Drug Susceptibility and Mutation Profiles in Mycobacterium tuberculosis Isolates from a Tertiary Care Hospital in Kerala, India

ABSTRACT.

The rising prevalence of drug-resistant Mycobacterium tuberculosis (MTB) strains poses a significant challenge to global tuberculosis (TB) control efforts. This study aimed to analyze drug resistance patterns and investigate the molecular characteristics of 193 MTB clinical isolates to shed light on the mechanisms of drug resistance. Of the 193 MTB clinical isolates, 28.5% (n = 53) exhibited mono-drug or multidrug resistance. Pyrazinamide mono-drug resistance (PZA^r) was the most prevalent (17%, n = 33), followed by isoniazid mono-drug resistance (3.6%, n = 7). Rifampicin resistance was associated with mutations in the rpoB gene (D435Y, D435V, S450L, L452P). Isoniazid resistance mutations were found in the katG (S315T), inhA (C[-15] T), and ndh (R268H) genes, whereas ethambutol resistance mutations were observed in the embB gene (M306V, M306I, M306L, G406S, Q497R). Surprisingly, 94% of PZA^r isolates (n = 31) showed no mutations in the pncA or rpsA genes. The presence of the R268H mutation in the ndh gene, not previously linked to PZA^r, was detected in 15% of PZA^r isolates (n = 5), suggesting its potential contribution to PZA^r in specific cases but not as a predominant mechanism. The specific molecular mechanisms underlying PZA^r in the majority of the isolates remain unknown, emphasizing the need for further research to uncover the contributing factors. These findings contribute to the understanding of drug resistance patterns and can guide future efforts in TB control and management.

INTRODUCTION

Tuberculosis (TB) remains a significant global health concern, with a high burden of morbidity and mortality. The first-line anti-TB drugs, including rifampicin (RIF), isoniazid (INH), ethambutol (EMB), and pyrazinamide (PZA), form the cornerstone of TB treatment regimens. These drugs target specific cellular components and metabolic pathways of Mycobacterium tuberculosis (MTB), the causative agent of TB, inhibiting bacterial growth and preventing disease progression. The emergence and spread of drug resistance in MTB present significant challenges for TB control efforts. Multidrug-resistant tuberculosis (MDR-TB) represents a critical threat, characterized by resistance to at least two of the most potent first-line antitubercular drugs, INH and RIF.¹ Globally, approximately 450,000 incident cases of MDR/RR–TB were reported in 2021. The estimated proportion of TB patients with MDR/RR–TB was 3.6% among new cases and 18% among those previously treated. The global prevalence of MDR-TB and extensively drug-resistant TB (XDR-TB) is estimated to be 11.6% and 2.5%, respectively.² Managing MDR-TB necessitates prolonged and intensive therapy, often involving less effective, more toxic, and costlier drugs for extended durations.^3,4 In addition, RIF-monoresistant TB, XDR-TB, and pre-extensively drug-resistant tuberculosis further complicate treatment options, as they exhibit resistance to multiple frontline and second-line drugs.⁵ Furthermore, the emergence of resistance to PZA, a pivotal component of first-line TB treatment with sterilizing properties, raises concerns regarding treatment efficacy and success rates.⁶

