Project description:To characterize the taxonomic and functional diversity of biofilms on plastics in marine environments, plastic pellets (PE and PS, ø 3mm) and wooden pellets (as organic control) were incubated at three stations: at the Baltic Sea coast in Heiligendamm (coast), in a dead branch of the river Warnow in Warnemünde (inlet), and in the Warnow estuary (estuary). After two weeks of incubation, all pellets were frozen for subsequent metagenome sequencing and metaproteomic analysis. Biofilm communities in the samples were compared on multiple levels: a) between the two plastic materials, b) between the individual incubation sites, and c) between the plastic materials and the wooden control. Using a semiquantitative approach, we established metaproteome profiles, which reflect the dominant taxonomic groups as well as abundant metabolic functions in the respective samples.
Project description:More than 99% of identified prokaryotes, including many from the marine environment, cannot be cultured in the laboratory. This lack of capability restricts our knowledge of microbial genetics and community ecology. Metagenomics, the culture-independent cloning of environmental DNAs that are isolated directly from an environmental sample, has already provided a wealth of information about the uncultured microbial world. It has also facilitated the discovery of novel biocatalysts by allowing researchers to probe directly into a huge diversity of enzymes within natural microbial communities. Recent advances in these studies have led to a great interest in recruiting microbial enzymes for the development of environmentally-friendly industry. Although the metagenomics approach has many limitations, it is expected to provide not only scientific insights but also economic benefits, especially in industry. This review highlights the importance of metagenomics in mining microbial lipases, as an example, by using high-throughput techniques. In addition, we discuss challenges in the metagenomics as an important part of bioinformatics analysis in big data.