Prioritizing targets for structural biology through the lens of proteomics: The archaeal protein TGAM_1934 from Thermococcus gammatolerans

ORFans are hypothetical proteins lacking any significant sequence similarity with other proteins. Here, we highlighted by quantitative proteomics the TGAM_1934 ORFan from the hyperradioresistant Thermococcus gammatolerans archaeon as one of the most abundant hypothetical proteins. This protein has been selected as a priority target for structure determination on the basis of its abundance in three cellular conditions. Its solution structure has been determined using multidimensional heteronuclear NMR spectroscopy. TGAM_1934 displays an original fold, although sharing some similarities with the 3D structure of the bacterial ortholog of frataxin, CyaY, a protein conserved in bacteria and eukaryotes and involved in iron–sulfur cluster biogenesis. These results highlight the potential of structural proteomics in prioritizing ORFan targets for structure determination based on quantitative proteomics data. The proteomic data and structure coordinates have been deposited to the ProteomeXchange with identifier PXD000402 ( http://proteomecentral.proteomexchange.org/dataset/PXD000402 ) and Protein Data Bank under the accession number 2mcf, respectively.     

Proteome analysis of Rickettsia conorii by two-dimensional gel electrophoresis coupled with mass spectrometry

The availability of genome sequence offers the opportunity to further expand our knowledge about proteins expressed by Rickettsia conorii, strictly intracellular bacterium responsible for Mediterranean spotted fever. Using two-dimensional polyacrylamide gel electrophoresis combined with MALDI-TOF mass spectrometry, we established the first reference map of R. conorii proteome. This approach also allowed identification of GroEL as the major antigen recognized by rabbit serum and sera of infected patients. Altogether, this work opens the way to characterize the proteome of R. conorii, to compare protein profiles of different isolates or of bacteria maintained under different experimental conditions and to identify immunogenic proteins as potential vaccine targets.     

Characterization of species-specific genes using a flexible,web-based querying system

We describe a query-based web-accessible system (www.neurogadgets.com/bws.php) for facilitating comparative microbial genomics. A variety of query pages are available, each with numerous options, that allow a biologist to pose relevant questions of genomic data. We illustrate with a characterization of species-specific protein-coding genes (so-called "ORFans"), finding that they are on average smaller, faster evolving, and less G+C-rich, and that they encode proteins more basic in their predicted isoelectric point, compared with non-species-specific genes. Using a dual-threshold approach, we conclude that these are characteristics of true species-specific genes, rather than artifacts of mis-annotation.     

Theoretical model of restriction endonuclease HpaI in complex with DNA, predicted by fold recognition and validated by site-directed mutagenesis

Type II restriction enzymes are commercially important deoxyribonucleases and very attractive targets for protein engineering of new specificities. At the same time they are a very challenging test bed for protein structure prediction methods. Typically, enzymes that recognize different sequences show little or no amino acid sequence similarity to each other and to other proteins. Based on crystallographic analyses that revealed the same PD-(D/E)XK fold for more than a dozen case studies, they were nevertheless considered to be related until the combination of bioinformatics and mutational analyses has demonstrated that some of these proteins belong to other, unrelated folds PLD, HNH, and GIY-YIG. As a part of a large-scale project aiming at identification of a three-dimensional fold for all type II REases with known sequences (currently approximately 1000 proteins), we carried out preliminary structure prediction and selected candidates for experimental validation. Here, we present the analysis of HpaI REase, an ORFan with no detectable homologs, for which we detected a structural template by protein fold recognition, constructed a model using the FRankenstein monster approach and identified a number of residues important for the DNA binding and catalysis. These predictions were confirmed by site-directed mutagenesis and in vitro analysis of the mutant proteins. The experimentally validated model of HpaI will serve as a low-resolution structural platform for evolutionary considerations in the subgroup of blunt-cutting REases with different specificities. The research protocol developed in the course of this work represents a streamlined version of the previously used techniques and can be used in a high-throughput fashion to build and validate models for other enzymes, especially ORFans that exhibit no sequence similarity to any other protein in the database.     

VIROME: a standard operating procedure for analysis of viral metagenome sequences

One consistent finding among studies using shotgun metagenomics to analyze whole viral communities is that most viral sequences show no significant homology to known sequences. Thus, bioinformatic analyses based on sequence collections such as GenBank nr, which are largely comprised of sequences from known organisms, tend to ignore a majority of sequences within most shotgun viral metagenome libraries. Here we describe a bioinformatic pipeline, the Viral Informatics Resource for Metagenome Exploration (VIROME), that emphasizes the classification of viral metagenome sequences (predicted open-reading frames) based on homology search results against both known and environmental sequences. Functional and taxonomic information is derived from five annotated sequence databases which are linked to the UniRef 100 database. Environmental classifications are obtained from hits against a custom database, MetaGenomes On-Line, which contains 49 million predicted environmental peptides. Each predicted viral metagenomic ORF run through the VIROME pipeline is placed into one of seven ORF classes, thus, every sequence receives a meaningful annotation. Additionally, the pipeline includes quality control measures to remove contaminating and poor quality sequence and assesses the potential amount of cellular DNA contamination in a viral metagenome library by screening for rRNA genes. Access to the VIROME pipeline and analysis results are provided through a web-application interface that is dynamically linked to a relational back-end database. The VIROME web-application interface is designed to allow users flexibility in retrieving sequences (reads, ORFs, predicted peptides) and search results for focused secondary analyses.