To develop effective treatment strategies and to prevent the spread of the disease, a thorough understanding of the underlying molecular mechanisms of drug resistance is essential. Several studies have identified genetic mutations in MTB strains that confer resistance to specific drugs. For instance, RIF acts by binding to the β-subunit of RNA polymerase, encoded by the rpoB gene, thus inhibiting transcription and RNA synthesis. Resistance to RIF predominantly arises because of mutations in the RIF resistance determining region (RRDR) of the rpoB gene, spanning 81 base pairs (codons 426 and 452, 27 codons).^7,8 These mutations prevent the binding of RIF to RNA polymerase, rendering the drug ineffective. Moreover, mutations in other genes involved in RNA polymerase, such as rpoA, rpoC, and rpoD, have also been linked to RIF resistance, albeit less frequently.^9,10 Isoniazid, a prodrug that targets the mycolic acid synthesis pathway, undergoes activation through the action of catalase-peroxidase (KatG). The resulting active INH products target specific enzymes, including enoyl acyl carrier protein reductase (InhA) and beta-ketoacyl ACP synthase (KasA), which play vital roles in various biosynthetic networks and pathways. Conversely, arylamine N-acetyltransferases (NATs) can deactivate INH. Resistance to INH is primarily attributed to mutations in the katG gene, encoding the KatG enzyme responsible for activating INH, or in the inhA gene itself. Additional mutations in the fabG1, ndh, and kasA genes have also been associated with INH resistance.¹¹ Ethambutol disrupts the biosynthesis of arabinogalactan, an essential component of the mycobacterial cell wall, by inhibiting the enzyme arabinosyltransferase. Resistance to EMB primarily results from mutations in the embB gene, which encodes the arabinosyltransferase enzyme. Mutations in embC and embA genes have also been associated with EMB resistance, though less commonly observed.¹² PZA plays a critical role in shortening the duration of TB treatment and effectively targeting dormant MTB populations. Pyrazinamide is converted into its active form, pyrazinoic acid, by the enzyme pyrazinamidase, encoded by the pncA gene. Resistance to PZA is primarily caused by mutations in the pncA gene, resulting in reduced or loss of pyrazinamidase activity.¹³ Mutations in ribosomal protein S1 (rpsA) disrupt critical interactions with PZA, resulting in resistance.^14,15 Furthermore, mutations in the panD gene, essential for coenzyme A synthesis, can also confer PZA resistance.^16,17 Other reported mechanisms of PZA resistance include overexpression of efflux proteins such as Rv0191, Rv3756c, Rv3008, and Rv1667c.¹⁸ In addition, a potential role of arylamine NAT activity via acetylation is hypothesized in PZA resistance. However, direct evidence confirming this mechanism in PZA-resistant isolates is lacking. Missense mutations in the rpsL gene, which codes for ribosomal protein S12, and nucleotide substitutions in the 16S ribosomal RNA gene (rrs) have been linked to streptomycin resistance.¹⁹ Amino acid substitutions within the DNA gyrase A subunit gene (gyrA) have been repeatedly identified in fluoroquinolone-resistant MTB isolates.²⁰

Understanding the resistance patterns and molecular mechanisms associated with these first-line anti-TB drugs is vital for effective TB management. Molecular testing would provide rapid and accurate detection of specific genetic mutations associated with drug resistance in MTB strains. It enables early and precise diagnosis, allowing for the prompt initiation of targeted treatment regimens tailored to the drug resistance profile of each patient. This study aimed to investigate the molecular basis of drug resistance in MTB culture isolates.

MATERIALS AND METHODS

Mycobacterium tuberculosis complex isolates.

The current descriptive study was performed with 193 clinical M. tuberculosis complex isolates from 2017 to 2022. Patient demographics including age, sex, comorbidities, and past TB infection, were collected.

Mycobacterial culture.

All clinical specimens underwent digestion and decontamination using the standard N-acetyl-L-cysteine-NaOH method. The resulting sediments were then suspended in 1 mL of sterile phosphate-buffered saline with a pH of 6.8. From the processed specimen, an inoculum of 0.5 mL was extracted. Mycobacterial culturing was carried out using the BACTEC Mycobacterial Growth Indicator Tube (MGIT) 960 TB system (BD Diagnostics, Franklin Lakes, NJ).²¹ Inoculated MGIT vials were placed in the MGIT 960 instrument and incubated until flagged positive or up to 6 weeks. Positive MGIT isolates were confirmed via acid-fast bacillus staining.²² The isolates were further tested using rapid immunochromatographic assay, SD Bioline MPT64 Card assay (Standard Diagnostics, Suwon, Korea) to distinguish between mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacteria (NTM).^23,24 The culture isolates, positive for MPT64 antigen, were identified as MTBC, and negatives were identified as NTM.

Phenotypic drug susceptibility testing.

Phenotypic drug susceptibility testing (DST) for MTB isolates was performed following the guidelines of the Clinical and Laboratory Standards Institute. The MGIT960 system was used to perform susceptibility testing for first-line anti-TB drugs using these concentrations: streptomycin (1.0 and 6.0 µg/mL), INH (0.1 and 0.4 µg/mL), RIF (1.0 µg/mL), and EMB (5.0 and 7.5 µg/mL). For PZA susceptibility testing, modified broth at pH 5.9 was used with PZA (100 µg/mL). Each drug-containing tube, including MGIT PZA, was inoculated with 0.5 mL of positive broth culture. streptomycin, isoniazid, rifampin and ethambutol (SIRE) control had 0.5 mL (1:100 dilution of the positive culture broth, and PZA control had 0.5 mL (1:10 dilution of the positive culture broth in sterile saline).^25,26 The tubes were incubated in the M960 instrument and monitored continuously, with automated interpretation of susceptibility/resistance using predefined algorithms.

