Identification of genetic pathways driving Ebola virus disease in humans and targets for therapeutic intervention

Abstract

Introduction: LCK gene, also known as lymphocyte-specific proto-oncogene, is expressed in lymphocytes, and associated with coordinated expression of MHC class I and II in response to physiological stimuli, mediated through a combined interaction of promoters, suppressors, and enhancers. Differential usage of LCK promoters, transcribes dysfunctional transcript variants leading to leukemogenesis and non-induction of MHC class I gene variants. Viruses use C-type lectins, like CD209, to penetrate the cell, and inhibit Pattern Recognition Receptors (PRR), hence evading immune destruction. Given that Ebolavirus (EBOV) disease burden could result from a dysfunctional LCK pathway, identification of the genetic pathway leading to proper immune induction is a major priority. Methods: Data for EBOV related virus samples were obtained from Gene Expression Omnibus database and RMEAN information per gene per sample were entered into a table of values. R software v.3.3.1 was used to process differential expression patterns across samples for LCK, CD209 and immune-related genes. Principal component analysis (PCA) using ggbiplot v.0.55 was used to explain the variance across samples. Results: Data analyses identified three viral clusters based on transmission patterns as follows: LCK-CD209 dependent, LCK-dependent specific to EBOV, and CD209 dependent. Compared to HLA class II gene variants, HLA class I (A, B and C) variants were <2 fold expressed, especially for EBOV samples. PCA analyses classified TYRO3, TBK1 and LCK genes independent of the data, leading to identification of a possible pathway involving LCK, IL2, PI3k, TBK1, TYRO3 and MYB genes with downstream induction of immune T-cells. Discussion: This is the first study undertaken to understand the non-functional immune pathway, leading to EBOV disease pathogenesis and high fatality rates. Our lab currently exploits, through cutting edge genetic technology to understand the interplay of identified genes required for proper immune induction. This will guide antiviral therapy and possible markers for viral disease identification during outbreaks.