Evidence map›Paper›PMID 41444230›Full record

ArticleNature communications2025

A stationary phase-specific bacterial green light sensor for enhancing metabolite production.

John T Lazar, Daniel J Haller, Abbas Ghaddar, Jae J Kim, Kevin Yang, Sebastián M Castillo-Hair, Andrew R Gilmour, Ross Thyer, Jeffrey J Tabor

Abstract read
In one paragraph

Article in Nature communications, 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. 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

9 authors.

John T LazarDepartment of Chemical and Biomolecular Engineering, Rice University, Houston, TX, USA.
Daniel J HallerPh.D. Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, USA.ORCID http://orcid.org/0000-0003-3057-5078
Abbas GhaddarDepartment of Bioengineering, Rice University, Houston, TX, USA.
Jae J KimDepartment of Bioengineering, Rice University, Houston, TX, USA.
Kevin YangDepartment of Bioengineering, Rice University, Houston, TX, USA.
Sebastián M Castillo-HairDepartment of Bioengineering, Rice University, Houston, TX, USA.ORCID http://orcid.org/0000-0002-2384-3129
Andrew R GilmourPh.D. Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, USA.
Ross ThyerDepartment of Chemical and Biomolecular Engineering, Rice University, Houston, TX, USA.ORCID http://orcid.org/0000-0002-0356-5790
Jeffrey J TaborDepartment of Chemical and Biomolecular Engineering, Rice University, Houston, TX, USA. jeff.tabor@rice.edu.ORCID http://orcid.org/0000-0001-7316-0361

Funding

National Science Foundation (NSF) CAREER 1553317National Science Foundation (NSF) MCB 2204402
6 · The paper itself

Abstract

Genetically-encoded sensors are used to control protein and metabolite production in bacterial fermentations. However, these sensors are generally optimized for exponential growth rather than stationary phase where production occurs. Here, we find that our previously engineered E. coli green light sensor CcaSR, which functions robustly in exponential phase, fails in stationary phase due to spontaneous loss of an engineered chromophore biosynthetic pathway and accumulation of CcaS and CcaR. We optimize the genetic context and expression determinants of each component, resulting in a stable system named CcaSR

Indexed as

Escherichia coliLightBioreactorsCoumaric AcidsEscherichia coli ProteinsFermentationGene Expression Regulation, BacterialGreen LightMetabolic EngineeringPropionatesCoumaric AcidsEscherichia coli Proteinsp-coumaric acidPropionates

Identifiers

PMID41444230
PMCPMC12852798

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.