Molecular testing.

Genomic DNA was isolated from 5 mL of MGIT broth culture isolates using the QIAmp DNA Mini Kit (QIAGEN, Hilden, Germany) per the manufacturer’s instructions. The targeted regions of the genes rpoB, inhA, katG, pncA, rpsA, ndh, and embB were polymerase chain reaction (PCR) amplified using the primers listed in Table 1. All amplification reactions were performed in a final volume of 50 µL using 2× EmeraldAmp GT PCR mix (Takara, Kusatsu, Japan) containing 2× PCR buffer, 1.5 mM MgCl₂, 20 mM deoxyribonucleotide triphosphates, 2 U Taq DNA polymerase, 10 pM forward and reverse primer, and 35 ng of DNA template. Polymerase chain reaction–amplified fragments were separated by electrophoresis using 1–2% agarose gels in 0.5× tris-borate-EDTA buffer and visualized by staining with ethidium bromide, and gel images were captured.

Table 1.

Primers used in this study

Drug	Target	Primer	Primer Sequences (5′ to 3′)	Product Size (bp)
Rifampicin	rpoB	rpoB_F	CCCAGGACGTGGAGGCGATCAC	537
		rpoB_R	GGCGGGGCGAGACGTCCATGTA
		rpoB_Res_F	CACACCGCAGACGTTGAT	167
		rpoB_Res_R	CACGCTCACGTGACAGACC
Isoniazid	inhA	inhA_15_F	CGAAGTGTGCTGAGTCACACCG	203
		inhA_15_R	TCCGGTAACCAGGACTGAAC
	katG	katG_315_F	CATGAACGACGTCGAAACAG	233
		katG_315_R	CGAGGAAACTGTTGTCCCAT
Pyrazinamide	pncA	pncA_F	GATCTATCCCGCCGGTTGGGTG	798
		pncA_R	CCGGTGAACAACCCGACCCAG
	rpsA	rpsA_F	GGCCGCAGCTGGGACGCGGC	739
		rpsA_R	CGTTGTTGCGGTTCTTGTC
	ndh	ndh_F	GACAGATCGCCGAGCTGGC	372
		ndh_R	TGGACAGGTCGGGCAGCAC
EMB	embB	EMB_1687_F	GACACCCGGTTCTCCACCCG	1,687
		EMB_1687_R	CGTCCAGCGGCTTCATGAAACC
		EMB_647_F	CGGCGGCCATGGTCTTGCTG	647
		EMB_647_R	GGCGGCGAACAGCCCGAAGT
		EMB_591_F	GGCGGCTGATGGGCGTCATC	Sequencing Primer
		EMB_579_R	GTTGAACGGCATCCACGCG	Sequencing Primer

EMB = ethambutol.

Polymerase chain reaction products were purified (EXO-SAP, NEB Biolabs, Ipswich MA) and were sequenced using the BigDye v.3.1 Terminator Cycle Sequencing Kit (Applied Biosystems, Waltham, MA) in the ABI 3500 Genetic Analyzer (Applied Biosystems). Sequence analysis was performed using FinchTV software (v.1.4.0). The sequences were compared with the M. tuberculosis reference strain H37Rv sequence of the respective genes from GenBank database using the BLASTN algorithm. Whole-genome sequencing (WGS) was performed using probe-based enrichment capture to sequence the entire 4.4-Mb genome of resistant (n = 10) and sensitive (n = 2) MTB culture isolates. The sequencing was performed on the Illumina HiSeq platform (San Diego, CA). Adapter removal and trimming of the raw sequences was done by Trimgalore, and bases with Phred quality scores greater than 20 were aligned to the MTB reference strain H37Rv (GenBank NC_018143.2). Variant calling was performed using LoFreq, followed by variant annotation using Variant Effect Predictor.

RESULTS

Patient characteristics.

