Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection

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.

The detection of mixed tuberculosis infections using culture filtrate and resuscitation promoting factor deficient filtrate

Tuberculosis (TB) infected individuals harbor a heterogenous population of differentially culturable tubercle bacilli (DCTB). Herein, we describe how DCTB assays using culture filtrate either containing or deficient in resuscitation promoting factors can uncover mixed infections. We demonstrate that Mycobacterium tuberculosis (Mtb) strain genotypes can be separated in DCTB assays based on their selective requirement for growth stimulatory factors. Beijing mixed infections appear to be associated with a higher bacterial load and reduced reliance on growth stimulatory factors. These data have important implications for identifying mixed infections and hetero-resistance, which in turn can affect selection of treatment regimen and establishment of transmission links.

M. tuberculosis microvariation is common and is associated with transmission: analysis of three years prospective universal sequencing in England

BACKGROUND

The prevalence, association with disease status, and public health impact of infection with mixtures of M. tuberculosis strains is unclear, in part due to limitations of existing methods for detecting mixed infections.

METHODS

We developed an algorithm to identify mixtures of M. tuberculosis strains using next generation sequencing data, assessing performance using simulated sequences. We identified mixed M. tuberculosis strains when there was at least one mixed nucleotide position, and where both the mixture's components were present in similar isolates from other individuals, compatible with transmission of the component strains. We determined risk factors for mixed infection among isolations of M. tuberculosis in England using logistic regression. We used survival analyses to assess the association between mixed infection and putative transmission.

FINDINGS

6,560 isolations of TB were successfully sequenced in England 2016-2018. Of 3,691 (56%) specimens for which similar sequences had been isolated from at least two other individuals, 341 (9.2%) were mixed. Mixed infection was more common in lineages other than Lineage 4. Among the 1,823 individuals with pulmonary infection with Lineage 4 M. tuberculosis, mixed infection was associated with significantly increased risk of subsequent isolation of closely related organisms from a different individual (HR 1.43, 95% CI 1.05,1.94), indicative of transmission.

INTERPRETATION

Mixtures of transmissible strains occur in at least 5% of tuberculosis infections in England; when present in pulmonary disease, such mixtures are associated with an increased risk of tuberculosis transmission.

FUNDING

Public Health England; NIHR Health Protection Research Units; European Union.

Possible Transmission Mechanisms of Mixed Mycobacterium tuberculosis Infection in High HIV Prevalence Country, Botswana

Tuberculosis caused by concurrent infection with multiple Mycobacteriumtuberculosis strains (i.e., mixed infection) challenges clinical and epidemiologic paradigms. We explored possible transmission mechanisms of mixed infection in a population-based, molecular epidemiology study in Botswana during 2012–2016. We defined mixed infection as multiple repeats of alleles at >2 loci within a discrete mycobacterial interspersed repetitive unit–variable-number tandem-repeat (MIRU-VNTR) result. We compared mixed infection MIRU-VNTR results with all study MIRU-VNTR results by considering all permutations at each multiple allele locus; matched MIRU-VNTR results were considered evidence of recently acquired strains and nonmatched to any other results were considered evidence of remotely acquired strains. Among 2,051 patients, 34 (1.7%) had mixed infection, of which 23 (68%) had recently and remotely acquired strains. This finding might support the mixed infection mechanism of recent transmission and simultaneous remote reactivation. Further exploration is needed to determine proportions of transmission mechanisms in settings where mixed infections are prevalent.

Genomic analyses of Mycobacterium tuberculosis from human lung resections reveal a high frequency of polyclonal infections

Polyclonal infections occur when at least two unrelated strains of the same pathogen are detected in an individual. This has been linked to worse clinical outcomes in tuberculosis, as undetected strains with different antibiotic resistance profiles can lead to treatment failure. Here, we examine the amount of polyclonal infections in sputum and surgical resections from patients with tuberculosis in the country of Georgia. For this purpose, we sequence and analyse the genomes of Mycobacterium tuberculosis isolated from the samples, acquired through an observational clinical study (NCT02715271). Access to the lung enhanced the detection of multiple strains (40% of surgery cases) as opposed to just using a sputum sample (0-5% in the general population). We show that polyclonal infections often involve genetically distant strains and can be associated with reversion of the patient's drug susceptibility profile over time. In addition, we find different patterns of genetic diversity within lesions and across patients, including mutational signatures known to be associated with oxidative damage; this suggests that reactive oxygen species may be acting as a selective pressure in the granuloma environment. Our results support the idea that the magnitude of polyclonal infections in high-burden tuberculosis settings is underestimated when only testing sputum samples.

