Fine-scale spatiotemporal variations in bacterial community diversity in agricultural pond water

Microbial communities in surface waters are affected by environmental conditions and can influence changes in water quality. To explore the hypothesis that the microbiome in agricultural waters associates with spatiotemporal variations in overall water quality and, in turn, has implications for resource monitoring and management, we characterized the relationships between the microbiota and physicochemical properties in a model irrigation pond as a factor of sampling time (i.e., 9:00, 12:00, 15:00) and location within the pond (i.e., bank vs. interior sites and cross-sectional depths at 0, 1, and 2 m). The microbial communities, which were defined by 16S rRNA gene sequencing analysis, significantly varied based on all sampling factors (PERMANOVA P < 0.05 for each). While the relative abundances of dominant phyla (e.g., Proteobacteria and Bacteroidetes) were relatively stable throughout the pond, subtle yet significant increases in α-diversity were observed as the day progressed (ANOVA P < 0.001). Key water quality properties that also increased between the morning and afternoon (i.e., pH, dissolved oxygen, and temperature) positively associated with relative abundances of Cyanobacteria, though were inversely proportional to Verrucomicrobia. These properties, among additional parameters such as bioavailable nutrients (e.g., NH3, NO3, PO4), chlorophyll, phycocyanin, conductivity, and colored dissolved organic matter, exhibited significant relationships with relative abundances of various bacterial genera as well. Further investigation of the microbiota in underlying sediments revealed significant differences between the bank and interior sites of the pond (P < 0.05 for α- and β-diversity). Overall, our findings emphasize the importance of accounting for time of day and water sampling location and depth when surveying the microbiomes of irrigation ponds and other small freshwater sources.

Characterizing a riverine microbiome impacted by extreme disturbance caused by a mining sludge tsunami

Studies on disturbance events in riverine systems caused by environmental disasters and their effects on microbial diversity are scarce. Here, we evaluated the impact of the collapse of an iron ore dam holding approximately 50 million cubic meters of waste on both water and sediment microbiomes by deeply sequencing the 16S rRNA gene. Samples were taken from two impacted rivers and one reference river 7, 30 and 150 days postdisturbance. The impacted community structure changed greatly over spatiotemporal scales, being less diverse and more uneven, particularly on day 7 for the do Carmo River (the closest to the dam). However, the reference community structure remained similar between sampling events. Moreover, the impacted sediments were positively correlated with metals. The taxa abundance varied greatly over spatiotemporal scales, allowing for the identification of several potential bioindicators, e.g., Comamonadaceae, Novosphingobium, Sediminibacterium and Bacteriovorax. Our results showed that the impacted communities consisted mostly of Fe(II) oxidizers and Fe(III) reducers, aromatic compound degraders and predator bacteria. Network analysis showed a highly interconnected microbiome whose interactions switched from positive to negative or vice versa between the impacted and reference communities. This work revealed potential molecular signatures associated with the rivers heavily impacted by metals that might be useful sentinels for predicting riverine health.

Quenching by sodium thiosulfate does not influence 16S rRNA gene sequencing profiles of reclaimed water from three sites in the Mid-Atlantic, United States

A quenching agent is commonly added to chlorinated, reclaimed water during sample collection to prevent chlorine-mediated die-off of viable microbiota. However, the effect of quenching on downstream 16S rRNA-based bacterial community analyses is unclear. We conducted a side-by-side comparison of 16S rRNA sequencing data from reclaimed water samples quenched with sodium thiosulfate and non-quenched samples. Our data showed that 16 S rRNA processing and sequencing methods, and resulting bacterial profiles, were not negatively impacted by quenching.