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Utpatel, C.

Publications and source records attributed to Utpatel, C..

10 recordsLinked to original sources

Evolution of β-lactam resistance causes fitness reductions and several cases of collateral sensitivities in the human pathogen Haemophilus influenzae

The evolution of antimicrobial resistant (AMR) pathogens poses a global health threat and it is unclear if evolutionary trajectories to resistance lead to predictable phenotypes. We analyzed AMR-evolution in the human pathogen Haemophilus influenzae in controlled evolution experiments with increasing concentrations of either ampicillin, cefotaxime, or ceftriaxone. We isolated 315 clones from different time points of six independent experiments and characterized changes in genome sequences, bacterial fitness, and minimum inhibitory concentrations (MICs) to 14 antibiotics. Resistance evolution under ampicillin and cefotaxime was mainly driven by mutations in the ftsI gene, encoding the penicillin-binding protein 3. However, ceftriaxone exposure repeatedly selected for amino acid substitutions in the outer membrane protein P2 (OmpP2). Some OmpP2-mutants reproducibly showed phenotypic heterogeneity for ceftriaxone but also for fluoroquinolones, rifampicin and tetracycline. Bacterial fitness assessments revealed trade-offs between resistance-associated mutations and growth, though no systematic correlation of MIC increase and growth deficit was detected. Over 50% of the selected clones became more susceptible to aminoglycosides, clarithromycin, and colistin, while some mutation patterns resulted in cross-resistance to meropenem and fluoroquinolones. Overall, beta-lactam antibiotics reproducibly selected mutants with increased MICs, but evolutionary pathways and resulting phenotypes remain unpredictable. These findings highlight the complexity of resistance evolution and suggest that future AMR treatment strategies may need to consider strain-specific and collateral effects more closely.

genomics↗

Phylogenomic and genomic analysis reveals unique and shared genetic signatures of Mycobacterium kansasii complex species

Species belonging to the Mycobacterium kansasii complex (MKC) are frequently isolated from humans and the environment and can cause serious diseases. The most common MKC infections are caused by the species M. kansasii (stricto sensu), leading to tuberculosis-like disease. However, a broad spectrum of virulence, antimicrobial resistance and pathogenicity of these non-tuberculous mycobacteria (NTM) are observed across the MKC. Many genomic aspects of the MKC that relate to these broad phenotypes are not well elucidated. Here, we performed genomic analyses from a collection of 665 MKC strains, isolated from environmental, animal and human sources. We inferred the MKC pangenome, mobilome, resistome, virulome and defense systems and show that the MKC species harbors unique and shared genomic signatures. High frequency of presence of prophages and different types of defense systems was observed. We found that the M. kansasii species splits into four lineages, of which three are lowly represented and mainly in Brazil, while one lineage is dominant and globally spread. Moreover, we show that four sub-lineages of this most distributed M. kansasii lineage emerged during the 20th century. Further analysis of the M. kansasii genomes revealed almost 300 regions of difference contributing to genomic diversity, as well as fixed mutations that may explain the M. kansasiis increased virulence and drug resistance. RepositoriesBioProject PRJNA1048499. Impact statementMycobacterium kansasii complex (MKC) is a group of closely related non-tuberculous mycobacteria species, recognized as a significant source of human infection. Species belonging to the MKC may present a broad spectrum of virulence, antimicrobial resistance and pathogenicity and there is a lack of knowledge about their genomic content related to these broad phenotypes. We have provided whole genomic sequencing DNA for 342 MKC isolates and, together with public data, investigated the MKC pangenome, mobilome, resistome, virulome and defense systems and show unique and shared genetic signatures within MKC species. Furthermore, with phylogenomic and bayesian population analysis, we inferred the distribution and emergence of the Mycobacterium kansasii species lineages and sub-lineages. This study has considerably expanded the MKC available data, by providing genomic sequences of isolates from countries and global regions with unknown or poorly MKC data until now. Data summaryNGS data generated in the study are available in the NCBI Sequence Read Archive (SRA) repository under the accession number PRJNA1048499 and the accession numbers for all data sets used are provided in Supplementary Table 1.

