Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues

Abstract

Whole genome sequencing (WGS) of Mycobacterium tuberculosis has rapidly evolved from a research tool to a clinical application for the diagnosis and management of tuberculosis and in public health surveillance. This evolution has been facilitated by the dramatic drop in costs, advances in technology, and concerted efforts to translate sequencing data into actionable information. There is however a risk that, in the absence of a consensus and international standards, the widespread use of WGS technology may result in data and processes that lack harmonisation, comparability and validation. In this review, we outline the current landscape of WGS pipelines and applications and set out best practices for M. tuberculosis WGS, including standards for bioinformatics pipelines, curated repository of resistance-causing variants, phylogenetic analyses, quality control processes, and standardised reporting. 1. Introduction Mycobacterium tuberculosis complex (Mtbc) pathogens are collectively the top infectious disease killer globally, causing 10 million new tuberculosis (TB) cases annually 1. Increasingly, 95 new TB cases are already resistant to rifampicin and isoniazid (termed multidrug resistance; 96 MDR-TB), the key first line drugs 1. Tackling the spread and drug resistance burden of this pathogen requires concerted global effort in prevention, diagnosis, treatment and surveillance.

New insights into the mycobacterial PE and PPE proteins provide a framework for future research

“…This problem is aggravated by many gene duplications and repetitive sequences that distinguish certain subgroups of pe and ppe genes (Gey van Pittius et al, 2006;McEvoy et al, 2012;Copin et al, 2014). Because of the challenges associated with mapping pe/ppe reads to mycobacterial reference genomes, these genes have generally been excluded from frequently used bioinformatic pipelines and have remained relatively understudied with genome-based techniques (Coll et al, 2014;Phelan et al, 2016;Meehan et al, 2019). Similarly, mass spectrometry of PE and PPE proteins is hampered by a paucity of trypsin cleavage sites and high homology between and within PE and PPE proteins (Banu et al, 2002;Schubert et al, 2013;Ates et al, 2015).…”

Exact mapping of Illumina blind spots in theMycobacterium tuberculosisgenome reveals platform-wide and workflow-specific biases

“…While many researchers are unaware of coverage bias, some recognize the problem and address it by omitting large regions of the M. tuberculosis genome that are associated with known sequencing biases. These omitted regions are typically restricted to members of the PE, PPE, and PE-PGRS gene families ("PE/PPE genes"), disregarded due to their hypervariable nature, repetitive elements, and propensity for erroneous read mapping (23,24,50). However, we identified blind spots beyond these regions.…”

“…We provide these deliverables for seven sequencing workflows separately, and in a pooled set. We find that blind spots distribute differently across the M. tuberculosis genome than accounted for by common practices in WGS analysis pipelines (7,(23)(24)(25)(26) and overlap a variety of genes, including several implicated in drug resistance. Workflow-stratified analyses identify a modified Nextera library prep (29) as the least biased option and reveal distinct coverage biases across Illumina sequencing workflows, and the unexpected finding of coverage bias at homopolymers of a shorter length than previously thought.…”

“…Many researchers are unaware that Illumina WGS data is affected by coverage bias, and take very low coverage to imply true deletions, ignoring coverage bias as a potential cause (20,21). Others are aware of this bias, and handle it by excluding large regions of the genome that meet field-standard criteria with limited knowledge of which locations are affected (7,22,23). A common practice for handling Illumina sequencing bias in M. tuberculosis is to exclude all or part of the PE and PPE multigene families (23)(24)(25)(26).…”

“…Others are aware of this bias, and handle it by excluding large regions of the genome that meet field-standard criteria with limited knowledge of which locations are affected (7,22,23). A common practice for handling Illumina sequencing bias in M. tuberculosis is to exclude all or part of the PE and PPE multigene families (23)(24)(25)(26). These genes make up 10% of the coding capacity of the genome (27) and play roles in evading host immunity that are important, yet poorly understood (28).…”