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

Cell Metab

Aix Marseille Univ, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Marseille, France; Institute for Research in Biomedicine (iBiMED) and Ilidio Pinho Foundation, Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal; International Associated Laboratory (LIA) CNRS "Mistra", 13288 Marseille Cedex 9, France.

Published: December 2020

AI Article Synopsis

  • Energetic metabolism reprogramming is essential for understanding cancer and immune responses, but traditional methods analyze cells in bulk, which can miss important details.
  • The new technique, SCENITH, allows for detailed metabolic profiling at the single-cell level using flow cytometry, particularly effective for analyzing rare cells in whole blood without biases from cell culture.
  • By applying SCENITH to myeloid cells in tumor samples, researchers discovered diverse metabolic profiles that didn’t correlate with cell lineage or activation, enhancing the potential for better therapeutic evaluation and patient treatment strategies.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407169PMC
http://dx.doi.org/10.1016/j.cmet.2020.11.007DOI Listing

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