Deciphering the hidden role of soil viruses in nitrogen cycling revealed by metagenomic stable isotope probing

Chen Liu; Hanpeng Liao; Tian Gao; Chaofan Ai; Xiang Tang; Ville-Petri Friman; Shungui Zhou

doi:10.59717/j.xinn-geo.2024.100101

The Innovation Geoscience > 2024 Vol. 2 > No. 4 > 100101

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Deciphering the hidden role of soil viruses in nitrogen cycling revealed by metagenomic stable isotope probing

1.
Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2.
Department of Microbiology, University of Helsinki, Helsinki 00014, Finland

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Corresponding authors: liaohp@fafu.edu.cn (H. L.); sgzhou@fafu.edu.cn (S. Z.)
Received Date: 23 April 2024

Accepted Date: 06 November 2024

Published Online: 26 November 2024

The Innovation Geoscience 2(4), https://doi.org/10.59717/j.xinn-geo.2024.100101 | Cite this article

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GRAPHICAL ABSTRACT

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PUBLIC SUMMARY
1. Uncovering the role of soil viruses in nitrogen cycling through metagenomic stable isotope probing.
  
  Soil viruses can promote microbial nitrogen turnover through viral lysis and carrying auxiliary metabolic genes.
  
  Lytic viruses with the potential to infect N-fixing MAGs may impact soil nitrogen turnover.

ABSTRACT

ABSTRACT

Viruses are the most abundant microbial entities on Earth, playing a critical role in elemental cycling. However, to date, there is no experimental evidence demonstrating whether viruses participate in nitrogen (N) cycling in soil. Here, we combined stable isotope probing (SIP) and metagenomics to detect ¹⁵N assimilation by viruses and their putative bacterial hosts in soil microcosms incubated with ¹⁵N-labeled N₂. We recovered 609 viral operational taxonomic units (vOTUs, > 5 kb) and 49 metagenome–assembled genomes (MAGs) from the ¹⁵N-labeled soils using metagenomics. Based on metagenomic–SIP, a total of 65 vOTUs and 10 MAGs with potential N–transforming abilities were identified due to their exclusive enrichment in the heavy fractions under ¹⁵N₂ treatment compared to ¹⁴N₂, indicating their significance for soil N transformation. Moreover, three N–fixing MAGs (active diazotrophs) and one lytic virus with the potential to infect these diazotrophs were observed in the ¹⁵N-labeled soil. This indicates that viruses can assimilate ¹⁵N into their DNA via infection of diazotrophs. Additionally, two auxiliary metabolic genes associated with N cycling were identified in two viruses, suggesting that viruses may provision their hosts with N-cycling genes. Overall, our results demonstrate that soil viruses can promote microbial N turnover through viral lysis, highlighting the viral shunt as an important mechanism facilitating elemental cycling in soils.
- viruses /
- metagenomics /
- nitrogen cycling /
- stable isotope probing

