 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 UriSelect4 agar, 37 °C L-5557 Rothia amarae 99.9 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae FC_3 UriSelect4 agar, 37 °C L-5559 Acinetobacter haemolyticus 99.12 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae FC_3 UriSelect4 agar, 37 °C L-5560 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 blood agar, 37 °C L-5561 Microbacterium zeae 98.63 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R3 blood agar, 37 °C L-5562 Microbacterium lacus 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae FC_R3 blood agar, 37 °C L-5563 Brevibacterium sanguinis 99.71 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R3 blood agar, 37 °C L-5564 Brevibacterium sanguinis 99.72 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R3 UriSelect4 agar, 37 °C L-5565 Pseudomonas alcaligenes 98.79 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 UriSelect4 agar, 37 °C L-5566 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 UriSelect4 agar, 37 °C L-5567 Stenotrophomonas maltophilia 99.91 2 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae FC_R3 blood agar, 37 °C L-5568 Rhodococcus corynebacterioides 99.81 1 Actinomycetota, Actinomycetes, Mycobacteriales, Nocardiaceae FC_R3 blood agar, 37 °C L-5569 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 blood agar, 37 °C 93Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5570 Brevibacterium sanguinis/ Brevibacterium celere/ Brevibacterium antiquum/ Brevibacterium aurantiacum/ Brevibacterium casei 100 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R3 blood agar, 37 °C L-5571 Pseudomonas peli 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae FC_R3 UriSelect4 agar, 37 °C L-5572 Brevibacterium sanguinis 99.7 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae FC_R3 UriSelect4 agar, 37 °C L-5573 Brevundimonas mediterranea 99.91 1 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae BC_3 blood agar, 37 °C L-5574 Aquincola tertiaricarbonis 98.24 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis BC_3 blood agar, 37 °C L-5575 Brevundimonas vesicularis/ Brevundimonas nasdae 99.91 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae BC_3 blood agar, 37 °C L-5576 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae BC_3 UriSelect4 agar, 37 °C L-5577 Acinetobacter lwoffii 99.48 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_3 blood agar, 37 °C L-5578 Acinetobacter johnsonii 99.91 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_3 blood agar, 37 °C L-5579 Microbacterium paraoxydans 99.52 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_3 blood agar, 37 °C L-5580 Aeromonas media 99.79 1 Pseudomonadota, Gammaproteobacteria, Aeromonadales, Aeromonadaceae RC_3 blood agar, 37 °C L-5581 Pseudomonas plecoglossicida 99.72 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_3 blood agar, 37 °C L-5582 Tsukamurella pulmonis 100 2 Actinomycetota, Actinomycetes, Mycobacteriales, Tsukamurellaceae RC_3 blood agar, 37 °C L-5583 Microbacterium foliorum 99.53 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_3 blood agar, 37 °C L-5584 Acinetobacter lwoffii 99.53 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_3 blood agar, 37 °C 94Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5585 Delftia lacustris 99.91 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_3 UriSelect4 agar, 37 °C L-5586 Acinetobacter johnsonii 99.31 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_3 UriSelect4 agar, 37 °C L-5587 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_3 UriSelect4 agar, 37 °C L-5588 Microbacterium paraoxydans 99.82 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_3 UriSelect4 agar, 37 °C L-5589 Acinetobacter johnsonii 99.01 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_3 UriSelect4 agar, 37 °C L-5591 Microbacterium schleiferi 99.16 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_3 blood agar, 37 °C L-5592 Micrococcus yunnanensis 99.72 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_3 UriSelect4 agar, 37 °C L-5593 Delftia lacustris 100 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_3 UriSelect4 agar, 37 °C L-5594 Aeromonas salmonicida/ Aeromonas piscicola/ Aeromonas bestiarum 99.91 1 Pseudomonadota, Gammaproteobacteria, Aeromonadales, Aeromonadaceae RC_3 UriSelect4 agar, 37 °C L-5595 Acidovorax soli 98.6 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_R3 blood agar, 37 °C L-5596 Microbacterium phyllosphaerae 99.72 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R3 blood agar, 37 °C L-5597 Microbacterium maritypicum 99.82 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R3 blood agar, 37 °C L-5598 Exiguobacterium mexicanum 99.82 1 Bacillota, Bacilli, Bacillales, Bacillales Incertae Sedis XII RC_R3 blood agar, 37 °C L-5599 Acinetobacter johnsonii 99.37 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R3 blood agar, 37 °C L-5600 Acinetobacter johnsonii 99.43 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R3 blood agar, 37 °C L-5601 Acinetobacter lwoffii 99.65 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R3 blood agar, 37 °C L-5602 Brevibacterium casei 99.52 2 Actinomycetota, Actinomycetes, Micrococcales, Brevibacteriaceae RC_R3 UriSelect4 agar, 37 °C L-5603 Sphingomonas panaciterrae 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae RC_R3 UriSelect4 agar, 37 °C 95Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5604 Acidovorax soli 98.63 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_R3 UriSelect4 agar, 37 °C L-5605 Neomicrococcus aestuarii 99.9 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae RC_R3 UriSelect4 agar, 37 °C L-5606 Acinetobacter johnsonii 99.71 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R3 UriSelect4 agar, 37 °C L-5607 Acinetobacter lwoffii 99.81 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae RC_R3 UriSelect4 agar, 37 °C L-5608 Microbacterium maritypicum 99.82 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R3 UriSelect4 agar, 37 °C L-5609 Microbacterium maritypicum 100 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R3 UriSelect4 agar, 37 °C L-5610 Microbacterium paraoxydans 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae RC_R3 UriSelect4 agar, 37 °C L-5611 Comamonas testosteroni 99.64 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae RC_R3 blood agar, 37 °C L-5612 Pseudomonas oryzihabitans 99.45 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae RC_R3 blood agar, 37 °C L-5613 Acinetobacter lwoffii 