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Miotto, Paolo. et al. A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis. Eur Respir J 2017; 50: 1701354. [https://doi.org/10.1183/13993003.01354-2017]. 13 páginas, 2 figuras, 4 tablas. ; A clear understanding of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.We identified 286 confidence-graded mutations associated with resistance. Compared to phenotypic methods, sensitivity (95% CI) for rifampicin was 90.3% (89.6-90.9%), while for isoniazid it was 78.2% (77.4-79.0%) and their specificities were 96.3% (95.7-96.8%) and 94.4% (93.1-95.5%), respectively. For second-line drugs, sensitivity varied from 67.4% (64.1-70.6%) for capreomycin to 88.2% (85.1-90.9%) for moxifloxacin, with specificity ranging from 90.0% (87.1-92.5%) for moxifloxacin to 99.5% (99.0-99.8%) for amikacin.This study provides a standardised and comprehensive approach for the interpretation of mutations as predictors of M. tuberculosis drug-resistant phenotypes. These data have implications for the clinical interpretation of molecular diagnostics and next-generation sequencing as well as efficient individualised therapy for patients with drug-resistant tuberculosis. ; This study was supported by tEhe Bill and Melinda Gates Foundation under grant agreement FIND OPP1115209 to address how to score mutations in the ReSeqTB data sharing platform initiative. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. K. Dheda is supported by the South African MRC and the EDCTP. I. Comas is supported by the Ministerio de Economía y Competitividad (Spanish Government) research grant SAF2016–77346-R and the European Research Council (ERC) (638553-TB-ACCELERATE). L. Chindelevitch is supported by a Sloan Fellowship. S. Niemann is supported by grants of the German Center for Infection Research. Funding information for this article has been deposited with the Crossref Funder Registry. ; Peer reviewed

13 Páginas, 7 figuras . Contiene información suplementaria en : 10.1038/s41598-018-22237-5 ; Every year, species of the Mycobacterium tuberculosis complex (MTBC) kill more people than any other infectious disease caused by a single agent. As a consequence of its global distribution and parallel evolution with the human host the bacteria is not genetically homogeneous. The observed genetic heterogeneity has relevance at different phenotypic levels, from gene expression to epidemiological dynamics. However, current systems biology datasets have focused on the laboratory reference strain H37Rv. By using large expression datasets testing the role of almost two hundred transcription factors, we have constructed computational models to grab the expression dynamics of Mycobacterium tuberculosis H37Rv genes. However, we have found that many of those transcription factors are deleted or likely dysfunctional across strains of the MTBC. As a result, we failed to predict expression changes in strains with a different genetic background when compared with experimental data. These results highlight the importance of designing systems biology approaches that take into account the genetic diversity of tubercle bacilli, or any other pathogen, if we want to identify universal targets for vaccines, diagnostics and treatments. ; This work was funded by projects BFU2014-58656-R and BFU2017-89594-R from Ministerio de Economía y Competitividad (Spanish Government) and PROMETEO/2016/122 from Generalitat Valenciana (to FGC), Ministerio de Economía y Competitividad (Spanish Government) research grant SAF2016-77346-R, and the European Research Council (ERC) (638553-TB-ACCELERATE) (to IC). ACO is recipient of a FPU fellowship from Ministerio de Educación y Ciencia FPU13/00913 (Spanish Government). ; Peer reviewed

