Infection with Mycobacterium tuberculosis is a major cause of human morbidity and mortality, and has wide-ranging clinical manifestations. While host factors, particularly T-cell-mediated immunity, are well known to influence disease presentation and outcome, bacterial factors are also important, but elusive to pinpoint. The majority of studies assessing strain-specific factors have looked at associations between lineage and disease manifestation; at present there is little known about the role of specific genes in determining disease phenotype (Coscolla & Gagneux, 2010). In recent years, technology allowing large-scale whole genome sequencing (WGS) has become increasingly available, which is facilitating a rapid increase in our understanding of the evolution of bacterial populations and in particular molecular mechanisms of drug resistance. Here we have used genomics to investigate the evolution of M. tuberculosis during human pulmonary infection. Researchers described a case of chronic pulmonary multidrug-resistant tuberculosis (TB), and reported the results of WGS analysis of eight serial M. tuberculosis isolates collected from the same patient over a 21-year period. They described the heterogeneity in sequencing results suggestive of dynamic bacterial subpopulations, and provided an estimate of the mutation rate of M. tuberculosis during active infection. They also described the baseline resistance-associated mutations and subsequent mutations that explain the changing pattern of drug resistance, and the potential influence of emergent mutations in the genes encoding putative exporter proteins, bacA, Rv1819c, Rv2326c and mshA, on the disease course.
Unlike many bacilli that obtain antibiotic resistance through horizontal gene transfer, Mtb obtains its resistance via mutations in chromosomal genes. Genotypic resistance mostly results from single nucleotide polymorphisms (SNPs), insertions or deletions (indels) and to a certain extent, deletions in genes that encode drug targets - or drug metabolizing enzymes within the bacilli. Resistance can result in failure to metabolize prodrugs to their active forms, as well as poor drug permeability, increased efflux or modifications in the drug-target structure that result in the inhibition of effective drug binding. Regarding drug resistance, there are three groups of Mtbs: those susceptible to the drug, resistant to a single drug, multi drug-resistant (MDR) and extensively drug-resistant (XDR) [Mabhula et al, 2019].
Link to the Data Source
https://www.ebi.ac.uk/ena/browser/view/PRJEB10002?show=reads
We will run three different pipelines for MTB_1087, MTB_4891, MTB_5288 which correspond to multiple drug resistance as mentioned below:
MTB_1087 (Isolate collected after 4 years of Infection): Resistant to Rifampicin, Isoniazid & Pyrazinamide
MTB_4891 (Isolate collected after 19 years of Infection): Resistant to Rifampicin, Isoniazid, Pyrazinamide, ethambutol, streptomycin, capreomycin & ethionamide
MTB_5288 (Isolate collected after 20 years of Infection): Resistant to Rifampicin, Isoniazid, Pyrazinamide, ethambutol, streptomycin, capreomycin & ethionamide
Links to PE FTP fastq files for different isolates considered in the study:
MTB_1087:
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR973/ERR973454/ERR973454_1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR973/ERR973454/ERR973454_2.fastq.gz
MTB_4891:
ftp.sra.ebi.ac.uk/vol1/fastq/ERR973/ERR973457/ERR973457_1.fastq.gz
ftp.sra.ebi.ac.uk/vol1/fastq/ERR973/ERR973457/ERR973457_2.fastq.gz
MTB_5288:
ftp.sra.ebi.ac.uk/vol1/fastq/ERR973/ERR973458/ERR973458_1.fastq.gz
ftp.sra.ebi.ac.uk/vol1/fastq/ERR973/ERR973458/ERR973458_2.fastq.gz
You can run the demo pipeline on the T-Bioinfo Server to learn the flow of steps in the pipeline and visualize the results obtained: https://server.t-bio.info/pipelinesmutationvariant/demopipelines/demo-multi-drug-resistant-tuberculosis
To get more insights about the project, run the pipelines and learn to interpret results, you can visit the example project on the OmicsLogic Learn Portal: https://learn.omicslogic.com/courses/course/project-17-tuberculosis-infection-and-treatment