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_3 blood agar, 37 °C L-5614 Massilia varians 99.6 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae UC_3 blood agar, 37 °C L-5615 Microbacterium maritypicum 99.73 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_3 blood agar, 37 °C L-5616 Pseudomonas peli 98.82 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_3 blood agar, 37 °C L-5617 Acinetobacter lwoffii 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_3 blood agar, 37 °C L-5618 Rothia amarae 97.99 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae UC_3 UriSelect4 agar, 37 °C L-5619 Sphingomonas olei 99.82 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae UC_3 UriSelect4 agar, 37 °C L-5620 Massilia varians 99.79 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae UC_3 UriSelect4 agar, 37 °C 96Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5621 Pseudomonas pseudoalcaligenes 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_3 UriSelect4 agar, 37 °C L-5622 Massilia timonae 99.89 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae UC_3 UriSelect4 agar, 37 °C L-5623 Acinetobacter lwoffii 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_3 UriSelect4 agar, 37 °C L-5624 Pseudomonas stutzeri 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_3 blood agar, 37 °C L-5625 Sphingomonas olei/ Sphingomonas panaciterrae 99.9 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae UC_3 blood agar, 37 °C L-5626 Massilia timonae 99.89 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae UC_3 blood agar, 37 °C L-5627 Rothia terrae 99.26 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae UC_3 UriSelect4 agar, 37 °C L-5628 Pseudomonas oryzihabitans/ Pseudomonas psychrotolerans 99.53 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_3 UriSelect4 agar, 37 °C L-5629 Microbacterium maritypicum 99.91 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_3 UriSelect4 agar, 37 °C L-5630 Acinetobacter lwoffii 99.8 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_3 UriSelect4 agar, 37 °C L-5631 Massilia varians 99.79 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae UC_3 UriSelect4 agar, 37 °C L-5633 Pseudomonas peli 99.07 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_R3 blood agar, 37 °C L-5634 Sphingomonas olei 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae UC_R3 blood agar, 37 °C L-5635 Acinetobacter lwoffii 100 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_R3 blood agar, 37 °C 97Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5636 Pseudomonas peli 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_R3 blood agar, 37 °C L-5637 Brevundimonas vesicularis/ Brevundimonas nasdae 100 2 Pseudomonadota, Alphaproteobacteria, Caulobacterales, Caulobacteraceae UC_R3 blood agar, 37 °C L-5638 Sphingomonas olei/ Sphingomonas panaciterrae 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae UC_R3 UriSelect4 agar, 37 °C L-5639 Pseudomonas peli 100 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_R3 UriSelect4 agar, 37 °C L-5640 Acinetobacter schindleri 98.68 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_R3 UriSelect4 agar, 37 °C L-5643 Acinetobacter lwoffii 99.91 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae UC_R3 blood agar, 37 °C L-5644 Sphingomonas olei/ Sphingomonas panaciterrae 99.9 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae UC_R3 blood agar, 37 °C L-5645 Pseudomonas koreensis 99.91 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae UC_R3 UriSelect4 agar, 37 °C L-5646 Rothia terrae 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae UC_R3 UriSelect4 agar, 37 °C L-5647 Rothia terrae 99.72 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae UC_R3 UriSelect4 agar, 37 °C L-5648 Microbacterium maritypicum 99.81 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae UC_R3 UriSelect4 agar, 37 °C L-5649 Limnobacter thiooxidans 99.7 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiaceae UC_R3 UriSelect4 agar, 37 °C L-5650 Rothia kristinae 99.54 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae UC_R3 UriSelect4 agar, 37 °C L-5651 Hydrogenophaga palleronii 99.91 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Comamonadaceae SI_3 blood agar, 37 °C L-5653 Sphingobium hydrophobicum 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SI_3 blood agar, 37 °C 98Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5654 Sphingomonas olei/ Sphingomonas panaciterrae 99.91 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae SI_3 blood agar, 37 °C L-5655 Aquincola tertiaricarbonis 98.15 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis SI_3 blood agar, 37 °C L-5656 Acinetobacter lwoffii 99.82 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SI_3 blood agar, 37 °C L-5657 Pseudomonas koreensis 99.72 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_3 blood agar, 37 °C L-5658 Aquincola tertiaricarbonis 98.2 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Burkholderiales incertae sedis SI_3 UriSelect4 agar, 37 °C L-5659 Chryseobacterium shandongense 99.27 - Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae SI_3 UriSelect4 agar, 37 °C L-5660 Pseudomonas koreensis 99.55 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_3 UriSelect4 agar, 37 °C L-5661 Acinetobacter johnsonii 99.72 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SI_3 UriSelect4 agar, 37 °C L-5662 Chryseobacterium aquaticum 99.63 1 Bacteroidota, Flavobacteriia, Flavobacteriales, Weeksellaceae SI_3 UriSelect4 agar, 37 °C L-5663 Acinetobacter beijerinckii 99.37 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SI_3 blood agar, 37 °C L-5667 Pseudomonas koreensis 99.72 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_3 UriSelect4 agar, 37 °C L-5668 Rothia amarae 97.9 1 Actinomycetota, Actinomycetes, Micrococcales, Micrococcineae SI_3 UriSelect4 agar, 37 °C L-5671 Acinetobacter johnsonii 99.3 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SI_R3 blood agar, 37 °C L-5672 Microbacterium maritypicum 99.89 1 Actinomycetota, Actinomycetes, Micrococcales, Microbacteriaceae SI_R3 blood agar, 37 °C L-5673 Acinetobacter johnsonii 99.37 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae SI_R3 blood agar, 37 °C 99Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5675 Massilia varians 99.34 1 Pseudomonadota, Betaproteobacteria, Burkholderiales, Oxalobacteraceae SI_R3 UriSelect4 agar, 37 °C L-5676 Stenotrophomonas rhizophila 99.63 1 Pseudomonadota, Gammaproteobacteria, Lysobacterales, Lysobacteraceae SI_R3 UriSelect4 agar, 37 °C L-5677 