Evidence map›Paper›PMID 40835634›Full record

ArticleScientific reports2025

Genetic and environmental determinants of streaming and aggregation in Myxococcus xanthus.

Trosporsha T Khan, Patrick Murphy, Jiangguo Zhang, Oleg A Igoshin, Roy D Welch

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. Deep learning framework for quantifying self-organization inProceedings of the National Academy of Sciences of the United States of America · 2026
    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

5 authors.

Trosporsha T KhanDepartment of Biology, Syracuse University, Syracuse, NY, USA.
Patrick MurphyDepartment of Bioengineering, Rice University, Houston, TX, USA.
Jiangguo ZhangDepartment of Bioengineering, Rice University, Houston, TX, USA.
Oleg A IgoshinDepartment of Bioengineering, Rice University, Houston, TX, USA.
Roy D WelchDepartment of Biology, Syracuse University, Syracuse, NY, USA. rowelch@syr.edu.

Funding

National Science Foundation DMS-1903275
6 · The paper itself

Abstract

Under starvation conditions, a spot of a few million Myxococcus xanthus cells on agar will migrate inward to form aggregates that mature into dome-shaped fruiting bodies. This migration is thought to occur within structures called 'streams,' which are considered crucial for initiating aggregation. The prevailing traffic jam model hypothesizes that intersections of streams cause cell crowding and 'jamming,' thereby initiating the process of aggregate formation. However, this hypothesis has not been rigorously tested, in part due to the lack of a standardized, quantifiable definition of streams. To address this gap, we captured time-lapse movies and conducted fluorescent cell tracking experiments using wild-type and two motility-deficient mutant M. xanthus strains. By quantitatively defining streams and developing a novel stream detection mask, we show that streams are not essential for nascent aggregate formation, though they may accelerate the process. Moreover, our results indicate that streaming has a genetic component: disrupting only one of the two M. xanthus motility systems hinders stream formation. Together, these findings challenge the idea that stream intersections are required to drive aggregate formation and suggest that M. xanthus aggregation may be driven by mechanisms independent of streaming, highlighting the need for alternative models to fully explain aggregation dynamics.

Indexed as

Myxococcus xanthusMutationTime-Lapse ImagingAggregateBiofilmMyxococcus xanthusStreamTraffic jam model

Identifiers

PMID40835634
PMCPMC12368150

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.