evolutionary biology↗

Phylogroup-specific variation shapes pangenome dynamics in Pseudomonas aeruginosa

BackgroundPseudomonas aeruginosa is an opportunistic pathogen consisting of three phylogroups (hereafter named A, B, and C) of unevenly distributed size. Here, we assessed phylogroup-specific evolutionary dynamics in a collection of P. aeruginosa genomes. MethodsIn this genomic analysis, using phylogenomic and comparative genomic analyses, we generated 18 hybrid assemblies from a phylogenetically diverse collection of clinical and environmental P. aeruginosa isolates, and contextualised this information with 1991 publicly available genomes of the same species. We explored to what extent antimicrobial resistance (AMR) genes, defence systems, and virulence genes vary in their distribution across regions of genome plasticity (RGPs) and "masked" (RGP-free) genomes, and to what extent this variation differs among the phylogroups. FindingsWe found that members of phylogroup B possess larger genomes, contribute a comparatively larger number of pangenome families, and show lower abundance of CRISPR-Cas systems. Furthermore, AMR and defence systems are pervasive in RGPs and integrative and conjugative/mobilizable elements (ICEs/IMEs) from phylogroups A and B, and the abundance of these cargo genes is often significantly correlated. Moreover, inter- and intra-phylogroup interactions occur at the accessory genome level, suggesting frequent recombination events. Finally, we provide here a panel of diverse P. aeruginosa strains to be used as reference for functional analyses. InterpretationAltogether, our results highlight distinct pangenome characteristics of the P. aeruginosa phylogroups, which are possibly influenced by variation in the abundance of CRISPR-Cas systems and that are shaped by the differential distribution of other defence systems and AMR genes. FundingGerman Science Foundation, Max-Planck Society, Leibniz ScienceCampus Evolutionary Medicine of the Lung, BMBF program Medical Infection Genomics, Kiel Life Science Postdoc Award. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo date, pangenome studies exploring the epidemiology and evolution dynamics of bacterial pathogens have been limited due to the use of gene frequencies across whole species dataset without accounting for biased sampling or the population structure of the genomes in the dataset. We searched PubMed without language restrictions for articles published before September 1, 2021, that investigated the phylogroup-specific evolutionary dynamics across bacterial species. In this literature search we used the search terms "pangenome" and "phylogroup" or "uneven", which returned 14 results. Of these, only one study used a population structure-aware approach to explore pangenome dynamics in a bacterial species consisting of multiple phylogroups with unevenly distributed members. Added value of this studyTo our knowledge, this study is the first to assess phylogroup-specific evolutionary dynamics in a collection of genomes belonging to the nosocomial pathogen P. aeruginosa. Using a refined approach that challenges traditional pangenome analyses, we found specific signatures for each of the three phylogroups, and we demonstrate that members of phylogroup B contribute a comparatively larger number of pangenome families, have larger genomes, and have a lower prevalence of CRISPR-Cas systems. Additionally, we observed that antibiotic resistance and defence systems are pervasive in regions of genome plasticity and integrative and conjugative/mobilizable elements from phylogroups A and B, and that antibiotic resistance and defence systems are often significantly correlated in these mobile genetic elements. Implications of all the available evidenceThese results indicate that biases inherent to traditional pangenome approaches can obscure the real distribution of important cargo genes in a bacterial species with a complex population structure. Furthermore, our findings pave the way to new pangenome approaches that are currently under-explored in comparative genomics and, crucially, shed a new light on the role that integrative and conjugative/mobilizable elements may play in protecting the host against foreign DNA.

microbiology↗

Deciphering Bedaquiline and Clofazimine Resistance in Tuberculosis: An Evolutionary Medicine Approach

