dRNASb: a systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq...

Area of Science:

• Bioinformatics and Computational Biology
• Microbiology and Infectious Diseases
• Systems Biology

Background:

• Host-pathogen interactions involve complex, dynamic molecular exchanges influencing gene expression in both organisms.
• Dual RNA-sequencing (RNA-seq) provides simultaneous host and pathogen transcript data, crucial for studying these interactions, especially for intracellular pathogens.
• The increasing volume of dual RNA-seq data necessitates advanced computational tools for holistic, systems-level, and temporal analyses.

Purpose of the Study:

• To develop an integrative, network-driven bioinformatics pipeline, dRNASb, for analyzing temporal dual RNA-seq data.
• To enable systems-level insights into host-pathogen transcriptional dynamics and inter-species interactions.
• To identify key host and pathogen transcripts and their functional roles during infection.

Main Methods:

• Developed dRNASb, a systems biology-based computational pipeline integrating network analysis.
• dRNASb analyzes temporal transcriptional clusters and molecular interaction networks (e.g., protein-protein interactions).
• The pipeline identifies key transcripts and associates host and pathogen temporal transcriptomes to decipher inter-species interactions.

Main Results:

• Applied dRNASb to temporal dual RNA-seq data from Salmonella-infected human cells.
• Uncovered genes critical to the infection process and elucidated their potential functions.
• Identified putative associations between host and pathogen genes during infection.

Conclusions:

• dRNASb is a versatile pipeline applicable to diverse dual RNA-seq data across species and experimental conditions.
• The pipeline facilitates the identification of key genes involved in bacterial pathogenesis or host defense.
• dRNASb has potential for identifying novel therapeutic targets for infectious diseases.