Direct transmission of within-host Mycobacterium tuberculosis diversity to secondary cases can lead to variable between-host heterogeneity without de novo mutation: A genomic investigation

A Genome-Focused Investigation Reveals the Emergence of a Mycobacterium tuberculosis Strain Related to Multidrug-Resistant Tuberculosis in the Amazon Region of Brazil

A previous study in Pará, Northern Brazil, described a strain of Mycobacterium tuberculosis with a unique genotype (SIT2517/T1) associated with multidrug-resistant tuberculosis (MDR-TB). To improve our understanding of MDR-TB transmission dynamics of these strains within this region, we performed phenotypic and genotypic drug susceptibility testing (pDST/gDST), 24-loci mycobacterial interspersed repetitive units (MIRU-VNTR) genotyping, whole-genome sequencing (WGS) and geo-epidemiology analysis. Of the 28 SIT2517/T1 isolates, 19 (67.9%) could be genotyped by 24-loci MIRU-VNTR and 15 by WGS. All belonged to sublineage 4.1.1.3, distinct from other representative Lineage 4 isolates identified in Brazil. The MDR phenotype determined by pDST was confirmed by gDST, the latter also demonstrating the presence of additional mutations conferring pre-extensively drug-resistance (pre-XDR). Discrepancies between gDST and pDST were observed for pyrazinamide and fluoroquinolones. Thirteen out of 15 isolates analyzed by WGS were clustered when applying a 12 single nucleotide polymorphisms (SNPs) cutoff. The SIT2517/T1 isolates were distributed across the metropolitan regions of Belém and Collares municipalities, showing no geographic clustering. WGS-transmission network analysis revealed a high likelihood of direct transmission and the formation of two closely linked transmission chains. This study highlights the need to implement TB genomic surveillance in the Brazilian Amazon region.

Signatures of transmission in within-host M. tuberculosis variation

Background

Because M. tuberculosis evolves slowly, transmission clusters often contain multiple individuals with identical consensus genomes, making it difficult to reconstruct transmission chains. Finding additional sources of shared M. tuberculosis variation could help overcome this problem. Previous studies have reported M. tuberculosis diversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear.

Methods

To evaluate the transmission information present in within-host M. tuberculosis variation, we re-analyzed publicly available sequence data from three household transmission studies, using household membership as a proxy for transmission linkage between donor-recipient pairs.

Findings

We found moderate levels of minority variation present in M. tuberculosis sequence data from cultured isolates that varied significantly across studies (mean: 6, 7, and 170 minority variants above a 1% minor allele frequency threshold, outside of PE/PPE genes). Isolates from household members shared more minority variants than did isolates from unlinked individuals in the three studies (mean 98 shared minority variants vs. 10; 0.8 vs. 0.2, and 0.7 vs. 0.2, respectively). Shared within-host variation was significantly associated with household membership (OR: 1.51 [1.30,1.71], for one standard deviation increase in shared minority variants). Models that included shared within-host variation improved the accuracy of predicting household membership in all three studies as compared to models without within-host variation (AUC: 0.95 versus 0.92, 0.99 versus 0.95, and 0.93 versus 0.91).

Interpretation

Within-host M. tuberculosis variation persists through culture and could enhance the resolution of transmission inferences. The substantial differences in minority variation recovered across studies highlights the need to optimize approaches to recover and incorporate within-host variation into automated phylogenetic and transmission inference.

Funding

NIAID: 5K01AI173385.

Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis

Mixed infections of Mycobacterium tuberculosis, defined as the coexistence of multiple genetically distinct strains within a single host, have been associated with unfavorable treatment outcomes. Different methods have been used to detect mixed infections, but their performances have not been carefully evaluated. To compare the sensitivity of whole-genome sequencing (WGS) and variable-number tandem repeats (VNTR) typing to detect mixed infections, we prepared 10 artificial samples composed of DNA mixtures from two strains in different proportions and retrospectively collected 1,084 clinical isolates. The limit of detection (LOD) for the presence of a minor strain was 5% for both WGS and VNTR typing. The overall clinical detection rate of mixed infections was 3.7% (40/1,084) for the two methods combined, WGS identified 37/1,084 (3.4%), and VNTR typing identified 14/1,084 (1.3%), including 11 also identified by WGS. Multivariate analysis demonstrated that retreatment patients had a 2.7 times (95% confidence interval [CI], 1.2 to 6.0) higher risk of mixed infections than new cases. Collectively, WGS is a more reliable tool to identify mixed infections than VNTR typing, and mixed infections are more common in retreated patients. IMPORTANCE Mixed infections of M. tuberculosis have the potential to render treatment regimens ineffective and affect the transmission dynamics of the disease. VNTR typing, currently the most widely used method for the detection of mixed infections, detects mixed infections only by interrogating a small fraction of the M. tuberculosis genome, which necessarily limits sensitivity. With the introduction of WGS, it became possible to study the entire genome, but no quantitative comparison has yet been undertaken. Our systematic comparison of the ability of WGS and VNTR typing to detect mixed infections, using both artificial samples and clinical isolates, revealed the superior performance of WGS at a high sequencing depth (~100×) and found that mixed infections are more common in patients being retreated for tuberculosis (TB) in the populations studied. This provides valuable information for the application of WGS in the detection of mixed infections and the implications of mixed infections for tuberculosis control.

Genomic Sequencing Profiles of Mycobacterium tuberculosis in Mandalay Region, Myanmar

This study aimed to characterize whole-genome sequencing (WGS) information of Mycobacterium tuberculosis (Mtb) in the Mandalay region of Myanmar. It was a cross-sectional study conducted with 151 Mtb isolates obtained from the fourth nationwide anti-tuberculosis (TB) drug-resistance survey. Frequency of lineages 1, 2, 3, and 4 were 55, 65, 9, and 22, respectively. The most common sublineage was L1.1.3.1 (n = 31). Respective multi-drug resistant tuberculosis (MDR-TB) frequencies were 1, 1, 0, and 0. Four clusters of 3 (L2), 2 (L4), 2 (L1), and 2 (L2) isolates defined by a 20-single-nucleotide variant (SNV) cutoff were detected. Simpson's index for sublineages was 0.0709. Such high diversity suggests that the area probably had imported Mtb from many geographical sources. Relatively few genetic clusters and MDR-TB suggest there is a chance the future control will succeed if it is carried out properly.

Whole genome sequencing analysis to evaluate the influence of T2DM on polymorphisms associated with drug resistance in M. tuberculosis

Background

Type 2 diabetes mellitus (T2DM) has been associated with treatment failure, and the development of drug resistance in tuberculosis (TB). Also, whole-genome sequencing has provided a better understanding and allowed the growth of knowledge about polymorphisms in genes associated with drug resistance. Considering the above, this study analyzes genome sequences to evaluate the influence of type 2 diabetes mellitus in the development of mutations related to tuberculosis drug resistance. M. tuberculosis isolates from individuals with (n = 74), and without (n = 74) type 2 diabetes mellitus was recovered from online repositories, and further analyzed.

Results

The results showed the presence of 431 SNPs with similar proportions between diabetics, and non-diabetics individuals (48% vs. 52%), but with no significant relationship. A greater number of mutations associated with rifampicin resistance was observed in the T2DM-TB individuals (23.2% vs. 16%), and the exclusive presence of rpoBQ432L, rpoBQ432P, rpoBS441L, and rpoBH445L variants. While these variants are not private to T2DM-TB cases they are globally rare highlighting a potential role of T2DM. The phylogenetic analysis showed 12 sublineages, being 4.1.1.3, and 4.1.2.1 the most prevalent in T2DM-TB individuals but not differing from those most prevalent in their geographic location. Four clonal complexes were found, however, no significant relationship with T2DM was observed. Samples size and potential sampling biases prevented us to look for significant associations.