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REFERENCES

[1]	Lu, J., Fan, S., Ding, W., et al. (2023). Microbial resource mining from ancient biofilms. Innov. Geosci. 1: 100018. DOI: 10.59717/j.xinn–geo.2023.100018. View in Article CrossRef Google Scholar
[2]	Zehr, J.P. and Capone, D.G. (2020). Changing perspectives in marine nitrogen fixation. Science. 368: eaay9514. DOI: 10.1126/science.aay9514. View in Article CrossRef Google Scholar
[3]	Kuypers, M.M., Marchant, H.K., and Kartal, B. (2018). The microbial nitrogeN-cycling network. Nat. Rev. Microbiol. 16: 263−276. DOI: 10.1038/nrmicro.2018.9. View in Article CrossRef Google Scholar
[4]	Boyle, S.A., Yarwood, R.R., Bottomley, P.J., et al. (2008). Bacterial and fungal contributions to soil nitrogen cycling under douglas fir and red alder at two sites in oregon. Soil Biol. Biochem. 40: 443−451. DOI: 10.1016/j.soilbio.2007.09.007. View in Article CrossRef Google Scholar
[5]	Chevallereau, A., Pons, B.J., van Houte, S., et al. (2022). Interactions between bacterial and phage communities in natural environments. Nat. Rev. Microbiol. 20: 49−62. DOI: 10.1038/s41579–021–00602–y. View in Article CrossRef Google Scholar
[6]	Jansson, J.K. and Wu, R. (2023). Soil viral diversity, ecology and climate change. Nat. Rev. Microbiol. 21: 296−311. DOI: 10.1038/s41579–022–00811–z. View in Article CrossRef Google Scholar
[7]	Jover, L.F., Effler, T.C., Buchan, A., et al. (2014). The elemental composition of virus particles: Implications for marine biogeochemical cycles. Nat. Rev. Microbiol. 12: 519−528. DOI: 10.1038/nrmicro3289. View in Article CrossRef Google Scholar
[8]	Gazitúa, M.C., Vik, D.R., Roux, S., et al. (2021). Potential virus–mediated nitrogen cycling in oxygen–depleted oceanic waters. ISME J. 15: 981−998. DOI: 10.1038/s41396–020–00825–6. View in Article CrossRef Google Scholar
[9]	Zheng, X., Jahn, M.T., Sun, M., et al. (2022). Organochlorine contamination enriches virus–encoded metabolism and pesticide degradation associated auxiliary genes in soil microbiomes. ISME J. 16: 1397−1408. DOI: 10.1038/s41396–022–01188–w. View in Article CrossRef Google Scholar
[10]	Barnett, S.E. and Buckley, D.H. (2023). Metagenomic stable isotope probing reveals bacteriophage participation in soil carbon cycling. Environ. Microbiol. 25: 1785−1795. DOI: 10.1111/1462–2920.16395. View in Article CrossRef Google Scholar
[11]	Lee, S., Sieradzki, E.T., Nicol, G.W., et al. (2023). Propagation of viral genomes by replicating ammonia–oxidising archaea during soil nitrification. ISME J. 17: 309−314. DOI: 10.1038/s41396–022–01341–5. View in Article CrossRef Google Scholar
[12]	Liu, W., Ling, N., Guo, J., et al. (2020). Legacy effects of 8–year nitrogen inputs on bacterial assemblage in wheat rhizosphere. Biol. Fertil. Soils. 56: 583−596. DOI: 10.1007/s00374–020–01435–2. View in Article CrossRef Google Scholar
[13]	Liao, H., Liu, C., Ai, C., et al. (2023). Mesophilic and thermophilic viruses are associated with nutrient cycling during hyperthermophilic composting. The ISME Journal. 17: 916−930. DOI: 10.1038/s41396–023–01404–1. View in Article CrossRef Google Scholar
[14]	Kapili, B.J., Barnett, S.E., Buckley, D.H., et al. (2020). Evidence for phylogenetically and catabolically diverse active diazotrophs in deep–sea sediment. ISME J. 14: 971−983. DOI: 10.1038/s41396–019–0584–8. View in Article CrossRef Google Scholar
[15]	Lee, S., Hazard, C., and Nicol, G.W. (2024). Activity of novel virus families infecting soil nitrifiers is concomitant with host niche differentiation. ISME J. wrae205. DOI: 10.1093/ismejo/wrae205. View in Article Google Scholar
