Aix Marseille Univ, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Marseille, France.
Department of Pathology, University of California, San Francisco, San Francisco, CA, USA; ImmunoX Initiative, University of California, San Francisco, San Francisco, CA, USA.
Cell Metab. 2020 Dec 1;32(6):1063-1075.e7. doi: 10.1016/j.cmet.2020.11.007.
Energetic metabolism reprogramming is critical for cancer and immune responses. Current methods to functionally profile the global metabolic capacities and dependencies of cells are performed in bulk. We designed a simple method for complex metabolic profiling called SCENITH, for single-cell energetic metabolism by profiling translation inhibition. SCENITH allows for the study of metabolic responses in multiple cell types in parallel by flow cytometry. SCENITH is designed to perform metabolic studies ex vivo, particularly for rare cells in whole blood samples, avoiding metabolic biases introduced by culture media. We analyzed myeloid cells in solid tumors from patients and identified variable metabolic profiles, in ways that are not linked to their lineage or their activation phenotype. SCENITH's ability to reveal global metabolic functions and determine complex and linked immune-phenotypes in rare cell subpopulations will contribute to the information needed for evaluating therapeutic responses or patient stratification.
能量代谢重编程对癌症和免疫反应至关重要。目前用于功能分析细胞全局代谢能力和依赖性的方法都是在批量水平上进行的。我们设计了一种名为 SCENITH 的简单方法，用于通过抑制翻译来进行单细胞能量代谢的复杂代谢特征分析。SCENITH 通过流式细胞术允许对多种细胞类型的代谢反应进行平行研究。SCENITH 旨在进行离体代谢研究，特别是针对全血样本中的稀有细胞，避免了由培养基引入的代谢偏差。我们分析了来自患者实体瘤中的髓样细胞，并确定了不同的代谢特征，这些特征与它们的谱系或激活表型无关。SCENITH 能够揭示全局代谢功能，并确定稀有细胞亚群中复杂且相关的免疫表型，这将有助于评估治疗反应或患者分层所需的信息。
