Delayed type I interferon response and the subsequent out-of-sequence cytokine signal inhibit T cell induction in non-surviving Ebola virus-infected patients

Zhao, Gang (avtor), Korva, Miša (avtor), Muñoz-Fontela, César (avtor), Günther, Stephan (avtor), Kerber, Romy (avtor), Binder, Sebastian C. (avtor), Meyer-Hermann, Michael (avtor)

Introduction: While there is evidence that Ebola virus (EBOV) antagonizes the antiviral type I interferon (IFN-I) response, the role of IFN-I for EBOV disease remains controversial, as initially protective responses may contribute to disease pathogenesis later. Methods: We analyzed patient data from the 2014-2016 West Africa epidemic with a combination of machine learning and mathematical modeling to identify predictive immune mediators and reconstruct their temporal dynamics in survivors and non-survivors. Results: Our results suggest that IFN-I response in survivors occurs before symptom onset, while non-survivors mount IFN-I responses 3-4 days later, although with a similar strength. This delayed IFN-I response overlaps in time with IL-12 signals in non-survivors. As optimal T cell activation requires a particular temporal sequence in cytokine signals, this impairs the development of T cell-based cellular immunity. Discussion: The presented patient data analysis helps reconcile the seemingly contradictory role of IFN-I in EBOV disease from a cytokine dynamics perspective and supports the theory of sequential T cell activation, according to which a dysregulated temporal sequence of cytokine signals keeps T cells unresponsive to the pathogen.

• Jezik: Angleški jezik
• Ključne besede: Ebola virus, cytokine dynamics, innate adaptive immune crosstalk, machine learning - ML, mathematical model, sequential cytokine signaling, type I interferon
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: MF - Medicinska fakulteta
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2026
• Št. strani: 10 str.
• Številčenje: Vol. 17, art. 1806697
• PID: 20.500.12556/RUL-183189
• UDK: 616-097
• ISSN pri članku: 1664-3224
• DOI: 10.3389/fimmu.2026.1806697
• COBISS.SI-ID: 280576771
• Datum objave v RUL: 07.06.2026

Gradivo je del revije

• Naslov: Frontiers in immunology
• Skrajšan naslov: Front. immunol.
• Založnik: Frontiers Research Foundation
• ISSN: 1664-3224
• COBISS.SI-ID: 30774233

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: virus Ebola, dinamika citokinov, interakcija med prirojenim in pridobljenim imunskim odzivom, strojno učenje - ML, matematični model, sekvenčno signaliziranje citokinov, interferon tipa I

Projekti

• Financer: MWK - Lower Saxony Ministry of Science and Culture