[16]	Shaffer, M., Borton, M.A., McGivern, B.B., et al. (2020). Dram for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 48: 8883−8900. DOI: 10.1093/nar/gkaa621. View in Article CrossRef Google Scholar
[17]	Feng, W., Qiao, J., Li, J., et al. (2023). Anammox granule destruction and reconstruction in a partial nitrification/anammox system under hydroxylamine stress. J. Environ. Manag. 345: 118688. DOI: 10.1016/j.jenvman.2023.118688. View in Article CrossRef Google Scholar
[18]	Kapili, B.J., Barnett, S.E., Buckley, D.H., et al. (2020). Evidence for phylogenetically and catabolically diverse active diazotrophs in deep–sea sediment. ISME J. 14: 971−983. DOI: 10.1038/s41396–019–0584–8. View in Article CrossRef Google Scholar
[19]	Liao, H., Li, X., Yang, Q., et al. (2021). Herbicide selection promotes antibiotic resistance in soil microbiomes. Mol Biol Evol. 38: 2337−2350. DOI: 10.1093/molbev/msab029. View in Article CrossRef Google Scholar
[20]	Bolyen, E.Rideout, J.R.Dillon, M.R., et al. (2019). Reproducible, interactive, scalable and extensible microbiome data science using qiime 2. Nat Biotechnol. 37: 852−857. DOI: 10.1038/s41587–019–0209–9. View in Article CrossRef Google Scholar
[21]	Dong, X., Zhang, C., Peng, Y., et al. (2022). Phylogenetically and catabolically diverse diazotrophs reside in deep–sea cold seep sediments. Nat Commun. 13: 4885. DOI: 10.1038/s41467–022–32503–w. View in Article CrossRef Google Scholar
[22]	Bolger, A.M., Lohse, M., and Usadel, B. (2014). Trimmomatic: A flexible trimmer for illumina sequence data. Bioinformatics 30: 2114−2120. DOI: 10.1093/bioinformatics/btu170. View in Article CrossRef Google Scholar
[23]	Li, D., Luo, R., Liu, C.–M., et al. (2016). Megahit v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 102 :3–11. DOI: 10.1016/j.ymeth.2016.02.020. View in Article Google Scholar
[24]	Uritskiy, G.V., DiRuggiero, J., and Taylor, J. (2018). Metawrap–a flexible pipeline for genome–resolved metagenomic data analysis. Microbiome. 6: 158. DOI: 10.1186/s40168–018–0541–1. View in Article CrossRef Google Scholar
[25]	Kang, D.D., Li, F., Kirton, E., et al. (2019). Metabat 2: An adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ. 7: e7359. DOI: 10.7717/peerj.7359. View in Article CrossRef Google Scholar
[26]	Wu, Y.–W., Simmons, B.A., and Singer, S.W. (2016). Maxbin 2.0: An automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics. 32 :605–607. DOI: 10.1093/bioinformatics/btv638. View in Article Google Scholar
[27]	Alneberg, J., Bjarnason, B.S., de Bruijn, I., et al. (2014). Binning metagenomic contigs by coverage and composition. Nat. Methods. 11: 1144−1146. DOI: 10.1038/nmeth.3103. View in Article CrossRef Google Scholar
[28]	Parks, D.H., Imelfort, M., Skennerton, C.T., et al. (2015). Checkm: Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25: 1043−1055. DOI: 10.1101/gr.186072.114. View in Article CrossRef Google Scholar
[29]	Olm, M.R., Brown, C.T., Brooks, B., et al. (2017). Drep: A tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de–replication. ISME J. 11: 2864−2868. DOI: 10.1038/ismej.2017.126. View in Article CrossRef Google Scholar
[30]	Chaumeil, P.–A., Mussig, A.J., Hugenholtz, P., et al. (2019). Gtdb–tk: A toolkit to classify genomes with the genome taxonomy database. Bioinformatics. 36: 1925−1927. DOI: 10.1093/bioinformatics/btz848 %J Bioinformatics. DOI: 10.1093/bioinformatics/btz848%JBioinformatics. View in Article CrossRef Google Scholar
[31]	Buchfink, B., Xie, C., and Huson, D.H. (2015). Fast and sensitive protein alignment using diamond. Nat. Methods. 12: 59−60. DOI: 10.1038/nmeth.3176. View in Article CrossRef Google Scholar
