A predicted CRISPR-mediated symbiosis between uncultivated archaea.


Journal

Nature microbiology
ISSN: 2058-5276
Titre abrégé: Nat Microbiol
Pays: England
ID NLM: 101674869

Informations de publication

Date de publication:
09 2023
Historique:
received: 09 05 2023
accepted: 23 06 2023
medline: 31 8 2023
pubmed: 28 7 2023
entrez: 27 7 2023
Statut: ppublish

Résumé

CRISPR-Cas systems defend prokaryotic cells from invasive DNA of viruses, plasmids and other mobile genetic elements. Here, we show using metagenomics, metatranscriptomics and single-cell genomics that CRISPR systems of widespread, uncultivated archaea can also target chromosomal DNA of archaeal episymbionts of the DPANN superphylum. Using meta-omics datasets from Crystal Geyser and Horonobe Underground Research Laboratory, we find that CRISPR spacers of the hosts Candidatus Altiarchaeum crystalense and Ca. A. horonobense, respectively, match putative essential genes in their episymbionts' genomes of the genus Ca. Huberiarchaeum and that some of these spacers are expressed in situ. Metabolic interaction modelling also reveals complementation between host-episymbiont systems, on the basis of which we propose that episymbionts are either parasitic or mutualistic depending on the genotype of the host. By expanding our analysis to 7,012 archaeal genomes, we suggest that CRISPR-Cas targeting of genomes associated with symbiotic archaea evolved independently in various archaeal lineages.

Identifiants

pubmed: 37500801
doi: 10.1038/s41564-023-01439-2
pii: 10.1038/s41564-023-01439-2
doi:

Substances chimiques

DNA 9007-49-2

Banques de données

figshare
['10.6084/m9.figshare.22339555', '10.6084/m9.figshare.22738568', '10.6084/m9.figshare.22739849']

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S. Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1619-1633

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2023. The Author(s), under exclusive licence to Springer Nature Limited.

