Genome-resolved metagenomics reveal soil and viral drivers of keystone bacterial traits shaping nutrient cycling and soybean yield across agroecosystems

Xiaowei Huang , Xueling Yang , Yuxuan Chen , Jie Cheng , Zhongyi Cheng , Jiachun Shi , Yan He , Jianming Xu

Soil Ecology Letters ›› 2025, Vol. 7 ›› Issue (4) : 250346

PDF (7716KB)
Soil Ecology Letters ›› 2025, Vol. 7 ›› Issue (4) : 250346 DOI: 10.1007/s42832-025-0346-7
RESEARCH ARTICLE

Genome-resolved metagenomics reveal soil and viral drivers of keystone bacterial traits shaping nutrient cycling and soybean yield across agroecosystems

Author information +
History +
PDF (7716KB)

Abstract

Soil microbes are crucial for agricultural sustainability, yet the genomic evidence of their interactions with soil abiotic and biotic factors remains unclear. Herein, we evaluated the contribution of soil bacteria to soil functions and soybean yields by analyzing 4281 bacterial metagenomic assembled genomes (MAGs) recovered from 113 natural fields across China, integrated 12 enzymic activities and 58 quantified nutrient-cycling genes. Genome-resolved metagenomics revealed the diverse genic traits of keystone bacteria, and their roles in nutrient accumulation, fungal pathogen suppression, and herbicide biodegradation, thereby promoting soybean yields. Soil pH and C/N content were important abiotic factors that determined the dominant life history strategy of keystone communities, thus affecting nutrient-cycling genes abundance. We proposed agricultural management suggestions based on diversified planting aligned with the soil environmental preferences of keystone bacteria, verified in two long-term cropping fields. By recovering 7803 vMAGs, we found the lysogenic virus-host dynamics could promote keystone bacteria adaptation by providing P-acquisition auxiliary metabolic genes (AMGs), leading to ecological advantages. We reported a novel P-acquisition strategy involving phnA-associated phosphonate hydrolysis employed by viruses, significantly influencing keystone-host phosphorus cycling. Overall, our study significantly advances the understanding of keystone bacteria in supporting crop production, with implications for precision microbiome management in agroecosystems.

Graphical abstract

Keywords

metagenomic assembled genomes / nutrient cycling / crop pathogen suppression / pesticide pollution / sustainable agriculture / virus-host dynamics

Highlight

● Keystone bacteria’s effect on soil health was found by genome-resolved metagenomics.

● Soil pH and C/N content were important for affecting keystone communities.

● Available phosphorus lacked a significant effect on keystone bacteria.

● Lysogenic virus-host dynamics help keystone bacteria adaption by P-acquisition AMGs.

Cite this article

Download citation ▾
Xiaowei Huang, Xueling Yang, Yuxuan Chen, Jie Cheng, Zhongyi Cheng, Jiachun Shi, Yan He, Jianming Xu. Genome-resolved metagenomics reveal soil and viral drivers of keystone bacterial traits shaping nutrient cycling and soybean yield across agroecosystems. Soil Ecology Letters, 2025, 7(4): 250346 DOI:10.1007/s42832-025-0346-7

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J., 1990. Basic local alignment search tool. Journal of Molecular Biology215, 403–410.

[2]

Aramaki, T., Blanc-Mathieu, R., Endo, H., Ohkubo, K., Kanehisa, M., Goto, S., Ogata, H., 2020. KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold. Bioinformatics36, 2251–2252.

[3]

Banerjee, S., Schlaeppi, K., van der Heijden, M.G.A., 2018. Keystone taxa as drivers of microbiome structure and functioning. Nature Reviews Microbiology16, 567–576.

[4]

Banerjee, S., van der Heijden, M.G.A., 2023. Soil microbiomes and one health. Nature Reviews Microbiology21, 6–20.

[5]

Banerjee, S., Walder, F., Büchi, L., Meyer, M., Held, A.Y., Gattinger, A., Keller, T., Charles, R., van der Heijden, M.G.A., 2019. Agricultural intensification reduces microbial network complexity and the abundance of keystone taxa in roots. The ISME Journal13, 1722–1736.

[6]

Bi, L., Yu, D.T., Du, S., Zhang, L.M., Zhang, L.Y., Wu, C.F., Xiong, C., Han, L.L., He, J.Z., 2021. Diversity and potential biogeochemical impacts of viruses in bulk and rhizosphere soils. Environmental Microbiology23, 588–599.

[7]

Bland, C., Ramsey, T.L., Sabree, F., Lowe, M., Brown, K., Kyrpides, N.C., Hugenholtz, P., 2007. CRISPR recognition tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinformatics8, 209.

[8]

Blin, K., Shaw, S., Kloosterman, A.M., Charlop-Powers, Z., van Wezel, G.P., Medema, M.H., Weber, T., 2021. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Research49, W29–W35.

[9]

Bowers, R.M., Kyrpides, N.C., Stepanauskas, R., Harmon-Smith, M., Doud, D., Reddy, T.B.K., Schulz, F., Jarett, J., Rivers, A.R., Eloe-Fadrosh, E.A., Tringe, S.G., Ivanova, N.N., Copeland, A., Clum, A., Becraft, E.D., Malmstrom, R.R., Birren, B., Podar, M., Bork, P., Weinstock, G.M., Garrity, G.M., Dodsworth, J.A., Yooseph, S., Sutton, G., Glöckner, F.O., Gilbert, J.A., Nelson, W.C., Hallam, S.J., Jungbluth, S.P., Ettema, T.J.G., Tighe, S., Konstantinidis, K.T., Liu, W.T., Baker, B.J., Rattei, T., Eisen, J.A., Hedlund, B., McMahon, K.D., Fierer, N., Knight, R., Finn, R., Cochrane, G., Karsch-Mizrachi, I., Tyson, G.W., Rinke, C., The Genome Standards Consortium, Lapidus, A., Meyer, F., Yilmaz, P., Parks, D.H., Murat Eren, A., Schriml, L., Banfield, J.F., Hugenholtz, P., Woyke, T., 2017. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nature Biotechnology35, 725–731.

