TY - JOUR
T1 - Single-cell metabolic profiling of human cytotoxic T cells
AU - Hartmann, Felix J.
AU - Mrdjen, Dunja
AU - McCaffrey, Erin
AU - Glass, David R.
AU - Greenwald, Noah F.
AU - Bharadwaj, Anusha
AU - Khair, Zumana
AU - Verberk, Sanne G.S.
AU - Baranski, Alex
AU - Baskar, Reema
AU - Graf, William
AU - Van Valen, David
AU - Van den Bossche, Jan
AU - Angelo, Michael
AU - Bendall, Sean C.
N1 - Funding Information: We thank L. Keren for insightful discussions and invaluable feedback as well as the Nakamura lab at the Gladstone Institutes for access to their Seahorse XF analyzer. Further, we thank A. Tsai for advice and help with clinical samples. This study was supported by an EMBO Long-Term Fellowship ALTF 1141–2017 (to F.J.H.), the Novartis Foundation for Medical-Biological Research 16C148 (to F.J.H.) and the Swiss National Science Foundation SNF Early Postdoc Mobility P2ZHP3-171741 (to F.J.H.). In addition, we received support from National Institutes of Health 1DP2OD022550-01 (to S.C.B.), 1R01AG056287-01 (to S.C.B.), 1R01AG057915-01 (to S.C.B.) and 1U24CA224309-01 (to S.C.B.). Publisher Copyright: © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/2
Y1 - 2021/2
N2 - Cellular metabolism regulates immune cell activation, differentiation and effector functions, but current metabolic approaches lack single-cell resolution and simultaneous characterization of cellular phenotype. In this study, we developed an approach to characterize the metabolic regulome of single cells together with their phenotypic identity. The method, termed single-cell metabolic regulome profiling (scMEP), quantifies proteins that regulate metabolic pathway activity using high-dimensional antibody-based technologies. We employed mass cytometry (cytometry by time of flight, CyTOF) to benchmark scMEP against bulk metabolic assays by reconstructing the metabolic remodeling of in vitro-activated naive and memory CD8+ T cells. We applied the approach to clinical samples and identified tissue-restricted, metabolically repressed cytotoxic T cells in human colorectal carcinoma. Combining our method with multiplexed ion beam imaging by time of flight (MIBI-TOF), we uncovered the spatial organization of metabolic programs in human tissues, which indicated exclusion of metabolically repressed immune cells from the tumor–immune boundary. Overall, our approach enables robust approximation of metabolic and functional states in individual cells.
AB - Cellular metabolism regulates immune cell activation, differentiation and effector functions, but current metabolic approaches lack single-cell resolution and simultaneous characterization of cellular phenotype. In this study, we developed an approach to characterize the metabolic regulome of single cells together with their phenotypic identity. The method, termed single-cell metabolic regulome profiling (scMEP), quantifies proteins that regulate metabolic pathway activity using high-dimensional antibody-based technologies. We employed mass cytometry (cytometry by time of flight, CyTOF) to benchmark scMEP against bulk metabolic assays by reconstructing the metabolic remodeling of in vitro-activated naive and memory CD8+ T cells. We applied the approach to clinical samples and identified tissue-restricted, metabolically repressed cytotoxic T cells in human colorectal carcinoma. Combining our method with multiplexed ion beam imaging by time of flight (MIBI-TOF), we uncovered the spatial organization of metabolic programs in human tissues, which indicated exclusion of metabolically repressed immune cells from the tumor–immune boundary. Overall, our approach enables robust approximation of metabolic and functional states in individual cells.
UR - http://www.scopus.com/inward/record.url?scp=85089994636&partnerID=8YFLogxK
U2 - https://doi.org/10.1038/s41587-020-0651-8
DO - https://doi.org/10.1038/s41587-020-0651-8
M3 - Article
C2 - 32868913
SN - 1087-0156
VL - 39
SP - 186
EP - 197
JO - Nature biotechnology
JF - Nature biotechnology
IS - 2
ER -