ArticlePLoS computational biology2020
Unravelling the γ-butyrolactone network in Streptomyces coelicolor by computational ensemble modelling.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
The trial behind it
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Unlocking the biosynthetic potential and taxonomy of the Antarctic microbiome along temporal and spatial gradients.Microbiology spectrum · 2024Article
- Comparative Proteomic Analysis of Transcriptional and Regulatory Proteins Abundances inInternational journal of molecular sciences · 2022Article
- A Regulator Based "Semi-Targeted" Approach to Activate Silent Biosynthetic Gene Clusters.International journal of molecular sciences · 2021Article
- Antifungal Activity and Biosynthetic Potential of NewInternational journal of molecular sciences · 2021Article
- Synthetic biology approaches to actinomycete strain improvement.FEMS microbiology letters · 2021Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Antibiotic production is coordinated in the Streptomyces coelicolor population through the use of diffusible signaling molecules of the γ-butyrolactone (GBL) family. The GBL regulatory system involves a small, and not completely defined two-gene network which governs a potentially bi-stable switch between the "on" and "off" states of antibiotic production. The use of this circuit as a tool for synthetic biology has been hampered by a lack of mechanistic understanding of its functionality. We here present the creation and analysis of a versatile and adaptable ensemble model of the Streptomyces GBL system (detailed information on all model mechanisms and parameters is documented in http://www.systemsbiology.ls.manchester.ac.uk/wiki/index.php/Main_Page). We use the model to explore a range of previously proposed mechanistic hypotheses, including transcriptional interference, antisense RNA interactions between the mRNAs of the two genes, and various alternative regulatory activities. Our results suggest that transcriptional interference alone is not sufficient to explain the system's behavior. Instead, antisense RNA interactions seem to be the system's driving force, combined with an aggressive scbR promoter. The computational model can be used to further challenge and refine our understanding of the system's activity and guide future experimentation.
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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.