Countrywide implementation of whole genome sequencing: an opportunity to improve tuberculosis management, surveillance and contact tracing in low incidence countries

Performance evaluation of core genome multilocus sequence typing for genotyping of Mycobacterium tuberculosis strains in China: based on multicenter, population-based collection

PURPOSE

To evaluate the performance of core genome multilocus sequence typing (cgMLST) for genotyping Mycobacterium tuberculosis (M.tuberculosis) Strains in regions where the lineage 2 strains predominate.

METHODS

We compared clustering by whole-genome SNP typing with cgMLST clustering in the analysis of WGS data of 6240 strains from five regions of China. Using both the receiver operating characteristic (ROC) curve and epidemiological investigation to determine the optimal threshold for defining genomic clustering by cgMLST. The performance of cgMLST was evaluated by quantifying the sensitivity, specificity and concordance of clustering between two methods. Logistic regression was used to gauge the impact of strain genetic diversity and lineage on cgMLST clustering.

RESULTS

The optimal threshold for cgMLST to define genomic clustering was determined to be ≤ 10 allelic differences between strains. The overall sensitivity and specificity of cgMLST averaged 99.6% and 96.3%, respectively; the concordance of clustering between two methods averaged 97.1%. Concordance was significantly correlated with strain genetic diversity and was 3.99 times (95% CI, 2.94-5.42) higher in regions with high genetic diversity (π > 1.55 × 10-4) compared to regions with low genetic diversity. The difference missed statistical significance, while concordance for lineage 2 strains (96.8%) was less than that for lineage 4 strains (98.3%). CONCLUSION : cgMLST showed a discriminatory power comparable to whole-genome SNP typing and could be used to genotype clinical M.tuberculosis strains in different regions of China. The discriminative power of cgMLST was significantly correlated with strain genetic diversity and was slightly lower with strains from regions with low genetic diversity.

Single-tube protocol for culture-independent spoligotyping of Mycobacterium tuberculosis based on MeltArray

IMPORTANCE

Spacer oligonucleotide typing (spoligotyping), the first-line genotyping assay for Mycobacterium tuberculosis (MTB), plays a fundamental role in the investigation of its epidemiology and evolution. In this study, we established a single-tube spoligotyping assay using MeltArray, a highly multiplex polymerase chain reaction (PCR) approach that runs on a real-time PCR thermocycler. The MeltArray protocol included an internal positive control, gyrB, to indicate the abundance of MTB via the quantification cycle and 43 spacers to identify the spoligotype via melting curve analysis. The entire protocol was completed in a single step within 2.5 hours. The lowest detectable copy number for the tested strains was 20 copies/reaction and thus sufficient for analyzing both culture and sputum samples. We conclude that MeltArray-based spoligotyping could be used immediately in low- and middle-income countries with a high tuberculosis burden, given its easy access, improved throughput, and potential applicability to clinical samples.

Exploring programmatic indicators of tuberculosis control that incorporate routine Mycobacterium tuberculosis sequencing in low incidence settings: a comprehensive (2017-2021) patient cohort analysis

Background

Routine whole genome sequencing of Mycobacterium tuberculosis has been implemented with increasing frequency. However, its value for tuberculosis (TB) control programs beyond individual case management and enhanced drug resistance detection has not yet been explored.

Methods

We analysed routine sequencing data of culture-confirmed TB cases notified between 1st January 2017 and 31st December 2021 in New South Wales (NSW), Australia. Genomic surveillance included evidence of local TB transmission, defined by single nucleotide polymorphism (SNP) clustering over a variable (0-25) SNP threshold, and drug resistance conferring mutations.

Findings

M. tuberculosis sequences from 1831 patients were examined, representing 64.8% of all notified TB cases and 96.2% of culture-confirmed cases. Applying a traditional 5-SNP cluster threshold identified 62 transmission clusters with 183 clustered cases; 101/183 (55.2%) had 0 SNP differences. Cluster assessment over a 5-year period, using a 5-SNP threshold, provided a comprehensive overview of likely recent transmission within NSW, Australia, as an indicator of local TB control. Genotypic drug susceptibility testing (DST) was highly concordant with phenotypic DST and provided a 6.8% increase in antimycobacterial resistance detection. Importantly, it detected mutations missed by routine molecular tests. Lineage 2 strains were more likely to be drug resistant (p < 0.0001) and locally transmitted if drug resistant (p < 0.0001).

