Robust barcoding and identification of Mycobacterium tuberculosis lineages for epidemiological and clinical studies

SNPs in Genes Related to DNA Damage Repair in Mycobacterium Tuberculosis: Their Association with Type 2 Diabetes Mellitus and Drug Resistance

Genes related to DNA damage repair in Mycobacterium tuberculosis are critical for survival and genomic diversification. The aim of this study is to compare the presence of SNPs in genes related to DNA damage repair in sensitive and drug-resistant M. tuberculosis genomes isolated from patients with and without type 2 diabetes mellitus (T2DM). We collected 399 M. tuberculosis L4 genomes from several public repositories; 224 genomes belonging to hosts without T2DM, of which 123 (54.9%) had drug sensitive tuberculosis (TB) and 101 (45.1%) had drug resistance (DR)-TB; and 175 genomes from individuals with T2DM, of which 100 (57.1%) had drug sensitive TB and 75 (42.9%) had DR-TB. The presence of SNPs in the coding regions of 65 genes related to DNA damage repair was analyzed and compared with the resistance profile and the presence/absence of T2DM in the host. The results show the phylogenetic relationships of some SNPS and L4 sub-lineages, as well as differences in the distribution of SNPs present in DNA damage repair-related genes related to the resistance profile of the infecting strain and the presence of T2DM in the host. Given these differences, it was possible to generate two discriminant functions to distinguish between drug sensitive and drug resistant genomes, as well as patients with or without T2DM.

SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission

Whole genome sequencing (WGS) can provide insight into drug-resistance, transmission chains and the identification of outbreaks, but data analysis remains an obstacle to its routine clinical use. Although several drug-resistance prediction tools have appeared, until now no website integrates drug-resistance prediction with strain genetic relationships and species identification of nontuberculous mycobacteria (NTM). We have established a free, function-rich, user-friendly online platform for MTB WGS data analysis (SAM-TB, http://samtb.szmbzx.com) that integrates drug-resistance prediction for 17 antituberculosis drugs, detection of variants, analysis of genetic relationships and NTM species identification. The accuracy of SAM-TB in predicting drug-resistance was assessed using 3177 sequenced clinical isolates with results of phenotypic drug-susceptibility tests (pDST). Compared to pDST, the sensitivity of SAM-TB for detecting multidrug-resistant tuberculosis was 93.9% [95% confidence interval (CI) 92.6–95.1%] with specificity of 96.2% (95% CI 95.2–97.1%). SAM-TB also analyzes the genetic relationships between multiple strains by reconstructing phylogenetic trees and calculating pairwise single nucleotide polymorphism (SNP) distances to identify genomic clusters. The incorporated mlstverse software identifies NTM species with an accuracy of 98.2% and Kraken2 software can detect mixed MTB and NTM samples. SAM-TB also has the capacity to share both sequence data and analysis between users. SAM-TB is a multifunctional integrated website that uses WGS raw data to accurately predict antituberculosis drug-resistance profiles, analyze genetic relationships between multiple strains and identify NTM species and mixed samples containing both NTM and MTB. SAM-TB is a useful tool for guiding both treatment and epidemiological investigation.

Whole-genome single nucleotide variant phylogenetic analysis of Mycobacterium tuberculosis Lineage 1 in endemic regions of Asia and Africa

Mycobacterium tuberculosis (Mtb) lineage 1 (L1) contributes considerably to the disease morbidity. While whole genome sequencing (WGS) is increasingly used for studying Mtb, our understanding of genetic diversity of L1 remains limited. Using phylogenetic analysis of WGS data from endemic range in Asia and Africa, we provide an improved genotyping scheme for L1. Mapping deletion patterns of the 68 direct variable repeats (DVRs) in the CRISPR region of the genome onto the phylogeny provided supporting evidence that the CRISPR region evolves primarily by deletion, and hinted at a possible Southeast Asian origin of L1. Both phylogeny and DVR patterns clarified some relationships between different spoligotypes, and highlighted the limited resolution of spoligotyping. We identified a diverse repertoire of drug resistance mutations. Altogether, this study demonstrates the usefulness of WGS data for understanding the genetic diversity of L1, with implications for public health surveillance and TB control. It also highlights the need for more WGS studies in high-burden but underexplored regions.

Connection between two historical tuberculosis outbreak sites in Japan, Honshu, by a new ancestral Mycobacterium tuberculosis L2 sublineage

By gathering 680 publicly available Sequence Read Archives from isolates of Mycobacterium tuberculosis complex (MTBC) including 190 belonging to the lineage 2 Beijing , and using an in-house bioinformatical pipeline, the TB-Annotator , that analyses more than 50 000 characters, we describe herein a new L2 sublineage from 20 isolates found in the Tochigi province, (Japan), that we designate as asia ancestral 5 (AAnc5). These isolates harbour a number of specific criteria (42 SNPs) and their intra-cluster pairwise distance suggests historical and not epidemiological transmission. These isolates harbour a mutation in rpoC , and do not fulfil, any of the modern Beijing lineage criteria, nor any of the other ancestral Beijing lineages described so far. Asia ancestral 5 isolates do not possess mutT2 58 and ogt 12 characteristics of modern Beijing , but possess ancestral Beijing SNPs characteristics. By looking into the literature, we found a reference isolate ID381, described in Kobe and Osaka belonging to the ‘G3’ group, sharing 36 out of the 42 specific SNPs found in AAnc5. We also assessed the intermediate position of the asia ancestral 4 (AAnc4) sublineage recently described in Thailand and propose an improved classification of the L2 that now includes AAnc4 and AAnc5. By increasing the recruitment into TB-Annotator to around 3000 genomes (including 642 belonging to L2), we confirmed our results and discovered additional historical ancestral L2 branches that remain to be investigated in more detail. We also present, in addition, some anthropological and historical data from Chinese and Japan history of tuberculosis, as well as from Korea, that could support our results on L2 evolution. This study shows that the reconstruction of the early history of tuberculosis in Asia is likely to reveal complex patterns since its emergence.

A modified decision tree approach to improve the prediction and mutation discovery for drug resistance in Mycobacterium tuberculosis

BACKGROUND

Drug resistant Mycobacterium tuberculosis is complicating the effective treatment and control of tuberculosis disease (TB). With the adoption of whole genome sequencing as a diagnostic tool, machine learning approaches are being employed to predict M. tuberculosis resistance and identify underlying genetic mutations. However, machine learning approaches can overfit and fail to identify causal mutations if they are applied out of the box and not adapted to the disease-specific context. We introduce a machine learning approach that is customized to the TB setting, which extracts a library of genomic variants re-occurring across individual studies to improve genotypic profiling.

RESULTS

We developed a customized decision tree approach, called Treesist-TB, that performs TB drug resistance prediction by extracting and evaluating genomic variants across multiple studies. The application of Treesist-TB to rifampicin (RIF), isoniazid (INH) and ethambutol (EMB) drugs, for which resistance mutations are known, demonstrated a level of predictive accuracy similar to the widely used TB-Profiler tool (Treesist-TB vs. TB-Profiler tool: RIF 97.5% vs. 97.6%; INH 96.8% vs. 96.5%; EMB 96.8% vs. 95.8%). Application of Treesist-TB to less understood second-line drugs of interest, ethionamide (ETH), cycloserine (CYS) and para-aminosalisylic acid (PAS), led to the identification of new variants (52, 6 and 11, respectively), with a high number absent from the TB-Profiler library (45, 4, and 6, respectively). Thereby, Treesist-TB had improved predictive sensitivity (Treesist-TB vs. TB-Profiler tool: PAS 64.3% vs. 38.8%; CYS 45.3% vs. 30.7%; ETH 72.1% vs. 71.1%).

CONCLUSION

Our work reinforces the utility of machine learning for drug resistance prediction, while highlighting the need to customize approaches to the disease-specific context. Through applying a modified decision learning approach (Treesist-TB) across a range of anti-TB drugs, we identified plausible resistance-encoding genomic variants with high predictive ability, whilst potentially overcoming the overfitting challenges that can affect standard machine learning applications.

Revised nomenclature and SNP barcode for Mycobacterium tuberculosis lineage 2

Mycobacterium tuberculosis (Mtb) lineage 2 (L2) strains are present globally, contributing to a widespread tuberculosis (TB) burden, particularly in Asia where both prevalence of TB and numbers of drug resistant TB are highest. The increasing availability of whole-genome sequencing (WGS) data worldwide provides an opportunity to improve our understanding of the global genetic diversity of Mtb L2 and its association with the disease epidemiology and pathogenesis. However, existing L2 sublineage classification schemes leave >20 % of the Modern Beijing isolates unclassified. Here, we present a revised SNP-based classification scheme of L2 in a genomic framework based on phylogenetic analysis of >4000 L2 isolates from 34 countries in Asia, Eastern Europe, Oceania and Africa. Our scheme consists of over 30 genotypes, many of which have not been described before. In particular, we propose six main genotypes of Modern Beijing strains, denoted L2.2.M1–L2.2.M6. We also provide SNP markers for genotyping L2 strains from WGS data. This fine-scale genotyping scheme, which can classify >98 % of the studied isolates, serves as a basis for more effective monitoring and reporting of transmission and outbreaks, as well as improving genotype-phenotype associations such as disease severity and drug resistance. This article contains data hosted by Microreact.

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

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 have 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, which 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 culture isolates of high depth of coverage and low-level contamination. In the complex genomic regions, however, XBS accurately identified 9.0 % more SNPs 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 whole genome sequencing (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 rRNA 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 WGS 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.

Practical approach to detection and surveillance of emerging highly resistant Mycobacterium tuberculosis Beijing 1071-32-cluster

Ancient sublineage of the Mycobacterium tuberculosis Beijing genotype is endemic and prevalent in East Asia and rare in other world regions. While these strains are mainly drug susceptible, we recently identified a novel clonal group Beijing 1071-32 within this sublineage emerging in Siberia, Russia and present in other Russian regions. This cluster included only multi/extensive drug resistant (MDR/XDR) isolates. Based on the phylogenetic analysis of the available WGS data, we identified three synonymous SNPs in the genes Rv0144, Rv0373c, and Rv0334 that were specific for the Beijing 1071-32-cluster and developed a real-time PCR assay for their detection. Analysis of the 2375 genetically diverse M. tuberculosis isolates collected between 1996 and 2020 in different locations (European and Asian parts of Russia, former Soviet Union countries, Albania, Greece, China, Vietnam, Japan and Brazil), confirmed 100% specificity and sensitivity of this real-time PCR assay. Moreover, the epidemiological importance of this strain and the newly developed screening assay is further stressed by the fact that all identified Beijing 1071-32 isolates were found to exhibit MDR genotypic profiles with concomitant resistance to additional first-line drugs due to a characteristic signature of six mutations in rpoB450, rpoC485, katG315, katG335, rpsL43 and embB497. In conclusion, this study provides a set of three concordant SNPs for the detection and screening of Beijing 1071-32 isolates along with a validated real-time PCR assay easily deployable across multiple settings for the epidemiological tracking of this significant MDR cluster.

Tuberculosis in Australia's tropical north: a population-based genomic epidemiological study

BACKGROUND

The Northern Territory (NT) has the highest tuberculosis (TB) rate of all Australian jurisdictions. We combined TB public health surveillance data with genomic sequencing of Mycobacterium tuberculosis isolates in the tropical 'Top End' of the NT to investigate trends in TB incidence and transmission.

METHODS

This retrospective observational study included all 741 culture-confirmed cases of TB in the Top End over three decades from 1989-2020. All 497 available M. tuberculosis isolates were sequenced. We used contact tracing data to define a threshold pairwise SNP distance for hierarchical single linkage clustering, and examined putative transmission clusters in the context of epidemiologic information.

FINDINGS

There were 359 (48%) cases born overseas, 329 (44%) cases among Australian First Nations peoples, and 52 (7%) cases were Australian-born and non-Indigenous. The annual incidence in First Nations peoples from 1989-2019 fell from average 50.4 to 11.0 per 100,000 (P<0·001). First Nations cases were more likely to die from TB (41/329, 12·5%) than overseas-born cases (11/359, 3·1%; P<0·001). Using a threshold of ≤12 SNPs, 28 clusters of between 2-64 individuals were identified, totalling 250 cases; 214 (86%) were First Nations cases and 189 (76%) were from a remote region. The time between cases and past epidemiologically- and genomically-linked contacts ranged from 4·5 months to 24 years.

INTERPRETATION

Our findings support prioritisation of timely case detection, contact tracing augmented by genomic sequencing, and latent TB treatment to break transmission chains in Top End remote hotspot regions.

