Prediction of microbial phenotypes based on comparative genomics.

The accessibility of almost complete genome sequences of uncultivable microbial species from metagenomes necessitates computational methods predicting microbial phenotypes solely based on genomic data. Here we investigate how comparative genomics can be utilized for the prediction of microbial phenotypes. The PICA framework facilitates application and comparison of different machine learning techniques for phenotypic trait prediction. We have improved and extended PICA's support vector machine plug-in and suggest its applicability to large-scale genome databases and incomplete genome sequences.
Feldbauer R, Schulz F, Horn M, Rattei T
2015 - BMC Bioinformatics, S1

Effective--a database of predicted secreted bacterial proteins.

Protein secretion is a key virulence mechanism of pathogenic and symbiotic bacteria, which makes the investigation of secreted proteins ('effectors') crucial for understanding the molecular bacterium-host interactions. Effective ( is a database of predicted bacterial secreted proteins, implementing two complementary prediction strategies for protein secretion: the identification of eukaryotic-like protein domains and the recognition of signal peptides in amino acid sequences. The Effective web portal provides user-friendly tools for browsing and retrieving comprehensive precalculated predictions for whole bacterial genomes as well as for the interactive prediction of effectors in user-provided protein sequences.

Jehl MA, Arnold R, Rattei T
2011 - Nucleic Acids Res., D591-5

Targeting effectors: the molecular recognition of Type III secreted proteins.

The Type III secretion system (TTSS) facilitates the export of effector proteins from pathogenic and symbiotic Gram-negative bacteria into the cytosol of eukaryotic host cells. The current functional and evolutionary knowledge on the molecular recognition of TTSS substrates and computational models of the secretion signal are discussed in this review.

Arnold R, Jehl A, Rattei T
2010 - Microbes Infect., 5: 346-58