Marine microbial communities are an untapped reservoir of genetic and metabolic diversity and a valuable source for the discovery of new natural products of biotechnological interest. The conditions in these environments, i.e., high temperatures, low pH values and high concentration of heavy metals, often resemble harsh industrial settings. Thus, these environments may serve as pools of enzymes of enhanced catalytic properties that may provide benefits to biotechnology. Here, we screened 11 metagenomic libraries previously constructed from microbial mat samples covering the seafloor and the polymetallic chimneys of Kolumbo volcano as well as mat samples from Santorini caldera, to mine, in silico, genes associated with bioenergy applications.
PEMA is a containerized assembly of key metabarcoding analysis tools that requires low effort in setting up, running, and customizing to researchers’ needs. Based on third-party tools, PEMA performs read pre-processing, (molecular) operational taxonomic unit clustering, amplicon sequence variant inference, and taxonomy assignment for 16S and 18S ribosomal RNA, as well as ITS and COI marker gene data. Owing to its simplified parameterization and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against both mock communities and previously published datasets and achieved results of comparable quality.
PEMA is a BigDataScript-based workflwow for the analysis of amplicon data.
PEMA supports the metabarcoding analysis of four marker genes, 16S rRNA (Bacteria), ITS (Fungi) as well as COI and 18S rRNA (metazoa). As input, PEMA accepts .fastq.gz files as returned by Illumina sequencing platforms. Since the v.2.1.4 release, PEMA supports also the analysis of the 12S rRNA marker gene!
PEMA always needs your help to keep up-to-date and integrate new features. If you are interested in contributing to the project, feel free to open an Issue, or a PR on GitHub or contact me for more!
