Evidence map›Paper›PMID 41423463›Full record

ArticleNature communications2025

Single cell profiling framework reveals metabolic subpopulations as drivers of bioproduction heterogeneity.

Juline Savigny, Kiyan Shabestary, Maria Portela, Cinzia Klemm, Yvette Sum, Piotr Hapeta, Marko Storch, Christopher Rowlands, Rodrigo Ledesma-Amaro

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Juline SavignyDepartment of Bioengineering, Imperial College London, London, UK.
Kiyan ShabestaryDepartment of Bioengineering, Imperial College London, London, UK.
Maria PortelaDepartment of Bioengineering, Imperial College London, London, UK.ORCID http://orcid.org/0009-0008-7887-1726
Cinzia KlemmDepartment of Bioengineering, Imperial College London, London, UK.ORCID http://orcid.org/0000-0003-3198-4439
Yvette SumDepartment of Bioengineering, Imperial College London, London, UK.
Piotr HapetaLondon Biofoundry, Translation and Innovation Hub, Imperial College White City Campus, London, UK.
Marko StorchLondon Biofoundry, Translation and Innovation Hub, Imperial College White City Campus, London, UK.ORCID http://orcid.org/0000-0003-1503-8282
Christopher RowlandsDepartment of Bioengineering, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-8261-2371
Rodrigo Ledesma-AmaroDepartment of Bioengineering, Imperial College London, London, UK. r.ledesma-amaro@imperial.ac.uk.ORCID http://orcid.org/0000-0003-2631-5898

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Euratom (H2020 Euratom Research and Training Programme 2014-2018) DEUSBIO - 949080RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/R01602X/1, BB/T013176/1, BB/T011408/1 - 19-ERACoBioTech- 33 SyCoLim, BB/X01911X/1, BB/Y008510/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) AI-4-EB BB/W013770/1, and EEBio Programme Grant EP/Y014073/1
6 · The paper itself

Abstract

Heterogeneity within clonal cell populations remains a critical bottleneck within bioprocess engineering, notably by undermining bioproduction yields. Efforts to mitigate its impact have, however, been hampered by technological difficulties quantifying metabolism at the single-cell level. Here, we propose a framework based on single-cell biosensor analysis that enables robust characterisation of cell's metabolic states, leveraging it to detect and isolate isogeneic heterogeneity in response to environmental perturbations and within microbial cell factories. We identify acute and gradual glucose depletion to induce differentiation of metabolically distinct subpopulations and reveal these subpopulations to exhibit differential production capabilities, with lower intracellular pH subpopulations exhibiting enhanced product accumulation within violacein-producing strains but reduced yields within lycopene-producing strains. Lastly, we highlight galactose cultivation as a method to modulate subpopulation dynamics towards higher-producing lycopene phenotypes. Altogether, our research provides insights into subpopulation differentiation and establishes promising avenues for the engineering of more robust and higher-producing strains.

Indexed as

Single-Cell AnalysisBiosensing TechniquesCarotenoidsEscherichia coliGalactoseGlucoseHydrogen-Ion ConcentrationIndolesLycopeneMetabolic EngineeringCarotenoidsGalactoseGlucoseIndolesLycopeneviolacein

Identifiers

PMID41423463
PMCPMC12816005

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.