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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Hi-Jack: a novel computational framework for pathway-based inference of host-pathogen interactions.

Dimitrios Kleftogiannis¹, Limsoon Wong², John A C Archer³

¹Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, Jeddah 23955-6900, Saudi Arabia.

Bioinformatics (Oxford, England)

|March 12, 2015

Summary

This study introduces Hi-Jack, a computational framework to identify how pathogens hijack host metabolites for replication. It reveals key metabolic pathways in humans, like carbohydrate and lipid metabolism, potentially exploited by Mycobacterium tuberculosis.

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Area of Science:

Computational biology
Systems biology
Infectious disease research

Background:

Pathogens, especially obligate intracellular ones, exploit host cellular machinery for replication.
Host-pathogen interactions often involve metabolic alterations favoring pathogen proliferation.
Previous computational methods have not focused on metabolite hijacking as a key interaction mechanism.

Purpose of the Study:

To develop a novel computational framework, Hi-Jack, for inferring host-pathogen interactions via metabolite hijacking.
To identify specific metabolic pathways and metabolites involved in host-pathogen crosstalk.
To provide a new perspective on understanding infectious disease mechanisms.

Main Methods:

Developed the Hi-Jack computational framework.
Analyzed host and pathogen metabolic network data.
Implemented a novel scoring function to rank hijacked reactions and pathways.
Conducted a case study using Mycobacterium tuberculosis (Mtb) and human metabolic data.

Main Results:

Hi-Jack successfully infers pathway-based host-pathogen interactions.
Identified key human metabolic pathways (carbohydrate, lipid, amino acid metabolism) likely hijacked by Mtb.
Revealed potential interconnections, such as human fatty acid biosynthesis linked to Mtb unsaturated fatty acid biosynthesis.

Conclusions:

Metabolite hijacking is a crucial, yet understudied, aspect of host-pathogen interactions.
The Hi-Jack framework offers a novel approach to dissecting these interactions computationally.
Findings provide insights into Mtb pathogenesis and potential therapeutic targets.