SplitStrains, a tool to identify and separate mixed Mycobacterium tuberculosis infections from WGS data.
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ABSTRACT:
SUBMITTER: Gabbassov E
PROVIDER: S-EPMC8461467 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMixed, polyclonal Mycobacterium tuberculosis infection occurs in natural populations. Developing an effective method for detecting such cases is important in measuring the success of treatment and reconstruction of transmission between patients. Using whole genome sequence (WGS) data, we assess two methods for detecting mixed infection: (i) a combination of the number of heterozygous sites and the proportion of heterozygous sites to total SNPs, and (ii) Bayesian model-based clustering of allele frequencies from sequencing reads at heterozygous sites.ResultsIn silico and in vitro artificially mixed and known pure M. tuberculosis samples were analysed to determine the specificity and sensitivity of each method. We found that both approaches were effective in distinguishing between pure strains and mixed infection where there was relatively high (> 10%) proportion of a minor strain in the mixture. A large dataset of clinical isolates (n = 1963) from the Karonga Prevention Study in Northern Malawi was tested to examine correlations with patient characteristics and outcomes with mixed infection. The frequency of mixed infection in the population was found to be around 10%, with an association with year of diagnosis, but no association with age, sex, HIV status or previous tuberculosis.ConclusionsMixed Mycobacterium tuberculosis infection was identified in silico using whole genome sequence data. The methods presented here can be applied to population-wide analyses of tuberculosis to estimate the frequency of mixed infection, and to identify individual cases of mixed infections. These cases are important when considering the evolution and transmission of the disease, and in patient treatment.
| S-EPMC6092779 | biostudies-literature
Project description:BACKGROUND:Mixed infections of Mycobacterium tuberculosis and antibiotic heteroresistance continue to complicate tuberculosis (TB) diagnosis and treatment. Detection of mixed infections has been limited to molecular genotyping techniques, which lack the sensitivity and resolution to accurately estimate the multiplicity of TB infections. In contrast, whole genome sequencing offers sensitive views of the genetic differences between strains of M. tuberculosis within a sample. Although metagenomic tools exist to classify strains in a metagenomic sample, most tools have been developed for more divergent species, and therefore cannot provide the sensitivity required to disentangle strains within closely related bacterial species such as M. tuberculosis. Here we present QuantTB, a method to identify and quantify individual M. tuberculosis strains in whole genome sequencing data. QuantTB uses SNP markers to determine the combination of strains that best explain the allelic variation observed in a sample. QuantTB outputs a list of identified strains, their corresponding relative abundances, and a list of drugs for which resistance-conferring mutations (or heteroresistance) have been predicted within the sample. RESULTS:We show that QuantTB has a high degree of resolution and is capable of differentiating communities differing by less than 25 SNPs and identifying strains down to 1× coverage. Using simulated data, we found QuantTB outperformed other metagenomic strain identification tools at detecting strains and quantifying strain multiplicity. In a real-world scenario, using a dataset of 50 paired clinical isolates from a study of patients with either reinfections or relapses, we found that QuantTB could detect mixed infections and reinfections at rates concordant with a manually curated approach. CONCLUSION:QuantTB can determine infection multiplicity, identify hetero-resistance patterns, enable differentiation between relapse and re-infection, and clarify transmission events across seemingly unrelated patients - even in low-coverage (1×) samples. QuantTB outperforms existing tools and promises to serve as a valuable resource for both clinicians and researchers working with clinical TB samples.
| S-EPMC6986090 | biostudies-literature
Project description:Mixed infections and heteroresistance of Mycobacterium tuberculosis contribute to the difficulty of diagnosis, treatment, and control of tuberculosis. However, there is still no proper solution for these issues. This study aimed to investigate the potential relationship between mixed infections and heteroresistance and to determine the high-risk groups related to these factors. A total of 499 resistant and susceptible isolates were subjected to spoligotyping and 24-locus variable-number tandem repeat methods to analyze their genotypic lineages and the occurrence of mixed infections. Two hundred ninety-two randomly selected isolates were sequenced on their rpoB gene to examine mutations and heteroresistance. The results showed that 12 patients had mixed infections, and the corresponding isolates belonged to Manu2 (n = 8), Beijing (n = 2), T (n = 1), and unknown (n = 1) lineages. Manu2 was found to be significantly associated with mixed infections (odds ratio, 47.72; confidence interval, 9.68 to 235.23; P < 0.01). Four isolates (1.37%) were confirmed to be heteroresistant, which was caused by mixed infections in three (75%) isolates; these belonged to Manu2. Additionally, 3.8% of the rifampin-resistant isolates showing no mutation in the rpoB gene were significantly associated with mixed infections (?(2), 56.78; P < 0.01). This study revealed for the first time that Manu2 was the predominant group in the cases of mixed infections, and this might be the main reason for heteroresistance and a possible mechanism for isolates without any mutation in the rpoB gene to become rifampin resistant. Further studies should focus on this lineage to clarify its relevance to mixed infections.
| S-EPMC4473183 | biostudies-literature
Project description:Numerous studies have reported that individuals can simultaneously harbor multiple distinct strains of Mycobacterium tuberculosis. To date, there has been limited discussion of the consequences for the individual or the epidemiological importance of mixed infections. Here, we review studies that documented mixed infections, highlight challenges associated with the detection of mixed infections, and discuss possible implications of mixed infections for the diagnosis and treatment of patients and for the community impact of tuberculosis control strategies. We conclude by highlighting questions that should be resolved in order to improve our understanding of the importance of mixed-strain M. tuberculosis infections.