Bedaquiline (BDQ) and clofazimine (CFZ) are core drugs for treatment of multidrug resistant tuberculosis (MDR-TB), however, our understanding of the resistance mechanisms for these drugs is sparse which is hampering rapid molecular diagnostics. To address this, we employed a unique approach using experimental evolution, protein modelling, genome sequencing, and minimum inhibitory concentration data combined with genomes from a global strain collection of over 14,151 Mycobacterium tuberculosis complex isolates and an extensive literature review. Overall, 230 genomic variants causing elevated BDQ and/or CFZ MICs could be discerned, with 201 (87.4%) variants affecting the transcriptional repressor (Rv0678) of an efflux system (mmpS5-mmpL5). Structural modelling of Rv0678 suggests four major mechanisms that confer resistance: impairment of DNA binding, reduction in protein stability, disruption of protein dimerization, and alteration in affinity for its fatty acid ligand. These modelling and experimental techniques will improve personalized medicine in an impending drug resistant era.

microbiology↗

Transmission of pre-XDR and XDR-TB in the Mumbai Metropolitan Region, India

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. To address this, 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. Overall, 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 < 0.001). Cluster rates were high among MDR (78 %) and pre-XDR/XDR (85 %) strains with three dominant L2 strain clusters (Cl 1-3) representing half of the pre-XDR and two thirds of the XDR-TB cases. Cl 1 strains accounted for 52.5 % of the XDR MTBC strains. Transmission could be confirmed by identical mutation patterns of particular pre-XDR/XDR strains. As a conclusion 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 especially of pre-XDR/XDR L2 strains.

molecular biology↗

In silico secretome characterization of clinical Mycobacterium abscessus isolates provides insights into antigenic differences

Mycobacterium abscessus (MAB) is a widely disseminated pathogenic non-tuberculous mycobacterium (NTM). Like with M. tuberculosis complex (MTBC), excreted / secreted (ES) proteins play an essential role for its virulence and survival inside the host. ES proteins contain highly immunogenic proteins, which are of interest for novel diagnostic assays and vaccines. Here, we used a robust bioinformatics pipeline to predict the secretome of the M. abscessus ATCC 19977 reference strain and fifteen clinical isolates belonging to all three MAB subspecies, M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense. We found that ~18% of the proteins encoded in the MAB genomes were predicted as secreted and that the three MAB subspecies shared > 85 % of the predicted secretomes. MAB isolates with a rough (R) colony morphotype showed larger predicted secretomes than isolates with a smooth (S) morphotype. Additionally, proteins exclusive to the secretomes of MAB R variants had higher antigenic densities than those exclusive to S variants, independently of the subspecies. For all investigated isolates, ES proteins had a significantly higher antigenic density than non-ES proteins. We identified 337 MAB ES proteins with homologues in previously investigated M. tuberculosis secretomes. Among these, 222 have previous experimental support of secretion, and some proteins showed homology with protein drug targets reported in the DrugBank database. The predicted MAB secretomes showed a higher abundance of proteins related to quorum-sensing and Mce domains as compared to MTBC indicating the importance of these pathways for MAB pathogenicity and virulence. Comparison of the predicted secretome of M. abscessus ATCC 19977 with the list of essential genes revealed that 99 secreted proteins corresponded to essential proteins required for in vitro growth. All predicted secretomes were deposited in the Secret-AAR web-server (http://microbiomics.ibt.unam.mx/tools/aar/index.php).

bioinformatics↗

Characterization of genomic variants associated with resistance to bedaquiline and delamanid in naïve Mycobacterium tuberculosis clinical strains

