PS 16-10 - Correlations between cyanobacteria and other bacterioplankton in freshwater lakes

Tuesday, August 8, 2017
Exhibit Hall, Oregon Convention Center
Jin Zeng1, Feng Shen2, Dayong Zhao2, Rui Huang2 and Qinglong Wu1, (1)State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, CAS, Nanjing, China, (2)Hohai University, Nanjing, China
Background/Question/Methods

In recent years, great attention has been paid to the eutrophication in freshwater ecosystems, especially in Chinese lakes. Bacterioplankton, which have an extremely high level of genetic diversity, are a fundamental component of the lake ecosystem and play essential roles in the global biogeochemical cycles. Therefore, investigating the community compositions and ecological functions of the bacterioplankton in freshwater lakes is of great importance for better understanding the freshwater ecosystem. In the past few years, correlation-based network analysis has been successfully applied to explore the co-occurrence and co-exclusion patterns of microbial communities. But less study was conducted to examine the interactions between cyanobacteria and other bacterioplankton in eutrophied freshwater lakes

In the present study, high-throughput sequencing was employed to investigate the seasonal variations in the composition of bacterioplankton communities in six eutrophic urban lakes of Nanjing City, China. Association network approaches were used for exploring the associations between bacterial communities.

Results/Conclusions

Over 150,000 16S rRNA sequences were derived from 52 water samples, and correlation-based network analyses were conducted. The architecture of the co-occurrence networks varied in different seasons. Cyanobacteria played various roles in the ecological networks during different seasons. Co-occurrence patterns revealed that members of Cyanobacteria shared a very similar niche and they had weak positive correlations with other phyla in summer. To explore the effect of environmental factors on species-species co-occurrence networks and to determine the most influential environmental factors, the original positive network was simplified by module partitioning and by calculating module eigengenes. Module eigengene analysis indicated that temperature only affected some Cyanobacteria; the rest were mainly affected by nitrogen associated factors throughout the year. Cyanobacteria were dominant in summer which may result from strong co-occurrence patterns and suitable living conditions.

Overall, this study has improved our understanding of the roles of Cyanobacteria and other bacterioplankton in ecological networks.