Capacity building for whole genome sequencing of Mycobacterium tuberculosis and bioinformatics in high TB burden countries

De Novo Genome Assembly for an Endangered Lemur Using Portable Nanopore Sequencing in Rural Madagascar

As one of the most threatened mammalian taxa, lemurs of Madagascar are facing unprecedented anthropogenic pressures. To address conservation imperatives such as this, researchers have increasingly relied on conservation genomics to identify populations of particular concern. However, many of these genomic approaches necessitate high-quality genomes. While the advent of next-generation sequencing technologies and the resulting reduction in associated costs have led to the proliferation of genomic data and high-quality reference genomes, global discrepancies in genomic sequencing capabilities often result in biological samples from biodiverse host countries being exported to facilities in the Global North, creating inequalities in access and training within genomic research. Here, we present the first published reference genome for the endangered red-fronted brown lemur (Eulemur rufifrons) from sequencing efforts conducted entirely within the host country using portable Oxford Nanopore sequencing. Using an archived E. rufifrons specimen, we conducted long-read, nanopore sequencing at the Centre ValBio Research Station near Ranomafana National Park, in rural Madagascar, generating over 750 Gb of sequencing data from 10 MinION flow cells. Exclusively using this long-read data, we assembled 2.157 gigabase, 2980-contig nuclear assembly with an N50 of 101.6 Mb and a 17,108 bp mitogenome. The nuclear assembly had 30× average coverage and was comparable in completeness to other primate reference genomes, with a 96.1% BUSCO completeness score for primate-specific genes. As the first published reference genome for E. rufifrons and the only annotated genome available for the speciose Eulemur genus, this resource will prove vital for conservation genomic studies while our efforts exhibit the potential of this protocol to address research inequalities and build genomic capacity.

Strategies to Enhance Diagnostic Capabilities for the New Drug-Resistant Tuberculosis (DR-TB) Drugs

The global burden of drug-resistant tuberculosis (DR-TB) continues to challenge healthcare systems worldwide. There is a critical need to tackle DR-TB by enhancing diagnostics and drug susceptibility testing (DST) capabilities, particularly for emerging DR-TB drugs. This endeavor is crucial to optimize the efficacy of new therapeutic regimens and prevent the resistance and overuse of these invaluable weapons. Despite this urgency, there remains a lack of comprehensive review of public health measures aimed at improving the diagnostics and DST capabilities. In this review, we outline strategies to enhance the capabilities, especially tailored to address the challenges posed by resistance to new DR-TB drugs. We discuss the current landscape of DR-TB drugs, existing diagnostic and susceptibility testing methods, and notable gaps and challenges in these methods and explore strategies for ensuring fair access to DST while narrowing these disparities. The strategies include public health interventions aimed at strengthening laboratory infrastructure, workforce training, and quality assurance programs, technology transfer initiatives, involving drug developers in the DST development, establishing national or regional referral hubs, fostering collaboration and resources pooling with other infection control efforts, extending testing access in underserved areas through public-private partnerships, advocating for lowering costs or loans at low interest, remote technical support, and implementing mandatory molecular surveillance monitoring. This review underscores the urgent need to enhance DST capacities for new DR-TB drugs and identifies opportunities for innovation and improvement. Assessing the extent of the global health impact of these measures is crucial to ensure their effectiveness in combating DR-TB.

