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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]

In this study, we successfully demonstrated that 454 pyrosequencing was a powerful approach for investigating the bacterial communities in the activated sludge, digestion sludge, influent, and effluent samples of a full scale wastewater treatment plant treating saline sewage. For each sample, 18,808 effective sequences were selected and utilized to do the bacterial diversity and abundance analysis. In total, 2,455, 794, 1,667, and 1,932 operational taxonomic units were obtained at 3 % distance cutoff in the activated sludge, digestion sludge, influent, and effluent samples, respectively. The corresponding most dominant classes in the four samples are Alphaproteobacteria, Thermotogae, Deltaproteobacteria, and Gammaproteobacteria. About 67 % sequences in the digestion sludge sample were found to be affiliated with the Thermotogales order. Also, these sequences were assigned into a recently proposed genus Kosmotoga by the Ribosomal Database Project classifier . In the effluent sample, we found high abundance of Mycobacterium and Vibrio, which are genera containing pathogenic bacteria. Moreover, in this study, we proposed a method to differentiate the 'gene percentage' and 'cell percentage' by using Ribosomal RNA Operon Copy Number Database. [ABSTRACT FROM AUTHOR]