Références

Garneau, J. E. et al. The CRISPR/Cas bacterial immune system cleaves bacteriophage and plasmid DNA. Nature 468, 67 (2010).
pubmed: 21048762
Andersson, A. F. & Banfield, J. F. Virus population dynamics and acquired virus resistance in natural microbial communities. Science 320, 1047–1050 (2008).
pubmed: 18497291
Koonin, E. V. & Makarova, K. S. Evolutionary plasticity and functional versatility of CRISPR systems. PLoS Biol. 20, e3001481 (2022).
pubmed: 34986140 pmcid: 8730458
Makarova, K. S. et al. An updated evolutionary classification of CRISPR–Cas systems. Nat. Rev. Microbiol. 13, 722 (2015).
pubmed: 26411297 pmcid: 5426118
Makarova, K. S. et al. Evolutionary classification of CRISPR–Cas systems: a burst of class 2 and derived variants. Nat. Rev. Microbiol. 18, 67–83 (2020).
pubmed: 31857715
Maniv, I., Jiang, W., Bikard, D. & Marraffini, L. A. Impact of different target sequences on type III CRISPR–Cas immunity. J. Bacteriol. 198, 941 (2016).
pubmed: 26755632 pmcid: 4772595
Marraffini, L. A. & Sontheimer, E. J. Self versus non-self discrimination during CRISPR RNA-directed immunity. Nature 463, 568–571 (2010).
pubmed: 20072129 pmcid: 2813891
Dombrowski, N., Lee, J.-H., Williams, T. A., Offre, P. & Spang, A. Genomic diversity, lifestyles and evolutionary origins of DPANN archaea. FEMS Microbiol. Lett. 366, fnz008 (2019).
pubmed: 30629179 pmcid: 6349945
Rinke, C. et al. Insights into the phylogeny and coding potential of microbial dark matter. Nature 499, 431–437 (2013).
pubmed: 23851394
Castelle, C. J. et al. Biosynthetic capacity, metabolic variety and unusual biology in the CPR and DPANN radiations. Nat. Rev. Microbiol. 16, 629–645 (2018).
pubmed: 30181663
Sakai, H. D. et al. Insight into the symbiotic lifestyle of DPANN archaea revealed by cultivation and genome analyses. Proc. Natl Acad. Sci. USA 119, e2115449119 (2022).
pubmed: 35022241 pmcid: 8784108
Jahn, U. et al. Nanoarchaeum equitans and Ignicoccus hospitalis: new insights into a unique, intimate association of two archaea. J. Bacteriol. 190, 1743–1750 (2008).
pubmed: 18165302
Huber, H. et al. A new phylum of Archaea represented by a nanosized hyperthermophilic symbiont. Nature 417, 63–67 (2002).
pubmed: 11986665
Schwank, K. et al. An archaeal symbiont–host association from the deep terrestrial subsurface. ISME J. 13, 2135–2139 (2019).
pubmed: 31048756 pmcid: 6776059
Hamm, J. N. et al. Unexpected host dependency of Antarctic Nanohaloarchaeota. Proc. Natl Acad. Sci. USA 116, 14661 (2019).
pubmed: 31253704 pmcid: 6642349
Munson-McGee, J. H. et al. Nanoarchaeota, their Sulfolobales host, and Nanoarchaeota virus distribution across Yellowstone National Park hot springs. Appl. Environ. Microbiol. 81, 7860–7868 (2015).
pubmed: 26341207 pmcid: 4616950
Jarett, J. K. et al. Single-cell genomics of co-sorted Nanoarchaeota suggests novel putative host associations and diversification of proteins involved in symbiosis. Microbiome 6, 161 (2018).
pubmed: 30223889 pmcid: 6142677
Wurch, L. et al. Genomics-informed isolation and characterization of a symbiotic Nanoarchaeota system from a terrestrial geothermal environment. Nat. Commun. 7, 12115 (2016).
pubmed: 27378076 pmcid: 4935971
Hamm, J. N. et al. The parasitic lifestyle of an archaeal symbiont. Preprint at bioarXiv https://doi.org/10.1101/2023.02.24.5298342.24.529834v2 (2023).
Probst, A. J. et al. Differential depth distribution of microbial function and putative symbionts through sediment-hosted aquifers in the deep terrestrial subsurface. Nat. Microbiol. 3, 328–336 (2018).
pubmed: 29379208 pmcid: 6792436
Heimerl, T. et al. A complex endomembrane system in the archaeon Ignicoccus hospitalis tapped by Nanoarchaeum equitans. Front. Microbiol. 8, 1072 (2017).
pubmed: 28659892 pmcid: 5468417
Comolli, L. R. & Banfield, J. F. Inter-species interconnections in acid mine drainage microbial communities. Front. Microbiol. 5, 367 (2014).
pubmed: 25120533 pmcid: 4110969
Baker, B. J. et al. Enigmatic, ultrasmall, uncultivated Archaea. Proc. Natl Acad. Sci. USA 107, 8806–8811 (2010).
pubmed: 20421484 pmcid: 2889320
Hernsdorf, A. W. et al. Potential for microbial H
pubmed: 28350393 pmcid: 5520028
Probst, A. J. et al. Biology of a widespread uncultivated archaeon that contributes to carbon fixation in the subsurface. Nat. Commun. 5, 5497 (2014).
pubmed: 25425419
Probst, A. J. et al. Genomic resolution of a cold subsurface aquifer community provides metabolic insights for novel microbes adapted to high CO
pubmed: 27112493
