How did the bacterial community respond to the level of urbanization along the Yangtze River?

Bacterial Diversity and Vertical Distribution Patterns in Sandy Sediments: A Study on the Bacterial Community Structure Based on Environmental Factors in Tributaries of the Yangtze River

Bacterial diversity and its distribution characteristics in sediments are critical to understanding and revealing biogeochemical cycles in sediments. However, little is known about the relationship between biogeochemistry processes and vertical spatial distribution of bacterial communities in sandy sediments. In this study, we used fluorescence quantitative PCR, high-throughput sequencing technology and statistical analysis to explore the vertical distribution pattern of bacterial community diversity and its influencing factors in sandy sediments of the Yangtze River Basin. The aim is to enrich the understanding of the ecological characteristics and functions of bacteria in river ecosystems. The results showed that both sediment bacterial abundance and diversity showed a gradual decrease from surface to bottom in the vertical distribution. The main environmental factors that influenced the bacterial distribution pattern were pore water dissolved oxygen (DO), total nitrogen (TN) concentration and sediment nitrogen (N) content. The dominant bacterial species, Massilia and Flavobacterium, are suitable for growth and reproduction in high oxygen and nutrient-richer environments, while Limnobacter prefers low oxygen or anaerobic conditions. The vertical distribution pattern of bacteria and its influencing factors in river sandy sediment found in this study differ from the results in mud sediment, which may be related to the larger granular gap between sandy sediment and the lower content of organic matter. The findings of this study further our understanding of the distribution patterns and ecological preferences of microbial communities in river sediments, providing insights into how these communities may adapt to varying environmental conditions.

The investigation of the physiochemical factors and bacterial communities indicates a low-toxic infectious risk of the Qiujiang River in Shanghai, China

The overall water quality of urban rivers is closely related to the community structure and the physiochemical factors in them. In this study, the bacterial communities and physiochemical factors of the Qiujiang River, an important urban river in Shanghai, were explored. Water samples were collected from nine sites of the Qiujiang River on November 16, 2020. The water quality and bacterial diversity were studied through physicochemical detection, microbial culture and identification, luminescence bacteria method, and 16S rRNA Illumina MiSeq high-throughput sequencing technology. The water pollution of the Qiujiang River was quite serious with three water quality evaluation indexes, including Cd²⁺, Pb²⁺, and NH₄⁺-N, exceeding the Class V standard set by the Environmental Quality Standards for Surface Water (China, GB3838-2002), while the luminescent bacteria test indicated low toxicity of nine sampling sites. Through 16S rRNA sequencing, a total of 45 phyla, 124 classes, and 963 genera were identified, in which Proteobacteria, Gammaproteobacteria, and Limnohabitans were the most abundant phylum, class, and genus, respectively. The Spearman correlation heatmap and redundancy analysis showed that the bacterial communities in the Qiujiang River were correlated with pH; the concentrations of K⁺, and NH₄⁺-N, and the Limnohabitans were significantly correlated with the concentrations of K⁺, and NH₄⁺-N in the Zhongyuan Road bridge segment. In addition, opportunistic pathogens Enterobacter cloacae complex and Klebsiella pneumoniae in the samples collected in the Zhongyuan Road bridge segment and Huangpu River segment, respectively, were successfully cultured. The Qiujiang River was a heavily polluted urban river. The bacterial community structure and diversity were greatly affected by the physiochemical factors of the Qiujiang River, and it displayed low toxicity while a relatively high infectious risk of intestinal and lung infectious diseases.

Effects of lead pollution on bacterial communities in biofilm attached to submerged plants

Submerged plants and biofilms have significant advantages in hydro-ecology rehabilitation, but their tolerance and physiological responses to heavy metal stress have thus far been under-investigated. This study investigated the influence of lead on physiological and biochemical responses, as well as variation in bacterial communities and functional characteristics of submerged plant biofilms. The results showed that chlorophyll a content of two submerged plants decreased with increased lead concentration. The concentration of malondialdehyde of both submerged plants was higher under high lead concentrations than under low lead concentrations, and the concentrations of malondialdehyde and hydrogen peroxide in Vallisneria natans were more stable. The antioxidant enzyme systems of the two plants played protective roles against lead stress. High lead concentration can inhibit the bacterial community and lead to decreased diversity. The most abundant bacterial phyla were Proteobacteria (40.9%), Cyanobacteria (21.5%), and Bacteroidetes (14.3%). Proteobacteria abundance decreased with increased lead concentration, while Cyanobacteria abundance increased. The lead concentration in plants (19.7%, P < 0.01) and the lead concentration in aquatic environment (17.7%, P < 0.01) were significantly correlated with variation in bacterial communities. High lead concentration inhibits the activity of these bacteria related to the conversion of nitrogen and sulfur.

Improved quantitative microbiome profiling for environmental antibiotic resistance surveillance

BACKGROUND

Understanding environmental microbiomes and antibiotic resistance (AR) is hindered by over reliance on relative abundance data from next-generation sequencing. Relative data limits our ability to quantify changes in microbiomes and resistomes over space and time because sequencing depth is not considered and makes data less suitable for Quantitative Microbial Risk Assessments (QMRA), critical in quantifying environmental AR exposure and transmission risks.

RESULTS

Here we combine quantitative microbiome profiling (QMP; parallelization of amplicon sequencing and 16S rRNA qPCR to estimate cell counts) and absolute resistome profiling (based on high-throughput qPCR) to quantify AR along an anthropogenically impacted river. We show QMP overcomes biases caused by relative taxa abundance data and show the benefits of using unified Hill number diversities to describe environmental microbial communities. Our approach overcomes weaknesses in previous methods and shows Hill numbers are better for QMP in diversity characterisation.

CONCLUSIONS

Methods here can be adapted for any microbiome and resistome research question, but especially providing more quantitative data for QMRA and other environmental applications.