Interpretation

Performing routine prospective WGS in a low incidence country like Australia, provides genomically informed programmatic indicators of local TB control. A rolling 5-year cluster assessment reflects epidemic containment and progress towards 'zero TB transmission'. Genomic DST also provides valuable information for clinical care and drug resistance surveillance.

Funding

NHMRC Centre for Research Excellence in Tuberculosis (www.tbcre.org.au) and NSW Health Prevention Research Support Program.

Implementation of national whole-genome sequencing of Mycobacterium tuberculosis, National Public Health Laboratory, Singapore, 2019-2022

The National Tuberculosis Programme (NTBP) monitors the occurrence and spread of tuberculosis (TB) and multidrug-resistant TB (MDR-TB) in Singapore. Since 2020, whole-genome sequencing (WGS) of Mycobacterium tuberculosis isolates has been performed at the National Public Health Laboratory (NPHL) for genomic surveillance, replacing spoligotyping and mycobacterial interspersed repetitive unit-variable number tandem repeats analysis (MIRU-VNTR). Four thousand three hundred and seven samples were sequenced from 2014 to January 2023, initially as research projects and later developed into a comprehensive public health surveillance programme. Currently, all newly diagnosed culture-positive cases of TB in Singapore are prospectively sent for WGS, which is used to perform lineage classification, predict drug resistance profiles and infer genetic relationships between TB isolates. This paper describes NPHL's operational and technical experiences with implementing the WGS service in an urban TB-endemic setting, focusing on cluster detection and genomic drug susceptibility testing (DST). Cluster detection: WGS has been used to guide contact tracing by detecting clusters and discovering unknown transmission networks. Examples have been clusters in a daycare centre, housing apartment blocks and a horse-racing betting centre. Genomic DST: genomic DST prediction (gDST) identifies mutations in core genes known to be associated with TB drug resistance catalogued in the TBProfiler drug resistance mutation database. Mutations are reported with confidence scores according to a standardized approach referencing NPHL's internal gDST confidence database, which is adapted from the World Health Organization (WHO) TB drug mutation catalogue. Phenotypic-genomic concordance was observed for the first-line drugs ranging from 2959/2998 (98.7 %) (ethambutol) to 2983/2996 (99.6 %) (rifampicin). Aspects of internal database management, reporting standards and caveats in results interpretation are discussed.

Mycobacterium tuberculosis Intra-Host Evolution Among Drug-Resistant Tuberculosis Patients Failing Treatment

Background

Understanding Mycobacterium tuberculosis (Mtb) intra-host evolution of drug resistance is important for successful drug-resistant tuberculosis (DR-TB) treatment and control strategies. This study aimed to characterise the acquisition of genetic mutations and low-frequency variants associated with treatment-emergent Mtb drug resistance in longitudinally profiled clinical isolates from patients who experienced DR-TB treatment failure.

Patients and Methods

We performed deep Whole Genome Sequencing on 23 clinical isolates obtained longitudinally across nine timepoints from five patients who experienced DR-TB treatment failure enrolled in the CAPRISA 020 InDEX study. The minimum inhibitory concentrations (MICs) were established on the BACTEC™ MGIT 960™ instrument on 15/23 longitudinal clinical isolates for eight anti-TB drugs (rifampicin, isoniazid, ethambutol, levofloxacin, moxifloxacin, linezolid, clofazimine, bedaquiline).

Results

In total, 22 resistance associated mutations/variants were detected. We observed four treatment-emergent mutations in two out of the five patients. Emerging resistance to the fluoroquinolones was associated with 16- and 64-fold elevated levofloxacin (2-8 mg/L) and moxifloxacin (1-2 mg/L) MICs, respectively, resulting from the D94G/N and A90V variants in the gyrA gene. We identified two novel mutations associated with elevated bedaquiline MICs (>66-fold): an emerging frameshift variant (D165) on the Rv0678 gene and R409Q variant on the Rv1979c gene present from baseline.

Conclusion

Genotypic and phenotypic resistance to the fluoroquinolones and bedaquiline was acquired in two out of five patients who experienced DR-TB treatment failure. Deep sequencing of multiple longitudinal clinical isolates for resistance-associated mutations coupled with phenotypic MIC testing confirmed intra-host Mtb evolution.