Conclusions

The occurrence of globally rare rifampicin variants identified only in isolates from individuals with T2DM could be due to the hyperglycemic environment within the host. Therefore, further studies about the dynamics of SNPs’ generation associated with antibiotic resistance in patients with diabetes mellitus are necessary.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08709-z.

MycoVarP: Mycobacterium Variant and Drug Resistance Prediction Pipeline for Whole-Genome Sequence Data Analysis

Whole-genome sequencing (WGS) provides a comprehensive tool to analyze the bacterial genomes for genotype–phenotype correlations, diversity of single-nucleotide variant (SNV), and their evolution and transmission. Several online pipelines and standalone tools are available for WGS analysis of Mycobacterium tuberculosis (Mtb) complex (MTBC). While they facilitate the processing of WGS data with minimal user expertise, they are either too general, providing little insights into bacterium-specific issues such as gene variations, INDEL/synonymous/PE-PPE (IDP family), and drug resistance from sample data, or are limited to specific objectives, such as drug resistance. It is understood that drug resistance and lineage-specific issues require an elaborate prioritization of identified variants to choose the best target for subsequent therapeutic intervention. Mycobacterium variant pipeline (MycoVarP) addresses these specific issues with a flexible battery of user-defined and default filters. It provides an end-to-end solution for WGS analysis of Mtb variants from the raw reads and performs two quality checks, viz, before trimming and after alignments of reads to the reference genome. MycoVarP maps the annotated variants to the drug-susceptible (DS) database and removes the false-positive variants, provides lineage identification, and predicts potential drug resistance. We have re-analyzed the WGS data reported by Advani et al. (2019) using MycoVarP and identified some additional variants not reported so far. We conclude that MycoVarP will help in identifying nonsynonymous, true-positive, drug resistance–associated variants more effectively and comprehensively, including those within the IDP of the PE-PPE/PGRS family, than possible from the currently available pipelines.

Mutation of Mycobacterium tuberculosis and Implications for Using Whole-Genome Sequencing for Investigating Recent Tuberculosis Transmission

Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis (Mtb) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of WGS results. To estimate the association between infection duration and single nucleotide polymorphism (SNP) accumulation in the Mtb genome, we first analyzed pairwise SNP differences among TB cases from Los Angeles County, California, with strong epidemiologic links. We found that SNP distance alone was insufficient for concluding that cases are linked through recent transmission. Second, we describe a well-characterized cluster of TB cases in California to illustrate the role of genomic data in conclusions regarding recent transmission. Longer presumed latent periods were inconsistently associated with larger SNP differences. Our analyses suggest that WGS alone cannot be used to definitively determine that a case is attributable to recent transmission. Methods for integrating clinical, epidemiologic, and genomic data can guide conclusions regarding the likelihood of recent transmission, providing local public health practitioners with better tools for monitoring and investigating TB transmission.

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.

The within-host evolution of antimicrobial resistance in Mycobacterium tuberculosis

Tuberculosis (TB) has been responsible for the greatest number of human deaths due to an infectious disease in general, and due to antimicrobial resistance (AMR) in particular. The etiological agents of human TB are a closely-related group of human-adapted bacteria that belong to the Mycobacterium tuberculosis complex (MTBC). Understanding how MTBC populations evolve within-host may allow for improved TB treatment and control strategies. In this review, we highlight recent works that have shed light on how AMR evolves in MTBC populations within individual patients. We discuss the role of heteroresistance in AMR evolution, and review the bacterial, patient and environmental factors that likely modulate the magnitude of heteroresistance within-host. We further highlight recent works on the dynamics of MTBC genetic diversity within-host, and discuss how spatial substructures in patients' lungs, spatiotemporal heterogeneity in antimicrobial concentrations and phenotypic drug tolerance likely modulates the dynamics of MTBC genetic diversity in patients during treatment. We note the general characteristics that are shared between how the MTBC and other bacterial pathogens evolve in humans, and highlight the characteristics unique to the MTBC.