16 p´ginas, 12 figuras, 1 tabla. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Supplementary data files can be found at 10.6084/m9.figshare.14562321. ; The occurrence of multiple strains of a bacterial pathogen such as M. tuberculosis or C. difficile within a single human host, referred to as a mixed infection, has important implications for both healthcare and public health. However, methods for detecting it, and especially determining the proportion and identities of the underlying strains, from WGS (whole-genome sequencing) data, have been limited. In this paper we introduce SplitStrains, a novel method for addressing these challenges. Grounded in a rigorous statistical model, SplitStrains not only demonstrates superior performance in proportion estimation to other existing methods on both simulated as well as real M. tuberculosis data, but also successfully determines the identity of the underlying strains. We conclude that SplitStrains is a powerful addition to the existing toolkit of analytical methods for data coming from bacterial pathogens and holds the promise of enabling previously inaccessible conclusions to be drawn in the realm of public health microbiology ; This work has been funded in part by a CANSSI Collaborative Research Team grant, 'Statistical methods for challenging problems in public health microbiology' and a Genome Canada grant, 'Machine Learning Methods to Predict Drug Resistance in Pathogenic Bacteria'. LC acknowledges funding from a Sloan Foundation fellowship (FG-2016–6392) and the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth and Development Office (FCDO), under the MRC/FCDO Concordat agreement, and is part of the EDCTP2 programme supported by the European Union. ML acknowledges funding from a NSERC Discovery grant. ; Peer reviewed

The Troika Host-Pathogen-Extrinsic Factors in Tuberculosis: Modulating Inflammation and Clinical Outcomes ; The already enormous burden caused by tuberculosis (TB) will be further aggravated by the association of this disease with modern epidemics, as human immunodeficiency virus and diabetes. Furthermore, the increasingly aging population and the wider use of suppressive immune therapies hold the potential to enhance the incidence of TB. New preventive and therapeutic strategies based on recent advances on our understanding of TB are thus needed. In particular, understanding the intricate network of events modulating inflammation in TB will help to build more effective vaccines and host-directed therapies to stop TB. This review integrates the impact of host, pathogen, and extrinsic factors on inflammation and the almost scientifically unexplored complexity emerging from the interactions between these three factors. We highlight the exciting data showing a contribution of this troika for the clinical outcome of TB and the need of incorporating it when developing novel strategies to rewire the immune response in TB. ; HN-B acknowledges the receipt of research scholarships from Bolsa D. Manuel de Mello and the Portuguese Society for Pneumology. NO acknowledges FCT IF/00474/2014. SG is funded by the European Research Council (grant number 309540-EVODRTB); the Swiss National Science Foundation (grant number 310030_166687) SystemsX.ch. IC lab is financed by Ministerio de Economía y Competitividad (Spanish Government) research grant SAF2013-43521-R, SAF2016- 77346-R, and PROMETEO/2016/122 from Generalitat Valenciana and the European Research Council (ERC) (638553-TB-ACCELERATE). The MS lab is financed by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT in the framework of the project "Institute for Research and Innovation in Health Sciences" ...

The already enormous burden caused by tuberculosis (TB) will be further aggravated by the association of this disease with modern epidemics, as human immunodeficiency virus and diabetes. Furthermore, the increasingly aging population and the wider use of suppressive immune therapies hold the potential to enhance the incidence of TB. New preventive and therapeutic strategies based on recent advances on our understanding of TB are thus needed. In particular, understanding the intricate network of events modulating inflammation in TB will help to build more effective vaccines and host-directed therapies to stop TB. This review integrates the impact of host, pathogen, and extrinsic factors on inflammation and the almost scientifically unexplored complexity emerging from the interactions between these three factors. We highlight the exciting data showing a contribution of this troika for the clinical outcome of TB and the need of incorporating it when developing novel strategies to rewire the immune response in TB. ; HN-B acknowledges the receipt of research scholarships from Bolsa D. Manuel de Mello and the Portuguese Society for Pneumology. NO acknowledges FCT IF/00474/2014. SG is funded by the European Research Council (grant number 309540-EVODRTB); the Swiss National Science Foundation (grant number 310030_166687) SystemsX.ch. IC lab is financed by Ministerio de Economía y Competitividad (Spanish Government) research grant SAF2013-43521-R, SAF2016-77346-R, and PROMETEO/2016/122 from Generalitat Valenciana and the European Research Council (ERC) (638553-TB-ACCELERATE). The MS lab is financed by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT in the framework of the project "Institute for Research and Innovation in Health Sciences" (POCI-01-0145-FEDER-007274). MS is an FCT Principal Investigator. Some graphical elements in the figures were designed by kjpargeter/Freepik. The funding agencies had no role in the design of the manuscript. ; Peer reviewed

