Real-time computer vision tracking of stemness

描述（由申请人提供）：该提案解决了对新的干细胞工程工具集的需求，该工具集可以离体调节成体干细胞扩增（自我更新，无分化），以产生足够数量的细胞用于临床应用。该提案的目标是：1）开发一种计算机视觉系统，该系统可以在相衬图像中实时跟踪体外细胞分裂的时空历史; 2）使用这些数据自动导出对称性，分裂时间，汇合和预测人口增长模型的实时度量;和3）应用该系统开发新的策略，使生长因子介导的条件下成体干细胞扩增的产量最大化。“实时”意味着处理在图像采集之间的15分钟间隔内“在线”完成，并且该信息在细胞培养期间可用作过程监测和控制的反馈。在目标1中，将使用多模态细胞跟踪模块来实现对密集细胞群的鲁棒图像分割和跟踪，这些模块从不同的角度表示和推理细胞状态和运动，然后融合和协调各自的输出以做出协作决策。多模态模块将被制定为基于矢量的图形处理硬件上的快速实现。该系统将测量：增殖、谱系（即，亲本-子代关系）、静止和凋亡状态，所述细胞在发育中的肌源性干细胞（MDSC）的汇合群体内培养，所述MDSC包括永生化多能C2 C12、原代小鼠MDSC和原代人MDSC。在目标2中，该系统将被应用于细胞扩增行为的有效发现和表征以及标称培养条件的确定，以使用细胞外基质基质上的固定化生长因子的生物打印组合阵列来最大化对称性。在目标3中，将使用适应性传代培养策略证明细胞扩增的实时监测和控制;预测生长模型将发出何时暂停细胞培养的信号，然后进行荧光激活细胞分选以排除凋亡或分化细胞，从而选择性地富集传代培养物中表现出最高增殖率的细胞。将使用体外成骨和成肌作为范例分化指标，在传代培养之间监测分化潜能的维持。

DESCRIPTION (provided by applicant): This proposal addresses the need for new stem cell engineering toolsets that can regulate adult stem cell expansion (self-renewal, without differentiation) ex vivo in order to create sufficient numbers of cells for clinical applications. The goals of this proposal are to: 1) develop a computer vision system that tracks in real-time the spatiotemporal histories of cell divisions in vitro in phase-contrast imagery; 2) use this data to automatically derive real-time metrics of symmetry, division times, confluence, and predictive population growth models; and, 3) apply this system to develop novel strategies that maximize the yield of adult stem cell expansion in growth factor-mediated conditions. 'Real-time' means that processing is completed 'on-line' in the 15 minute intervals between image acquisitions, and this information is available during cell culture as feedback for process monitoring and control. In Aim 1, robust image segmentation and tracking of dense cell populations will be achieved using multi-modal cell tracking modules that represent and reason about cell states and motion from different perspectives, and then fuse and coordinate their respective outputs to make collaborative decisions. The multi-modal modules will be formulated for fast implementation on vector-based graphics processing hardware. The system will measure: proliferation, lineage (i.e., parent-daughter relationship), quiescence, and apoptotic states of each cell in culture within developing confluent populations of muscle-derived stem cells (MDSCs), including immortalized pluripotent C2C12, primary mouse MDSCs, and primary human MDSCs. In Aim 2, the system will be applied to efficient discovery and characterization of cell expansion behaviors and determination of nominal culture conditions to maximize symmetry using bio-printed combinatorial arrays of immobilized growth factors on extracellular matrix substrates. In Aim 3, real-time monitoring and control of cell expansion will be demonstrated using an adaptive subculturing strategy; the predictive growth model will signal when to suspend cell culture, followed by fluorescent-activated cell sorting to exclude apoptotic or differentiating cells, thus selectively enriching subcultures for cells exhibiting the highest proliferation rates. Maintenance of differentiative potential will be monitored between subcultures using in vitro osteogenesis and myogenesis as paradigm differentiation indices.