The role of genetic mutations in genes associated to phenotypic resistance to bedaquiline (BDQ) and delamanid (DLM) in Mycobacterium tuberculosis complex (MTBc) strains is poorly understood. However, a clear understanding of the role of each genetic variant is crucial to guide the development of molecular-based drug susceptibility testing (DST). In this work, we analysed all mutations in candidate genomic regions associated with BDQ- and DLM-resistant phenotypes using a whole genome sequencing (WGS) dataset from a collection of 4795 MTBc clinical isolates from six high-burden countries of tuberculosis (TB). From WGS analysis, we identified 61 and 158 unique mutations in genomic regions potentially involved in BDQ- and DLM-resistant phenotypes, respectively. Importantly, all strains were isolated from patients who likely have never been exposed to the medicines. In order to characterize the role of mutations, we performed an energetic in silico analysis to evaluate their effect in the available protein structures Ddn (DLM), Fgd1 (DLM) and Rv0678 (BDQ), and minimum inhibitory concentration (MIC) assays on a subset of MTBc strains carrying mutations to assess their phenotypic effect. The combination of structural protein information and phenotypic data allowed for cataloging the mutations clearly associated with resistance to BDQ (n= 4) and DLM (n= 35), as well as about a hundred genetic variants without any correlation with resistance. Importantly, these results show that both BDQ and DLM resistance-related mutations are diverse and distributed across the entire region of each gene target, which is of critical importance to the development of comprehensive molecular diagnostic tools. ImportancePhenotypic drug susceptibility tests (DST) are too slow to provide an early indication of drug susceptibility status at the time of treatment initiation and very demanding in terms of specimens handling and biosafety. The development of molecular assays to detect resistance to bedaquiline (BDQ) and delamanid (DLM) requires accurate categorization of genetic variants according to their association with phenotypic resistance. We have evaluated a large multi-country set of clinical isolates to identify mutations associated with increased minimum inhibitory concentrations (MICs) and used an in silico protein structure analysis to further unravel the potential role of these mutations in drug resistance mechanisms. The results of this study are an important source of information for the development of molecular diagnostic tests to improve the provision of appropriate treatment and care to TB patients.

microbiology↗

Improving tuberculosis surveillance by detecting international transmission using publicly available whole-genome sequencing data

IntroductionImproving the surveillance of tuberculosis (TB) is especially important for multidrug-resistant (MDR) and extensively drug-resistant (XDR)-TB. The large amount of publicly available whole-genome sequencing (WGS) data for TB gives us the chance to re-use data and to perform additional analysis at a large scale. AimWe assessed the usefulness of raw WGS data of global MDR/XDR-TB isolates available from public repositories to improve TB surveillance. MethodsWe extracted raw WGS data and the related metadata of Mycobacterium tuberculosis isolates available from the Sequence Read Archive. We compared this public dataset with WGS data and metadata of 131 MDR- and XDR-TB isolates from Germany in 2012-2013. ResultsWe aggregated a dataset that includes 1,081 MDR and 250 XDR isolates among which we identified 133 molecular clusters. In 16 clusters, the isolates were from at least two different countries. For example, cluster2 included 56 MDR/XDR isolates from Moldova, Georgia, and Germany. By comparing the WGS data from Germany and the public dataset, we found that 11 clusters contained at least one isolate from Germany and at least one isolate from another country. We could, therefore, connect TB cases despite missing epidemiological information. ConclusionWe demonstrated the added value of using WGS raw data from public repositories to contribute to TB surveillance. By comparing the German and the public dataset, we identified potential international transmission events. Thus, using this approach might support the interpretation of national surveillance results in an international context.

microbiology↗

The global phylogenetic landscape and nosocomial spread of the multidrug-resistant opportunist Stenotrophomonas maltophilia

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 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 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.\n\nOne Sentence SummaryThe S. maltophilia complex comprises genetically diverse, globally distributed lineages with evidence for intra-hospital transmission.

genomics↗

The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology

BackgroundTracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult.\n\nMethodsThis study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005-2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated.\n\nFindingsOur results suggest that clusters based on Spoligotyping could encompass transmission events that occurred over 70 years prior to sampling while 24-loci-MIRU-VNTR often represented two or more decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events in timespans of up to 10 years e.g. for a 5 SNP/allele cut-off.\n\nInterpretationWith the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting.

epidemiology↗