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Volume 12
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10.3390/pathogens12010018
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Article

CD4+ T Cell Regulatory Network Underlies the Decrease in Th1 and the Increase in Anergic and Th17 Subsets in Severe COVID-19

by
Mariana Esther Martinez-Sánchez
1,
José Alberto Choreño-Parra
2,
Elena R. Álvarez-Buylla
3,4,
Joaquín Zúñiga
2,5,* and
Yalbi Itzel Balderas-Martínez
1,*
1
Laboratory of Computational Biology, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City CP 14080, Mexico
2
Laboratory of Immunobiology and Genetics, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City CP 14080, Mexico
3
Instituto de Ecología, Universidad Nacional Autónoma de Mexico, Mexico City CP 04510, Mexico
4
Centro de Ciencias de la Complejidad (C3), Universidad Nacional Autónoma de Mexico, Mexico City CP 04510, Mexico
5
Tecnológico de Monterrey, School of Medicine and Health Sciences, Mexico City CP 14380, Mexico
*
Authors to whom correspondence should be addressed.
Pathogens 2023, 12(1), 18; https://doi.org/10.3390/pathogens12010018
Submission received: 10 November 2022 / Revised: 10 December 2022 / Accepted: 14 December 2022 / Published: 22 December 2022
(This article belongs to the Special Issue Mechanisms of Gene Expression Regulation during Host-Pathogen Interaction)
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Abstract

In this model we use a dynamic and multistable Boolean regulatory network to provide a mechanistic explanation of the lymphopenia and dysregulation of CD4+ T cell subsets in COVID-19 and provide therapeutic targets. Using a previous model, the cytokine micro-environments found in mild, moderate, and severe COVID-19 with and without TGF-β and IL-10 was we simulated. It shows that as the severity of the disease increases, the number of antiviral Th1 cells decreases, while the the number of Th1-like regulatory and exhausted cells and the proportion between Th1 and Th1R cells increases. The addition of the regulatory cytokines TFG-β and IL-10 makes the Th1 attractor unstable and favors the Th17 and regulatory subsets. This is associated with the contradictory signals in the micro-environment that activate SOCS proteins that block the signaling pathways. Furthermore, it determined four possible therapeutic targets that increase the Th1 compartment in severe COVID-19: the activation of the IFN-γ pathway, or the inhibition of TGF-β or IL-10 pathways or SOCS1 protein; from these, inhibiting SOCS1 has the lowest number of predicted collateral effects. Finally, a tool is provided that allows simulations of specific cytokine environments and predictions of CD4 T cell subsets and possible interventions, as well as associated secondary effects.
Keywords: COVID-19; Boolean model; regulatory model; simulation study; CD4+ T cell; immune response; cytokines; Th1; Th17; Treg COVID-19; Boolean model; regulatory model; simulation study; CD4+ T cell; immune response; cytokines; Th1; Th17; Treg
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MDPI and ACS Style

Martinez-Sánchez, M.E.; Choreño-Parra, J.A.; Álvarez-Buylla, E.R.; Zúñiga, J.; Balderas-Martínez, Y.I. CD4+ T Cell Regulatory Network Underlies the Decrease in Th1 and the Increase in Anergic and Th17 Subsets in Severe COVID-19. Pathogens 2023, 12, 18. https://doi.org/10.3390/pathogens12010018

AMA Style

Martinez-Sánchez ME, Choreño-Parra JA, Álvarez-Buylla ER, Zúñiga J, Balderas-Martínez YI. CD4+ T Cell Regulatory Network Underlies the Decrease in Th1 and the Increase in Anergic and Th17 Subsets in Severe COVID-19. Pathogens. 2023; 12(1):18. https://doi.org/10.3390/pathogens12010018

Chicago/Turabian Style

Martinez-Sánchez, Mariana Esther, José Alberto Choreño-Parra, Elena R. Álvarez-Buylla, Joaquín Zúñiga, and Yalbi Itzel Balderas-Martínez. 2023. "CD4+ T Cell Regulatory Network Underlies the Decrease in Th1 and the Increase in Anergic and Th17 Subsets in Severe COVID-19" Pathogens 12, no. 1: 18. https://doi.org/10.3390/pathogens12010018

APA Style

Martinez-Sánchez, M. E., Choreño-Parra, J. A., Álvarez-Buylla, E. R., Zúñiga, J., & Balderas-Martínez, Y. I. (2023). CD4+ T Cell Regulatory Network Underlies the Decrease in Th1 and the Increase in Anergic and Th17 Subsets in Severe COVID-19. Pathogens, 12(1), 18. https://doi.org/10.3390/pathogens12010018

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