TBProfiler for automated calling of the association with drug resistance of variants in Mycobacterium tuberculosis

Following a huge global effort, the first World Health Organization (WHO)-endorsed catalogue of 17,356 variants in the Mycobacterium tuberculosis complex along with their classification as associated with resistance (interim), not associated with resistance (interim) or uncertain significance was made public In June 2021. This marks a critical step towards the application of next generation sequencing (NGS) data for clinical care. Unfortunately, the variant format used makes it difficult to look up variants when NGS data is generated by other bioinformatics pipelines. Furthermore, the large number of variants of uncertain significance in the catalogue hamper its useability in clinical practice. We successfully converted 98.3% of variants from the WHO catalogue format to the standardized HGVS format. We also created TBProfiler version 4.4.0 to automate the calling of all variants located in the tier 1 and 2 candidate resistance genes along with their classification when listed in the WHO catalogue. Using a representative sample of 339 clinical isolates from South Africa containing 691 variants in a tier 1 or 2 gene, TBProfiler classified 105 (15%) variants as conferring resistance, 72 (10%) as not conferring resistance and 514 (74%) as unclassified, with an average of 29 unclassified variants per isolate. Using a second cohort of 56 clinical isolates from a TB outbreak in Spain containing 21 variants in the tier 1 and 2 genes, TBProfiler classified 13 (61.9%) as unclassified, 7 (33.3%) as not conferring resistance, and a single variant (4.8%) classified as conferring resistance. Continued global efforts using standardized methods for genotyping, phenotyping and bioinformatic analyses will be essential to ensure that knowledge on genomic variants translates into improved patient care.

Evaluating the clinical impact of routine whole genome sequencing in tuberculosis treatment decisions and the issue of isoniazid mono-resistance

Background

The UK has implemented routine use of whole genome sequencing (WGS) in TB diagnostics. The WHO recommends addition of a fluoroquinolone for isoniazid mono-resistance, so early detection may be of use. The aim of this study was to describe the clinical utility and impact of WGS on treatment decisions for TB in a low incidence high resource clinical setting. The clinical turnaround time (TAT) for WGS was analysed in comparison to TB PCR using Xpert MTB/RIF (Cepheid, Sunnyvale, CA) results where available and subsequent phenotypic drug susceptibility testing (DST) when required.

Methods

This was a retrospective analysis of TB cases from January 2018 to March 2019 in London. Susceptibility and TAT by WGS, phenotypic DST, TB PCR using Xpert MTB/RIF were correlated to drug changes in order to describe the utility of WGS on treatment decisions on isoniazid mono-resistance in a low incidence high resource setting.

Results

189 TB cases were identified; median age 44 years (IQR 28–60), m:f ratio 112:77, 7 with HIV and 6 with previous TB. 80/189 cases had a positive culture and WGS result. 50/80 were fully sensitive to 1st line treatment on WGS, and the rest required additional DST. 20/80 cases required drug changes; 12 were defined by WGS: 8 cases had isoniazid mono-resistance, 2 had MDR-TB, 1 had isoniazid and pyrazinamide resistance and 1 had ethambutol resistance. The median TAT for positive culture was 16 days (IQR 12.5–20.5); for WGS was 35 days (IQR 29.5–38.75) and for subsequent DST was 86 days (IQR 69.5–96.75), resulting in non-WHO regimens for a median of 50.5 days (IQR 28.0–65.0). 9/12 has TB PCRs (Xpert MTB/RIF), with a median TAT of 1 day.

Conclusion

WGS clearly has a substantial role in our routine UK clinical settings with faster turnaround times in comparison to phenotypic DST. However, the majority of treatment changes defined by WGS were related to isoniazid resistance and given the 1 month TAT for WGS, it would be preferable to identify isoniazid resistance more quickly. Therefore if resources allow, diagnostic pathways should be optimised by parallel use of WGS and new molecular tests to rapidly identify isoniazid resistance in addition to rifampicin resistance and to minimise delays in starting WHO isoniazid resistance treatment.

