Cited by 44Bacteriophages and microbial interactionsEvolution and Genetic DynamicsPlant and Fungal Interactions Research

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Highly host-linked viromes in the built environment possess habitat-dependent diversity and functions for potential virus-host coevolution

Open access

Published version of a preprint

Abstract

Viruses in built environments (BEs) raise public health concerns, yet they are generally less studied than bacteria. To better understand viral dynamics in BEs, this study assesses viromes from 11 habitats across four types of BEs with low to high occupancy. The diversity, composition, metabolic functions, and lifestyles of the viromes are found to be habitat dependent. Caudoviricetes species are ubiquitous on surface habitats in the BEs, and some of them are distinct from those present in other environments. Antimicrobial resistance genes are identified in viruses inhabiting surfaces frequently touched by occupants and in viruses inhabiting occupants’ skin. Diverse CRISPR/Cas immunity systems and anti-CRISPR proteins are found in bacterial hosts and viruses, respectively, consistent with the strongly coupled virus–host links. Evidence of viruses potentially aiding host adaptation in a specific-habitat manner is identified through a unique gene insertion. This work illustrates that virus–host interactions occur frequently in BEs and that viruses are integral members of BE microbiomes.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-023-38400-0

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 101

  1. Manrique, P., Dills, M. & Young, M. J. The human gut phage community and its implications for health and disease. Viruses 9, 141 (2017). · DOI
  2. Li, Z. et al. Deep sea sediments associated with cold seeps are a subsurface reservoir of viral diversity. ISME J. 15, 2366–2378 (2021). · DOI
  3. Coutinho, F. H. et al. Marine viruses discovered via metagenomics shed light on viral strategies throughout the oceans. Nat. Commun. 8, 15955 (2017). · DOI
  4. Trubl, G. et al. Active virus-host interactions at sub-freezing temperatures in Arctic peat soil. Microbiome 9, 208 (2021). · DOI
  5. Gilbert, J. A. & Stephens, B. Microbiology of the built environment. Nat. Rev. Microbiol. 16, 661–670 (2018). · DOI
  6. Lax, S. et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science 345, 1048–1052 (2014). · DOI
  7. Fouquier, J., Schwartz, T. & Kelley, S. Rapid assemblage of diverse environmental fungal communities on public restroom floors. Indoor Air 26, 869–879 (2016). · DOI
  8. Prussin, A. J., Garcia, E. B. & Marr, L. C. Total virus and bacteria concentrations in indoor and outdoor air. Environ. Sci. Technol. Lett. 2, 84–88 (2015). · DOI · Paper page
  9. Tong, X. et al. Metagenomic insights into the microbial communities of inert and oligotrophic outdoor pier surfaces of a coastal city. Microbiome 9, 213 (2021). · DOI
  10. Cantú, V. J. et al. Implementation of practical surface SARS-CoV-2 surveillance in school settings. mSystems 7, e00103–e00122 (2022).
  11. Sacchetto, L. et al. Neighbor danger: Yellow fever virus epizootics in urban and urban-rural transition areas of Minas Gerais state, during 2017-2018 yellow fever outbreaks in Brazil. PLOS Negl. Trop. Dis. 14, e0008658 (2020). · DOI
  12. Prussin, A. J. et al. Seasonal dynamics of DNA and RNA viral bioaerosol communities in a daycare center. Microbiome 7, 53 (2019). · DOI
  13. Gibbons, S. M. et al. Ecological succession and viability of human-associated microbiota on restroom surfaces. Appl. Environ. Microbiol. 81, 765–773 (2015). · DOI
  14. Whon, T. W. et al. Metagenomic characterization of airborne viral DNA diversity in the near-surface atmosphere. J. Virol. 86, 8221–8231 (2012). · DOI
  15. Danko, D. et al. A global metagenomic map of urban microbiomes and antimicrobial resistance. Cell 184, 3376–3393 (2021). · DOI
  16. He, T., Li, H. & Zhang, X. Deep-sea hydrothermal vent viruses compensate for microbial metabolism in virus-host interactions. MBio 8, e00893–17 (2017). · DOI
  17. Emerson, J. B. et al. Host-linked soil viral ecology along a permafrost thaw gradient. Nat. Microbiol. 3, 870–880 (2018). · DOI
  18. Coclet, C. & Roux, S. Global overview and major challenges of host prediction methods for uncultivated phages. Curr. Opin. Virol. 49, 117–126 (2021). · DOI
  19. Desfarges, S. & Ciuffi, A. in Viruses: Essential Agents of Life (ed. Witzany, G.) 147–175 (Springer Netherlands, 2012). · DOI
  20. Suttle, C. A. Viruses in the sea. Nature 437, 356–361 (2005). · DOI
  21. Jian, H. et al. Diversity and distribution of viruses inhabiting the deepest ocean on Earth. ISME J. 15, 3094–3110 (2021). · DOI
  22. Brown, T. L., Charity, O. J. & Adriaenssens, E. M. Ecological and functional roles of bacteriophages in contrasting environments: marine, terrestrial and human gut. Curr. Opin. Microbiol. 70, 102229 (2022). · DOI
  23. Doron, S. et al. Systematic discovery of antiphage defense systems in the microbial pangenome. Science 359, eaar4120 (2018). · DOI
  24. Münch, P. C., Franzosa, E. A., Stecher, B., McHardy, A. C. & Huttenhower, C. Identification of natural CRISPR systems and targets in the human microbiome. Cell Host Microbe 29, 94–106.e4 (2021). · DOI
  25. Landsberger, M. et al. Anti-CRISPR phages cooperate to overcome CRISPR-Cas Immunity. Cell 174, 908–916 (2018). · DOI
  26. Burstein, D. et al. Major bacterial lineages are essentially devoid of CRISPR-Cas viral defence systems. Nat. Commun. 7, 10613 (2016). · DOI
  27. Guo, J. et al. VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses. Microbiome 9, 37 (2021). · DOI
  28. Ren, J. et al. Identifying viruses from metagenomic data using deep learning. Quant. Biol. 8, 64–77 (2020). · DOI
  29. 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). · DOI · Paper page
  30. Nayfach, S. et al. Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome. Nat. Microbiol. 6, 960–970 (2021). · DOI · Paper page
  31. Boeckman, J. et al. Sheep in wolves’ clothing: Temperate T7-like bacteriophages and the origins of the Autographiviridae. Virology 568, 86–100 (2022). · DOI
  32. Sherier, A. J., Woerner, A. E. & Budowle, B. Population informative markers selected using Wright’s fixation index and machine learning improves human identification using the skin microbiome. Appl. Environ. Microbiol. 87, e01208–e01221 (2021). · DOI
  33. Duponchel, S. & Fischer, M. G. Viva lavidaviruses! Five features of virophages that parasitize giant DNA viruses. PLoS Pathog. 15, e1007592 (2019). · DOI
  34. Ryndock, E. J. & Meyers, C. A risk for non-sexual transmission of human papillomavirus? Expert. Rev. Anti. Infect. Ther. 12, 1165–1170 (2014). · DOI
  35. Saheb Kashaf, S. et al. Integrating cultivation and metagenomics for a multi-kingdom view of skin microbiome diversity and functions. Nat. Microbiol. 7, 169–179 (2022). · DOI
  36. Gregory, A. C. et al. Marine DNA viral macro- and microdiversity from pole to pole. Cell 177, 1109–1123.e14 (2019). · DOI
  37. Enault, F. et al. Phages rarely encode antibiotic resistance genes: a cautionary tale for virome analyses. ISME J. 11, 237–247 (2017). · DOI
  38. El-Gebali, S. et al. The Pfam protein families database in 2019. Nucleic Acids Res. 47, D427–D432 (2019). · DOI · Paper page
  39. Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2020). · DOI · Paper page
  40. Gibson, M. K., Forsberg, K. J. & Dantas, G. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology. ISME J. 9, 207–216 (2015). · DOI
  41. Feldgarden, M. et al. AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence. Sci. Rep. 11, 12728 (2021). · DOI
  42. Feldgarden, M. et al. Validating the AMRFinder tool and resistance gene database by using antimicrobial resistance genotype–phenotype correlations in a collection of isolates. Antimicrob. Agents Chemother. 63, e00483–19 (2019). (2019). · DOI
  43. Lim, K. T., Hanifah, Y. A. & Yusof, M. Y. M. ermA, ermC, tetM and tetK are essential for erythromycin and tetracycline resistance among methicillin-resistant Staphylococcus aureus strains isolated from a tertiary hospital in Malaysia. Indian J. Med. Microbiol. 30, 203–207 (2012). · DOI
  44. Schouten, M. A. et al. Prevalence of vancomycin-resistant enterococci in Europe. Eur. J. Clin. Microbiol. Infect. Dis. 19, 816–822 (2000). · DOI
  45. Roberts, M. C. Update on acquired tetracycline resistance genes. FEMS Microbiol. Lett. 245, 195–203 (2005). · DOI · Paper page
  46. Galiez, C., Siebert, M., Enault, F., Vincent, J. & Söding, J. WIsH: who is the host? Predicting prokaryotic hosts from metagenomic phage contigs. Bioinformatics 33, 3113–3114 (2017). · DOI
  47. Taxiarchi, C. et al. A genetically encoded anti-CRISPR protein constrains gene drive spread and prevents population suppression. Nat. Commun. 12, 3977 (2021). · DOI
  48. Wang, J. et al. PaCRISPR: a server for predicting and visualizing anti-CRISPR proteins. Nucleic Acids Res. 48, W348–W357 (2020). · DOI
  49. Lu, S. et al. CDD/SPARCLE: the conserved domain database in 2020. Nucleic Acids Res. 48, D265–D268 (2020). · DOI
  50. Osuna, B. A. et al. Critical anti-CRISPR locus repression by a bi-functional Cas9 inhibitor. Cell Host Microbe 28, 23–30 (2020). · DOI
  51. Young, R. Phage lysis: three steps, three choices, one outcome. J. Microbiol. 52, 243–258 (2014). · DOI
  52. Pálinkás, H. L. et al. CRISPR/Cas9-mediated knock-out of dUTPase in mice leads to early embryonic lethality. Biomolecules 9, 136 (2019). · DOI
  53. Torrents, E. Ribonucleotide reductases: essential enzymes for bacterial life. Front. Cell. Infect. Microbiol. 4, 52 (2014). · DOI
  54. Xu, Y., Zhang, R. & Jiao, N. Complete genome sequence of Paracoccus marcusii phage vB_PmaS-R3 isolated from the South China Sea. Stand Genom. Sci. 10, 94 (2015). · DOI
  55. Kredich, N. M. Biosynthesis of cysteine. EcoSal Plus 3, https://doi.org/10.1128/ecosalplus.3.6.1.11 (2008). · DOI
  56. Neuwald, A. F. et al. cysQ, a gene needed for cysteine synthesis in Escherichia coli K-12 only during aerobic growth. J. Bacteriol. 174, 415–425 (1992). · DOI
  57. Adams, R. I., Bateman, A. C., Bik, H. M. & Meadow, J. F. Microbiota of the indoor environment: a meta-analysis. Microbiome 3, 49 (2015). · DOI
  58. López-Leal, G. et al. Mining of thousands of prokaryotic genomes reveals high abundance of prophages with a strictly narrow host range. mSystems 7, e00326–22 (2022). · DOI
  59. Gohli, J. et al. The subway microbiome: seasonal dynamics and direct comparison of air and surface bacterial communities. Microbiome 7, 160 (2019). · DOI
  60. Vignuzzi, M. & López, C. B. Defective viral genomes are key drivers of the virus–host interaction. Nat. Microbiol. 4, 1075–1087 (2009). · DOI
  61. Bobay, L. M., Rocha, E. P. & Touchon, M. The adaptation of temperate bacteriophages to their host genomes. Mol. Biol. Evol. 30, 737–751 (2013). · DOI
