Evidence map›Paper›PMID 21946159›Full record

ReviewMetabolic engineering2012

Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways.

Joshua K Michener, Kate Thodey, Joe C Liang, Christina D Smolke

Abstract readReview
In one paragraph

Review in Metabolic engineering, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
5.2field-weighted citation impact, top 3% of its field
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

51 citing papers in PubMed, 146 citations in OpenAlex.

  1. Review
  2. Advancing lignocellulosic conversion though biosensor-enabled metabolic engineering.Green chemistry : an international journal and green chemistry resource : GC · 2025
    Review
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  14. Tools and systems for evolutionary engineering of biomolecules and microorganisms.Journal of industrial microbiology & biotechnology · 2019
    Review
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  16. Review
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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

4 authors at 2 institutions in 1 country.

Joshua K MichenerDepartment of Bioengineering, California Institute of Technology, Pasadena, CA 91125, USA.
Kate Thodey
Joe C Liang
Christina D Smolke
California Institute of Technology · USStanford University · US

Funding

Frameworks for programming ligand-responsive RNA regulatory systemsR01GM086663 · NIGMS · STANFORD UNIVERSITY · PI ENDY, DREW · 2009 to 2024
$3.7M
Molecular sensors for real-time metabolite detection and dynamic network controlR01GM077347 · NIGMS · STANFORD UNIVERSITY · PI SMOLKE, CHRISTINA D · 2006 to 2008
$381k
NIGMS NIH HHS R01 GM077347NIGMS NIH HHS R01 GM086663
6 · The paper itself

Abstract

Cells are filled with biosensors, molecular systems that measure the state of the cell and respond by regulating host processes. In much the same way that an engineer would monitor a chemical reactor, the cell uses these sensors to monitor changing intracellular environments and produce consistent behavior despite the variable environment. While natural systems derive a clear benefit from pathway regulation, past research efforts in engineering cellular metabolism have focused on introducing new pathways and removing existing pathway regulation. Synthetic biology is a rapidly growing field that focuses on the development of new tools that support the design, construction, and optimization of biological systems. Recent advances have been made in the design of genetically-encoded biosensors and the application of this class of molecular tools for optimizing and regulating heterologous pathways. Biosensors to cellular metabolites can be taken directly from natural systems, engineered from natural sensors, or constructed entirely in vitro. When linked to reporters, such as antibiotic resistance markers, these metabolite sensors can be used to report on pathway productivity, allowing high-throughput screening for pathway optimization. Future directions will focus on the application of biosensors to introduce feedback control into metabolic pathways, providing dynamic control strategies to increase the efficient use of cellular resources and pathway reliability.

Indexed as

Biosensing TechniquesGenes, ReporterGenetic MarkersMetabolic EngineeringOrganisms, Genetically ModifiedSynthetic BiologyGenetic Markers

Identifiers

PMID21946159
PMCPMC3256257
OpenAlexW2078272501

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.