Evidence map›Paper›PMID 40980877›Full record

ArticlemBio2025

A delivered DNase toxin creates population heterogeneity through transient intoxication of siblings.

Hanna Eriksson, Susan Schlegel, Sanna Koskiniemi

Abstract read
In one paragraph

Article in mBio, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hanna ErikssonDepartment of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.ORCID 0009-0001-8140-508X
Susan SchlegelDepartment of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
Sanna KoskiniemiDepartment of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-3275-0936

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population heterogeneity is important for multicellular behavior, as well as bet-hedging strategies. Recent findings suggest a role for bacterial toxin delivery in generating population heterogeneity, but the molecular mechanisms by which this occurs are not well understood. Here, we address IMPORTANCE: Population heterogeneity is important for multicellularity, as well as for bet-hedging strategies. A heterogeneous population allows cells with the same genotype to respond differently to environmental cues and stresses. For multicellularity, heterogeneity originates from coordinated signaling, whereas bet-hedging strategies can arise stochastically due to cell-to-cell variation in the concentration of signaling molecules. However, recent advances suggest a role for bacterial toxin delivery in the generation of population heterogeneity. How toxins mediate heterogeneity mechanistically is, however, unclear. Here, we show that kin cells transiently intoxicate each other with CdiA toxins, resulting in physiological changes. These changes are specific to the toxic activity, i.e., other toxins with different activities are likely to give rise to other responses. Thus, we find that the arsenal of toxins that bacteria harbor could affect their ability to participate in bet-hedging strategies, as well as in multicellular behavior.

Indexed as

Bacterial ToxinsDeoxyribonucleasesEscherichia coliEscherichia coli ProteinsMembrane ProteinsGene Expression Regulation, BacterialSOS Response, GeneticsBacterial ToxinsCdiA protein, E coliDeoxyribonucleasesEscherichia coli ProteinsMembrane Proteinsbacteriabet-hedgingcontact-dependent growth inhibitionmulticellularitypopulation heterogeneitySOS-responsetoxin delivery

Identifiers

PMID40980877
PMCPMC12607911

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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.