24 research outputs found

    Integrative network modeling reveals mechanisms underlying T cell exhaustion.

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    Failure to clear antigens causes CD8+ T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8+ T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier pro-memory/proliferative (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that drug-induced interference with EZH2 function increases the proportion of pro-memory/proliferative cells in the early days post-activation

    Proinflammatory cytokine signaling required for the generation of natural killer cell memory

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    Although natural killer (NK) cells are classified as innate immune cells, recent studies demonstrate that NK cells can become long-lived memory cells and contribute to secondary immune responses. The precise signals that promote generation of long-lived memory NK cells are unknown. Using cytokine receptor-deficient mice, we show that interleukin-12 (IL-12) is indispensible for mouse cytomegalovirus (MCMV)-specific NK cell expansion and generation of memory NK cells. In contrast to wild-type NK cells that proliferated robustly and resided in lymphoid and nonlymphoid tissues for months after MCMV infection, IL-12 receptor–deficient NK cells failed to expand and were unable to mediate protection after MCMV challenge. We further demonstrate that a STAT4-dependent IFN-γ–independent mechanism contributes toward the generation of memory NK cells during MCMV infection. Understanding the full contribution of inflammatory cytokine signaling to the NK cell response against viral infection will be of interest for the development of vaccines and therapeutics

    In silico toxicology protocols

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    The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information
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