Data · dataset · 2026
RNA Quality Control Enables Antibiotic Tolerance
Listed in Teesside University Research Data Repository
Antibiotic resistance poses a significant clinical challenge, yet the mechanisms underlying adaptation to antibiotic pressure within the complex host environment remain incompletely understood.
Description
By experimentally evolving Streptococcus pneumoniae in mice subjected to various antibiotics and immune states, we demonstrate that the high fitness costs of canonical resistance mutations severely restrict their emergence in vivo.
Instead, populations adopt distinct adaptive strategies depending on the specific selective context: while neutrophil-replete environments select for immune-evasive, loss-of-function mutations in the nicotinamidase SP_1583, general antibiotic stress drives convergent mutations in rny, encoding the RNA degradosome scaffold RNase Y. Isogenic rny mutants exhibit broad-spectrum tolerance and accelerated recovery. Single-cell transcriptomics reveals that antibiotic-induced death in wild-type bacteria is driven by transcriptional collapse, a lethal surge of uncontrolled transcription followed by a catastrophic loss of RNA quantity and integrity.
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In contrast, rny mutants avert this fate via a bet-hedging strategy: a resilient minority maintains a near baseline transcriptional profile, while a quiescent majority undergoes rapid, selective RNA degradation to preserve transcript fidelity. Upon stress removal, these populations execute a prioritized transcriptional ribosomal reboot, facilitating accelerated recovery. These findings identify RNA turnover as a tunable master regulator of stress tolerance that pathogens can exploit to survive the combined pressures of antibiotics and immunity.
Links
Where it is published
- DOI doi.org/10.17632/6j3ckhtp8x.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Medical biotechnology 69%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/6j3ckhtp8x.1 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:3206 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |