CoMet—a web server for comparative functional profiling of metagenomes

Analyzing the functional potential of newly sequenced genomes and metagenomes has become a common task in biomedical and biological research. With the advent of high-throughput sequencing technologies comparative metagenomics opens the way to elucidate the genetically determined similarities and differences of complex microbial communities. We developed the web server ‘CoMet’ (http://comet.gobics.de), which provides an easy-to-use comparative metagenomics platform that is well-suitable for the analysis of large collections of metagenomic short read data. CoMet combines the ORF finding and subsequent assignment of protein sequences to Pfam domain families with a comparative statistical analysis. Besides comprehensive tabular data files, the CoMet server also provides visually interpretable output in terms of hierarchical clustering and multi-dimensional scaling plots and thus allows a quick overview of a given set of metagenomic samples

Microbial Consortium Associated with the Antarctic Marine Ciliate Euplotes focardii: An Investigation from Genomic Sequences

We report the characterization of the bacterial consortium associated to Euplotes focardii, a strictly psychrophilic marine ciliate that was maintained in laboratory cultures at 4 °C after its first isolation from Terra Nova Bay, in Antarctica. By Illumina genome analyser, we obtained 11,179 contigs of potential prokaryotic origin and classified them according to the NCBI’s prokaryotic attributes table. The majority of these sequences correspond to either Bacteroidetes (16 %) or Proteobacteria (78 %). The latter were dominated by gamma- (39 %, including sequences related to the pathogenic genus Francisella), and alpha-proteobacterial (30 %) sequences. Analysis of the Pfam domain family and Gene Ontology term variation revealed that the most frequent terms that appear unique to this consortium correspond to proteins involved in “transmembrane transporter activity” and “oxidoreductase activity”. Furthermore, we identified genes that encode for enzymes involved in the catabolism of complex substance for energy reserves. We also characterized members of the transposase and integrase superfamilies, whose role in bacterial evolution is well documented, as well as putative antifreeze proteins. Antibiotic treatments of E. focardii cultures delayed the cell division of the ciliate. To conclude, our results indicate that this consortium is largely represented by bacteria derived from the original Antarctic sample and may contribute to the survival of E. focardii in laboratory condition. Furthermore, our results suggest that these bacteria may have a more general role in E. focardii survival in its natural cold and oxidative environment

Bioinformatic and Experimental Approaches for Deeper Metaproteomic Characterization of Complex Environmental Samples

The coupling of high performance multi-dimensional liquid chromatography and tandem mass spectrometry for characterization of microbial proteins from complex environmental samples has paved the way for a new era in scientific discovery. The field of metaproteomics, which is the study of protein suite of all the organisms in a biological system, has taken a tremendous leap with the introduction of high-throughput proteomics. However, with corresponding increase in sample complexity, novel challenges have been raised with respect to efficient peptide separation via chromatography and bioinformatic analysis of the resulting high throughput data. In this dissertation, various aspects of metaproteomic characterization, including experimental and computational approaches have been systematically evaluated. In this study, robust separation protocols employing strong cation exchange and reverse phase have been designed for efficient peptide separation thus offering excellent orthogonality and ease of automation. These findings will be useful to the proteomics community for obtaining deeper non-redundant peptide identifications which in turn will improve the overall depth of semi-quantitative proteomics. Secondly, computational bottlenecks associated with screening the vast amount of raw mass spectra generated in these proteomic measurements have been addressed. Computational matching of tandem mass spectra via conventional database search strategies lead to modest peptide/protein identifications. This seriously restricts the amount of information retrieved from these complex samples which is mainly due to high complexity and heterogeneity of the sample containing hundreds of proteins shared between different microbial species often having high level of homology. Hence, the challenges associated with metaproteomic data analysis has been addressed by utilizing multiple iterative search engines coupled with de novo sequencing algorithms for a comprehensive and in-depth characterization of complex environmental samples. The work presented here will utilize various sample types ranging from isolates and mock microbial mixtures prepared in the laboratory to complex community samples extracted from industrial waste water, acid-mine drainage and methane seep sediments. In a broad perspective, this dissertation aims to provide tools for gaining deeper insights to proteome characterization in complex environmental ecosystems