  62. Chen, R., Wang, H. & Mansky, L. M. Roles of uracil-DNA glycosylase and dUTPase in virus replication. J. Gen. Virol. 83, 2339–2345 (2002). · DOI
  63. Mara, P. et al. Viral elements and their potential influence on microbial processes along the permanently stratified Cariaco Basin redox- cline. ISME J. 14, 3079–3092 (2020). · DOI
  64. Okazaki, Y., Nishimura, Y., Yoshida, T., Ogata, H. & Nakano, S. I. Genome-resolved viral and cellular metagenomes revealed potential key virus-host interactions in a deep freshwater lake. Environ. Microbiol. 21, 4740–4754 (2019). · DOI
  65. McCarty, R. M., Somogyi, A., Lin, G., Jacobsen, N. E. & Bandarian, V. The deazapurine biosynthetic pathway revealed: in vitro enzymatic synthesis of PreQ(0) from guanosine 5’-triphosphate in four steps. Biochemistry 48, 3847–3852 (2009). · DOI
  66. Middelboe, M. Bacterial growth rate and marine virus-host dynamics. Microb. Ecol. 40, 114–124 (2000). · DOI
  67. Calero-Cáceres, W. & Muniesa, M. Persistence of naturally occurring antibiotic resistance genes in the bacteria and bacteriophage fractions of wastewater. Water Res. 95, 11–18 (2016). · DOI
  68. Pfeifer, E., Bonnin, R. A. & Rocha, E. P. C. Phage-plasmids spread antibiotic resistance genes through infection and lysogenic conversion. mBio 13, e01851–22 (2022). · DOI
  69. Moon, K. et al. Freshwater viral metagenome reveals novel and functional phage-borne antibiotic resistance genes. Microbiome 8, 75 (2020). · DOI
  70. Shen, J., Zhou, J., Xu, Y. & Xiu, Z. Prophages contribute to genome plasticity of Klebsiella pneumoniae and may involve the chromosomal integration of ARGs in CG258. Genomics 112, 998–1010 (2020). · DOI
  71. Hynes, A. P. et al. An anti-CRISPR from a virulent streptococcal phage inhibits Streptococcus pyogenes Cas9. Nat. Microbiol. 2, 1374–1380 (2017). · DOI
  72. Callanan, J. et al. Biases in viral metagenomics-based detection, cataloguing and quantification of bacteriophage genomes in human faeces, a review. Microorganisms 9, 524 (2021). · DOI
  73. Johansen, J. et al. Genome binning of viral entities from bulk metagenomics data. Nat. Commun. 13, 965 (2022). · DOI
  74. Chng, K. R. et al. Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment. Nat. Med. 26, 941–951 (2020). · DOI
  75. Wilkins, D. et al. Diurnal variation in the human skin microbiome affects accuracy of forensic microbiome matching. Microbiome 9, 129 (2021). · DOI
  76. Leung, M. H. Y. et al. Characterization of the public transit air microbiome and resistome reveals geographical specificity. Microbiome 9, 112 (2021). · DOI
  77. Schubert, M., Lindgreen, S. & Orlando, L. AdapterRemoval v2: rapid adapter trimming, identification, and read merging. BMC Res. Notes 9, 88 (2016). · DOI
  78. Uritskiy, G. V., DiRuggiero, J. & Taylor, J. MetaWRAP—a flexible pipeline for genome- resolved metagenomic data analysis. Microbiome 6, 158 (2018). · DOI · Paper page
  79. Nayfach, S. et al. CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nat. Biotechnol. 39, 578–585 (2021). · DOI
  80. Arndt, D. et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 44, W16–W21 (2016). · DOI
  81. 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). · DOI
  82. Enright, A. J., Van Dongen, S. & Ouzounis, C. A. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 30, 1575–1584 (2002). · DOI
  83. Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinform. 11, 1–11 (2010). · DOI
  84. Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003). · DOI
  85. Low, S. J., Džunková, M., Chaumeil, P. A., Parks, D. H. & Hugenholtz, P. Evaluation of a concatenated protein phylogeny for classification of tailed double-stranded DNA viruses belonging to the order Caudovirales. Nat. Microbiol. 4, 1306–1315 (2019). · DOI
  86. Capella-Gutierrez, S., Silla-Martinez, J. M. & Gabaldon, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009). · DOI
  87. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650 (2009). · DOI · Paper page
  88. Haft, D. H. The TIGRFAMs database of protein families. Nucleic Acids Res. 31, 371–373 (2003). · DOI · Paper page
  89. Paez-Espino, D. et al. Uncovering Earth’s virome. Nature 536, 425–430 (2016). · DOI
  90. Alcock, B. P. et al. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res. 48, D517–D255 (2019).
  91. Shaffer, M. et al. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 48, 8883–8900 (2020). · DOI
  92. Benler, S. et al. Thousands of previously unknown phages discovered in whole-community human gut metagenomes. Microbiome 9, 78 (2021). · DOI
  93. Hauser, M., Steinegger, M. & Soding, J. MMseqs software suite for fast and deep clustering and searching of large protein sequence sets. Bioinformatics 32, 1323–1330 (2016). · DOI
  94. Deorowicz, S., Debudaj-Grabysz, A. & Gudyś, A. FAMSA: Fast and accurate multiple sequence alignment of huge protein families. Sci. Rep. 6, 1–13 (2016). · DOI
  95. 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). · DOI · Paper page
  96. Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014). · DOI
  97. 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). · DOI
  98. 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). · DOI
  99. 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). · DOI
  100. Camacho, C. et al. BLAST+: architecture and applications. BMC Bioinform. 10, 421 (2009). · DOI · Paper page
  101. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003). · DOI · Paper page

