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.

细胞能够感知外部的机械信号并将其转化为生化信号，这些信号在组织稳态、发育和疾病期间对细胞过程具有重要影响。然而，我们的理解力传感和转导的具体机制目前是有限的，在生理背景下，许多重要的机械化学过程的分子机制仍然在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感测和响应。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-细胞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的方法，在工程和微制造，生物物理学，计算机视觉和建模，先进的生物成像和生物信息学显微镜的创新。我们的平台的新颖设计将使细胞的顺序加载，以形成平行的细胞操作和成像的细胞双峰。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一个巨大的挑战。我们还将开发一种新的流动管理系统，允许可编程和有针对性的细胞检索，用于芯片外分析，如组学方法。我们将进一步调整光片显微镜，以成像整个细胞体积和亚细胞分子动力学。我们将开发新的微流控室设计和成像协议，同时双色图像采集。此外，行业合作伙伴Intelligent imaging innovations（3 i）是光片显微镜的领先开发商，将提供对广泛用户有价值的实用解决方案。我们将使用先进的方法进行自动细胞分割和亚细胞区域跟踪，以绘制4D荧光分布图。我们将利用神经网络生成建模的最新发展，从双色通道实验中聚合数据。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，我们将使用两个独立的细胞系统。制造心脏/心肌的心肌细胞负责产生收缩力并永久暴露于机械刺激。传递到核膜的外力被证明在心肌细胞功能中是关键的，并且该途径中的缺陷可导致疾病（心脏纤层蛋白病）。胚胎干细胞（ES）通过产生体内所有细胞谱系在发育中发挥关键作用，在再生医学中也至关重要。ES细胞需要来自邻近细胞的机械信号，以在发育期间发挥适当的功能，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，我们的平台很容易适应其他细胞类型和粘附基底上的非悬浮细胞，并且可以与化合物的靶向递送相结合。我们预计我们的平台还将能够在更广泛的背景下研究机械传导的作用，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。