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Gao J, Wang Z, Deng W, Sa B, Chen X, Cai R, Yan Y, Jiao N, Leung ELH, Liu D, Yan W. Improved resolution of microbial diversity in deep-sea surface sediments using PacBio long-read 16S rRNA gene sequencing. mSphere 2024; 9:e0077024. [PMID: 39530673 DOI: 10.1128/msphere.00770-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2024] [Accepted: 10/17/2024] [Indexed: 11/16/2024] Open
Abstract
16S rRNA gene sequencing is the gold standard for identifying microbial diversity in environmental communities. The Illumina short-read platform is widely used in marine environment studies due to its cost-effectiveness and high accuracy, but its limited read length restricts taxonomic identification mainly to genus or family levels. Recently, the PacBio long-read sequencing platform was developed. This method has exceptional base-level resolution exceeding 99%, thereby effectively mitigating the challenges associated with high error rates commonly observed in long-read sequencing technologies. However, few studies have compared the PacBio long-read and Illumina short-read platforms in marine deep-sea sediments. Here, the PacBio long-read and Illumina short-read platforms were compared with samples collected from the deep-sea surface sediments from the cold seep in the Shenhu area of the South China Sea offshore Pearl River Estuary. Comparisons revealed a more comprehensive taxonomic identification, α-diversity, and β-diversity by PacBio long-reads. The PacBio long-read platform exhibited higher classified rates and classified taxonomy at all levels, particularly at the species level. The PacBio long-read platform was also more accurate at capturing fine spatial-scale variations in microbial communities in sediments. Our studies will facilitate the selection of 16S rRNA sequencing platforms for investigating fine spatial-scale patterns in microbial communities in deep-sea surface sediments and serve as a crucial methodological reference for future studies on microbial diversity. IMPORTANCE The PacBio long-read platform, with its exceptional base-level resolution exceeding 99%, has advanced our comprehension of deep-sea microbial diversity. By comparing microbial community analyses conducted using the Illumina short-read and PacBio long-read sequencing platforms, we have provided an enhanced understanding of fine spatial-scale patterns in microbial community diversity with depth across a deep-sea sediment core, as well as methodological insights that will be valuable for future research in this field.
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Affiliation(s)
- Jie Gao
- Computational Virology Group, Etiology Research Center, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China
- College of Marine Science and Technology, China University of Geosciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ziming Wang
- Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Wenjie Deng
- College of Marine Science and Technology, China University of Geosciences, Wuhan, China
| | - Boxuan Sa
- College of Marine Science and Technology, China University of Geosciences, Wuhan, China
| | - Xiaoxia Chen
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
- Carbon Neutral Innovation Research Center, Xiamen University, Global ONCE Program, Xiamen, China
| | - Ruanhong Cai
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
- Carbon Neutral Innovation Research Center, Xiamen University, Global ONCE Program, Xiamen, China
| | - Yi Yan
- Computational Virology Group, Etiology Research Center, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Nianzhi Jiao
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
- Carbon Neutral Innovation Research Center, Xiamen University, Global ONCE Program, Xiamen, China
| | | | - Di Liu
- Computational Virology Group, Etiology Research Center, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wei Yan
- College of Marine Science and Technology, China University of Geosciences, Wuhan, China
- State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
- Carbon Neutral Innovation Research Center, Xiamen University, Global ONCE Program, Xiamen, China
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Wu R, Xia H, Wu Y, Zhang S, Fang J, Wang Y, Wang H, Zhu Y, Liu L, Du S. Graphene oxide inhibits the transfer of ARGs in rice by reducing the root endophytic bacterial complexity. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 368:122241. [PMID: 39186855 DOI: 10.1016/j.jenvman.2024.122241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 08/12/2024] [Accepted: 08/16/2024] [Indexed: 08/28/2024]
Abstract
Antibiotic resistance genes (ARGs) as an emerging contaminant have attracted much attention for their transfer in agricultural ecosystems. Meanwhile, graphene oxide (GO), due to its high adsorption capacity and antibacterial properties, poses potential environmental ecological risks to the occurrence of ARGs, bacteria, and plant physiological ecology. However, the impact and mechanism of GO on the transfer of ARGs in host plants remain unclear. Therefore, this study selected rice as the research object and inoculated Bacillus subtilis carrying ARGs to investigate the influence of GO on the migration of ARGs into rice and its microbiological mechanism. The study found that GO had a certain inhibitory effect on the transfer of ARGs in rice. Although GO reduced the rhizosphere pH in rice, leading to a transition in endophytic bacteria from dominance by Burkholderia to dominance by Gordonia, this process did not directly affect the transfer of ARGs in rice. Further analysis of bacterial interactions revealed that GO could inhibit the transfer of ARGs in rice by reducing the network complexity of endophytic bacteria. Additionally, GO inhibited the formation of endophytic bacterial biofilms and mobile elements, which might affect ARGs' migration in rice. This study elucidated the key microbiological ecological processes of GO on the transfer of ARGs in rice, providing fundamental information for the ecological risk assessment of GO.
