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Background: Mixed infection with multiple strains of the same pathogen in a single host can present clinical and analytical challenges. Whole genome sequence (WGS) data can identify signals of multiple strains in samples, though the precision of previous methods can be improved. Here, we present MixInfect2, a new tool to accurately detect mixed samples from Mycobacterium tuberculosis short-read WGS data. We then evaluate three approaches for reconstructing the underlying mixed constituent strain sequences. This allows these samples to be included in downstream analysis to gain insights into the epidemiology and transmission of mixed infections., Methods: We employed a Gaussian mixture model to cluster allele frequencies at mixed sites (hSNPs) in each sample to identify signals of multiple strains. Building upon our previous tool, MixInfect, we increased the accuracy of classifying in vitro mixed samples through multiple improvements to the bioinformatic pipeline. Major and minor proportion constituent strains were reconstructed using three approaches and assessed by comparing the estimated sequence to the known constituent strain sequence. Lastly, mixed infections in a real-world Mycobacterium tuberculosis population from Moldova were detected with MixInfect2 and clusters of recent transmission that included major and minor constituent strains were built., Results: All 36/36 in vitro mixed and 12/12 non-mixed samples were correctly classified with MixInfect2, and major strain proportions were estimated with high accuracy (within 3% of the true strain proportion), outperforming previous tools. Reconstructed major strain sequences closely matched the true constituent sequence by taking the allele at the highest frequency at hSNPs, while the best-performing approach to reconstruct the minor proportion strain sequence was identifying the closest non-mixed isolate in the same population, though no approach was effective when the minor strain proportion was at 5%. Finally, fewer mixed infections were identified in Moldova than previous estimates (6.6% vs 17.4%) and we found multiple instances where the constituent strains of mixed samples were present in transmission clusters., Conclusions: MixInfect2 accurately detects samples with evidence of mixed infection from short-read WGS data and provides an excellent estimate of the mixture proportions. While there are limitations in reconstructing the constituent strain sequences of mixed samples, we present recommendations for the best approach to include these isolates in further analyses., Competing Interests: Declarations. Ethics approval and consent to participate: This study was approved by the Ethics Committee of Research of the Phthisiopneumology Institute in Moldova and the Yale University Human Investigation Committee (no. 2000023071). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Background: Mycobacterium tuberculosis complex (MTBC) species evolve slowly, so isolates from individuals linked in transmission often have identical or nearly identical genomes, making it difficult to reconstruct transmission chains. Finding additional sources of shared MTBC variation could help overcome this problem. Previous studies have reported MTBC diversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear. Here, we aimed to quantify within-host MTBC variation and assess whether such information improves transmission inferences., Methods: We conducted a retrospective genomic epidemiology study in which we reanalysed publicly available sequence data from household transmission studies published in PubMed from database inception until Jan 31, 2024, for which both genomic and epidemiological contact data were available, using household membership as a proxy for transmission linkage. We quantified minority variants (ie, positions with two or more alleles each supported by at least five-fold coverage and with a minor allele frequency of 1% or more) outside of PE and PPE genes, within individual samples and shared across samples. We used receiver operator characteristic (ROC) curves to compare the performance of a general linear model for household membership that included shared minority variants and one that included only fixed genetic differences., Findings: We identified three MTBC household transmission studies with publicly available whole-genome sequencing data and epidemiological linkages: a household transmission study in Vitória, Brazil (Colangeli et al), a retrospective population-based study of paediatric tuberculosis in British Columbia, Canada (Guthrie et al), and a retrospective population-based study in Oxfordshire, England (Walker et al). We found moderate levels of minority variation present in MTBC sequence data from cultured isolates that varied significantly across studies: mean 168·6 minority variants (95% CI 151·4-185·9) for the Colangeli et al dataset, 5·8 (1·5-10·2) for Guthrie et al (p<0·0001, Wilcoxon rank sum test, vs Colangeli et al), and 7·1 (2·4-11·9) for Walker et al (p<0·0001, Wilcoxon rank sum test, vs Colangeli et al). Isolates from household pairs shared more minority variants than did randomly selected pairs of isolates: mean 97·7 shared minority variants (79·1-116·3) versus 9·8 (8·6-11·0) in Colangeli et al, 0·8 (0·1-1·5) versus 0·2 (0·1-0·2) in Guthrie et al, and 0·7 (0·1-1·3) versus 0·2 (0·2-0·2) in Walker et al (all p<0·0001, Wilcoxon rank sum test). Shared within-host variation was significantly associated with household membership (odds ratio 1·51 [95% CI 1·30-1·71], p<0·0001), for one standard deviation increase in shared minority variants. Models that included shared within-host variation