Pseudomonas rhodesiae 99.82 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R3 UriSelect4 agar, 37 °C L-5678 Bacillus aryabhattai 99.9 1 Bacillota, Bacilli,Bacillales, Bacillaceae SI_R3 UriSelect4 agar, 37 °C L-5680 Serratia quinivorans 99.53 1 Pseudomonadota, Gammaproteobacteria, Enterobacteriales, Yersiniaceae SI_R3 UriSelect4 agar, 37 °C L-5681 Pseudomonas rhodesiae 99.73 1 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Pseudomonadaceae SI_R3 blood agar, 37 °C L-5682 Acinetobacter johnsonii 99.24 2 Pseudomonadota, Gammaproteobacteria, Pseudomonadales, Moraxellaceae VC_3 UriSelect4 agar, 37 °C L-5683 Sphingobium hydrophobicum 99.81 - Pseudomonadota, Alphaproteobacteria, Sphingomonadales, Sphingomonadaceae DC_3 blood agar, 37 °C 100Acta Biologica Slovenica, 2022, 65 (2), 42–103 Table S2: List of the isolates selected for the antimicrobial susceptibility testing with the corresponding antimicrobial profile. + indicates resistance; - indicates susceptibility. Ampicillin (AMP) 100 mg/l; Chloramphenicol (CHL) 25 mg/l; Cefotaxime (CTX) 2 mg/l; Colistin (COL) 3.5 mg/l; Enrofloxacin (ENR) 0.5 mg/l; Erythromycin (ERY) 15 mg/l; Imipenem (IPM) 4 mg/l; Kanamycin (KAN) 50 mg/l); Tetracycline (TET) 10 mg/l. Tabela S2: Seznam izolatov, izbranih za testiranje odpornosti proti antibiotikom, s protimikrobnim profilom. + označuje odpornost; - označuje občutljivost. Mycosmo culture collection No. (EXB) Bacterial strain AMP 100 mg/l TET 12,5 mg/l IPM 4 mg/l ERY 15 mg/l CHL 25 mg/l KAN 50 mg/l CTX 2 mg/l ENR 0.5 mg/l COL 3.5 mg/l LB L-5122 Acinetobacter beijerinckii - - - - - - - - + + L-5171 Acinetobacter beijerinckii - - - - - - - - + + L-5091 Acinetobacter haemolyticus - - - - - - + - + + L-5256 Acinetobacter haemolyticus - - - - - - + - + + L-5279 Acinetobacter haemolyticus - - - - - - + - + + L-5539 Acinetobacter haemolyticus - - - - - - + - + + L-5559 Acinetobacter haemolyticus - - - - - - + - + + L-5094 Acinetobacter johnsonii - - - - - - + - - + L-5125 Acinetobacter johnsonii - - - - - - + - - + L-5165 Acinetobacter johnsonii - - - + - - + + + + L-5183 Acinetobacter johnsonii - - - - - - + - - + L-5217 Acinetobacter johnsonii - - - - - - + - - + L-5232 Acinetobacter johnsonii - - - - - - + - - + L-5286 Acinetobacter johnsonii - - - - - - + - - + L-5296 Acinetobacter johnsonii - - - - - - + - - + L-5470 Acinetobacter johnsonii - - - - - - + - - + L-5523 Acinetobacter johnsonii - - - - - - + - - + L-5578 Acinetobacter johnsonii - - - - - - + - - + L-5522 Acinetobacter lwoffii - - - - - - - - - + L-5577 Acinetobacter lwoffii - - - - - - + - - + L-5397 Acinetobacter lwoffii/Prolinoborus fasciculus - - - - - - + - - + L-5401 Acinetobacter lwoffii/Prolinoborus fasciculus - - - - - - + - - + L-5072 Brevibacterium casei - - - - + - + + + + 101Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5563 Brevibacterium sanguinis - - - - - - - - + + L-5032 Brevundimonas aurantiaca - - - - - - + + + + L-5168 Brevundimonas aurantiaca - - - - - + + - + + L-5266 Brevundimonas aurantiaca - - - - - - + + + + L-5226 Brevundimonas diminuta - - - - - - + + + + L-5081 Brevundimonas mediterranea - - - - - - + - + + L-5179 Brevundimonas mediterranea - - - - - - + - + + L-5492 Brevundimonas olei - - - - - - + + + + L-5050 Brevundimonas vesicularis/ Brevundimonas nasdae - - - - - - - - + + L-5083 Brevundimonas vesicularis/ Brevundimonas nasdae - - - - - - - - + + L-5182 Brevundimonas vesicularis/ Brevundimonas nasdae - - - - - - - - + + L-5421 Brevundimonas vesicularis/ Brevundimonas nasdae - - - - - - + - + + L-5321 Chryseobacterium echinoideorum - - - - - + + - + + L-5201 Chryseobacterium sediminis + + + - - + + - + + L-5071 Chryseobacterium shandongense - - - - - + + - + + L-5398 Chryseobacterium shandongense - - - - - + - - + + L-5364 Citrobacter freundii - - - + - - - - - + L-5593 Delftia lacustris + - - + - - - - + + L-5494 Enterobacter cloacae - - - + - - - - + + L-5108 Enterococcus silesiacus/ Enterococcus caccae/ Enterococcus ureilyticus - - - - - - + + + + L-5029 Kocuria arsenatis/Kocuria rhizophila - - - - - - - + + + L-5114 Kocuria carniphila - - - - - - - + + + L-5129 Kocuria carniphila - - - - - - - - + + 102Acta Biologica Slovenica, 2022, 65 (2), 42–103 L-5181 Kocuria uropygioeca - - - - - - - + + + L-5223 Microbacterium lacus - - - - - - - - - + L-5587 Microbacterium maritypicum - - - + - - - - + + L-5205 Microbacterium paraoxydans - - - + - + + - + + L-5483 Microbacterium paraoxydans - - - + - + + - + + L-5579 Microbacterium paraoxydans - - - - - - + - + + L-5099 Microbacterium testaceum - - - - - - - + + + L-5268 Pantoea dispersa - - - + - - - - - + L-5292 Pseudomonas aeruginosa + + + + + + + - - + L-5565 Pseudomonas alcaligenes + - + + - - + - - + L-5243 Pseudomonas chloritidismutans - - - - - - - - - + L-5293 Pseudomonas chloritidismutans - - - - - - - - - + L-5344 Pseudomonas chloritidismutans - - - - - - - - - + L-5521 Pseudomonas chloritidismutans - - - - - - - - - + L-5527 Pseudomonas koreensis + - - + + - + - - + L-5275 Pseudomonas oryzihabitans - - - - - - - - - + L-5390 Pseudomonas oryzihabitans - - - + - - + + - + L-5467 Pseudomonas oryzihabitans - - - + - - + - - + L-5242 Pseudomonas putida - - - + - - + - - + L-5474 Pseudomonas putida + - - + - - + - - + L-5055 Rothia amarae - - - - - - - + + + L-5204 Rothia amarae - - - - - - - + + + L-5049 Rothia kristinae - - - - - - - + + + L-5553 Rothia kristinae - - - - - - - + + + L-5487 Sphingobacterium cellulitidis - - - - - + + - + + 103Turk et al.: Aerobic bacteria in holy water from Catholic churches L-5469 Sphingobacterium multivorum - - - - - - - + + + L-5488 Sphingobacterium multivorum - - + - - + + - + + L-5177 Sphingomonas paucimobilis - - - - - - - - + + L-5531 Staphylococcus epidermidis - - - + - - - - + + L-5057 Staphylococcus haemolyticus - - - - - - - - + + L-5207 Staphylococcus haemolyticus - - - + - - - - + + L-5412 Staphylococcus lentus - - - - - - + - + + L-5028 Staphylococcus lugdunensis - - - - - - - - + + L-5076 Stenotrophomonas maltophilia - - + + - + + - - + L-5250 Stenotrophomonas maltophilia + - + + - + + - + + L-5259 Stenotrophomonas maltophilia/ Pseudomonas hibiscicola - - + + - + + - - + L-5269 Stenotrophomonas pavanii/ Stenotrophomonas maltophilia + - + + - + + + + + ACTA BIOLOGICA SLOVENICA LJUBLJANA 2022 Vol. 65, Št. 2: 104–115 Phylogenetic study of Aliinostoc species (Cyanobacteria) using pc-igs, nifH and mcy as markers for investigation of horizontal gene transfer Filogenetska študija vrst Aliinostoc (Cyanobacteria) z uporabo označevalcev pc-igs, nifH in mcy za