[32]	Tu, Q., Lin, L., Cheng, L., et al. (2018). Ncycdb: A curated integrative database for fast and accurate metagenomic profiling of nitrogen cycling genes. Bioinformatics. 35: 1040−1048. DOI: 10.1093/bioinformatics/bty741. View in Article CrossRef Google Scholar
[33]	Emerson, J.B., Roux, S., Brum, J.R., et al. (2018). Host–linked soil viral ecology along a permafrost thaw gradient. Nat Microbiol. 3: 870−880. DOI: 10.1038/s41564–018–0190–y. View in Article CrossRef Google Scholar
[34]	Guo, J., Bolduc, B., Zayed, A.A., et al. (2021). Virsorter2: A multi–classifier, expert–guided approach to detect diverse DNA and rna viruses. Microbiome. 9: 37. DOI: 10.1186/s40168–020–00990–y. View in Article CrossRef Google Scholar
[35]	Ren, J., Song, K., Deng, C., et al. (2020). Identifying viruses from metagenomic data using deep learning. Quantitative Biol. 8: 64−77. DOI: 10.1007/s40484–019–0187–4. View in Article CrossRef Google Scholar
[36]	Guo, J., Vik, D., Pratama, A.A., et al. (2021). Viral sequence identification sop with virsorter2 v.3. protocols.io. 3 . DOI: 10.17504/protocols.io.bwm5pc86. View in Article Google Scholar
[37]	Nayfach, S., Camargo, A.P., Schulz, F., et al. (2021). Checkv assesses the quality and completeness of metagenome–assembled viral genomes. Nat Biotechnol. 39: 578−585. DOI: 10.1038/s41587–020–00774–7. View in Article CrossRef Google Scholar
[38]	Steinegger, M. and Söding, J. (2017). Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 35: 1026−1028. DOI. DOI: 10.1038/nbt.3988. View in Article CrossRef Google Scholar
[39]	Kieft, K., Zhou, Z., and Anantharaman, K. (2020). Vibrant: Automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences. Microbiome. 8: 90. DOI: 10.1186/s40168–020–00867–0. View in Article CrossRef Google Scholar
[40]	Shang, J., Tang, X., and Sun, Y. (2022). Phatyp: Predicting the lifestyle for bacteriophages using bert. Briefings in Bioinformatics. 24: bbac487. DOI: 10.1093/bib/bbac487. View in Article CrossRef Google Scholar
[41]	Muscatt, G., Hilton, S., Raguideau, S., et al. (2022). Crop management shapes the diversity and activity of DNA and rna viruses in the rhizosphere. Microbiome. 10: 1−16. DOI: 10.1101/2022.04.22.488307. View in Article CrossRef Google Scholar
[42]	Bland, C., Ramsey, T.L., Sabree, F., et al. (2007). Crispr recognition tool (crt): A tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinf. 8: 209. DOI: 10.1186/1471–2105–8–209. View in Article CrossRef Google Scholar
[43]	Segata, N., Izard, J., Waldron, L., et al. (2011). Metagenomic biomarker discovery and explanation. Genome Biol. 12: R60. DOI: 10.1186/gb–2011–12–6–r60. View in Article CrossRef Google Scholar

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Liu C., Liao H., Gao T., et al., (2024). Deciphering the hidden role of soil viruses in nitrogen cycling revealed by metagenomic stable isotope probing. The Innovation Geoscience 2(4): 100101. https://doi.org/10.59717/j.xinn-geo.2024.100101

Liu C., Liao H., Gao T., et al., (2024). Deciphering the hidden role of soil viruses in nitrogen cycling revealed by metagenomic stable isotope probing. The Innovation Geoscience 2(4): 100101. https://doi.org/10.59717/j.xinn-geo.2024.100101

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Deciphering the hidden role of soil viruses in nitrogen cycling revealed by metagenomic stable isotope probing

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PUBLIC SUMMARY

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