Mechanisms of a Sustained Anti-inflammatory Drug Response in Alveolar Macrophages Unraveled with Mathematical Modeling

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, proinflammatory and anti-inflammatory cytokines interplay to orchestrate fine-tuned and dynamic immune responses. The cytokine interplay governs switches in the inflammatory response and dictates the propagation and development of the inflammatory response. 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 mathematical models that 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 proinflammatory and anti-inflammatory cytokines with a focus on tumor necrosis factor and interleukin 10 (IL-10) in lipopolysaccharide-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 simulations to disentangle the role of IL-10 feedbacks during an acute inflammatory event. 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-tumor necrosis factor 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.

Engineering constructed of high selectivity dexamethasone aptamer based on truncation and mutation technology

Various biosensors based on aptamers are currently the most popular rapid detection approaches, but the performance of these sensors is closely related to the affinity of aptamers. In this work, a strategy for constructed high-affinity aptamer was proposed. By truncating the bases flanking the 59 nt dexamethasones (DEX) original aptamer sequence to improve the sensitivity of the aptamer to DEX, and then base mutation was introduced to further improve the sensitivity and selectivity of aptamers. Finally, the 33 nt aptamer Apt-M13 with G-quadruplex structures was obtained. The dissociation constant (K_d) was determined to be 200 nM by Graphene oxide (GO)-based fluorometry. As-prepared Apt-M13 was used for a label-free colorimetric aptamer sensor based on gold nanoparticles, the LOD was 3.2-fold lower than the original aptamer described in previous works. The anti-interference ability of DEX analogs is also further improved. It indicates that truncation technology effectively improves the specificity of the aptamer to DEX in this work, and the introduction of mutation further improves the affinity and selectivity of the aptamer to DEX. Therefore, the proposed aptamer optimization method is also expected to become a general strategy for various aptamer sequences.