ugotavljanje horizontalnega genskega prenosa Bahareh Nowruzi Department of Biotechnology, Science and Research Branch, Islamic Azad University, Tehran, Iran. Correspondence: bahare77biol@gmail.com Abstract: Selection of genes that have not been horizontally transferred for prokary- ote phylogenetic studies is regarded as a challenging task. Internal transcribed spacer of ribosomal genes (16S–23S ITS), microcystin synthetase genes (mcy), nitrogenase (nifH) and phycocyanin intergenic spacer (PC-IGS) are among the most used markers in cyanobacteria. The region of the ribosomal genes has been considered stable, whereas the nifH, mcyG and PC-IGS may have undergone horizontal transfer. To investigate the occurrence of horizontal transfer of nifH, mcyG and PC-IGS, phylogenetic trees of Aliinostoc strains Ay1375 and Me1355 were generated and compared. Phylogenetic trees based on the markers were mostly congruent for PC-IGS, indicating a common evolutionary history among ribosomal and phycocyanin genes with no evidence for horizontal transfer of PC-IGS. Phylogenetic trees constructed from the nifH and 16S rRNA genes were incongruent. Our results suggest that nifH has been transferred from one cyanobacterium to another. Moreover, the low non-synonymous/synonymous muta- tion ratio (Ka/Ks) was consistent with an ancient origin of the mcyG. Keywords: 16S–23S ITS, cyanobacteria, horizontal gene transfer, molecular phylogeny, phycocyanin, ribosomal genes Izvleček: Za filogenetske študije prokariontov velja, da je izbira genov, ki niso bili horizontalno preneseni, zahtevna naloga. Notranji prepisani vmesnik ribosomskih genov (16S–23S ITS), geni mikrocistin sintetaze (mcy), nitrogenaze (nifH) in fikocianinski medgenski vmesnik (PC-IGS) so med najpogosteje uporabljenimi označevalci pri ci- anobakterijah. Območje ribosomskih genov velja za stabilno, medtem ko so zaporedja nifH, mcyG in PC-IGS lahko bila prenesena s horizontalnim genskim prenosom. Da bi raziskali pojav horizontalnega prenosa nifH, mcyG in PC-IGS, smo ustvarili filoge- netska drevesa sevov Ay1375 in Me1355 vrste Aliinostoc ter jih med seboj primerjali. Filogenetska drevesa na podlagi označevalcev so bila večinoma skladna za PC-IGS in niso razkrila morebitnih horizontalnih genskih prenosov, kar kaže na skupno evolucijsko zgodovino med ribosomskimi in fikocianinskimi geni. Primerjava filogenetskih dreves, pridobljenih na podlagi gena nifH s filogenetskimi drevesi, pridobljenimi na podlagi gena za 16S rRNA, je razkrila neskladja. Naši rezultati tako nakazujejo, da je bil nifH prenesen iz ene cianobakterije v drugo s horizontalnim genskim prenosom. Poleg tega 105Nowruzi: Phylogenetic study of Aliinostoc species Abbreviations: 16S–23S ITS, internal transcribed spacer of ribosomal genes marker; HGT, horizontal gene transfer; PC-IGS, phycocyanin intergenic spacer marker se nizko razmerje med nesinonimnimi/sinonimnimi mutacijami (Ka/Ks), ki smo ga razkrili v študiji, sklada s starodavnim izvorom gena mcyG. Ključne besede: 16S–23S ITS, cianobakterije, horizontalni genski prenos, mole- kularna filogenija, fikocianin, ribosomski geni Introduction The morphological characteristics of cyanobac- teria do not always correspond to their taxonomic diversity (Komárek et al. 2016) and therefore the use of molecular markers for phylogenetic studies have become essential (Han et al. 2009). Aliinostoc species is a cosmopolitan, nitrogen (N2)-fixing cyanobacterial species found in tem- perate to tropical freshwater or terrestrial habitats. The widespread proliferation of Aliinostoc species in paddy fields has increased the nitrogen in soils. Molecular approaches are particularly useful in the detection and identification of specific strains, especially those that are morphologically identical at the species level. Genetic identification can also be used to characterize the degree of genetic simi- larity among populations (Kabirnataj et al. 2020; Nowruzi et al., 2021; Nowruzi and Shalygin 2021). One of the genes utilized for genetic differences between Aliinostoc cultures was nifH, a highly conserved gene that encodes dinitrogenase reduc- tase, a protein subunit in the nitrogenase complex involved in N2 fixation. Common to all N2 fixers, the 324-bp nifH fragment is useful in characterizing diazotrophic communities and for differentiating cyanobacterial genera (Foster and Zehr, 2006). The other genetic locus used was cpcBA-IGS, which includes the highly variable intergenic spacer (IGS) region between two phycobilisome subunits (cpcB and cpcA) within the phycocyanin operon (Dyble et al., 2002; Brient et al., 2008). Both cpcA-IGS (Bastien et al., 2011) and nifH appear to be more useful in discriminating between strains than the commonly employed 16S rRNA gene, which exhibits low intrageneric variability in many cyanobacteria (Teneva et al., 2012). Moreover, mi- crocystins, cyclic heptapeptide hepatotoxins, are by far the most prevalent of the cyanobacterial toxins and are produced by microcystin synthetase gene cluster (Jungblut et al. 2006; Nowruzi et al., 2022). One of the greatest challenges in the selection of markers for phylogenetic studies in cyanobac- teria is targeting markers that have not undergone horizontal gene transfer (HGT) (Yerrapragada and Siefert, 2009; Piccin‐Santos et al., 2014). HGT and orthologous gene substitutions are relatively common among cyanobacteria and have been important processes in the evolution of this group (Piccin‐Santos et al., 2014). However, HGT events in cyanobacteria may still be underestimated, and genes with several functions could have been sub- jected to this process (Zhaxybayeva et al. 2006). There is no reported evidence that the operons of ribosomal genes have undergone HGT among cyanobacteria. However, the variability observed among the multiple copies of the ribosomal operon found within a single individual can hinder their use in phylogenetic studies (Iteman et al. 2002). The construction and comparison of phyloge- netic trees are perhaps the best ways to assess the contribution of HGT to the evolutionary history of a gene family (Koonin et al., 2002). Incongruence is taken to indicate a role for HGT, whereas congru- ence is consistent with descent through common ancestry. Therefore, to resolve the relationship be- tween microcystin synthetase genes, PC-IGS, nifH, 16S rRNA and the role of HGT in the evolutionary history, we undertook a molecular phylogenetic study. We analyzed and tested for congruence two data sets comprised of genes involved in primary metabolism