近日，法国艾克斯马赛大学Rafael J. Argüello等研究人员开发了一种单细胞能量代谢分析方法。相关论文发表在2020年12月1日出版的《细胞—代谢》杂志上。

研究人员设计了一种简单的用于复杂代谢谱分析的方法，称为SCENITH，可通过对翻译抑制谱进行分析来进行单细胞能量代谢。SCENITH能够通过流式细胞仪同时研究多种细胞类型的代谢反应。SCENITH旨在进行离体代谢研究，特别是对全血样品中的稀有细胞进行代谢研究，从而避免了培养基引起的代谢偏差。

研究人员分析了患者实体瘤中的髓样细胞，并以与其谱系或激活表型无关的方式鉴定了变化的代谢谱。SCENITH能够揭示全局代谢功能并确定稀有细胞亚群中复杂且关联的免疫表型，这将有助于评估治疗反应或用于患者分层。

据介绍，能量代谢重编程对于癌症和免疫反应至关重要。在功能上描述全局代谢能力和细胞依赖性的现有方法是批量进行的。

附：英文原文

Title: SCENITH: A Flow Cytometry-Based Method to Functionally Profile Energy Metabolism with Single-Cell Resolution

Author: Rafael J. Argüello, Alexis J. Combes, Remy Char, Julien-Paul Gigan, Ania I. Baaziz, Evens Bousiquot, Voahirana Camosseto, Bushra Samad, Jessica Tsui, Peter Yan, Sebastien Boissonneau, Dominique Figarella-Branger, Evelina Gatti, Emeline Tabouret, Matthew F. Krummel, Philippe Pierre

Issue&Volume: 2020/12/01

Abstract: 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.

DOI: 10.1016/j.cmet.2020.11.007

Source: https://www.cell.com/cell-metabolism/fulltext/S1550-4131(20)30602-1