Mycoplasma agassizii, an opportunistic pathogen of tortoises, shows very little genetic variation across the Mojave and Sonoran Deserts

Mycoplasma agassizii is a common cause of upper respiratory tract disease in Mojave desert tortoises (Gopherus agassizii). So far, only two strains of this bacterium have been sequenced, and very little is known about its patterns of genetic diversity. Understanding genetic variability of this pathogen is essential to implement conservation programs for their threatened, long-lived hosts. We used next generation sequencing to explore the genomic diversity of 86 cultured samples of M. agassizii collected from mostly healthy Mojave and Sonoran desert tortoises in 2011 and 2012. All samples with enough sequencing coverage exhibited a higher similarity to M. agassizii strain PS6^T (collected in Las Vegas Valley, Nevada) than to strain 723 (collected in Sanibel Island, Florida). All eight genomes with a sequencing coverage over 2x were subjected to multiple analyses to detect single-nucleotide polymorphisms (SNPs). Strikingly, even though we detected 1373 SNPs between strains PS6^T and 723, we did not detect any SNP between PS6^T and our eight samples. Our whole genome analyses reveal that M. agassizii strain PS6^T may be present across a wide geographic extent in healthy Mojave and Sonoran desert tortoises.

Mycobacterium tuberculosis polyclonal infections through treatment and recurrence

Background

Mixed/polyclonal infections due to different genotypes are reported in Tuberculosis. The current study was designed to understand the fate of mixed infections during the course of treatment and follow-up and its role in disease pathogenesis.

Methods

Sputum samples were collected on 0,1,2,3,6,12 and 24 months from 157 treatment-naïve patients, cultures subjected to Drug-Susceptibility-testing (MGIT 960), spoligotyping, MIRU-VNTR and SNP genotyping. All isolated colonies on thin layer agar (7H11) were subjected to spoligotyping.

Findings

One thirty three baseline cultures were positive (133/157, 84.7%), 43(32.3%) had mixture of genotypes. Twenty-four of these patients (55.8%) showed change in genotype while six showed different drug-susceptibility patterns while on treatment. Twenty-three (53.5%) patients with polyclonal infections showed resistance to at least one drug compared to 10/90 (11.1%) monoclonal infections (P<0.0001). Eight patients had recurrent TB, two with a new genotype and two with altered phenotypic DST.

Conclusions

The coexistence of different genotypes and change of genotypes during the same disease episode, while on treatment, confirms constancy of polyclonal infections. The composition of the mixture of genotypes and the relative predominance may be missed by culture due to its limit of detection. Polyclonal infections in TB could be a rule rather than exception and challenges the age-old dogma of reactivation/reinfection.

Computational Methods for Strain-Level Microbial Detection in Colony and Metagenome Sequencing Data

Metagenomic sequencing is a powerful tool for examining the diversity and complexity of microbial communities. Most widely used tools for taxonomic profiling of metagenomic sequence data allow for a species-level overview of the composition. However, individual strains within a species can differ greatly in key genotypic and phenotypic characteristics, such as drug resistance, virulence and growth rate. Therefore, the ability to resolve microbial communities down to the level of individual strains within a species is critical to interpreting metagenomic data for clinical and environmental applications, where identifying a particular strain, or tracking a particular strain across a set of samples, can help aid in clinical diagnosis and treatment, or in characterizing yet unstudied strains across novel environmental locations. Recently published approaches have begun to tackle the problem of resolving strains within a particular species in metagenomic samples. In this review, we present an overview of these new algorithms and their uses, including methods based on assembly reconstruction and methods operating with or without a reference database. While existing metagenomic analysis methods show reasonable performance at the species and higher taxonomic levels, identifying closely related strains within a species presents a bigger challenge, due to the diversity of databases, genetic relatedness, and goals when conducting these analyses. Selection of which metagenomic tool to employ for a specific application should be performed on a case-by case basis as these tools have strengths and weaknesses that affect their performance on specific tasks. A comprehensive benchmark across different use case scenarios is vital to validate performance of these tools on microbial samples. Because strain-level metagenomic analysis is still in its infancy, development of more fine-grained, high-resolution algorithms will continue to be in demand for the future.

Prediction of the hidden genotype of mixed infection strains in Iranian tuberculosis patients

BACKGROUND

Patients with mixed-strain Mycobacterium tuberculosis infections may be at a high risk of poor treatment outcomes. However, the mechanisms through which mixed infections affect the clinical manifestations are not well recognized. Evidence suggests that failure to detect the pathogen diversity within the host can influence the clinical results. We aimed to investigate the effects of different genotypes in mixed infections and determine their relationship with heteroresistance in the treatment of Iranian tuberculosis patients.

METHODS

One of the genotypes was identified in the culture and another genotype pattern in the mixed infection was predicted by comparing the pattern of MIRU-VNTR between the clinical specimens and their respective cultures in each patient. For all patients, the drug susceptibility testing was carried out on three single colonies from each clinical sample. The follow-up of patients was carried out during six months of treatment.