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Affiliation(s)
- Ran Wu
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, 310015, China
| | - Hanche Xia
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, 310015, China
| | - Yue Wu
- Zhejiang Zhongyi Testing Research Institute Co., Ltd, Ningbo, 315040, China
| | - Siyu Zhang
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, 310015, China
| | - Jin Fang
- College of Environmental Science and Engineering, Zhejiang Gongshang University, Hangzhou, 310018, China
| | - Yuying Wang
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, 310015, China
| | - Hua Wang
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, 321004, China
| | - Yaxin Zhu
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, 310015, China
| | - Lijuan Liu
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, 310015, China
| | - Shaoting Du
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, 310015, China.
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Tao K, Jensen IT, Zhang S, Villa-Rodríguez E, Blahovska Z, Salomonsen CL, Martyn A, Björgvinsdóttir ÞN, Kelly S, Janss L, Glasius M, Waagepetersen R, Radutoiu S. Nitrogen and Nod factor signaling determine Lotus japonicus root exudate composition and bacterial assembly. Nat Commun 2024; 15:3436. [PMID: 38653767 DOI: 10.1038/s41467-024-47752-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
Symbiosis with soil-dwelling bacteria that fix atmospheric nitrogen allows legume plants to grow in nitrogen-depleted soil. Symbiosis impacts the assembly of root microbiota, but it is unknown how the interaction between the legume host and rhizobia impacts the remaining microbiota and whether it depends on nitrogen nutrition. Here, we use plant and bacterial mutants to address the role of Nod factor signaling on Lotus japonicus root microbiota assembly. We find that Nod factors are produced by symbionts to activate Nod factor signaling in the host and that this modulates the root exudate profile and the assembly of a symbiotic root microbiota. Lotus plants with different symbiotic abilities, grown in unfertilized or nitrate-supplemented soils, display three nitrogen-dependent nutritional states: starved, symbiotic, or inorganic. We find that root and rhizosphere microbiomes associated with these states differ in composition and connectivity, demonstrating that symbiosis and inorganic nitrogen impact the legume root microbiota differently. Finally, we demonstrate that selected bacterial genera characterizing state-dependent microbiomes have a high level of accurate prediction.
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Affiliation(s)
- Ke Tao
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Ib T Jensen
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- Department of Mathematical Sciences, Aalborg University, Aarhus, Denmark
| | - Sha Zhang
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Eber Villa-Rodríguez
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Zuzana Blahovska
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | | | - Anna Martyn
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- Department of Plant-Microbe Interactions, Max-Planck-Institute for Plant Breeding Research, Cologne, Germany
| | | | - Simon Kelly
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- Biotechnology, Lincoln Agritech, Canterbury, New Zealand
| | - Luc Janss
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | | | | | - Simona Radutoiu
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
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