Emerson, J. B., Thomas, B. C., Alvarez, W. & Banfield, J. F. Metagenomic analysis of a high carbon dioxide subsurface microbial community populated by chemolithoautotrophs and bacteria and archaea from candidate phyla. Environ. Microbiol. 18, 1686–1703 (2016).
pubmed: 25727367
Rahlff, J. et al. Lytic archaeal viruses infect abundant primary producers in Earth’s crust. Nat. Commun. 12, 4642 (2021).
pubmed: 34330907 pmcid: 8324899
Wimmer, F., Mougiakos, I., Englert, F. & Beisel, C. L. Rapid cell-free characterization of multi-subunit CRISPR effectors and transposons. Mol. Cell 82, 1210–1224.e6 (2022).
pubmed: 35216669
Marshall, R. et al. Rapid and scalable characterization of CRISPR technologies using an E. coli cell-free transcription-translation system. Mol. Cell 69, 146–157.e3 (2018).
pubmed: 29304331 pmcid: 5976856
Heussler, G. E. & O’Toole, G. A. Friendly fire: biological functions and consequences of chromosomal targeting by CRISPR–Cas systems. J. Bacteriol. 198, 1481–1486 (2016).
pubmed: 26929301 pmcid: 4859606
Stern, A., Keren, L., Wurtzel, O., Amitai, G. & Sorek, R. Self-targeting by CRISPR: gene regulation or autoimmunity? Trends Genet. 26, 335–340 (2010).
pubmed: 20598393 pmcid: 2910793
Aklujkar, M. & Lovley, D. R. Interference with histidyl-tRNA synthetase by a CRISPR spacer sequence as a factor in the evolution of Pelobacter carbinolicus. BMC Evol. Biol. 10, 230 (2010).
pubmed: 20667132 pmcid: 2923632
Bhaya, D., Davison, M. & Barrangou, R. CRISPR–Cas systems in bacteria and archaea: versatile small RNAs for adaptive defense and regulation. Annu. Rev. Genet. 45, 273–297 (2011).
pubmed: 22060043
Wilson, G. G. Organization of restriction-modification systems. Nucleic Acids Res. 19, 2539–2566 (1991).
pubmed: 2041731 pmcid: 328170
Bornemann, T. L. V. et al. Genetic diversity in terrestrial subsurface ecosystems impacted by geological degassing. Nat. Commun. 13, 284 (2022).
pubmed: 35022403 pmcid: 8755723
Turgeman-Grott, I. et al. Pervasive acquisition of CRISPR memory driven by inter-species mating of archaea can limit gene transfer and influence speciation. Nat. Microbiol. 4, 177–186 (2019).
pubmed: 30478289
Stachler, A.-E. et al. High tolerance to self-targeting of the genome by the endogenous CRISPR–Cas system in an archaeon. Nucleic Acids Res. 45, 5208–5216 (2017).
pubmed: 28334774 pmcid: 5435918
Vink, J. N. A., Baijens, J. H. L. & Brouns, S. J. J. PAM-repeat associations and spacer selection preferences in single and co-occurring CRISPR–Cas systems. Genome Biol. 22, 281 (2021).
pubmed: 34593010 pmcid: 8482600
Pyenson, N. C., Gayvert, K., Varble, A., Elemento, O. & Marraffini, L. A. Broad targeting specificity during bacterial type III CRISPR–Cas immunity constrains viral escape. Cell Host Microbe 22, 343–353 (2017).
pubmed: 28826839 pmcid: 5599366
Chabas, H., Müller, V., Bonhoeffer, S. & Regoes, R. R. Epidemiological and evolutionary consequences of different types of CRISPR-Cas systems. PLoS Comput. Biol. 18, e1010329 (2022).
pubmed: 35881633 pmcid: 9355216
Brodt, A., Lurie-Weinberger, M. N. & Gophna, U. CRISPR loci reveal networks of gene exchange in archaea. Biol. Direct 6, 65 (2011).
pubmed: 22188759 pmcid: 3285040
Paper, W. et al. Ignicoccus hospitalis sp. nov., the host of ‘Nanoarchaeum equitans’. Int. J. Syst. Evol. Microbiol. 57, 803–808 (2007).
pubmed: 17392210
Dombrowski, N., Teske, A. P. & Baker, B. J. Expansive microbial metabolic versatility and biodiversity in dynamic Guaymas Basin hydrothermal sediments. Nat. Commun. 9, 4999 (2018).
pubmed: 30479325 pmcid: 6258724
Hohenester, E. & Yurchenco, P. D. Laminins in basement membrane assembly. Cell Adhes. Migr. 7, 56–63 (2013).
Hohenester, E. Laminin G-like domains: dystroglycan-specific lectins. Curr. Opin. Struct. Biol. 56, 56–63 (2019).
pubmed: 30530204
Benner, S. A., Ellington, A. D. & Tauer, A. Modern metabolism as a palimpsest of the RNA world. Proc. Natl Acad. Sci. USA 86, 7054–7058 (1989).
pubmed: 2476811 pmcid: 297992
Joshi, N. A. & Fass, J. N. Sickle: a sliding-window, adaptive, quality-based trimming tool for FastQ files (v.1.33) Github https://github.com/najoshi/sickle (2011).
Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. A. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 27, 824–834 (2017).
pubmed: 28298430 pmcid: 5411777
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
pubmed: 22388286 pmcid: 3322381
Bornemann, T. L. V., Esser, S. P., Stach, T. L., Burg, T. & Probst, A. J. uBin—a manual refining tool for genomes from metagenomes. Environ. Microbiol. 25, 1077–1083 (2023).
Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).
pubmed: 25977477 pmcid: 4484387
Eddy, S. R. Accelerated profile HMM searches. PLoS Comput. Biol. 7, e1002195 (2011).