RESULTS

Based on MIRU-VNTR profiles of clinical samples, we showed that 55.6% (25/45) of the Iranian patients included in the study had mixed infections. Patients with mixed infections had a higher rate of treatment failure, compared to others (P=0.03). By comparing clinical sample profiles to profiles obtained after culture, we were able to distinguish between major and hidden genotypes. Among hidden genotypes, Haarlem (L4.1.2) and Beijing (L2) were associated to treatment failure (6/8 patients).

CONCLUSIONS

To conclude, we propose a procedure using the MIRU-VNTR method to identify the different genotypes in mixed infections. The present findings suggest that genotypes with potentially higher pathogenicity may not be detected when performing experimental culture in patients with mixed infections.

Bacterial Genotyping of Central Nervous System Tuberculosis in South Africa: Heterogenic Mycobacterium tuberculosis Infection and Predominance of Lineage 4

Tuberculous meningitis (TBM), the most severe extrapulmonary manifestation of tuberculosis, is caused by the pathogen Mycobacterium tuberculosis The M. tuberculosis complex includes seven lineages, all described to harbor a unique geographical dissemination pattern and clinical presentation. In this study, we set out to determine whether a certain M. tuberculosis lineage demonstrated tropism to cause TBM in patients from Cape Town, South Africa. DNA was extracted from formalin-fixed paraffin-embedded central nervous system (CNS) tissue from a unique neuropathological cohort of 83 TBM patients, collected between 1975 and 2012. M. tuberculosis lineages 1, 2, 3, and 4 were determined using an allele-specific PCR and Sanger sequencing. Of the 83 patient specimens tested, bacterial characterization could be performed on 46 specimens (55%). M. tuberculosis lineage 4 was present in 26 patient specimens (56%), and non-lineage 4 was identified in 10 cases (22%). Moreover, genomic heterogeneity was detected in the CNS specimens of 7 adults and 3 children. We could show that infection of the CNS is not restricted to a single M. tuberculosis lineage and that even young children with rapid progression of disease can harbor more than one M. tuberculosis lineage in the CNS.

Identifying Mixed Mycobacterium tuberculosis Infection and Laboratory Cross-Contamination during Mycobacterial Sequencing Programs

The detection of laboratory cross-contamination and mixed tuberculosis infections is an important goal of clinical mycobacteriology laboratories. The objective of this study was to develop a method to detect mixtures of different Mycobacterium tuberculosis lineages in laboratories performing mycobacterial next-generation sequencing (NGS). The setting was the Public Health England National Mycobacteriology Laboratory Birmingham, which performs Illumina sequencing on DNA extracted from positive mycobacterial growth indicator tubes. We analyzed 4,156 samples yielding M. tuberculosis from 663 MiSeq runs, which were obtained during development and production use of a diagnostic process using NGS. The counts of the most common (major) variant and all other variants (nonmajor variants) were determined from reads mapping to positions defining M. tuberculosis lineages. Expected variation was estimated during process development. For each sample, we determined the nonmajor variant proportions at 55 sets of lineage-defining positions. The nonmajor variant proportion in the two most mixed lineage-defining sets (F2 metric) was compared with that of the 47 least-mixed lineage-defining sets (F47 metric). The following three patterns were observed: (i) not mixed by either metric; (ii) high F47 metric, suggesting mixtures of multiple lineages; and (iii) samples compatible with mixtures of two lineages, detected by differential F2 metric elevations relative to F47. Pattern ii was observed in batches, with similar patterns in the M. tuberculosis H37Rv control present in each run, and is likely to reflect cross-contamination. During production, the proportions of samples in the patterns were 97%, 2.8%, and 0.001%, respectively. The F2 and F47 metrics described could be used for laboratory process control in laboratories sequencing M. tuberculosis genomes.

Bias in detection of Mycobacterium tuberculosis polyclonal infection: Use clinical samples or cultures?

The application of MIRU-VNTR has unveiled that infection by Mycobacterium tuberculosis can be polyclonal. Our comparative study demonstrated that based on the studied samples (clinical specimen or culture) detection of polyclonal M. tuberculosis infection can be significantly different.

