Whole genome sequencing for drug resistance determination in Mycobacterium tuberculosis

South Africa remains challenged with a high tuberculosis burden accompanied by an increase in drug resistant cases. We assessed the use of the Illumina MiSeq, a next-generation sequencing platform for whole genome sequencing, followed by bioinformatic analysis using a commercial software package to determine resistance to selected drugs used for Mycobacterium tuberculosis treatment in our setting. Whole genome sequencing shows potential as a diagnostic platform for the detection of drug resistance in Mycobacterium tuberculosis with the provision of information for several drugs simultaneously.Funding was provided by the National Institute for Communicable Diseases, a division of the National Health Laboratory Service, South Africa.The National Institute for Communicable Diseases, a division of the National Health Laboratory Service, South Africahttp://www.ajlmonline.orgam2020Medical Microbiolog

Whole genome sequencing for drug resistance determination in Mycobacterium tuberculosis

South Africa remains challenged with a high tuberculosis burden accompanied by an increase in drug resistant cases. We assessed the use of the Illumina MiSeq, a next-generation sequencing platform for whole genome sequencing, followed by bioinformatic analysis using a commercial software package to determine resistance to selected drugs used for Mycobacterium tuberculosis treatment in our setting. Whole genome sequencing shows potential as a diagnostic platform for the detection of drug resistance in Mycobacterium tuberculosis with the provision of information for several drugs simultaneously

Laboratory evaluation of a specimen transport medium for downstream molecular processing of sputum samples to detect Mycobacterium tuberculosis

BACKGROUND : Modern molecular-based approaches for the detection of Mycobacterium tuberculosis in sputum samples promise quicker and more accurate detection of cases. However, processing sputum samples at central diagnostic facilities provides a diagnostic approach, but requires a safe and efficient system that is not affected by transport delays and ambient temperature to be feasible. We evaluated the technical properties of PrimeStore®-Molecular Transport Medium(PS-MTM) for its ability to inactivate mycobacteria, ensuring stability of DNA over time at ambient temperatures and to assess the compatibility of the transport medium with DNA extraction systems. METHODS : Assessment of the transport medium for application of sputum samples processed for the detection of M. tuberculosis included the inactivation of M. tuberculosis in spiked sputum samples, compatibility of the medium with three commercial nucleic extraction systems and stability of DNA in the medium at ambient temperature over 28 days. We further performed a clinical laboratory evaluation on 256 sputum specimens sent for tuberculosis investigation. RESULTS : Complete inactivation ofM. tuberculosis occurredwithin 30 min of exposure at a ratio of 1:3 for sputumto PS-MTM. Sputum specimen in PS-MTMshowed very good compatibility with automated bead-based extraction systems, producing high DNA output (estimated lower limits of detection: ~170 CFU/ml). Furthermore, PS-MTM samples remained stable over 28 days at ambient temperature displaying no significant change over time in Ctvalues (b5% on a mean starting value of 22.47). Of the 256 clinical sputumspecimens, 10.2%were culture positive and 11.0% were positive by real-time PCR of PS-MTM samples. CONCLUSIONS : Collecting and transporting sputum from TB suspects in PS-MTM offer safe transport at ambient temperature, DNA stability for extended periods without cooling and specimens directly suitable for molecular testing. This novel approach may support introduction and further scale-up of molecular diagnostics for TB in resource-limited settings.http://www.elsevier.com/locate/jmicmeth2016-10-31hb201

A subset of circulating blood mycobacteria-specific CD4 T cells can predict the time to Mycobacterium tuberculosis sputum culture conversion

