Molecular Diagnosis of Drug-Resistant Tuberculosis; A Literature Review

Tuberculosis remains the leading cause of death from an infectious disease worldwide. Early and accurate diagnosis and detection of drug-sensitive and drug-resistant tuberculosis is essential for achieving global tuberculosis control. Despite the introduction of the Xpert MTB/RIF assay as the first-line rapid tuberculosis diagnostic test, the gap between global estimates of incidence and new case notifications is 4·1 million people. More accurate, rapid, and cost-effective screening tests are needed to improve case detection. Diagnosis of extrapulmonary tuberculosis and tuberculosis in children, people living with HIV, and pregnant women remains particularly problematic. The diagnostic molecular technology landscape has continued to expand, including the development of tests for resistance to several antituberculosis drugs. Biomarkers are urgently needed to indicate progression from latent infection to clinical disease, to predict risk of reactivation after cure, and to provide accurate endpoints for drug and vaccine trials. Sophisticated bioinformatic computational tools and systems biology approaches are being applied to the discovery and validation of biomarkers, with substantial progress taking place. New data have been generated from the study of T-cell responses and T-cell function, serological studies, flow cytometric-based assays, and protein and gene expression studies. Alternative diagnostic strategies under investigation as potential screening and triaging tools include non-sputum-based detection with breath-based tests and automated digital radiography. We review developments and key achievements in the search for new tuberculosis diagnostics and biomarkers. We highlight gaps and challenges in evaluation and rollout of new diagnostics and biomarkers, and prioritise areas needing further investment, including impact assessment and cost-benefit studies.

Nanopore sequencing technology has the potential to render other sequencing technologies obsolete with its ability to generate long reads and provide portability. However, high error rates of the technology pose a challenge while generating accurate genome assemblies. The tools used for nanopore sequence analysis are of critical importance, as they should overcome the high error rates of the technology. Our goal in this work is to comprehensively analyze current publicly available tools for nanopore sequence analysis to understand their advantages, disadvantages and performance bottlenecks. It is important to understand where the current tools do not perform well to develop better tools. To this end, we (1) analyze the multiple steps and the associated tools in the genome assembly pipeline using nanopore sequence data, and (2) provide guidelines for determining the appropriate tools for each step. Based on our analyses, we make four key observations: (1) the choice of the tool for basecalling plays a critical role in overcoming the high error rates of nanopore sequencing technology. (2) Read-to-read overlap finding tools, GraphMap and Minimap, perform similarly in terms of accuracy. However, Minimap has a lower memory usage, and it is faster than GraphMap. (3) There is a trade-off between accuracy and performance when deciding on the appropriate tool for the assembly step. The fast but less accurate assembler Miniasm can be used for quick initial assembly, and further polishing can be applied on top of it to increase the accuracy, which leads to faster overall assembly. (4) The state-of-the-art polishing tool, Racon, generates high-quality consensus sequences while providing a significant speedup over another polishing tool, Nanopolish. We analyze various combinations of different tools and expose the trade-offs between accuracy, performance, memory usage and scalability. We conclude that our observations can guide researchers and practitioners in making conscious and effective choices for each step of the genome assembly pipeline using nanopore sequence data. Also, with the help of bottlenecks we have found, developers can improve the current tools or build new ones that are both accurate and fast, to overcome the high error rates of the nanopore sequencing technology.

The current methods available to diagnose antimicrobial-resistant Mycobacterium tuberculosis infections require a positive culture or only test a limited number of resistance-associated mutations. A rapid accurate identification of antimicrobial resistance enables the prompt initiation of effective treatment.