Department of Developmental Biology, Washington University School of Medicine in St. Louis, 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine in St. Louis, 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA; Center of Regenerative Medicine, Washington University School of Medicine in St. Louis, 660 S. Euclid Avenue, Campus Box 8103, St. Louis, MO 63110, USA.
Department of Biology, New York University, New York, NY 10003, USA.
Cell Stem Cell. 2022 Apr 7;29(4):635-649.e11. doi: 10.1016/j.stem.2022.03.001. Epub 2022 Mar 29.
Measuring cell identity in development, disease, and reprogramming is challenging as cell types and states are in continual transition. Here, we present Capybara, a computational tool to classify discrete cell identity and intermediate "hybrid" cell states, supporting a metric to quantify cell fate transition dynamics. We validate hybrid cells using experimental lineage tracing data to demonstrate the multi-lineage potential of these intermediate cell states. We apply Capybara to diagnose shortcomings in several cell engineering protocols, identifying hybrid states in cardiac reprogramming and off-target identities in motor neuron programming, which we alleviate by adding exogenous signaling factors. Further, we establish a putative in vivo correlate for induced endoderm progenitors. Together, these results showcase the utility of Capybara to dissect cell identity and fate transitions, prioritizing interventions to enhance the efficiency and fidelity of stem cell engineering.
在发育、疾病和重编程过程中，衡量细胞的身份是具有挑战性的，因为细胞类型和状态在不断转变。在这里，我们提出了 Capybara，这是一种用于分类离散细胞身份和中间“混合”细胞状态的计算工具，支持用于量化细胞命运转变动态的度量。我们使用实验谱系追踪数据来验证混合细胞，以证明这些中间细胞状态的多谱系潜力。我们将 Capybara 应用于诊断几种细胞工程方案的缺陷，鉴定心脏重编程中的混合状态和运动神经元编程中的靶外身份，并通过添加外源性信号因子来缓解这些状态。此外，我们为诱导内胚层祖细胞建立了一个假定的体内相关性。总之，这些结果展示了 Capybara 用于剖析细胞身份和命运转变的实用性，优先考虑干预措施以提高干细胞工程的效率和保真度。