A total of 193 patients for whom first-line susceptibility data were available between 2017 and 2022 were included in the analysis. The median age of TB patients in the study was 51 years (range: 19–87 years), with a male infection rate of 60.62% and a female infection rate of 39.38%. Among the cases, 96.37% (186/193) were newly diagnosed, whereas 3.63% (7/193) had previously received anti-TB therapy. Comorbidities were present in 39.38% (76/193) of the cases, with diabetes (25.39%) and hypertension (12.44%) being the most common risk factors associated with TB (Table 2).

Table 2.

Patient demographic details (N = 193)

Parameter	No. of Patients (%)
Sex
Male	117 (60.62)
Female	76 (39.38)
Age Group
1–20 Years	2 (1.04)
21–40 Years	61 (31.61)
41–60 Years	70 (36.27)
61–80 Years	54 (27.98)
>80 Years	06 (3.11)
Risk Factors
Diabetes	49 (25.39)
Hypertension	24 (12.44)
Chronic Liver Disease	12 (6.22)
Cardiovascular Diseases	12 (6.22)
Past TB Infection	7 (3.63)
Chronic Kidney Disease	6 (3.11)
Chronic Obstructive Pulmonary Disease	5 (2.59)
Malignancy	4 (2.07)

TB = tuberculosis.

Phenotypic DST.

Of the 193 isolates tested, 138 (71.5%) were found to be susceptible to all first-line drugs, whereas the remaining 55 (28.5%) exhibited mono- or multidrug resistance. Pyrazinamide mono-drug resistance was the most prevalent, observed in 33 isolates (17%), followed by INH mono-drug resistance in seven isolates (3.6%), whereas RIF mono-resistance was observed in 1% (n = 2) of the isolates. None of the isolates exhibited mono-drug resistance to EMB. Multidrug resistance, involving INH and RIF, was detected in only three isolates (1.6%). Six isolates (3.1%) displayed resistance to both INH, PZA, and/or EMB but sensitive to RIF (polyresistant Hr-TB), whereas no isolates with resistance to RIF, PZA, and/or EMB but sensitivity to INH (polyresistant RR-TB) were detected. Two isolates (1.03%) were multidrug resistant, including resistance to EMB. In addition, two isolates (1.03%) were resistant to all four first-line anti-TB drugs (Table 3). Notably, isolates resistant to EMB also showed resistance to INH. The GeneXpert RIF resistance data for the DST isolates correlated with the culture method.

Table 3.

Drug susceptibility test data of the MTBC clinical isolates

Details	Number of Isolates	Percentage (%)
No. of Isolates DST Done	193
Total No. of Sensitive Isolates	138	71.5
Total No. of Resistant Isolates	55	28.5
Drug Resistance Type
Pyrazinamide	33	17
Isoniazid	7	3.6
Rifampicin	2	1.0
EMB	0	0.0
Isoniazid and Rifampicin (MDR)	3	1.6
Polyresistant Hr-TB	6	3.1
Polyresistant RR-TB	0	0.0
MDR- and EMB-Resistant Isolates	2	1.03
No. of Isolates Resistant to All Firstline Anti-TB Drugs	2	1.03

DST = drug susceptibility test; EMB = ethambutol; MDR = multidrug resistance; MTBC = Mycobacterium tuberculosis complex; polyresistant Hr-TB = resistant to INH, PZA, and/or EMB but sensitive to RIF; polyresistant RR-TB = resistant to RIF, PZA, and/or EMB but sensitive to INH.

Drug resistance mutations.

Characterization of the drug resistance mutations present in MTB isolates was done using a combination of Sanger sequencing (SS) and WGS techniques. A total of 53 MTB isolates that were resistant to at least one drug were analyzed for resistance mutations in genes associated with four key anti-TB drugs: RIF (rpoB), INH (inhA and katG), PZA (pncA, rpsA, and ndh), and EMB (embB). Five isolates that were sensitive to all four drugs were also analyzed. Whole-genome sequencing was also conducted on a total of 12 MTB isolates, consisting of 10 resistant and two sensitive strains. The lineage identification of the MTB isolates revealed a diverse distribution: nine isolates belonged to the Indo-Oceanic or EAI lineage (Lineage 1); one isolate was classified as East-Asian lineage, Beijing (Lineage 2); and two isolates belonged to the central Asian Strain or CAS lineage (Lineage 3).

Whole-genome sequencing analysis and SS targeting RRDR of the rpoB gene identified mutations at codons 435 (GAC→TAC, D435Y, one isolate; GAC→GTC, D435V, one isolate), 450 (TCG→TTG, S450L, six isolates), and at codon 452 (CTG→CCG, L452P, one isolate). Of the 20 INH-resistant isolates analyzed, five exhibited a serine to threonine substitution at codon 315 (AGC→ACC, S315T) of the katG gene, whereas six isolates displayed a C(-15) T mutation in the promoter region of the inhA gene. Mutation analysis of the embB gene that was performed on eight EMB-resistant isolates revealed mutations at codons 306, 406, and 497 in six isolates. At codon 306, methionine was replaced by either valine (ATG→GTG, M306V, one isolate), isoleucine (ATG→ATA, M306I, one isolate), or leucine (ATG→CTG, M306L, one isolate). Two isolates showed a substitution of glycine406 by serine (GGC→AGC, G406S, two isolates). Furthermore, at codon 497, glutamine was replaced by arginine (CAG→CGG, Q497R, one isolate). Interestingly, an EMB-sensitive isolate exhibited a mutation at codon 285 (TTC→TTA), resulting in the replacement of phenylalanine with leucine (F285L). Among the 33 PZA mono-drug–resistant isolates analyzed, 31 isolates did not exhibit any mutations in either the pncA or rpsA gene. However, one isolate was found to carry a mutation at codon 134 (GCC→ACC, A134T) within the pncA gene, and another isolate displayed a T (-11)C mutation in the promoter region of the same gene. Interestingly, WGS analysis of two PZA-resistant isolates did not reveal any known mutations associated with PZA resistance in the examined genes. Instead, a mutation in the ndh gene at codon 268 (CGC→CAC, R268H) was detected in both isolates. However, further SS of the ndh gene in the rest of the PZA mono-drug–resistant isolates identified this mutation in only three isolates. The underlying molecular mechanisms that contributed to PZA resistance in the majority of the isolates remain unknown. Furthermore, two isolates exhibited a mutation at codon 43 in the rpsL gene, leading to the replacement of lysine with arginine (AAG→AGG, K43R) (Table 4). This mutation is known to confer resistance to streptomycin.

Table 4.

Summary of the drug resistance/sensitive mutations identified in MTB isolates

Drug	Gene	Method	No. of Isolates	Nucleotide Change	Amino Acid Change	Codon	Phenotype
RIF	rpoB	SS	3	TCG→TTG	Ser to Leu	450	Resistant
		SS	1	CTG→CCG	Leu to Pro	452	Resistant
		WGS	1	GAC→TAC	Asp to Tyr	435	Low-Level Resistant
		WGS	1	GAC→GTC	Asp to Val	435	Low-Level Resistant
		WGS	3	TCG→TTG	Ser to Leu	450	Resistant
INH	katG	WGS	5	AGC→ACC	Ser to Thr	315	Resistant
	inhA	SS	6	C(-15) T	–	–	Resistant
PZA	pncA	SS	1	GCC→ACC	Ala to Thr	134	Resistant
	pncA	SS	1	T(-11)C	–	–	Resistant
	ndh	SS	3	CGC→CAC	Arg to His	268	Resistant
	ndh	WGS	1	CGC→CAC	Arg to His	268	Resistant
INH and EMB and PZA	ndh	WGS	1	CGC→CAC	Arg to His	268	Resistant
INH and EMB	ndh	WGS	2	CGC→CAC	Arg to His	268	Resistant
EMB	embB	SS	1	ATG→ATA	Met to Ile	306	Resistant
		SS	1	ATG→CTG	Met to Leu	306	Resistant
		SS	1	CAG→CGG	Gln to Arg	497	Resistant
		WGS	2	GGC→AGC	Gly to Ser	406	Resistant
		WGS	1	ATG→GTG	Met to Val	306	Resistant
		SS	1	TTC→TTA	Phe to Leu	285	Sensitive
FQ	gyrA	WGS	2	GAC→GGC	Asp to Gly	94	Resistant
		WGS	1	GAC→TAC	Asp to Tyr	94	Resistant
STR	rpsL	WGS	2	AAG→AGG	Lys to Arg	43	Resistant

Ala = alanine; Arg = arginine; Asp = aspartate; EMB = ethambutol; FQ = fluoroquinolone; Gln = glutamine; Gly = glycine; His = histidine; Ile = isoleucine; INH = isoniazid; Leu = leucine; Lys = lysine; Met = methionine; MTB = Mycobacterium tuberculosis; Phe = phenylalanine; Pro = proline; PZA = pyrazinamide; RIF = rifampicin; Ser = serine; STR = streptomycin; SS = Sanger sequencing; Tyr = tyrosine; Thr = threonine; Val = valine; WGS = whole-genome sequencing.

