The frequency and severity of cyanobacterial bloom are at risk of increasing as a consequence of eutrophication and increased water temperature. The elevated cyanobacterial biovolume can have substantial impacts on water ecosystem function by producing toxic secondary metabolites and subsequent induction of hypoxia affecting microbial community structure and biogeochemical cycles. Here we combined 16S rRNA gene sequencing and microscopic cell counting to explore the seasonality and co-occurrence patterns of bacteria, algae, and zooplankton following a reservoir cyanobacterial bloom. During the sampling period, 22 distinct cyanobacteria genus were identified, and the dominant ones were Chroococcus, Planktolyngbya, Aphanizomenon, Pseudanabaena, and Cylindrospermopsis. Our results showed that the bloom event significantly altered the bacterial community composition without affecting the alpha diversity. Time-lag analysis found that the similarities of microbial communities significantly declined with the increase in time-lag. Regression modeling showed that environmental variables strongly affect the distribution of functional profiles, but weakly influence taxonomic composition within individual functional groups. Neutral community modeling revealed that stochastic processes also strongly affected bacterial community assembly, and the fit of the model varied over the sampling period and was the lowest during the bloom. Co-occurrence network analysis showed that correlations between bacterial taxa were predominantly positive, suggesting cooperation interactions might contribute to the stability of the microbial community during cyanobacterial succession. Overall, we concluded that changes in the structure of bacterioplankton are associated with the changes in the abundance and composition of freshwater cyanobacteria.