Comprehensive and accurate genetic variant identification from contaminated and low coverage Mycobacterium tuberculosis whole genome sequencing data

Abstract

Improved understanding of the genomic variants that allow Mycobacterium tuberculosis (Mtb) to acquire drug resistance, or tolerance, and increase its virulence are important factors in controlling the current tuberculosis epidemic. Current approaches to Mtb sequencing however cannot reveal Mtb’s full genomic diversity due to the strict requirements of low contamination levels, high Mtb sequence coverage, and elimination of complex regions.

We developed the XBS (compleX Bacterial Samples) bioinformatics pipeline which implements joint calling and machine-learning-based variant filtering tools to specifically improve variant detection in the important Mtb samples that do not meet these criteria, such as those from unbiased sputum samples. Using novel simulated datasets, that permit exact accuracy verification, XBS was compared to the UVP and MTBseq pipelines. Accuracy statistics showed that all three pipelines performed equally well for sequence data that resemble those obtained from high depth coverage and low-level contamination culture isolates. In the complex genomic regions however, XBS accurately identified 9.0% more single nucleotide polymorphisms and 8.1% more single nucleotide insertions and deletions than the WHO-endorsed unified analysis variant pipeline. XBS also had superior accuracy for sequence data that resemble those obtained directly from sputum samples, where depth of coverage is typically very low and contamination levels are high. XBS was the only pipeline not affected by low depth of coverage (5-10×), type of contamination and excessive contamination levels (>50%). Simulation results were confirmed using WGS data from clinical samples, confirming the superior performance of XBS with a higher sensitivity (98.8%) when analysing culture isolates and identification of 13.9% more variable sites in WGS data from sputum samples as compared to MTBseq, without evidence for false positive variants when ribosomal RNA regions were excluded.

The XBS pipeline facilitates sequencing of less-than-perfect Mtb samples. These advances will benefit future clinical applications of Mtb sequencing, especially whole genome sequencing directly from clinical specimens, thereby avoiding in vitro biases and making many more samples available for drug resistance and other genomic analyses. The additional genetic resolution and increased sample success rate will improve genome-wide association studies and sequence-based transmission studies.