aXonica: A support package for MRI based Neuroimaging

Magnetic Resonance Imaging (MRI) assists in studying the nervous system. MRI scans undergo significant processing before presenting the final images to medical practitioners. These processes are executed with ease due to excellent software pipelines. However, establishing software workstations is non-trivial and requires researchers in life sciences to be comfortable in downloading, installing, and scripting software that is non-user-friendly and may lack basic GUI. As researchers struggle with these skills, there is a dire need to develop software packages that can automatically install software pipelines speeding up building software workstations and laboratories. Previous solutions include NeuroDebian, BIDS Apps, Flywheel, QMENTA, Boutiques, Brainlife and Neurodesk. Overall, all these solutions complement each other. NeuroDebian covers neuroscience and has a wider scope, providing only 51 tools for MRI. Whereas, BIDS Apps is committed to the BIDS format, covering only 45 software related to MRI. Boutiques is more flexible, facilitating its pipelines to be easily installed as separate containers, validated, published, and executed. Whereas, both Flywheel and Qmenta are propriety, leaving four for users looking for 'free for use' tools, i.e., NeuroDebian, Brainlife, Neurodesk, and BIDS Apps. This paper presents an extensive survey of 317 tools published in MRI-based neuroimaging in the last ten years, along with 'aXonica,' an MRI-based neuroimaging support package that is unbiased towards any formatting standards and provides 130 applications, more than that of NeuroDebian (51), BIDS App (45), Flywheel (70), and Neurodesk (85). Using a technology stack that employs GUI as the front-end and shell scripted back-end, aXonica provides (i) 130 tools that span the entire MRI-based neuroimaging analysis, and allow the user to (ii) select the software of their choice, (iii) automatically resolve individual dependencies and (iv) installs them. Hence, aXonica can serve as an important resource for researchers and teachers working in the field of MRI-based Neuroimaging to (a) develop software workstations, and/or (b) install newer tools in their existing workstations.

An overview of next generation sequencing strategies and genomics tools used for tuberculosis research

Tuberculosis (TB) is a grave public health concern and is considered the foremost contributor to human mortality resulting from infectious disease. Due to the stringent clonality and extremely restricted genomic diversity, conventional methods prove inefficient for in-depth exploration of minor genomic variations and the evolutionary dynamics operating in Mycobacterium tuberculosis (M.tb) populations. Until now, the majority of reviews have primarily focused on delineating the application of whole-genome sequencing (WGS) in predicting antibiotic resistant genes, surveillance of drug resistance strains, and M.tb lineage classifications. Despite the growing use of next generation sequencing (NGS) and WGS analysis in TB research, there are limited studies that provide a comprehensive summary of there role in studying macroevolution, minor genetic variations, assessing mixed TB infections, and tracking transmission networks at an individual level. This highlights the need for systematic effort to fully explore the potential of WGS and its associated tools in advancing our understanding of TB epidemiology and disease transmission. We delve into the recent bioinformatics pipelines and NGS strategies that leverage various genetic features and simultaneous exploration of host-pathogen protein expression profile to decipher the genetic heterogeneity and host-pathogen interaction dynamics of the M.tb infections. This review highlights the potential benefits and limitations of NGS and bioinformatics tools and discusses their role in TB detection and epidemiology. Overall, this review could be a valuable resource for researchers and clinicians interested in NGS-based approaches in TB research.

Boosting pathogen genomics and bioinformatics workforce in Africa

Next-generation sequencing (NGS) of genomic data has established its fundamental value in public health surveillance, research and development, and precision medicine. In Africa, severe shortages of competent experts in genomics and bioinformatics, few opportunities for research, and inadequate genomic infrastructure have had a knock-on effect on the use of NGS technologies for research and public health practice. Several reasons-ranging from poor funding, inadequate infrastructure for training and practice, to brain drain-might partly account for the scarcity of genomics and bioinformatics expertise in the region. In recognition of these shortcomings and the importance of NGS genomic data, which was amplified during the COVID-19 pandemic in mid-2021, the Africa Centres for Disease Control and Prevention (Africa CDC) through the Africa Pathogen Genomics Initiative began building and expanding Africa's workforce in pathogen surveillance. By the end of 2022, the Africa CDC in collaboration with its partners and centres of excellence had trained 413 personnel, mostly from public health institutions, in 53 (96%) of 55 African Union Member States. Although this training has increased genomics, bioinformatics, and genomic epidemiology literacy, and genomic-informed pathogen surveillance, there is still a need for a strategic and sustainable public health workforce development in Africa.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

Lineage classification and antitubercular drug resistance surveillance of Mycobacterium tuberculosis by whole-genome sequencing in Southern India

