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 | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
SplitStrains, a tool to identify and separate mixed <i>Mycobacterium tuberculosis</i> infections from WGS data.
Gabbassov Einar E Moreno-Molina Miguel M Comas Iñaki I Libbrecht Maxwell M Chindelevitch Leonid L
Microbial genomics 20210601 6
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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:Tuberculosis disease (TB), caused by Mycobacterium tuberculosis, is a major global public health problem, resulting in more than 1 million deaths each year. Drug resistance (DR), including multi-drug (MDR-TB), is making TB control difficult and accounts for 16% of new and 48% of previously treated cases. To further complicate treatment decision-making, many clinical studies have reported patients harbouring multiple distinct strains of M. tuberculosis across the main lineages (L1 to L4). The extent to which drug-resistant strains can be deconvoluted within mixed strain infection samples is understudied. Here, we analysed M. tuberculosis isolates with whole genome sequencing data (n = 50,723), which covered the main lineages (L1 9.1%, L2 27.6%, L3 11.8%, L4 48.3%), with genotypic resistance to isoniazid (HR-TB; n = 9546 (29.2%)), rifampicin (RR-TB; n = 7974 (24.4%)), and at least MDR-TB (n = 5385 (16.5%)). TB-Profiler software revealed 531 (1.0%) isolates with potential mixed sub-lineage infections, including some with DR mutations (RR-TB 21/531; HR-TB 59/531; at least MDR-TB 173/531). To assist with the deconvolution of such mixtures, we adopted and evaluated a statistical Gaussian Mixture model (GMM) approach. By simulating 240 artificial mixtures of different ratios from empirical data across L1 to L4, a GMM approach was able to accurately estimate the DR profile of each lineage, with a low error rate for the estimated mixing proportions (mean squared error 0.012) and high accuracy for the DR predictions (93.5%). Application of the GMM model to the clinical mixtures (n = 531), found that 33.3% (188/531) of samples consisted of DR and sensitive lineages, 20.2% (114/531) consisted of lineages with only DR mutations, and 40.6% (229/531) consisted of lineages with genotypic pan-susceptibility. Overall, our work demonstrates the utility of combined whole genome sequencing data and GMM statistical analysis approaches for providing insights into mono and mixed M. tuberculosis infections, thereby potentially assisting diagnosis, treatment decision-making, drug resistance and transmission mapping for infection control.
| S-EPMC10564873 | 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 (χ(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:Tuberculosis (TB) is an ongoing threat to public health, and furthermore, the incidence of infections by nontuberculous mycobacteria (NTM), whose symptoms are not distinguishable from TB, is increasing globally, thus indicating a need for accurate diagnostics for patients with suspected mycobacterial infections. Such diagnostic strategies need to include two steps, (i) detecting the mycobacterial infections and, if the case is an NTM infection, (ii) identifying the causative NTM pathogen. To eliminate a false-positive TB diagnosis for a host vaccinated by the bacillus Calmette-Guérin (BCG) strain of Mycobacterium bovis, a new target specific for M. tuberculosis species was selected, together with the species-specific targets for the six dominant NTM species of clinical importance, i.e., M. intracellulare, M. avium, M. kansasii, M. massiliense, M. abscessus, and M. fortuitum. Using sets of primers and probes, a two-step real-time multiplex PCR method was designed. The diagnostic performance was assessed by using a total of 1,772 clinical specimens from patients with suspected TB or NTM infection. A total of 69.4% of M. tuberculosis and 28.8% of NTM infections were positive for the primary step of the real-time PCR corresponding to the culture within 10 weeks, and mycobacterial species of 75.5% of the NTM-positive cases were identified by the secondary step. The two-step method described herein presented promising results and similar diagnostic sensitivity and specificity to commercially available real-time PCR kits for detecting TB and NTM infections. The method also enabled the identification of mycobacterial species in three-quarters of NTM infection cases, thus providing a better treatment strategy. IMPORTANCE Tuberculosis (TB) is an ongoing threat to public health. In addition, infection by nontuberculous mycobacteria (NTM) is a nonnegligible issue for global public health, with increasing incidences. Since the antimicrobial treatment strategy needs to be differed by the causative pathogen, a rapid and accurate diagnostic method is necessary. In this study, we developed a two-step molecular diagnostic method using clinical specimens of TB and NTM infection-suspected patients. The diagnostic power of the new method using the novel target was similar to the widely used TB detection kit, and, among the NTM-positive specimens, three-quarters of the NTM species were able to be identified. This simple and powerful method will be useful as it is, and it could be applied easily to a point-of-care diagnostic apparatus for better application to patients, especially those living in developing countries.
| S-EPMC10434164 | 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: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