Genetic diversity of candidate loci linked to Mycobacterium tuberculosis resistance to bedaquiline, delamanid and pretomanid

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is one of the deadliest infectious diseases worldwide. Multidrug and extensively drug-resistant strains are making disease control difficult, and exhausting treatment options. New anti-TB drugs bedaquiline (BDQ), delamanid (DLM) and pretomanid (PTM) have been approved for the treatment of multi-drug resistant TB, but there is increasing resistance to them. Nine genetic loci strongly linked to resistance have been identified (mmpR5, atpE, and pepQ for BDQ; ddn, fgd1, fbiA, fbiB, fbiC, and fbiD for DLM/PTM). Here we investigated the genetic diversity of these loci across >33,000 M. tuberculosis isolates. In addition, epistatic mutations in mmpL5-mmpS5 as well as variants in ndh, implicated for DLM/PTM resistance in M. smegmatis, were explored. Our analysis revealed 1,227 variants across the nine genes, with the majority (78%) present in isolates collected prior to the roll-out of BDQ and DLM/PTM. We identified phylogenetically-related mutations, which are unlikely to be resistance associated, but also high-impact variants such as frameshifts (e.g. in mmpR5, ddn) with likely functional effects, as well as non-synonymous mutations predominantly in MDR-/XDR-TB strains with predicted protein destabilising effects. Overall, our work provides a comprehensive mutational catalogue for BDQ and DLM/PTM associated genes, which will assist with establishing associations with phenotypic resistance; thereby, improving the understanding of the causative mechanisms of resistance for these drugs, leading to better treatment outcomes.

Structural and Genomic Insights Into Pyrazinamide Resistance in Mycobacterium tuberculosis Underlie Differences Between Ancient and Modern Lineages

Resistance to drugs used to treat tuberculosis disease (TB) continues to remain a public health burden, with missense point mutations in the underlying Mycobacterium tuberculosis bacteria described for nearly all anti-TB drugs. The post-genomics era along with advances in computational and structural biology provide opportunities to understand the interrelationships between the genetic basis and the structural consequences of M. tuberculosis mutations linked to drug resistance. Pyrazinamide (PZA) is a crucial first line antibiotic currently used in TB treatment regimens. The mutational promiscuity exhibited by the pncA gene (target for PZA) necessitates computational approaches to investigate the genetic and structural basis for PZA resistance development. We analysed 424 missense point mutations linked to PZA resistance derived from ∼35K M. tuberculosis clinical isolates sourced globally, which comprised the four main M. tuberculosis lineages (Lineage 1-4). Mutations were annotated to reflect their association with PZA resistance. Genomic measures (minor allele frequency and odds ratio), structural features (surface area, residue depth and hydrophobicity) and biophysical effects (change in stability and ligand affinity) of point mutations on pncA protein stability and ligand affinity were assessed. Missense point mutations within pncA were distributed throughout the gene, with the majority (>80%) of mutations with a destabilising effect on protomer stability and on ligand affinity. Active site residues involved in PZA binding were associated with multiple point mutations highlighting mutational diversity due to selection pressures at these functionally important sites. There were weak associations between genomic measures and biophysical effect of mutations. However, mutations associated with PZA resistance showed statistically significant differences between structural features (surface area and residue depth), but not hydrophobicity score for mutational sites. Most interestingly M. tuberculosis lineage 1 (ancient lineage) exhibited a distinct protein stability profile for mutations associated with PZA resistance, compared to modern lineages.

Characterization of rifampicin-resistant Mycobacterium tuberculosis in Khyber Pakhtunkhwa, Pakistan

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is endemic in Pakistan. Resistance to both firstline rifampicin and isoniazid drugs (multidrug-resistant TB; MDR-TB) is hampering disease control. Rifampicin resistance is attributed to rpoB gene mutations, but rpoA and rpoC loci may also be involved. To characterise underlying rifampicin resistance mutations in the TB endemic province of Khyber Pakhtunkhwa, we sequenced 51 M. tuberculosis isolates collected between 2016 and 2019; predominantly, MDR-TB (n = 44; 86.3%) and lineage 3 (n = 30, 58.8%) strains. We found that known mutations in rpoB (e.g. S405L), katG (e.g. S315T), or inhA promoter loci explain the MDR-TB. There were 24 unique mutations in rpoA, rpoB, and rpoC genes, including four previously unreported. Five instances of within-host resistance diversity were observed, where two were a mixture of MDR-TB strains containing mutations in rpoB, katG, and the inhA promoter region, as well as compensatory mutations in rpoC. Heteroresistance was observed in two isolates with a single lineage. Such complexity may reflect the high transmission nature of the Khyber Pakhtunkhwa setting. Our study reinforces the need to apply sequencing approaches to capture the full-extent of MDR-TB genetic diversity, to understand transmission, and to inform TB control activities in the highly endemic setting of Pakistan.

