A clear understanding of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.We identified 286 confidence-graded mutations associated with resistance. Compared to phenotypic methods, sensitivity (95% CI) for rifampicin was 90.3% (89.6-90.9%), while for isoniazid it was 78.2% (77.4-79.0%) and their specificities were 96.3% (95.7-96.8%) and 94.4% (93.1-95.5%), respectively. For second-line drugs, sensitivity varied from 67.4% (64.1-70.6%) for capreomycin to 88.2% (85.1-90.9%) for moxifloxacin, with specificity ranging from 90.0% (87.1-92.5%) for moxifloxacin to 99.5% (99.0-99.8%) for amikacin.This study provides a standardised and comprehensive approach for the interpretation of mutations as predictors of M. tuberculosis drug-resistant phenotypes. These data have implications for the clinical interpretation of molecular diagnostics and next-generation sequencing as well as efficient individualised therapy for patients with drug-resistant tuberculosis.

BACKGROUND: The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear. METHODS: We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance. RESULTS: A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted. CONCLUSIONS: Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.).

Inappropriately high breakpoints have resulted in systematic false-susceptible AST results to anti-TB drugs. MIC, PK/PD and clinical outcome data should be combined when setting breakpoints to minimise the emergence and spread of antimicrobial resistance. https://bit.ly/3i43wb6 | Approximately 85 000 deaths globally in 2019 were due to drug-resistant tuberculosis (TB), which corresponds to 7% of global deaths attributable to bacterial antimicrobial resistance [1]. Yet concerns have been mounting that drug-resistant TB was being underestimated because the approaches to define susceptibility and resistance to anti-TB agents had not kept up with those used for other major bacterial pathogens [2–9]. Here, we outline the recent, evidence-based initiatives spearheaded by the World Health Organization (WHO) and others to update breakpoints (traditionally referred to as critical concentrations (CCs)) that are used for phenotypic antimicrobial susceptibility testing (AST), also called drug susceptibility testing in the TB literature. | eng

Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the integration and analysis of whole-genome sequencing, clinical, and epidemiological data. Based on the work typically performed by hand during a cluster investigation, LITT identifies and ranks potential source cases for each case in a TB cluster. We evaluated LITT using a diverse dataset of 534 cases in 56 clusters (size range: 2-69 cases), which were investigated locally in three different U.S. jurisdictions. Investigators and LITT agreed on the most likely source case for 145 (80%) of 181 cases. By reviewing discrepancies, we found that many of the remaining differences resulted from errors in the dataset used for the LITT algorithm. In addition, we developed a graphical user interface, user's manual, and training resources to improve LITT accessibility for frontline staff. While LITT cannot replace thorough field investigation, the algorithm can help investigators systematically analyze and interpret complex data over the course of a TB cluster investigation. Code available at: https://github.com/CDCgov/TB_molecular_epidemiology/tree/1.0; https://zenodo.org/badge/latestdoi/166261171.

Fluoroquinolones (FQ) are crucial components of multidrug-resistant tuberculosis (MDR TB) treatment. Varying levels of resistance are associated with specific mutations within the Quinolone Resistance Determining Region (QRDR) of gyrA We sequenced the QRDR from serial isolates of MDR TB patients in the Preserving Effective TB Treatment Study (PETTS) with baseline (FQ(R)) or acquired FQ resistance (FQ(ACQR)) using the IonTorrent™ Personal Genome Machine to a depth of 10,000x and reported single nucleotide polymorphisms in ≥1% of reads. FQ(R) isolates harbored 15 distinct alleles with 1.3 (max=6) on average per isolate. Eighteen alleles were identified in FQ(ACQR) isolates with an average of 1.6 (max=9) per isolate. Isolates from 78% of FQ(ACQR) individuals had mutant alleles identified within 6 months of treatment initiation. Asp94Gly followed by Ala90Val were the predominant alleles in initial FQ-resistant isolates. Seventy-seven percent (36/47) of FQ(ACQR) group patients had isolates with FQ resistance alleles prior to changes to the FQ component of their treatment. Unlike individuals treated initially with other FQs, none of the 21 individuals treated initially with levofloxacin developed genotypic or phenotypic FQ resistance, although, country of residence is likely a contributing factor since 69% of these individuals were from a single country. Initial detection of phenotypic and genotypic resistance occurred simultaneously for most; however, phenotypic resistance occurred earlier in isolates harboring mixtures of very low-abundance (<1% of reads) alleles while genotypic resistance often occurred earlier for low-level resistance-associated alleles. Understanding factors influencing acquisition and evolution of FQ resistance could reveal strategies for improved treatment success.