Application of Next Generation Sequencing for Diagnosis and Clinical Management of Drug-Resistant Tuberculosis: Updates on Recent Developments in the Field

The World Health Organization’s End TB Strategy prioritizes universal access to an early diagnosis and comprehensive drug susceptibility testing (DST) for all individuals with tuberculosis (TB) as a key component of integrated, patient-centered TB care. Next generation whole genome sequencing (WGS) and its associated technology has demonstrated exceptional potential for reliable and comprehensive resistance prediction for Mycobacterium tuberculosis isolates, allowing for accurate clinical decisions. This review presents a descriptive analysis of research describing the potential of WGS to accelerate delivery of individualized care, recent advances in sputum-based WGS technology and the role of targeted sequencing for resistance detection. We provide an update on recent research describing the mechanisms of resistance to new and repurposed drugs and the dynamics of mixed infections and its potential implication on TB diagnosis and treatment. Whilst the studies reviewed here have greatly improved our understanding of recent advances in this arena, it highlights significant challenges that remain. The wide-spread introduction of new drugs in the absence of standardized DST has led to rapid emergence of drug resistance. This review highlights apparent gaps in our knowledge of the mechanisms contributing to resistance for these new drugs and challenges that limit the clinical utility of next generation sequencing techniques. It is recommended that a combination of genotypic and phenotypic techniques is warranted to monitor treatment response, curb emerging resistance and further dissemination of drug resistance.

Exploiting genomics to mitigate the public health impact of antimicrobial resistance

Antimicrobial resistance (AMR) is a major global public health threat, which has been largely driven by the excessive use of antimicrobials. Control measures are urgently needed to slow the trajectory of AMR but are hampered by an incomplete understanding of the interplay between pathogens, AMR encoding genes, and mobile genetic elements at a microbial level. These factors, combined with the human, animal, and environmental interactions that underlie AMR dissemination at a population level, make for a highly complex landscape. Whole-genome sequencing (WGS) and, more recently, metagenomic analyses have greatly enhanced our understanding of these processes, and these approaches are informing mitigation strategies for how we better understand and control AMR. This review explores how WGS techniques have advanced global, national, and local AMR surveillance, and how this improved understanding is being applied to inform solutions, such as novel diagnostic methods that allow antimicrobial use to be optimised and vaccination strategies for better controlling AMR. We highlight some future opportunities for AMR control informed by genomic sequencing, along with the remaining challenges that must be overcome to fully realise the potential of WGS approaches for international AMR control.

GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning

BACKGROUND

Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens.

RESULTS

We present Translational Genomics platform for Tuberculosis (GenTB), a free and open web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tuberculosis drugs, respectively. We benchmark GenTB's predictive performance along with leading TB resistance prediction tools (Mykrobe and TB-Profiler) using a ground truth dataset of 20,408 isolates with laboratory-based drug susceptibility data. All four tools reliably predicted resistance to first-line tuberculosis drugs but had varying performance for second-line drugs. The mean sensitivities for GenTB-RF and GenTB-WDNN across the nine shared drugs were 77.6% (95% CI 76.6-78.5%) and 75.4% (95% CI 74.5-76.4%), respectively, and marginally higher than the sensitivities of TB-Profiler at 74.4% (95% CI 73.4-75.3%) and Mykrobe at 71.9% (95% CI 70.9-72.9%). The higher sensitivities were at an expense of ≤ 1.5% lower specificity: Mykrobe 97.6% (95% CI 97.5-97.7%), TB-Profiler 96.9% (95% CI 96.7 to 97.0%), GenTB-WDNN 96.2% (95% CI 96.0 to 96.4%), and GenTB-RF 96.1% (95% CI 96.0 to 96.3%). Averaged across the four tools, genotypic resistance sensitivity was 11% and 9% lower for isoniazid and rifampicin respectively, on isolates sequenced at low depth (< 10× across 95% of the genome) emphasizing the need to quality control input sequence data before prediction. We discuss differences between tools in reporting results to the user including variants underlying the resistance calls and any novel or indeterminate variants CONCLUSIONS: GenTB is an easy-to-use online tool to rapidly and accurately predict resistance to anti-tuberculosis drugs. GenTB can be accessed online at https://gentb.hms.harvard.edu , and the source code is available at https://github.com/farhat-lab/gentb-site .

