Abstract
Groundwater ecosystems harbor diverse microbial communities adapted to energy-limited, light-deprived conditions, yet the role of viruses in these environments remains poorly understood. Here, we analyzed 1.24 terabases of metagenomic and metatranscriptomic data from seven wells in the Hainich Critical Zone Exploratory (CZE) to characterize groundwater viromes. We identified 257,252 viral operational taxonomic units (vOTUs) (≥ 5 kb), with 99% novel at order, family and genus levels against global ocean, freshwater and/or other publicly available datasets. In silico host predictions suggest that vOTUs primarily targeted Proteobacteria, Candidate Phyla Radiation (CPR) bacteria, and DPANN archaea, which reflects abundant and active groundwater microbial members. Patterns of virus-host abundance ratios, CRISPR-spacers, and prophage screening suggest the potential for multi-layer interactions involving CPR/DPANN lineages, their hosts, and viruses. Additionally, we identified 289 KEGG metabolic modules, 31.1% of which were targeted by 3378 vOTUs encoded auxiliary metabolic genes (AMGs) linked to carbon, nitrogen, and sulfur cycling. These findings provide a baseline for exploring how viruses influence microbial community dynamics, metabolic reprogramming and nutrient cycling in groundwater.
Data availability
Source data are provided with this paper. The data used for this study have been deposited in the European Nucleotide Archive (ENA). Raw metagenomic sequencing reads from 2019 were deposited under ENA project accession PRJEB36505 (https://www.ebi.ac.uk/ena/browser/view/PRJEB36523), while 2022 sequencing reads were deposited under NCBI project accession PRJNA1236243. Processed data are available through Zenodo, including viral populations (≥5 kb), Dereplicated MAGs, putative AMG genes, putative AMG cluster genes, and identified CRIPSR-Cas spacers (https://doi.org/10.5281/zenodo.17897233). Source data are provided with this paper.
Code availability
Workflows, codes and data related to this manuscript are available at https://github.com/AAdjieP/Groundwater_virome/ or https://doi.org/10.5281/zenodo.17898531.
References
Suttle, S. W. Viruses and nutrient cycles in the sea. Bioscience 49 (1999).
Wilhelm, S. W. & Suttle, C. A. Viruses and nutrient cycles in the sea: viruses play critical roles in the structure and function of aquatic food webs. Bioscience 49, 781–788 (1999).
Suttle, C. A. Marine viruses — major players in the global ecosystem. Nat. Rev. Microbiol. 5, 801–812 (2007).
Jiang, S. C. & Paul, J. H. Gene transfer by transduction in the marine environment. Appl. Environ. Microbiol. 64, 2780–2787 (1998).
Forterre, P. The virocell concept and environmental microbiology. ISME J 7, 233–236 (2013).
Howard-Varona, C. et al. Phage-specific metabolic reprogramming of virocells. ISME J 14, 881–895 (2020).
Howard-Varona, C. et al. Environment-specific virocell metabolic reprogramming. ISME J 18, wrae055 (2024).
Guidi, L. et al. Plankton networks driving carbon export in the oligotrophic ocean. Nature 532, 465–470 (2016).
Gregory, A. C. et al. Marine DNA Viral Macro- and Microdiversity from Pole to Pole. Cell 177, 1109–1123.e14 (2019).
Dominguez-Huerta, G. et al. Diversity and ecological footprint of Global Ocean RNA viruses. 376, 1202–1208 (2022).
Sullivan, M. B. et al. Prevalence and evolution of core photosystem II genes in marine cyanobacterial viruses and their hosts. PLoS Biol 4, e234 (2006).
Zimmerman, A. E. et al. Metabolic and biogeochemical consequences of viral infection in aquatic ecosystems. Nat. Rev. Microbiol. 18, 21–34 (2020).
Rodríguez-Ramos, J. et al. Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream. Front. Microbiomes 2, 1199766 (2023).
Elbehery, A. H. A. & Deng, L. Insights into the global freshwater virome. Front. Microbiol. 13, 953500 (2022).
Overholt, W. A. et al. Carbon fixation rates in groundwater similar to those in oligotrophic marine systems. Nat. Geosci. 15, 561–567 (2022).
Danczak, R. E. et al. Members of the Candidate Phyla Radiation are functionally differentiated by carbon- and nitrogen-cycling capabilities. Microbiome 5, 112 (2017).
Taubert, M. et al. Bolstering fitness via CO2 fixation and organic carbon uptake: mixotrophs in modern groundwater. ISME J 16, 1153–1162 (2022).
