Emerging Microbes and Infections (Jan 2021)

Blood transcriptomics to characterize key biological pathways and identify biomarkers for predicting mortality in melioidosis

  • Thatcha Yimthin,
  • Jacqueline Margaret Cliff,
  • Rungnapa Phunpang,
  • Peeraya Ekchariyawat,
  • Taniya Kaewarpai,
  • Ji-Sook Lee,
  • Clare Eckold,
  • Megan Andrada,
  • Ekkachai Thiansukhon,
  • Kittisak Tanwisaid,
  • Somchai Chuananont,
  • Chumpol Morakot,
  • Narongchai Sangsa,
  • Wirayut Silakun,
  • Sunee Chayangsu,
  • Noppol Buasi,
  • Nicholas Day,
  • Ganjana Lertmemongkolchai,
  • Wasun Chantratita,
  • T. Eoin West,
  • Narisara Chantratita

DOI
https://doi.org/10.1080/22221751.2020.1858176
Journal volume & issue
Vol. 10, no. 1
pp. 8 – 18

Abstract

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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.

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