11 páginas, 4 figuras, 1 tabla y fórmulas. Plots of all trajectories calculated (Dataset S7) have been deposited in Figshare (https://dx.doi.org/10.6084/m9.figshare.19335854). Previously published data were also used for this work [data from Brites et al. (4), Coll et al. (29), Stucki et al. (30), Guerra-Assunc¸~ao et al. (31), Zignol et al. (32), Bos et al. (33), Ates et al. (34), Comas et al. (10, 35), Borrell et al. (36), and Cancino-Mu~noz et al. (37)]. ; SignificancePrevious attempts to identify the action of natural selection in the Mycobacterium tuberculosis complex (MTBC) were limited by sample size and averaging across time and lineages. We investigate changes in selective pressures across time for every single gene of the MTBC. We developed a methodology to analyze temporal signals of selection in a large dataset (∼5,000 complete genomes) and showed that 1) almost half of the genes seem to have been under positive selection at some point in time; 2) experimentally confirmed epitopes tend to accumulate more mutations in deeper branches than in external branches; and 3) temporal signals identify genes that were conserved in the past but under positive selection in the present, suggesting ongoing adaptation to the host. ; This project received funding from the European Research Council under the European Union's Horizon 2020 Research and Innovation Program Grant 101001038 (TB-RECONNECT). In addition, this work was funded by Ministerio de Ciencia (Spanish Government) Project PID2019- 104477RB-I00 and Generalitat Valenciana Project AICO/2018/113. This research work was also funded by the European Commission – NextGenerationEU (Regulation EU 2020/2094), through CSIC's Global Health Platform (PTI Salud Global) ; Peer reviewed

11 págs., 6 figuras. All data generated or analyzed during this study are included in this published article (and its SupplementaryInformation fles) at https://doi.org/10.1038/s41598-020-75853-5. ; Glucocorticoid (GC) actions are mediated through two closely related ligand-dependent transcription factors, the GC receptor (GR) and the mineralocorticoid receptor (MR). Given the wide and effective use of GCs to combat skin inflammatory diseases, it is important to understand the relative contribution of these receptors to the transcriptional response to topical GCs. We evaluated the gene expression profiles in the skin of mice with epidermal-specific loss of GR (GREKO), MR (MREKO), or both (double KO; DKO) in response to dexamethasone (Dex). The overall transcriptional response was abolished in GREKO and DKO skin suggesting dependence of the underlying dermis on the presence of epidermal GR. Indeed, the observed dermal GC resistance correlated with a constitutive decrease in GR activity and up-regulation of p38 activity in this skin compartment. Upon Dex treatment, more than 90% of differentially expressed genes (DEGs) in CO overlapped with MREKO. However, the number of DEGs was fourfold increased and the magnitude of response was higher in MREKO vs CO, affecting both gene induction and repression. Taken together our data reveal that, in the cutaneous transcriptional response to GCs mediated through endogenous receptors, epidermal GR is mandatory while epidermal MR acts as a chief modulator of gene expression. ; Tis work was supported by grant SAF2017-88046-R (MICINN, Spanish Government). J. Bigas is recipient of FPI fellowship of MINECO. We thank NURCAMEIN (SAF2017-90604-REDT) for support for dissemination.We also thank Julia Boix for assisting with the animal experiments. ; Peer reviewed

12 páginas, 4 figuras, 1 tabla ; Efforts to eradicate tuberculosis are hampered by the rise and spread of antibiotic resistance. Several large-scale projects have aimed to specifically link clinical mutations to resistance phenotypes, but they were limited in both their explanatory and predictive powers. Here, we combine functional genomics and phylogenetic associations using clinical strain genomes to decipher the architecture of isoniazid resistance and search for new resistance determinants. This approach has allowed us to confirm the main target route of the antibiotic, determine the clinical relevance of redox metabolism as an isoniazid resistance mechanism and identify novel candidate genes harboring resistance mutations in strains with previously unexplained isoniazid resistance. This approach can be useful for characterizing how the tuberculosis bacilli acquire resistance to new antibiotics and how to forestall them. ; This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programs 638553 (TB-ACCELERATE), SAF2016-77346-R from Ministerio de Economía y Competitividad (Spanish Government) and AICO/2018/113 from Generalitat Valenciana (to I.C.). M.M.-M. is recipient of a FPI grant from the Ministerio de Economía y Competitividad (Spanish Government, code BES-2017-079656). V.F. was recipient of a post-doctoral research grant from the Ministerio de Economía y Competitividad (Spanish Government, code FPDI-2013-18757). Action cofinanced by the European Union through the Operational Program of European Regional Development Fund (ERDF) of Valencia Region (Spain) 2014-2020. ; Peer reviewed

