Evidence map›Paper›PMID 30133447›Full record

ArticlePLoS computational biology2018

Lineage space and the propensity of bacterial cells to undergo growth transitions.

Arnab Bandyopadhyay, Huijing Wang, J Christian J Ray

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Epigenetic cellular memory inProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  2. Article
  3. 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

3 authors at 1 institution in 1 country.

Arnab BandyopadhyayCenter for Computational Biology, Department of Molecular Biosciences, University of Kansas, Lawrence, KS United States of America.
Huijing WangCenter for Computational Biology, Department of Molecular Biosciences, University of Kansas, Lawrence, KS United States of America.ORCID 0000-0001-7614-5714
J Christian J RayCenter for Computational Biology, Department of Molecular Biosciences, University of Kansas, Lawrence, KS United States of America.ORCID 0000-0001-7968-0851
University of Kansas · US

Funding

Mentoring CoreP20GM103418 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Douglas E Wright · 2012 to 2026
$63.0M
Understanding the mechanobiology of stem cells in a microengineered 3D cardiac tissue environment with cardiomyopathyP20GM103638 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI LUNTE, SUSAN M · 2012 to 2021
$22.1M
NIGMS NIH HHS P20 GM103418NIGMS NIH HHS P20 GM103638
6 · The paper itself

Abstract

The molecular makeup of the offspring of a dividing cell gradually becomes phenotypically decorrelated from the parent cell by noise and regulatory mechanisms that amplify phenotypic heterogeneity. Such regulatory mechanisms form networks that contain thresholds between phenotypes. Populations of cells can be poised near the threshold so that a subset of the population probabilistically undergoes the phenotypic transition. We sought to characterize the diversity of bacterial populations around a growth-modulating threshold via analysis of the effect of non-genetic inheritance, similar to conditions that create antibiotic-tolerant persister cells and other examples of bet hedging. Using simulations and experimental lineage data in Escherichia coli, we present evidence that regulation of growth amplifies the dependence of growth arrest on cellular lineage, causing clusters of related cells undergo growth arrest in certain conditions. Our simulations predict that lineage correlations and the sensitivity of growth to changes in toxin levels coincide in a critical regime. Below the critical regime, the sizes of related growth arrested clusters are distributed exponentially, while in the critical regime clusters sizes are more likely to become large. Furthermore, phenotypic diversity can be nearly as high as possible near the critical regime, but for most parameter values it falls far below the theoretical limit. We conclude that lineage information is indispensable for understanding regulation of cellular growth.

Indexed as

Anti-Bacterial AgentsBacteriaBacterial Physiological PhenomenaCell Growth ProcessesCell ProliferationComputer SimulationEscherichia coliEscherichia coli ProteinsGene Regulatory NetworksModels, GeneticPhenotypeAnti-Bacterial AgentsEscherichia coli Proteins

Identifiers

PMID30133447
PMCPMC6122811
OpenAlexW2949457894

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.