The effect of long-term application of nitrogen-rich fertilizers on soil resistome: A study of conventional and organic cropping systems

doi:10.1007/s42832-023-0215-1

2024, Vol. 6

Issue (3) : 230215 https://doi.org/10.1007/s42832-023-0215-1

The effect of long-term application of nitrogen-rich fertilizers on soil resistome: A study of conventional and organic cropping systems

Alexey S. Vasilchenko¹(

), Evgenii O. Burlakov^2,³, Darya V. Poshvina¹, Denis S. Gruzdev⁴, Sergey V. Kravchenko¹, Aleksandr V. Iashnikov¹, Ning Ling⁵, Anastasia V. Vasilchenko¹

¹. Laboratory of Antimicrobial Resistance, Institute of Environmental and Agricultural Biology (X-BIO), Tyumen State University, Tyumen, Russia
². Research Institute of Mathematics, Physics and Computer Science, Derzhavin Tambov State University, Tambov, Russia
³. International Integrated Research Laboratory for Climate Change, Land Use and Biodiversity, Institute of Environmental and Agricultural Biology (X-BIO), Tyumen State University, Tyumen, Russia
⁴. SciBear OU, Tartu Mnt 67/1-13b, Kesklinna Linnaosa, 10115 Tallinn, Estonia
⁵. Center for Grassland Microbiome, State Key Laboratory of Grassland Agro-Ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China

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Abstract

● Soil resistomes of conventional and organic systems were similar in terms of ARG biodiversity.

● Soil resistomes of conventional and organic systems were different regarding individual ARGs.

● Uncultivated bacteria and archaea can contribute significantly to soil resistome.

Metagenomic studies of various soil environments have previously revealed the widespread distribution of antibiotic resistance genes (ARGs) around the globe. In this study, we applied shotgun metagenomics to investigate differences in microbial communities and resistomes in Chernozem soils that have been under long-term organic and conventional cropping practices. The organic cropping system was seeded with Triticum spelta without any fertilizer. The conventional cropping system was seeded with Tríticum durum Desf and used mineral fertilizer (NPK), that resulted in an increased amount of total and available carbon and nitrogen in soils. Across all samples, we identified a total of 21 ARG classes, among which the dominant were vancomycin, tetracycline and multidrug. Profiling of soil microbial communities revealed differences between the studied fields in the relative abundances of 14 and 53 genera in topsoil and subsoil, respectively. Correlation analysis showed significant correlations (positive and negative) among 18 genera and 6 ARGs, as well as between these ARGs and some chemical properties of soils. The analysis of metagenome-assembled genomes revealed that Nitrospirota, Thermoproteota, Actinobacteriota and Binatota phyla of archaea and bacteria serve as hosts for glycopeptide and fluoroquinolone/tetracycline ARGs. Collectively, the data obtained enrich knowledge about the consequences of human agricultural activities in terms of soil microbiome modification and highlight the role of nitrogen cycling taxa, including uncultivated genera, in the formation of soil resistome.

Keywords soil microbiome inorganic fertilizer nitrogen cycle uncultured bacteria chemolithotrophs Binatia

Corresponding Author(s): Alexey S. Vasilchenko

Issue Date: 12 January 2024

Cite this article:

Alexey S. Vasilchenko,Evgenii O. Burlakov,Darya V. Poshvina, et al. The effect of long-term application of nitrogen-rich fertilizers on soil resistome: A study of conventional and organic cropping systems[J]. Soil Ecology Letters, 2024, 6(3): 230215.

URL:

https://academic.hep.com.cn/sel/EN/10.1007/s42832-023-0215-1
https://academic.hep.com.cn/sel/EN/Y2024/V6/I3/230215

Tab.1 Chemical properties of the soils.

Fig.1 Beta-diversity of soil microbial community of organic and conventional cropping systems. PCoA analysis of variations in the relative abundance of prokaryotic phyla (A). Heat map of the most common prokaryotic phyla, built on the basis of the average abundance for all samples (B).

Tab.2 Two-way PERMANOVA based on Bray−Curtis similarity output of the effects of cropping systems, sampling depth and their interactions on soil microbial communities and ARGs.

Fig.2 The differences in soil bacterial community compositions of organic and conventional cropping systems. The Shannon biodiversity indices of soil microbial communities of the various cropping systems and sampling depths (A). The relative abundance of microbial genera expressed as the log₂fold change values between conventional and organic cropping systems. Only genera with significance difference (p < 0.05, two-sample t-test) between two cropping systems are presented. Soils were sampled at the topsoil (0−5 cm) (B) and the subsoil (5−15 cm) (C).

Tab.3 Annotation of assembled genomes for ARGs and biosynthetic gene clusters.

Fig.3 Heatmap showing the abundance of ARG classes across various cropping systems and soil sampling depth (A). PCoA analysis of ARGs distribution across the samples (B). Shannon diversity indices of soil resistomes (C). The histogram of the distribution of ARGs among the soil samples studied, selected from the topsoil (0−5 cm) and subsoil (5−15 cm) of conventional and organic cropping systems. Only antibiotics for which differences between samples were significant (p < 0.05, two-sample t-test) are shown (D).

Fig.4 Heatmap of distribution of ARG gene families (A) and resistance mechanisms (B) across the study soil groups. Data are presented as the mean gene copy numbers (A) and percent (B) in soils across various cropping systems and soil sampling depth.

Fig.5 Correlation analysis between genera, ARGs and soil chemical properties across all soil samples. Only genera with significative correlation (Spearman R_s > 0.8 and p < 0.01) with at least one ARGs are represented (A). Relative “weights” of predictors for multidrug and beta-lactam ARGs based on their abundance in soils (B). Heatmap of Pearson’s correlation coefficients of the relative abundance of ARGs and the chemical properties of the soils (p < 0.05).

1	B.P., Alcock, W., Huynh, R., Chalil, K.W., Smith, A.R., Raphenya, M.A., Wlodarski, A., Edalatmand, A., Petkau, S.A., Syed, K.K., Tsang, S.J.C., Baker, M., Dave, M.C., McCarthy, K.M., Mukiri, J.A., Nasir, B., Golbon, H., Imtiaz, X., Jiang, K., Kaur, M., Kwong, Z.C., Liang, K.C., Niu, P., Shan, J.Y.J., Yang, K.L., Gray, G.R., Hoad, B., Jia, T., Bhando, L.A., Carfrae, M.A., Farha, S., French, R., Gordzevich, K., Rachwalski, M.M., Tu, E., Bordeleau, D., Dooley, E., Griffiths, H.L., Zubyk, E.D., Brown, F., Maguire, R.G., Beiko, W.W.L., Hsiao, F.S.L., Brinkman, G., Van Domselaar, A.G., McArthur, 2023. CARD 2023: Expanded curation, support for machine learning, and resistome prediction at the comprehensive antibiotic resistance database. Nucleic Acids Research51, D690–D699. https://doi.org/10.1093/nar/gkac920
2	E.C., Alexopoulos, 2010. Introduction to multivariate regression analysis. Hippokratia14, 23–28.
3	H.K., Allen, L.A., Moe, J., Rodbumrer, A., Gaarder, J., Handelsman, 2009. Functional metagenomics reveals diverse beta-lactamases in a remote Alaskan soil. ISME Journal3, 243–251. https://doi.org/10.1038/ismej.2008.86
4	J., Armalyte˙, J., Skerniškyte˙, E., Bakiene˙, R., Krasauskas, R., Šiugždiniene˙, V., Kareiviene˙, S., Kerziene˙, I., Klimiene˙, E., Sužiedėlienė, M., Ružauskas, E., Sužiedeliene˙ M., Ružauskas 2019. Microbial diversity and antimicrobial resistance profile in microbiota from soils of conventional and organic farming systems. Frontiers in Microbiology10, 892. https://doi.org/10.3389/fmicb.2019.00892
5	M., Bill, L., Chidamba, J.K., Gokul, N., Labuschagne, L., Korsten, 2021. Bacterial community dynamics and functional profiling of soils from conventional and organic cropping systems. Applied Soil Ecology157, 103734. https://doi.org/10.1016/j.apsoil.2020.103734
6	K., Blin, S., Shaw, A.M., Kloosterman, Z., Charlop-Powers, G.P., van Weezel, M.H., Medema, T., Weber, 2021. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Research 49, W29–W35.
7	A.M., Bolger, M., Lohse, B., Usadel, 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics (Oxford, England)30, 2114–2120. https://doi.org/10.1093/bioinformatics/btu170
8	R.M., Bowers, N.C., Kyrpides, R., Stepanauskas, M., Harmon-Smith, D., Doud, T.B.K., Reddy, F., Schulz, J., Jarett, A.R., Rivers, E.A., Eloe-Fadrosh, S.G., Tringe, N.N., Ivanova, A., Copeland, A., Clum, E.D., Becraft, R.R., Malmstrom, B., Birren, M., Podar, P., Bork, G.M., Weinstock, G.M., Garrity, J.A., Dodsworth, S., Yooseph, G., Sutton, F.O., Glöckner, J.A., Gilbert, W.C., Nelson, S.J., Hallam, S.P., Jungbluth, T.J.G., Ettema, S., Tighe, K.T., Konstantinidis, W.T., Liu, B.J., Baker, T., Rattei, J.A., Eisen, B., Hedlund, K.D., McMahon, N., Fierer, R., Knight, R., Finn, G., Cochrane, I., Karsch-Mizrachi, G.W., Tyson, C., Rinke, A., Lapidus, F., Meyer, P., Yilmaz, D.H., Parks, A., Murat Eren, L., Schriml, J.F., Banfield, P., Hugenholtz, T., Woyke, Lapidus, A., the Genome Standards Consortium, F., Meyer, P., Yilmaz, D.H., Parks, A.M., Eren, L., Schriml, J.F., Banfield, P., Hugenholtz, T., Woyke 2017. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nature Biotechnology35, 725–731. https://doi.org/10.1038/nbt.3893
9	F., Brescia, A., Vlassi, A., Bejarano, B., Seidl, M., Marchetti-Deschmann, R., Schuhmacher, G., Puopolo, 2021. Characterisation of the antibiotic profile of Lysobacter capsici AZ78, an effective biological control agent of plant pathogenic microorganisms. Microorganisms17, 1320. https://doi.org/10.3390/microorganisms9061320
10	M., Cadena, L.M., Durso, D.N., Miller, H.M., Waldrip, B.L., Castleberry, R.A., Drijber, C., Wortmann, 2018. Tetracycline and sulfonamide antibiotic resistance genes in soils from nebraska organic farming operations. Frontiers in Microbiology9, 1283. https://doi.org/10.3389/fmicb.2018.01283
11	P.A., Chaumeil, A.J., Mussig, P., Hugenholtz, D.H., Parks, 2019. GTDB-Tk: a toolkit to classify genomes with the genome taxonomy database. Bioinformatics (Oxford, England)36, 1925–1927. https://doi.org/10.1093/bioinformatics/btz848
12	Q., Chen, X., An, H., Li, J., Su, Y., Ma, Y.G., Zhu, 2016. Long-term field application of sewage sludge increases the abundance of antibiotic resistance genes in soil. Environment International 92–93, 1–10.
13	Y., Chen, X., Liu, Y., Hou, S., Zhou, B., Zhu, 2021. Particulate organic carbon is more vulnerable to nitrogen addition than mineral-associated organic carbon in soil of an alpine meadow. Plant and Soil458, 93–103. https://doi.org/10.1007/s11104-019-04279-4
14	M., Chuvochina, C., Rinke, D.H., Parks, M.S., Rappé, G.W., Tyson, P., Yilmaz, W.B., Whitman, P., Hugenholtz, 2019. The importance of designating type material for uncultured taxa. Systematic and Applied Microbiology42, 15–21. https://doi.org/10.1016/j.syapm.2018.07.003
15	L., Crémet, P., Bemer, O., Zambon, A., Reynaud, N., Caroff, S., Corvec, 2009. Chitinophaga terrae bacteremia in human. Emerging Infectious Diseases15, 1134–1135. https://doi.org/10.3201/eid1507.090124
16	V.M., D’Costa, K.M., McGrann, D.W., Hughes, G.D., Wright, 2006. Sampling the antibiotic resistome. Science311, 374–377. https://doi.org/10.1126/science.1120800
17	M., Delgado-Baquerizo, H.W., Hu, F.T., Maestre, C.A., Guerra, N., Eisenhauer, D.J., Eldridge, Y.G., Zhu, Q.L., Chen, P., Trivedi, S., Du, T.P., Makhalanyane, J.P., Verma, B., Gozalo, V., Ochoa, S., Asensio, L., Wang, E., Zaady, J.G., Illán, C., Siebe, T., Grebenc, X., Zhou, Y.R., Liu, A.R., Bamigboye, J.L., Blanco-Pastor, J., Duran, A., Rodríguez, S., Mamet, F., Alfaro, S., Abades, A.L., Teixido, G.F., Peñaloza-Bojacá, M.A., Molina-Montenegro, C., Torres-Díaz, C., Perez, A., Gallardo, L., García-Velázquez, P.E., Hayes, S., Neuhauser, J.Z., He, 2022. The global distribution and environmental drivers of the soil antibiotic resistome. Microbiome10, 219. https://doi.org/10.1186/s40168-022-01405-w
18	L.C., Dinca, P., Grenni, C., Onet, A., Onet, 2022. Fertilization and soil microbial community: A review. Applied Sciences (Basel, Switzerland)12, 1198. https://doi.org/10.3390/app12031198
19	W., Durner, S.C., Iden, G., von Unold, 2017. The integral suspension pressure method (ISP) for precise particle−size analysis by gravitational sedimentation. Water Resources Research53, 33–48. https://doi.org/10.1002/2016WR019830
20	D.C., Edmeades, 2003. The long-term effects of manures and fertilisers on soil productivity and quality: a review. Nutrient Cycling in Agroecosystems66, 165–180. https://doi.org/10.1023/A:1023999816690
21	L., Epelde, L., Jauregi, J., Urra, L., Ibarretxe, J., Romo, I., Goikoetxea, C., Garbisu, 2018. Characterization of composted organic amendments for agricultural use. Frontiers in Sustainable Food Systems2, 44. https://doi.org/10.3389/fsufs.2018.00044
22	K.J., Fosberg, S., Patel, M.K., Gibson, C.L., Lauber, R., Knight, N., Fierer, G., Dantas, 2016. Bacterial phylogeny structures soil resistomes across habitats. Nature5909, 612–616. https://doi.org/10.1038/nature13377
23	R.D., Finn, P., Coggill, R.Y., Eberhardt, S.R., Eddy, J., Mistry, A.L., Mitchell, S.C., Potter, M., Punta, M., Qureshi, A., Sangrador-Vegas, G.A., Salazar, J., Tate, A., Bateman, 2016. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Research44, D279–D285. https://doi.org/10.1093/nar/gkv1344
24	D., Francioli, E., Schulz, G., Lentendu, T., Wubet, F., Buscot, T., Reitz, 2016. Mineral vs. organic amendments: Microbial community structure, activity and abundance of agriculturally relevant microbes are driven by long-term fertilization strategies. Frontiers in Microbiology7, 1446. https://doi.org/10.3389/fmicb.2016.01446
25	M.Y., Galperin, K.S., Makarova, Y.I., Wolf, E.V., and Koonin, 2014. Expanded microbial genome coverage and improved protein family annotation in the COG database. Nucleic Acids Research43, D261–D269. https://doi.org/10.1093/nar/gku1223
26	S., Ghosh, B., Wilson, S., Ghoshal, N., Senapati, B., Mandal, 2012. Organic amendments influence soil quality and carbon sequestration in the Indo-Gangetic plains of India. Agriculture, Ecosystems & Environment156, 134–141. https://doi.org/10.1016/j.agee.2012.05.009
27	A., Gurevich, V., Saveliev, N., Vyahhi, G., Tesler, 2013. QUAST: quality assessment tool for genome assemblies. Bioinformatics (Oxford, England)29, 1072–1075. https://doi.org/10.1093/bioinformatics/btt086
28	Ø., Hammer, D.A.T., Harper, P.D., Ryan, 2001. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica,4, 9.
29	J., Hao, Y.N., Chai, L.D., Lopes, R.A., Ordóñez, E.E., Wright, S., Archontoulis, D.P., Schachtman, 2021. The effects of soil depth on the structure of microbial communities in agricultural soils in Iowa, USA. Applied and Environmental Microbiology87, e02673–e20. https://doi.org/10.1128/AEM.02673-20
30	K., Iwata, A., Azlan, H., Yamakawa, T., Omori, 2010. Ammonia accumulation in culture broth by the novel nitrogen-fixing bacterium, Lysobacter sp. E4. Journal of Bioscience and Bioengineering 110, 415–418.
31	G.H., Ji, L.F., Wei, Y.Q., He, Y.P., Wu, X.H., Bai, 2008. Biological control of rice bacterial blight by Lysobacter antibioticus strain 13–1. Biological Control45, 288–296. https://doi.org/10.1016/j.biocontrol.2008.01.004
32	C., Jochum, L., Osborne, G., Yuen, 2006. Fusarium head blight biological control with Lysobacter enzymogenes strain C3. Biological Control39, 336–344. https://doi.org/10.1016/j.biocontrol.2006.05.004
33	D.D., Kang, F., Li, E., Kirton, A., Thomas, R., Egan, H., An, Z., Wang, 2019. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ7, e7359. https://doi.org/10.7717/peerj.7359
34	J., Kang, Y., Liu, X., Chen, F., Xu, W., Xiong, X., Li, 2022. Shifts of antibiotic resistomes in soil following amendments of antibiotics-contained dairy manure. International Journal of Environmental Research and Public Health19, 10804. https://doi.org/10.3390/ijerph191710804
35	A., Kaviani Rad, A., Astaykina, R., Streletskii, Y., Afsharyzad, H., Etesami, M., Zarei, S.K., Balasundram, 2022. An Overview of antibiotic resistance and abiotic stresses affecting antimicrobial resistance in agricultural soils. International Journal of Environmental Research and Public Health19, 4666. https://doi.org/10.3390/ijerph19084666
36	M., Kaze, L., Brooks, M., Sistrom, 2021. Antimicrobial resistance in Bacillus-based biopesticide products. Microbiology (Reading, England) 167.
37	K., Lawther, F.G., Santos, L.B., Oyama, F., Rubino, S., Morrison, C.J., Creevey, J.W., McGrath, S.A., Huws, 2022. Resistome analysis of global livestock and soil microbiomes. Frontiers in Microbiology13, 897905. https://doi.org/10.3389/fmicb.2022.897905
38	B., Li, Y., Yang, L., Ma, F., Ju, F., Guo, J.M., Tiedje, T., Zhang, 2015. Metagenomic and network analysis reveal wide distribution and co-occurrence of environmental antibiotic resistance genes. ISME Journal9, 2490–2502. https://doi.org/10.1038/ismej.2015.59
39	H., Li, 2018. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics (Oxford, England)34, 3094–3100. https://doi.org/10.1093/bioinformatics/bty191
40	S., Li, Q., Yao, J., Liu, D., Wei, B., Zhou, P., Zhu, X., Cui, J., Jin, X., Liu, G., Wang, 2020. Profiles of antibiotic resistome with animal manure application in black soils of northeast China. Journal of Hazardous Materials384, 121216. https://doi.org/10.1016/j.jhazmat.2019.121216
41	Y., Li, F., Kong, S., Li, J., Wang, J., Hu, S., Chen, Q., Chen, Y., Li, X., Ha, W., Sun, 2023. Insights into the driving factors of vertical distribution of antibiotic resistance genes in long-term fertilized soils. Journal of Hazardous Materials456, 131706. https://doi.org/10.1016/j.jhazmat.2023.131706
42	P., Liu, S., Jia, X., He, X., Zhang, L., Ye, 2017. Different impacts of manure and chemical fertilizers on bacterial community structure and antibiotic resistance genes in arable soils. Chemosphere188, 455–464. https://doi.org/10.1016/j.chemosphere.2017.08.162
43	W., Liu, Y., Cheng, J., Guo, Y., Duan, S., Wang, Q., Xu, M., Liu, C., Xue, S., Guo, Q., Shen, N., Ling, 2022. Long-term manure inputs induce a deep selection on agroecosystem soil antibiotic resistome. Journal of Hazardous Materials436, 129163. https://doi.org/10.1016/j.jhazmat.2022.129163
44	Z., Liu, Y., Zhao, B., Zhang, J., Wang, L., Zhu, B., Hu, 2023. Deterministic effect of pH on shaping soil resistome revealed by metagenomic analysis. Environmental Science & Technology57, 985–996. https://doi.org/10.1021/acs.est.2c06684
45	E.S., Miller, C.R., Woese, S., Brenner, 1991. Description of the erythromycin-producing bacterium Arthrobacter sp. strain NRRL B-3381 as Aeromicrobium erythreum gen. nov., sp. nov. International Journal of Systematic Bacteriology 41, 363–368
46	C.L., Murphy, A., Sheremet, P.F., Dunfield, J.R., Spear, R., Stepanauskas, T., Woyke, M.S., Elshahed, N.H., Youssef, 2021. Genomic analysis of the yet-uncultured Binatota reveals broad methylotrophic, alkane-degradation, and pigment production capacities. mBio12, e00985–e21. https://doi.org/10.1128/mBio.00985-21
47	J., Nesme, P., Simonet, 2015. The soil resistome: a critical review on antibiotic resistance origins, ecology and dissemination potential in telluric bacteria. Environmental Microbiology17, 913–930. https://doi.org/10.1111/1462-2920.12631
48	J.N., Nissen, J., Johansen, R.L., Allesøe, C.K., Sønderby, J.J.A., Armenteros, C.H., Grønbech, L.J., Jensen, H.B., Nielsen, T.N., Petersen, O., Winther, S., Rasmussen, 2021. Improved metagenome binning and assembly using deep variational autoencoders. Nature Biotechnology39, 555–560. https://doi.org/10.1038/s41587-020-00777-4
49	M.T., Nõlvak, K., Kanger, M., Tampere, M., Espenberg, E., Loit, H., Raave, J., Truu, 2016. Inorganic and organic fertilizers impact the abundance and proportion of antibiotic resistance and integron-integrase genes in agricultural grassland soil. Science of the Total Environment562, 678–689. https://doi.org/10.1016/j.scitotenv.2016.04.035
50	S., Nurk, D., Meleshko, A., Korobeynikov, P.A., Pevzner, 2017. metaSPAdes: a new versatile metagenomic assembler. Genome Research27, 824–834. https://doi.org/10.1101/gr.213959.116
51	K., Okonechnikov, A., Conesa, F., García-Alcalde, 2016. Qualimap 2: advanced multi-sample quality control for high-throughput sequencing data. Bioinformatics (Oxford, England)32, 292–294. https://doi.org/10.1093/bioinformatics/btv566
52	M., Pansu, J., Gautheyrou, 2007. Handbook of Soil Analysis: Mineralogical, Organic and Inorganic Methods. Springer Berlin, Heidelberg
53	D.H., Parks, M., Imelfort, C.T., Skennerton, P., Hugenholtz, G.W., Tyson, 2015. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Research25, 1043–1055. https://doi.org/10.1101/gr.186072.114
54	P., Pathak, A.S., Reddy, 2021. Vertical distribution analysis of soil organic carbon and total nitrogen in different land use patterns of an agro-organic farm. Tropical Ecology62, 386–397. https://doi.org/10.1007/s42965-021-00164-3
55	G., Puopolo, A., Raio, A., Zoina, 2010. Identification and characterization of Lysobacter capsici strain PG4: A new plant health-promoting rhizobacterium. Journal of Plant Pathology92, 157–164. https://doi.org/10.4454/jpp.v92i1.25
56	X., Qian, S., Gunturu, J., Guo, B., Chai, J.R., Cole, J., Gu, J.M., Tiedje, 2021. Metagenomic analysis reveals the shared and distinct features of the soil resistome across tundra, temperate prairie, and tropical ecosystems. Microbiome9, 108. https://doi.org/10.1186/s40168-021-01047-4
57	D., Qiu, M., Ke, Q., Zhang, F., Zhang, T., Lu, L., Sun, H., Qian, 2022. Response of microbial antibiotic resistance to pesticides: An emerging health threat. Science of the Total Environment850, 158057. https://doi.org/10.1016/j.scitotenv.2022.158057
58	J.A., Rodríguez-Ramos, M.A., Borton, B.B., McGivern, G.J., Smith, L.M., Solden, M., Shaffer, R.A., Daly, S.O., Purvine, C.D., Nicora, E.K., Eder, M., Lipton, D.W., Hoyt, J.C., Stegen, K.C., Wrighton, 2022. Genome-resolved metaproteomics decodes the microbial and viral contributions to coupled carbon and nitrogen cycling in river sediments. mSystems7, e0051622. https://doi.org/10.1128/msystems.00516-22
59	Z., Rchiad, M., Dai, C., Hamel, L.D., Bainard, B.J., Cade-Menun, Y., Terrat, M., St-Arnaud, M., Hijri, 2022. Soil depth significantly shifted microbial community structures and functions in a semiarid prairie agroecosystem. Frontiers in Microbiology13, 815890. https://doi.org/10.3389/fmicb.2022.815890
60	D.L., Rubinfeld, 2011. Reference Guide on Multiple Regression, in Reference Manual on Scientific Evidence: Third Edition. National Academies Press, Wahington, DC
61	E., Ruppé, A., Ghozlane, J., Tap, N., Pons, A.S., Alvarez, N., Maziers, T., Cuesta, S., Hernando-Amado, I., Clares, J.L., Martínez, T.M., Coque, F., Baquero, V.F., Lanza, L., Máiz, T., Goulenok, V., de Lastours, N., Amor, B., Fantin, I., Wieder, A., Andremont, W., van Schaik, M., Rogers, X., Zhang, R.J.L., Willems, A.G., de Brevern, J.M., Batto, H.M., Blottière, P., Léonard, V., Léjard, A., Letur, F., Levenez, K., Weiszer, F., Haimet, J., Doré, S.P., Kennedy, S.D., Ehrlich, 2019. Prediction of the intestinal resistome by a three-dimensional structure-based method. Nature Microbiology4, 112–123. https://doi.org/10.1038/s41564-018-0292-6
62	C., Sanz, M., Casadoi, Đ., Tadic, E.J., Pastor-López, L., Navarro-Martin, J., Parera, J., Tugues, C.A., Ortiz, J.M., Bayona, B., Piña, 2022. Impact of organic soil amendments in antibiotic levels, antibiotic resistance gene loads, and microbiome composition in corn fields and crops. Environmental Research 214, 113760.
63	T., Seemann, 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics (Oxford, England)30, 2068–2069. https://doi.org/10.1093/bioinformatics/btu153
64	C.M., Sieber, A.J., Probst, A., Sharrar, B.C., Thomas, M., Hess, S.G., Tringe, J.F., Banfield, 2018. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nature Microbiology3, 836–843. https://doi.org/10.1038/s41564-018-0171-1
65	R., Sun, X., Guo, D., Wang, H., Chu, 2015. Effects of long-term application of chemical and organic fertilizers on the abundance of microbial communities involved in the nitrogen cycle. Applied Soil Ecology95, 171–178. https://doi.org/10.1016/j.apsoil.2015.06.010
66	M.W., Van Goethem, R., Pierneef, O.K.I., Bezuidt, Y., Van De Peer, D.A., Cowan, T.P., Makhalanyane, 2018. A reservoir of ‘historical’ antibiotic resistance genes in remote pristine Antarctic soils. Microbiome6, 40. https://doi.org/10.1186/s40168-018-0424-5
67	E.D., Vance, P.C., Brookes, D.S., Jenkinson, 1987. An extraction method for measuring soil microbial biomass C. Soil Biology & Biochemistry19, 703–707. https://doi.org/10.1016/0038-0717(87)90052-6
68	A.M., Venturini, J.B., Gontijo, J.A., Mandro, F.S., Paula, C.A., Yoshiura, A.G., da França, S.M., Tsai, 2022. Genome-resolved metagenomics reveals novel archaeal and bacterial genomes from Amazonian forest and pasture soils. Microbial Genomics8, mgen000853. https://doi.org/10.1099/mgen.0.000853
69	F., Wang, W., Han, S., Chen, W., Dong, M., Qiao, C., Hu, B., Liu, 2020A. Fifteen-year application of manure and chemical fertilizers differently impacts soil ARGs and microbial community structure. Frontiers in Microbiology 11, 62
70	J., Wang, X., Tu, H., Zhang, J., Cui, K., Ni, J., Chen, Y., Cheng, J., Zhang, S.X., Chang, 2020B. Effects of ammonium-based nitrogen addition on soil nitrification and nitrogen gas emissions depend on fertilizer-induced changes in pH in a tea plantation soil. Science of the Total Environment 747, 141340
71	Y.W., Wu, B.A., Simmons, S.W., Singer, 2016. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics (Oxford, England) 32, 605–607.
72	X.L., Yin, X.T., Jiang, B.L., Chai, L.G., Li, Y., Yang, J.R., Cole, J.M., Tiedje, T., Zhang, 2018. ARGs-OAP v2.0 with an expanded SARG database and Hidden Markov Models for enhancement characterization and quantification of antibiotic resistance genes in environmental metagenomes. Bioinformatics 34, 2263–2270
73	W.Y., Xie, S.T., Yuan, M.G., Xu, X.P., Yang, Q.R., Shen, W.W., Zhang, J.Q., Su, F.J., Zhao, 2018. Long-term effects of manure and chemical fertilizers on soil antibiotic resistome. Soil Biology & Biochemistry122, 111–119. https://doi.org/10.1016/j.soilbio.2018.04.009
74	Y., Xu, H., Li, L., Tan, Q., Li, W., Liu, C., Zhang, Y., Gao, X., Wei, Q., Gong, X., Zheng, 2016. Alterations in soil microbial community composition and biomass following agricultural land use change. Scientific Reports6, 36587. https://doi.org/10.1038/srep36587
75	Y., Yang, X.T., Jiang, B.L., Chai, L.P., Ma, B., Li, A.N., Zhang, J.R., Cole, J.M., Tiedje, T., Zhang, 2016. ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database. Bioinform.32, 2346–2351. https://doi.org/10.1093/bioinformatics/btw136
76	Q., Zhang, J., Wu, F., Yang, Y., Lei, Q., Zhang, X., Cheng, 2016. Alterations in soil microbial community composition and biomass following agricultural land use change. Scientific Reports6, 36587. https://doi.org/10.1038/srep36587

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