and genes involved directly in the synthesis of microcystins and nodularins. Our goal, using strains of Aliinostoc species as models, was to evaluate the possible occurrence of HGT by comparing phylogenetic trees built with mcy, PC-IGS, nifH and 16S rRNA. This is the first study to compare the different molecular markers in characterizing two Aliinostoc isolates originating from paddy fields of Iran. 106Acta Biologica Slovenica, 2022, 65 (2), 104–115 Material and methods Strains and cultivation conditions The clonal and axenic strains (strain designa- tions Ay1375 and Me1355) of Aliinostoc belonged to the Cyanobacteria Culture Collection (CCC) and ALBORZ herbarium. Strains were maintained in climate chambers with controlled conditions of continues light and temperature (25 ± 5°C) in BG-11 cultivation medium (Rippka et al. 1979), of pH value 7.4. Molecular and sequence analysis Genomic DNA was isolated from 16-18 days old log phase cultures using the Himedia Ultrasensitive Spin Purification Kit (MB505) following the in- structions of the manufacturer, except the increase of incubation time for the lysis solutions AL and C1, which were set to 60 and 20 min, respectively. DNA fragments within the following genes were amplified using the oligonucleotide primers and PCR programs listed in Table 1: 16S rRNA gene, ITS, nifH, PC-IGS, mcyG and mcyD. PCR reactions were performed using a thermal cycler 5.9 and the following procedure: 25 µl aliquots containing 10- 20 ng DNA template, 0.5 µM of each primer, 1.5 mM MgCl2, 200 µM dNTPs and 1U/µl Taq DNA polymerase (Robertson et al., 2001; Dyble et al., 2002; Nowruzi and Lorenzi, 2021). PCR products were analyzed by electrophoresis on 1% agarose gels (SeaPlaque® GTG®, Cambrex Corporation), using standard protocols. The products were purified directly using the Geneclean® Turbo kit (Qbiogene, MP Biomedicals) and sequenced using the BigDye® Terminator v3.1 cycle sequencing kit (Applied Biosystems, Life Technologies). The partial sequences were compared with the ones available in the NCBI database (March, 2022) using BLASTn. The BLAST X tool (blast.ncbi.nlm. nih.gov/Blast.cgi) was used for cpcA-IGS, nifH, mcy D and mcyE genes. The sequences were annotated with the NCBI ORF Finder and the ExPASY (https:// www.ncbi.nlm.nih.gov/orffinder/) proteomics tools. Table 1. Target genes, oligonucleotide primers and PCR programs used in this study. Tabela 1: Tarčni geni, začetni oligonukleotidi in programi PCR, uporabljeni v raziskavi. Target gene/ sequence Primer designation (sequence 5´3´) PCR program (reference in superscript) 16S rRNA PA (5’-AGAGTTTGATCCTGGCTCAG-3’) B23S (5’-CTTCGCCTCTGTGTGCCTAGGT-3’) 194˚C, 3 min 130 × (94˚C, 30 s; 55˚C, 40 s; 72˚C, 1.30 min) 272˚C, 3 min 24˚C, ∞ 16S-23S rRNA ITS ITS-F (5’-TGTACACACCGCCCGTC-3’) ITS-R (5’-CTCTGTGTGCCTAGGTATCC-3’) cpcA-IGS Cpc F (5’-GGCTGCTTGTTTACGCGACA-3’) Cpc R (5’-CCAGTACCACCAGCAACTAA-3’) 394˚C, 5 min 330 × (92˚C, 1 min; 55˚C, 1 min; 72˚C, 2 min) 372˚C, 6 min 34˚C, ∞ psbA PSBA86F (5’-TTTATGTGGGTTGGTTCGG-3’) PSBA980R4 (5’-TGAGCATTACGCTCGTGC-3’) 494˚C, 5 min 435 × (94˚C, 60 s; 56˚C, 60 s; 72˚C, 60 s) 572˚C, 10 min 54˚C, ∞ nifH nifH F (5’-CGTAGGTTGCGACCCTAAGGCTGA-3’) nifH R (5’-GCATACATCGCCATCATTTCACC-3’) mcyG mcyG F (5’-GAAATTGGTGCGGGAACTGGAG-3’) mcyG R (5’-TTTGAGCAACAATGATACTTTGCTG-3’) 695˚C, 5 min 634 × (95˚C, 30 s; 53˚C, 30 s; 72˚C, 60 s) 772˚C, 5 min 74˚C, ∞ mcyD mcyD F (5’-GCTCAAGAAAAATTACATCAAG-3’) mcyD R (5’-TTAAAGGAGAATGAAAAGCATGAGA-3’) References: 1Taton et al. 2003; 2 Iteman et al. 2000, 3 Neilan et al. 1997, 4 Junier et al. 2007, 5 Gaby and Buckley 2012, 6 Fewer et al. 2007, 7 Rantala et al. 2004 107Nowruzi: Phylogenetic study of Aliinostoc species Nucleotide sequence accession numbers Sequence data were deposited in the DNA Data Bank of Japan (DDBJ) under the accession numbers showed in Table 2. Table 2: Accession numbers of sequence data deposited in the DNA Data Bank of Japan. mcyG was not found in Aliinostoc sp. Ay1375. Tabela 2: Oznake v japonski podatkovni bazi DNA deponiranih nukleotidnih zaporedij Aliinostoc sp. mcyG pri Aliinostoc sp. Ay1375 ni bil določen. Nucleotide ID Target gene Strain Number of nucleotides Number of amino acids Tree model ON751925 ON751926 16S rRNA Ay1375 Me1355 1442 1442 - TVM+F+I+G4 ON755128 ON755129 nifH Ay1375 Me1355 286 282 80 79 TIM2e+I+G4+F ON755126 ON755127 cpcA-IGS Ay1375 Me1355 589 612 98 98 LG+G4 OM801556 mcyG Me1355 494 164 TPM3U+G4+F Phylogenetic analysis The 16S rRNA, ITS, cpcA-IGS, nifH, mcyG and mcyD genes sequences obtained in this study, as well as the best hit sequences (> 94% identity) retrieved from GenBank, were first aligned using MUSCLE (Edgar 2004), and then maximum likeli- hood phylogenetic trees were inferred in IQ-Tree (multicore v1.5.5) (Nguyen et al. 2015). Different models were used as suggested (BIC criterion) after employing model test implemented in IQ- tree (Table 2). Tree robustness was estimated with bootstrap percentages using 100 standard bootstrap and 10,000 ultrafast bootstrap to evaluate branch supports (Guajardo-Leiva et al. 2018). 16S-23S rRNA ITS region secondary structure analysis The sequences corresponding to the D1-D1’ helix, D2, D3, Box-B and Box-A regions of the 16S-23S ITS of the studied strains were character- ized according to the Johansen et al. (2011), and trRNAIle and trRNAAla were determined accord- ing to the tRNAscan-SE 2.0 (Chan et al., 2021). Comparison of the ITS secondary structures of studied strains and the reference strains were generated using the M-fold web server (ver- sion 2.3) (Zuker 2003) under ideal conditions of untangled loop fix and the temperature set to default (37 °C). Sequence divergence We calculated the number of non-synonymous substitutions per non-synonymous site (Ka) and the number of synonymous substitutions per synony- mous site (Ks) by using MEGA X (Nowruzi and Blanco, 2019). A Ka/Ks ratio >1 indicates positive selection for advantageous mutations, whereas a Ka/Ks ratio <1 indicates purifying selection to prevent the spread of detrimental mutations (Leikoski et al., 2009). 