Value of routine whole genome sequencing for Mycobacterium tuberculosis drug resistance detection

Routine whole genome sequencing (WGS) of pathogens is becoming more feasible as sequencing costs decrease and access to benchtop sequencing equipment and bioinformatics pipelines increases. This study examined the added value gained from implementing routine WGS of all Mycobacterium tuberculosis isolates in New South Wales, Australia. Drug resistance markers inferred from WGS data were compared to commercial genotypic drug susceptibility testing (DST) assays and conventional phenotypic DST in all isolates sequenced between 2016 and 2019. Of the 1107 clinical M. tuberculosis isolates sequenced, 29 (2.6%) were multi-drug resistant (MDR); most belonged to Beijing (336; 30.4%) or East-African Indian (332; 30%) lineages. Compared with conventional phenotypic DST, WGS identified an additional 1% of isolates which were likely drug resistant, explained by mutations previously associated with treatment failure and mixed bacterial populations. However, WGS provided a 20% increase in drug resistance detection in comparison with commercial genotypic assays by identifying mutations outside of the classic resistance determining regions in rpoB, inhA, katG, pncA and embB genes. Gains in drug resistance detection were significant (p = 0.0137, paired t-test), but varied substantially for different phylogenetic lineages. In low incidence settings, routine WGS of M. tuberculosis provides better guidance for person-centered management of drug resistant tuberculosis than commercial genotypic assays.

Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark

BACKGROUND

Pathogen genomics have become increasingly important in infectious disease epidemiology and public health. The Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) guidelines were developed to outline a minimum set of criteria that should be reported in genomic epidemiology studies to facilitate assessment of study quality. We evaluate such reporting practices, using tuberculosis as an example.

METHODS

For this systematic review, we initially searched MEDLINE, Embase Classic, and Embase on May 3, 2017, using the search terms "tuberculosis" and "genom* sequencing". We updated this initial search on April 23, 2019, and also included a search of bioRxiv at this time. We included studies in English, French, or Spanish that recruited patients with microbiologically confirmed tuberculosis and used whole genome sequencing for typing of strains. Non-human studies, conference abstracts, and literature reviews were excluded. For each included study, the number and proportion of fulfilled STROME-ID criteria were recorded by two reviewers. A comparison of the mean proportion of fulfilled STROME-ID criteria before and after publication of the STROME-ID guidelines (in 2014) was done using a two-tailed t test. Quasi-Poisson regression and tobit regression were used to examine associations between study characteristics and the number and proportion of fulfilled STROME-ID criteria. This study was registered with PROSPERO, CRD42017064395.

FINDINGS

976 titles and abstracts were identified by our primary search, with an additional 16 studies identified in bioRxiv. 114 full texts (published between 2009 and 2019) were eligible for inclusion. The mean proportion of STROME-ID criteria fulfilled was 50% (SD 12; range 16-75). The proportion of criteria fulfilled was similar before and after STROME-ID publication (51% [SD 11] vs 46% [14], p=0·26). The number of criteria reported (among those applicable to all studies) was not associated with impact factor, h-index, country of affiliation of senior author, or sample size of isolates. Similarly, the proportion of criteria fulfilled was not associated with these characteristics, with the exception of a sample size of isolates of 277 or more (the highest quartile). In terms of reproducibility, 100 (88%) studies reported which bioinformatic tools were used, but only 33 (33%) reported corresponding version numbers. Sequencing data were available for 86 (75%) studies.

INTERPRETATION

The reporting of STROME-ID criteria in genomic epidemiology studies of tuberculosis between 2009 and 2019 was low, with implications for assessment of study quality. The considerable proportion of studies without bioinformatics version numbers or sequencing data available highlights a key concern for reproducibility.

Identification of a Mycobacterium tuberculosis-specific gene marker for diagnosis of tuberculosis using semi-nested melt-MAMA qPCR (lprM-MAMA)

Tuberculosis (TB) is the deadliest of infectious diseases. TB diagnosis, based on sputum microscopy, culture, and nucleic acid amplification tests (NAATs) to identify its main causative agent, Mycobacterium tuberculosis (MTB), remains challenging. The current available NAATs, endorsed by World Health Organization (WHO), can differentiate MTB from some MTB complex (MTBC) members. Using bioinformatics, we identified a single nucleotide polymorphism (SNP) in lprM (Rv1970) gene that differentiate MTB from other MTBC members. A forward mismatch amplification mutation assay (MAMA) primer was designed for the targeted mutation and was used in a semi-nested melt-MAMA qPCR (lprM-MAMA). Using the optimized protocol, lprM-MAMA was positive with all MTB reference and clinical strains, and negative with other MTBC members, non-tuberculous mycobacteria (NTM) and other non-mycobacterial (NM) reference strains. The limit of detection (LOD) of lprM-MAMA was 76.29 fg. Xpert® MTB/RIF (Xpert)-positive sputum samples were also positive by lprM-MAMA, except for samples classified as having "very low" bacterial load by Xpert. Xpert-negative sputum samples were also negative by lprM-MAMA. In conclusion, lprM-MAMA demonstrated to be a useful tool for specific MTB diagnosis. Further evaluation with higher number of reference strains, including NTM and NM; and sputum samples are required to determine its potential for clinical application.