DISCUSSION

In India in 2022, an estimated 2.94 million cases of TB were reported, of which 2.42 million were notified. A National Anti-Tuberculosis Drug Resistance Survey of India revealed high levels of MDR-TB, coupled with additional resistance to fluoroquinolones and second-line injectable drugs.²⁷ Moreover, TB mortality rates in India are high, with more than 493,000 HIV-negative TB cases resulting in death, whereas HIV-positive TB cases resulted in 11,000 deaths.²⁸ Our findings align with existing data showcasing regional variations in the prevalence of PZA resistance. Although the global burden of MDR-TB is estimated at 11.6%, MDR prevalence within previously treated cases can be significantly higher, as observed in East Africa (21%) and south India (11.6%).^29–31 In this study, a high PZA mono-resistance rate (17%) was observed, exceeding all other mono- and multidrug resistance rates. This observation is consistent with previous studies of Kurbatova et al., who reported a 42.8% prevalence of PZA monoresistance among MTB isolates, and a Ugandan study that reported phenotypic PZA resistance in 21% of TB patients.^32,33 Furthermore, global estimates suggest PZA resistance in one out of six TB cases (16.2%), with more than half of MDR-TB cases demonstrating PZA resistance.³⁴ These findings underscore the need for continued efforts to improve prevention, diagnosis, and treatment outcomes. The analysis of drug resistance mutations in MTB isolates using a combination of SS and WGS techniques in this study has provided valuable insights into the genetic basis of resistance to key anti-TB drugs. The lineage distribution of MTB in India exhibits a distinct pattern compared with the global landscape. Lineages 1 and 3 predominate within the country, demonstrating a regional skew, with lineage 1 concentrated in the southern, western, and eastern regions and lineage 3 prevalent in the central and northern parts.^35,36 This study also revealed a predominance of Lineage 1, which underscores the complexity of MTB diversity and its distinct prevalence in different geographical regions.

Monoresistance to RIF being rare was observed in only 1% of our isolates. All nine RIF-resistant isolates analyzed in this study exhibited mutations within the RRDR of the rpoB gene, with single nucleotide substitutions at codon 450 (S450L) being the predominant type. S450L was reported to be associated with high-level resistance to RIF, whereas D435V was associated with moderate-level resistance to RIF.³⁷ Molecular diagnostic techniques, such as GeneXpert MTB/RIF, and GenoType MTBDRplus, play a crucial role in rapidly identifying RIF resistance. These advanced methods significantly expedite the detection of RIF-resistant strains, aiding in more effective management of TB infections.^4,38,39 The primary cause of INH resistance is often attributed to mutations in the katG gene. Following katG mutations, other genes such as inhA, ahpC, kasA, ndh, iniABC, fadE, furA, Rv1592c, and Rv1772, contribute to INH resistance.¹¹ In addition, efflux genes and substitutions in genes, such as accD, fabD, and nat, highlight the genetic complexity associated with INH resistance.^11,40 In this study, we identified several mutations associated with INH resistance. Specifically, we detected the S315T mutation in the katG gene, the C(-15) T mutation in the promoter region of the inhA gene, and the R268H mutation in the ndh gene. However, for the remaining 30% of cases (n = 6), the exact cause of resistance remains unknown. Isolates that harbored R268H mutation in the ndh gene did not display any other mutations associated with INH resistance. One of the primary mechanisms associated with resistance to EMB involves mutations in the embB gene, which codes for the enzyme arabinosyltransferase involved in the biosynthesis of arabinogalactan, a key component of the mycobacterial cell wall.¹² Also in this study, mutations in specific regions of the embB gene, such as codons 306, 406, and 497, and R268H mutation in the ndh gene were found to be associated with EMB resistance. This R268H mutation has been reported to confer co-resistance to INH and ethionamide.⁴¹ Notably, in this study we also detected a F285L mutation in a phenotypically EMB-sensitive isolate.

Pyrazinamide is a key drug for TB treatment, but the emergence of PZA-resistant TB is a growing concern. Detection methods for PZA resistance involve both phenotypic and genotypic approaches. Phenotypic DST is limited because of drawbacks such as poor buffering of media and higher false resistance rates in the BACTEC MGIT system.^6,42 Mutations in the pncA gene are the primary cause of PZA resistance in MTB, leading to reduced pyrazinamidase activity and decreased susceptibility to PZA. pncA gene sequencing is considered a reliable method recommended by the WHO to detect PZA resistance.⁴³ In addition to pncA mutations, genetic determinants of PZA resistance include mutations in the rpsA gene (encoding ribosomal protein S1), clpC1 gene, and panD gene (involved in coenzyme A biosynthesis) as well as efflux pumps. In this study, we investigated the genetic mutations associated with PZA resistance in 33 PZA mono-drug–resistant isolates. Surprisingly, the majority of isolates (31 of 33, 94%) did not exhibit mutations in either the pncA or rpsA gene. Among the two isolates with detectable mutations, one exhibited a mutation at codon 134 (GCC→ACC, A134T), whereas the other displayed a T(-11) mutation in the promoter region of the pncA gene. The A134T mutation replaced alanine at the 134th position, which has been reported as an essential residue for active site formation, and the potential cause of resistance could be due to impaired hydrolysis of PZA to its active state.⁴⁴ Interestingly, WGS analysis of two PZA-resistant isolates did not identify any known mutations associated with PZA resistance in the examined genes. Instead, an R268H mutation in the ndh gene was detected. Further, SS of the ndh gene of the remaining isolates revealed this mutation in only three isolates, suggesting its limited occurrence within this cohort. The limited prevalence of the ndh gene mutation among the isolates (15%) suggests a potential contribution to PZA resistance in certain cases. However, it does not constitute the primary mechanism underlying resistance. The direct contribution of the R268H mutation to PZA resistance remains to be elucidated in future studies. It is also important to acknowledge the limitation of performing WGS on only two PZA-resistant isolates in this study. This restricts our understanding of the full spectrum of genetic determinants underlying PZA resistance. Further comprehensive genomic analysis of a larger set of isolates is crucial for understanding the mechanisms contributing to PZA resistance. However, WGS findings highlight the complexity of PZA resistance and the presence of alternative mechanisms beyond the well-established genes such as pncA, rpsA, and panD.

Inappropriate treatment of MDR-TB can lead to life-threatening consequences. There is an urgent need to enhance early diagnosis access and to ensure effective drug availability for all forms of TB, consistent with the WHO’s TB control strategies. The identification of mutations in the ndh gene in the PZA resistance isolates in our study suggests alternative resistance mechanisms. Current diagnostics rely heavily on pncA and rpsA mutations, potentially missing isolates with alternative resistance mechanisms. Broader diagnostic approaches are needed to address this. If alternative mechanisms are not considered, current PZA-based regimens may be ineffective against a significant subset of isolates, leading to treatment failure and potential spread of drug-resistant strains.

In conclusion, our study highlights the presence of drug-resistant MTB strains. The high prevalence of PZA resistance and the emergence of MDR-TB and polyresistant Hr-TB underscore the need for effective treatment strategies. Traditional genotypic methods, focused on specific genes, may overlook resistance-conferring mutations in less-explored genomic regions. The incorporation of WGS into diagnostics may prove advantageous in capturing a broader spectrum of genomic variations associated with drug resistance. The scope of WGS beneficiaries extends to those at high risk of MDR TB, encompassing close contacts and individuals with a history of treatment default. In addition, individuals who have not responded adequately to first- or second-line regimens are likely harboring resistance mutations that WGS can identify, allowing for adjustments in the treatment plan. Furthermore, WGS might contribute to patients with a past history of TB, whether relapse or reinfection, as they may have acquired new resistance mechanisms, which WGS can help elucidate, ensuring effective treatment and ultimately enhancing clinical outcomes. Its judicious use in resource-constrained settings might prove financially viable, offering a cost-effective solution. Understanding the mechanisms underlying drug resistance and improving detection methods are pivotal for effective tuberculosis management and mitigating disease transmission.