Nanberg, E. | bioRxiv Science

bioRxiv2023

Mathematical models disentangle the role of IL-10 feedbacks in human monocytes upon proinflammatory activation

Inflammation is one of the vital mechanisms through which the immune system responds to harmful stimuli. During inflammation, pro and anti-inflammatory cytokines interplay to orchestrate fine-tuned, dynamic immune responses. The cytokine interplay governs switches in the inflammatory response and dictates the propagation of inflammation. Molecular pathways underlying the interplay are complex, and time-resolved monitoring of mediators and cytokines is necessary as a basis to study them in detail. Our understanding can be advanced by in silico models which enable to analyze the system of interactions and their dynamical interplay in detail. We, therefore, used a mathematical modeling approach to study the interplay between prominent pro and anti-inflammatory cytokines with a focus on Tumor Necrosis Factor (TNF) and Interleukin 10 (IL-10) in lipopolysaccharide (LPS)-primed primary human monocytes. Relevant time-resolved data were generated by experimentally adding or blocking IL-10 at different time points. The model was successfully trained and could predict independent validation data and was further used to perform in silico experiments to disentangle the role of IL-10 feedbacks in acute inflammation. We used the insight to obtain a reduced predictive model including only the necessary IL-10-mediated feedbacks. Finally, the validated reduced model was used to predict early IL-10 - TNF switches in the inflammatory response. Overall, we gained detailed insights into fine-tuning of inflammatory responses in human monocytes and present a model for further use in studying the complex and dynamic process of cytokine-regulated acute inflammation.

systems biology↗

bioRxiv2017

From Cohorts to Molecules: Adverse Impacts of Endocrine Disrupting Mixtures

Convergent evidence associates endocrine disrupting chemicals (EDCs) with major, increasingly-prevalent human disorders. Regulation requires elucidation of EDC-triggered molecular events causally linked to adverse health outcomes, but two factors limit their identification. First, experiments frequently use individual chemicals, whereas real life entails simultaneous exposure to multiple EDCs. Second, population-based and experimental studies are seldom integrated. This drawback was exacerbated until recently by lack of physiopathologically meaningful human experimental systems that link epidemiological data with results from model organisms.\n\nWe developed a novel approach, integrating epidemiological with experimental evidence. Starting from 1,874 mother-child pairs we identified mixtures of chemicals, measured during early pregnancy, associated with language delay or low-birth weight in offspring. These mixtures were then tested on multiple complementary in vitro and in vivo models. We demonstrate that each EDC mixture, at levels found in pregnant women, disrupts hormone-regulated and disease-relevant gene regulatory networks at both the cellular and organismal scale.

molecular biology↗