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

Rafael J Argüello 1∞ , Rafael Argüello (1, 2) , Alexis J Combes (3) , Remy Char (1) , Julien-Paul Gigan (1) , Ania Baaziz (1) , Evens Bousiquot (1) , Voahirana Camosseto (1) , Bushra Samad (4) , Jessica Tsui (4) , Peter Yan (4) , Sebastien Boissonneau (5) , Dominique Figarella-Branger (6, 7) , Evelina Gatti (1) , Emeline Tabouret (6, 8) , Matthew F Krummel , Philippe Pierre (1, 9)

1 CIML - Centre d'Immunologie de Marseille - Luminy
2 INSERM - Institut National de la Santé et de la Recherche Médicale
3 UC San Francisco - University of California [San Francisco]
4 Department of Pathology, University of California, San Francisco
5 AMU MED - Aix-Marseille Université - Faculté de médecine
6 INP - Institut de neurophysiopathologie
7 ACPNP - Service d'Anatomo-Cyto-Pathologie et de NeuroPathologie [Hôpital de la Timone - APHM]
8 Neuro-Oncologie [Hôpital de la Timone - APHM]
9 iBiMED - Institute for Research in Biomedicine

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 nor their activation phenotype. SCENITH 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.

Domaines: Biologie cellulaire; Immunologie

Rafael J Argüello 1∞, Rafael Argüello, Alexis J Combes, Remy Char, Julien-Paul Gigan, et al.. SCENITH: A Flow Cytometry-Based Method to Functionally Profile Energy Metabolism with Single-Cell Resolution. Cell Metabolism, 2020, 32 (6), pp.1063-1075.e7. ⟨10.1016/j.cmet.2020.11.007⟩. ⟨hal-03082094⟩