Herrmann, M. et al. Large fractions of CO 2-fixing microorganisms in pristine limestone aquifers appear to be involved in the oxidation of reduced sulfur and nitrogen compounds. Appl Environ Microbiol 81, 2384–2394 (2015).
Krüger, M. et al. Differential contribution of nitrifying prokaryotes to groundwater nitrification. ISME J. 17, 1601–1611 (2023).
Bell, E. et al. Active sulfur cycling in the terrestrial deep subsurface. ISME J. 14, 1260–1272 (2020).
Wegner, C.-E. et al. Biogeochemical regimes in shallow aquifers reflect the metabolic coupling of the elements nitrogen, sulfur, and carbon. Appl. Environ. Microbiol. 85, e02346–18 (2019).
Mouchos, E. M. et al. Geochemical cycling in aquifers contributes to the transport, storage and transfer of anthropogenically-derived phosphorus to surface waters. Front. Environ. Sci. 10, 932566 (2022).
Hernsdorf, A. W. et al. Potential for microbial H2 and metal transformations associated with novel bacteria and archaea in deep terrestrial subsurface sediments. ISME J. 11, 1915–1929 (2017).
Griebler, C. & Lueders, T. Microbial biodiversity in groundwater ecosystems. Freshw. Biol. 54, 649–677 (2009).
Tian, R. et al. Small and mighty: adaptation of superphylum Patescibacteria to groundwater environment drives their genome simplicity. Microbiome 8, 51 (2020).
Méheust, R., Burstein, D., Castelle, C. J. & Banfield, J. F. The distinction of CPR bacteria from other bacteria based on protein family content. Nat. Commun. 10, 4173 (2019).
He, C. et al. Genome-resolved metagenomics reveals site-specific diversity of episymbiotic CPR bacteria and DPANN archaea in groundwater ecosystems. Nat. Microbiol. 6, 354–365 (2021).
Yan, L. et al. Groundwater bacterial communities evolve over time in response to recharge. Water Res. 201, 117290 (2021).
Chaudhari, N. M., Pérez-Carrascal, O. M., Overholt, W. A., Totsche, K. U. & Küsel, K. Genome streamlining in Parcubacteria transitioning from soil to groundwater. Environ. Microbiome 19, 41 (2024).
Herrmann, M. et al. Predominance of Cand. Patescibacteria in groundwater is caused by their preferential mobilization from soils and flourishing under oligotrophic conditions. Front. Microbiol. 10, 1407 (2019).
Prangishvili, D. et al. The enigmatic archaeal virosphere. Nat. Rev. Microbiol. 15, 724–739 (2017).
Niazi, H. et al. Global peak water limit of future groundwater withdrawals. Nat. Sustain. 7, 413–422 (2024).
Wunsch, A., Liesch, T. & Broda, S. Deep learning shows declining groundwater levels in Germany until 2100 due to climate change. Nat. Commun. 13, 1221 (2022).
Kohlhepp, B. et al. Aquifer configuration and geostructural links control the groundwater quality in thin-bedded carbonate–siliciclastic alternations of the Hainich CZE, central Germany. Hydrol. Earth Syst. Sci. 21, 6091–6116 (2017).
Zhong, Z.-P. et al. Lower viral evolutionary pressure under stable versus fluctuating conditions in subzero Arctic brines. Microbiome 11, 174 (2023).
Roux, S. et al. Minimum Information about an Uncultivated Virus Genome (MIUViG). Nat. Biotechnol. 37, 29–37 (2019).
Camargo, A. P. et al. IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata. Nucleic Acids Res. 51, D733–D743 (2023).
Gios, E., Mosley, O. E., Hoggard, M. & Handley, K. M. High niche specificity and host genetic diversity of groundwater viruses. ISME J. 18, wrae035 (2024).
Holmfeldt, K. et al. The Fennoscandian Shield deep terrestrial virosphere suggests slow-motion ‘boom and burst’ cycles. Commun. Biol. 4, 307 (2021).
Wu, Z. et al. Unveiling the unknown viral world in groundwater. Nat. Commun. 15, 6788 (2024).
Tian, F. et al. Prokaryotic-virus-encoded auxiliary metabolic genes throughout the global oceans. Microbiome 12, 159 (2024).
Zhou, Y.-L. et al. Ecogenomics reveals viral communities across the Challenger Deep oceanic trench. Commun. Biol. 5, 1055 (2022).
Braga, L. P. P. et al. Viruses direct carbon cycling in lake sediments under global change. Proc. Natl. Acad. Sci. USA 119, e2202261119 (2022).
