Evidence map›Paper›PMID 24608180›Full record

ArticleNature methods2014

Dynamic characterization of growth and gene expression using high-throughput automated flow cytometry.

Ignacio A Zuleta, Andrés Aranda-Díaz, Hao Li, Hana El-Samad

Abstract read
In one paragraph

Article in Nature methods, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Review
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  19. Delayed Ras/PKA signaling augments the unfolded protein response.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  20. The author file: Hana El-Samad.Nature methods · 2014
    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

4 authors.

Ignacio A Zuleta1] Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA. [2] The California Institute for Quantitative Biosciences, San Francisco, California, USA.
Andrés Aranda-Díaz1] Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA. [2] The California Institute for Quantitative Biosciences, San Francisco, California, USA.
Hao Li1] Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA. [2] The California Institute for Quantitative Biosciences, San Francisco, California, USA.
Hana El-Samad1] Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA. [2] The California Institute for Quantitative Biosciences, San Francisco, California, USA.

Funding

Rewiring Therapeutic Cells: User-Controlled T Cells and Stem CellsP50GM081879 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIM, WENDELL A · 2010 to 2017
$19.0M
Structure function and evolution of yeast transcription networksR01GM070808 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LI, HAO · 2004 to 2012
$2.3M
NIGMS NIH HHS P50 GM081879NIGMS NIH HHS R01 GM070808NIGMS NIH HHS R01-GM070808
6 · The paper itself

Abstract

Cells adjust to changes in environmental conditions using complex regulatory programs. These cellular programs are the result of an intricate interplay between gene expression, cellular growth and protein degradation. Technologies that enable simultaneous and time-resolved measurements of these variables are necessary to dissect cellular homeostatic strategies. Here we report the development of an automated flow cytometry robotic setup that enables real-time measurement of precise and simultaneous relative growth and protein synthesis rates of multiplexed microbial populations across many conditions. These measurements generate quantitative profiles of dynamically evolving protein synthesis and degradation rates. We demonstrate this setup in the context of gene regulation of the unfolded protein response (UPR) of Saccharomyces cerevisiae and uncover a dynamic and complex landscape of gene expression, growth dynamics and proteolysis following perturbations.

Indexed as

AutomationFlow CytometryFungal ProteinsGene Expression Regulation, FungalSaccharomyces cerevisiaeFungal Proteins

Identifiers

PMID24608180
PMCPMC4016179

What OpenQuestion holds

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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 OpenQuestion graph.