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Identifying host factors that influence infectious disease transmission is an important step toward developing interventions to reduce disease incidence. Recent advances in methods for reconstructing infectious disease transmission events using pathogen genomic and epidemiological data open the door for investigation of host factors that affect onward transmission. While most transmission reconstruction methods are designed to work with densely sampled outbreaks, these methods are making their way into surveillance studies, where the fraction of sampled cases with sequenced pathogens could be relatively low. Surveillance studies that use transmission event reconstruction then use the reconstructed events as response variables (i.e., infection source status of each sampled case) and use host characteristics as predictors (e.g., presence of HIV infection) in regression models. We use simulations to study estimation of the effect of a host factor on probability of being an infection source via this multi-step inferential procedure. UsingTransPhylo— a widely-used method for Bayesian estimation of infectious disease transmission events — and logistic regression, we find that low sensitivity of identifying infection sources leads to dilution of the signal, biasing logistic regression coefficients toward zero. We show that increasing the proportion of sampled cases improves sensitivity and some, but not all properties of the logistic regression inference. Application of these approaches to real world data from a population-based TB study in Botswana fails to detect an association between HIV infection and probability of being a TB infection source. We conclude that application of a pipeline, where one first usesTransPhyloand sparsely sampled surveillance data to infer transmission events and then estimates effects of host characteristics on probabilities of these events, should be accompanied by a realistic simulation study to better understand biases stemming from imprecise transmission event inference.Author summaryFactors that affect infectious disease transmission are poorly understood, which impede efforts to prevent the spread of infectious diseases. Recently, software packages have been developed to infer transmission histories of infectious disease outbreaks using data from infectious disease genetics and epidemiology. These software packages have been used as part of methods to identify individual characteristics that affect infectious disease transmission. We used computer simulation to explore whether a statistical pipeline using the software packageTransPhylocan successfully identify individual risk factors for being an infection source in a realistic public health setting where only a small proportion of pathogens are sequenced. We simulated tuberculosis (TB) outbreaks with different odds of being an infection source for TB transmission between people living with and without HIV. We found that theTransPhylo-based pipeline consistently underestimated the odds ratio for the association between HIV and being an infection source for TB transmission. We then applied this method to data from a TB study from Botswana and found no evidence of an association between HIV and being an infection source for TB transmission. Identification of transmission risk factors may be difficult in settings with low sampling proportion for genetic data.

IntroductionCombining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis (Mtb) transmission in high tuberculosis burden settings.MethodsWe performed whole genome sequencing (WGS) on Mtb DNA extracted from sputum cultures from a population-based tuberculosis study conducted in 2012–2016 in Gaborone, Botswana. We used kernel density estimation, spatial K-functions, and created spatial distributions of phylogenetic trees. WGS-based clusters of isolates ≤5 single nucleotide polymorphisms were considered recent transmission, and large WGS-based clusters (≥10 members) were considered outbreaks.ResultsWe analyzed data from 1449 participants with culture-confirmed TB. Among these, 946 (65%) participants had both molecular and geospatial data. A total of 62 belonged to five large outbreaks (10–19 participants each). Geospatial clustering was detected in two of the five large outbreaks, suggesting heterogeneous spatial patterns within the community.ConclusionsIntegration of genomic and geospatial data identified distinct patterns of tuberculosis transmission in a high-tuberculosis burden setting. Targeted interventions in these smaller geographies may interrupt on-going transmission.

Recent studies portend a rising global spread and adaptation of human- or healthcare-associated pathogens. Here, we analyse an international collection of the emerging, multidrug-resistant, opportunistic pathogen Stenotrophomonas maltophilia from 22 countries to infer population structure and clonality at a global level. We show that the S. maltophilia complex is divided into 23 monophyletic lineages, most of which harbour strains of all degrees of human virulence. Lineage Sm6 comprises the highest rate of human-associated strains, linked to key virulence and resistance genes. Transmission analysis identifies potential outbreak events of genetically closely related strains isolated within days or weeks in the same hospitals., Multidrug resistance of the opportunistic pathogen Stenotrophomonas maltophilia is an increasing problem. Here, analyzing strains from 22 countries, the authors show that the S. maltophilia complex is divided into 23 monophyletic lineages and find evidence for intra-hospital transmission.