Camargo, A. P. et al. Identification of mobile genetic elements with geNomad. Nat. Biotechnol. 42, 1303–1312 (2023).
Bin Jang, H. et al. Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks. Nat. Biotechnol. 37, 632–639 (2019).
Bolduc, B. et al. Machine learning enables scalable and systematic hierarchical virus taxonomy. Nat. Biotechnol. 1–10. https://doi.org/10.1038/s41587-025-02946-9 (2025).
Gregory, A. C. et al. The gut virome database reveals age-dependent patterns of virome diversity in the human gut. Cell Host Microbe 28, 724–740.e8 (2020).
Ma, B. et al. Biogeographic patterns and drivers of soil viromes. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-024-02347-2 (2024).
Pruitt, K. D., Tatusova, T. & Maglott, D. R. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res 35, D61–D65 (2007).
Yan, M. et al. Interrogating the viral dark matter of the rumen ecosystem with a global virome database. Nat. Commun. 14, 5254 (2023).
Emerson, J. B. et al. Host-linked soil viral ecology along a permafrost thaw gradient. Nat. Microbiol. 3, 870–880 (2018).
Sieradzki, E. T., Ignacio-Espinoza, J. C., Needham, D. M., Fichot, E. B. & Fuhrman, J. A. Dynamic marine viral infections and major contribution to photosynthetic processes shown by spatiotemporal picoplankton metatranscriptomes. Nat. Commun. 10, 1169 (2019).
Denison, E. R., Zepernick, B. N., McKay, R. M. L. & Wilhelm, S. W. Metatranscriptomic analysis reveals dissimilarity in viral community activity between an ice-free and ice-covered winter in Lake Erie. mSystems 9, e00753–24 (2024).
Sun, C. L. et al. Virus ecology and 7-year temporal dynamics across a permafrost thaw gradient. Environ. Microbiol. 26, e16665 (2024).
Trubl, G. et al. Active virus-host interactions at sub-freezing temperatures in Arctic peat soil. Microbiome 9, 208 (2021).
Wang, H. et al. Groundwater microbiomes balance resilience and vulnerability to hydroclimatic extremes. Commun. Earth Environ. 6, 683 (2025).
Chaudhari, N. M. et al. The economical lifestyle of CPR bacteria in groundwater allows little preference for environmental drivers. Environ. Microbiome 16, 24 (2021).
Hart, S. P., Schreiber, S. J. & Levine, J. M. How variation between individuals affects species coexistence. Ecol. Lett. 19, 825–838 (2016).
Jurgensen, S. K. et al. Viral community analysis in a marine oxygen minimum zone indicates increased potential for viral manipulation of microbial physiological state. ISME J. 16, 972–982 (2022).
Brüwer, J. D. et al. Globally occurring pelagiphage infections create ribosome-deprived cells. Nat. Commun. 15, 3715 (2024).
Roux, S. et al. iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria. PLoS Biol. 21, e3002083 (2023).
Roux, S. & Brum, J. R. Counting dots or counting reads? Complementary approaches to estimate virus-to-microbe ratios. ISME J. 17, 1521–1522 (2023).
Liu, J., Jaffe, A. L., Chen, L., Bor, B. & Banfield, J. F. Host translation machinery is not a barrier to phages that interact with both CPR and non-CPR bacteria. MBio 14, e01766–23 (2023).
Zhou, Y. et al. Viruses and virus satellites of haloarchaea and their nanosized DPANN symbionts reveal intricate nested interactions. Nat. Microbiol. https://doi.org/10.1038/s41564-025-02149-7 (2025).
Buderka, F. et al. Culture- and genome-based characterization of a tripartite interaction between patescibacterial epibionts, methylotrophic proteobacteria, and a jumbo phage in freshwater ecosystems. Preprint at https://doi.org/10.1101/2024.03.08.584096 (2024).
Wu, Z., Liu, S. & Ni, J. Metagenomic characterization of viruses and mobile genetic elements associated with the DPANN archaeal superphylum. Nat. Microbiol. 9, 3362–3375 (2024).
Coenen, A. R. & Weitz, J. S. Limitations of correlation-based inference in complex virus-microbe communities. mSystems 3, https://doi.org/10.1128/msystems.00084-18 (2018).
Tang, M., Chen, Q., Zhong, H., Liu, S. & Sun, W. CPR bacteria and DPANN archaea play pivotal roles in response of microbial community to antibiotic stress in groundwater. Water Res. 251, 121137 (2024).
Burstein, D. et al. Major bacterial lineages are essentially devoid of CRISPR-Cas viral defence systems. Nat. Commun. 7, 10613 (2016).