versus models without within-host variation improved the accuracy of predicting household membership in all three studies: area under the ROC curve 0·95 versus 0·92 for the Colangeli et al study, 0·99 versus 0·95 for the Guthrie et al study, and 0·93 versus 0·91 for the Walker et al study., Interpretation: Within-host MTBC variation persists through culture of sputum and could enhance the resolution of transmission inferences. The substantial differences in minority variation recovered across studies highlight the need to optimise approaches to recover and incorporate within-host variation into automated phylogenetic and transmission inference., Funding: National Institutes of Health., Competing Interests: Declaration of interests JRA reports support from the US National Institutes of Health (NIH); receiving donated Cepheid disposable open cartridges from Cepheid to Stanford University for NIH-funded tuberculosis research; participation in two Data Safety Monitoring Boards for NIH-funded tuberculosis trials; and participation in the Science Advisory Board for an NIH-funded tuberculosis network. JC reports grants from the NIH, Valneva/Butantan Institution, Coalition for Epidemic Preparedness Innovations–Sabin Institute, MSD, and Sanofi Pasteur for clinical and epidemiological studies; honoraria from Pfizer; participation in the Brazil Advisory Board for the mRNA-1273 vaccine Moderna–Zodiac, the Latin America and Brazilian Advisory Board for paxlovid (nirmatrelvir–ritonavir; Pfizer), the Brazil Advisory Board for the Qdenga vaccine (Takeda), and the Takeda Global Dengue Steering Committee. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Recent rises in incident tuberculosis (TB) cases in Paraguay and the increasing concentration of TB within prisons highlight the urgency of targeting strategies to interrupt transmission and prevent new infections. However, whether specific cities or carceral institutions play a disproportionate role in transmission remains unknown. We conducted prospective genomic surveillance, sequencing 471 Mycobacterium tuberculosis complex genomes, from inside and outside prisons in Paraguay's two largest urban areas, Asunción and Ciudad del Este, from 2016 to 2021. We found genomic evidence of frequent recent transmission within prisons and transmission linkages spanning prisons and surrounding populations. We identified a signal of frequent M. tuberculosis spread between urban areas and marked recent population size expansion of the three largest genomic transmission clusters. Together, our findings highlight the urgency of strengthening TB control programs to reduce transmission risk within prisons in Paraguay, where incidence was 70 times that outside prisons in 2021., (© 2023. The Author(s).)

Tuberculosis (TB) remains a leading cause of infectious mortality globally, yet most cases cannot be epidemiologically linked even with extensive contact investigations and whole genome sequencing. Consequently, there remain major gaps in our understanding of where and when M. tuberculosis (Mtb) exposures occur. We aimed to investigate whether Mtb can be detected in environments where TB patients were recently present, which could serve as a tool for characterizing exposure risk. We collected 389 environment surface (ES) swabs from two high TB burden prisons in Brazil, sampling 41 (n = 340) cells occupied by individuals with active TB and 7 (n = 49) cells from individuals without TB. In a subset of pooled swabs (n = 6) and a swab from a cigarette lighter from the cell with active TB patients, we enriched Mtb DNA using RNA-bait hybrid capture assays and performed whole genome sequencing. In prison cells, Mtb DNA was detected in 55/340 (16 %) of ES swabs from cells occupied by active TB patients and none (0/49) from cells in which no active TB patients were present. Mtb was detected in 13/16 (81 %) prison cells occupied by the individuals with high/medium sputum Xpert Mtb load and 8/25 (32 %) with low/very low sputum Mtb load (p = 0.003). Seven hybrid capture samples had a median genomic coverage of 140×. rpoB mutations conferring high-level rifampin resistance were detected in 3/7 ES swabs. Mtb was frequently detectable in environments recently occupied by individuals with active TB. This approach could be applied in congregate environments to identify and characterize high-risk settings for Mtb exposure., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jason R. Andrews reports financial support was provided by National Institutes of Health., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

International migrants are at heightened risk for tuberculosis (TB) disease. Intensified incarceration at international borders may compound population-wide TB risk. However, few studies have investigated the contributions of migration, local transmission, or prisons in driving incident TB at international borders. We conducted prospective population-based genomic surveillance in 3 cities along Brazil's central western border from 2014-2017. Although most isolates (89/132; 67%) fell within genomic transmission clusters, genetically unique isolates disproportionately occurred among participants with recent international travel (17/42; 40.5%), suggesting that both local transmission and migration contribute to incident TB. Isolates from 40 participants with and 76 without an incarceration history clustered together throughout a maximum-likelihood phylogeny, indicating the close interrelatedness of prison and community epidemics. Our findings highlight the need for ongoing surveillance to control continued introductions of TB and reduce the disproportionate burden of TB in prisons at Brazil's international borders.

