Blood Systems Biology

描述（由申请人提供）：该提案侧重于人类血液的综合和高通量功能表型，通过系统生物学和生物工程方法匹配患者特异性训练的计算机模型，以识别和量化对凝血触发因素或药理学药物的反应。个体血液样本的高通量表型将用于训练静态、静脉和动脉血流动力学条件下自下而上和自上而下的血液凝固模型。目的1：使用高通量细胞内钙测量来训练神经网络模型来预测患者对组合和顺序刺激的特异性反应，从而测试血小板在血栓形成过程中实际经历的环境。此外，高通量的由内而外的信号将被用于血小板代谢途径的大规模计算模拟的发展。目标2：随着血小板表型，我们将使用经过验证的高通量凝血酶表型来识别存在但未定义缺陷的患者的缺陷途径和协同作用。这些方法允许开发一个完整的血小板-血浆凝血的计算机模拟。目的3：使用经过验证的组织因子微阵列流动室和微流体室，我们将在血液动力学条件和药物调节下对正常供体和患者的血栓产生和凝块稳定性进行功能表型分析。目的4：使用小鼠激光损伤模型进行体内研究，以跟踪不断变化的血栓内空间梯度。流动研究得到了先进的多尺度晶格动力学蒙特卡罗（LKMC）模拟的支持，该模拟使用了来自所有三个特定目标的数据。这些方法首次将血小板信号模型与调节黏附键功能和血浆蛋白酶网络的现实和分层血液动力学/质量传输模拟完全整合在一起。更好地阐明和定量测量血液动力学条件下的血液反应和血小板信号通路，有助于血栓形成风险评估、术中抗凝治疗、血小板靶向治疗和脑卒中研究的临床需要。

DESCRIPTION (provided by applicant): This proposal focuses on the integrative and high throughput functional phenotyping of human blood, matched by Systems Biology and Bioengineering approaches for patient-specific training of computer models to identify and quantify responses to clotting triggers or pharmacological agents. High throughput phenotyping of individual blood samples will be used to train bottom-up and top-down models of blood clotting under static, venous, and arterial hemodynamic conditions. Specific Aims are: Aim 1: Use high throughput intracellular calcium measurements to train neural network models to predict patient-specific response to combinatorial and sequential stimulation, thus testing the milieu that platelets actually experience during thrombosis. Furthermore, high throughput measures of inside-out signaling will be implemented for the development of large scale computational simulation of platelet metabolic pathways. Aim 2: Along with platelet phenotyping, we will use validated high throughput blood thrombin phenotyping to identify pathways and synergisms that are defective in patients with existing but undefined defects. These approaches then allow the development of a full platelet-plasma computer simulation of coagulation. Aim 3: Using validated tissue factor microarray-flow chambers and microfluidic chambers, we will functionally phenotype thrombus production and clot stability for normal donors and patients under hemodynamic conditions and pharmacological modulation. Aim 4: In vivo studies using a mouse laser injury model to follow evolving intrathrombic spatial gradients. The flow studies are supported by advanced multiscale Lattice Kinetic Monte Carlo (LKMC) simulation of clotting under flow using data from all three specific aims. These approaches represent the first full integration of platelet signaling models with realistic and hierarchical hemodynamic/mass transport simulations that regulate adhesive bond function and plasma protease networks. Better elucidation and quantitative measurement of blood reactions and platelet signaling pathways under hemodynamic conditions are directed at clinical needs in thrombosis risk assessment, anti-coagulation therapy during surgery, platelet targeted therapies, and stroke research. PUBLIC HEALTH RELEVANCE: Blood is ideal for Systems Biology research since it is easily obtained from donors or patients, amenable to high throughput liquid handling experiments, and clinically relevant. Clotting and bleeding diseases of aging are seldom due to acquired mutations and this drives the need for advanced functional phenotyping in concert with Systems Biology and other sequencing/genomic approaches.