9 páginas, 3 figuras ; Background Direct whole-genome sequencing of Mycobacterium tuberculosis from clinical specimens will be a major breakthrough in tuberculosis diagnosis and control. To date, direct whole-genome sequencing has never been used in genomic epidemiology, and its accuracy in transmission inference remains unknown. We investigated the technical challenges imposed by direct whole-genome sequencing, and used it to infer transmission clusters and predict drug resistance. Methods Using an optimised workflow, we did direct whole-genome sequencing for 37 clinical specimens from 23 tuberculosis patients. Nine sputum samples from nine patients who were infected with different non-tuberculous mycobacteria and culture-negative for tuberculosis were used as controls in the qPCR assays and pre-sequencing runs. Additionally, 780 clinical isolates in the region of Comunidad Valenciana (Spain) were whole-genome sequenced between Jan 1, 2014, and Dec 31, 2016. We analysed the genomic variants to build a tuberculosis transmission network for the region, including the clinical specimens, and to predict drug susceptibility profiles. Findings After sequencing 37 clinical specimens, 28 specimens (22 [85%] of 26 smear-positive and six [55%] of 11 smear-negative) met the quality criteria for downstream analysis. All 28 clinical specimens clustered with their matching culture isolates, with a median distance of 0 single nucleotide polymorphisms. Of the 28 clinical specimens, 16 (57%) were accurately assigned to ten transmission clusters in the region, and 12 (43%) were unique cases. Transmission inferences and drug-susceptibility predictions from direct whole-genome sequencing data were concordant with sequences from corresponding cultures and phenotypic drug-susceptibility testing. Complete genomic analysis, within a week of specimen receipt, cost €217 per sample (excluding personnel costs). Interpretation Direct whole-genome sequencing could be used to accurately delineate transmission clusters of tuberculosis and conduct culture-independent surveillance. Compared with conventional approaches, direct wholegenome sequencing allows researchers to do real-time genomic epidemiology and drug resistance surveillance in settings where culture and drug susceptibility testing are not available. ; This work was supported by projects of the European Research Council (638553-TB-ACCELERATE), Ministerio de Economía y Competitividad, and Ministerio de Ciencia, Innovación y Universidades (Spanish Government; SAF2013-43521-R, SAF2016-77346-R, and SAF2017-92345-EXP [to IC], and BES-2014-071066 [to GAG]) ; Peer reviewed

The role of clonal complexity has gradually been accepted in infection by Mycobacterium tuberculosis (MTB), although analyses of this issue are limited. We performed an in-depth study of a case of recurrent MTB infection by integrating genotyping, whole genome sequencing, analysis of gene expression and infectivity in in vitro and in vivo models. Four different clonal variants were identified from independent intrapatient evolutionary branches. One of the single-nucleotide polymorphisms in the variants mapped in mce3R, which encodes a repressor of an operon involved in virulence, and affected expression of the operon. Competitive in vivo and in vitro co-infection assays revealed higher infective efficiency for one of the clonal variants. A new clonal variant, which had not been observed in the clinical isolates, emerged in the infection assays and showed higher fitness than its parental strain. The analysis of other patients involved in the same transmission cluster revealed new clonal variants acquired through novel evolutionary routes, indicating a high tendency toward microevolution in some strains that is not host-dependent. Our study highlights the need for integration of various approaches to advance our knowledge of the role and significance of microevolution in tuberculosis. ; This study was funded by the Ministry of Economy and Competitiveness ISCIII-FIS (PI15/01554) and co-funded by ERDF (FEDER) funds from the European Commission, "A way of making Europe." Research by YN was supported by a PICATA pre-doctoral fellowship (BE55/11) from the Moncloa Campus of International Excellence (UCM-UPM, Instituto de Investigación Sanitaria Gregorio Marañón). LP-L was supported by a Miguel Servet contract (MS15/00075- CP15/00075). IC lab is financed by Ministerio de Economía y Competitividad (Spanish Government) research grant SAF2013- 43521-R, SAF2016-77346-R, and the European Research Council (ERC) (638553-TB-ACCELERATE). ; Peer reviewed

