Temporal patterns of bacterial communities in the Billings Reservoir system.

Scientific reports(2024)

引用 0|浏览6
暂无评分
摘要
In this study, high-throughput sequencing of 16S rRNA amplicons and predictive PICRUSt functional profiles were used to perform a comprehensive analysis of the temporal bacterial distribution and metabolic functions of 19 bimonthly samples collected from July 2019 to January 2020 in the surface water of Billings Reservoir, São Paulo. The results revealed that most of the bacterial 16S rRNA gene sequences belonged to Cyanobacteria and Proteobacteria, which accounted for more than 58% of the total bacterial abundance. Species richness and evenness indices were highest in surface water from summer samples (January 2020), followed by winter (July 2019) and spring samples (September and November 2019). Results also showed that the highest concentrations of sulfate (SO4-2), phosphate (P), ammonia (NH3), and nitrate (NO3-) were detected in November 2019 and January 2020 compared with samples collected in July and September 2019 (P < 0.05). Principal component analysis suggests that physicochemical factors such as pH, DO, temperature, and NH3 are the most important environmental factors influencing spatial and temporal variations in the community structure of bacterioplankton. At the genus level, 18.3% and 9.9% of OTUs in the July and September 2019 samples, respectively, were assigned to Planktothrix, while 14.4% and 20% of OTUs in the November 2019 and January 2020 samples, respectively, were assigned to Microcystis. In addition, PICRUSt metabolic analysis revealed increasing enrichment of genes in surface water associated with multiple metabolic processes rather than a single regulatory mechanism. This is the first study to examine the temporal dynamics of bacterioplankton and its function in Billings Reservoir during the winter, spring, and summer seasons. The study provides comprehensive reference information on the effects of an artificial habitat on the bacterioplankton community that can be used to interpret the results of studies to evaluate and set appropriate treatment targets.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要