BACKGROUND: Mutations in the genes inhA, katG and rpoB confer resistance to anti-tuberculosis (TB) drugs isoniazid and rifampin. We questioned whether specific mutations in these genes were associated with different clinical and microbiological characteristics. METHODS: In a multi-country prospective cohort study of MDR-TB, we identified inhA, katG and rpoB mutations in sputum isolates using the Hain MTBDRplus line probe assay. For specific mutations, we performed bivariate analysis to determine relative risk of baseline or acquired resistance to other TB drugs. We compared time-to-sputum-culture-conversion (TSCC) using Kaplan-Meier curves and stratified Cox regression. RESULTS: In total, 447 participants enrolled January 2005-December 2008 from seven countries were included. Relative to rpoB S531L, isolates with rpoB D516V had less cross-resistance to rifabutin, increased baseline resistance to other drugs, and increased acquired fluoroquinolone resistance.Relative to mutation of katG only, mutation of inhA promoter and katG was associated with increased acquired fluoroquinolone resistance and slower TSCC (125.5 vs. 89.0 days). CONCLUSIONS: Specific mutations in inhA and katG are associated with differences in resistance to other drugs and TSCC. Molecular testing may make it possible to tailor treatment and assess additional drug resistance risk according to specific mutation profile.

BACKGROUND: Atypical Beijing genotype Mycobacterium tuberculosis strains are widespread in South Africa and have acquired resistance to up to 13 drugs on multiple occasions. It is puzzling that these strains have retained fitness and transmissibility despite the potential fitness cost associated with drug resistance mutations. METHODS: We conducted Illumina sequencing of 211 Beijing genotype M. tuberculosis isolates to facilitate the detection of genomic features that may promote acquisition of drug resistance and restore fitness in highly resistant atypical Beijing forms. Phylogenetic and comparative genomic analysis was done to determine changes that are unique to the resistant strains that also transmit well. Minimum inhibitory concentration (MIC) determination for streptomycin and bedaquiline was done for a limited number of isolates to demonstrate a difference in MIC between isolates with and without certain variants. RESULTS: Phylogenetic analysis confirmed that two clades of atypical Beijing strains have independently developed resistance to virtually all the potent drugs included in standard (pre-bedaquiline) drug-resistant TB treatment regimens. We show that undetected drug resistance in a progenitor strain was likely instrumental in this resistance acquisition. In this cohort, ethionamide (ethA A381P) resistance would be missed in first-line drug-susceptible isolates, and streptomycin (gidB L79S) resistance may be missed due to an MIC close to the critical concentration. Subsequent inadequate treatment historically led to amplification of resistance and facilitated spread of the strains. Bedaquiline resistance was found in a small number of isolates, despite lack of exposure to the drug. The highly resistant clades also carry inhA promoter mutations, which arose after ethA and katG mutations. In these isolates, inhA promoter mutations do not alter drug resistance, suggesting a possible alternative role. CONCLUSION: The presence of the ethA mutation in otherwise susceptible isolates from ethionamide-naive patients demonstrates that known exposure is not an adequate indicator of drug susceptibility. Similarly, it is demonstrated that bedaquiline resistance can occur without exposure to the drug. Inappropriate treatment regimens, due to missed resistance, leads to amplification of resistance, and transmission. We put these results into the context of current WHO treatment regimens, underscoring the risks of treatment without knowledge of the full drug resistance profile.

Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies.

Bedaquiline improves survival among persons with multidrug-resistant tuberculosis (MDR-TB).1 We report the case of a 65-year-old South African man who was negative for human immunodeficiency virus and in whom MDR-TB was diagnosed in 2013 (resistant to rifampin and isoniazid; phenotypically susceptible to a fluoroquinolone and amikacin). A baseline radiograph showed changes consistent with bilateral tuberculosis with left apex cavitation. He started standardized treatment that included moxifloxacin, pyrazinamide, kanamycin, ethionamide, isoniazid, and terizidone. After initial sputum culture conversion (at month 3) and clinical improvement, the patient again became culture-positive, and bilateral cavitation developed. After detection of phenotypic resistance to fluoroquinolones (at month 6), his treatment was revised (at month 8) to include high-dose isoniazid, ethambutol, pyrazinamide, terizidone, linezolid, paraaminosalicylic acid, and kanamycin (Figure 1 and the Supplementary Appendix, available with the full text of this letter at NEJM.org). Bedaquiline was added 22 days later and was administered for 6 months.2 The patient remained culture-positive (treatment failure), and treatment was stopped 15 months after revision of the regimen. The patient died 7 months later.

Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibility testing (DST) and clinical data. We developed a unified analysis variant pipeline (UVP) ( https://github.com/CPTR-ReSeqTB/UVP ) to identify variants and assign lineage from MTBC sequence data. Stringent thresholds and quality control measures were incorporated in this open source tool. The pipeline was validated using a well-characterized dataset of 90 diverse MTBC isolates with conventional DST and DNA Sanger sequencing data. The UVP exhibited 98.9% agreement with the variants identified using Sanger sequencing and was 100% concordant with conventional methods of assigning lineage. We analyzed 4636 publicly available MTBC isolates in the ReSeqTB platform representing all seven major MTBC lineages. The variants detected have an above 94% accuracy of predicting drug based on the accompanying DST results in the platform. The aggregation of variants over time in the platform will establish confidence-graded mutations statistically associated with phenotypic drug resistance. These tools serve as critical reference standards for future molecular diagnostic assay developers, researchers, public health agencies and clinicians working towards the control of drug-resistant tuberculosis.

Resistance to the first-line anti-tuberculosis (TB) drug, isoniazid (INH), is widespread, and the mechanism of resistance is unknown in approximately 15% of INH-resistant (INH-R) strains. To improve molecular detection of INH-R TB, we used whole genome sequencing (WGS) to analyze 52 phenotypically INH-R Mycobacterium tuberculosis complex (MTBC) clinical isolates that lacked the common katG S315T or inhA promoter mutations. Approximately 94% (49/52) of strains had mutations at known INH-associated loci that were likely to confer INH resistance. All such mutations would be detectable by sequencing more DNA adjacent to existing target regions. Use of WGS minimized the chances of missing infrequent INH resistance mutations outside commonly targeted hotspots. We used recombineering to generate 12 observed clinical katG mutations in the pansusceptible H37Rv reference strain and determined their impact on INH resistance. Our functional genetic experiments have confirmed the role of seven suspected INH resistance mutations and discovered five novel INH resistance mutations. All recombineered katG mutations conferred resistance to INH at a minimum inhibitory concentration of >/=0.25 mug/mL and should be added to the list of INH resistance determinants targeted by molecular diagnostic assays. We conclude that WGS is a useful tool for detecting uncommon INH resistance mutations that would otherwise be missed by current targeted molecular testing methods, and suggest that its use (or use of expanded conventional or NGS-based targeted sequencing) may provide earlier diagnosis of INH-R TB.

We previously reported use of genotype surveillance data to predict outbreaks among incident tuberculosis clusters. We propose a method to detect possible outbreaks among endemic tuberculosis clusters. We detected 15 possible outbreaks, of which 10 had epidemiologic data or whole-genome sequencing results. Eight outbreaks were corroborated.

Pyrazinamide (PZA) is a standard component of first-line treatment regimens for Mycobacterium tuberculosis (Mtb) and is included in treatment regimens for drug-resistant Mtb whenever possible. It is therefore imperative that susceptibility to PZA be reliably assessed prior to initiation of therapy. Currently-available growth-based PZA susceptibility tests are time consuming and results can be inconsistent. Molecular tests have been developed for most first-line antituberculosis drugs, however, a commercial molecular test is not yet available for rapid detection of PZA resistance. Recently, a line probe assay, NIPRO GenoscholarPZA-TB II, was developed for the detection of mutations within the pncA gene including the promoter region likely to lead to PZA resistance. The sensitivity and specificity of this assay was evaluated by two independent laboratories using a combined total of 249 strains with mutations in pncA and its promoter as well as 21 strains with wild-type pncA Overall, the assay showed good sensitivity (93.2%, 95%CI 89.3, 95.8) and moderate specificity (91.2%, 95%CI 77.0, 97.0) for the identification of Mtb predicted to be resistant to PZA based upon the presence of mutations (excluding known PZA susceptible mutations) in the pncA coding region or promoter. The assay shows promise for the molecular prediction of PZA resistance.

