• Characterization of Genomic Variants Associated with Resistance to Bedaquiline and Delamanid in Naive Mycobacterium tuberculosis Clinical Strains

      Battaglia, S.; Spitaleri, A.; Cabibbe, A.M.; Meehan, Conor J.; Utpatel, C.; Ismail, N.; Tahseen, S.; Skrahina, A.; Alikhanova, N.; Mostofa Kamal, S.M.; et al. (2020-10)
      The role of mutations in genes associated with phenotypic resistance to bedaquiline (BDQ) and delamanid (DLM) in Mycobacterium tuberculosis complex (MTBc) strains is poorly characterized. A clear understanding of the genetic variants' role is crucial to guide the development of molecular-based drug susceptibility testing (DST). In this work, we analyzed all mutations in candidate genomic regions associated with BDQ- and DLM-resistant phenotypes using a whole-genome sequencing (WGS) data set from a collection of 4,795 MTBc clinical isolates from six countries with a high burden of tuberculosis (TB). From WGS analysis, we identified 61 and 163 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 these medicines. To characterize the role of mutations, we calculated the free energy variation upon mutations in the available protein structures of Ddn (DLM), Fgd1 (DLM), and Rv0678 (BDQ) and performed MIC assays on a subset of MTBc strains carrying mutations to assess their phenotypic effect. The combination of structural and phenotypic data allowed for cataloguing the mutations clearly associated with resistance to BDQ (n = 4) and DLM (n = 35), only two of which were previously described, as well as about a hundred genetic variants without any correlation with resistance. Significantly, 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 for the development of comprehensive molecular diagnostic tools.
    • The phylogenetic landscape and nosocomial spread of the multidrug-resistant opportunist Stenotrophomonas maltophilia

      Groschel, M.I.; Meehan, Conor J.; Barilar, I.; Diricks, M.; Gonzaga, A.; Steglich, M.; Conchillo-Solé, O.; Scherer, I.-C.; Mamat, U.; Luz, C.F.; et al. (2020-04)
      Recent studies portend a rising global spread and adaptation of human- or healthcare- associated pathogens. Here, we analyse an international collection of the emerging, multi-drug-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.
    • The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology

      Meehan, Conor J.; Moris, P.; Kohl, T.A.; Pečerska, J.; Akter, S.; Merker, M.; Utpatel, C.; Beckert, P.; Gehre, F.; Lempens, P.; et al. (2018-11)
      Background: Tracking 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. Methods: This 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. Findings: Our results suggest that clusters based on Spoligotyping could encompass transmission events that occurred almost 200 years prior to sampling while 24-loci-MIRU-VNTR often represented three decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events, e.g. in timespans of up to 10 years for a 5 SNP/allele cut-off. Interpretation: With 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.
    • Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues

      Meehan, Conor J.; Goig, G.A.; Kohl, T.A.; Verboven, L.; Dippenaar, A.; Ezewudo, M.; Farhat, M.R.; Guthrie, J.L.; Laukens, K.; Miotto, P.; et al. (2019-09)
      Whole genome sequencing (WGS) of Mycobacterium tuberculosis has rapidly progressed from a research tool to a clinical application for the diagnosis and management of tuberculosis and in public health surveillance. This development has been facilitated by drastic drops in cost, advances in technology and concerted efforts to translate sequencing data into actionable information. There is, however, a risk that, in the absence of a consensus and international standards, the widespread use of WGS technology may result in data and processes that lack harmonization, comparability and validation. In this Review, we outline the current landscape of WGS pipelines and applications, and set out best practices for M. tuberculosis WGS, including standards for bioinformatics pipelines, curated repositories of resistance-causing variants, phylogenetic analyses, quality control and standardized reporting.