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To comprehensively understand the profile of free-living bacteria and potential bacterial pathogens in sewage treatment plants (STPs), this study applied high-throughput sequencing-based metagenomics approaches to investigate the effects of activated sludge (AS) treatment process and ultraviolet (UV) disinfection on the community of bacterial pathogens in two full-scale STPs. A total of 23 bacterial genera were identified as free-living bacteria, and 243 species/OTU97% were identified as potential bacterial pathogens, 6 of which were confidently detected in the STPs (with the total abundances ranging from 0.02 to 14.19%). Both diversity and relative abundance of the detected bacterial pathogens decreased obviously after AS treatment process (p < 0.05), and increased slightly after sedimentation (p < 0.05). UV disinfection shows no obvious effects on the total relative abundance of the free-living pathogenic bacteria in sewage. Although large amounts of the particle-bound pathogens were eliminated through the sewage treatment process, the STPs could not effectively remove the free-living bacterial pathogens, and some pathogenic bacteria (e.g., Pseudomonas aeruginosa) present in the effluent had higher relative abundance after UV disinfection. Overall, the results extend our knowledge regarding the community of potential pathogens (especially free-living pathogens) in STPs. [ABSTRACT FROM AUTHOR]

The ubiquitous occurrence of microorganisms gives rise to continuous public concerns regarding their pathogenicity and threats to human environment, as well as potential engineering benefits in biotechnology. The development and wide application of environmental biotechnology, for example in bioenergy production, wastewater treatment, bioremediation, and drinking water disinfection, have been bringing us with both environmental and economic benefits. Strikingly, extensive applications of microscopic and molecular techniques since 1990s have allowed engineers to peep into the microbiology in 'black box' of engineered microbial communities in biotechnological processes, providing guidelines for process design and optimization. Recently, revolutionary advances in DNA sequencing technologies and rapidly decreasing costs are altering conventional ways of microbiology and ecology research, as it launches an era of next-generation sequencing (NGS). The principal research burdens are now transforming from traditional labor-intensive wet-lab experiments to dealing with analysis of huge and informative NGS data, which is computationally expensive and bioinformatically challenging. This study discusses state-of-the-art bioinformatics and statistical analyses of 16S ribosomal RNA (rRNA) gene high-throughput sequencing (HTS) data from prevalent NGS platforms to promote its applications in exploring microbial diversity of functional and pathogenic microorganisms, as well as their interactions in biotechnological processes. [ABSTRACT FROM AUTHOR]