Evidence map›Paper›PMID 26693906›Full record

ArticlePLoS computational biology2015

Sources of Variability in a Synthetic Gene Oscillator.

Alan Veliz-Cuba, Andrew J Hirning, Adam A Atanas, Faiza Hussain, Flavia Vancia, Krešimir Josić, Matthew R Bennett

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Elements of biological oscillations in time and space.Nature structural & molecular biology · 2016
    Article
  11. 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

7 authors.

Alan Veliz-CubaDepartment of Biosciences, Rice University, Houston, Texas, United States of America.
Andrew J HirningDepartment of Biosciences, Rice University, Houston, Texas, United States of America.
Adam A AtanasDepartment of Biosciences, Rice University, Houston, Texas, United States of America.
Faiza HussainDepartment of Biosciences, Rice University, Houston, Texas, United States of America.
Flavia VanciaDepartment of Mathematics, University of Houston, Houston, Texas, United States of America.
Krešimir JosićDepartment of Mathematics, University of Houston, Houston, Texas, United States of America.
Matthew R BennettDepartment of Biosciences, Rice University, Houston, Texas, United States of America.

Funding

Experimental and mathematical analysis of delay in transcripitional signalingR01GM104974 · NIGMS · RICE UNIVERSITY · PI BENNETT, MATTHEW R. · 2012 to 2016
$1.4M
NIGMS NIH HHS R01 GM104974NIGMS NIH HHS R01GM104974
6 · The paper itself

Abstract

Synthetic gene oscillators are small, engineered genetic circuits that produce periodic variations in target protein expression. Like other gene circuits, synthetic gene oscillators are noisy and exhibit fluctuations in amplitude and period. Understanding the origins of such variability is key to building predictive models that can guide the rational design of synthetic circuits. Here, we developed a method for determining the impact of different sources of noise in genetic oscillators by measuring the variability in oscillation amplitude and correlations between sister cells. We first used a combination of microfluidic devices and time-lapse fluorescence microscopy to track oscillations in cell lineages across many generations. We found that oscillation amplitude exhibited high cell-to-cell variability, while sister cells remained strongly correlated for many minutes after cell division. To understand how such variability arises, we constructed a computational model that identified the impact of various noise sources across the lineage of an initial cell. When each source of noise was appropriately tuned the model reproduced the experimentally observed amplitude variability and correlations, and accurately predicted outcomes under novel experimental conditions. Our combination of computational modeling and time-lapse data analysis provides a general way to examine the sources of variability in dynamic gene circuits.

Indexed as

Models, GeneticBiological ClocksComputer SimulationGene Expression RegulationGene Regulatory NetworksGenes, SyntheticGenetic VariationHumansMaleOscillometry

Identifiers

PMID26693906
PMCPMC4692282

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.