108Acta Biologica Slovenica, 2022, 65 (2), 104–115 Results Phylogenetic analyses Phylogenetic trees based on different gen markers are shown in Figs. 1 to 3. The nifH gene fragment and the fragment of the phycocyanin operon (cpcA-IGS) were amplified from both studied strains, however mcyG was only detected in Aliinostoc Me1355 strain. The Aliinostoc phylogenetic trees based on the markers PC-IGS and 16S–23S ITS (Fig. 1) showed similar topologies. From the phylogenetic analysis based on 16 rRNA gene sequences, it is possible to observe that the studied strain is within a cluster composed by other Nostoc strains and its closest one is Nostoc_elgonense_TAU-MAC_0299 (MN062664). However, the phylogenetic trees obtained using nifH and 16S–23S ITS (Fig. 2) have differences in the branch positions of some strains. In the phylogeny based on the gene 16S–23S ITS, the studied strains were placed with Nostoc_calcicola_Ind32 (N216874) in the same cluster, However, when we look into the phylogeny based on nifH gene, the studied strains fall into separate clades and its closest one is Nostoc_sp. NQAIF320 (KJ636979), indicating that this gene probably could be the best marker for a high resolution at species level. The highest mcyG sequence similarity was found to be 100% identical with Nostoc sp. CENA88 (Q259210) (Fig. 3). Moreover, The Aliinostoc phylogenetic trees based on the mark- ers mcyG and 16S–23S ITS (Fig. 3) showed similar topologies. We have also compared the 16S rRNA p-distances of our strains with related genera, namely Aliinostoc_morphoplasticum NOS (KY403996_1), Aliinostoc sp. SA46 (MK503795), Aliinostoc sp. SA9 (MK503790) and Aliinostoc magnakinetifex SA18 (MK503791). Results showed that Aliinostoc sp. strain Ay1375 shared a 16S rRNA sequence similarity of 97.22% with Aliinostoc morphoplasticum NOS (KY403996_1), 96.52% with Aliinostoc sp. SA46 (MK503795), 96.80% with Aliinostoc sp. SA9 (MK503790) and 93.73% with Aliinostoc magnakinetifex SA18 (MK503791), while Aliinostoc sp. strain Me1355 shared a 16S rRNA sequence similar- ity of 97.22% with Aliinostoc morphoplasticum NOS (KY403996_1), 96.38% with Aliinostoc sp. SA46 (MK503795), 96.80% with Aliinostoc sp. SA9 (MK503790) and 93.59% with Aliinostoc magnakinetifex SA18 (MK503791) (Tab. 3). Figure 1: Congruence between phylogenies inferred from the 16S rRNA and cpcA-IGS sequences. A maximum-likelihood tree based on the 16SrRNA data set (left). A maximum-likelihood tree based on the cpcA-IGS data set (right). Numbers near nodes indicate standard bootstrap support (%) / ultrafast bootstrap support (%) for ML analyses. Slika 1: Skladnost med nizoma podatkov nukleotidnih zaporedij 16S rRNA in cpcA-IGS. Drevo, ocenjeno po metodi največjega verjetja na osnovi 16S rRNA (levo). Drevo, ocenjeno po metodi največjega verjetja na osnovi cpcA-IGS (desno). Številke ob razvejitvah prikazujejo podporo izračunano z običajno metodo samovzorčenja (%) / ultrahitro metodo samovzorčenja (%) za analize največjega verjetja. 109Nowruzi: Phylogenetic study of Aliinostoc species Fig. 2. Congruence between phylogenies inferred from the 16S rRNA and nifH sequences. A maximum-likelihood tree based on the 16SrRNA data set (left). A maximum-likelihood tree based on the nifH data set (right). Numbers near nodes indicate standard bootstrap support (%) / ultrafast bootstrap support (%) for ML analyses. Slika 2: Skladnost med nizoma podatkov nukleotidnih zaporedij 16S rRNA in nifH. Drevo, ocenjeno po metodi največjega verjetja na osnovi 16S rRNA (levo). Drevo, ocenjeno po metodi največjega verjetja na osnovi nifH (desno). Številke ob razvejitvah prikazujejo podporo izračunano z običajno metodo samovzorčenja (%) / ultrahitro metodo samovzorčenja (%) za analize največjega verjetja. Fig. 3. Congruence between phylogenies inferred from the 16S rRNA and mcyG sequences. A maximum-likelihood tree based on the mcyG data set (left). A maximum-likelihood tree based on the 16SrRNA data set (right). Numbers near nodes indicate standard bootstrap support (%) / ultrafast bootstrap support (%) for ML analyses. Slika 3: Skladnost med nizoma podatkov nukleotidnih zaporedij 16S rRNA in mcyG. Drevo, ocenjeno po metodi največjega verjetja na osnovi 16S rRNA (levo). Drevo, ocenjeno po metodi največjega verjetja na osnovi mcyG (desno). Številke ob razvejitvah prikazujejo podporo izračunano z običajno metodo samovzorčenja (%) / ultrahitro metodo samovzorčenja (%) za analize največjega verjetja. 110Acta Biologica Slovenica, 2022, 65 (2), 104–115 Table 3. 16S rRNA gene sequence similarity matrix of studied strains and related taxa. Tabela 3: Matrika podobnosti za nukleotidno zaporedje gena 16S rRNA pri preučevanih sevih in sorodnih taksonih. Strain Aliinostoc sp. strain Ay1375 Aliinostoc sp. strain Me1355 KY403996_1_ Aliinostoc_ morphoplasticum_ NOS MK503795_1_ Aliinostoc_ sp_SA46 MK503790_1_ Aliinostoc_ sp_SA9 Aliinostoc sp. strain Ay1375 Aliinostoc sp. strain Me1355 0 Aliinostoc_morphoplasticum_NOS 97.22 97.22 Aliinostoc_sp_SA46 96.52 96.38 95.80 Aliinostoc_sp_SA9 96.80 96.80 95.52 99.33 Aliinostoc_magnakinetifex_SA18 93.73 93.59 94.16 95.79 95.50 16S-23S rRNA ITS secondary structure Four reference sequences were used to search for ITS secondary structure. According to Johansen et al. (2011), nine different areas (D1-D1’ helix, D2, D3, trRNAIle, trRNAAla, Box-B, Box-A and D4) were found in the ITS secondary structure of studied strain. The D1-D1’ and Box-B regions of all studied strains were revealed to be very different in terms of length and shape (Fig. 4, Tab. 4). The D1-D1’ region included a terminal bilat- eral bulge (A), bilateral bulge (B), unilateral bulge (C), and basal clamp (D) (Fig. 4). The lengths of D1-D1’ helix varied from 93 nt (Aliinostoc sp. strain Ay1375, Aliinostoc sp. strain Me1355, KY403996.1 Aliinostoc morphoplasticum NOS) to 60 nt (Aliinostoc magnakinetifex SA18) (Tab. 4). The basal stem revealed to be the same for all studied strains (5’- GACCUA- UAGGUC - 3’) (Fig. 4). Box-B was nominated by a terminal bilateral bulge (A) and bilateral bulge (B). Box-B helix was not found for Aliinostoc magnakinetifex SA18. As to the Box-B + spacer, lengths varied from 39 nt (Aliinostoc morphoplasticum NOS) to 55 nt (Aliinostoc sp. SA46), with studied strains showing a length of 44 nt (Fig. 4) (Tab. 5). Figure 4. Comparison of secondary structures of D1–D1´ helices (upper row) and Box-B helices and V3 helices (lower row), both from 16S–23S intergenic spacers between studied strains with reference strains. Marks: A - Terminal bilateral bulge, B - bilateral bulge, C - Unilateral bulge, D - Basal clamp, arrows - bulges and basal clamp. Slika 4: Primerjava sekundarnih struktur D1-D1’ vijačnic (zgornja vrstica) ter Box-B vijačnic in V3 vijačnic (spodnja vrstica) iz 16S–23S medgenskih vmesnikov med preučevanimi in referenčnimi sevi. Oznake: A - Terminalna bilateralna izboklina, B - Bilateralna izboklina, C - Unilateralna izboklina, D – Bazalna spona, puščice – izbokline in bazalna spona. 