Metadata

Authors
Du, S., Tong, X., Lai, A. C. K., Chan, C. K., Mason, C. E., & Lee, P. K. H.
Affiliations
  • City University of Hong Kong (HK)
  • Weill Cornell Medicine (US)
Corresponding author
Lee, Patrick K. H.
Venue
Nature Communications
Published
2023-05-09
Volume
14
Issue
1
Pages
2676-2676
ISSN
2041-1723 (ISSN-L)
OpenAlex
W4376132774
Cited by
44
References
2
Citations by year
2026: 12 · 2025: 15 · 2024: 16 · 2023: 1
FWCI
7.11
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • CityU Scholars (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
Funders
  • Impact Fund
  • National Institutes of Health
  • National Institute on Drug Abuse (U01DA053941)
  • National Institute of Allergy and Infectious Diseases (R01AI151059)
Topics
  • Life Sciences › Immunology and Microbiology › Virology › Bacteriophages and microbial interactions
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Life Sciences › Immunology and Microbiology › Virology › Plant and Fungal Interactions Research
Keywords
host-virus coevolution, host-virus interaction, Caudoviricetes, antimicrobial resistance genes, CRISPR-Cas, anti-CRISPR proteins, built environment microbiome
MeSH terms
Built Environment, Virome, Alkanesulfonic Acids, Microbiota

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review