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Melioidosis is an often lethal tropical disease caused by the Gram-negative bacillus, Burkholderia pseudomallei. The study objective was to characterize transcriptomes in melioidosis patients and identify genes associated with outcome. Whole blood RNA-seq was performed in a discovery set of 29 melioidosis patients and 3 healthy controls. Transcriptomic profiles of patients who did not survive to 28 days were compared with patients who survived and healthy controls, showing 65 genes were significantly up-regulated and 218 were down-regulated in non-survivors compared to survivors. Up-regulated genes were involved in myeloid leukocyte activation, Toll-like receptor cascades and reactive oxygen species metabolic processes. Down-regulated genes were hematopoietic cell lineage, adaptive immune system and lymphocyte activation pathways. RT-qPCR was performed for 28 genes in a validation set of 60 melioidosis patients and 20 healthy controls, confirming differential expression. IL1R2, GAS7, S100A9, IRAK3, and NFKBIA were significantly higher in non-survivors compared with survivors (P < 0.005) and healthy controls (P < 0.0001). The AUROCC of these genes for mortality discrimination ranged from 0.80-0.88. In survivors, expression of IL1R2, S100A9 and IRAK3 genes decreased significantly over 28 days (P < 0.05). These findings augment our understanding of this severe infection, showing expression levels of specific genes are potential biomarkers to predict melioidosis outcomes.

Original publication

DOI

10.1080/22221751.2020.1858176

Type

Journal article

Journal

Emerging microbes & infections

Publication Date

12/2021

Volume

10

Pages

8 - 18

Addresses

Faculty of Tropical Medicine, Department of Microbiology and Immunology, Mahidol University, Bangkok, Thailand.

Keywords

Humans, Melioidosis, Survival Analysis, Case-Control Studies, Prospective Studies, Gene Expression Profiling, Sequence Analysis, RNA, Gene Expression Regulation, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Gene Regulatory Networks, Biomarkers