Dataset Information

SNPs in Genes Related to DNA Damage Repair in Mycobacterium Tuberculosis: Their Association with Type 2 Diabetes Mellitus and Drug Resistance.

ABSTRACT: Genes related to DNA damage repair in Mycobacterium tuberculosis are critical for survival and genomic diversification. The aim of this study is to compare the presence of SNPs in genes related to DNA damage repair in sensitive and drug-resistant M. tuberculosis genomes isolated from patients with and without type 2 diabetes mellitus (T2DM). We collected 399 M. tuberculosis L4 genomes from several public repositories; 224 genomes belonging to hosts without T2DM, of which 123 (54.9%) had drug sensitive tuberculosis (TB) and 101 (45.1%) had drug resistance (DR)-TB; and 175 genomes from individuals with T2DM, of which 100 (57.1%) had drug sensitive TB and 75 (42.9%) had DR-TB. The presence of SNPs in the coding regions of 65 genes related to DNA damage repair was analyzed and compared with the resistance profile and the presence/absence of T2DM in the host. The results show the phylogenetic relationships of some SNPS and L4 sub-lineages, as well as differences in the distribution of SNPs present in DNA damage repair-related genes related to the resistance profile of the infecting strain and the presence of T2DM in the host. Given these differences, it was possible to generate two discriminant functions to distinguish between drug sensitive and drug resistant genomes, as well as patients with or without T2DM.

SUBMITTER: Perez-Martinez DE

PROVIDER: S-EPMC9029044 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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SNPs in Genes Related to DNA Damage Repair in Mycobacterium Tuberculosis: Their Association with Type 2 Diabetes Mellitus and Drug Resistance.

Pérez-Martínez Damián E DE Bermúdez-Hernández Gustavo A GA Madrazo-Moya Carlos F CF Cancino-Muñoz Irving I Montero Hilda H Licona-Cassani Cuauhtemoc C Muñiz-Salazar Raquel R Comas Iñaki I Zenteno-Cuevas Roberto R

Genes 20220329 4

Genes related to DNA damage repair in Mycobacterium tuberculosis are critical for survival and genomic diversification. The aim of this study is to compare the presence of SNPs in genes related to DNA damage repair in sensitive and drug-resistant M. tuberculosis genomes isolated from patients with and without type 2 diabetes mellitus (T2DM). We collected 399 M. tuberculosis L4 genomes from several public repositories; 224 genomes belonging to hosts without T2DM, of which 123 (54.9%) had drug sen ...[more]

PMID: 35456415

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Project description:BackgroundA paucity of studies focused on the genetic association that tuberculosis (TB) patients with non-communicable diseases (NCDs) are more likely to be infected with Mycobacterium tuberculosis (MTB) with more potent virulence on anti-TB drug resistance than those without NCDs. The study aimed to document the predominant genotype, determine the association between MTB genotypes and NCD status and drug resistance.MethodsWe conducted a molecular study in 105 TB patients based on a cross-sectional study focused on the comorbid relationship between chronic conditions and TB among 1773 subjects from September 1, 2019 to August 30, 2020 in Guizhou, China. The participants were investigated through face-to-face interviews, followed by NCDs screening. The DNA of MTB isolates was extracted prior to genotyping using 24 loci MIRU-VNTR. The subsequent evaluations were performed by phylogenetic trees, combined with tests of statistical power, Chi-square or Fisher and multivariate logistic regression analysis.ResultsThe Beijing family of Lineage 2 (East Asia) was the predominant genotype accounting for 43.8% (46/105), followed by Lineage 4 (Euro-America) strains, including Uganda I (34.3%, 36/105), and the NEW-1 (9.5%, 10/105). The proportion of Beijing strain in patients with and without NCDS was 28.6% (8/28) and 49.4% (38/77), respectively, with a statistical power test value of 24.3%. No significant association was detected between MTB genotype and NCD status. A low clustering rate (2.9%) was identified, consisting of two clusters. The rates of global, mono-, poly- and multi-drug resistance were 16.2% (17/105), 14.3% (15/105), 1.0% (1/105) and 4.8% (5/105), respectively. The drug-resistant rates of rifampicin, isoniazid, and streptomycin, were 6.7% (7/105), 11.4% (12/105) and 5.7% (6/105), respectively. Isoniazid resistance was significantly associated with the Beijing genotype of Lineage 2 (19.6% versus 5.1%).ConclusionsThe Lineage 2 East Asia/Beijing genotype is the dominant genotype of the local MTB with endogenous infection preponderating. Not enough evidence is detected to support the association between the MTB genotype and diabetes/hypertension. Isoniazid resistance is associated with the Lineage 2 East Asia/Beijing strain.

