Evidence map›Paper›PMID 35522697›Full record

ArticlePLoS computational biology2022

Gene regulation by a protein translation factor at the single-cell level.

Roswitha Dolcemascolo, Lucas Goiriz, Roser Montagud-Martínez, Guillermo Rodrigo

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Analysis of MSX1, RYK, NFκB p65, and CCL4 Proteins andInternational journal of molecular sciences · 2025
    Article
  2. Article
  3. Quantitative mass spectrometry imaging: therapeutics & biomolecules.Chemical communications (Cambridge, England) · 2024
    Review
  4. Article
  5. 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 at 1 institution in 1 country.

Roswitha DolcemascoloInstitute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Paterna, Spain.ORCID 0000-0003-2851-7194
Lucas GoirizInstitute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Paterna, Spain.ORCID 0000-0001-7182-5008
Roser Montagud-MartínezInstitute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Paterna, Spain.ORCID 0000-0003-4487-1599
Guillermo RodrigoInstitute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Paterna, Spain.ORCID 0000-0002-1871-9617
Universitat de València · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression is inherently stochastic and pervasively regulated. While substantial work combining theory and experiments has been carried out to study how noise propagates through transcriptional regulations, the stochastic behavior of genes regulated at the level of translation is poorly understood. Here, we engineered a synthetic genetic system in which a target gene is down-regulated by a protein translation factor, which in turn is regulated transcriptionally. By monitoring both the expression of the regulator and the regulated gene at the single-cell level, we quantified the stochasticity of the system. We found that with a protein translation factor a tight repression can be achieved in single cells, noise propagation from gene to gene is buffered, and the regulated gene is sensitive in a nonlinear way to global perturbations in translation. A suitable mathematical model was instrumental to predict the transfer functions of the system. We also showed that a Gamma distribution parameterized with mesoscopic parameters, such as the mean expression and coefficient of variation, provides a deep analytical explanation about the system, displaying enough versatility to capture the cell-to-cell variability in genes regulated both transcriptionally and translationally. Overall, these results contribute to enlarge our understanding on stochastic gene expression, at the same time they provide design principles for synthetic biology.

Indexed as

Gene Expression RegulationProtein BiosynthesisModels, GeneticStochastic ProcessesSynthetic Biology

Identifiers

PMID35522697
PMCPMC9116677
OpenAlexW4229003071

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.