Development and application of an integrated robotic imaging platform for cell culture monitoring and optimization

前言：通过分化和表观遗传漂变来表征细胞和克隆谱系异质性的发展，在生物过程和组织工程的核心提出了许多基本挑战。目前迫切需要发展非破坏性的多参数分析技术，以评估跨越多代的细胞动力学。目标：我实验室的长期目标是发展生物工程策略，使个体细胞水平的生物过程和产品的优化和表征成为可能。生物工程在这个层面上的细节需要机器人显微镜，单细胞处理和操作，以及数据分析的信息学方法。我们假设，使用长期高分辨率活细胞成像进行的细胞行为分析将提供足够的措施，以实现培养控制方案，指导单个细胞沿着特定的分化轨迹发育。分类和控制方案将仅受限于成像的时空光谱分辨率和动态行为和细胞外观识别的鲁棒性。方法：在本项目中进行的工作将包括继续开发和优化用于生物组装的单个细胞的机械和光子操作；高精度显微镜机器人技术实现多维亮场和荧光时程成像制定算法和软件，以分析在延长时间过程成像过程中产生的多变量数据。现在，这些组件中的每一个都将集成到机器人成像生物反应器系统中，以实现对数百到数千个细胞的分辨率跟踪和分析，其中每个细胞的细节随着时间的推移可以观察到。新颖性：将高含量多维活细胞成像与信息学、单细胞操作机器人和光子学相结合，为生物发现和先进生物过程工程方法的发展提供了一个高度新颖的平台。此外，谱系信息学在细胞分析中的应用代表了培养分析中一个全新的细节水平——培养物不是根据总参数测量来分析的，而是在多代的单细胞尺度上估计和跟踪参数。随着细胞用于移植治疗和单细胞分析成为一项要求，这项工作预计将出现制造挑战。因此，拟议的研究项目具有发展基本方法和策略的潜力，这些方法和策略将在细胞治疗和基于细胞的药物制造领域得到广泛应用。

Preamble: Characterization of cells and the development of clonal lineage heterogeneity through differentiation and epigenetic drift poses many fundamental challenges at the heart of bioprocess and tissue engineering. There is an urgent and specific need for the development of nondestructive multi-parameter analytical technologies that can assess cellular dynamics along trajectories that span multiple generations.      Objectives: The long term objective of my laboratory is to develop bioengineering strategies that enables the optimization and characterization of bioprocesses and products at the level of the individual cell.  Bioengineering at this level of detail requires robotic microscopy, single cell handling and manipulation, and an informatics approach to data analysis.  We hypothesized that cellular behavior analysis performed using long-term high resolution live-cell imaging will provide sufficient measures to enable culture control schemes that direct the development of individual cells along specific differentiation trajectories. Classification and control schemes will be limited only by the spatial-temporal-spectral resolution of imaging and the robustness of dynamic behavior and cell appearance identification.    Approach:  The work performed in this project will involve continued development and optimization of mechanical and photonic manipulation of individual cells for bio-assembly;  the implementation of multidimensional bright field and fluorescence time course imaging using high precision microscope robotics; the formulation of algorithms and software to analyze the multivariate data produced during extended time course imaging.  Each of these components will now be integrated into a robotic-imaging bioreactor system to enable the tracking and analysis of hundreds to thousands of cells at resolutions in which details are observable for each cell over time.Novelty:  The integration of high-content multidimensional live-cell imaging with informatics and single cell manipulation robotics and photonics represents a highly novel platform for biological discovery and the development of advanced bioprocess engineering methodologies.  Further, the application of lineage informatics for the analysis of cells represents an entirely new level of detail in culture analysis - cultures are not analyzed in terms of gross parameter measurements, but rather parameters are estimated and tracked at the single cell scale over multiple generations.  This work anticipates manufacturing challenges that will arise as cells are used for transplant therapy and single-cell analysis becomes a requirement.  As such, the proposed research program has the potential to develop fundamental methods and strategies that will find wide application in the areas of cell therapy and cell-based pharmaceutical manufacturing.