Filipovic David, Kana Omar, Marri Daniel, Bhattacharya Sudin
Institute for Quantitative Health Science & Engineering, East Lansing, MI, 48824, USA.
Department of Pharmacology & Toxicology, Michigan State University, East Lansing, MI, 48824, USA.
Curr Opin Toxicol. 2024 Jun;38. doi: 10.1016/j.cotox.2024.100475. Epub 2024 Mar 29.
The application and analysis of single-cell transcriptomics in toxicology presents unique challenges. These include identifying cell sub-populations sensitive to perturbation; interpreting dynamic shifts in cell type proportions in response to chemical exposures; and performing differential expression analysis in dose-response studies spanning multiple treatment conditions. This review examines these challenges while presenting best practices for critical single cell analysis tasks. This covers areas such as cell type identification; analysis of differential cell type abundance; differential gene expression; and cellular trajectories. Towards enhancing the use of single-cell transcriptomics in toxicology, this review aims to address key challenges in this field and offer practical analytical solutions. Overall, applying appropriate bioinformatic techniques to single-cell transcriptomic data can yield valuable insights into cellular responses to toxic exposures.
单细胞转录组学在毒理学中的应用与分析面临着独特的挑战。这些挑战包括识别对扰动敏感的细胞亚群；解释化学暴露后细胞类型比例的动态变化；以及在跨越多种处理条件的剂量反应研究中进行差异表达分析。本综述在探讨这些挑战的同时，还介绍了关键单细胞分析任务的最佳实践。这涵盖了细胞类型识别、差异细胞类型丰度分析、差异基因表达分析以及细胞轨迹分析等领域。为了加强单细胞转录组学在毒理学中的应用，本综述旨在解决该领域的关键挑战并提供实用的分析解决方案。总体而言，将适当的生物信息学技术应用于单细胞转录组数据能够为细胞对毒性暴露的反应提供有价值的见解。
