Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology
Thomas Hu
(Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)
Mayar Allam
(Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)
Shuangyi Cai
(Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)
Walter Henderson
(Institute for Electronics and Nanotechnology, Georgia Institute of Technology)
Brian Yueh
(Cold Spring Harbor Laboratory)
Aybuke Garipcan
(Cold Spring Harbor Laboratory)
Anton V. Ievlev
(Oak Ridge National Laboratory, Center for Nanophase Materials Sciences)
Maryam Afkarian
(Division of Nephrology, Department of Internal Medicine, University of California)
Semir Beyaz
(Cold Spring Harbor Laboratory)
Ahmet F. Coskun
(Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)
Abstract Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite profiling of single immune and cancer cells in male human tissues by incorporating untargeted spatial metabolomics and targeted multiplexed protein imaging in a single pipeline. We utilized the scSpaMet to profile cell types and spatial metabolomic maps of 19507, 31156, and 8215 single cells in human lung cancer, tonsil, and endometrium tissues, respectively. The scSpaMet analysis revealed cell type-dependent metabolite profiles and local metabolite competition of neighboring single cells in human tissues. Deep learning-based joint embedding revealed unique metabolite states within cell types. Trajectory inference showed metabolic patterns along cell differentiation paths. Here we show scSpaMet’s ability to quantify and visualize the cell-type specific and spatially resolved metabolic-protein mapping as an emerging tool for systems-level understanding of tissue biology.
Thomas Hu, Mayar Allam, Shuangyi Cai, et al. (2023). "Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology". Nature Communications. https://doi.org/10.1038/s41467-023-43917-5