Phenotypic and genotypic features of the Mycobacterium tuberculosis lineage 1 subgroup in central Vietnam

Mycobacterium tuberculosis (Mtb) has different features depending on different geographic areas. We collected Mtb strains from patients with smear-positive pulmonary tuberculosis in Da Nang, central Vietnam. Using a whole genome sequencing platform, including genome assembly complemented by long-read-sequencing data, genomic characteristics were studied. Of 181 Mtb isolates, predominant Vietnamese EAI4_VNM and EAI4-like spoligotypes (31.5%), ZERO strains (5.0%), and part of EAI5 (11.1%) were included in a lineage-1 (L1) sublineage, i.e., L1.1.1.1. These strains were found less often in younger people, and they genetically clustered less frequently than other modern strains. Patients infected with ZERO strains demonstrated less lung infiltration. A region in RD2bcg spanning six loci, i.e., PE_PGRS35, cfp21, Rv1985c, Rv1986, Rv1987, and erm(37), was deleted in EAI4_VNM, EAI4-like, and ZERO strains, whereas another 118 bp deletion in furA was specific only to ZERO strains. L1.1.1.1-sublineage-specific deletions in PE_PGRS4 and PE_PGRS22 were also identified. RD900, seen in ancestral lineages, was present in majority of the L1 members. All strains without IS6110 (5.0%) had the ZERO spoligo-pattern. Distinctive features of the ancestral L1 strains provide a basis for investigation of the modern versus ancestral Mtb lineages and allow consideration of countermeasures against this heterogeneous pathogen.

Underwhelming or Misunderstood? Genetic Variability of Pattern Recognition Receptors in Immune Responses and Resistance to Mycobacterium tuberculosis

Human genetic control is thought to affect a considerable part of the outcome of infection with Mycobacterium tuberculosis (Mtb). Most of us deal with the pathogen by containment (associated with clinical "latency") or sterilization, but tragically millions each year do not. After decades of studies on host genetic susceptibility to Mtb infection, genetic variation has been discovered to play a role in tuberculous immunoreactivity and tuberculosis (TB) disease. Genes encoding pattern recognition receptors (PRRs) enable a consistent, molecularly direct interaction between humans and Mtb which suggests the potential for co-evolution. In this review, we explore the roles ascribed to PRRs during Mtb infection and ask whether such a longstanding and intimate interface between our immune system and this pathogen plays a critical role in determining the outcome of Mtb infection. The scientific evidence to date suggests that PRR variation is clearly implicated in altered immunity to Mtb but has a more subtle role in limiting the pathogen and pathogenesis. In contrast to 'effectors' like IFN-γ, IL-12, Nitric Oxide and TNF that are critical for Mtb control, 'sensors' like PRRs are less critical for the outcome of Mtb infection. This is potentially due to redundancy of the numerous PRRs in the innate arsenal, such that Mtb rarely goes unnoticed. Genetic association studies investigating PRRs during Mtb infection should therefore be designed to investigate endophenotypes of infection - such as immunological or clinical variation - rather than just TB disease, if we hope to understand the molecular interface between innate immunity and Mtb.

Insight into the drug resistance whole genome of Mycobacterium tuberculosis isolates from Khyber Pakhtunkhwa, Pakistan

Whole genome sequencing (WGS) is one of the most reliable methods for detection of drug resistance, genetic diversity in other virulence factor and also evolutionary dynamics of Mycobacterium tuberculosis complex (MTBC). First-line anti-tuberculosis drugs are the major weapons against Mycobacterium tuberculosis (MTB). However, the emergence of drug resistance remained a major obstacle towards global tuberculosis (TB) control program 2030, especially in high burden countries including Pakistan. To overcome the resistance and design potent drugs, genomic variations in drugs targets as well as in the virulence and evolutionary factors might be useful for better understanding and designing potential inhibitors. Here we aimed to find genomic variations in the first-line drugs targets, along with other virulence and evolutionary factors among the circulating isolates in Khyber Pakhtunkhwa, Pakistan. Samples were collected and drug susceptibility testing (DST) was performed as per WHO standard. The resistance samples were subjected to WGS. Among the five whole genome sequences, three samples (NCBI BioProject Accession: PRJNA629298, PRJNA629388) harbored 1997, 1162, and 2053 mutations. Some novel mutations have been detected in drugs targets. Similarly, numerous novel variants have also been detected in virulency and evolutionary factors, PE, PPE, and secretory system of MTB isolates. Exploring the genomic variations among the circulating isolates in geographical specific locations might be useful for future drug designing. To the best of our knowledge, this is the first study that provides useful data regarding the insight genomic variations in virulency, evolutionary factors including ESX and PE/PPE as well as drug targets, for better understanding and management of TB in a WHO declared high burden country.