Roux, S. et al. Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses. Nature 537, 689–693 (2016).
Kieft, K. et al. Ecology of inorganic sulfur auxiliary metabolism in widespread bacteriophages. Nat. Commun. 12, 3503 (2021).
Shaffer, M. et al. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 48, 8883–8900 (2020).
Pratama, A. A. et al. Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation. PeerJ 9, e11447 (2021).
Zhou, Z. et al. Unravelling viral ecology and evolution over 20 years in a freshwater lake. Nat. Microbiol. 10, 231–245 (2025).
Hurwitz, B. L., Hallam, S. J. & Sullivan, M. B. Metabolic reprogramming by viruses in the sunlit and dark ocean. Genome Biol. 14, R123 (2013).
Kieft, K. et al. Virus-associated organosulfur metabolism in human and environmental systems. Cell Rep. 36, 109471 (2021).
Kulongoski, J. T. & McMahon, P. B. Methane emissions from groundwater pumping in the USA. Npj Clim. Atmos. Sci. 2, 11 (2019).
Mustafa, O., Thornton, S. F., Bau, D. & Mahmmud, R. A review of the occurrence, fate, and transport of SARS‑CoV‑2 in the aqueous environment, with specific reference to groundwater. Environ. Earth Sci. 84, 251 (2025).
Fromm, A. et al. Single-cell RNA-seq of the rare virosphere reveals the native hosts of giant viruses in the marine environment. Nat. Microbiol. 9, 1619–1629 (2024).
Bickhart, D. M. et al. Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation. Genome Biol. 20, 153 (2019).
Sakowski, E. G. et al. Interaction dynamics and virus–host range for estuarine actinophages captured by epicPCR. Nat. Microbiol. 6, 630–642 (2021).
Grodner, B. et al. Spatial mapping of mobile genetic elements and their bacterial hosts in complex microbiomes. Nat. Microbiol. 9, 2262–2277 (2024).
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).
Man, D. K. W. et al. Enrichment of different taxa of the enigmatic candidate phyla radiation bacteria using a novel picolitre droplet technique. ISME Commun. 4, ycae080 (2024).
Pérez-Carrascal, O. M., Pratama, A. A., Sullivan, M. B. & Küsel, K. Unveiling plasmid diversity and functionality in pristine groundwater. Environ. Microbiome 20, 42 (2025).
Guo, J. et al. Mobile genetic elements that shape microbial diversity and functions in thawing permafrost soils. Preprint at https://doi.org/10.1101/2025.02.12.637893 (2025).
Régimbeau, A. et al. Planetary-scale heterotrophic microbial community modeling assesses metabolic synergy and viral impacts. bioRxiv. https://doi.org/10.1101/2025.02.13.638167 (2025).
Taubert, M. et al. Tracking active groundwater microbes with D2O labelling to understand their ecosystem function. Environ. Microbiol. 20, 369–384 (2018).
Lehmann, R. & Totsche, K. U. Multi-directional flow dynamics shape groundwater quality in sloping bedrock strata. J. Hydrol. 580, 124291 (2020).
Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. A. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 27, 824–834 (2017).
Graham, E. D., Heidelberg, J. F. & Tully, B. J. BinSanity: unsupervised clustering of environmental microbial assemblies using coverage and affinity propagation. PeerJ 5, e3035 (2017).
Wu, Y.-W., Simmons, B. A. & Singer, S. W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics 32, 605–607 (2016).
Kang, D. D. et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 7, e7359 (2019).
Uritskiy, G. V., DiRuggiero, J. & Taylor, J. MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis. Microbiome 6, 158 (2018).
Olm, M. R., Brown, C. T., Brooks, B. & Banfield, J. F. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 11, 2864–2868 (2017).
Eren, A. M. et al. Community-led, integrated, reproducible multi-omics with anvi’o. Nat. Microbiol. 6, 3–6 (2020).
Parks, D. H. et al. Recovery of nearly 8000 metagenome-assembled genomes substantially expands the tree of life. Nat. Microbiol. 2, 1533–1542 (2017).
The Genome Standards Consortium et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat. Biotechnol. 35, 725–731 (2017).
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).
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).
Aroney, S. T. N. et al. CoverM: read alignment statistics for metagenomics. Bioinformatics 41, btaf147 (2025).
Li, D. et al. MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods 102, 3–11 (2016).
Roux, S., Emerson, J. B., Eloe-Fadrosh, E. A. & Sullivan, M. B. Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity. PeerJ 5, e3817 (2017).
