Project description:Instrument data for publication "Metagenomic and metaproteomic insights into bacterial communities in leaf-cutter ant fungus gardens", ISME J. 2012 Sep; 6(9): 1688-1701. PMID: 22378535. PMCID: PMC3498920
Project description:16S rRNA gene sequencing, comparative analysis of bacterial communities in intestinal tract and respiratory organ of Chinese giant salamander (Andrias davidianus)
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.
Project description:In this study, we analyzed the microbial communities from a methane-based bio-reactor with selenate as an electron accepter. Four biological replicates were analyzed by metagenomics, of which data can be found in the SRA database (Accession number: SRP136677, SRP136696, SRP136790 and SRP136859). Based on the metagenomic data, we detected the expressed proteins using metaproteomics. This data is also included in this submission.