pubmed: 22039361 pmcid: 3197634
Darling, A. E. et al. PhyloSift: phylogenetic analysis of genomes and metagenomes. PeerJ 2, e243 (2014).
pubmed: 24482762 pmcid: 3897386
Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).
pubmed: 15034147 pmcid: 390337
Criscuolo, A. & Gribaldo, S. BMGE (Block Mapping and Gathering with Entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evol. Biol. 10, 210 (2010).
pubmed: 20626897 pmcid: 3017758
Minh, B. Q. et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534 (2020).
pubmed: 32011700 pmcid: 7182206
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).
pubmed: 28481363 pmcid: 5453245
Wang, H.-C., Minh, B. Q., Susko, E. & Roger, A. J. Modeling site heterogeneity with posterior mean site frequency profiles accelerates accurate phylogenomic estimation. Syst. Biol. 67, 216–235 (2017).
Hoang, D. T., Chernomor, O., von Haeseler, A., Minh, B. Q. & Vinh, L. S. UFBoot2: improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518–522 (2017).
pmcid: 5850222
Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).
pubmed: 20525638
Anisimova, M., Gil, M., Dufayard, J.-F., Dessimoz, C. & Gascuel, O. Survey of branch support methods demonstrates accuracy, power, and robustness of fast likelihood-based approximation schemes. Syst. Biol. 60, 685–699 (2011).
pubmed: 21540409 pmcid: 3158332
Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 47, W256–W259 (2019).
pubmed: 30931475 pmcid: 6602468
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59 (2014).
pubmed: 25402007
Gouy, M., Tannier, E., Comte, N. & Parsons, D. P. in Multiple Sequence Alignment: Methods and Protocols (ed. Katoh, K.) 241–260 (Springer, 2021).
Couvin, D. et al. CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins. Nucleic Acids Res. 46, W246–W251 (2018).
pubmed: 29790974 pmcid: 6030898
Moller, A. G. & Liang, C. MetaCRAST: reference-guided extraction of CRISPR spacers from unassembled metagenomes. PeerJ 5, e3788 (2017).
pubmed: 28894651 pmcid: 5592083
Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150–3152 (2012).
pubmed: 23060610 pmcid: 3516142
Biswas, A., Fineran, P. C. & Brown, C. M. Accurate computational prediction of the transcribed strand of CRISPR non-coding RNAs. Bioinformatics 30, 1805–1813 (2014).
pubmed: 24578404
Roux, S., Enault, F., Hurwitz, B. L. & Sullivan, M. B. VirSorter: mining viral signal from microbial genomic data. PeerJ 3, e985 (2015).
pubmed: 26038737 pmcid: 4451026
Xie, Z. & Tang, H. ISEScan: automated identification of insertion sequence elements in prokaryotic genomes. Bioinformatics 33, 3340–3347 (2017).
pubmed: 29077810
Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).
pubmed: 20709691
Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).
pubmed: 2231712
Nayfach, S. et al. CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nat. Biotechnol. 39, 578–585 (2021).
pubmed: 33349699
Cook, R. et al. INfrastructure for a PHAge REference. Database: identification of large-scale biases in the current collection of cultured phage genomes. Phage 2, 214–223 (2021).
Bolduc, B. et al. vConTACT: an iVirus tool to classify double-stranded DNA viruses that infect archaea and bacteria. PeerJ 5, e3243 (2017).
pubmed: 28480138 pmcid: 5419219
Bin Jang, H. et al. Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks. Nat. Biotechnol. 37, 632–639 (2019).
Meier-Kolthoff, J. P. & Göker, M. VICTOR: genome-based phylogeny and classification of prokaryotic viruses. Bioinformatics 33, 3396–3404 (2017).
pubmed: 29036289 pmcid: 5860169
Moraru, C., Varsani, A. & Kropinski, A. M. VIRIDIC—a novel tool to calculate the intergenomic similarities of prokaryote-infecting viruses. Viruses 12, 1268 (2020).
pubmed: 33172115 pmcid: 7694805
Meier-Kolthoff, J. P., Auch, A. F., Klenk, H.-P. & Göker, M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinform. 14, 60 (2013).
Lefort, V., Desper, R. & Gascuel, O. FastME 2.0: a comprehensive, accurate, and fast distance-based phylogeny inference program. Mol. Biol. Evol. 32, 2798–2800 (2015).
pubmed: 26130081 pmcid: 4576710
Farris, J. S. Estimating phylogenetic trees from distance matrices. Am. Nat. 106, 645–668 (1972).
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).
pubmed: 14597658 pmcid: 403769
Nishimura, Y. et al. ViPTree: the viral proteomic tree server. Bioinformatics 33, 2379–2380 (2017).
pubmed: 28379287
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
pubmed: 19505943 pmcid: 2723002
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
pubmed: 20110278 pmcid: 2832824
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).
