kth.sePublications KTH
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Dissecting autonomous enzymatic variability in single cells
KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-6566-3559
KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0003-3361-3797
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-5326-7134
Show others and affiliations
2026 (English)In: Nature Communications, E-ISSN 2041-1723, Vol. 17, no 1, article id 5788Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature , 2026. Vol. 17, no 1, article id 5788
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-387126DOI: 10.1038/s41467-026-74172-zISI: 001811552100004PubMedID: 42393051Scopus ID: 2-s2.0-105043610619OAI: oai:DiVA.org:kth-387126DiVA, id: diva2:2092079
Note

QC 20260813

Available from: 2026-08-13 Created: 2026-08-13 Last updated: 2026-08-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Gnann, ChristianSigaeva, AlinaLe, TrangCesnik, Anthony J.Sariyar, SanemMahdessian, DianaUhlén, MathiasAxelsson, UlrikaKäller Lundberg, Emma

Search in DiVA

By author/editor
Gnann, ChristianSigaeva, AlinaLe, TrangCesnik, Anthony J.Sariyar, SanemMahdessian, DianaUhlén, MathiasAxelsson, UlrikaKäller Lundberg, Emma
By organisation
Science for Life Laboratory, SciLifeLabSchool of Engineering Sciences in Chemistry, Biotechnology and Health (CBH)Systems BiologyBiomedical proteomics
In the same journal
Nature Communications
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 14 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf