Journal Article > ResearchFull Text
Int J Tuberc Lung Dis. 2023 January 1; Volume 27 (Issue 1); 41-48.; DOI:10.5588/ijtld.22.0138
Mansoor H, Hirani N, Chavan VV, Das M, Sharma J, et al.
Int J Tuberc Lung Dis. 2023 January 1; Volume 27 (Issue 1); 41-48.; DOI:10.5588/ijtld.22.0138
BACKGROUND
In high TB burden countries, access to drug susceptibility testing is a major bottleneck. Targeted next-generation sequencing (tNGS) is a promising technology for rapid resistance detection. This study assessed the role of tNGS for the diagnosis of drug-resistant TB (DR-TB).
METHODS
A total of 161 samples from bacteriologically confirmed TB cases were subjected to tNGS using the Deeplex® Myc-TB kit and sequenced using the MiSeq platform. These samples were also processed for conventional phenotypic DST (pDST) using 13 drugs on Mycobacteria Growth Indicator Tube and line-probe assays (MTBDR plus and MTBDRsl).
RESULTS
There were 146 DR-TB and 15 drug-susceptible TB (DS-TB) samples. About 70% of patients with DR-TB had no previous TB treatment history. Overall, 88.2% had rifampicin-resistant/multidrug-resistant TB (RR/MDR-TB), 58.5% pre-extensively drug-resistant TB (pre-XDR-TB) and 9.2% had XDR-TB as defined by the WHO (2020). Around 8% (n=13) of samples were non-culturable; however, identified 8 were resistant to first and second-line drugs using tNGS. Resistance frequency was similar across methods, with discordance in drugs less reliable using pDST or with limited mutational representation within databases. Sensitivities were aligned with literature reports for most drugs. We observed 10% heteroresistance, while 75% of strains were of Lineages 2 and 3.
CONCLUSIONS
Programme data supported tNGS in the diagnosis of DR-TB for early treatment using individualised regimens.
In high TB burden countries, access to drug susceptibility testing is a major bottleneck. Targeted next-generation sequencing (tNGS) is a promising technology for rapid resistance detection. This study assessed the role of tNGS for the diagnosis of drug-resistant TB (DR-TB).
METHODS
A total of 161 samples from bacteriologically confirmed TB cases were subjected to tNGS using the Deeplex® Myc-TB kit and sequenced using the MiSeq platform. These samples were also processed for conventional phenotypic DST (pDST) using 13 drugs on Mycobacteria Growth Indicator Tube and line-probe assays (MTBDR plus and MTBDRsl).
RESULTS
There were 146 DR-TB and 15 drug-susceptible TB (DS-TB) samples. About 70% of patients with DR-TB had no previous TB treatment history. Overall, 88.2% had rifampicin-resistant/multidrug-resistant TB (RR/MDR-TB), 58.5% pre-extensively drug-resistant TB (pre-XDR-TB) and 9.2% had XDR-TB as defined by the WHO (2020). Around 8% (n=13) of samples were non-culturable; however, identified 8 were resistant to first and second-line drugs using tNGS. Resistance frequency was similar across methods, with discordance in drugs less reliable using pDST or with limited mutational representation within databases. Sensitivities were aligned with literature reports for most drugs. We observed 10% heteroresistance, while 75% of strains were of Lineages 2 and 3.
CONCLUSIONS
Programme data supported tNGS in the diagnosis of DR-TB for early treatment using individualised regimens.
Journal Article > ResearchFull Text
Public Health Action. 2023 June 21; Volume 13 (Issue 2); 43-49.; DOI:10.5588/pha.22.0041
Iyer AS, Ndlovu Z, Sharma J, Mansoor H, Bharati M, et al.
Public Health Action. 2023 June 21; Volume 13 (Issue 2); 43-49.; DOI:10.5588/pha.22.0041
English
Français
BACKGROUND
Phenotypic drug susceptibility testing (pDST) for Mycobacterium tuberculosis can take up to 8 weeks, while conventional molecular tests identify a limited set of resistance mutations. Targeted next-generation sequencing (tNGS) offers rapid results for predicting comprehensive drug resistance, and this study sought to explore its operational feasibility within a public health laboratory in Mumbai, India.
METHODS
Pulmonary samples from consenting patients testing Xpert MTB-positive were tested for drug resistance by conventional methods and using tNGS. Laboratory operational and logistical implementation experiences from study team members are shared below.
RESULTS
Of the total number of patients tested, 70% (113/161) had no history of previous TB or treatment; however, 88.2% (n = 142) had rifampicin-resistant/multidrug-resistant TB (RR/MDR-TB). There was a high concordance between resistance predictions of tNGS and pDST for most drugs, with tNGS more accurately identifying resistance overall. tNGS was integrated and adapted into the laboratory workflow; however, batching samples caused significantly longer result turnaround time, fastest at 24 days. Manual DNA extraction caused inefficiencies; thus protocol optimisations were performed. Technical expertise was required for analysis of uncharacterised mutations and interpretation of report templates. tNGS cost per sample was US$230, while for pDST this was US$119.
CONCLUSIONS
Implementation of tNGS is feasible in reference laboratories. It can rapidly identify drug resistance and should be considered as a potential alternative to pDST.
Phenotypic drug susceptibility testing (pDST) for Mycobacterium tuberculosis can take up to 8 weeks, while conventional molecular tests identify a limited set of resistance mutations. Targeted next-generation sequencing (tNGS) offers rapid results for predicting comprehensive drug resistance, and this study sought to explore its operational feasibility within a public health laboratory in Mumbai, India.
METHODS
Pulmonary samples from consenting patients testing Xpert MTB-positive were tested for drug resistance by conventional methods and using tNGS. Laboratory operational and logistical implementation experiences from study team members are shared below.
RESULTS
Of the total number of patients tested, 70% (113/161) had no history of previous TB or treatment; however, 88.2% (n = 142) had rifampicin-resistant/multidrug-resistant TB (RR/MDR-TB). There was a high concordance between resistance predictions of tNGS and pDST for most drugs, with tNGS more accurately identifying resistance overall. tNGS was integrated and adapted into the laboratory workflow; however, batching samples caused significantly longer result turnaround time, fastest at 24 days. Manual DNA extraction caused inefficiencies; thus protocol optimisations were performed. Technical expertise was required for analysis of uncharacterised mutations and interpretation of report templates. tNGS cost per sample was US$230, while for pDST this was US$119.
CONCLUSIONS
Implementation of tNGS is feasible in reference laboratories. It can rapidly identify drug resistance and should be considered as a potential alternative to pDST.