Hierarchical effects of pro-inflammatory cytokines on the post-influenza susceptibility to pneumococcal coinfection

Abstract

In the course of influenza A virus (IAV) infections, a secondary bacterial infection frequently leads to serious respiratory conditions provoking high hospitalization and death tolls. Although abundant pro-inflammatory responses have been reported as key contributing factors for these severe dual infections, the relative contributions of cytokines remain largely unclear. In the current study, mathematical modelling based on murine experimental data dissects IFN-γ as a cytokine candidate responsible for impaired bacterial clearance, thereby promoting bacterial growth and systemic dissemination during acute IAV infection. We also found a time-dependent detrimental role of IL-6 in curtailing bacterial outgrowth which was not as distinct as for IFN-γ. Our numerical simulations suggested a detrimental effect of IFN-γ alone and in synergism with IL-6 but no conclusive pathogenic effect of IL-6 and TNF-α alone. This work provides a rationale to understand the potential impact of how to manipulate temporal immune components, facilitating the formulation of hypotheses about potential therapeutic strategies to treat coinfections.

Host‐pathogen kinetics during influenza infection and coinfection: insights from predictive modeling

“…It also begins to reveal the relationship between these rates and the strength needed to induce a change in the dynamics (eg, with drug therapy or coinfection). Further investigating how changing the rates affects outcome, for example, through sensitivity analysis, has generated predictions about the response to therapy or coinfection with other pathogens . Collectively, these types of analyses reveal aspects of influenza biology that are not immediately available from the experimental or clinical data alone.…”

“…Data-driven mathematical modeling studies are iterative and entail developing a model to describe the underlying biology, calibrating the model to experimental or clinical data, analyzing the model with mathematical techniques, using the model to make predictions and design experiments, and validating the predictions in the laboratory or clinic investigating how changing the rates affects outcome, for example, through sensitivity analysis, has generated predictions about the response to therapy 14,[19][20][21]36,56 or coinfection with other pathogens. [41][42][43]45 Collectively, these types of analyses reveal aspects of influenza biology that are not immediately available from the experimental or clinical data alone.…”

Influenza Species and Subtypes Circulation among Hospitalized Patients in Laleh Hospital during Two Influenza Seasonal (2016-2017 and 2017-2018) Using a Multiplex Real Time-Polymerase Chain Reaction

“…[10][11][12][13] Contrary to our results that showed subtype fluA H1N1 has least common prevalence, previous studies performed in Iran including prevalence of 10.6% to 17.5%. [14][15][16][17] The pattern of flu subtypes was different in two years period. Flu A was the dominant species in the 2016-2017 season, On the other hand, flu B was the major type in the 2017-1018 seasons.…”

The combination of oseltamivir with azithromycin does not show additional benefits over oseltamivir monotherapy in mice infected with influenza A(H1N1)pdm2009 virus

“…In this regard, azithromycin, a macrolide with known anti‐inflammatory and immunomodulatory properties, appears as an interesting therapeutic option . In addition, the antimicrobial properties of azithromycin could be of interest for preventing and/or treating secondary bacterial complications during influenza infections as well as concomitantly downregulating excessive inflammation . The benefits of macrolide therapy in clinical influenza infection remain unclear.…”

“…6 In addition, the antimicrobial properties of azithromycin could be of interest for preventing and/or treating secondary bacterial complications during influenza infections as well as concomitantly downregulating excessive inflammation. 7 The benefits of macrolide therapy in clinical influenza infection remain unclear. A randomized clinical study, including adults infected with A(H1N1)pdm09 influenza, demonstrated that the combination of azithromycin with oseltamivir led to earlier resolution of some influenza symptoms.…”