Biology subjects

Farhat, M. R.

Publications and source records attributed to Farhat, M. R..

3 recordsLinked to original sources

bioRxiv2018

Genome wide association with quantitative resistance phenotypes in Mycobacterium tuberculosis reveals novel resistance genes and regulatory regions

Drug resistance is threatening attempts at tuberculosis epidemic control. Molecular diagnostics for drug resistance that rely on the detection of resistance-related mutations could expedite patient care and accelerate progress in TB eradication. We performed minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We then used a linear mixed model to evaluate genome wide associations between mutations in MTB genes or noncoding regions and drug resistance, followed by validation of our findings in an independent dataset of 792 patient isolates. Novel associations at 13 genomic loci were confirmed in the validation set, with 2 involving noncoding regions. We found promoter mutations to have smaller average effects on resistance levels than gene body mutations in genes where both can contribute to resistance. Enabled by a quantitative measure of resistance, we estimated the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. We also report the proportion of variation in resistance levels explained by the novel loci identified here. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causative or compensatory loci, and emphasizes the contribution of the noncoding portion of the genome.

evolutionary biology↗

bioRxiv2018

Rifampicin and rifabutin resistance in 1000 Mycobacterium tuberculosis clinical isolates

SynopsisDrug resistant tuberculosis (TB) remains a public health challenge with limited treatment options and high associated mortality. Rifamycins are among the most potent anti-TB drugs, and the loss of susceptibility to these agents, a hallmark of MDR TB, is considered a substantial therapeutic challenge. Rifamycins are known to target the RpoB subunit of RNA polymerase; however, our understanding of how rifamycin resistance is genetically encoded remains incomplete. Here we investigated rpoB genetic diversity and cross resistance between the two rifamycin drugs rifampicin (RIF) and rifabutin (RFB). We performed whole genome sequencing of 1005 MTB clinical isolates and measured minimum inhibitory concentration (MIC) to both agents on 7H10 agar using the indirect proportion method. Of the 1005 isolates, 767 were RIF resistant, and of these, 211 (27%) were sensitive to RFB at the critical concentration of 0.5ug/ml; 101/211 isolates had the rpoB mutation D435V (E.coli D516V). Isolates with discrepant resistance (RIF R and RFB S) 16.9 times more likely to harbor a D435V mutation as those resistant to both agents (OR 95% CI 10.5-27.9, P-value <10-40). To further understand this discrepancy, we generated both D435V and S450L (E.coli S531L) rpoB mutants in a laboratory strain and measured their antibiotic susceptibility using the alamar blue reduction assay. Compared with wildtype, D435V increased the 50% inhibitory concentration (IC50) to both RIF and RFB, however in both cases to a lesser degree than the S450L mutation. The observation that the rpoB D435V mutation produces an increase in the IC50 for both drugs contrasts with findings from previous smaller studies that suggested that isolates with D435V mutation remain RFB susceptible despite being RIF resistant. Our finding thus suggests that the recommended critical testing concentration for RFB should be revised.

evolutionary biology↗

bioRxiv2018

Genotypic clustering does not imply recent tuberculosis transmission in a high prevalence setting: A genomic epidemiology study in Lima, Peru

BackgroundWhole genome sequencing (WGS) can elucidate Mycobacterium tuberculosis (Mtb) transmission patterns but more data is needed to guide its use in high-burden settings. In a household-based transmissibility study of 4,000 TB patients in Lima, Peru, we identified a large MIRU-VNTR Mtb cluster with a range of resistance phenotypes and studied host and bacterial factors contributing to its spread.\n\nMethodsWGS was performed on 61 of 148 isolates in the cluster. We compared transmission link inference using epidemiological or genomic data with and without the inclusion of controversial variants, and estimated the dates of emergence of the cluster and antimicrobial drug resistance acquisition events by generating a time-calibrated phylogeny. We validated our findings in genomic data from an outbreak of 325 TB cases in London. Using a larger set of 12,032 public Mtb genomes, we determined bacterial factors characterizing this cluster and under positive selection in other Mtb lineages.\n\nFindingsFour isolates were distantly related and the remaining 57 isolates diverged ca. 1968 (95% HPD: 1945-1985). Isoniazid resistance arose once, whereas rifampicin resistance emerged subsequently at least three times. Amplification of other drug resistance occurred as recently as within the last year of sampling. High quality PE/PPE variants and indels added information for transmission inference. We identified five cluster-defining SNPs, including esxV S23L to be potentially contributing to transmissibility.\n\nInterpretationClusters defined by MIRU-VNTR typing, could be circulating for decades in a high-burden setting. WGS allows for an improved understanding of transmission, as well as bacterial resistance and fitness factors.\n\nFundingThe study was funded by the National Institutes of Health (Peru Epi study U19-AI076217 and K01-ES026835 to MRF). The funding sources had no role in any aspect of the study, manuscript or decision to submit it for publication.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSUse of whole genome sequencing (WGS) to study tuberculosis (TB) transmission has proven to have higher resolution that traditional typing methods in low-burden settings. The implications of its use in high-burden settings are not well understood.\n\nAdded value of this studyUsing WGS, we found that TB clusters defined by traditional typing methods may be circulating for several decades. Genomic regions typically excluded from WGS analysis contain large amount of genetic variation that may affect interpretation of transmission events. We also identified five bacterial mutations that may contribute to transmission fitness.\n\nImplications of all the available evidenceAdded value of WGS for understanding TB transmission may be even higher in high-burden vs. low-burden settings. Methods integrating variants found in polymorphic sites and insertions and deletions are likely to have higher resolution. Several host and bacterial factors may be responsible for higher transmissibility that can be targets of intervention to interrupt TB transmission in communities.

microbiology↗