Vectors as Epidemiological Sentinels: Patterns of Within-Tick Borrelia burgdorferi Diversity

Hosts including humans, other vertebrates, and arthropods, are frequently infected with heterogeneous populations of pathogens. Within-host pathogen diversity has major implications for human health, epidemiology, and pathogen evolution. However, pathogen diversity within-hosts is difficult to characterize and little is known about the levels and sources of within-host diversity maintained in natural populations of disease vectors. Here, we examine genomic variation of the Lyme disease bacteria, Borrelia burgdorferi (Bb), in 98 individual field-collected tick vectors as a model for study of within-host processes. Deep population sequencing reveals extensive and previously undocumented levels of Bb variation: the majority (~70%) of ticks harbor mixed strain infections, which we define as levels Bb diversity pre-existing in a diverse inoculum. Within-tick diversity is thus a sample of the variation present within vertebrate hosts. Within individual ticks, we detect signatures of positive selection. Genes most commonly under positive selection across ticks include those involved in dissemination in vertebrate hosts and evasion of the vertebrate immune complement. By focusing on tick-borne Bb, we show that vectors can serve as epidemiological and evolutionary sentinels: within-vector pathogen diversity can be a useful and unbiased way to survey circulating pathogen diversity and identify evolutionary processes occurring in natural transmission cycles.

Lyme disease, caused by a bacteria carried by deer ticks, is the most common vector-borne disease in North America and over 30,000 cases are reported each year in the United States. Ticks may be infected with multiple strains of the Lyme disease bacteria, which differ in transmissibility and the harm they pose to humans. In this study, we collected 98 infected deer ticks from across the United States and southern Canada. We used genetic techniques to investigate the diversity of the Lyme disease bacteria infecting each individual tick. We find that 70% of ticks are infected with multiple strains of the Lyme disease bacteria, indicating that humans may be exposed to and infected with multiple bacterial strains from a single tick bite. We also find evidence that the Lyme disease bacteria is evolving in response to the immune defenses of its natural hosts (including rodents and birds). Our study shows that individual ticks and other disease vectors can be studied as epidemiological sentinels, which reveal the extensive diversity of pathogens circulating in natural disease cycles and how they are evolving.

Deep Whole-Genome Sequencing to Detect Mixed Infection of Mycobacterium tuberculosis

Mixed infection by multiple Mycobacterium tuberculosis (MTB) strains is associated with poor treatment outcome of tuberculosis (TB). Traditional genotyping methods have been used to detect mixed infections of MTB, however, their sensitivity and resolution are limited. Deep whole-genome sequencing (WGS) has been proved highly sensitive and discriminative for studying population heterogeneity of MTB. Here, we developed a phylogenetic-based method to detect MTB mixed infections using WGS data. We collected published WGS data of 782 global MTB strains from public database. We called homogeneous and heterogeneous single nucleotide variations (SNVs) of individual strains by mapping short reads to the ancestral MTB reference genome. We constructed a phylogenomic database based on 68,639 homogeneous SNVs of 652 MTB strains. Mixed infections were determined if multiple evolutionary paths were identified by mapping the SNVs of individual samples to the phylogenomic database. By simulation, our method could specifically detect mixed infections when the sequencing depth of minor strains was as low as 1× coverage, and when the genomic distance of two mixed strains was as small as 16 SNVs. By applying our methods to all 782 samples, we detected 47 mixed infections and 45 of them were caused by locally endemic strains. The results indicate that our method is highly sensitive and discriminative for identifying mixed infections from deep WGS data of MTB isolates.

Protocol for a population-based molecular epidemiology study of tuberculosis transmission in a high HIV-burden setting: the Botswana Kopanyo study

INTRODUCTION

Mycobacterium tuberculosis (Mtb) is transmitted from person to person via airborne droplet nuclei. At the community level, Mtb transmission depends on the exposure venue, infectiousness of the tuberculosis (TB) index case and the susceptibility of the index case's social network. People living with HIV infection are at high risk of TB, yet the factors associated with TB transmission within communities with high rates of TB and HIV are largely undocumented. The primary aim of the Kopanyo study is to better understand the demographic, clinical, social and geospatial factors associated with TB and multidrug-resistant TB transmission in 2 communities in Botswana, a country where 60% of all patients with TB are also infected with HIV. This manuscript describes the methods used in the Kopanyo study.

METHODS AND ANALYSIS

The study will be conducted in greater Gaborone, which has high rates of HIV and a mobile population; and in Ghanzi, a rural community with lower prevalence of HIV infection and home to the native San population. Kopanyo aims to enrol all persons diagnosed with TB during a 4-year study period. From each participant, sputum will be cultured, and for all Mtb isolates, molecular genotyping (24-locus mycobacterial interspersed repetitive units-variable number of tandem repeats) will be performed. Patients with matching genotype results will be considered members of a genotype cluster, a proxy for recent transmission. Demographic, behavioural, clinical and social information will be collected by interview. Participant residence, work place, healthcare facilities visited and social gathering venues will be geocoded. We will assess relationships between these factors and cluster involvement to better plan interventions for reducing TB transmission.

ETHICS

Ethical approval from the Independent Review Boards at the University of Pennsylvania, US Centers for Disease Control and Prevention, Botswana Ministry of Health and University of Botswana has been obtained.