The type II TA systems of mycobacteria were investigated. Schematic diagram of the toxin-antitoxin system.

<p>(A) TA systems are annotated according to the GenBank database, excluding VapBC50 (rv3750c-rv3749c), VapBC49 (rv3180c-rv3181c), HigBA3 (rv3182-rv3183), HigBA2 (rv2022c-rv2021c), MazEF10 (rv0298-rv0299) and VapBC45 (rv2018-rv2019) systems; these systems are annotated according to Sala et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.ref032" target="_blank">32</a>]. The system RelBE3 (rv3358-rv3357, GenBank database, NCBI) is called the YefM/YoeB system by Sala. All of the TA systems depicted here are type II (systems marked with an asterisk are novel TA systems that are not classified to any family, but for which functional activity has been shown [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.ref032" target="_blank">32</a>]). The 13 genes, our proposed set for genotyping, are highlighted in bold. (B) Type II TA systems are encoded by two genes, a toxin and an antitoxin, that form one operon with a promoter located upstream of the first antitoxin gene. PIN domain is the functional part of the toxin gene, the four conserved acidic residues marked at the picture: the three well-conserved acidic residues, at positions 4[D], 40[E] and 93[D], and with fourth acidic residue is less well conserved at position 112[D].</p

Phylogenetic relationship between different genotypes of the <i>M</i>. <i>tuberculosis</i>.

<p>(A) Phylogenetic tree constructed on the basis of polymorphisms (SNP) in all of the considered genes of type II TA systems. An unrooted phylogenetic tree for the 173 strains from this study was constructed based on the presence/absence of SNPs in the nucleotide sequences of 71 TA systems (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.s003" target="_blank">S3 Table</a>); (B) Phylogenetic tree constructed on the basis of SNP in a minimum set of genes of type II TA systems. An unrooted phylogenetic tree for 173 strains constructed based on SNPs in the nucleotide sequences of 13 genes (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#pone.0143682.t002" target="_blank">Table 2</a>). In both of cases strains included in the one cluster belong to the same genotype (various genotypes highlighted by color). The trees was constructed by the neighbor-joining approach. The TA systems sequences were retrieved from different databases (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143682#sec002" target="_blank">Materials and Methods</a>). Sequences were multiply aligned by using ClustalW ver. 2.1 software. The trees was calculated using MEGA ver. 6. Bootstrap support > 60% is indicated for the trees.</p

Scheme of typing of <i>M</i>. <i>tuberculosis</i> strains using 13 genes of type II TA systems.

<p>The algorithm for determining the genotype is presented. The scheme shows that, after the first iteration to determine the genotype, the number of genes for the analysis is decreased twofold. Each gene in the brackets is given its position that is replaced, and the appropriate nucleotide is indicated. All replacements are calculated relative to the reference strain H37Rv.</p

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

<div><p>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 <i>Mycobacterium tuberculosis</i> 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 <i>M</i>. <i>tuberculosis</i> 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 <i>M</i>. <i>tuberculosis</i> 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 <i>M</i>. <i>tuberculosis</i>. The possibility of using our set of genes for genotyping using PCR is also demonstrated.</p></div

Detection of the Ural genotype by qPCR.

<p>Fluorescence in the FAM channel (blue): (1)13_2978, (2) 13–3114, (3) 13–3086, (4) 13_3158, (5) 13_4178, (6) 13_3539, (7) 13_2566, (8) 13_3632, (9) 13_3599, (10) 13_3896, (11) 13_3582, (12) 13_4189, (13) 13_3535, (15) 13_3147; Fluorescence in the HEX channel (green): (14) 13_3147, (16) 13_2978. Fluorescence of the channel FAM (blue) indicates the accumulation of the PCR product containing cytosine (C); the fluorescence of the channel HEX (green) indicates the accumulation of the PCR product containing thymine (T, the variable nucleotide) and indicates the SNP in the <i>vapC10</i> gene (C394→T394) characteristic of the Ural genotype. Line 14 (13_3147) and 16 (13_2978) belong to the Ural genotype. For isolate 13_2978 fluorescence is detected on the two channels (FAM and HEX), this can indicate the presence of impurities (coinfection). qPCR fluorescence in RFU (relative fluorescence units) vs. PCR cycles. Intensity of fluorescence depending on the number of qPCR cycles for strains belonging to the Euro-American lineage.</p

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 10⁸ copies/μL, while the median abundance was 10⁴ and 10⁵ 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

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 10⁸ copies/μL, while the median abundance was 10⁴ and 10⁵ 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

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 10⁸ copies/μL, while the median abundance was 10⁴ and 10⁵ 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