[10]

Brum, J.R., Sullivan, M.B., 2015. Rising to the challenge: accelerated pace of discovery transforms marine virology. Nature Reviews Microbiology13, 147–159.

[11]

Brust, G.E., 2019. Management strategies for organic vegetable fertility. In: Biswas, D., Micallef, S.A., eds. Safety and Practice for Organic Food. Amsterdam: Elsevier, 193–212.

[12]

Buchfink, B., Reuter, K., Drost, H.G., 2021. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nature Methods18, 366–368.

[13]

Bushnell, B., 2014. BBMap: A Fast, Accurate, Splice-Aware Aligner. Berkeley: Lawrence Berkeley National Lab (LBNL).

[14]

Byrnes, J.E.K., Gamfeldt, L., Isbell, F., Lefcheck, J.S., Griffin, J.N., Hector, A., Cardinale, B.J., Hooper, D.U., Dee, L.E., Duffy, J.E., 2014. Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions. Methods in Ecology and Evolution5, 111–124.

[15]

Camargo, A.P., Roux, S., Schulz, F., Babinski, M., Xu, Y., Hu, B., Chain, P.S., Nayfach, S., Kyrpides, N.C., 2023. You can move, but you can’t hide: identification of mobile genetic elements with geNomad. Nature Biotechnology 42, 1303–1312..

[16]

Capella-Gutiérrez, S., Silla-Martínez, J.M., Gabaldón, T., 2009. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics25, 1972–1973.

[17]

Carrión, V.J., Perez-Jaramillo, J., Cordovez, V., Tracanna, V., de Hollander, M., Ruiz-Buck, D., Mendes, L.W., van Ijcken, W.F.J., Gomez-Exposito, R., Elsayed, S.S., Mohanraju, P., Arifah, A., van der Oost, J., Paulson, J.N., Mendes, R., van Wezel, G.P., Medema, M.H., Raaijmakers, J.M., 2019. Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science366, 606–612.

[18]

Chan, P.P., Lin, B.Y., Mak, A.J., Lowe, T.M., 2021. tRNAscan-SE 2.0: improved detection and functional classification of transfer RNA genes. Nucleic Acids Research 49, 9077–9096.

[19]

Chaumeil, P.A., Mussig, A.J., Hugenholtz, P., Parks, D.H., 2022. GTDB-Tk v2: memory friendly classification with the genome taxonomy database. Bioinformatics38, 5315–5316.

[20]

Chen, S.F., Zhou, Y.Q., Chen, Y.R., Gu, J., 2018. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics34, i884–i890.

[21]

Cheng, R.L., Li, X.F., Jiang, L.J., Gong, L.F., Geslin, C., Shao, Z.Z., 2022. Virus diversity and interactions with hosts in deep-sea hydrothermal vents. Microbiome10, 235.

[22]

Chevallereau, A., Pons, B.J., van Houte, S., Westra, E.R., 2022. Interactions between bacterial and phage communities in natural environments. Nature Reviews Microbiology20, 49–62.

[23]

Chklovski, A., Parks, D.H., Woodcroft, B.J., Tyson, G.W., 2023. CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning. Nature Methods20, 1203–1212.

[24]

Chuckran, P.F., Flagg, C., Propster, J., Rutherford, W.A., Sieradzki, E.T., Blazewicz, S.J., Hungate, B., Pett-Ridge, J., Schwartz, E., Dijkstra, P., 2023. Edaphic controls on genome size and GC content of bacteria in soil microbial communities. Soil Biology and Biochemistry178, 108935.

[25]

Costea, P.I., Hildebrand, F., Arumugam, M., Bäckhed, F., Blaser, M.J., Bushman, F.D., de Vos, W.M., Ehrlich, S.D., Fraser, C.M., Hattori, M., Huttenhower, C., Jeffery, I.B., Knights, D., Lewis, J.D., Ley, R.E., Ochman, H., O'Toole, P.W., Quince, C., Relman, D.A., Shanahan, F., Sunagawa, S., Wang, J., Weinstock, G.M., Wu, G.D., Zeller, G., Zhao, L.P., Raes, J., Knight, R., Bork, P., 2018. Enterotypes in the landscape of gut microbial community composition. Nature Microbiology3, 388–388.

[26]

Coutinho, F.H., Silveira, C.B., Gregoracci, G.B., Thompson, C.C., Edwards, R.A., Brussaard, C.P.D., Dutilh, B.E., Thompson, F.L., 2017. Marine viruses discovered via metagenomics shed light on viral strategies throughout the oceans. Nature Communications8, 15955.

[27]

Crowther, T.W., van den Hoogen, J., Wan, J., Mayes, M.A., Keiser, A.D., Mo, L., Averill, C., Maynard, D.S., 2019. The global soil community and its influence on biogeochemistry. Science365, aav0550.

[28]

Cui, J.W., Zhu, R.L., Wang, X.Y., Xu, X.P., Ai, C., He, P., Liang, G.Q., Zhou, W., Zhu, P., 2022. Effect of high soil C/N ratio and nitrogen limitation caused by the long-term combined organic-inorganic fertilization on the soil microbial community structure and its dominated SOC decomposition. Journal of Environmental Management303, 114155.

[29]

Dai, Z.M., Liu, G.F., Chen, H.H., Chen, C.R., Wang, J.K., Ai, S.Y., Wei, D., Li, D.M., Ma, B., Tang, C.X., Brookes, P.C., Xu, J.M., 2020. Long-term nutrient inputs shift soil microbial functional profiles of phosphorus cycling in diverse agroecosystems. The ISME Journal14, 757–770.

[30]

Dean, R., Van Kan, J.A.L., Pretorius, Z.A., Hammond-Kosack, K.E., Di Pietro, A., Spanu, P.D., Rudd, J.J., Dickman, M., Kahmann, R., Ellis, J., Foster, G.D., 2012. The Top 10 fungal pathogens in molecular plant pathology. Molecular Plant Pathology13, 414–430.

[31]

Delgado-Baquerizo, M., Maestre, F.T., Reich, P.B., Jeffries, T.C., Gaitan, J.J., Encinar, D., Berdugo, M., Campbell, C.D., Singh, B.K., 2016. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nature Communications7, 10541.

[32]

Delgado-Baquerizo, M., Oliverio, A.M., Brewer, T.E., Benavent-González, A., Eldridge, D.J., Bardgett, R.D., Maestre, F.T., Singh, B.K., Fierer, N., 2018. A global atlas of the dominant bacteria found in soil. Science359, 320–325.

[33]

Delgado-Baquerizo, M., Reich, P.B., Trivedi, C., Eldridge, D.J., Abades, S., Alfaro, F.D., Bastida, F., Berhe, A.A., Cutler, N.A., Gallardo, A., García-Velázquez, L., Hart, S.C., Hayes, P.E., He, J.Z., Hseu, Z.Y., Hu, H.W., Kirchmair, M., Neuhauser, S., Pérez, C.A., Reed, S.C., Santos, F., Sullivan, B.W., Trivedi, P., Wang, J.T., Weber-Grullon, L., Williams, M.A., Singh, B.K., 2020. Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nature Ecology & Evolution4, 210–220.

[34]

Du, J.N., Ma, W.W., Li, G., Wu, J.H., Chang, W.H., 2025. Vegetation degradation and its progressive impact on soil nitrogen mineralization in the Qinghai-Tibet Plateau’s alpine wetlands: insights from a three-year study. Journal of Environmental Management373, 123668.

[35]

Duhamel, S., Diaz, J.M., Adams, J.C., Djaoudi, K., Steck, V., Waggoner, E.M., 2021. Phosphorus as an integral component of global marine biogeochemistry. Nature Geoscience14, 359–368.

[36]

Edgar, R.C., 2007. PILER-CR: fast and accurate identification of CRISPR repeats. BMC Bioinformatics8, 18.

[37]

Emerson, J.B., Roux, S., Brum, J.R., Bolduc, B., Woodcroft, B.J., Jang, H.B., Singleton, C.M., Solden, L.M., Naas, A.E., Boyd, J.A., Hodgkins, S.B., Wilson, R.M., Trubl, G., Li, C.S., Frolking, S., Pope, P.B., Wrighton, K.C., Crill, P.M., Chanton, J.P., Saleska, S.R., Tyson, G.W., Rich, V.I., Sullivan, M.B., 2018. Host-linked soil viral ecology along a permafrost thaw gradient. Nature Microbiology3, 870–880.

[38]

Escalas, A., Hale, L., Voordeckers, J.W., Yang, Y.F., Firestone, M.K., Alvarez-Cohen, L., Zhou, J.Z., 2019. Microbial functional diversity: from concepts to applications. Ecology and Evolution9, 12000–12016.

[39]

Fan, K.K., Delgado-Baquerizo, M., Guo, X.S., Wang, D.Z., Zhu, Y.G., Chu, H.Y., 2021. Biodiversity of key-stone phylotypes determines crop production in a 4-decade fertilization experiment. The ISME Journal15, 550–561.

[40]

Fan, L.J., Xue, Y.W., Wu, D.H., Xu, M.C., Li, A.D., Zhang, B.X., Mo, J.M., Zheng, M.H., 2024. Long-term nitrogen and phosphorus addition have stronger negative effects on microbial residual carbon in subsoils than topsoils in subtropical forests. Global Change Biology30, e17210.

[41]

Finn, R.D., Coggill, P., Eberhardt, R.Y., Eddy, S.R., Mistry, J., Mitchell, A.L., Potter, S.C., Punta, M., Qureshi, M., Sangrador-Vegas, A., Salazar, G.A., Tate, J., Bateman, A., 2016. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Research44, D279–D285.

[42]

Fortmann-Roe, S., 2015. Consistent and clear reporting of results from diverse modeling techniques: the A3 method. Journal of Statistical Software66, 1–23.

[43]

French, E., Kaplan, I., Iyer-Pascuzzi, A., Nakatsu, C.H., Enders, L., 2021. Emerging strategies for precision microbiome management in diverse agroecosystems. Nature Plants7, 256–267.

[44]

Friedman, J., Alm, E.J., 2012. Inferring correlation networks from genomic survey data. PLoS Computational Biology8, e1002687.

[45]

Gao, S.M., Paez-Espino, D., Li, J.T., Ai, H.X., Liang, J.L., Luo, Z.H., Zheng, J., Chen, H., Shu, W.S., Huang, L.N., 2022. Patterns and ecological drivers of viral communities in acid mine drainage sediments across Southern China. Nature Communications13, 2389.

[46]

Grazziotin, A.L., Koonin, E.V., Kristensen, D.M., 2017. Prokaryotic Virus Orthologous Groups (pVOGs): a resource for comparative genomics and protein family annotation. Nucleic Acids Research45, D491–D498.

[47]

Hartmann, M., Six, J., 2023. Soil structure and microbiome functions in agroecosystems. Nature Reviews Earth & Environment4, 4–18.

[48]

Herren, C.M., McMahon, K.D., 2017. Cohesion: a method for quantifying the connectivity of microbial communities. The ISME Journal11, 2426–2438.

[49]

Hickl, O., Queirós, P., Wilmes, P., May, P., Heintz-Buschart, A., 2022. binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets. Briefings in Bioinformatics23, bbac431.

[50]

Holmes, I., Harris, K., Quince, C., 2012. Dirichlet multinomial mixtures: generative models for microbial metagenomics. PLoS One7, e30126.

[51]

Hu, Z.K., Delgado-Baquerizo, M., Fanin, N., Chen, X.Y., Zhou, Y., Du, G.Z., Hu, F., Jiang, L., Hu, S.J., Liu, M.Q., 2024. Nutrient-induced acidification modulates soil biodiversity-function relationships. Nature Communications15, 2858.

[52]

Hyatt, D., Chen, G.L., LoCascio, P.F., Land, M.L., Larimer, F.W., Hauser, L.J., 2010. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics11, 119.

[53]

Jagadesh, M., Dash, M., Kumari, A., Singh, S.K., Verma, K.K., Kumar, P., Bhatt, R., Sharma, S.K., 2024. Revealing the hidden world of soil microbes: metagenomic insights into plant, bacteria, and fungi interactions for sustainable agriculture and ecosystem restoration. Microbiological Research285, 127764.

[54]

Jang, H.B., Bolduc, B., Zablocki, O., Kuhn, J.H., Roux, S., Adriaenssens, E.M., Brister, J.R., Kropinski, A.M., Krupovic, M., Lavigne, R., Turner, D., Sullivan, M.B., 2019. Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks. Nature Biotechnology37, 632–639.

[55]

Jansson, J.K., Wu, R.N., 2023. Soil viral diversity, ecology and climate change. Nature Reviews Microbiology21, 296–311.

[56]

Jiao, S., Lu, Y.H., Wei, G.H., 2022. Soil multitrophic network complexity enhances the link between biodiversity and multifunctionality in agricultural systems. Global Change Biology28, 140–153.

[57]

Johansen, J., Plichta, D.R., Nissen, J.N., Jespersen, M.L., Shah, S.A., Deng, L., Stokholm, J., Bisgaard, H., Nielsen, D.S., Sørensen, S.J., Rasmussen, S., 2022. Genome binning of viral entities from bulk metagenomics data. Nature Communications13, 965.

[58]

Jover, L.F., Effler, T.C., Buchan, A., Wilhelm, S.W., Weitz, J.S., 2014. The elemental composition of virus particles: implications for marine biogeochemical cycles. Nature Reviews Microbiology12, 519–528.

[59]

Kamoun, S., Furzer, O., Jones, J.D.G., Judelson, H.S., Ali, G.S., Dalio, R.J.D., Roy, S.G., Schena, L., Zambounis, A., Panabières, F., Cahill, D., Ruocco, M., Figueiredo, A., Chen, X.R., Hulvey, J., Stam, R., Lamour, K., Gijzen, M., Tyler, B.M., Grünwald, N.J., Mukhtar, M.S., Tomé, D.F.A., Tör, M., Van den Ackerveken, G., McDowell, J., Daayf, F., Fry, W.E., Lindqvist-Kreuze, H., Meijer, H.J.G., Petre, B., Ristaino, J., Yoshida, K., Birch, P.R.J., Govers, F., 2015. The Top 10 oomycete pathogens in molecular plant pathology. Molecular Plant Pathology16, 413–434.

[60]

Kang, D.D., Li, F., Kirton, E., Thomas, A., Egan, R., An, H., Wang, Z., 2019. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ7, e7359.

[61]

Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular Biology and Evolution30, 772–780.

[62]

Kehler, A., Haygarth, P., Tamburini, F., Blackwell, M., 2021. Cycling of reduced phosphorus compounds in soil and potential impacts of climate change. European Journal of Soil Science72, 2517–2537.

[63]

Kelley, L.A., Mezulis, S., Yates, C.M., Wass, M.N., Sternberg, M.J.E., 2015. The Phyre2 web portal for protein modeling, prediction and analysis. Nature Protocols10, 845–858.

[64]

Kieft, K., Adams, A., Salamzade, R., Kalan, L., Anantharaman, K., 2022. vRhyme enables binning of viral genomes from metagenomes. Nucleic Acids Research50, e83.

[65]

Kieft, K., Zhou, Z.C., Anderson, R.E., Buchan, A., Campbell, B.J., Hallam, S.J., Hess, M., Sullivan, M.B., Walsh, D.A., Roux, S., Anantharaman, K., 2021. Ecology of inorganic sulfur auxiliary metabolism in widespread bacteriophages. Nature Communications12, 3503.

[66]

Knowles, B., Silveira, C.B., Bailey, B.A., Barott, K., Cantu, V.A., Cobián-Güemes, A.G., Coutinho, F.H., Dinsdale, E.A., Felts, B., Furby, K.A., George, E.E., Green, K.T., Gregoracci, G.B., Haas, A.F., Haggerty, J.M., Hester, E.R., Hisakawa, N., Kelly, L.W., Lim, Y.W., Little, M., Luque, A., McDole-Somera, T., McNair, K., de Oliveira, L.S., Quistad, S.D., Robinett, N.L., Sala, E., Salamon, P., Sanchez, S.E., Sandin, S., Silva, G.G.Z., Smith, J., Sullivan, C., Thompson, C., Vermeij, M.J.A., Youle, M., Young, C., Zgliczynski, B., Brainard, R., Edwards, R.A., Nulton, J., Thompson, F., Rohwer, F., 2016. Lytic to temperate switching of viral communities. Nature539, 123–123.

[67]

Kulakova, A.N., Kulakov, L.A., Akulenko, N.V., Ksenzenko, V.N., Hamilton, J.T.G., Quinn, J.P., 2001. Structural and functional analysis of the phosphonoacetate hydrolase (phnA) gene region in Pseudomonas fluorescens 23F. Journal of Bacteriology183, 3268–3275.

[68]

Kursa, M.B., Rudnicki, W.R., 2010. Feature selection with the Boruta package. Journal of Statistical Software36, 1–13.

[69]

Li, D.H., Liu, C.M., Luo, R.B., Sadakane, K., Lam, T.W., 2015. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics31, 1674–1676.

[70]

Li, H., 2013. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv: 1303.3997.

[71]

Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., 1000 Genome Project Data Processing Subgroup, 2009. The sequence alignment/map format and SAMtools. Bioinformatics25, 2078–2079.

[72]

Liang, J.L., Feng, S.W., Lu, J.L., Wang, X.N., Li, F.L., Guo, Y.Q., Liu, S.Y., Zhuang, Y.Y., Zhong, S.J., Zheng, J., Wen, P., Yi, X., Jia, P., Liao, B., Shu, W.S., Li, J.T., 2024. Hidden diversity and potential ecological function of phosphorus acquisition genes in widespread terrestrial bacteriophages. Nature Communications15, 2827.

[73]

Liao, H.P., Liu, C., Ai, C.F., Gao, T., Yang, Q.E., Yu, Z., Gao, S.M., Zhou, S.G., Friman, V.P., 2023. Mesophilic and thermophilic viruses are associated with nutrient cycling during hyperthermophilic composting. The ISME Journal17, 916–930.

[74]

Liu, L., Gao, Z.Y., Yang, Y., Gao, Y., Mahmood, M., Jiao, H.J., Wang, Z.H., Liu, J.S., 2023a. Long-term high-P fertilizer input shifts soil P cycle genes and microorganism communities in dryland wheat production systems. Agriculture, Ecosystems & Environment342, 108226.

[75]

Liu, S.L., Zhang, M., Feng, F., Tian, Z.X., 2020. Toward a "green revolution" for soybean. Molecular Plant13, 688–697.

[76]

Liu, S.W., Zeng, J.X., Yu, H., Wang, C., Yang, Y.F., Wang, J.J., He, Z.L., Yan, Q.Y., 2023b. Antimony efflux underpins phosphorus cycling and resistance of phosphate-solubilizing bacteria in mining soils. The ISME Journal17, 1278–1289.

[77]

Lockwood, S., Greening, C., Baltar, F., Morales, S.E., 2022. Global and seasonal variation of marine phosphonate metabolism. The ISME Journal16, 2198–2212.

[78]

Luo, X.Q., Wang, P.D., Li, J.L., Ahmad, M., Duan, L., Yin, L.Z., Deng, Q.Q., Fang, B.Z., Li, S.H., Li, W.J., 2022. Viral community-wide auxiliary metabolic genes differ by lifestyles, habitats, and hosts. Microbiome10, 190.

[79]

Ma, B., Lu, C.Y., Wang, Y.L., Yu, J.W., Zhao, K.K., Xue, R., Ren, H., Lv, X.F., Pan, R.H., Zhang, J.B., Zhu, Y.G., Xu, J.M., 2023. A genomic catalogue of soil microbiomes boosts mining of biodiversity and genetic resources. Nature Communications14, 7318.

[80]

Ma, B., Stirling, E., Liu, Y.H., Zhao, K.K., Zhou, J.Z., Singh, B.K., Tang, C.X., Dahlgren, R.A., Xu, J.M., 2021. Soil biogeochemical cycle couplings inferred from a function-taxon network. Research2021, 7102769.

[81]

Ma, B., Wang, Y.L., Zhao, K.K., Stirling, E., Lv, X.F., Yu, Y.J., Hu, L.F., Tang, C., Wu, C.Y., Dong, B.Y., Xue, R., Dahlgren, R.A., Tan, X.F., Dai, H.Y., Zhu, Y.- G., Chu, H.Y., Xu, J.M., 2024. Biogeographic patterns and drivers of soil viromes. Nature Ecology & Evolution8, 717–728.

[82]

Malik, A.A., Thomson, B.C., Whiteley, A.S., Bailey, M., Griffiths, R.I., 2017. Bacterial physiological adaptations to contrasting edaphic conditions identified using landscape scale metagenomics. mBio8, e00799–17.

[83]

Manning, P., van der Plas, F., Soliveres, S., Allan, E., Maestre, F.T., Mace, G., Whittingham, M.J., Fischer, M., 2018. Redefining ecosystem multifunctionality. Nature Ecology & Evolution2, 427–436.

[84]

Martin, M., 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal17, 10–12.

[85]

McGrath, J.W., Chin, J.P., Quinn, J.P., 2013. Organophosphonates revealed: new insights into the microbial metabolism of ancient molecules. Nature Reviews Microbiology11, 412–419.

[86]

Minh, B.Q., Schmidt, H.A., Chernomor, O., Schrempf, D., Woodhams, M.D., von Haeseler, A., Lanfear, R., 2020. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Molecular Biology and Evolution37, 2461–2461.

[87]

Mirdita, M., Steinegger, M., Breitwieser, F., Söding, J., Karin, E.L., 2021. Fast and sensitive taxonomic assignment to metagenomic contigs. Bioinformatics37, 3029–3031.

[88]

Nair, R.M., Boddepalli, V.N., Yan, M.R., Kumar, V., Gill, B., Pan, R.S., Wang, C.S., Hartman, G.L., Souza, R.S.E., Somta, P., 2023. Global status of vegetable soybean. Plants12, 609.

[89]

Navarro-Muñoz, J.C., Selem-Mojica, N., Mullowney, M.W., Kautsar, S.A., Tryon, J.H., Parkinson, E.I., De Los Santos, E.L.C., Yeong, M., Cruz-Morales, P., Abubucker, S., Roeters, A., Lokhorst, W., Fernandez-Guerra, A., Cappelini, L.T.D., Goering, A.W., Thomson, R.J., Metcalf, W.W., Kelleher, N.L., Barona-Gomez, F., Medema, M.H., 2020. A computational framework to explore large-scale biosynthetic diversity. Nature Chemical Biology16, 60–68.

[90]

Nayfach, S., Camargo, A.P., Schulz, F., Eloe-Fadrosh, E., Roux, S., Kyrpides, N.C., 2021a. CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nature Biotechnology39, 578–585.

[91]

Nayfach, S., Páez-Espino, D., Call, L., Low, S.J., Sberro, H., Ivanova, N.N., Proal, A.D., Fischbach, M.A., Bhatt, A.S., Hugenholtz, P., Kyrpides, N.C., 2021b. Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome. Nature Microbiology6, 960–970.

[92]

Nilsson, R.H., Larsson, K.H., Taylor, A.F.S., Bengtsson-Palme, J., Jeppesen, T.S., Schigel, D., Kennedy, P., Picard, K., Glöckner, F.O., Tedersoo, L., Saar, I., Kõljalg, U., Abarenkov, K., 2019. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research47, D259–D264.

[93]

Nissen, J.N., Johansen, J., Allesøe, R.L., Sønderby, C.K., Armenteros, J.J.A., Grønbech, C.H., Jensen, L.J., Nielsen, H.B., Petersen, T.N., Winther, O., Rasmussen, S., 2021. Improved metagenome binning and assembly using deep variational autoencoders. Nature Biotechnology39, 555–560.

[94]

O'Leary, N.A., Wright, M.W., Brister, J.R., Ciufo, S., Haddad, D., McVeigh, R., Rajput, B., Robbertse, B., Smith-White, B., Ako-Adjei, D., Astashyn, A., Badretdin, A., Bao, Y.M., Blinkova, O., Brover, V., Chetvernin, V., Choi, J., Cox, E., Ermolaeva, O., Farrell, C.M., Goldfarb, T., Gupta, T., Haft, D., Hatcher, E., Hlavina, W., Joardar, V.S., Kodali, V.K., Li, W.J., Maglott, D., Masterson, P., McGarvey, K.M., Murphy, M.R., O'Neill, K., Pujar, S., Rangwala, S.H., Rausch, D., Riddick, L.D., Schoch, C., Shkeda, A., Storz, S.S., Sun, H.Z., Thibaud-Nissen, F., Tolstoy, I., Tully, R.E., Vatsan, A.R., Wallin, C., Webb, D., Wu, W., Landrum, M.J., Kimchi, A., Tatusova, T., DiCuccio, M., Kitts, P., Murphy, T.D., Pruitt, K.D., 2016. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Research44, D733–D745.

[95]

Olm, M.R., Brown, C.T., Brooks, B., Banfield, J.F., 2017. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. The ISME Journal11, 2864–2868.

[96]

Paez-Espino, D., Eloe-Fadrosh, E.A., Pavlopoulos, G.A., Thomas, A.D., Huntemann, M., Mikhailova, N., Rubin, E., Ivanova, N.N., Kyrpides, N.C., 2016. Uncovering Earth’s virome. Nature536, 425–430.

[97]

Pan, S.J., Zhu, C.K., Zhao, X.M., Coelho, L.P., 2022. A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments. Nature Communications13, 2326.

[98]

Parks, D.H., Chuvochina, M., Rinke, C., Mussig, A.J., Chaumeil, P.A., Hugenholtz, P., 2022. GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Research50, D785–D794.

[99]

Parks, D.H., Chuvochina, M., Waite, D.W., Rinke, C., Skarshewski, A., Chaumeil, P.A., Hugenholtz, P., 2018. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nature Biotechnology36, 996–1004.

[100]

Piton, G., Allison, S.D., Bahram, M., Hildebrand, F., Martiny, J.B.H., Treseder, K.K., Martiny, A.C., 2023. Life history strategies of soil bacterial communities across global terrestrial biomes. Nature Microbiology8, 2093–2102.

[101]

Pratama, A.A., Bolduc, B., Zayed, A.A., Zhong, Z.P., Guo, J.R., Vik, D.R., Gazitúa, M.C., Wainaina, J.M., Roux, S., Sullivan, M.B., 2021. Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation. PeerJ9, e11447.

[102]

Qian, L., Yu, X.L., Gu, H., Liu, F., Fan, Y.J., Wang, C., He, Q., Tian, Y., Peng, Y.S., Shu, L.F., Wang, S.Q., Huang, Z.J., Yan, Q.Y., He, J.G., Liu, G.L., Tu, Q.C., He, Z.L., 2023. Vertically stratified methane, nitrogen and sulphur cycling and coupling mechanisms in mangrove sediment microbiomes. Microbiome11, 71.

[103]

Qian, L., Yu, X.L., Zhou, J.Y., Gu, H., Ding, J.J., Peng, Y.S., He, Q., Tian, Y., Liu, J.H., Wang, S.Q., Wang, C., Shu, L.F., Yan, Q.Y., He, J.G., Liu, G.L., Tu, Q.C., He, Z.L., 2022. MCycDB: a curated database for comprehensively profiling methane cycling processes of environmental microbiomes. Molecular Ecology Resources22, 1803–1823.

[104]

Rognes, T., Flouri, T., Nichols, B., Quince, C., Mahé, F., 2016. VSEARCH: a versatile open source tool for metagenomics. PeerJ4, e2584.

[105]

Rosseel, Y., 2012. lavaan: an R package for structural equation modeling. Journal of Statistical Software48, 1–36.

[106]

Roux, S., Adriaenssens, E.M., Dutilh, B.E., Koonin, E.V., Kropinski, A.M., Krupovic, M., Kuhn, J.H., Lavigne, R., Brister, J.R., Varsani, A., Amid, C., Aziz, R.K., Bordenstein, S.R., Bork, P., Breitbart, M., Cochrane, G.R., Daly, R.A., Desnues, C., Duhaime, M.B., Emerson, J.B., Enault, F., Fuhrman, J.A., Hingamp, P., Hugenholtz, P., Hurwitz, B.L., Ivanova, N.N., Labonté, J.M., Lee, K.B., Malmstrom, R.R., Martinez-Garcia, M., Mizrachi, I.K., Ogata, H., Páez-Espino, D., Petit, M.A., Putonti, C., Rattei, T., Reyes, A., Rodriguez-Valera, F., Rosario, K., Schriml, L., Schulz, F., Steward, G.F., Sullivan, M.B., Sunagawa, S., Suttle, C.A., Temperton, B., Tringe, S.G., Thurber, R.V., Webster, N.S., Whiteson, K.L., Wilhelm, S.W., Wommack, K.E., Woyke, T., Wrighton, K.C., Yilmaz, P., Yoshida, T., Young, M.J., Yutin, N., Allen, L.Z., Kyrpides, N.C., Eloe-Fadrosh, E.A., 2019. Minimum Information about an Uncultivated Virus Genome (MIUViG). Nature Biotechnology37, 29–37.

[107]

Roux, S., Brum, J.R., Dutilh, B.E., Sunagawa, S., Duhaime, M.B., Loy, A., Poulos, B.T., Solonenko, N., Lara, E., Poulain, J., Pesant, S., Kandels-Lewis, S., Dimier, C., Picheral, M., Searson, S., Cruaud, C., Alberti, A., Duarte, C.M., Gasol, J.M., Vaqué, D., Bork, P., Acinas, S.G., Wincker, P., Sullivan, M.B., 2016. Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses. Nature537, 689–693.

[108]

Santos-Medellin, C., Zinke, L.A., Ter Horst, A.M., Gelardi, D.L., Parikh, S.J., Emerson, J.B., 2021. Viromes outperform total metagenomes in revealing the spatiotemporal patterns of agricultural soil viral communities. The ISME Journal15, 1956–1970.

[109]

Sayers, E.W., Cavanaugh, M., Clark, K., Pruitt, K.D., Schoch, C.L., Sherry, S.T., Karsch-Mizrachi, I., 2022. GenBank. Nucleic Acids Research50, D161–D164.

[110]

Shaffer, M., Borton, M.A., McGivern, B.B., Zayed, A.A., La Rosa, S.L., Solden, L.M., Liu, P.F., Narrowe, A.B., Rodriguez-Ramos, J., Bolduc, B., Gazitúa, M.C., Daly, R.A., Smith, G.J., Vik, D.R., Pope, P.B., Sullivan, M.B., Roux, S., Wrighton, K.C., 2020. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Research48, 8883–8900.

[111]

Shang, J.Y., Tang, X.B., Sun, Y.N., 2023. PhaTYP: predicting the lifestyle for bacteriophages using BERT. Briefings in Bioinformatics24, bbac487.

[112]

Sinsabaugh, R.L., Hill, B.H., Follstad Shah, J.J., 2009. Ecoenzymatic stoichiometry of microbial organic nutrient acquisition in soil and sediment. Nature462, 795–798.

[113]

Steinegger, M., Söding, J., 2017. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology35, 1026–1028.

[114]

Stewart, C.J., Ajami, N.J., O'Brien, J.L., Hutchinson, D.S., Smith, D.P., Wong, M.C., Ross, M.C., Lloyd, R.E., Doddapaneni, H., Metcalf, G.A., Muzny, D., Gibbs, R.A., Vatanen, T., Huttenhower, C., Xavier, R.J., Rewers, M., Hagopian, W., Toppari, J., Ziegler, A.G., She, J.X., Akolkar, B., Lernmark, A., Hyoty, H., Vehik, K., Krischer, J.P., Petrosino, J.F., 2018. Temporal development of the gut microbiome in early childhood from the TEDDY study. Nature562, 583–588.

[115]

Terlouw, B.R., Blin, K., Navarro-Munoz, J.C., Avalon, N.E., Chevrette, M.G., Egbert, S., Lee, S., Meijer, D., Recchia, M.J.J., Reitz, Z.L., van Santen, J.A., Selem-Mojica, N., Torring, T., Zaroubi, L., Alanjary, M., Aleti, G., Aguilar, C., Al-Salihi, S.A.A., Augustijn, H.E., Avelar-Rivas, J.A., Avitia-Dominguez, L.A., Barona-Gomez, F., Bernaldo-Aguero, J., Bielinski, V.A., Biermann, F., Booth, T.J., Carrion Bravo, V.J., Castelo-Branco, R., Chagas, F.O., Cruz-Morales, P., Du, C., Duncan, K.R., Gavriilidou, A., Gayrard, D., Gutierrez-Garcia, K., Haslinger, K., Helfrich, E.J.N., van der Hooft, J.J.J., Jati, A.P., Kalkreuter, E., Kalyvas, N., Kang, K.B., Kautsar, S., Kim, W., Kunjapur, A.M., Li, Y.X., Lin, G.M., Loureiro, C., Louwen, J.J.R., Louwen, N.L.L., Lund, G., Parra, J., Philmus, B., Pourmohsenin, B., Pronk, L.J.U., Rego, A., Rex, D.A.B., Robinson, S., Rosas-Becerra, L.R., Roxborough, E.T., Schorn, M.A., Scobie, D.J., Singh, K.S., Sokolova, N., Tang, X., Udwary, D., Vigneshwari, A., Vind, K., Vromans, S., Waschulin, V., Williams, S.E., Winter, J.M., Witte, T.E., Xie, H., Yang, D., Yu, J., Zdouc, M., Zhong, Z., Collemare, J., Linington, R.G., Weber, T., Medema, M.H., 2023. MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters. Nucleic Acids Research51, D603–D610.

[116]

Toju, H., Peay, K.G., Yamamichi, M., Narisawa, K., Hiruma, K., Naito, K., Fukuda, S., Ushio, M., Nakaoka, S., Onoda, Y., Yoshida, K., Schlaeppi, K., Bai, Y., Sugiura, R., Ichihashi, Y., Minamisawa, K., Kiers, E.T., 2018. Core microbiomes for sustainable agroecosystems. Nature Plants4, 247–257.

[117]

Tu, Q.C., Lin, L., Cheng, L., Deng, Y., He, Z.L., 2019. NCycDB: a curated integrative database for fast and accurate metagenomic profiling of nitrogen cycling genes. Bioinformatics35, 1040–1048.

[118]

Uritskiy, G.V., DiRuggiero, J., Taylor, J., 2018. MetaWRAP-a flexible pipeline for genome-resolved metagenomic data analysis. Microbiome6, 158.

[119]

USDA, 2019. Agricultural Chemical Use Survey-Wheat. .

[120]

USDA, 2021. Agricultural Chemical Use Survey-Corn. .

[121]

USDA, 2023. Agricultural Chemical Use Survey-Soybeans. .

[122]

Walker, A.S., Clardy, J., 2021. A machine learning bioinformatics method to predict biological activity from biosynthetic gene clusters. Journal of Chemical Information and Modeling61, 2560–2571.

[123]

Wang, C., Yu, Q.Y., Ji, N.N., Zheng, Y., Taylor, J.W., Guo, L.D., Gao, C., 2023a. Bacterial genome size and gene functional diversity negatively correlate with taxonomic diversity along a pH gradient. Nature Communications14, 7437.

[124]

Wang, D.P., Zhang, Y.B., Zhang, Z., Zhu, J., Yu, J., 2010. KaKs_Calculator 2.0: a toolkit incorporating gamma-series methods and sliding window strategies. Genomics, Proteomics & Bioinformatics 8, 77–80.

[125]

Wang, H.G., Wei, Z., Mei, L.J., Gu, J.X., Yin, S.S., Faust, K., Raes, J., Deng, Y., Wang, Y.L., Shen, Q.R., Yin, S.X., 2017. Combined use of network inference tools identifies ecologically meaningful bacterial associations in a paddy soil. Soil Biology and Biochemistry105, 227–235.