BACKGROUND: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of anti-tuberculosis drugs. OBJECTIVES: To determine the optimal molecular approach needed, we sought to create a comprehensive catalogue of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance. METHODS: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug resistance loci in M.tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1397 clinical M.tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line anti-tuberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool. RESULTS: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity, but was lower for other drugs. The number of mutations needed to diagnose resistance is large and for the 13 drugs studied it was 238 across 18 genetic loci. CONCLUSION: These data suggest that a comprehensive M.tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole genome sequencing, encode resistance to second-line TB drugs.

Despite the interactions known to occur between various lower respiratory tract pathogens and alveolar epithelial cells (AECs), few reports examine factors influencing the interplay between Mycobacterium tuberculosis bacilli and AECs during infection. Importantly, in vitro studies have demonstrated that the M. tuberculosis hbha and esxA gene products HBHA and ESAT6 directly or indirectly influence AEC survival. In this report, we identify Rv3351c as another M. tuberculosis gene that impacts the fate of both the pathogen and AEC host. Intracellular replication of an Rv3351c mutant in the human AEC type II pneumocyte cell line A549 was markedly reduced relative to the complemented mutant and parent strain. Deletion of Rv3351c diminished the release of lactate dehydrogenase and decreased uptake of trypan blue vital stain by host cells infected with M. tuberculosis bacilli, suggesting attenuated cytotoxic effects. Interestingly, an isogenic hbha mutant displayed reductions in AEC killing similar to those observed for the Rv3351c mutant. This opens the possibility that multiple M. tuberculosis gene products interact with AECs. We also observed that Rv3351c aids intracellular replication and survival of M. tuberculosis in macrophages. This places Rv3351c in the same standing as HBHA and ESAT6, which are important factors in AECs and macrophages. Defining the mechanism(s) by which Rv3351c functions to aid pathogen survival within the host may lead to new drug or vaccine targets.

As the prevalence of multidrug-resistant and extensively drug-resistant tuberculosis strains continues to rise, so does the need to develop accurate and rapid molecular tests to complement time consuming growth-based drug susceptibility testing. Performance of molecular methods relies on the association of specific mutations with phenotypic drug resistance and while considerable progress has been made for resistance detection of first-line antituberculosis drugs, rapid detection of resistance for second-line drugs lags behind. The rrs A1401G allele is considered a strong predictor of cross-resistance between the three second-line injectable drugs, capreomycin (CAP), kanamycin, and amikacin. However, discordance is often observed between the rrs A1401G mutation and CAP resistance, with up to 40% of rrs A1401G mutants being classified as CAP susceptible. We measured the minimal inhibitory concentrations (MICs) to CAP in 53 clinical isolates harboring the A1401G mutation and found that the CAP MICs ranged from 8 mug/ml to 40 mug/ml. These results were drastically different from engineered A1401G mutants generated in isogenic Mycobacterium tuberculosis, which exclusively exhibited high-level CAP MICs of 40 mug/ml. These data support prior studies suggesting the critical concentration of CAP (10 mug/ml) used to determine resistance by indirect agar proportion may be too high to detect all CAP resistant strains and suggests that a larger percentage of resistant isolates could be identified by lowering the critical concentration. These data also suggest that differences in resistance levels among clinical isolates are possibly due to second site or compensatory mutations located elsewhere in the genome.

Owing to the rise in drug resistance in tuberculosis combined with the global spread of its causative pathogen, Mycobacterium tuberculosis (Mtb), innovative anti mycobacterial agents are urgently needed. Recently, we developed a novel primase-pyrophosphatase assay and used it to discover inhibitors of an essential Mtb enzyme, primase DnaG (Mtb DnaG), a promising and unexplored potential target for novel antituberculosis chemotherapeutics. Doxorubicin, an anthracycline antibiotic used as an anticancer drug, was found to be a potent inhibitor of Mtb DnaG. In this study, we investigated both inhibition of Mtb DnaG and the inhibitory activity against in vitro growth of Mtb and M. smegmatis (Msm) by other anthracyclines, daunorubicin and idarubicin, as well as by less cytotoxic DNA intercalators: aloe-emodin, rhein and a mitoxantrone derivative. Generally, low-muM inhibition of Mtb DnaG by the anthracyclines was correlated with their low-muM minimum inhibitory concentrations. Aloe-emodin displayed threefold weaker potency than doxorubicin against Mtb DnaG and similar inhibition of Msm (but not Mtb) in the mid-muM range, whereas rhein (a close analog of aloe-emodin) and a di-glucosylated mitoxantrone derivative did not show significant inhibition of Mtb DnaG or antimycobacterial activity. Taken together, these observations strongly suggest that several clinically used anthracyclines and aloe-emodin target mycobacterial primase, setting the stage for a more extensive exploration of this enzyme as an antibacterial target.

