In-depth immunometabolic profiling by measuring single-cell protein translation inhibition via bioorthogonal noncanonical amino acid tagging (SCENITH-BONCAT)

Abstract

MotivationExtracellular Flux (XF) analysis has been a key technique in immunometabolism research, measuring cellular oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) to determine immune cell metabolic profiles. However, XF analysis has several limitations, including the need for purified adherent cells, relatively high cell numbers, and specialized equipment. Recently, a novel flow cytometry-based technique called SCENITH (Single Cell Energetic metabolism by profiling Translation inhibition) was introduced, which measures the inhibition of cellular protein synthesis as a proxy for metabolic activity in single cells. A limitation of this technique is its reliance on fluorescent staining of intracellular puromycin, a toxic antibiotic. To address this, we propose an alternative approach using biorthogonal noncanonical amino acid tagging (BONCAT) to measure protein synthesis. SummaryThe field of immunometabolism has revealed that cellular energy metabolism significantly contributes to immune cell function. Disturbances in immune cell metabolism have been associated with various diseases, including obesity, atherosclerosis, and cancer. To further advance immunometabolic research, developing novel methods to study the metabolism of immune cells in complex samples is essential. Here, we introduce CENCAT (Cellular Energetics through Non-Canonical Amino acid Tagging). This technique utilizes click-labeling of alkyne-bearing non-canonical amino acids (ncAAs) to measure protein synthesis inhibition as a proxy of metabolic activity. CENCAT successfully reproduced known metabolic signatures of immune cell activation. Specifically, LPS/IFN{gamma}-induced classical activation increased glycolytic capacity, and IL-4-induced alternative activation enhanced mitochondrial dependence in human primary macrophages. The assays applicability was further explored in more complex samples, including peripheral blood mononuclear cells (PBMCs) from healthy volunteers, which revealed diverse metabolic rewiring in immune cell subsets upon stimulation with different activators. Finally, CENCAT was used to analyze the cellular metabolism of murine tissue-resident immune cells from various organs. Principal component analysis (PCA) revealed tissue-specific clustering based on metabolic profiles, likely driven by microenvironmental priming of tissue-resident immune cells. In conclusion, CENCAT offers valuable insights into immune cell metabolic responses and presents a powerful platform for studying immune cell metabolism in complex samples and tissue-resident immune populations in both human and murine studies.