14 páginas, 6 figuras ; Models on how bacterial lineages differentiate increase our understanding of early bacterial speciation events and the genetic loci involved. Here, we analyze the population genomics events leading to the emergence of the tuberculosis pathogen. The emergence is characterized by a combination of recombination events involving core pathogenesis functions and purifying selection on early diverging loci. We identify the phoR gene, the sensor kinase of a two-component system involved in virulence, as a key functional player subject to pervasive positive selection after the divergence of the Mycobacterium tuberculosis complex from its ancestor. Previous evidence showed that phoR mutations played a central role in the adaptation of the pathogen to different host species. Now, we show that phoR mutations have been under selection during the early spread of human tuberculosis, during later expansions, and in ongoing transmission events. Our results show that linking pathogen evolution across evolutionary and epidemiological time scales points to past and present virulence determinants. ; : This work was funded by projects of the European Research Council (638553-TB-ACCELERATE) and Ministerio de Economía y Competitividad (Spanish government) research grant SAF2016-77346-R (to I.C.); BFU2014-58656-R and BFU2017-89594-R from Ministerio de Economía y Competitividad (Spanish government) and PROMETEO/2016/122 from Generalitat Valenciana (to F.G.-C); and the Swiss National Science Foundation (grants 310030_166687, IZRJZ3_164171, IZLSZ3_170834, and CRSII5_177163), the European Research Council (309540-EVODRTB), and SystemsX.ch (to S.G.). Á.C.-O. is the recipient of an FPU fellowship from Ministerio de Ciencia, Innovación y Universidades FPU13/00913 (Spanish government). L.S.-B. was funded by Wellcome grant number 098051. ; Peer reviewed

5 páginas, 2 figuras. AVAILABILITY AND IMPLEMENTATION: The database of non-tuberculous mycobacteria assemblies can be accessed at: 10.5281/zenodo.3374377. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online: http://dx.doi.org/10.1093/bioinformatics/btz729 ; MOTIVATION: Tuberculosis (TB) remains one of the main causes of death worldwide. The long and cumbersome process of culturing Mycobacterium tuberculosis complex (MTBC) bacteria has encouraged the development of specific molecular tools for detecting the pathogen. Most of these tools aim to become novel TB diagnostics, and big efforts and resources are invested in their development, looking for the endorsement of the main public health agencies. Surprisingly, no study has been conducted where the vast amount of genomic data available is used to identify the best MTBC diagnostic markers. RESULTS: In this work, we used large-scale comparative genomics to identify 40 MTBC-specific loci. We assessed their genetic diversity and physiological features to select 30 that are good targets for diagnostic purposes. Some of these markers could be used to assess the physiological status of the bacilli. Remarkably, none of the most used MTBC markers is in our catalog. Illustrating the translational potential of our work, we develop a specific qPCR assay for quantification and identification of MTBC DNA. Our rational design of targeted molecular assays for TB could be used in many other fields of clinical and basic research. ; This work was supported by projects of the European Research Council (ERC) (638553-TB-ACCELERATE), Ministerio de Economía y Competitividad and Ministerio de Ciencia, Innovación y Universidades (Spanish Government), SAF2013-43521-R, SAF2016-77346-R and SAF2017–92345–EXP (to I.C.), BES-2014-071066 (to G.A.G.), FPU 13/00913 (to A.C.O.). ; Peer reviewed