Background Rifampicin- or multidrug-resistant (RR/MDR) Mycobacterium tuberculosis complex (MTBC) strains account for considerable morbidity and mortality globally. WGS-based prediction of drug resistance may guide clinical decisions, especially for the design of RR/MDR-TB therapies. Methods We compared WGS-based drug resistance-predictive mutations for 42 MTBC isolates from MDR-TB patients in Tanzania with the MICs of 14 antibiotics measured in the Sensititre™ MycoTB assay. An isolate was phenotypically categorized as resistant if it had an MIC above the epidemiological-cut-off (ECOFF) value, or as susceptible if it had an MIC below or equal to the ECOFF. Results Overall, genotypically non-wild-type MTBC isolates with high-level resistance mutations (gNWT-R) correlated with isolates with MIC values above the ECOFF. For instance, the median MIC value (mg/L) for rifampicin-gNWT-R strains was >4.0 (IQR 4.0–4.0) compared with 0.5 (IQR 0.38–0.50) in genotypically wild-type (gWT-S, P 4.0 (IQR 2.0–4.0) compared with 0.25 (IQR 0.12–1.00) among gWT-S (P = 0.001); ethionamide-gNWT-R 15.0 (IQR 10.0–20.0) compared with 2.50 (IQR; 2.50–5.00) among gWT-S (P 0.5 and >0.125 mg/L, respectively. No known resistance-conferring mutations were present in genes associated with resistance to fluoroquinolones, aminoglycosides, capreomycin, bedaquiline, delamanid, linezolid, clofazimine, cycloserine, or p-amino salicylic acid. Conclusions WGS-based drug resistance prediction worked well to rule-in phenotypic drug resistance and the absence of second-line drug resistance-mediating mutations has the potential to guide the design of RR/MDR-TB regimens in the future.

Whole-genome sequencing (WGS) of Mycobacterium tuberculosis complex has become an important tool in diagnosis and management of drug-resistant tuberculosis. However, data correlating resistance genotype with quantitative phenotypic antimicrobial susceptibility testing (AST) are scarce.In a prospective multicentre observational study, 900 clinical M tuberculosis complex isolates were collected from adults with drug-resistant tuberculosis in five high-endemic tuberculosis settings around the world (Georgia, Moldova, Peru, South Africa, and Viet Nam) between Dec 5, 2014, and Dec 12, 2017. Minimum inhibitory concentrations (MICs) and resulting binary phenotypic AST results for up to nine antituberculosis drugs were determined and correlated with resistance-conferring mutations identified by WGS.Considering WHO-endorsed critical concentrations as reference, WGS had high accuracy for prediction of resistance to isoniazid (sensitivity 98·8% [95% CI 98·5-99·0]; specificity 96·6% [95% CI 95·2-97·9]), levofloxacin (sensitivity 94·8% [93·3-97·6]; specificity 97·1% [96·7-97·6]), kanamycin (sensitivity 96·1% [95·4-96·8]; specificity 95·0% [94·4-95·7]), amikacin (sensitivity 97·2% [96·4-98·1]; specificity 98·6% [98·3-98·9]), and capreomycin (sensitivity 93·1% [90·0-96·3]; specificity 98·3% [98·0-98·7]). For rifampicin, pyrazinamide, and ethambutol, the specificity of resistance prediction was suboptimal (64·0% [61·0-67·1], 83·8% [81·0-86·5], and 40·1% [37·4-42·9], respectively). Specificity for rifampicin increased to 83·9% when borderline mutations with MICs overlapping with the critical concentration were excluded. Consequently, we highlighted mutations in M tuberculosis complex isolates that are often falsely identified as susceptible by phenotypic AST, and we identified potential novel resistance-conferring mutations.The combined analysis of mutations and quantitative phenotypes shows the potential of WGS to produce a refined interpretation of resistance, which is needed for individualised therapy, and eventually could allow differential drug dosing. However, variability of MIC data for some M tuberculosis complex isolates carrying identical mutations also reveals limitations of our understanding of the genotype and phenotype relationships (eg, including epistasis and strain genetic background).BillMelinda Gates Foundation, German Centre for Infection Research, German Research Foundation, Excellence Cluster Precision Medicine of Inflammation (EXC 2167), and Leibniz ScienceCampus EvoLUNG.

