Project description:16S rRNA gene amplicon sequencing and metagenome-assembled genomes (MAGs) sequencing and assembly from the Eastern Lau Spreading Center
Project description:<p>A variety of anthropogenic organohalide contaminants generated from industry are released into the environment, and thus cause serious pollution that endangers human health. In the present study, we investigated the microbial community composition of industrial saponification wastewater using 16S rRNA sequencing, providing genomic insights of potential organohalide dehalogenation bacteria (OHDBs) by whole-metagenome sequencing. We also explored yet-to-culture OHDBs involved in the microbial community. Microbial diversity analysis reveals that Proteobacteria and Patescibacteria phyla dominate microbiome abundance of the wastewater. In addition, a total of six bacterial groups (Rhizobiales, Rhodobacteraceae, Rhodospirillales, Flavobạcteriales, Micrococcales, and Saccharimonadales) were found as biomarkers in the key organohalide removal module. Ninety-four metagenome-assembled genomes (MAGs) were reconstructed from the microbial community, and 105 hydrolytic dehalogenase genes within 42 MAGs were identified, suggesting that the potential for hydrolytic organohalide dehalogenation is present in the microbial community. Subsequently, we characterized the organohalide dehalogenation of an isolated OHDB, Microbacterium sp. J1-1, which shows the dehalogenation activities of chloropropanol, dichloropropanol, and epichlorohydrin. This study provides a community-integrated multi-omics approach to gain functional OHDBs for industrial organohalide dehalogenation.</p>
Project description:Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of microbial populations (metaproteomics), yet not their genomic abundance (16S rRNA gene amplicon sequencing), supporting the hypothesis that metabolic activity may be more closely linked to climate than community composition.
Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.