We investigated 18 HIV-negative patients with MDR-TB for M. tuberculosis (Mtb)- and PPD-specific CD4 T cell responses and followed them over 6 months of drug therapy. Twelve of these patients were sputum culture (SC) positive and six patients were SC negative upon enrollment. Our aim was to identify a subset of mycobacteria-specific CD4 T cells that would predict time to culture conversion. The total frequency of mycobacteria-specific CD4 T cells at baseline could not distinguish patients showing positive or negative SC. However, a greater proportion of late-differentiated (LD) Mtb- and PPD-specific memory CD4 T cells was found in SC positive patients than in those who were SC negative (p = 0.004 and p = 0.0012, respectively). Similarly, a higher co-expression of HLA-DR + Ki67 + on Mtb- and PPD-specific CD4 T cells could also discriminate between sputum SC positive versus SC negative (p = 0.004 and p = 0.001, respectively). Receiver operating characteristic (ROC) analysis revealed that baseline levels of Ki67 + HLA-DR + Mtb- and PPD-specific CD4 T cells were predictive of the time to sputum culture conversion, with area-under-the-curve of 0.8 (p = 0.027). Upon treatment, there was a significant decline of these Ki67 + HLA-DR + T cell populations in the first 2 months, with a progressive increase in mycobacteria-specific polyfunctional IFNγ + IL2 + TNFα + CD4 T cells over 6 months. Thus, a subset of activated and proliferating mycobacterial-specific CD4 T cells (Ki67 + HLA-DR + ) may provide a valuable marker in peripheral blood that predicts time to sputum culture conversion in TB patients at the start of treatment

Determining the risk-factors for molecular clustering of drug-resistant tuberculosis in South Africa

Abstract Background Drug-resistant tuberculosis (DR-TB) epidemic is driven mainly by the effect of ongoing transmission. In high-burden settings such as South Africa (SA), considerable demographic and geographic heterogeneity in DR-TB transmission exists. Thus, a better understanding of risk-factors for clustering can help to prioritise resources to specifically targeted high-risk groups as well as areas that contribute disproportionately to transmission. Methods The study analyzed potential risk-factors for recent transmission in SA, using data collected from a sentinel molecular surveillance of DR-TB, by comparing demographic, clinical and epidemiologic characteristics with clustering and cluster sizes. A genotypic cluster was defined as two or more patients having identical patterns by the two genotyping methods used. Clustering was used as a proxy for recent transmission. Descriptive statistics and multinomial logistic regression were used. Result The study identified 277 clusters, with cluster size ranging between 2 and 259 cases. The majority (81.6%) of the clusters were small (2–5 cases) with few large (11–25 cases) and very large (≥ 26 cases) clusters identified mainly in Western Cape (WC), Eastern Cape (EC) and Mpumalanga (MP). In a multivariable model, patients in clusters including 11–25 and ≥ 26 individuals were more likely to be infected by Beijing family, have XDR-TB, living in Nelson Mandela Metro in EC or Umgungunglovo in Kwa-Zulu Natal (KZN) provinces, and having history of imprisonment. Individuals belonging in a small genotypic cluster were more likely to infected with Rifampicin resistant TB (RR-TB) and more likely to reside in Frances Baard in Northern Cape (NC). Conclusion Sociodemographic, clinical and bacterial risk-factors influenced rate of Mycobacterium tuberculosis (M. tuberculosis) genotypic clustering. Hence, high-risk groups and hotspot areas for clustering in EC, WC, KZN and MP should be prioritized for targeted intervention to prevent ongoing DR-TB transmission

Distribution and clonality of drug-resistant tuberculosis in South Africa

BACKGROUND: Studies have shown that drug-resistant tuberculosis (DR-TB) in South Africa (SA) is clonal and is caused mostly by transmission. Identifying transmission chains is important in controlling DR-TB. This study reports on the sentinel molecular surveillance data of Rifampicin-Resistant (RR) TB in SA, aiming to describe the RR-TB strain population and the estimated transmission of RR-TB cases. METHOD: RR-TB isolates collected between 2014 and 2018 from eight provinces were genotyped using combination of spoligotyping and 24-loci mycobacterial interspersed repetitive-units-variable-number tandem repeats (MIRU-VNTR) typing. RESULTS: Of the 3007 isolates genotyped, 301 clusters were identified. Cluster size ranged between 2 and 270 cases. Most of the clusters (247/301; 82.0%) were small in size (< 5 cases), 12.0% (37/301) were medium sized (5–10 cases), 3.3% (10/301) were large (11–25 cases) and 2.3% (7/301) were very large with 26–270 cases. The Beijing genotype was responsible for majority of RR-TB cases in Western and Eastern Cape, while the East-African-Indian-Somalian (EAI1_SOM) genotype accounted for a third of RR-TB cases in Mpumalanga. The overall proportion of RR-TB cases estimated to be due to transmission was 42%, with the highest transmission-rate in Western Cape (64%) and the lowest in Northern Cape (9%). CONCLUSION: Large clusters contribute to the burden of RR-TB in specific geographic areas such as Western Cape, Eastern Cape and Mpumalanga, highlighting the need for community-wide interventions. Most of the clusters identified in the study were small, suggesting close contact transmission events, emphasizing the importance of contact investigations and infection control as the primary interventions in SA.The President’s Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC), CTB and NICD.http://www.biomedcentral.com/bmcmicrobiolpm2021Medical Microbiolog

A subset of circulating blood mycobacteria-specific CD4 T cells can predict the time to Mycobacterium tuberculosis sputum culture conversion.