RationaleBedaquiline has been classified as a group A drug for the treatment of multidrug-resistant tuberculosis (MDR-TB) by the World Health Organization; however, globally emerging resistance threatens the effectivity of novel MDR-TB treatment regimens.ObjectivesWe analysed pre-existing and emerging bedaquiline resistance in bedaquiline-based MDR-TB therapies, and risk factors associated with treatment failure and death.MethodsIn a cross-sectional cohort study, we employed patient data, whole-genome sequencing (WGS) and phenotyping of Mycobacterium tuberculosis complex (MTBC) isolates. We could retrieve baseline isolates from 30.5% (62 out of 203) of all MDR-TB patients who received bedaquiline between 2016 and 2018 in the Republic of Moldova. This includes 26 patients for whom we could also retrieve a follow-up isolate.Measurements and main resultsAt baseline, all MTBC isolates were susceptible to bedaquiline. Among 26 patients with available baseline and follow-up isolates, four (15.3%) patients harboured strains which acquired bedaquiline resistance under therapy, while one (3.8%) patient was re-infected with a second bedaquiline-resistant strain. Treatment failure and death were associated with cavitary disease (p=0.011), and any additional drug prescribed in the bedaquiline-containing regimen with WGS-predicted resistance at baseline (OR 1.92 per unit increase, 95% CI 1.15–3.21; p=0.012).ConclusionsMDR-TB treatments based on bedaquiline require a functional background regimen to achieve high cure rates and to prevent the evolution of bedaquiline resistance. Novel MDR-TB therapies with bedaquiline require timely and comprehensive drug resistance monitoring.

Rifampicin- or multidrug-resistant (RR/MDR)We compared WGS-based drug resistance-predictive mutations for 42 MTBC isolates from MDR-TB patients in Tanzania with the MICs of 14 antibiotics measured in the Sensititre™ MycoTB assay. An isolate was phenotypically categorized as resistant if it had an MIC above the epidemiological-cut-off (ECOFF) value, or as susceptible if it had an MIC below or equal to the ECOFF.Overall, genotypically non-wild-type MTBC isolates with high-level resistance mutations (gNWT-R) correlated with isolates with MIC values above the ECOFF. For instance, the median MIC value (mg/L) for rifampicin-gNWT-R strains was4.0 (IQR 4.0-4.0) compared with 0.5 (IQR 0.38-0.50) in genotypically wild-type (gWT-S,WGS-based drug resistance prediction worked well to rule-in phenotypic drug resistance and the absence of second-line drug resistance-mediating mutations has the potential to guide the design of RR/MDR-TB regimens in the future.

Antibiotic resistance among bacterial pathogens poses a major global health threat. Mycobacterium tuberculosis complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the low growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug susceptibility testing (DST) for this pathogen is to rely on genotypic techniques. This raises the fundamental question of whether a mutation is a reliable surrogate for phenotypic resistance or whether the presence of a second mutation can completely counteract its effect, resulting in major diagnostic errors (i.e., systematic false resistance results). To date, such epistatic interactions have only been reported for streptomycin that is now rarely used. By analyzing more than 31,000 MTBC genomes, we demonstrated that the eis C-14T promoter mutation, which is interrogated by several genotypic DST assays endorsed by the World Health Organization, cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function (LoF) mutations in the coding region of eis. To our knowledge, this represents the first definitive example of antibiotic reversion in MTBC. Moreover, we raise the possibility that mmpR (Rv0678) mutations are not valid markers of resistance to bedaquiline and clofazimine if these coincide with an LoF mutation in the efflux pump encoded by mmpS5 (Rv0677c) and mmpL5 (Rv0676c).

Antibiotic resistance among bacterial pathogens poses a major global health threat. M. tuberculosis complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the slow growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug-susceptibility testing (DST) for this pathogen is to rely on genotypic techniques. This raises the fundamental question of whether a mutation is a reliable surrogate for phenotypic resistance or whether the presence of a second mutation can completely counteract its effect, resulting in major diagnostic errors (i.e. systematic false resistance results). To date, such epistatic interactions have only been reported for streptomycin that is now rarely used. By analyzing more than 31,000 MTBC genomes, we demonstrated that eis C-14T promoter mutation, which is interrogated by several genotypic DST assays endorsed by the World Health Organization, cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function (LoF) mutations in the coding region of eis. To our knowledge, this represents the first definitive example of antibiotic reversion in MTBC. Moreover, we raise the possibility that mmpR (Rv0678) mutations are not valid markers of resistance to bedaquiline and clofazimine if these coincide with LoF mutation in the efflux pump encoded by mmpS5 (Rv0677c) and mmpL5 (Rv0676c).

Background Comprehensive and reliable drug susceptibility testing (DST) is urgently needed to provide adequate treatment regimens for patients with multidrug-resistant/rifampicin-resistant tuberculosis (MDR/RR-TB). We determined whether next-generation sequencing (NGS) analysis of Mycobacterium tuberculosis complex isolates and genes implicated in drug resistance can guide the design of effective MDR/RR-TB treatment regimens. Methods NGS-based genomic DST predictions of M. tuberculosis complex isolates from MDR/RR-TB patients admitted to a TB reference center in Germany between 1 January 2015 and 30 April 2019 were compared with phenotypic DST results of mycobacteria growth indicator tubes (MGIT). Standardized treatment algorithms were applied to design individualized therapies based on either genomic or phenotypic DST results, and discrepancies were further evaluated by determination of minimal inhibitory drug concentrations (MICs) using Sensititre MYCOTBI and UKMYC microtiter plates. Results In 70 patients with MDR/RR-TB, agreement among 1048 pairwise comparisons of genomic and phenotypic DST was 86.3%; 76 (7.2%) results were discordant, and 68 (6.5%) could not be evaluated due to the presence of polymorphisms with yet unknown implications for drug resistance. Importantly, 549 of 561 (97.9%) predictions of drug susceptibility were phenotypically confirmed in MGIT, and 27 of 64 (42.2%) false-positive results were linked to previously described mutations mediating a low or moderate MIC increase. Virtually all drugs (99.0%) used in combination therapies that were inferred from genomic DST were confirmed to be susceptible by phenotypic DST. Conclusions NGS-based genomic DST can reliably guide the design of effective MDR/RR-TB treatment regimens.

