Mycobacterium tuberculosis Type II Toxin-Antitoxin Systems: Genetic Polymorphisms and Functional Properties and the Possibility of Their Use for Genotyping.

Various genetic markers such as IS-elements, DR-elements, variable number tandem repeats (VNTR), single nucleotide polymorphisms (SNPs) in housekeeping genes and other groups of genes are being used for genotyping. We propose a different approach. We suggest the type II toxin-antitoxin (TA) systems, which play a significant role in the formation of pathogenicity, tolerance and persistence phenotypes, and thus in the survival of Mycobacterium tuberculosis in the host organism at various developmental stages (colonization, infection of macrophages, etc.), as the marker genes. Most genes of TA systems function together, forming a single network: an antitoxin from one pair may interact with toxins from other pairs and even from other families. In this work a bioinformatics analysis of genes of the type II TA systems from 173 sequenced genomes of M. tuberculosis was performed. A number of genes of type II TA systems were found to carry SNPs that correlate with specific genotypes. We propose a minimally sufficient set of genes of TA systems for separation of M. tuberculosis strains at nine basic genotype and for further division into subtypes. Using this set of genes, we genotyped a collection consisting of 62 clinical isolates of M. tuberculosis. The possibility of using our set of genes for genotyping using PCR is also demonstrated.

Gene-centric content management system.

The Human Proteome Project (HPP) was started two years ago and the international consortia have elaborated a number of informational resources to harbor the HPP data. Selected informational resources are currently used to elaborate the HPP baseline metrics, which were introduced to estimate future contribution of HPP to the knowledge domain. We developed a Web-based tool Gene-centric Content Management System (GenoCMS) for comparing public resources to proprietary results by using the representation of proteins as color-coded catalog. Within our CMS, the features of protein-coding genes are uploaded from the public domain and then appended by additional features derived from original experimental workflows. We describe the heat-map/traffic light representation of our proteomic experiments as the background of data taken from NeXtProt, MS/MS repositories, the Human Protein Atlas and the RNAseqAtlas. The system presented at www.kb18.ru comprises a collaborative knowledge base for annotating the gene sets and disseminating these annotations through the Web. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Chromosome 18 transcriptoproteome of liver tissue and HepG2 cells and targeted proteome mapping in depleted plasma: update 2013.

We report the results obtained in 2012-2013 by the Russian Consortium for the Chromosome-centric Human Proteome Project (C-HPP). The main scope of this work was the transcriptome profiling of genes on human chromosome 18 (Chr 18), as well as their encoded proteome, from three types of biomaterials: liver tissue, the hepatocellular carcinoma-derived cell line HepG2, and blood plasma. The transcriptome profiling for liver tissue was independently performed using two RNaseq platforms (SOLiD and Illumina) and also by droplet digital PCR (ddPCR) and quantitative RT-PCR. The proteome profiling of Chr 18 was accomplished by quantitatively measuring protein copy numbers in the three types of biomaterial (the lowest protein concentration measured was 10(-13) M) using selected reaction monitoring (SRM). In total, protein copy numbers were estimated for 228 master proteins, including quantitative data on 164 proteins in plasma, 171 in the HepG2 cell line, and 186 in liver tissue. Most proteins were present in plasma at 10(8) copies/µL, while the median abundance was 10(4) and 10(5) protein copies per cell in HepG2 cells and liver tissue, respectively. In summary, for liver tissue and HepG2 cells a "transcriptoproteome" was produced that reflects the relationship between transcript and protein copy numbers of the genes on Chr 18. The quantitative data acquired by RNaseq, PCR, and SRM were uploaded into the "Update_2013" data set of our knowledgebase (www.kb18.ru) and investigated for linear correlations.