IMPORTANCE

Studies mapping genetic heterogeneity of clinical isolates of M. tuberculosis for determining their strain lineage and drug resistance by whole-genome sequencing are limited in high tuberculosis burden settings. We carried out whole-genome sequencing of 242 M. tuberculosis isolates from drug-sensitive and drug-resistant tuberculosis patients, identified and collected as part of the TB Portals Program, to have a comprehensive insight into the genetic diversity of M. tuberculosis in Southern India. We report several genetic variations in M. tuberculosis that may confer resistance to antitubercular drugs. Further wide-scale efforts are required to fully characterize M. tuberculosis genetic diversity at a population level in high tuberculosis burden settings for providing precise tuberculosis treatment.

Whole Genomic Analysis Revealed High Genetic Diversity and Drug-Resistant Characteristics of Mycobacterium tuberculosis in Guangxi, China

Background

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a major public health issue in China. Nevertheless, the prevalence and drug resistance characteristics of isolates vary in different regions and provinces. In this study, we investigated the population structure, transmission dynamics and drug-resistant profiles of Mtb in Guangxi, located on the border of China.

Methods

From February 2016 to April 2017, 462 clinical M. tuberculosis isolates were selected from 5 locations in Guangxi. Drug-susceptibility testing was performed using 6 common anti-tuberculosis drugs. The genotypic drug resistance and transmission dynamics were analyzed by the whole genome sequence.

Results

Our data showed that the Mtb in Guangxi has high genetic diversity including Lineage 1 to Lineage 4, and mostly belong to Lineage 2 and Lineage 4. Novelty, 9.6% of Lineage 2 isolates were proto-Beijing genotype (L2.1), which is rare in China. About 12.6% of isolates were phylogenetically clustered and formed into 28 transmission clusters. We observed that the isolates with the high resistant rate of isoniazid (INH, 21.2%), followed by rifampicin (RIF, 13.2%), and 6.7%, 12.1%, 6.7% and 1.9% isolates were resistant to ethambutol (EMB), streptomycin (SM), ofloxacin (OFL) and kanamycin (KAN), respectively. Among these, 6.5% and 3.3% of isolates belong to MDR-TB and Pre-XDR, respectively, with a high drug-resistant burden. Genetic analysis identified the most frequently encountered mutations of INH, RIF, EMB, SM, OFL and KAN were katG_Ser315Thr (62.2%), rpoB_Ser450Leu (42.6%), embB_Met306Vol (45.2%), rpsL_Lys43Arg (53.6%), gyrA_Asp94Gly (29.0%) and rrs_A1401G (66.7%), respectively. Additionally, we discovered that isolates from border cities are more likely to be drug-resistant than isolates from non-border cities.

Conclusion

Our findings provide a deep analysis of the genomic population characteristics and drug-resistant of M. tuberculosis in Guangxi, which could contribute to developing effective TB prevention and control strategies.

Genomic Sequencing Profiles of Mycobacterium tuberculosis in Mandalay Region, Myanmar

This study aimed to characterize whole-genome sequencing (WGS) information of Mycobacterium tuberculosis (Mtb) in the Mandalay region of Myanmar. It was a cross-sectional study conducted with 151 Mtb isolates obtained from the fourth nationwide anti-tuberculosis (TB) drug-resistance survey. Frequency of lineages 1, 2, 3, and 4 were 55, 65, 9, and 22, respectively. The most common sublineage was L1.1.3.1 (n = 31). Respective multi-drug resistant tuberculosis (MDR-TB) frequencies were 1, 1, 0, and 0. Four clusters of 3 (L2), 2 (L4), 2 (L1), and 2 (L2) isolates defined by a 20-single-nucleotide variant (SNV) cutoff were detected. Simpson's index for sublineages was 0.0709. Such high diversity suggests that the area probably had imported Mtb from many geographical sources. Relatively few genetic clusters and MDR-TB suggest there is a chance the future control will succeed if it is carried out properly.