Background Multidrug-resistant (MDR) and extensively drug resistant (XDR) Mycobacterium tuberculosis complex (MTBC) strains are a great challenge for tuberculosis (TB) control in India. Still, factors driving the MDR/XDR epidemic in India are not well defined. Methods Whole genome sequencing (WGS) data from 1 852 MTBC strains obtained from patients from a tertiary care hospital laboratory in Mumbai were used for phylogenetic strain classification, resistance prediction, and cluster analysis (12 allele distance threshold). Factors associated with pre-XDR/XDR-TB were defined by odds ratios and a multivariate logistic regression model. Results 1 017 MTBC strains were MDR, out of which 57.8 % (n=591) were pre-XDR, and 17.9 % (n=183) were XDR. Lineage 2 (L2) strains represented 41.7 % of the MDR, 77.2 % of the pre-XDR, and 86.3 % of the XDR strains, and were significantly associated with pre-XDR/XDR-TB (P Conclusions High rates of pre-XDR/XDR strains among MDR-TB patients require rapid changes in treatment and control strategies. Transmission of particular pre-XDR/XDR L2 strains is the main driver of the pre-XDR/XDR-TB epidemic. Accordingly, control of the epidemic in the region requires measures with stopping transmission esp. of pre-XDR/XDR L2 strains. Funding source Parts of this work have been supported within the CRYPTIC consortium by the Bill & Melinda Gates Foundation [OPP1133541] and the Wellcome Trust [200205/Z/15/Z], the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germanys Excellence Strategy – EXC 2167 Precision Medicine in Inflammation, and the Leibniz Science Campus Evolutionary Medicine of the LUNG (EvoLUNG). The funders had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. Research in context Evidence before this study India is particularly affected by multidrug resistant (MDR), and extremely drug resistant (XDR) tuberculosis (TB), e.g., accounting for 27 % of the globally newly emerging MDR-TB cases. Over the past 2 decades several studies have highlighted high rates of drug resistance in Mumbai. More recently in the Mumbai metropolitan area, around 5,000 new MDR-TB cases are notified annually, with a more than 30% increase over a three-year period from 2015 to 2017. These data are extremely alarming, threatening human health and TB control in one of the most populated regions of the world. To tackle this dramatic situation, a better understanding of the epidemiological reasons is urgently needed to better guide TB control interventions. Small studies employing whole genome sequencing (WGS) of clinical Mycobacterium tuberculosis complex (MTBC) strains suggest that occurrence and transmission of particular MDR MTBC strain types may be important factors, however, large scale data on the determinants of the MDR/XDR-TB epidemic in the region are missing. Added value of this study To understand more precisely the reasons for the high MDR/XDR-TB rates, we performed WGS of 1 852 MTBC strains obtained from patients from a tertiary care hospital laboratory in Mumbai. We found a high rate of pre-XDR (57.8%) and XDR (17.9 %) among the 1017 MDR MTBC strains. Cluster rates were high among MDR (78 %) and pre-XDR/XDR (85 %) strains with three dominant L2 (Beijing) strain clusters (Cl 1-3) representing half of the pre-XDR and two thirds of the XDR-TB cases. Just cluster 1 strains accounted for 52.5 % of the XDR MTBC strains. Cluster 1-3 strains also had very high combined resistance rates to first line and second line drugs, thus, reducing available group A, B, and C drugs proposed for the treatment of MDR-TB cases to a minimal set and making the application of the short MDR-TB regimen impossible. Transmission could be further confirmed by identical mutation patterns of particular pre-XDR/XDR strains. Implication of all the available evidence Our study documents extremely high pre-XDR and XDR-TB levels in the MDR-TB strain population that has not been described before. This remarkable shift towards pre-XDR is mediated by high frequency FQ resistance mutations that, in combination with particular injectable drug resistance mutations, result in XDR-TB. In addition, pre-XDR, and XDR strains are virtually all L2 strains and show high cluster rates as an indication of ongoing transmission. Thus, successful control of the DR epidemic urgently requires measures stopping transmission of MDR/pre-XDR/XDR L2 strains in this region. As the majority of pre-XDR strains are already FQ resistant, treatment options are limited and urgent modification in treatment strategies are needed, for example, comprehensive resistance detection for all cases accompanied by design of new effective treatment combinations. It is likely, that the uniform use of treatment regimens including newest MDR-TB drugs without precise knowledge of each case ‘s resistance patterns combined with close patient monitoring likely results in ongoing transmission and further resistance development as described previously. In light of previously reported associations between BCG vaccine escape and rapid spread of L2 strains, vaccine non-responsiveness of MDR/pre-XDR/XDR L2 strains may prove to be a likely scenario in Mumbai.

Background: Multidrug-resistant (MDR) and extensively drug resistant (XDR) Mycobacterium tuberculosis complex (MTBC) strains are a great challenge for tuberculosis (TB) control in India. Still, factors driving the MDR/XDR epidemic in India are not well defined. Methods: Whole genome sequencing (WGS) data from 1 852 MTBC strains obtained from patients from a tertiary care hospital laboratory in Mumbai were used for phylogenetic strain classification, resistance prediction, and cluster analysis (12 allele distance threshold). Factors associated with pre-XDR/XDR-TB were defined by odds ratios and a multivariate logistic regression model. Results: 1 017 MTBC strains were MDR, out of which 57.8 % (n=591) were pre-XDR, and 17.9 % (n=183) were XDR. Lineage 2 (L2) strains represented 41.7 % of the MDR, 77.2 % of the pre-XDR, and 86.3 % of the XDR strains, and were significantly associated with pre-XDR/XDR-TB (P

