Conor J Meehan | Search PubMed

PubMed2026

Spatial clustering and transmission networks of multidrug-resistant tuberculosis in Rwanda: a national retrospective genomic and spatial epidemiological study.

BACKGROUND: Approximately 96% of rifampicin resistance/multidrug-resistant tuberculosis (RR/MDR-TB) cases in Rwanda result from direct transmission rather than acquired resistance. However, the nationwide spatial distribution and transmission dynamics of RR/MDR-TB remain poorly characterised. This study aims to analyse spatial patterns of RR/MDR-TB in Rwanda and explore relationships between spatial proximity and RR/MDR-TB strains' genetic relatedness. METHODS: We conducted a retrospective analysis of 249 confirmed RR-TB cases across Rwanda from 2017 to 2024, using the known geolocations of patients' residences. Spatial and space-time clustering was assessed using Kulldorff's scan statistics. Demographic and socioeconomic determinants were evaluated using multivariable regression. For 201 cases with whole-genome sequencing data, we performed transmission analysis using a 5-SNP threshold to define recent transmission clusters and investigated spatial relationships within genetically related strains. RESULTS: Significant spatial clustering of RR/MDR-TB was identified in 21 sectors, mainly in Nyarugenge, southern Gasabo and western Kicukiro (relative risk: 10.06; p<0.001). Our multivariable analysis showed that population density is positively associated with case notification rates. Molecular analysis revealed 88.5% of cases belonged to genotype clusters defined using a 12-SNP threshold, with 73.6% forming clusters at a strict 5-SNP threshold. Spatial K-function analysis of the six major clusters revealed heterogeneous transmission patterns, characterised by both tightly clustered outbreaks and regional transmission networks that spanned administrative boundaries. Most clusters (5/6) extended beyond Kigali, indicating that transmission networks operate across administrative divides. CONCLUSION: RR/MDR-TB in Rwanda shows significant spatial clustering with transmission occurring through both localised and regional networks. Integrating genomic and spatial data reveals transmission patterns that extend beyond household contacts and administrative boundaries. These findings underscore the need to implement geographically targeted interventions that address community-level transmission to control RR/MDR-TB in Rwanda effectively.

Rwanda↗

PubMed2025

Pitfalls of bacterial pan-genome analysis approaches: a case study of Mycobacterium tuberculosis and two less clonal bacterial species.

SUMMARY: Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety in methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. Using Mycobacterium tuberculosis, a clonally evolving bacterium with a small accessory genome, as a model system, we systematically evaluated sources of variability in pan-genome estimates. Our analysis revealed that differences in assembly type (short-read versus hybrid), annotation pipeline, and pan-genome software, significantly impact predictions of core and accessory genome size. Extending our analysis to two additional bacterial species, Escherichia coli and Staphylococcus aureus, we observed consistent tool-dependent biases but species-specific patterns in pan-genome variability. Our findings highlight the importance of integrating nucleotide- and protein-level analyses to improve the reliability and reproducibility of pan-genome studies across diverse bacterial populations. AVAILABILITY AND IMPLEMENTATION: Panqc is freely available under an MIT license at https://github.com/maxgmarin/panqc.

Genome, Bacterial↗