Unravelling the population structure and transmission patterns of Mycobacterium tuberculosis in Mozambique, a high TB/HIV burden country

Genomic studies of Mycobacterium tuberculosis complex (MTBC) might shed light on the dynamics of its transmission, especially in high-burden settings, where recent outbreaks are embedded in the complex natural history of the disease. We applied Whole-genome sequencing (WGS) to characterize the local population of MTBC, unravel potential transmission links and evaluate associations with host and pathogen factors. Methods A one-year prospective study was conducted in Mozambique, a high HIV/TB burden country. WGS was applied to 295 positive cultures. We combined phylogenetic, geographical and clustering analysis, and investigated associations between risk factors of transmission. Findings A significant high proportion of strains were in recent transmission (45.5%). We fully characterized MTBC isolates by using phylogenetic approaches and dating evaluation. We found two likely endemic clades, comprised of 67 strains, belonging to L1.2, dating from the late XIX century and associated with recent spread among PLHIV. Interpretation Our results unveil the population structure of MTBC in our setting. The clustering analysis revealed an unexpected pattern of spread and high rates of progression, suggesting the failure of control measures. The long-term presence of local strains in Mozambique, which were responsible for large transmission among HIV/TB coinfected patients, hint at possible coevolution with sympatric host populations and challenge the role of HIV in TB transmission.Ministry of Enterprise and Knowledge (Government of Catalonia & European Social Fund, AGAUR fellowship); European Research Council (ERC) European Union’s Horizon 2020.N

Whole genome sequencing analysis to evaluate the influence of T2DM on polymorphisms associated with drug resistance in M. tuberculosis

9 páginas, 1 figura, 3 tablas. The datasets supporting the conclusions of this article are available in the BioSample (https://www.ncbi.nlm.nih.gov/biosample/), ENA (https://www. ebi.ac.uk/ena/browser/home) and Tb portals (https://tbportals.niaid.nih.gov/) repositories. The accession numbers of the genomes selected for this study can be found in the Additional fle 1.Background: Type 2 diabetes mellitus (T2DM) has been associated with treatment failure, and the development of drug resistance in tuberculosis (TB). Also, whole-genome sequencing has provided a better understanding and allowed the growth of knowledge about polymorphisms in genes associated with drug resistance. Considering the above, this study analyzes genome sequences to evaluate the influence of type 2 diabetes mellitus in the development of mutations related to tuberculosis drug resistance. M. tuberculosis isolates from individuals with (n = 74), and without (n = 74) type 2 diabetes mellitus was recovered from online repositories, and further analyzed. Results: The results showed the presence of 431 SNPs with similar proportions between diabetics, and non-diabetics individuals (48% vs. 52%), but with no significant relationship. A greater number of mutations associated with rifampicin resistance was observed in the T2DM-TB individuals (23.2% vs. 16%), and the exclusive presence of rpoBQ432L, rpoBQ432P, rpoBS441L, and rpoBH445L variants. While these variants are not private to T2DM-TB cases they are globally rare highlighting a potential role of T2DM. The phylogenetic analysis showed 12 sublineages, being 4.1.1.3, and 4.1.2.1 the most prevalent in T2DM-TB individuals but not differing from those most prevalent in their geographic location. Four clonal complexes were found, however, no significant relationship with T2DM was observed. Samples size and potential sampling biases prevented us to look for significant associations. Conclusions: The occurrence of globally rare rifampicin variants identified only in isolates from individuals with T2DM could be due to the hyperglycemic environment within the host. Therefore, further studies about the dynamics of SNPs' generation associated with antibiotic resistance in patients with diabetes mellitus are necessary.Gustavo Bermúdez was funded by CONACyT, fellow number 710466. Roberto Zenteno was funded by CONACYT: "Fondo sectorial de investigación para la educación” A1-S-22956.Peer reviewe

Whole genomic sequencing based genotyping reveals a specific X3 sublineage restricted to Mexico and related with multidrug resistance

9 páginas, 1 figurra, 3 tablas. Te online version contains supplementary material available at https://doi.org/10.1038/s41598-020-80919-5.Whole genome sequencing (WGS) has been shown to be superior to traditional procedures of genotyping in tuberculosis (TB), nevertheless, reports of its use in drug resistant TB (DR-TB) isolates circulating in Mexico, are practically unknown. Considering the above the main of this work was to identify and characterize the lineages and genomic transmission clusters present in 67 DR-TB isolates circulating in southeastern Mexico. The results show the presence of three major lineages: L1 (3%), L2 (3%) and L4 (94%), the last one included 16 sublineages. Sublineage 4.1.1.3 (X3) was predominant in 18 (27%) of the isolates, including one genomic cluster, formed by eleven multidrug resistant isolates and sharing the SIT 3278, which seems to be restricted to Mexico. By the use of WGS, it was possible to identify the high prevalence of L4 and a high number of sublineages circulating in the region, also was recognized the presence of a novel X3 sublineage, formed exclusively by multidrug resistant isolates and with restrictive circulation in Mexico for at least the past 17 years.AC-JR and CFM-M were CONACYT fellows of the Health Sciences Master of the Health Sciences Institute of Universidad Veracruzana. RZ-C and IC were funded by i-COOP-20017-COOPB2032.Peer reviewe

Whole genomic sequencing as a tool for diagnosis of drug and multidrug-resistance tuberculosis in an endemic region in Mexico.

BackgroundWhole genome sequencing (WGS) has been proposed as a tool for diagnosing drug resistance in tuberculosis. However, reports of its effectiveness in endemic countries with important numbers of drug resistance are scarce. The goal of this study was to evaluate the effectiveness of this procedure in isolates from a tuberculosis endemic region in Mexico.MethodsWGS analysis was performed in 81 tuberculosis positive clinical isolates with a known phenotypic profile of resistance against first-line drugs (isoniazid, rifampin, ethambutol, pyrazinamide and streptomycin). Mutations related to drug resistance were identified for each isolate; drug resistant genotypes were predicted and compared with the phenotypic profile. Genotypes and transmission clusters based on genetic distances were also characterized.FindingsPrediction by WGS analysis of resistance against isoniazid, rifampicin, ethambutol, pyrazinamide and streptomycin showed sensitivity values of 84%, 96%, 71%, 75% and 29%, while specificity values were 100%, 94%, 90%, 90% and 98%, respectively. Prediction of multidrug resistance showed a sensitivity of 89% and specificity of 97%. Moreover, WGS analysis revealed polymorphisms related to second-line drug resistance, enabling classification of eight and two clinical isolates as pre- and extreme drug-resistant cases, respectively. Lastly, four lineages were identified in the population (L1, L2, L3 and L4). The most frequent of these was L4, which included 90% (77) of the isolates. Six transmission clusters were identified; the most frequent was TC6, which included 13 isolates with a L4.1.1 and a predominantly multidrug-resistant condition.ConclusionsThe results illustrate the utility of WGS for establishing the potential for prediction of resistance against first and second line drugs in isolates of tuberculosis from the region. They also demonstrate the feasibility of this procedure for use as a tool to support the epidemiological surveillance of drug- and multidrug-resistant tuberculosis

Strategies and performance of the CMS silicon tracker alignment during LHC Run 2

The strategies for and the performance of the CMS silicon tracking system alignment during the 2015–2018 data-taking period of the LHC are described. The alignment procedures during and after data taking are explained. Alignment scenarios are also derived for use in the simulation of the detector response. Systematic effects, related to intrinsic symmetries of the alignment task or to external constraints, are discussed and illustrated for different scenarios