Detection of low-frequency resistance-mediating SNPs in next-generation sequencing data of Mycobacterium tuberculosis complex strains with binoSNP

Accurate drug resistance detection is key for guiding effective tuberculosis treatment. While genotypic resistance can be rapidly detected by molecular methods, their application is challenged by mixed mycobacterial populations comprising both susceptible and resistant cells (heteroresistance). For this, next-generation sequencing (NGS) based approaches promise the determination of variants even at low frequencies. However, accurate methods for a valid detection of low-frequency variants in NGS data are currently lacking. To tackle this problem, we developed the variant detection tool binoSNP which allows the determination of low-frequency single nucleotide polymorphisms (SNPs) in NGS datasets from Mycobacterium tuberculosis complex (MTBC) strains. By taking a reference-mapped file as input, binoSNP evaluates each genomic position of interest using a binomial test procedure. binoSNP was validated using in-silico, in-vitro, and serial patient isolates datasets comprising varying genomic coverage depths (100-500×) and SNP allele frequencies (1-30%). Overall, the detection limit for low-frequency SNPs depends on the combination of coverage depth and allele frequency of the resistance-associated mutation. binoSNP allows for valid detection of resistance associated SNPs at a 1% frequency with a coverage ≥400×. In conclusion, binoSNP provides a valid approach to detect low-frequency resistance-mediating SNPs in NGS data from clinical MTBC strains. It can be implemented in automated, end-user friendly analysis tools for NGS data and is a step forward towards individualized TB therapy.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Role and value of whole genome sequencing in studying tuberculosis transmission

BACKGROUND

Tuberculosis (TB) remains a serious public health threat worldwide. Theoretically ultimate resolution of whole genome sequencing (WGS) for Mycobacterium tuberculosis complex (MTBC) strain classification makes this technology very attractive for epidemiological investigations.

OBJECTIVES

To summarize the evidence available in peer-reviewed publications on the role and place of WGS in detection of TB transmission.

SOURCES

A total of 69 peer-reviewed publications identified in Pubmed database.

CONTENT

Evidence from >30 publications suggests that a cut-off value of fewer than six single nucleotide polymorphisms between strains efficiently excludes cases that are not the result of recent transmission and could be used for the identification of drug-sensitive isolates involved in direct human-to-human TB transmission. Sensitivity of WGS to identify epidemiologically linked isolates is high, reaching 100% in eight studies with specificity (17%-95%) highly dependent on the settings. Drug resistance and specific phylogenetic lineages may be associated with accelerated mutation rates affecting genetic distances. WGS can be potentially used to distinguish between true relapses and re-infections but in high-incidence low-diversity settings this would require consideration of epidemiological links and minority alleles. Data from four studies looking into within-host diversity highlight a need for developing criteria for acceptance or rejection of WGS relatedness results depending on the proportion of minority alleles.

IMPLICATIONS

WGS will potentially allow for more targeted public health actions preventing unnecessary investigations of false clusters. Consensus on standardization of raw data quality control processing criteria, analytical pipelines and reporting language is yet to be reached.

Evaluation of a gene-by-gene approach for prospective whole-genome sequencing-based surveillance of multidrug resistant Mycobacterium tuberculosis

