Omics · study · 2026
Regulatory Time-Kill Sequencing Maps Antibiotic-Specific Transcriptional Control of Escherichia coli Persistence at Genome Scale
Listed in NCBI GEO
Bacterial persistence enables a phenotypically tolerant subpopulation to survive lethal antibiotic exposure, contributing to the recalcitrance of chronic infections and facilitating the evolution of heritable resistance.
Description
Despite its importance, a systems-level, quantitative understanding of how transcriptional regulation shapes persistence kinetics has remained limited, largely because conventional time-kill assays are inherently low-throughput.
Here, we develop Regulatory Time-Kill Sequencing (RTK-seq), a high-throughput functional genomics strategy that combines a pooled CRISPR interference (CRISPRi) library targeting transcription factors with time-resolved antibiotic selection and deep barcode sequencing. RTK-seq simultaneously resolves multiphasic killing trajectories for 174 Escherichia coli transcriptional regulators over five orders of magnitude in survival.
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The resulting profiles recapture known persistence pathways and identify previously unrecognized regulators, including rcsA, narP, and csgD, that modulate distinct phases of antibiotic killing. Additionally, applying RTK-seq across multiple antibiotic classes reveals a highly condition-dependent regulatory landscape, demonstrating that persistence is governed not by a single universal program but by drug-specific metabolic and stress responses.
Overall, RTK-seq offers a scalable, versatile strategy for quantitatively mapping microbial survival networks and identifies targets for anti-persister therapies.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE347nnn/GSE347678 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE347678 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1530949 ncbi.nlm.nih.gov/bioproject/PRJNA1530949 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing
- From keywords
- Life Sciences
- Inferred from text
- Sequencing 75%
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE347678 | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| 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:sequencing | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| 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 |