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

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

doi:10.1038/s41467-023-43917-5

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

Nat Commun. 2023 Dec 13;14(1):8260. doi: 10.1038/s41467-023-43917-5.

Authors

Thomas Hu^#^{1

2}, Mayar Allam^#¹, Shuangyi Cai¹, Walter Henderson³, Brian Yueh⁴, Aybuke Garipcan⁴, Anton V Ievlev⁵, Maryam Afkarian⁶, Semir Beyaz⁴, Ahmet F Coskun^{7

8

9

10}

Affiliations

¹ Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
² School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
³ Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, USA.
⁴ Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
⁵ Oak Ridge National Laboratory, Center for Nanophase Materials Sciences, Oak Ridge, TN, USA.
⁶ Division of Nephrology, Department of Internal Medicine, University of California, Davis, CA, USA.
⁷ Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA. ahmet.coskun@bme.gatech.edu.
⁸ Interdisciplinary Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, GA, USA. ahmet.coskun@bme.gatech.edu.
⁹ Winship Cancer Institute, Emory University, Atlanta, GA, USA. ahmet.coskun@bme.gatech.edu.
¹⁰ Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA. ahmet.coskun@bme.gatech.edu.

^# Contributed equally.

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.

MeSH terms

Female
Humans
Lung Neoplasms*
Male
Metabolomics* / methods
Systems Biology

Abstract

MeSH terms

Grants and funding