Manti kumar Saha

Conference 2023 Presentation

 

Project title

Mathematical Modelling of Pathogen responsive circuit

 

Authors and Affiliations

Manti kumar Saha1,Yashika Ratra1,Soumen Basak1

1.National Institute of Immunology

 

Abstract

Background

Microbial sensing activates the host immune response via recognition of pathogen-derived cues by pathogen recognition receptors (PRRs). Stimulation of PRRs activates primarily canonical NFkB and IRF3 signalling pathways. RelA dimers (activated by canonnical NFkB pathway) and IRF3 dimers (activated by IRF3 pathway stimulation) synergistically induce Type I interferon (IFN) production, which culminates in establishing anti viral state. Although a lot of studies are there, supporting critical role of canonical RelA and IRF3 in regulation of Type I IFN, but the role of noncanonical NFkB is poorly understood. Recent experimental studies (Ratra et al., 2022) has suggested the role of noncanonical arm of the NFkB system in regulating Type I IFN, particularly IFNb. Based on it, we have presented an insilico study involving transcriptomics and mathematical modeling approaches for investigating crosstalk of both the NFkB arms (canononical and non canonical) with IRF3 axis in shaping IFNb response.

Methods

We have constructed a mathematical model of integrated NFkB- IRF3 system, depicting canonical and noncanonical NFkB pathways and IRF3-IFNb axis. The model is implemented in MATLAB and the model simulations are performed with ODE solver, provided by MATLAB core tool. The biochemical processes are formulated based on mass action kinetics and the model inputs are derived from experimental studies. IFNb expression profile in a time course is captured as model’s simulation output. Global transcriptomics analysis is performed in R platform. For functional analysis of differentially expressed genes, we have used bioconductor packages in R.

Results

Our global transcriptomics analysis reveal enrichment of antiviral signalling processes like Type I IFN pathway, Toll like receptor signalling, defence response to virus. Furthermore, we could dissect the relative contribution of kinases in tuning IFNb response via our mathematical modeling studies. Our simulation predicted the major attributes of regulatory kinase in determining interferon response.

Conclusions

Our studies has emphasized role of NFkB system, particularly of noncanonical NFkB and IRF3 pathways in regulation of Type I IFN response in a crosstalk setting. Our modeling analysis has revealed determining factor of regulation of interferon.