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Jiang MZ, Zhu HZ, Zhou N, Liu C, Jiang CY, Wang Y, Liu SJ. Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks. Sci Rep 2022; 12:18145. [PMID: 36307549 PMCID: PMC9616874 DOI: 10.1038/s41598-022-23000-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 10/21/2022] [Indexed: 12/31/2022] Open
Abstract
Co-occurrence networks inferred from the abundance data of microbial communities are widely applied to predict microbial interactions. However, the high workloads of bacterial isolation and the complexity of the networks themselves constrained experimental demonstrations of the predicted microbial associations and interactions. Here, we integrate droplet microfluidics and bar-coding logistics for high-throughput bacterial isolation and cultivation from environmental samples, and experimentally investigate the relationships between taxon pairs inferred from microbial co-occurrence networks. We collected Potamogeton perfoliatus plants (including roots) and associated sediments from Beijing Olympic Park wetland. Droplets of series diluted homogenates of wetland samples were inoculated into 126 96-well plates containing R2A and TSB media. After 10 days of cultivation, 65 plates with > 30% wells showed microbial growth were selected for the inference of microbial co-occurrence networks. We cultivated 129 bacterial isolates belonging to 15 species that could represent the zero-level OTUs (Zotus) in the inferred co-occurrence networks. The co-cultivations of bacterial isolates corresponding to the prevalent Zotus pairs in networks were performed on agar plates and in broth. Results suggested that positively associated Zotu pairs in the co-occurrence network implied complicated relations including neutralism, competition, and mutualism, depending on bacterial isolate combination and cultivation time.
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Affiliation(s)
- Min-Zhi Jiang
- grid.27255.370000 0004 1761 1174State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000 People’s Republic of China
| | - Hai-Zhen Zhu
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Nan Zhou
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Chang Liu
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Cheng-Ying Jiang
- grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
| | - Yulin Wang
- grid.27255.370000 0004 1761 1174State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000 People’s Republic of China
| | - Shuang-Jiang Liu
- grid.27255.370000 0004 1761 1174State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000 People’s Republic of China ,grid.9227.e0000000119573309State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 People’s Republic of China
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