Background Multidrug-resistant (MDR) Mycobacterium tuberculosis complex strains not detected by commercial molecular drug susceptibility testing (mDST) assays due to the RpoB I491F resistance mutation are threatening the control of MDR tuberculosis (MDR-TB) in Eswatini. Methods We investigate the evolution and spread of MDR strains in Eswatini with a focus on bedaquiline (BDQ) and clofazimine (CFZ) resistance using whole-genome sequencing in two collections ((1) national drug resistance survey, 2009–2010; (2) MDR strains from the Nhlangano region, 2014–2017). Results MDR strains in collection 1 had a high cluster rate (95%, 117/123 MDR strains) with 55% grouped into the two largest clusters (gCL3, n = 28; gCL10, n = 40). All gCL10 isolates, which likely emerged around 1993 (95% highest posterior density 1987–1998), carried the mutation RpoB I491F that is missed by commercial mDST assays. In addition, 21 (53%) gCL10 isolates shared a Rv0678 M146T mutation that correlated with elevated minimum inhibitory concentrations (MICs) to BDQ and CFZ compared to wild type isolates. gCL10 isolates with the Rv0678 M146T mutation were also detected in collection 2. Conclusion The high clustering rate suggests that transmission has been driving the MDR-TB epidemic in Eswatini for three decades. The presence of MDR strains in Eswatini that are not detected by commercial mDST assays and have elevated MICs to BDQ and CFZ potentially jeopardizes the successful implementation of new MDR-TB treatment guidelines. Measures to limit the spread of these outbreak isolates need to be implemented urgently.

Accurate drug resistance detection is key for guiding effective tuberculosis treatment. While genotypic resistance can be rapidly detected by molecular methods, their application is challenged by mixed mycobacterial populations comprising both susceptible and resistant cells (heteroresistance). For this, next-generation sequencing (NGS) based approaches promise the determination of variants even at low frequencies. However, accurate methods for a valid detection of low-frequency variants in NGS data are currently lacking. To tackle this problem, we developed the variant detection tool binoSNP which allows the determination of low-frequency single nucleotide polymorphisms (SNPs) in NGS datasets from Mycobacterium tuberculosis complex (MTBC) strains. By taking a reference-mapped file as input, binoSNP evaluates each genomic position of interest using a binomial test procedure. binoSNP was validated using in-silico, in-vitro, and serial patient isolates datasets comprising varying genomic coverage depths (100-500×) and SNP allele frequencies (1-30%). Overall, the detection limit for low-frequency SNPs depends on the combination of coverage depth and allele frequency of the resistance-associated mutation. binoSNP allows for valid detection of resistance associated SNPs at a 1% frequency with a coverage ≥400×. In conclusion, binoSNP provides a valid approach to detect low-frequency resistance-mediating SNPs in NGS data from clinical MTBC strains. It can be implemented in automated, end-user friendly analysis tools for NGS data and is a step forward towards individualized TB therapy.

Background A comprehensive understanding of the pre-existing genetic variation in genes associated with antibiotic resistance in the Mycobacterium tuberculosis complex (MTBC) is needed to accurately interpret whole-genome sequencing data for genotypic drug susceptibility testing (DST). Methods We investigated mutations in 92 genes implicated in resistance to 21 anti-tuberculosis drugs using the genomes of 405 phylogenetically diverse MTBC strains. The role of phylogenetically informative mutations was assessed by routine phenotypic DST data for the first-line drugs isoniazid, rifampicin, ethambutol, and pyrazinamide from a separate collection of over 7000 clinical strains. Selected mutations/strains were further investigated by minimum inhibitory concentration (MIC) testing. Results Out of 547 phylogenetically informative mutations identified, 138 were classified as not correlating with resistance to first-line drugs. MIC testing did not reveal a discernible impact of a Rv1979c deletion shared by M. africanum lineage 5 strains on resistance to clofazimine. Finally, we found molecular evidence that some MTBC subgroups may be hyper-susceptible to bedaquiline and clofazimine by different loss-of-function mutations affecting a drug efflux pump subunit (MmpL5). Conclusions Our findings underline that the genetic diversity in MTBC has to be studied more systematically to inform the design of clinical trials and to define sound epidemiologic cut-off values (ECOFFs) for new and repurposed anti-tuberculosis drugs. In that regard, our comprehensive variant catalogue provides a solid basis for the interpretation of mutations in genotypic as well as in phenotypic DST assays.

Multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) is an emerging threat to TB control in Ukraine, a country with the third highest XDR TB burden globally. We used whole-genome sequencing of a convenience sample to identify bacterial genetic and patient-related factors associated with MDR/XDR TB in this country. MDR/XDR TB was associated with 3 distinct Mycobacterium tuberculosis complex lineage 2 (Beijing) clades, Europe/Russia W148 outbreak, Central Asia outbreak, and Ukraine outbreak, which comprised 68.9% of all MDR/XDR TB strains from southern Ukraine. MDR/XDR TB was also associated with previous treatment for TB and urban residence. The circulation of Beijing outbreak strains harboring broad drug resistance, coupled with constraints in drug supply and limited availability of phenotypic drug susceptibility testing, needs to be considered when new TB management strategies are implemented in Ukraine.

In 2017, tuberculosis (TB), caused by Mycobacterium tuberculosis, was responsible for an estimated 1.6 million deaths ([1][1]). The control of this pandemic is threatened because of a strong increase of multidrug-resistant M. tuberculosis (MDR-TB) ([2][2]). This emergence of difficult-to-treat

We report on a whole-genome draft sequence of rye (Secale cereale L.). Rye is a diploid Triticeae species closely related to wheat and barley, and an important crop for food and feed in Central and Eastern Europe. Through whole-genome shotgun sequencing of the 7.9-Gbp genome of the winter rye inbred line Lo7 we obtained a de novo assembly represented by 1.29 million scaffolds covering a total length of 2.8 Gbp. Our reference sequence represents nearly the entire low-copy portion of the rye genome. This genome assembly was used to predict 27 784 rye gene models based on homology to sequenced grass genomes. Through resequencing of 10 rye inbred lines and one accession of the wild relative S. vavilovii, we discovered more than 90 million single nucleotide variants and short insertions/deletions in the rye genome. From these variants, we developed the high-density Rye600k genotyping array with 600 843 markers, which enabled anchoring the sequence contigs along a high-density genetic map and establishing a synteny-based virtual gene order. Genotyping data were used to characterize the diversity of rye breeding pools and genetic resources, and to obtain a genome-wide map of selection signals differentiating the divergent gene pools. This rye whole-genome sequence closes a gap in Triticeae genome research, and will be highly valuable for comparative genomics, functional studies and genome-based breeding in rye. Funding Agencies|German Federal Ministry of Education and Research (BMBF) within project RYE-SELECT [0315946A-E]

BackgroundPatients experiencing cardiac arrest (CA) and cardiopulmonary resuscitation (CPR) often die or suffer from severe neurological impairment. Post resuscitation syndrome is characterized by a systemic inflammatory response. Toll-like receptor 4 (TLR4) is a major mediator of inflammation and TLR4 has been implicated in the pathogenesis of post-resuscitation encephalopathy. The aim of this study was to evaluate whether TLR4 deficiency or inhibition can modulate survival and neurofunctional outcome after CA/CPR.MethodsFollowing intubation and central venous cannulation, CA was induced in wild type (C57Bl/6J, n = 38), TLR4 deficient (TLR4-/-, n = 37) and TLR4 antibody treated mice (5mg/kg MTS510, n = 15) by high potassium. After 10min, CPR was performed using a modified sewing machine until return of spontaneous circulation (ROSC). Cytokines and cerebral TNFalpha levels were measured 8h after CA/CPR. Survival, early neurological recovery, locomotion, spatial learning and memory were assessed over a period of 28 days.ResultsFollowing CA/CPR, all mice exhibited ROSC and 31.5% of wild type mice survived until day 28. Compared to wild type mice, neither TLR4-/- nor MTS510 treated wild type mice had statistically significant altered survival following CA/CPR (51.3 and 26.7%, P = 0.104 and P = 0.423 vs. WT, respectively). Antibody-treated but not TLR4-/- mice had higher IL-1β and IL-6 levels and TLR4-/- mice had higher IL-10 and cerebral TNFalpha levels. No differences existed between mice of all groups in early neurological recovery, locomotion, spatial learning ability or remembrance.ConclusionTherapeutic strategies targeting TLR4 may not be suitable for the reduction of mortality or neurofunctional impairment after CA/CPR.

