Dissecting autonomous enzymatic variability in single cells

C Christian Gnann A Alina Sigaeva T Trang Le A Anthony J. Cesnik S Sanem Sariyar D Diana Mahdessian R Rutger Schutten P Preethi Raghavan M Manuel D. Leonetti C Cecilia Lindskog M Mathias Uhlén (Department of Protein Science, SciLifeLab, KTH-Royal Institute of Technology) U Ulrika Axelsson E Emma Lundberg

Abstract

Abstract Metabolic enzymes perform life-sustaining functions in various cellular compartments. Anecdotally, metabolic activity is observed to vary between genetically identical cells, which impacts drug resistance, differentiation, and immune cell activation. However, no large-scale resource systematically reporting metabolic cellular heterogeneity exists. Here, we leverage imaging-based single-cell spatial proteomics to reveal the extent of non-genetic variability of the human enzymatic proteome, as a proxy for metabolic states. Nearly two fifths of enzymes exhibit cell-to-cell variable expression, and half localize to multiple cellular compartments. Metabolic heterogeneity arises largely autonomously of cell cycling, and individual cells reestablish these myriad metabolic phenotypes over several cell divisions. We reveal through multiplexed imaging that metabolic states are continuous and that the correlation between metabolic pathways is metabolic state dependent. These results establish cell-to-cell enzymatic heterogeneity as an organizing principle of cell biology that may rewire our understanding of drug resistance, treatment design, and other aspects of medicine.

Article Details

Volume / Issue Vol. 17, Issue 1
Published July 02, 2026
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (13)

C

Christian Gnann

A

Alina Sigaeva

T

Trang Le

A

Anthony J. Cesnik

S

Sanem Sariyar

D

Diana Mahdessian

R

Rutger Schutten

P

Preethi Raghavan

M

Manuel D. Leonetti

C

Cecilia Lindskog

M

Mathias Uhlén

Department of Protein Science, SciLifeLab, KTH-Royal Institute of Technology

U

Ulrika Axelsson

E

Emma Lundberg