| S-EPMC3485752 | biostudies-literature
Project description:BackgroundHeteroresistant Mycobacterium tuberculosis infections (defined as concomitant infection with drug-resistant and drug-susceptible strains) may explain the higher risk of poor tuberculosis treatment outcomes observed among patients with mixed-strain M. tuberculosis infections. We investigated the clinical effect of mixed-strain infections while controlling for pretreatment heteroresistance in a population-based sample of patients with tuberculosis starting first-line tuberculosis therapy in Botswana.MethodsWe performed 24-locus mycobacterial interspersed repetitive unit-variable number tandem-repeat analysis and targeted deep sequencing on baseline primary cultured isolates to detect mixed infections and heteroresistance, respectively. Drug-sensitive, micro-heteroresistant, macro-heteroresistant, and fixed-resistant infections were defined as infections in which the frequency of resistance was <0.1%, 0.1%-4%, 5%-94%, and ?95%, respectively, in resistance-conferring domains of the inhA promoter, the katG gene, and the rpoB gene.ResultsOf the 260 patients with tuberculosis included in the study, 25 (9.6%) had mixed infections and 30 (11.5%) had poor treatment outcomes. Micro-heteroresistance, macro-heteroresistance, and fixed resistance were found among 11 (4.2%), 2 (0.8%), and 11 (4.2%), respectively, for isoniazid and 21 (8.1%), 0 (0%), and 10 (3.8%), respectively, for rifampicin. In multivariable analysis, mixed infections but not heteroresistant infections independently predicted poor treatment outcomes.ConclusionsAmong patients starting first-line tuberculosis therapy in Botswana, mixed infections were associated with poor tuberculosis treatment outcomes, independent of heteroresistance.
| S-EPMC6217728 | biostudies-literature
Project description:Mycobacterium tuberculosis (MTB) is a highly successful pathogen because of its ability to persist in human lungs for long periods of time. MTB modulates several aspects of the host immune response. Lymphocyte-activation gene 3 (LAG3) is a protein with a high affinity for the CD4 receptor and is expressed mainly by regulatory T cells with immunomodulatory functions. To understand the function of LAG3 during MTB infection, a nonhuman primate model of tuberculosis, which recapitulates key aspects of natural human infection in rhesus macaques (Macaca mulatta), was used. We show that the expression of LAG3 is highly induced in the lungs and particularly in the granulomatous lesions of macaques experimentally infected with MTB. Furthermore, we show that LAG3 expression is not induced in the lungs and lung granulomas of animals exhibiting latent tuberculosis infection. However, simian immunodeficiency virus-induced reactivation of latent tuberculosis infection results in an increased expression of LAG3 in the lungs. This response is not observed in nonhuman primates infected with non-MTB bacterial pathogens, nor with simian immunodeficiency virus alone. Our data show that LAG3 was expressed primarily on CD4(+) T cells, presumably by regulatory T cells but also by natural killer cells. The expression of LAG3 coincides with high bacterial burdens and changes in the host type 1 helper T-cell response.
| S-EPMC4348466 | biostudies-literature
Project description:Mycobacterium tuberculosis 18b, a streptomycin (STR)-dependent mutant that enters a viable but nonreplicating state in the absence of STR, has been developed as a simple model for drug testing against dormant bacilli. Here, we further evaluated the STR-starved 18b (SS18b) model both in vitro and in vivo by comparing the behavior of 22 approved and experimental tuberculosis drugs. Using the resazurin reduction microplate assay (REMA), rifampin (RIF), rifapentine (RPT), TMC207, clofazimine (CFM), and linezolid (LIN) were found to be active against SS18b in vitro, and their bactericidal activity was confirmed by determining the number of CFU. A latent 18b infection was established in mice, and some of the above-mentioned drugs were used for treatment, either alone or in combination with RIF. RIF, RPT, TMC207, CFM, and pyrazinamide (PZA) were all active in vivo, while cell wall inhibitors were not. A comparative kinetic study of rifamycin efficacy was then undertaken, and the results indicated that RPT clears latent 18b infection in mice faster than RIF. Intrigued by the opposing responses of live and dormant 18b cells to cell wall inhibitors, we conducted a systematic analysis of 14 such inhibitors using REMA. This uncovered an SS18b signature (CWPRED) that accurately predicted the activities of cell wall inhibitors and performed well in a blind study. CWPRED will be useful for establishing the mode of action of compounds with unknown targets, while the SS18b system should facilitate the discovery of drugs for treating latent tuberculosis.
| S-EPMC3486556 | biostudies-other
Project description:BackgroundMixed/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.MethodsSputum 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.FindingsOne 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.ConclusionsThe 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.
| S-EPMC7437862 | biostudies-literature
Project description:Antibiotic-resistant tuberculosis poses a global threat, causing the deaths of hundreds of thousands of people annually. While whole-genome sequencing (WGS), with its unprecedented level of detail, promises to play an increasingly important role in diagnosis, data analysis is a daunting challenge. Here, we present a simple-to-use web service (free for academic use at http://phyresse.org). Delineating both lineage and resistance, it provides state-of-the-art methodology to life scientists and physicians untrained in bioinformatics. It combines elaborate data processing and quality control, as befits human diagnostics, with a treasure trove of validated resistance data collected from well-characterized samples in-house and worldwide.
| S-EPMC4432036 | biostudies-literature
Project description: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.
| S-EPMC10269500 | biostudies-literature