Altitudinal gradients in mountain regions are short-range clines of different environmental parameters such as temperature or radiation. We investigated genomic and phenotypic signatures of adaptation to such gradients in five Arabidopsis thaliana populations from the North Italian Alps that originated from 580 to 2350 m altitude by resequencing pools of 19-29 individuals from each population. The sample includes two pairs of low- and high-altitude populations from two different valleys. High-altitude populations showed a lower nucleotide diversity and negative Tajima's D values and were more closely related to each other than to low-altitude populations from the same valley. Despite their close geographic proximity, demographic analysis revealed that low- and high-altitude populations split between 260 000 and 15 000 years before present. Single nucleotide polymorphisms whose allele frequencies were highly differentiated between low- and high-altitude populations identified genomic regions of up to 50 kb length where patterns of genetic diversity are consistent with signatures of local selective sweeps. These regions harbour multiple genes involved in stress response. Variation among populations in two putative adaptive phenotypic traits, frost tolerance and response to light/UV stress was not correlated with altitude. Taken together, the spatial distribution of genetic diversity reflects a potentially adaptive differentiation between low- and high-altitude populations, whereas the phenotypic differentiation in the two traits investigated does not. It may resemble an interaction between adaptation to the local microhabitat and demographic history influenced by historical glaciation cycles, recent seed dispersal and genetic drift in local populations.

Altitudinal gradients represent short-range clines of environmental parameters like temperature, radiation, seasonality and pathogen abundance, which allows to study the footprints of natural selection in geographically close populations. We investigated phenotypic variation for frost resistance and light response in fiveArabidopsis thalianapopulations ranging from 580 to 2,350 meters altitude at two different valleys in the North Italian Alps. All populations were resequenced as pools and we used a Bayesian method to detect correlations between allele frequencies and altitude while accounting for sampling, pooled sequencing and the expected amount of shared drift among populations. The among population variation to frost resistance was not correlated with altitude. An anthocyanin deficiency causing a high leaf mortality was present in the highest population, which may be non-adaptive and potentially deleterious phenotypic variation. The genomic analysis revealed that the two high-altitude populations are more closely related than the geographically close low-altitude populations. A correlation of genetic variation with altitude revealed an enrichment of highly differentiated SNPs located in genes that are associated with biological processes like response to stress and light. We further identified regions with long blocks of presence absence variation suggesting a sweep-like pattern across populations. Our analysis indicate a complex interplay of local adaptation and a demographic history that was influenced by glaciation cycles and/or rapid seed dispersal by animals or other forces.

Recent studies portend a rising global spread and adaptation of human- or healthcare-associated pathogens. Here, we analysed an international collection of the emerging, multidrug-resistant, opportunistic pathogenStenotrophomonas maltophiliafrom 22 countries to infer population structure and clonality at a global level. We show that theS. maltophiliacomplex is divided into 23 monophyletic lineages, most of which harboured strains of all degrees of human virulence. Lineage Sm6 comprised the highest rate of human-associated strains, linked to key virulence and resistance genes. Transmission analysis identified potential outbreak events of genetically closely related strains isolated within days or weeks in the same hospitals.One Sentence SummaryTheS. maltophiliacomplex comprises genetically diverse, globally distributed lineages with evidence for intra-hospital transmission.