Evidence map›Paper›PMID 39669429›Full record

ArticleiScience2024

Intrinsically robust and scalable biofilm segmentation under diverse physical growth conditions.

Jian-Geng Chiou, Todd Kwang-Tao Chou, Jordi Garcia-Ojalvo, Gürol M Süel

Abstract read
In one paragraph

Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Jian-Geng ChiouDepartment of Molecular Biology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92093 USA.
Todd Kwang-Tao ChouDepartment of Molecular Biology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92093 USA.
Jordi Garcia-OjalvoDepartment of Medicine and Life Sciences, Universitat Pompeu Fabra, 08003 Barcelona, Spain.
Gürol M SüelDepartment of Molecular Biology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92093 USA.

Funding

Charge matters: Pursuing the most common, and least understood molecular interactions in cellsR35GM139645 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUEL, GUROL MEHMET · 2021 to 2025
$2.8M
Training Program in Quantitative Integrative BiologyT32GM127235 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HWA, TERENCE · 2018 to 2022
$1.3M
NIGMS NIH HHS R35 GM139645NIGMS NIH HHS T32 GM127235
6 · The paper itself

Abstract

Developmental patterning is a shared feature across biological systems ranging from vertebrates to bacterial biofilms. While vertebrate patterning benefits from well-controlled homeostatic environments, bacterial biofilms can grow in diverse physical contexts. What mechanisms provide developmental robustness under diverse environments remains an open question. We show that a native clock-and-wavefront mechanism robustly segments biofilms in both solid-air and solid-liquid interfaces. Biofilms grown under these distinct physical conditions differ 4-fold in size yet exhibit robust segmentation. The segmentation pattern scaled with biofilm growth rate in a mathematically predictable manner independent of habitat conditions. We show that scaling arises from the coupling between wavefront speed and biofilm growth rate. In contrast to the complexity of scaling mechanisms in vertebrates, our data suggests that the minimal bacterial clock-and-wavefront mechanism is intrinsically robust and scales in real time. Consequently, bacterial biofilms robustly segment under diverse conditions without requiring cell-to-cell signaling to track system size.

Indexed as

Biological sciencesMicrobiologyNatural sciences

Identifiers

PMID39669429
PMCPMC11635021

What OpenQuestion holds

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Registered trials

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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.