We investigated 18 HIV-negative patients with MDR-TB for M. tuberculosis (Mtb)- and PPD-specific CD4 T cell responses and followed them over 6 months of drug therapy. Twelve of these patients were sputum culture (SC) positive and six patients were SC negative upon enrollment. Our aim was to identify a subset of mycobacteria-specific CD4 T cells that would predict time to culture conversion. The total frequency of mycobacteria-specific CD4 T cells at baseline could not distinguish patients showing positive or negative SC. However, a greater proportion of late-differentiated (LD) Mtb- and PPD-specific memory CD4 T cells was found in SC positive patients than in those who were SC negative (p = 0.004 and p = 0.0012, respectively). Similarly, a higher co-expression of HLA-DR+ Ki67+ on Mtb- and PPD-specific CD4 T cells could also discriminate between sputum SC positive versus SC negative (p = 0.004 and p = 0.001, respectively). Receiver operating characteristic (ROC) analysis revealed that baseline levels of Ki67+ HLA-DR+ Mtb- and PPD-specific CD4 T cells were predictive of the time to sputum culture conversion, with area-under-the-curve of 0.8 (p = 0.027). Upon treatment, there was a significant decline of these Ki67+ HLA-DR+ T cell populations in the first 2 months, with a progressive increase in mycobacteria-specific polyfunctional IFNγ+ IL2+ TNFα+ CD4 T cells over 6 months. Thus, a subset of activated and proliferating mycobacterial-specific CD4 T cells (Ki67+ HLA-DR+) may provide a valuable marker in peripheral blood that predicts time to sputum culture conversion in TB patients at the start of treatment

Changes in the proportion of antigen-specific CD4 T cells co-expressing HLA-DR and Ki67 over time of chemotherapy in individuals with positive SC at baseline.

<p>(A) Representative flow cytometry dot-plots showing the level of Ki-67 and HLA-DR co-expression within PPD-specific CD4 T cells at baseline (BL), 2, 4 and 6 months (M) of treatment. The numbers in the quadrants represent the proportion of antigen-specific CD4 T cells co-expressing Ki-67 and HLA-DR. (B) Proportion of activated (Ki-67⁺HLA-DR⁺) cells within Mtb, PPD and mitogen responsive CD4 T cells over time (months). The statistical differences were assessed using Wilcoxon matched pairs test.</p

ROC curve analysis of mycobacteria-specific Ki-67⁺HLA-DR⁺ CD4 T cells with time to sputum culture conversion.

<p>Receiver Operating Characteristic curve for the proportion of mycobacteria-specific Ki-67⁺HLA-DR⁺ CD4 T cells at baseline with the time to sputum clearance. The area under the curve (AUC), p-value and 95% confidence interval (c.i.) are shown on the graph. The dotted line represents an AUC of 0.5, which would depict a random test.</p

Microbiological characteristics of patients enrolled into the study showing pre-admission and on-admission (visit 0) AFB smear, time between smears and time to first sputum culture negative, culture conversion and which antigen specificities were detectable in the ICS assay (% responders).

%<p>Y =  yes; N =  no.</p>§<p>MDR Classification: 2, New MDR after TB treatment failure; 4, MDR after TB default; 6, Primary MDR; 9, MDR 2nd episode.</p>1<p>Acid Fast Bacilli (intensity score: +).</p>2<p>Mitogen (QuantiFERON-TB Gold).</p><p>*culture conversion calculated as the interval between the date of admission/start of MDR regimen to date of the first of 2 consecutive negative cultures at least 30 days apart.</p>#<p>based on first negative sputum culture, no follow up sputum culture results recorded.</p>a<p>RIF/INH/EMB/PZA (Reg 1).</p>b<p>Reg 1 plus Streptomycin.</p>c<p>Reg 1 plus Ofloxacin/Ethionamide/Streptomycin.</p>d<p>PAS/Terizodone/High dose INH/Kanamycin/Clarithromycin.</p