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Integrating bacterial genomics and host transcriptomics links Burkholderia pseudomallei variation to melioidosis mortality and neutrophil responses

Year: 2026
Type: preprint
Abstract: Bacterial genetic variation contributes to the outcome of infection, but its relationship with host immune responses is rarely investigated in the same patients, limiting the biological interpretation of pathogen-associated disease severity. Here, we integrated pathogen genomics, clinical outcomes and host transcriptomics to investigate host-pathogen interactions in melioidosis, a frequently fatal infection caused by Burkholderia pseudomallei. We analysed prospective clinical data from 2,142 patients, whole-genome sequences from 2,101 infecting isolates and 646 paired host blood transcriptomes across five cohorts collected between 2012 and 2023. Infections were typically dominated by a single strain, with limited within-host diversification, supporting the use of an infecting isolate genome to investigate pathogen-associated clinical outcomes. Bacterial genome-wide association studies identified one locus associated with binary mortality at genome-wide significance. Incorporating patient age, sex, body mass index and Charlson Comorbidity Index increased this to four, while modelling time to death as a continuous phenotype identified seven loci. Integration with paired host transcriptomes linked mortality-associated bacterial genetic variation to imputed signatures of increased immature neutrophils and reduced neutrophil degranulation. An intergenic region upstream of the polyketide synthesis locus BPSS1006-BPSS1011 was additionally associated with downregulation of host genes involved in myeloid-cell signalling and cell proliferation pathways. These findings connect naturally occurring B. pseudomallei genomic variation associated with mortality to distinct host immune signatures, providing insight into pathogen-host interactions underlying severe melioidosis and a framework for investigating the contribution of pathogen genetic diversity to clinical outcomes.
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: green
OpenAlex ID: W7225628899
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