Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Hu, Thomas; Allam, Mayar; Cai, Shuangyi; Henderson, Walter; Yueh, Brian; Garipcan, Aybuke; Ievlev, Anton V.; Afkarian, Maryam; Beyaz, Semir; Coskun, Ahmet F.

doi:10.1038/s41467-023-43917-5

Title: Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Journal Article · 13 December 2023 · Nature Communications

DOI: https://doi.org/10.1038/s41467-023-43917-5 · OSTI ID:2441043

^[1];

^[2]; Cai, Shuangyi ^[2];

^[2]; Yueh, Brian ^[3]; Garipcan, Aybuke ^[3];

^[4];

^[5]; Beyaz, Semir ^[3];

^[1]

Georgia Institute of Technology, Atlanta, GA (United States); Emory Univ., Atlanta, GA (United States)
Georgia Institute of Technology, Atlanta, GA (United States)
Cold Spring Harbor Laboratory Cold Spring Harbor, NY (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)
Univ. of California, Davis, CA (United States)

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.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); National Science Foundation (NSF)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2441043

Journal Information:: Nature Communications, Journal Name: Nature Communications Journal Issue: 1 Vol. 14; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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