Implementing molecular tuberculosis diagnostic methods in limited-resource and high-burden countries

Tuberculosis (TB) is one of the deadliest infectious diseases in the world with more than a million people dying of TB each year. Accurate and timely TB diagnosis has the potential to alleviate the global TB burden; therefore, one of the pillars of the End TB Strategy developed by the World Health Organization (WHO) is the early diagnosis of TB, including universal drug-susceptibility testing (DST). The WHO emphasises the importance of DST before treatment initiation, using molecular WHO-recommended rapid diagnostic tests (mWRDs). Currently available mWRDs are nucleic acid amplification tests, line probe assays, whole genome sequencing, and targeted next-generation sequencing. However, implementing the sequencing mWRDs in routine laboratories in low-income countries is constrained by the existing infrastructure, high cost, the specialised skills needed, data storage, and the current delay in results compared with other routine methods. These limitations are pronounced in resource-limited settings, which often have a high TB burden and need for innovative TB diagnostic technologies. In this article we propose several possible solutions, like adapting infrastructure capacity to needs, advocating for lowering costs, building bioinformatics and laboratory capacity, and increasing the use of open-access resources for software and publications.

Bedaquiline resistance probability to guide treatment decision making for rifampicin-resistant tuberculosis: insights from a qualitative study

BACKGROUND

Bedaquiline (BDQ) is a core drug for rifampicin-resistant tuberculosis (RR-TB) treatment. Accurate prediction of a BDQ-resistant phenotype from genomic data is not yet possible. A Bayesian method to predict BDQ resistance probability from next-generation sequencing data has been proposed as an alternative.

METHODS

We performed a qualitative study to investigate the decision-making of physicians when facing different levels of BDQ resistance probability. Fourteen semi-structured interviews were conducted with physicians experienced in treating RR-TB, sampled purposefully from eight countries with varying income levels and burden of RR-TB. Five simulated patient scenarios were used as a trigger for discussion. Factors influencing the decision of physicians to prescribe BDQ at macro-, meso- and micro levels were explored using thematic analysis.

RESULTS

The perception and interpretation of BDQ resistance probability values varied widely between physicians. The limited availability of other RR-TB drugs and the high cost of BDQ hindered physicians from altering the BDQ-containing regimen and incorporating BDQ resistance probability in their decision-making. The little experience with BDQ susceptibility testing and whole-genome sequencing results, and the discordance between phenotypic susceptibility and resistance probability were other barriers for physicians to interpret the resistance probability estimates. Especially for BDQ resistance probabilities between 25% and 70%, physicians interpreted the resistance probability value dynamically, and other factors such as clinical and bacteriological treatment response, history of exposure to BDQ, and resistance profile were often considered more important than the BDQ probability value for the decision to continue or stop BDQ. In this grey zone, some physicians opted to continue BDQ but added other drugs to strengthen the regimen.

CONCLUSIONS

This study highlights the complexity of physicians' decision-making regarding the use of BDQ in RR-TB regimens for different levels of BDQ resistance probability.. Ensuring sufficient access to BDQ and companion drugs, improving knowledge of the genotype-phenotype association for BDQ resistance, availability of a rapid molecular test, building next-generation sequencing capacity, and developing a clinical decision support system incorporating BDQ resistance probability will all be essential to facilitate the implementation of BDQ resistance probability in personalizing treatment for patients with RR-TB.

MinION Whole-Genome Sequencing in Resource-Limited Settings: Challenges and Opportunities

Purpose of Review

The introduction of MinION whole-genome sequencing technology greatly increased and simplified complete genome sequencing in various fields of science across the globe. Sequences have been generated from complex organisms to microorganisms and are stored in genome databases that are readily accessible by researchers. Various new software for genome analysis, along with upgrades to older software packages, are being generated. New protocols are also being validated that enable WGS technology to be rapidly and increasingly used for sequencing in field settings.

Recent Findings

MinION WGS technology has been implemented in developed countries due to its advantages: portability, real-time analysis, and lower cost compared to other sequencing technologies. While these same advantages are critical in developing countries, MinION WGS technology is still under-utilized in resource-limited settings.

Summary

In this review, we look at the applications, advantages, challenges, and opportunities of using MinION WGS in resource-limited settings.