111Nowruzi: Phylogenetic study of Aliinostoc species Table 4: Nucleotide lengths of the 16S–23S ITS regions of the studied strains. Tabela 4: Dolžine nukleotidov za območja 16S–23S ITS pri preučevanih sevih. D 4 Bo x A B ox B +s pa ce r Tr RN AA la g en e sp ac er +V 2+ sp ac er tr RN AI le g en e D3 + sp ac er D3sp ac er +D 2+ sp ac er D1 -D 1, he lix Strain 91144---3033993Aliinostoc sp. strain Ay1375 91144---3033993Aliinostoc sp. strain Me1355 91139---2233893Aliinostoc morphoplasticum NOS 9-----3733460Aliinostoc magnakinetifex SA18 101055---4333866Aliinostoc sp. SA46 91154---4634066Aliinostoc sp. SA9 Table 5: Comparison of secondary structure of 16S-23S rRNA (D1-D1’ helix and Box-B helix) between the studied strains with reference strains. Tabela 5: Primerjava sekundarne zgradbe 16S-23S rRNA (vijačnica D1-D1’ in Box-B) med preučevanimi in referenčnimi sevi. Strain D1-D1’ helix Box-B Terminal bilateral bulge (A) Bilateral bulge (B) Unilateral bulge (C) Basal clamp (D) Terminal bilateral bulge (A) Bilateral bulge (B) Basal clamp (C) Number of nucleotides Number of loops Number of loops Number of nucleotides Number of nucleotides Number of loops Number of nucleotides Aliinostoc sp. strain Ay1375 7 3 1 12 6 1 8 Aliinostoc sp. strain Me1355 7 4 1 12 6 1 8 Aliinostoc morphoplasticum NOS 6 4 1 12 8 1 6 Aliinostoc magnakinetifex SA18 7 2 1 12 6 2 10 Aliinostoc sp. SA46 7 1 2 12 6 2 8 Aliinostoc sp. SA9 7 1 2 12 5 1 22 Sequence divergences Sequence divergences in the mcyG gene data set were much higher than expected in an evolutionary scenario, favoring recent horizontal gene transfer as a mechanism to explain the sporadic distribution of microcystin producers among cyanobacteria. To determine whether the mcyG gene is under positive 112Acta Biologica Slovenica, 2022, 65 (2), 104–115 or negative selection pressure, we compared the number of nonsynonymous substitutions per non- synonymous site (Ka) to the number of synonymous substitutions per synonymous site (Ks). The Ka/Ks ratio was well below 1 in pairwise comparisons from representative strains of each genus. A low Ka/Ks ratio is indicative of purifying selection in which deleterious mutations affecting the protein sequence are selected against and is consistent with an ancient origin of the mcyG gene. Discussion HGT is relatively common among cyanobac- teria, but it does not affect all genes in the same way. For some genomes, gene clusters have a lower probability of being transferred (Rantala et al., 2004). The phylograms based on PC-IGS and mcyG were mostly congruent and no clear HGT signal was found for these genes, indicating a common evolutionary pathway for the phycocyanin, mcyG and ribosomal genes. This result is consistent with those of Sanchis et al. (2005) and Dadheech et al. (2010), who found that PC-IGS and 16S–23S ITS regions of Microcystis and Arthrospira strains also showed a high similarity between marker topologies. Phylogenetic analysis of this region was largely consistent with that obtained from 16S rDNA sequence analysis and revealed a re- lationship between the 16S rDNA sequence and the phycobilin content of cells. However, phylogenetic trees constructed from the nifH and 16S rRNA genes were incongruent. Our results suggest that the nifH gene encoding the dinitrogenase reductase has been transferred from one cyanobacterium to another. However, the phylogenetic incongruence detected is likely to be a result of ancient horizontal transfers of the nifH biosynthetic genes since the sequence divergence of the dinitrogenase reductase genes was high. The main point of discordance between in the nifH phylogenetic tree was the location of two studied strains, in the phylogeny based on the gene 16S–23S ITS, they were placed in the same cluster, however into the phylogeny based on nifH gene, the studied strain falls into separate clades. In addition, it is noteworthy that in the 16S–23S ITS proposed phylogeny, there is a high Bayesian posterior probability to support its location. Morphological studies showed that both studied strains were morphologically similar to each other, but that two of them formed an isolated clade in the nifH phylogram, indicating that despite the morphological similarity, they represent geneti- cally divergent strains. Thus, the hypothesis that the divergence of the strains observed in the nifH tree could have been due to HGT was confirmed. Moreover, our analyses do not corroborate the presence of HGT in PC-IGS and mcyG, but this event cannot be neglected as a hypothesis for explaining divergences in phylogenies. A study on the genome of Synechococcus spp. indicated that genes encoding phycocyanin may have evolved independently from genes of the core genome such as the allo-PC gene or the ribosomal regions (Six et al. 2007). The search for more stable markers, not biased by HGT, has become essential for understanding the phylogeny and taxonomy of cyanobacteria (Gribaldo and Brochier 2009). The results pre- sented herein strongly support nifH as a marker of choice for cyanobacterial phylogenetic studies and emphasize the importance of using multiple molecular markers to prevent erroneous conclu- sions based on HGT. Summary Horizontal gene transfer (HGT), potentially followed by recombination with or replacement of resident homologues, represents an important factor in the phylogeny of prokaryotic organisms such as cyanobacteria, and shapes their evolutionar history. Nowadays, HGT seems to be a major factor in species delimitation in cyanobacteria and plays a key selection pressure leading to cyanobacterial diversification. In this study, PC-IGS, nifH, mcyD, mycG and the ribosomal gene spacer 16S–23S ITS as molecular markers were compared to investigate the occurrence of horizontal transfer. The phylograms based on PC-IGS and mcyG were mostly congruent and no clear HGT signal was found for these genes. However, phylogenetic trees constructed from the nifH and 16S rRNA genes were incongruent. The exploration for more 113Nowruzi: Phylogenetic study of Aliinostoc species steady markers, not biased by HGT, has become important for detection of the phylogeny and taxonomy of cyanobacteria. Povzetek Horizontalni genski prenos (HGT), ki mu lahko sledi rekombinacija ali zamenjava obstoječih homolognih zaporedij, predstavlja pomemben dejavnik v filogeniji prokariontskih organizmov, kot so cianobakterije, in oblikuje njihovo evolu- cijsko zgodovino. Danes se zdi, da je HGT glavni dejavnik pri razmejitvi vrst pri cianobakterijah in je ključni selekcijski pritisk, ki vodi v diverzifikacijo cianobakterij. V tej študiji smo primerjali nukle- otidna zaporedja PC-IGS, nifH, mcyD, mycG in ribosomski medgenski vmesnik 16S–23S ITS kot molekularne označevalce, da bi raziskali pojav HGT. Filogenetska drevesa, ki temeljijo na nukleotidnih zaporedijh PC-IGS in mcyG so si med seboj bila večinoma skladna, tzato lahko za ta nukleotidna zaporedja predvidevamo, da se niso prenašala s HGT. Filogenetska drevesa, ki so bila narejena na podlagi nukleotidnih zaporedij nifH in genov za 16S rRNA, so bila med seboj neskladna, kar nakazuje na HGT. 