Pathogen genomic data are increasingly used to characterize global and local transmission patterns of important human pathogens and to inform public health interventions. Yet, there is no current consensus on how to measure genomic variation. To test the effect of the variant-identification approach on transmission inferences for Mycobacterium tuberculosis, we conducted an experiment in which five genomic epidemiology groups applied variant-identification pipelines to the same outbreak sequence data. We compared the variants identified by each group in addition to transmission and phylogenetic inferences made with each variant set. To measure the performance of commonly used variant-identification tools, we simulated an outbreak. We compared the performance of three mapping algorithms, five variant callers and two variant filters in recovering true outbreak variants. Finally, we investigated the effect of applying increasingly stringent filters on transmission inferences and phylogenies. We found that variant-calling approaches used by different groups do not recover consistent sets of variants, which can lead to conflicting transmission inferences. Further, performance in recovering true variation varied widely across approaches. While no single variant-identification approach outperforms others in both recovering true genome-wide and outbreak-level variation, variant-identification algorithms calibrated upon real sequence data or that incorporate local reassembly outperform others in recovering true pairwise differences between isolates. The choice of variant filters contributed to extensive differences across pipelines, and applying increasingly stringent filters rapidly eroded the accuracy of transmission inferences and quality of phylogenies reconstructed from outbreak variation. Commonly used approaches to identify M. tuberculosis genomic variation have variable performance, particularly when predicting potential transmission links from pairwise genetic distances. Phylogenetic reconstruction may be improved by less stringent variant filtering. Approaches that improve variant identification in repetitive, hypervariable regions, such as long-read assemblies, may improve transmission inference.

Much remains unknown about Mycobacterium tuberculosis transmission. Seminal experimental studies from the 1950s demonstrated that airborne expulsion of droplet nuclei from an infectious tuberculosis (TB) patient is the primary route of transmission. However, these findings did not rule out other routes of M. tuberculos is transmission. We reviewed historical scientific evidence from the late 19th/early 20th century and contemporary studies investigating the presence, persistence and infectiousness of environmental M. tuberculosis We found both experimental and epidemiological evidence supporting the presence and viability of M. tuberculosis in multiple natural and built environments for months to years, presumably following contamination by a human source. Furthermore, several studies confirm M. tuberculosis viability and virulence in the environment using guinea pig and mouse models. Most of this evidence was historical; however, several recent studies have reported consistent findings of M. tuberculosis detection and viability in the environment using modern methods. Whether M. tuberculosis in environments represents an infectious threat to humans requires further investigation; this may represent an untapped source of data with which to further understand M. tuberculosis transmission. We discuss potential opportunities for harnessing these data to generate new insights into TB transmission in congregate settings., Competing Interests: Conflict of interest: L. Martinez has nothing to disclose. Conflict of interest: R. Verma has nothing to disclose. Conflict of interest: J. Croda has nothing to disclose. Conflict of interest: C.R. Horsburgh Jr has nothing to disclose. Conflict of interest: K.S. Walter has nothing to disclose. Conflict of interest: N. Degner has nothing to disclose. Conflict of interest: K. Middelkoop has nothing to disclose. Conflict of interest: A. Koch has nothing to disclose. Conflict of interest: S. Hermans has nothing to disclose. Conflict of interest: D.F. Warner has nothing to disclose. Conflict of interest: R. Wood has nothing to disclose. Conflict of interest: F. Cobelens has nothing to disclose. Conflict of interest: J.R. Andrews has nothing to disclose., (Copyright ©ERS 2019.)