4.6 Article

Network Analysis Reveals Seasonal Patterns of Bacterial Community Networks in Lake Taihu under Aquaculture Conditions

Journal

WATER
Volume 11, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/w11091868

Keywords

network analysis; bacterial community interactions; seasonal variation; aquaculture; Lake Taihu

Funding

  1. National Key R&D Program of China [2016YFC0402710]
  2. National Natural Science Foundation of China [31730013, 41621002, 41571108, 41671078, 41871096]
  3. National Key Technology RD Program [2015BAD13B01]
  4. Key Research Program of Frontier Science, CAS [QYZDJ-SSW-DQC030]
  5. Natural Science Foundation of Jiangsu Province [BK20181311]
  6. Fundamental Research Funds for the Central Universities [2018B43414]
  7. Belt and Road Special Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering [2018490211]

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Bacterial communities play essential roles in multiple ecological processes, such as primary production and nutrient recycling in aquatic systems. However, although the composition, diversity and function of bacterial communities have been well studied, little is known about the interactions and co-occurrence characteristics of these communities, let alone their seasonal patterns. To investigate the seasonal variations of bacterial community interactions, we collected water samples from four seasons in Lake Taihu and applied network analysis to reveal bacterial community interactions. Bacterial community networks were non-random in structure, and interactions among bacterial taxa in the networks varied markedly in different seasons. The autumnal bacterial network was the largest and most complex among obtained networks, whereas the spring correlation network was the simplest, having no module hubs or connectors. The important species of the networks were the dominant bacterial phyla/classes (e.g., Alphaproteobacteria and Bacteroidetes), although their relative abundance varied among seasons. The relationships between species and measured environmental variables changed over seasons; fewer environmental factors were correlated with bacterial species in the spring bacterial network, while we observed a greater number of species-environment correlations in the winter network. Our study highlights the seasonal differences in bacterial community interactions and expands our understanding of freshwater microbial ecology in systems affected by aquaculture.

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