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Whole Genome Sequencing and Spatial Analysis Identifies Recent Tuberculosis Transmission Hotspots in Ghana.

ABSTRACT: Whole genome sequencing (WGS) is progressively being used to investigate the transmission dynamics of Mycobacterium tuberculosis complex (MTBC). We used WGS analysis to resolve traditional genotype clusters and explored the spatial distribution of confirmed recent transmission clusters. Bacterial genomes from a total of 452 MTBC isolates belonging to large traditional clusters from a population-based study spanning July 2012 and December 2015 were obtained through short read next-generation sequencing using the illumina HiSeq2500 platform. We performed clustering and spatial analysis using specified R packages and ArcGIS. Of the 452 traditional genotype clustered genomes, 314 (69.5%) were confirmed clusters with a median cluster size of 7.5 genomes and an interquartile range of 4-12. Recent tuberculosis (TB) transmission was estimated as 24.7%. We confirmed the wide spread of a Cameroon sub-lineage clone with a cluster size of 78 genomes predominantly from the Ablekuma sub-district of Accra metropolis. More importantly, we identified a recent transmission cluster associated with isoniazid resistance belonging to the Ghana sub-lineage of lineage 4. WGS was useful in detecting unsuspected outbreaks; hence, we recommend its use not only as a research tool but as a surveillance tool to aid in providing the necessary guided steps to track, monitor, and control TB.

SUBMITTER: Asare P

PROVIDER: S-EPMC7248928 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWhole genome sequencing (WGS) is becoming an important part of epidemiological investigations of infectious diseases due to greater resolution and cost reductions compared to traditional typing approaches. Many public health and clinical teams will increasingly use WGS to investigate clusters of potential pathogen transmission, making it crucial to understand the benefits and assumptions of the analytical methods for investigating the data. We aimed to understand how different approaches affect inferences of transmission dynamics and outline limitations of the methods.MethodsWe comprehensively searched electronic databases for studies that presented methods used to interpret WGS data for investigating tuberculosis (TB) transmission. Two authors independently selected studies for inclusion and extracted data. Due to considerable methodological heterogeneity between studies, we present summary data with accompanying narrative synthesis rather than pooled analyses.ResultsTwenty-five studies met our inclusion criteria. Despite the range of interpretation tools, the usefulness of WGS data in understanding TB transmission often depends on the amount of genetic diversity in the setting. Where diversity is small, distinguishing re-infections from relapses may be impossible; interpretation may be aided by the use of epidemiological data, examining minor variants and deep sequencing. Conversely, when within-host diversity is large, due to genetic hitchhiking or co-infection of two dissimilar strains, it is critical to understand how it arose. Greater understanding of microevolution and mixed infection will enhance interpretation of WGS data.ConclusionsAs sequencing studies have sampled more intensely and integrated multiple sources of information, the understanding of TB transmission and diversity has grown, but there is still much to be learnt about the origins of diversity that will affect inferences from these data. Public health teams and researchers should combine epidemiological, clinical and WGS data to strengthen investigations of transmission.

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Whole Genome Sequencing and Spatial Analysis Identifies Recent Tuberculosis Transmission Hotspots in Ghana.

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