Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

Abstract

Background Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. Results We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93–95%) and 83% (95%CI 79–87%) with specificities of 98% (95%CI 98–99%) and 96% (95%CI 95–97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler , involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB , the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. Conclusions The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings. Electronic supplementary material The online version of this article (10.1186/s13073-019-0650-x) contains supplementary material, which is available to authorized users.

Dynamics of within-hostMycobacterium tuberculosisdiversity and heteroresistance during treatment

“…For identification of RAVs, we used a curated list of resistance-conferring mutations adapted from published sources (43,44) as listed in Supplementary Methods 3. We supplemented these mutations lists with more recent published data for new and repurposed drugs (45)(46)(47)(48).…”

Natural Polymorphisms in Mycobacterium tuberculosis Conferring Resistance to Delamanid in Drug-Naive Patients

“…In brief, M. tuberculosis DNA was extracted and sequenced using the Illumina HiSeq 2500 system (Illumina, San Diego, CA, USA). For the analysis, we used the well-established pipeline TBprofiler ( https://github.com/jodyphelan/TBProfiler ) ( 26 , 27 ). It aligns short reads to the M. tuberculosis reference strain H37Rv (GenBank accession no.…”

A lab in the field: applications of real-time, in situ metagenomic sequencing

“…Flagship examples of such applications are the fast (<24 h) detection of Ebola virus during the 2015 outbreak in West Africa [ 16 , 73 ], or the fast (<6 h) phylogenomic analysis of Salmonella strains during a hospital outbreak [ 74 ]. Other significant efforts have focused on the fast identification of single clinical isolates [ 75 ], including the analysis of ARGs in a timeframe of <6 h [ 76 , 77 ]. However, a range of use cases in the clinical field requires the use of metagenomic sequencing to unveil the identity of viral or microbial communities rather than single isolates.…”