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Urbanization promotes specific bacteria in freshwater microbiomes including potential pathogens
(2022)
Freshwater ecosystems are characterized by complex and highly dynamic microbial communities that are strongly structured by their local environment and biota. Accelerating urbanization and growing city populations detrimentally alter freshwater environments. To determine differences in freshwater microbial communities associated with urban-ization, full-length 16S rRNA gene PacBio sequencing was performed in a case study from surface waters and sedi-ments from a wastewater treatment plant, urban and rural lakes in the Berlin-Brandenburg region, Northeast Germany. Water samples exhibited highly habitat specific bacterial communities with multiple genera showing clear urban signatures. We identified potentially harmful bacterial groups associated with environmental parameters specific to urban habitats such as Alistipes, Escherichia/Shigella, Rickettsia and Streptococcus. We demonstrate that urban-ization alters natural microbial communities in lakes and, via simultaneous warming and eutrophication and creates favourable conditions that promote specific bacterial genera including potential pathogens. Our findings are evidence to suggest an increased potential for long-term health risk in urbanized waterbodies, at a time of rapidly expanding global urbanization. The results highlight the urgency for undertaking mitigation measures such as targeted lake restoration projects and sustainable water management efforts.
We investigated inflow of a wastewater treatment plant and sediment of an urban lake for the presence of Clostridioides difficile by cultivation and PCR. Among seven colonies we sequenced the complete genomes of three: two non-toxigenic isolates from wastewater and one toxigenic isolate from the urban lake. For all obtained isolates, a close genomic relationship with human-derived isolates was observed. (C) 2019 Elsevier Ltd. All rights reserved.
Wastewater samples from a Swedish chemi-thermo-mechanical pulp (CTMP) mill collected at different purification stages in a wastewater treatment plant (WWTP) were analyzed with an amperometric enzyme-based biosensor array in a flow-injection system. In order to resolve the complex composition of the wastewater, the array consists of several sensing elements which yield a multidimensional response. We used principal component analysis (PCA) to decompose the array's responses, and found that wastewater with different degrees of pollution can be differentiated. With the help of partial least squares regression (PLS-R), we could link the sensor responses to the toxicity parameter, as well as to global organic pollution parameters (COD, BOD, and TOC). From investigating the influences of individual sensors in the array, it was found that the best models were in most cases obtained when all sensors in the array were included in the PLS-R model. We find that fast simultaneous determination of several global environmental parameters characterizing wastewaters is possible with this kind of biosensor array, in particular because of the link between the sensor responses and the biological effect onto the ecosystem into which the wastewater would be released. In conjunction with multivariate data analysis tools, there is strong potential to reduce the total time until a result is yielded from days to a few minutes.