Formal modeling of the key determinants of Hepatitis C Virus (HCV) induced adaptive immune response network: An integrative approach to map the cellular and cytokine-mediated host immune regulations
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Abstract
Background. Hepatitis C Virus (HCV) is a major causative agent of liver infection leading to critical liver damage. In response to HCV, the improper regulation of host immune system leads to chronic infection. The host immune system employs multiple cell types, diverse variety of cytokine mediators and interacting signaling networks to neutralize the HCV infection. To understand the complexity of the interactions within the immune signaling networks, systems biology provides an efficient alternative approach. Integrating such approaches with immunology and virology helps to study highly complex immune regulatory networks within the host and presents a concise view of the whole system.
Methods. Initially, a logic-based diagram is generated based on multiple reported interactions between immune cells and cytokines during host immune response to HCV. Furthermore, an abstracted sub-network is modeled qualitatively which consists of both the key cellular and cytokine components of the HCV induced immune system. Rene’ Thomas formalism is applied in the study to generate a qualitative model which requires only the qualitative thresholds and associated logical parameters generated via SMBioNet software in accordance with biological observations. Furthermore, the continuous dynamics of the model have been studied via Petri nets based analysis.
Results. In the presence of NS5A protein of HCV, the behaviors of the Natural Killer (NK) and T regulatory (Tregs) cells along with cytokines such as IFN-γ, IL-10, IL-12 are predicted. The model also attempts to consider the viral strategies to circumvent immune response mediated by viral proteins. The state graph analysis enabled the prediction of paths leading to disease state. The most probable cycle is predicted based on maximum betweenness centrality. Furthermore, to study the continuous dynamics of the modeled network, a Petri net (PN) model was generated. The predictive ability of the model implicates the critical role of IL-12 over-expression in pathogenesis. This observation speculates that IL-12 has a dual role under varying circumstances and leads to varying disease outcomes.
Conclusion. This model attempts to reduce the noisy biological data and captures a holistic view of the regulations amongst the key determinants of HCV induced adaptive immune responses. The observations warrant for further studies to elucidate the role of IL-12 under varying external and internal stimuli. Also, introducing diversion by therapeutic perturbation may divert the system from diseased paths to recovery by stabilizing the activation of IFN-γ producing NK cells. The modeling approach employed in this study can be extended to include real-time experimental data to propose new therapeutic interventions.
Cite this as
2018. Formal modeling of the key determinants of Hepatitis C Virus (HCV) induced adaptive immune response network: An integrative approach to map the cellular and cytokine-mediated host immune regulations. PeerJ Preprints 6:e26456v1 https://doi.org/10.7287/peerj.preprints.26456v1Author comment
This is a submission to PeerJ for review.
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Supplemental Information
Parameters profile generated by SMbioNet software for selection of parameters
Additional Information
Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Ayesha Obaid conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables.
Anam Naz analyzed the data, reviewed drafts of the paper.
Shifa Tariq Ashraf performed the experiments, analyzed the data, reviewed drafts of the paper.
Faryal Mehwish Awan analyzed the data, reviewed drafts of the paper.
Aqsa Ikram analyzed the data, reviewed drafts of the paper.
Muhammad Tariq Saeed performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, reviewed drafts of the paper.
Abida Raza analyzed the data, reviewed drafts of the paper.
Jamil Ahmad conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, reviewed drafts of the paper.
Amjad Ali conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, reviewed drafts of the paper.
Data Deposition
The following information was supplied regarding data availability:
The raw data/code is included in the manuscript (Methods section. Results Section and supplementary files)
Funding
This work is supported by Higher Education Commission of Pakistan NRPU grant no. 4362. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