Dufault-Thompson, K., Steffensen, J. L. & Zhang, Y. in Metabolic Network Reconstruction and Modeling: Methods and Protocols (ed. Fondi, M.) 131–150 (Springer, 2018).
Steffensen, J. L., Dufault-Thompson, K. & Zhang, Y. PSAMM: a portable system for the analysis of metabolic models. PLoS Comput. Biol. 12, e1004732–e1004732 (2016).
pubmed: 26828591 pmcid: 4734835
Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).
pubmed: 16731699
Gonnerman, M. C., Benedict, M. N., Feist, A. M., Metcalf, W. W. & Price, N. D. Genomically and biochemically accurate metabolic reconstruction of Methanosarcina barkeri Fusaro, iMG746. Biotechnol. J. 8, 1070–1079 (2013).
pubmed: 23420771
Goyal, N., Widiastuti, H., Karimi, I. A. & Zhou, Z. A genome-scale metabolic model of Methanococcus maripaludis S
pubmed: 24553424
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).
pubmed: 27899662
Huerta-Cepas, J. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 47, D309–D314 (2019).
pubmed: 30418610
Saier, M. H. Jr et al. The transporter classification database (TCDB): recent advances. Nucleic Acids Res. 44, D372–D379 (2016).
pubmed: 26546518
Neidhardt, F. C., Neidhardt, F. C. N., Ingraham, J. L. & Schaechter, M. Physiology of the Bacterial Cell: A Molecular Approach (Sinauer Associates, 1990).
Nelson, D. L., Nelson, R. D. & Cox, M. M. Lehninger Principles of Biochemistry (W.H. Freeman, 2004).
Zhang, Y. & Sievert, S. Pan-genome analyses identify lineage- and niche-specific markers of evolution and adaptation in Epsilonproteobacteria. Front. Microbiol. 5, 110 (2014).
pubmed: 24678308 pmcid: 3958643
Biswas, A., Gagnon, J. N., Brouns, S. J. J., Fineran, P. C. & Brown, C. M. CRISPRTarget: bioinformatic prediction and analysis of crRNA targets. RNA Biol. 10, 817–827 (2013).
pubmed: 23492433 pmcid: 3737339
Crooks, G. E., Hon, G., Chandonia, J.-M. & Brenner, S. E. WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004).
pubmed: 15173120 pmcid: 419797
Schneider, T. D. & Stephens, R. M. Sequence logos: a new way to display consensus sequences. Nucleic Acids Res. 18, 6097–6100 (1990).
pubmed: 2172928 pmcid: 332411
Koboldt, D. C. et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 22, 568–576 (2012).
pubmed: 22300766 pmcid: 3290792
Oberortner, E., Cheng, J.-F., Hillson, N. J. & Deutsch, S. Streamlining the design-to-build transition with build-optimization software tools. ACS Synth. Biol. 6, 485–496 (2017).
pubmed: 28004921
Garamella, J., Marshall, R., Rustad, M. & Noireaux, V. The All E. coli TX-TL Toolbox 2.0: a platform for cell-free synthetic biology. ACS Synth. Biol. 5, 344–355 (2016).
pubmed: 26818434
Shin, J. & Noireaux, V. An E. coli cell-free expression toolbox: application to synthetic gene circuits and artificial cells. ACS Synth. Biol. 1, 29–41 (2012).
pubmed: 23651008
Leenay, R. T. et al. Identifying and visualizing functional PAM diversity across CRISPR–Cas systems. Mol. Cell 62, 137–147 (2016).
pubmed: 27041224 pmcid: 4826307
Ondov, B. D., Bergman, N. H. & Phillippy, A. M. Interactive metagenomic visualization in a web browser. BMC Bioinform. 12, 385 (2011).
Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36, 1925–1927 (2020).
Parks, D. H. et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat. Biotechnol. 36, 996–1004 (2018).
pubmed: 30148503
Parks, D. H. et al. A complete domain-to-species taxonomy for bacteria and archaea. Nat. Biotechnol. 38, 1079–1086 (2020).
pubmed: 32341564
Chen, I.-M. A. et al. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 47, D666–D677 (2019).
pubmed: 30289528
Esser, S. P. & Probst, A. J. Genomes of Ca. Altiarchaeum and Ca. Huberiarchaeum from Crystal Geyser and Horonobe Underground Research Laboratory. figshare https://doi.org/10.6084/m9.figshare.22339555 (2023).
Esser, S. P., Rahlff, J. & Probst, A. J. Viral operational taxonomic units (vOTUs) from Crystal Geyser. figshare https://doi.org/10.6084/m9.figshare.22738568.v1 (2023).
Turzynski, V., Esser, S. P. & Probst, A. J. Fluorescence in situ hybridization images of Ca. Altiarchaeum and Ca. Huberiarchaeu. figshare https://doi.org/10.6084/m9.figshare.22739849 (2023).
Sharrar, A. M. et al. Novel large sulfur bacteria in the metagenomes of groundwater-fed chemosynthetic microbial mats in the Lake Huron Basin. Front. Microbiol. 8, 791 (2017).
pubmed: 28533768 pmcid: 5421297
Bird, J. T., Baker, B. J., Probst, A. J., Podar, M. & Lloyd, K. G. Culture independent genomic comparisons reveal environmental adaptations for Altiarchaeales. Front. Microbiol. 7, 1221 (2016).
pubmed: 27547202 pmcid: 4975002
Posit team. Rstudio: Integrated development environment for R. https://posit.co/ ; version 2023.03.0+386 (2022).

Auteurs

Sarah P Esser (SP)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Janina Rahlff (J)

Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.
Centre for Ecology and Evolution in Microbial Model Systems (EEMiS), Department of Biology and Environmental Science, Linnaeus University, Kalmar, Sweden.

Weishu Zhao (W)

Department of Cell and Molecular Biology, College of the Environment and Life Sciences, University of Rhode Island, Kingston, RI, USA.
Shanghai Jiao Tong University, School of Life Sciences and Biotechnology, International Center for Deep Life Investigation (IC-DLI), Shanghai Jiao Tong University, Shanghai, China.

Michael Predl (M)

Computational Systems Biology, Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria.
Doctoral School in Microbiology and Environmental Science, University of Vienna, Vienna, Austria.

Julia Plewka (J)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Katharina Sures (K)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Franziska Wimmer (F)

Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz-Centre for Infection Research (HZI), Würzburg, Germany.

Janey Lee (J)

DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

Panagiotis S Adam (PS)

Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Julia McGonigle (J)

School of Biological Sciences, University of Utah, Salt Lake City, UT, USA.

Victoria Turzynski (V)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Indra Banas (I)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Katrin Schwank (K)

Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.
University of Regensburg, Biochemistry III, Regensburg, Germany.

Mart Krupovic (M)

Institut Pasteur, Université Paris Cité, CNRS UMR6047, Archaeal Virology Unit, Paris, France.

Till L V Bornemann (TLV)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Perla Abigail Figueroa-Gonzalez (PA)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany.

Jessica Jarett (J)

DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

Thomas Rattei (T)

Computational Systems Biology, Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria.
Doctoral School in Microbiology and Environmental Science, University of Vienna, Vienna, Austria.

Yuki Amano (Y)

Nuclear Fuel Cycle Engineering Laboratories, Japan Atomic Energy Agency, Tokai, Japan.

Ian K Blaby (IK)

DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

Jan-Fang Cheng (JF)

DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

William J Brazelton (WJ)

School of Biological Sciences, University of Utah, Salt Lake City, UT, USA.

Chase L Beisel (CL)

Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz-Centre for Infection Research (HZI), Würzburg, Germany.
Medical faculty, University of Würzburg, Würzburg, Germany.

Tanja Woyke (T)

DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

Ying Zhang (Y)

Department of Cell and Molecular Biology, College of the Environment and Life Sciences, University of Rhode Island, Kingston, RI, USA.

Alexander J Probst (AJ)

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany. alexander.probst@uni-due.de.
Group for Aquatic Microbial Ecology, Environmental Microbiology and Biotechnology, University of Duisburg-Essen, Essen, Germany. alexander.probst@uni-due.de.
Centre of Water and Environmental Research (ZWU), University of Duisburg-Essen, Essen, Germany. alexander.probst@uni-due.de.
Centre of Medical Biotechnology (ZMB), University of Duisburg-Essen, Essen, Germany. alexander.probst@uni-due.de.

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