Excel · study · 2026
Host infection selects for sRNA variants that drive bacterial social cheating
Listed in NCBI GEO
Single-nucleotide mutations in regulatory small RNAs (sRNAs) represent a largely unexplored route to social cheating during bacterial infection.
Description
Here we show that arcZ, encoding a conserved Hfq-dependent sRNA in the plant pathogen Dickeya solani, undergoes recurrent single-nucleotide mutations during potato tuber infection. Five distinct arcZ alleles define a graded series of ArcZ functional impairment in which antifungal and protease activities are progressively reduced while virulence is compromised only in a subset of alleles.
All five variants gain a fitness advantage exclusively during co-infection with wild-type arcZ1 cells, an advantage that is strongest when variants are rare, declines as cheater frequency increases, and correlates with declining total bacterial productivity, the canonical signature of social cheating and a tragedy of the commons.[kp1.1] No fitness benefit is detected in vitro. Transcriptomic profiling of five arcZ variants identifies a conserved core of 132 downregulated genes enriched in secreted and diffusible functions.
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Systematic genetic dissection, supported by quantitative proteomics, establishes BudAB-dependent acetoin production as the dominant cooperative public good exploited during co-infection. Wild-type arcZ1 cells divert pyruvate flux toward acetoin via the BudAB pathway, maintaining a less acidic tissue environment that sustains disease progression; arcZ variants, which repress this pathway, exploit the resulting pH buffering without contributing to it.
These results establish pleiotropic regulatory sRNAs as a previously unrecognized class of mutational targets for the emergence of social cheaters during host infection.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE334nnn/GSE334754 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE334754 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1476278 ncbi.nlm.nih.gov/bioproject/PRJNA1476278 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing
- From keywords
- Life Sciences
- Inferred from text
- Agricultural biotechnology 69% · Disease 75% · Mass spectrometry 65%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE334754 | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:3001 | enrichment · NCBI GEO | taxonomy-embedding@1.1.0 | title+keywords+description (69%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:mass-spectrometry | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |