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Data-mining of Antibiotic Resistance Genes Provides Insight into the Community Structure of Ocean Microbiome

Shiguang Hao, Pengshuo Yang, Maozhen Han, Junjie Xu, Shaojun Yu, Chaoyun Chen, Wei-Hua Chen, Houjin Zhang, Kang Ning
doi: https://doi.org/10.1101/246033
Shiguang Hao
Huazhong University of Science and Technology,College of Life Science and Technology
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Pengshuo Yang
Huazhong University of Science and Technology,College of Life Science and Technology
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Maozhen Han
Huazhong University of Science and Technology,College of Life Science and Technology
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Junjie Xu
Huazhong University of Science and Technology,College of Life Science and Technology
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Shaojun Yu
Huazhong University of Science and Technology,College of Life Science and Technology
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Chaoyun Chen
Huazhong University of Science and Technology,College of Life Science and Technology
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Wei-Hua Chen
Huazhong University of Science and Technology,College of Life Science and Technology
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Houjin Zhang
Huazhong University of Science and Technology,College of Life Science and Technology
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Kang Ning
Huazhong University of Science and Technology,College of Life Science and Technology
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  • For correspondence: ningkang@hust.edu.cn
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Abstract

Background: Antibiotics have been spread widely in environments, asserting profound effects on environmental microbes as well as antibiotic resistance genes (ARGs) within these microbes. Therefore, investigating the associations between ARGs and bacterial communities become an important issue for environment protection. Ocean microbiomes are potentially large ARG reservoirs, but the marine ARG distribution and its associations with bacterial communities remain unclear. Methods: we have utilized the big-data mining techniques on ocean microbiome data to analysis the marine ARGs and bacterial distribution on a global scale, and applied comprehensive statistical analysis to unveil the associations between ARG contents, ocean microbial community structures, and environmental factors by reanalyzing 132 metagenomic samples from the Tara Oceans project. Results: We identified in total 1,926 unique ARGs and found that: firstly, ARGs are more abundant and diverse in the mesopelagic zone than other water layers. Additionally, ARG-enriched genera are closely connected in co-occurrence network. We also found that ARG-enriched genera are often more abundant than their ARG-less neighbors. Furthermore, we found that samples from the Mediterranean that is surrounded by human activities often contain more ARGs. Conclusion: Our research for investigating the marine ARG distribution and revealing the association between ARG and bacterial communities provide a deeper insight into the marine bacterial communities. We found that ARG-enriched genera were often more abundant than their ARG-less neighbors in the same environment, indicating that genera enriched with ARGs might possess an advantage over others in the competition for survival in the oceanic microbial communities.

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The copyright holder for this preprint is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.
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  • Posted January 10, 2018.

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Data-mining of Antibiotic Resistance Genes Provides Insight into the Community Structure of Ocean Microbiome
Shiguang Hao, Pengshuo Yang, Maozhen Han, Junjie Xu, Shaojun Yu, Chaoyun Chen, Wei-Hua Chen, Houjin Zhang, Kang Ning
bioRxiv 246033; doi: https://doi.org/10.1101/246033
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Data-mining of Antibiotic Resistance Genes Provides Insight into the Community Structure of Ocean Microbiome
Shiguang Hao, Pengshuo Yang, Maozhen Han, Junjie Xu, Shaojun Yu, Chaoyun Chen, Wei-Hua Chen, Houjin Zhang, Kang Ning
bioRxiv 246033; doi: https://doi.org/10.1101/246033

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