Whole-genome sequencing (WGS) offers unprecedented resolution for tracking Mycobacterium tuberculosis transmission and antibiotic-resistance spread. Still, the establishment of standardized WGS-based pipelines and the definition of epidemiological clusters based on genetic relatedness are under discussion. We aimed to implement a dynamic gene-by-gene approach, fully relying on freely available software, for prospective WGS-based tuberculosis surveillance, demonstrating its application for detecting transmission chains by retrospectively analysing all M/XDR strains isolated in 2013-2017 in Portugal. We observed a good correlation between genetic relatedness and epidemiological links, with strongly epilinked clusters displaying mean pairwise allele differences (AD) always below 0.3% (ratio of mean AD over the total number of shared loci between same-cluster strains). This data parallels the genetic distances acquired by the core-SNV analysis, while providing higher resolution and epidemiological concordance than MIRU-VNTR genotyping. The dynamic analysis of strain sub-sets (i.e., increasing the number of shared loci within each sub-set) also strengthens the confidence in detecting epilinked clusters. This gene-by-gene strategy also offers several practical benefits (e.g., reliance on freely-available software, scalability and low computational requirements) that further consolidated its suitability for a timely and robust prospective WGS-based laboratory surveillance of M/XDR-TB cases.

ASAP-GxNet project in Burkina Faso: fulfil country capacity gaps to ensure efficient utilisation of GeneXpert instruments in tuberculosis care and cascade

Improving availability, accessibility and quality of national GeneXpert networks through ASAP-GxNet http://ow.ly/umaZ30mGRpE.

Prevalence of tuberculosis and multidrug resistant tuberculosis in the Middle East Region

INTRODUCTION

Prevalence of TB and MDR-TB varies considerably among various regions of World Health Organization (WHO) and also among individual countries within each region. Many Middle Eastern countries have war/civil war-like situations, refugees from war-torn countries or dynamic expatriate population from TB endemic countries which will likely affect the END-TB strategy launched by the WHO in 2015. Areas covered: The data for each of 17 countries comprising the Middle East were analyzed for estimated incidence of TB, number of notified TB cases, mortality rate, and rate of MDR-TB in new and previously treated TB cases as reported by WHO. Data from national surveys or surveillance studies from individual countries were also analyzed for incidence of MDR-TB in new and previously treated TB patients and compared with the estimated data by WHO. Expert commentary: Several Middle Eastern countries have low/intermediate incidence rate and are striving for TB elimination. Reaching pre-elimination (< 1 TB case per 100 000 population) stage will require testing and treatment of latent TB infection in groups at high risk of reactivation and effective treatment of drug-susceptible and drug-resistant TB cases. Large numbers of refugees, expatriate workers, or confounding noncommunicable diseases in some countries pose major challenges in achieving progress toward TB elimination.

Drug resistance mechanisms and drug susceptibility testing for tuberculosis

Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) is the deadliest infectious disease and the associated global threat has worsened with the emergence of drug resistance, in particular multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB). Although the World Health Organization (WHO) End-TB Strategy advocates for universal access to antimicrobial susceptibility testing, this is not widely available and/or it is still underused. The majority of drug resistance in clinical MTB strains is attributed to chromosomal mutations. Resistance-related mutations could also exert certain fitness cost to the drug-resistant MTB strains and growth fitness could be restored by the presence of compensatory mutations. Understanding these underlying mechanisms could provide an important insight into TB pathogenesis and predict the future trend of MDR-TB global pandemic. This review covers the mechanisms of resistance in MTB and provides a comprehensive overview of current phenotypic and molecular approaches for drug susceptibility testing, with particular attention to the methods endorsed and recommended by the WHO.

Use of whole genome sequencing in surveillance of drug resistant tuberculosis

INTRODUCTION

The threat of resistance to anti-tuberculosis drugs is of global concern. Current efforts to monitor resistance rely on phenotypic testing where cultured bacteria are exposed to critical concentrations of the drugs. Capacity for such testing is low in TB endemic countries. Drug resistance is caused by mutations in the Mycobacterium tuberculosis genome and whole genome sequencing to detect these mutations offers an alternative means of assessing resistance. Areas covered: The challenges of assessing TB drug resistance are discussed. Progress in elucidating the M. tuberculosis resistome and evidence of the accuracy of next generation sequencing for detecting resistance is reviewed. Expert Commentary: There are considerable advantages to using next generation sequencing for TB drug resistance surveillance. Accuracy is high for detecting resistance to the major first-line drugs but is currently lower for the second-line drugs due to our incomplete knowledge regarding resistance causing mutations. With the advances in sequencing technology and the opportunity to replace phenotypic drug susceptibility testing with safer and more cost effective methods it would appear that the question is when to implement. Current bottlenecks are sample extraction to allow whole genome sequencing directly from sputum and the lack of bioinformatics expertise in some TB endemic countries.