Understanding the interactions between fish gut microbiota and the aquatic environment is a key issue for understanding aquatic microorganisms. Environmental microorganisms enter fish intestines through feeding, and the amount of invasion varies due to different feeding habits. Traditional fish feeding habitat preferences are determined by fish morphology or behavior. However, little is known about how the feeding behavior of fish relative to the vertical structure in a shallow lake influences gut microbiota. In our study, we used nitrogen isotopes to measure the trophic levels of fish. Then high-throughput sequencing was used to describe the composition of environmental microbiota and fish gut microbiota, and FEAST (fast expectation-maximization for microbial source tracking) method was used to trace the source of fish gut microbiota. We investigated the microbial diversity of fish guts and their habitats in Lake Sanjiao and verified that the sediments indeed played an important role in the assembly of fish gut microbiota. Then, the FEAST analysis indicated that microbiota in water and sediments acted as the primary sources in half of the fish gut microbiota respectively. Furthermore, we classified the vertical habitat preferences using microbial data and significant differences in both composition and function of fish gut microbiota were observed between groups with distinct habitat preferences. The performance of supervised and unsupervised machine learning in classifying fish gut microbiota by habitat preferences actually exceeded classification by fish species taxonomy and fish trophic level. Finally, we described the stability of fish co-occurrence networks with different habitat preferences. Interestingly, the co-occurrence network seemed more stable in pelagic fish than in benthic fish. Our results show that the preferences of fish in the vertical structure of habitat was the main factor affecting their gut microbiota. We advocated the use of microbial interactions between fish gut and their surrounding environment to reflect fish preferences in vertical habitat structure. This approach not only offers a novel perspective for understanding the interactions between fish gut microbiota and environmental factors, but also provides new methods and ideas for studying fish habitat selection in aquatic ecosystems.

The mechanism of bacterial community assembly has been the hot spot in the field of microbial ecology and it is difficult to quantitatively estimate the influences of different ecological processes. Here, a total of 23 pairs of planktonic and sedimentary samples were collected from five lakes in Wuhan, China. significant higher α-diversity (p < 0.001) and β-diversity (p < 0.001) of bacterial communities were observed in sediment than those in water. Some phylum had linear relationships with the comprehensive TSI (TSIc) by regression analysis. Non-metric multidimensional scaling (NMDS) and redundancy analysis (RDA) revealed that the depth of water, NO₃⁻-N, NH₄⁺-N, PO4³⁻, and COD_cr were the key environmental variables in planktonic bacterial communities, whereas in sediment they were the depth, NO₃⁻-N, and NH₄⁺-N. Furthermore, variation partitioning analysis (VPA) showed that spatial and environmental factors could only explain 40.2% and 27.9% of the variation in planktonic and sedimentary bacterial communities, respectively. More importantly, null model analysis suggested that different assembly mechanisms were found between in water and in sediment with the fact that planktonic bacterial community assembly was mainly driven by dispersal limitation process whereas variable selection process played a vital role in that of sediment.

The Yangtze River Basin, one of China’s five major watersheds and a primary source of drinking water for the country, is experiencing serious environmental pollution as heavy metals are discharged into its rivers. To evaluate the water quality of the river, determined water quality parameters were compared with the maximum permissible limit values recommended by the World Health Organization and Chinese drinking water standards. Physical and chemical analyses were conducted on water samples taken from 19 locations along the river’s path. The study quantified the contents of sodium (Na), magnesium (Mg), calcium (Ca), strontium (Sr), barium (Ba), lithium (Li), cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), scandium (Sc) and mercury (Hg). The results show that the average values of Mg, Sr, Co, Cu, Fe, Mn and Sc are higher than the historical background values. Moreover, through a correlation analysis it was concluded that these nutrients and trace metals have high values due to anthropogenic pollution in the study area. The computed WQI values range between 9.59 and 20.26, indicating excellent water quality in the river basin. Finally, hazard quotient (HQ) values show that exposure to the detected pollutants will have no adverse effects on human health and does not pose a potential non-carcinogenic risk.

Global concerns over harmful cyanobacterial blooms brought on by eutrophication are now widespread. Aquatic ecological restoration techniques that use algicidal bacteria to control toxic algae show promise. A Bacillus subtilis S4 (S4) strain with strong Microcystis aeruginosa algicidal activity and the capacity to degrade microcystins (MCs) were successfully isolated and evaluated in this study. The dynamics of internal and extracellular MC concentration as well as the physiological response and morphological properties of M. aeruginosa were investigated in the M. aeruginosa/bacteria co-culture system. The findings demonstrated that when S4 density grew from 1 × 10⁶ cells/ml to 1 × 10⁸ cells/ml, the release of M. aeruginosa lysis and MCs was boosted; however, MCs dropped by approximately 90% within 18 h, regardless of bacterial density. Comparing the bacterial cell incubation system to the control and bacterial cell-free filtrate systems, the assessment of extracellular and intracellular MCs revealed a 95% reduction in MCs. The findings showed that 89% of MCs were decreased by bacterial cells, while 98% of M. aeruginosa cells were algaecided by bacterial metabolites. Sustainable eradication of M. aeruginosa and MCs has been accomplished by the combined efforts of the S4 strain and its metabolites. By secreting algicidal chemicals that are resistant to proteases, acid, base, and heat, the S4 strain indirectly acts as an algaecide. The S4 strain possesses a strong ability to break down MCs and a very effective and stable algaecide function, indicating that it can potentially treat eutrophic water with hazardous algae.