[126]

Wang, J., Wu, L., Xiao, Q., Huang, Y.P., Liu, K.L., Wu, Y., Li, D.C., Duan, Y.H., Zhang, W.J., 2023b. Long-term manuring enhances soil gross nitrogen mineralization and ammonium immobilization in subtropical area. Agriculture, Ecosystems & Environment348, 108439.

[127]

Westoby, M., Gillings, M.R., Madin, J.S., Nielsen, D.A., Paulsen, I.T., Tetu, S.G., 2021. Trait dimensions in bacteria and archaea compared to vascular plants. Ecology Letters24, 1487–1504.

[128]

Wu, X.J., Peng, J.J., Malik, A.A., Peng, Z.H., Luo, Y., Fan, F.L., Lu, Y.H., Wei, G.H., Delgado-Baquerizo, M., Liesack, W., Jiao, S., 2025. A global relationship between genome size and encoded carbon metabolic strategies of soil bacteria. Ecology Letters28, e70064.

[129]

Xu, S.B., Dai, Z.H., Guo, P.F., Fu, X.C., Liu, S.S., Zhou, L., Tang, W.L., Feng, T.Z., Chen, M.J., Zhan, L., Wu, T.Z., Hu, E.Q., Jiang, Y., Bo, X.C., Yu, G.C., 2021. ggtreeExtra: compact visualization of richly annotated phylogenetic data. Molecular Biology and Evolution38, 4039–4042.

[130]

Xun, W.B., Li, W., Xiong, W., Ren, Y., Liu, Y.P., Miao, Y.Z., Xu, Z.H., Zhang, N., Shen, Q.R., Zhang, R.F., 2019. Diversity-triggered deterministic bacterial assembly constrains community functions. Nature Communications10, 3833.

[131]

Yang, G.W., Wagg, C., Veresoglou, S.D., Hempel, S., Rillig, M.C., 2018. How soil biota drive ecosystem stability. Trends in Plant Science23, 1057–1067.

[132]

Yao, Q.M., Li, Z., Song, Y., Wright, S.J., Guo, X., Tringe, S.G., Tfaily, M.M., Paša-Tolić, L., Hazen, T.C., Turner, B.L., Mayes, M.A., Pan, C.L., 2018. Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil. Nature Ecology & Evolution2, 499–509.

[133]

Yu, G.C., Smith, D.K., Zhu, H.C., Guan, Y., Lam, T.T.Y., 2017. GGTREE: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution8, 28–36.

[134]

Yu, M.S., Zhang, M.H., Zeng, R.Y., Cheng, R.L., Zhang, R., Hou, Y.P., Kuang, F.F., Feng, X.J., Dong, X.Y., Li, Y.F., Shao, Z.Z., Jin, M., 2024. Diversity and potential host-interactions of viruses inhabiting deep-sea seamount sediments. Nature Communications15, 3228.

[135]

Yu, X.L., Zhou, J.Y., Song, W., Xu, M.Z., He, Q., Peng, Y.S., Tian, Y., Wang, C., Shu, L.F., Wang, S.Q., Yan, Q.Y., Liu, J.H., Tu, Q.C., He, Z.L., 2021. SCycDB: a curated functional gene database for metagenomic profiling of sulphur cycling pathways. Molecular Ecology Resources21, 924–940.

[136]

Yu, X.M., Doroghazi, J.R., Janga, S.C., Zhang, J.K., Circello, B., Griffin, B.M., Labeda, D.P., Metcalf, W.W., 2013. Diversity and abundance of phosphonate biosynthetic genes in nature. Proceedings of the National Academy of Sciences of the United States of America110, 20759–20764.

[137]

Yuan, M.M., Guo, X., Wu, L.W., Zhang, Y., Xiao, N.J., Ning, D.L., Shi, Z., Zhou, X.S., Wu, L.Y., Yang, Y.F., Tiedje, J.M., Zhou, J.Z., 2021. Climate warming enhances microbial network complexity and stability. Nature Climate Change11, 343–348.

[138]

Zang, H.D., Mehmood, I., Kuzyakov, Y., Jia, R., Gui, H., Blagodatskaya, E., Xu, X.L., Smith, P., Chen, H.Q., Zeng, Z.H., Fan, M.S., 2024. Not all soil carbon is created equal: labile and stable pools under nitrogen input. Global Change Biology30, e17405.

[139]

Zeng, J.X., Tu, Q.C., Yu, X.L., Qian, L., Wang, C., Shu, L.F., Liu, F., Liu, S.W., Huang, Z.J., He, J.G., Yan, Q.Y., He, Z.L., 2022. PCycDB: a comprehensive and accurate database for fast analysis of phosphorus cycling genes. Microbiome10, 101.

[140]

Zeng, Q.X., Peñuelas, J., Sardans, J., Zhang, Q.F., Zhou, J.C., Yue, K., Chen, Y., Yang, Y.S., Fan, Y.X., 2024. Keystone bacterial functional module activates P-mineralizing genes to enhance enzymatic hydrolysis of organic P in a subtropical forest soil with 5-year N addition. Soil Biology and Biochemistry192, 109383.

[141]

Zhang, K.L., Maltais-Landry, G., Liao, H.L., 2021. How soil biota regulate C cycling and soil C pools in diversified crop rotations. Soil Biology and Biochemistry156, 108219.

[142]

Zhang, Z., Xiao, J.F., Wu, J.Y., Zhang, H.Y., Liu, G.M., Wang, X.M., Dai, L., 2012. ParaAT: a parallel tool for constructing multiple protein-coding DNA alignments. Biochemical and Biophysical Research Communications419, 779–781.

[143]

Zimmerman, A.E., Howard-Varona, C., Needham, D.M., John, S.G., Worden, A.Z., Sullivan, M.B., Waldbauer, J.R., Coleman, M.L., 2020. Metabolic and biogeochemical consequences of viral infection in aquatic ecosystems. Nature Reviews Microbiology18, 21–34.

RIGHTS & PERMISSIONS

Higher Education Press

AI Summary AI Mindmap
PDF (7716KB)

Supplementary files

Supplementary Information

170

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/