ArticleNature biotechnology2014
Tunable protein degradation in bacteria.
Article in Nature biotechnology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers.
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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.
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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.
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Who cites it
120 citing papers in PubMed, 276 citations in OpenAlex.
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60 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Tunable control of protein degradation in bacteria would provide a powerful research tool. Here we use components of the Mesoplasma florum transfer-messenger RNA system to create a synthetic degradation system that provides both independent control of steady-state protein level and inducible degradation of targeted proteins in Escherichia coli. We demonstrate application of this system in synthetic circuit development and control of core bacterial processes and antibacterial targets, and we transfer the system to Lactococcus lactis to establish its broad functionality in bacteria. We create a 238-member library of tagged essential proteins in E. coli that can serve as both a research tool to study essential gene function and an applied system for antibiotic discovery. Our synthetic protein degradation system is modular, does not require disruption of host systems and can be transferred to diverse bacteria with minimal modification.
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Registered trials
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.