Guo, J. et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome 9, 37 (2021).
Ren, J. et al. Identifying viruses from metagenomic data using deep learning. Quant. Biol. 8, 64–77 (2020).
Kieft, K., Zhou, Z. & Anantharaman, K. VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences. Microbiome 8, 90 (2020).
Nayfach, S. et al. CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nat. Biotechnol. 39, 578–585 (2021).
Hegarty, B. et al. Benchmarking informatics approaches for virus discovery: caution is needed when combining in silico identification methods. mSystems 9, e01105-23 (2024).
Steinegger, M. & Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 35, 1026–1028 (2017).
Dobrindt, U., Hochhut, B., Hentschel, U. & Hacker, J. Genomic islands in pathogenic and environmental microorganisms. Nat. Rev. Microbiol. 2, 414–424 (2004).
Bertelli, C., Tilley, K. E. & Brinkman, F. S. L. Microbial genomic island discovery, visualization and analysis. Brief Bioinform. 20, 1685–1698 (2019).
Conway, J. R., Lex, A. & Gehlenborg, N. UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics 33, 2938–2940 (2017).
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag New York).
Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003).
Gregory, A. C. et al. MetaPop: a pipeline for macro- and microdiversity analyses and visualization of microbial and viral metagenome-derived populations. Microbiome 10, 49 (2022).
Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119 (2010).
Dion, M. B. et al. Streamlining CRISPR spacer-based bacterial host predictions to decipher the viral dark matter. Nucleic Acids Res. 49, 3127–3138 (2021).
Warner, H. R., Johnson, L. K. & Snustad, D. P. Early events after infection of Escherichia coli by bacteriophage T5. III. Inhibition of uracil-DNA glycosylase activity. J. Virol. 33, 535–538 (1980).
Warren, R. A. J. Modified bases in Bacteriophage DNAs. Annu. Rev. Microbiol. 34, 137–158 (1980).
Markine-Goriaynoff, N. et al. Glycosyltransferases encoded by viruses. J. Gen. Virol. 85, 2741–2754 (2004).
Young, P., Ohman, M. & Sjöberg, B. M. Bacteriophage T4 gene 55.9 encodes an activity required for anaerobic ribonucleotide reduction. J. Biol. Chem. 269, 27815–27818 (1994).
Kanehisa, M., Sato, Y. & Kawashima, M. KEGG mapping tools for uncovering hidden features in biological data. Protein Sci. 31, 47–53 (2022).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).
Iqbal, A., Duitama, C., Metge, F., Rosskopp, D. & Boucas, J. Flaski. Preprint at (2021).
Quinn, T. P., Richardson, M. F., Lovell, D. & Crowley, T. M. propr: an R-package for identifying proportionally abundant features using compositional data analysis. Sci. Rep. 7, 16252 (2017).
Otasek, D., Morris, J. H., Bouças, J., Pico, A. R. & Demchak, B. Cytoscape automation: empowering workflow-based network analysis. Genome Biol. 20, 185 (2019).
Acknowledgements
Akbar Adjie Pratama acknowledges financial support provided by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through Germany’s Excellence Strategy (EXC 2051, Project-ID 390713860), awarded to K.K. and M.B.S. Additional support was received from the Collaborative Research Centre AquaDiva (CRC 1076, Project-ID 218627073) awarded to K.K., provided by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). Part of this work was enabled by funding provided to M.B.S. by the U.S. Department of Energy, award #DE-SC0023307. The authors would like to thank Heiko Minkmar, Falko Gutmann, René Maskos, and Stefan Riedel for groundwater sampling and on-site measurements/sample preparation. The authors would also like to thank Olivier Zablocki for his input on the manuscript. Thank you to Benjamin Bolduc for his help in interpreting the virus taxonomic analysis.
Funding
Open Access funding enabled and organized by Projekt DEAL.
Author information
Authors and Affiliations
Contributions
A.A.P., K.K., and M.B.S. created the study design. O.P.C. and A.A.P. collected all datasets. O.P.C. and A.A.P. performed the data analysis and visualization. A.A.P., O.P.C., M.B.S., and K.K. contributed to the scientific discussion and wrote the manuscript. All authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Communications thanks Meng Li, and the other, anonymous, reviewers for their contribution to the peer review of this work. A peer review file is available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Source data
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Pratama, A.A., Pérez-Carrascal, O., Sullivan, M.B. et al. Diversity and ecological roles of hidden viral players in groundwater microbiomes. Nat Commun (2026). https://doi.org/10.1038/s41467-026-68914-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41467-026-68914-2