Analysis of Serial Multidrug-Resistant Tuberculosis Strains Causing Treatment Failure and Within-Host Evolution by Whole-Genome Sequencing

The cure rate of multidrug-resistant tuberculosis (MDR-TB) is relatively low in China. The reasons for the treatment failure and within-host evolution during treatment have not been sufficiently studied. All MDR-TB patients receiving standard treatment from January 2014 to September 2016 at a designated TB Hospital in Zhejiang Province were retrospectively included and grouped according to their known treatment outcome. Clinical information was collected. Baseline strains of all patients and serial strains of treatment-failure patients were revived. Drug susceptibility tests (DSTs) of 14 drugs and single nucleotide polymorphism (SNP) analysis based on whole-genome sequencing (WGS) were performed. The genetic distance and within-host evolution were investigated based on SNPs. In total, 20 treatment failure patients and 74 patients who succeeded in treatment were included. The number of effective drugs for patients who failed treatment was no more than three. Eighteen (90.0%) treatment-failure patients were characterized by a continuous infection of the primary strain, of which 14 patients (77.8%) developed phenotypic or genotypic acquired drug resistance under ineffective treatment. Acquired resistance to amikacin and moxifloxacin (2.0 mg/ml) was detected most frequently, in 5 and 4 patients, respectively. The insufficient number of effective drugs in the combined treatment regimen was the main reason for MDR-TB treatment failure. The study emphasizes the importance of DST for second-line drugs when implementing the second-line drug regimen in MDR-TB patients. For patients with risk factors for MDR-TB, DST of second-line antituberculosis drugs should be performed at initiation of treatment. Second-line drugs should be selected based on the results of DST to avoid acquired resistance. WGS detects low-frequency resistance mutations and heterogeneous resistance with high sensitivity, which is of great significance for guiding clinical treatment and preventing acquired resistance.IMPORTANCE Few studies have focused on the reasons for the low cure rate of multidrug-resistant tuberculosis in China and within-host evolution during treatment, which is of great significance for improving clinical treatment regimens. Acquired resistance events were common during the ineffective treatment, among which resistance to amikacin and high-level moxifloxacin were the most common. The main reason for the treatment failure of MDR-TB patients was insufficient effective drugs, which may lead to higher levels of drug resistance in MDR-TB strains. Therefore, the study emphasizes the importance of DST in the development of second-line treatment regimen when there is a risk of MDR. By performing whole-genome sequencing of serial strains from patients with treatment failure, we found that WGS can detect low-frequency resistance mutations and heterogeneous resistance with high sensitivity. It is thus recommended to conduct drug susceptibility tests at the beginning of treatment and repeat the DST when the sputum bacteria remain positive.

Mechanisms of Drug-Induced Tolerance in Mycobacterium tuberculosis

Successful treatment of tuberculosis (TB) can be hampered by Mycobacterium tuberculosis populations that are temporarily able to survive antibiotic pressure in the absence of drug resistance-conferring mutations, a phenomenon termed drug tolerance. We summarize findings on M. tuberculosis tolerance published in the past 20 years. Key M. tuberculosis responses to drug pressure are reduced growth rates, metabolic shifting, and the promotion of efflux pump activity. Metabolic shifts upon drug pressure mainly occur in M. tuberculosis's lipid metabolism and redox homeostasis, with reduced tricarboxylic acid cycle activity in favor of lipid anabolism. Increased lipid anabolism plays a role in cell wall thickening, which reduces sensitivity to most TB drugs. In addition to these general mechanisms, drug-specific mechanisms have been described. Upon isoniazid exposure, M. tuberculosis reprograms several pathways associated with mycolic acid biosynthesis. Upon rifampicin exposure, M. tuberculosis upregulates the expression of its drug target rpoB Upon bedaquiline exposure, ATP synthesis is stimulated, and the transcription factors Rv0324 and Rv0880 are activated. A better understanding of M. tuberculosis's responses to drug pressure will be important for the development of novel agents that prevent the development of drug tolerance following treatment initiation. Such agents could then contribute to novel TB treatment-shortening strategies.

