Towards GLIMPSE: Enabling technology to map cytokines in inflamed tissue

免疫和炎症是各种疾病的基础，如癌症、自身免疫和 神经退行性变。在这些系统中的每一个系统中，分泌的细胞因子协调着 淋巴细胞和组织驻留细胞，以正确平衡增殖、分化、迁移和细胞死亡。 尽管细胞因子起着关键的机械作用，它们有望成为药物靶点，但目前还没有工具 在没有基因修饰的情况下，检测它们在组织中的空间分布。我们推测，我们知道 当分泌细胞因子时，将极大地加速有效免疫疗法的设计 暴露出细胞活动的口袋。然而，成像细胞因子分布的尝试因快速的 小蛋白的质量传输，大抗体试剂的传递受阻，以及要求 试剂不会改变活细胞和组织的状态。 这个项目的目标是创造第一种方法来量化活组织中局部细胞因子的浓度 样品在体外，同时保存组织的状态和结构。我们的方法是轻轻地捕获一个 将分泌的细胞因子的一部分直接放到其分泌位置附近的细胞上，用荧光标记的 抗体片段，并通过活组织荧光成像成像蛋白的分布。为了避免 在化验过程中无意中激活了组织，我们将处理抗体片段和小肽 而不是可以结合Fc受体的完整抗体。淋巴结中的蛋白质信号将是 被用作案例研究，因为参与炎症的关键蛋白质(细胞因子)已经得到了很好的研究， 可以量化的效果，作为治疗炎症性疾病的药物靶点是有意义的。在这项试点计划中，我们将 开发一种概念验证试验，利用抗体片段检测T细胞特异性细胞因子的分泌(目标1)， 同时开发检测淋巴细胞表面标志和细胞因子的新型多肽试剂 (目标2)。该检测将以固定组织的免疫染色、流式细胞术和ELISA为基准。 该检测和新的试剂将在两个不同的物种上进行测试，小鼠和人类，以证明 炎症性疾病中细胞因子的检测原理。 如果成功，这个高风险、高回报的项目将展示第一次化学成像的可行性 方法在不固定的组织中产生细胞因子分泌的“地图”。拟议中的技术是故意 模块化，允许随时转座来检测其他组织中的其他蛋白质，并且很容易对多个 同时产生细胞因子。原则上，这项技术可以被用来可视化任何蛋白质 抗体对或多肽结合剂可用于任何软组织，以革命性地理解 免疫系统中基于蛋白质的串扰。这些数据将使未来的R01应用程序能够扩展 方法添加额外的细胞和细胞因子，能够随着时间的推移在同一组织中重复分析，并应用它 成像炎症性疾病，特别是神经炎性疾病中的动态细胞因子信号。

Immunity and inflammation are fundamental to diseases as diverse as cancer, autoimmunity, and neurodegeneration. In each of these systems, secreted cytokines coordinate an intricate dance between lymphocytes and tissue-resident cells, to correctly balance proliferation, differentiation, migration, and cell death. Despite the critical mechanistic role of cytokines and their promise as a drug target, there are currently no tools to detect their spatial distribution in tissue without genetic modification. We speculate that knowledge of where and when cytokines are secreted would dramatically accelerate the design of effective immunotherapies by revealing pockets of cellular activity. However, attempts to image cytokine distribution are frustrated by the rapid mass transport of small proteins, the hindered delivery of large antibody-based reagents, and the requirement that the reagents not alter the state of live cells and tissue. The goal of this project is to create the first method to quantify local cytokine concentrations in live tissue samples ex vivo, while preserving the state and structure of the tissue. Our approach is to gently capture a fraction of the secreted cytokine directly onto cells near where it was secreted, label it with a fluorescently-tagged antibody fragment, and image the distribution of the protein by live-tissue fluorescence imaging. To avoid inadvertently activating the tissue during the assay, we will work with antibody fragments and small peptide binders, rather than intact antibodies that could bind Fc receptors. Protein signaling in the lymph node will be used as a case study because the key proteins (cytokines) involved in inflammation are well-studied, have quantifiable effects, and are of interest as drug targets for inflammatory diseases. In this pilot proposal, we will develop a proof-of-concept assay to detect T cell-specific cytokine secretion, using antibody fragments (Aim 1), and simultaneously develop novel peptide-based reagents to detect lymphocyte surface markers and cytokines (Aim 2). The assay will be benchmarked against immunostaining of fixed tissues, flow cytometry, and ELISA. The assay and new reagents will be tested in two different species, mouse and human, to demonstrate proof-of- principle of cytokine detection during inflammatory disease. If successful, this high-risk, high-reward project will show the feasibility of the first chemical imaging method to generate “maps” of cytokine secretion in unfixed tissue. The proposed technology is deliberately modular to allow ready transposition to detect other proteins in other tissues, and is easily multiplexed for multiple cytokines simultaneously. The technology can, in principle, be adopted to visualize any protein for which an antibody pair or peptide binder is available, and used in any soft tissue, to revolutionize the understanding of protein-based cross-talk in the immune system. The data will enable a future R01 application to expand the method to additional cells and cytokines, enable repeated analysis in the same tissue over time, and to apply it to image dynamic cytokine signaling in inflammatory disease, particularly in neuroinflammation.