Species Inference and Quantification in Metaproteogenomics

• Applicant: Professor Dr. Bernhard Renard
• Subject Area: Bioinformatics and Theoretical Biology
• Term: from 2013 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 246180157

The main objective of this follow-up project is to extend the previously developed methodology of simultaneous proteogenomic analysis to the challenges arising when analyzing microbial community samples. In contrast to the proteogenomic investigation of genes and proteins from single organisms, the most severe issues of metaproteogenomics with multiple organisms within one sample are low sequence coverage, large yet incomplete reference databases, sequence similarity, and many false positive hits. Overall, these problems lead to an identification and quantification with high error rates at the species and strain level, respectively.To overcome these difficulties, the following specific aims will be pursued within this project by applying innovative bioinformatic methods: first, a tailored, iterative search strategy will be established for accurately identifying species and strains using proteogenomic databases. Second, the previously developed data model which integrates genomic reads and proteomic peptide identifications will be adapted to the multi-species scenario accordingly. A further important goal is to develop statistically robust approaches for quantification and comparison of multi-species samples which are implemented into a complete framework for metaproteogenomic data integration. Finally, based on the experience gained from this and the previous project, recommended guidelines will be proposed for researchers and users to support the application of optimized strategies of data analysis in metaproteogenomics.

• DFG Programme: Research Grants