Fluoroquinolone antibiotics are among the most potent second-line drugs used for treatment of multidrug-resistant tuberculosis (MDR TB), and resistance to this class of antibiotics is one criterion for defining extensively drug resistant tuberculosis (XDR TB). Fluoroquinolone resistance in Mycobacterium tuberculosis has been associated with modification of the quinolone resistance determining region (QRDR) of gyrA. Recent studies suggest that amino acid substitutions in gyrB may also play a crucial role in resistance, but functional genetic studies of these mutations in M. tuberculosis are lacking. In this study, we examined twenty six mutations in gyrase genes gyrA (seven) and gyrB (nineteen) to determine the clinical relevance and role of these mutations in fluoroquinolone resistance. Transductants or clinical isolates harboring T80A, T80A+A90G, A90G, G247S and A384V gyrA mutations were susceptible to all fluoroquinolones tested. The A74S mutation conferred low-level resistance to moxifloxacin but susceptibility to ciprofloxacin, levofloxacin and ofloxacin, and the A74S+D94G double mutation conferred cross resistance to all the fluoroquinolones tested. Functional genetic analysis and structural modeling of gyrB suggest that M330I, V340L, R485C, D500A, D533A, A543T, A543V and T546M mutations are not sufficient to confer resistance as determined by agar proportion. Only three mutations, N538D, E540V and R485C+T539N, conferred resistance to all four fluoroquinolones in at least one genetic background. The D500H and D500N mutations conferred resistance only to levofloxacin and ofloxacin while N538K and E540D consistently conferred resistance to moxifloxacin only. Transductants and clinical isolates harboring T539N, T539P or N538T+T546M mutations exhibited low-level resistance to moxifloxacin only but not consistently. These findings indicate that certain mutations in gyrB confer fluoroquinolone resistance, but the level and pattern of resistance varies among the different mutations. The results from this study provide support for the inclusion of the QRDR of gyrB in molecular assays used to detect fluoroquinolone resistance in M. tuberculosis.

The emergence of multi and extensively drug-resistant tuberculosis is a significant impediment to the control of this disease because treatment becomes more complex and costly. Reliable and timely drug susceptibility testing is critical to ensure patients receive effective treatment and become non-infectious. Molecular methods can provide accurate and rapid drug susceptibility results. We used DNA sequencing to detect resistance to the first-line antituberculosis drugs, isoniazid (INH), rifampin (RIF), pyrazinamide (PZA), and ethambutol (EMB), and the second-line drugs, amikacin (AMK), capreomycin (CAP), kanamycin (KAN), ciprofloxacin, (CIP) and ofloxacin (OFX). Nine loci were sequenced: rpoB for resistance to RIF, katG and inhA (INH), pncA (PZA), embB (EMB), gyrA (CIP and OFX), rrs, eis, and tlyA (KAN, AMK, and CAP). A total of 314 clinical M. tuberculosis complex isolates, representing a variety of antibiotic resistance patterns, genotypes and geographical origins were analyzed. The molecular data were compared to the phenotypic data and the accuracy values were calculated. Sensitivity and specificity values (as percentages) for the first-line drug loci were rpoB (97.1, 93.6), katG (85.4, 100), inhA (16.5, 100), katG and inhA together (90.6, 100) pncA (84.6, 85.8), and embB (78.6, 93.1). The values for the second-line drugs were also calculated. The size and scope of this study, in numbers of loci and isolates examined, and the phenotypic diversity of those isolates, support the use of DNA sequencing to detect drug resistance in the M. tuberculosis complex. Further, the results can be used to design diagnostic tests utilizing other mutation detection technologies.