16S rRNA gene high-throughput sequencing data mining of microbial diversity and interactions

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