The population genomics of within-host Mycobacterium tuberculosis

Recent progress in genomic sequencing from patient samples has allowed for the first detailed insight into the within-host genetic diversity of Mycobacterium tuberculosis (M.TB), revealing remarkably low levels of variation. While this has often been attributed to low mutation rates, other factors have been described, including resistance evolution (i.e., selective sweeps), widespread purifying and background selection, and, more recently, progeny skew. Here we review recent findings pertaining to the processes governing the evolutionary dynamics of M.TB, discuss their implications for improving our understanding of this important human pathogen, and make recommendations for future work. Significantly, this emerging evolutionary framework involving the joint estimation of demographic, selective, and reproductive processes is forming a new paradigm for the study of within-host pathogen evolution that will be widely applicable across organisms.

Whole-genome sequencing and Mycobacterium tuberculosis: Challenges in sample preparation and sequencing data analysis

The numbers of patients with tuberculosis (TB) caused by resistant strains are still alarming. Therefore, it is necessary to determine resistance more quickly and precisely, than it is with the currently used phenotypic and genotypic methods. In recent years, technological advances have been made and the whole-genome sequencing (WGS) method has been introduced as a part of routine diagnostics in clinical laboratories. Comparing a wide range of mycobacterial genomic variations with a reference genome leads to a consistent evaluation of molecular-epidemiology and resistance of Mycobacterium tuberculosis (M. tuberculosis) to a wide range of anti-TB drugs. The quality of the obtained sequencing data is closely related to the type of sample and the method used for DNA extraction and sequencing library preparation. Moreover, the correct interpretation of results is also influenced by a bioinformatic data processing. A large number of bioinformatics pipelines are currently available, the sensitivity of which varies due to the different sizes of databases containing relevant mutations. This review focuses on the individual steps included in the sequencing workflow and factors that may affect the interpretation of final results.

Contaminant DNA in bacterial sequencing experiments is a major source of false genetic variability

Background

Contaminant DNA is a well-known confounding factor in molecular biology and in genomic repositories. Strikingly, analysis workflows for whole-genome sequencing (WGS) data commonly do not account for errors potentially introduced by contamination, which could lead to the wrong assessment of allele frequency both in basic and clinical research.

Results

We used a taxonomic filter to remove contaminant reads from more than 4000 bacterial samples from 20 different studies and performed a comprehensive evaluation of the extent and impact of contaminant DNA in WGS. We found that contamination is pervasive and can introduce large biases in variant analysis. We showed that these biases can result in hundreds of false positive and negative SNPs, even for samples with slight contamination. Studies investigating complex biological traits from sequencing data can be completely biased if contamination is neglected during the bioinformatic analysis, and we demonstrate that removing contaminant reads with a taxonomic classifier permits more accurate variant calling. We used both real and simulated data to evaluate and implement reliable, contamination-aware analysis pipelines.

Conclusion

As sequencing technologies consolidate as precision tools that are increasingly adopted in the research and clinical context, our results urge for the implementation of contamination-aware analysis pipelines. Taxonomic classifiers are a powerful tool to implement such pipelines.

Previously undetected super-spreading of Mycobacterium tuberculosis revealed by deep sequencing

Tuberculosis disproportionately affects the Canadian Inuit. To address this, it is imperative we understand transmission dynamics in this population. We investigate whether 'deep' sequencing can provide additional resolution compared to standard sequencing, using a well-characterized outbreak from the Arctic (2011-2012, 50 cases). Samples were sequenced to ~500-1000x and reads were aligned to a novel local reference genome generated with PacBio SMRT sequencing. Consensus and heterogeneous variants were identified and compared across genomes. In contrast with previous genomic analyses using ~50x depth, deep sequencing allowed us to identify a novel super-spreader who likely transmitted to up to 17 other cases during the outbreak (35% of the remaining cases that year). It is increasingly evident that within-host diversity should be incorporated into transmission analyses; deep sequencing may facilitate more accurate detection of super-spreaders and transmission clusters. This has implications not only for TB, but all genomic studies of transmission - regardless of pathogen.