Project description:Tuberculosis (TB) is the leading cause of death by an infectious disease, and global TB control efforts are increasingly threatened by drug resistance in Mycobacterium tuberculosis. Unlike most bacteria, where lateral gene transfer is an important mechanism of resistance acquisition, resistant M. tuberculosis arises solely by de novo chromosomal mutation. Using whole-genome sequencing data from two natural populations of M. tuberculosis, we characterized the population genetics of known drug resistance loci using measures of diversity, population differentiation, and convergent evolution. We found resistant subpopulations to be less diverse than susceptible subpopulations, consistent with ongoing transmission of resistant M. tuberculosis. A subset of resistance genes ("sloppy targets") were characterized by high diversity and multiple rare variants; we posit that a large genetic target for resistance and relaxation of purifying selection contribute to high diversity at these loci. For "tight targets" of selection, the path to resistance appeared narrower, evidenced by single favored mutations that arose numerous times in the phylogeny and segregated at markedly different frequencies in resistant and susceptible subpopulations. These results suggest that diverse genetic architectures underlie drug resistance in M. tuberculosis and that combined approaches are needed to identify causal mutations. Extrapolating from patterns observed for well-characterized genes, we identified novel candidate variants involved in resistance. The approach outlined here can be extended to identify resistance variants for new drugs, to investigate the genetic architecture of resistance, and when phenotypic data are available, to find candidate genetic loci underlying other positively selected traits in clonal bacteria. IMPORTANCEMycobacterium tuberculosis, the causative agent of tuberculosis (TB), is a significant burden on global health. Antibiotic treatment imposes strong selective pressure on M. tuberculosis populations. Identifying the mutations that cause drug resistance in M. tuberculosis is important for guiding TB treatment and halting the spread of drug resistance. Whole-genome sequencing (WGS) of M. tuberculosis isolates can be used to identify novel mutations mediating drug resistance and to predict resistance patterns faster than traditional methods of drug susceptibility testing. We have used WGS from natural populations of drug-resistant M. tuberculosis to characterize effects of selection for advantageous mutations on patterns of diversity at genes involved in drug resistance. The methods developed here can be used to identify novel advantageous mutations, including new resistance loci, in M. tuberculosis and other clonal pathogens.

Project description:BackgroundEmergence of drug resistant varieties of tuberculosis is posing a major threat to global tuberculosis eradication programmes. Although several approaches have been explored to counter resistance, there has been limited success due to a lack of understanding of how resistance emerges in bacteria upon drug treatment. A systems level analysis of the proteins involved is essential to gain insights into the routes required for emergence of drug resistance.ResultsWe derive a genome-scale protein-protein interaction network for Mycobacterium tuberculosis H37Rv from the STRING database, with proteins as nodes and interactions as edges. A set of proteins involved in both intrinsic and extrinsic drug resistance mechanisms are identified from literature. We then compute shortest paths from different drug targets to the set of resistance proteins in the protein-protein interactome, to derive a sub-network relevant to study emergence of drug resistance. The shortest paths are then scored and ranked based on a new scheme that considers (a) drug-induced gene upregulation data, from microarray experiments reported in literature, for the individual nodes and (b) edge-hubness, a network parameter which signifies centrality of a given edge in the network. High-scoring paths identified from this analysis indicate most plausible pathways for the emergence of drug resistance. Different targets appear to have different propensities for four drug resistance mechanisms. A new concept of 'co-targets' has been proposed to counter drug resistance, co-targets being defined as protein(s) that need to be simultaneously inhibited along with the intended target(s), to check emergence of resistance to a given drug.ConclusionThe study leads to the identification of possible pathways for drug resistance, providing novel insights into the problem of resistance. Knowledge of important proteins in such pathways enables identification of appropriate 'co-targets', best examples being RecA, Rv0823c, Rv0892 and DnaE1, for drugs targeting the mycolic acid pathway. Insights obtained about the propensity of a drug to trigger resistance will be useful both for more careful identification of drug targets as well as to identify target-co-target pairs, both implementable in early stages of drug discovery itself. This approach is also inherently generic, likely to significantly impact drug discovery.

Project description:BackgroundDiabetes mellitus (DM) is a major risk factor for tuberculosis (TB), However, limited research exists on their clinical and strain characteristics. This study aims to investigate the correlation between these factors in TB-DM patients in Changping District. METHODS: Whole genome sequencing (WGS) and drug susceptibility tests (DST) were performed on culture-positive strains. Spearman correlation analysis was used to examine risk factors and the correlation between lineage, cavities, and hemoptysis in the TB-DM population. The specificity, sensitivity, and confidence intervals for predicting phenotypic drug resistance based on genotypic resistance were calculated.ResultsAmong the 3924 TB patients, 292 had DM, showing a doubling in the proportion of TB patients with DM over seven years. Among the 144 etiologically positive TB-DM cases treated at the Changping Institute for Tuberculosis Prevention and Treatment, 75% (108/144) of the patients exhibited tuberculosis lesions that formed cavities and 12.5% (18/144) with hemoptysis. A statistically significant difference in cavity formation across different age groups was observed (r = -0.198, P < 0.05). Out of the 144 etiologically positive patients, WGS successfully revived 73 MTB strains, with Lineage 2 being predominant. No statistical difference was found between lineages and the presence of cavities or hemoptysis. The DST results showed the highest resistance rates to isoniazid and streptomycin, both at 8.2% (6/73), with approximately one-quarter of the strains resistant to at least one anti-TB drug, and about half (47.1%, 8/17) resistant to first-line drugs. The study demonstrated good specificity but suboptimal sensitivity in predicting phenotypic drug resistance based on genotypic resistance.ConclusionsThe rising incidence of diabetes in tuberculosis patients within Changping District has intensified the spread of TB, with these patients demonstrating severe illness and high drug resistance. This study aims to develop targeted prevention and management strategies, offering crucial guidance for treating co-infections of TB and DM and controlling disease spread.

Dataset Information

SNPs in Genes Related to DNA Damage Repair in Mycobacterium Tuberculosis: Their Association with Type 2 Diabetes Mellitus and Drug Resistance.

Publications

SNPs in Genes Related to DNA Damage Repair in Mycobacterium Tuberculosis: Their Association with Type 2 Diabetes Mellitus and Drug Resistance.

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