ReviewCurrent opinion in chemical biology2016
Biofuel metabolic engineering with biosensors.
Review in Current opinion in chemical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Recent advances in metabolic engineering of microorganisms for advancing lignocellulose-derived biofuels.Bioengineered · 2022Review
- Approaches to genetic tool development for rapid domestication of non-model microorganisms.Biotechnology for biofuels · 2021Review
- Intelligent microbial cell factory with genetic pH shooting (GPS) for cell self-responsive base/acid regulation.Microbial cell factories · 2020Article
- Congo Red Fluorescence for RapidApplied and environmental microbiology · 2019Article
- Towards the directed evolution of protein materials.MRS communications · 2019Article
- Dynamic control of endogenous metabolism with combinatorial logic circuits.Molecular systems biology · 2018Article
- Development of a Metabolite Sensor for High-Throughput Detection of Aldehydes inFrontiers in bioengineering and biotechnology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Metabolic engineering offers the potential to renewably produce important classes of chemicals, particularly biofuels, at an industrial scale. DNA synthesis and editing techniques can generate large pathway libraries, yet identifying the best variants is slow and cumbersome. Traditionally, analytical methods like chromatography and mass spectrometry have been used to evaluate pathway variants, but such techniques cannot be performed with high throughput. Biosensors - genetically encoded components that actuate a cellular output in response to a change in metabolite concentration - are therefore a promising tool for rapid and high-throughput evaluation of candidate pathway variants. Applying biosensors can also dynamically tune pathways in response to metabolic changes, improving balance and productivity. Here, we describe the major classes of biosensors and briefly highlight recent progress in applying them to biofuel-related metabolic pathway engineering.
Indexed as
Identifiers
What OpenQuestion holds
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.