CMMI-EPSRC: A novel multifunctional platform to study cell and nuclear mechanosensing

CMMI-EPSRC：研究细胞和核机械传感的新型多功能平台

• 批准号: EP/X026663/1
• 负责人: Michael Smutny
• 金额: $ 111.69万
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX026663%2F1
• 关键词: CMMI; EPSRC; novel; multifunctional; platform

Cells are able to sense and translate external mechanical cues into biochemical signals, which have major effects on cellular processes during tissue homeostasis, development and diseases. However, our understanding of the specific mechanisms of force sensing and transduction is currently limited and molecular mechanisms underpinning many important mechanochemical processes in a physiological context remain largely elusive. In this project we will build on recent advances in microfluidics and fast 3D imaging as well as new machine learning methods for analysing complex 3D timeseries to develop precise, high-throughput methods to probe and quantify cellular force sensing and response. Our versatile high-throughput mechanobiology platform will allow us to study cellular and molecular responses of cells to specific mechanical signals transmitted through physical cell-cell interactions, providing insights into the role of mechanical stimuli in fundamental cellular and developmental processes. The generation of such a platform relies on an interdisciplinary approach with innovations in engineering and microfabrication, biophysics, computer vision and modelling, advanced microscopy for bioimaging and bioinformatics. The novel design of our platform will enable sequential loading of cells to form cell doublets for parallel cell manipulation and imaging. It will allow for the application of three physiologically relevant force types (shear, compression, tension) to cells with precise regulation of their magnitude, duration and frequency, which is vastly challenging with conventional microfluidic devices. We will also develop a new flow management system allowing programmable and targeted retrieval of cells for off-chip analyses such as omics approaches.We will further adapt light-sheet microscopy to image whole cell volumes and subcellular molecular dynamics. We will develop new microfluidic chamber designs and imaging protocols for simultaneous dual-color image acquisition. Moreover, industry partner Intelligent imaging innovations (3i), who are a leading developer of lightsheet microscopy, will provide practicable solutions that will be valuable to a wide range of users.We will use advanced methods for automated cell segmentation and tracking of subcellular regions to map fluorescence distributions in 4D. We will build on recent developments in generative modelling using neural networks to aggregate data from dual colour channel experiments. Mathematical models will help to interpret the complex relationships in the data and to guide new experiments.To demonstrate broad applicability and versatility of our platform, we will utilize two independent cellular systems. Cardiomyocyte cells that make the heart/cardiac muscle are responsible for generating contractile forces and are permanently exposed to mechanical stimulation. External forces transmitted to the nuclear envelope were shown to be critical in cardiomyocyte function and defects in this pathway can lead to diseases (cardiac laminopathies). Embryonic stem (ES) cells play pivotal roles in development by giving rise to all cell lineages in the body and are also crucial in regenerative medicine. ES cells require mechanical signals from neighboring cells for proper function during development including establishing specific cell identities . We will further advance recent bioinformatic analysis tools to identify changes in chromatin accessibility and gene expression due to specific force inputs.Importantly, our platform is easily adaptable to other cell types and non-suspended cells on adhesive substrates, and can be combined with targeted delivery of compounds. We anticipate that our platform will also enable investigating the role of mechanotransduction in a broader context, including cancer, immunology and regeneration, and can further be adapted for drug discovery and screening.

细胞能够感知外部机械信号并将其转化为生化信号，这对组织稳态、发育和疾病期间的细胞过程产生重大影响。然而，我们对力传感和转导的具体机制的理解目前是有限的，并且在生理背景下支撑许多重要的机械化学过程的分子机制仍然很大程度上难以捉摸。在这个项目中，我们将基于微流体和快速 3D 成像的最新进展以及用于分析复杂 3D 时间序列的新机器学习方法，开发精确、高通量的方法来探测和量化细胞力传感和响应。我们的多功能高通量机械生物学平台将使我们能够研究细胞对通过物理细胞间相互作用传递的特定机械信号的细胞和分子反应，从而深入了解机械刺激在基本细胞和发育过程中的作用。这样一个平台的产生依赖于跨学科方法，包括工程和微加工、生物物理学、计算机视觉和建模、生物成像和生物信息学的先进显微镜技术的创新。我们平台的新颖设计将能够顺序加载细胞以形成细胞双联体，用于并行细胞操作和成像。它将允许对细胞施加三种生理相关的力类型（剪切、压缩、张力），并精确调节其大小、持续时间和频率，这对传统的微流体装置来说是巨大的挑战。我们还将开发一种新的流程管理系统，允许对细胞进行可编程和有针对性的检索，以进行组学方法等片外分析。我们将进一步采用光片显微镜来对全细胞体积和亚细胞分子动力学进行成像。我们将开发新的微流体室设计和成像协议，以实现同时双色图像采集。此外，行业合作伙伴Intelligent Imaging Innovations (3i)是光片显微镜的领先开发商，他们将提供对广大用户有价值的实用解决方案。我们将使用先进的自动细胞分割和亚细胞区域跟踪方法来绘制 4D 荧光分布图。我们将基于生成模型的最新发展，使用神经网络来聚合来自双颜色通道实验的数据。数学模型将有助于解释数据中的复杂关系并指导新的实验。为了证明我们平台的广泛适用性和多功能性，我们将利用两个独立的细胞系统。构成心脏/心肌的心肌细胞负责产生收缩力并永久暴露于机械刺激下。研究表明，传递到核膜的外力对心肌细胞功能至关重要，该途径的缺陷可能导致疾病（心脏核纤层蛋白病）。胚胎干 (ES) 细胞在发育过程中发挥着关键作用，可产生体内所有细胞谱系，并且在再生医学中也至关重要。 ES 细胞在发育过程中需要来自邻近细胞的机械信号才能发挥正常功能，包括建立特定的细胞身份。我们将进一步推进最新的生物信息学分析工具，以识别由于特定的力输入而导致的染色质可及性和基因表达的变化。重要的是，我们的平台可以轻松适应其他细胞类型和粘附基质上的非悬浮细胞，并且可以与靶向递送相结合的化合物。我们预计我们的平台还将能够研究机械转导在更广泛的背景下的作用，包括癌症、免疫学和再生，并且可以进一步适用于药物发现和筛选。