18 páginas, 11 figuras, 3 tablas. Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2019.02464/full#supplementary-material ; The administration of a high fat content diet is an accelerating factor for metabolic syndrome, impaired glucose tolerance, and early type 2 diabetes. The present study aims to assess the impact of a high fat diet on tuberculosis progression and microbiota composition in an experimental animal model using a C3HeB/FeJ mouse strain submitted to single or multiple consecutive aerosol infections. These models allowed us to study the protection induced by Bacillus Calmette-Guérin vaccination as well as by the natural immunity induced by chemotherapy after a low dose Mycobacterium tuberculosis infection. Our results show that a high fat diet is able to trigger a pro-inflammatory response, which results in a faster progression toward active tuberculosis and an impaired protective effect of BCG vaccination, which is not the case for natural immunity. This may be related to dysbiosis and a reduction in the Firmicutes/Bacteroidetes ratio in the gut microbiota caused by a decrease in the abundance of the Porphyromonadaceae family and, in particular, the Barnesiella genus. It should also be noted that a high fat diet is also related to an increase in the genera Alistipes, Parasuterella, Mucispirillum, and Akkermansia, which have previously been related to dysbiotic processes. As diabetes mellitus type 2 is a risk factor for developing tuberculosis, these findings may prove useful in the search for new prophylactic strategies for this population subset. ; This work was supported by the European Commission Horizon 2020 research and innovation program under grant agreement TBVAC2020 No. 643381, European Research Council research grant 638553-TB-ACCELERATE and Ministerio de Economía y Competitividad (Spanish government) research grant SAF2017-92345- EXP (to IC). CV has a project Servet II contract funded by the Instituto de Salud Carlos III (ISCIII, CPII 18/00031). LA received an Improvement and Mobility Program grant from the Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES). GG contract was funded by Ministerio de Economia y Competitividad (Spanish Government) (BES-2014-071066). PC contract was funded by the Instituto de Salud Carlos III (IFI14/00015). The Experimental Tuberculosis Unit is accredited by the Catalan Agency for Management of University and Research Grants with code 2017 SGR500 and the IGTP is a member of the CERCA network of institutes. The funders played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Peer reviewed

This study was funded by the Spanish Government, Instituto de Salud Carlos III (ISCIII), through the CIBER CRP-TB and the FIS 011/01702 grants to PJC, and by Manresana de Micobacteriologia, s.l. Additional support came from IMPPC core funding from the Generalitat de Catalunya to LS. JV, GR, SS, were funded by grant ADE10/00026 from ISCIII. JV was also co-funded by ISIS contract II11/00014 from ISCIII. IC is supported by the Spanish Ministerio de Economia y Competitividad (MINECO) through a Ramón y Cajal contract RYC-2012-10627 and grant SAF2013-43521-R. E.J. was funded by Instituto de Salud Carlos III-PI1001438 and the European Regional Development Fund (FEDER), and CV by Miguel Servet Contract CP13/00174. ; We present here the draft genome sequences of two Mycobacterium setense strains. One of them corresponds to the M. setense type strain DSM-45070, originally isolated from a patient with a posttraumatic chronic skin abscess. The other one corresponds to the nonpathogenic M. setense strain Manresensis, isolated from the Cardener River crossing Manresa, Catalonia, Spain. A comparative genomic analysis shows a smaller genome size and fewer genes in M. setense strain Manresensis relative to those of the type strain, and it shows the genome segments unique to each strain.

11 páginas, 5 figuras, 1 tabla ; 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. ; The authors were supported by projects SAF2016-77346-R and PID2019-104477RB-I00 awarded to IC and the grant BES-2017-079656 awarded to MM by the Spanish Ministry of Economy and Competitiveness and Ministry of Science, the ERC project 638553-TBACCELERATE awarded to IC, Spanish Government-FEDER Funds through CV contract CPII18/00031 and grant PI16/01511, and Generalitat Valencia Grant to I.C. (code PROMETEO/2020/012). The grant providers played no part in study design, data collection, and analysis, or the preparation of the manuscript. ; Peer reviewed