Software Development for LC-MS/MS Based Metaproteomics
Motivation
Metaproteomics represents the large scale characterization of the entire protein complement expressed by a microbial community at a given time point and under defined environmental conditions. This research area aims at assessing the immediate catalytic potential of microbiota. However, the investigation of complex microbial communities by proteomic methods remains a challenging task as in contrast to pure-culture proteomics, metaproteome samples are heterogeneous and much more complex. Another problem constitutes the fact that only a small proportion of the microbial genome is sequenced which leads to insufficient MS-based protein identification results: a large quantity of fragmentation mass spectra remains unidentified due to the lack of appropriate protein sequence databases. Another important aspect is the functional analysis of complex microbial communities, as it constitutes an essential prerequisite for scientific endeavors such as improving the economic efficiency of biogas or waste water treatment plants, environmental remediation or investigating the complex microbial interactions in the human gut.
Aim of the project
Mainly due to the lack of appropriate software solutions, the analysis and interpretation of data derived from LC-MS/MS experiments present the major bottleneck in metaproteomics. In order to tackle the aforementioned challenges and overcome the limits of existing software solutions an improvement and adaptation of protein identification algorithms and database infrastructure is required, which our software project strives to provide. For that purpose we are developing a client-server application tailored for the in-depth analysis of metaproteomics data that allows for the automated functional and taxonomic characterization of contained proteins in the samples.
