Evidence map›Paper›PMID 30783105›Full record

ArticleNature communications2019

Eliciting the impacts of cellular noise on metabolic trade-offs by quantitative mass imaging.

A E Vasdekis, H Alanazi, A M Silverman, C J Williams, A J Canul, J B Cliff, A C Dohnalkova, G Stephanopoulos

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

17 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Video-rate Raman-based metabolic imaging by Airy light-sheet illumination and photon-sparse detection.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
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  8. Article
  9. Article
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  11. Article
  12. Microbial metabolic noise.WIREs mechanisms of disease · 2021
    Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
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

8 authors at 4 institutions in 1 country.

A E VasdekisDepartment of Physics, University of Idaho, Moscow, ID, 83844, USA. andreasv@uidaho.edu.
H AlanaziDepartment of Physics, University of Idaho, Moscow, ID, 83844, USA.
A M SilvermanDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
C J WilliamsDepartment of Statistical Science, University of Idaho, Moscow, ID, 83844, USA.
A J CanulDepartment of Physics, University of Idaho, Moscow, ID, 83844, USA.
J B CliffEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.
A C DohnalkovaEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.
G StephanopoulosDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
University of Idaho · USMassachusetts Institute of Technology · USEnvironmental Molecular Sciences Laboratory · USPacific Northwest National Laboratory · US

Funding

Sequence-structure-function relationships in human visual photopigmentsP20GM104420 · NIGMS · UNIVERSITY OF IDAHO · PI VAN LEUVEN, JAMES · 2015 to 2024
$22.9M
NIGMS NIH HHS P20 GM104420
6 · The paper itself

Abstract

Optimal metabolic trade-offs between growth and productivity are key constraints in strain optimization by metabolic engineering; however, how cellular noise impacts these trade-offs and drives the emergence of subpopulations with distinct resource allocation strategies, remains largely unknown. Here, we introduce a single-cell strategy for quantifying the trade-offs between triacylglycerol production and growth in the oleaginous microorganism Yarrowia lipolytica. The strategy relies on high-throughput quantitative-phase imaging and, enabled by nanoscale secondary ion mass spectrometry analyses and dedicated image processing, allows us to image how resources are partitioned between growth and productivity. Enhanced precision over population-averaging biotechnologies and conventional microscopy demonstrates how cellular noise impacts growth and productivity differently. As such, subpopulations with distinct metabolic trade-offs emerge, with notable impacts on strain performance and robustness. By quantifying the self-degradation of cytosolic macromolecules under nutrient-limiting conditions, we discover the cell-to-cell heterogeneity in protein and fatty-acid recycling, unmasking a potential bet-hedging strategy under starvation.

Indexed as

CytosolImage Processing, Computer-AssistedLipid DropletsMicroscopyOptical ImagingSingle-Cell AnalysisSpectrometry, Mass, Secondary IonTriglyceridesYarrowiaTriglycerides

Identifiers

PMID30783105
PMCPMC6381102
OpenAlexW2915290179

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.