Abstract
Tengiz-Korgalzhyn Lakes system, designated under the Ramsar Convention and UNESCO World Heritage Sites, is a unique ecosystem of wetlands inhabited by more than a hundred protected and endemic species. In the context of the constant ecological pressure in the area, it is critical to investigate the lake bacterioplankton species and their relationship with abiotic factors, especially since microbiome studies of the region are practically absent in the literature. This study aims to investigate the role of salinity gradient in shaping bacterial communities in lake ecosystems, as well as the extent to which the overall abiotic factor explains the heterogeneity of microbiome composition across the region. Data on microbial communities is based on the full-length 16S amplicons obtained with the MinION mk1c. Species-level classification and analysis are performed in Emu, and R Studio, using packages phyloseq and vegan. Our research has confirmed the importance of the salinity gradient in shaping the microbiome composition in lakes. We have shown that out of all abiotic factors, salinity exerts the most influence on the composition of microbial communities. The abundance of Beta- and Gamma-proteobacteria classes changed in parallel with raising salinity levels across all sampling sites: decreasing and increasing, respectively. Moreover, salinity negatively correlated with the community evenness index across distinct small lakes, implying the presence of dominant species. The high degree of variability between isolated water bodies was mainly attributed to the geographical separation.
Original language | English |
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Number of pages | 1 |
Publication status | Published - 2023 |
Event | FEMS 2023: 10th FEMS Congress of European Microbiologists - Hamburg, Germany Duration: Jul 9 2023 → Jul 13 2023 https://www.fems2023.org/ |
Conference
Conference | FEMS 2023 |
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Country/Territory | Germany |
City | Hamburg |
Period | 7/9/23 → 7/13/23 |
Internet address |
Keywords
- Microbial community
- Salinity gradient
- 16S amplicons
- nanopore-based next generation sequencing