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Dominik Vodnik (foto: Aleš Kladnik). 117Plants in Changing Evironment – mednarodna konferenca Slovenskega društva za biologijo rastlin Slovensko društvo za biologijo rastlin je 15. in 16. septembra 2022 v Biološkem središču v Ljubljani že osmič organiziralo mednarodno srečanje na temo biologije rastlin. Letos smo konferenco naslovili »Plants in Changing Environment« (slo. »Rastline v spreminjajočem se okolju«) in tako še posebej izpostavili pomen rastlin v luči zaskrbljujočih okoljskih razmer. Rastline so namreč temelj prehranske varnosti in hkrati blažijo negativne vplive klimatskih sprememb v okolju. Zanimiv program z enajstimi vabljenimi predavatelji je privabil skoraj sto udeležencev iz kar 11 različnih držav, ki so svoje delo predstavili še v okviru 18 kratkih predavanj in 38 posterjev. Konferenco je otvorila Maria J. Pozo iz CSIC Granada (Španija) s predavanjem o ugodnih vplivih mikroorganizmov na rast rastlin in njihovo odpornost na okoljske dejavnike. Predavanje je bilo odličen uvod v naslednjo sekcijo, kjer so bile predstavljene različne aplikativne in agronomske raziskave, od vpliva klimatskih sprememb na razširjanje povzročiteljev bolezni, njihove detekcije v različnih okoljih in razvoja alternativnih sredstev za zaščito rastlin. V sekciji »Metabolizem struktura in funkcija rastlin« so bile predstavljene različne visokozmogljive tehnike, od rentgenskih tehnik za odkrivanje elementov v sledovih v ratslinskih tkivih, fenotipizacije ter raziskave metabolizma glutationa. V najobsežnejši sekciji »Interakcije rastlin z drugimi organizmi« so bile predstavljene raziskave mikrobioma rastlin, endofitov ter virusnih povzročiteljev bolezni; po drugi strani pa različni vidiki imunskega odziva krom- pirja in vinske trte ter alelopatsko delovanje dresnika. V luči spreminjajočega okolja smo obravnavali tudi naravne ekosisteme, evolucijski potencial in fenotipsko plastičnost v gozdnih ekosistemih, vpliv abiotskih dejavnikov na mikorizne glive hrasta in razvoja lesa ter diferenciacijo in razširjenost bekic. V zadnji sekciji, »Interakcije rastlin z okoljem« so bile predstavljeni različni vidiki oksidativnega stresa rastlin ter raziskave odziva vinske trte na stresne dejavnike. Slednja tema je bila odličen uvod v zaključno predavanje, ko je Mario Pezotti z Univerze v Veroni (Italija) predstavil različne primere »omskih« raziskav vinske trte, ki je zaradi klimatskih sprememb še posebej prizadeta. Knjiga povzet- kov konference je dostopna na spletni strani društva https://www.plantslo.org/wp/conference2022/. Slovensko društvo za biologijo rastlin, ki je bilo sicer ustanovljeno kot Slovensko društvo za rastlin- sko fiziologijo, je aktivno od leta 1993 in združuje rastlinske biologe, ki delujejo na različnih področjih. Društvo mednarodna srečanja organizira vsake 4 leta, prvo je bilo organizirano leta 1993. Na tokratnem srečanju smo obeležili 40-letnico neprekinjenega delovanja društva in prvič podelili nagrade »nada«, ki nas po eni strani spominjajo na prof. dr. Nado Gogala, po drugi strani pa simbolizirajo upanje. Nagradi sta za dolgoletno in požrtvovalno delovanje v društvu, s katerim sta trajno prispevala k njegovemu delovanju in prepoznavnosti, prejela prof. dr. Marina Dermastia in prof. dr. Dominik Vodnik, ki sta izvedla tudi priložnostni predavanji o zgodovini društva in o vplivu atmosferskega sušenja na rastline. Konferenco je finančno podprlo šest podjetij, Omega d.o.o., Mediline d.o.o., AciesBio d.o.o., VWR International GmbH, Bia do.o.o., in Medis d.o.o., materialno pa Kmetijski inštitut Slovenije in Univerza v Mariboru. Konferenco smo izvedli v sodelovanju z Oddelkom za biologijo Biotehniške fakultete Univerze v Ljubljani ter Nacionalnim inštitutom za biologijo. Za pomoč pri izvedbi se zahvaljujemo tudi Fakulteti za kemijo in kemijsko tehnologijo Univerze v Ljubljani. Ponovno je bila konferenca, poleg obravnave aktualnih tematik, odlična priložnost za povezovanje strokovnjakov z različnih področij biologije rastlin v Sloveniji in okolici, in ne dvomimo, da bo krepitev obstoječih navezav in vzpostavitev novih vodila v nova sodelovanja. Špela Baebler predsednica organizacijskega odbora Acta Biologica Slovenica (2022) – Vol. 65: št. 2 PREGLEDNA ČLANKA – REVIEW PAPERS: Adrijana LEONARDI Masna spektrometrija v raziskavah kačjih strupov / Mass spectrometry in snake venom research...........................................................................................................................................5 Alenka GABERŠČIK, Matej HOLCAR, Mateja GRAŠIČ Optical properties of different structures of some herbaceous understorey plant species from temperate deciduous forests / Optične lastnosti različnih struktur pri nekaterih zelnatih rastlinskih vrstah v podrasti zmernega listopadnega gozda..........................................................26 ZNANSTVENA ČLANKA – SCIENTIFIC ARTICLES: Martina TURK, Vesna PODGRAJŠEK, Cene GOSTINČAR, Nina GUNDE-CIMERMAN Aerobic bacteria in holy water from Catholic churches in Slovenia / Aerobne bakterije v blagoslovljeni vodi iz katoliških cerkva v Sloveniji......................................................................42 Bahareh NOWRUZI Phylogenetic study of Aliinostoc species (Cyanobacteria) using pc-igs, nifH and mcy as markers for investigation of horizontal gene transfer / Filogenetska študija vrst Aliinostoc (Cyanobacteria) z uporabo označevalcev pc-igs, nifH in mcy za ugotavljanje horizontalnega genskega prenosa.........................................................................................................................104 NOVICA – NEWS: Špela BAEBLER Plants in changing evironment – mednarodna konferenca Slovenskega društva za biologijo rastlin / Plants in changing evironment – International symposium of Slovene society of plant biology.........................................................................................................................................116