Evidence map›Paper›PMID 31585026›Full record

ReviewChemphyschem : a European journal of chemical physics and physical chemistry2020

Synthetic Biology Enables Programmable Cell-Based Biosensors.

Maggie Hicks, Till T Bachmann, Baojun Wang

Abstract readReview
In one paragraph

Review in Chemphyschem : a European journal of chemical physics and physical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing 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

60 citing papers in PubMed.

  1. Review
  2. Article
  3. Programming Next-Generation Synthetic Biosensors by Genetic Circuit Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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  5. Article
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  19. Engineering signalling pathways in mammalian cells.Nature biomedical engineering · 2024
    Review
  20. A modular toolkit for environmentalApplied and environmental microbiology · 2024
    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

3 authors.

Maggie HicksSchool of Biological Sciences, University of Edinburgh, Edinburgh, UK.
Till T BachmannInfection Medicine, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh, UK.
Baojun WangSchool of Biological Sciences, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-4858-8937

Funding

Medical Research Council MR/S018875/1Wellcome TrustWellcome Trust 202078/Z/16/Z
6 · The paper itself

Abstract

Cell-based biosensors offer cheap, portable and simple methods of detecting molecules of interest but have yet to be truly adopted commercially. Issues with their performance and specificity initially slowed the development of cell-based biosensors. With the development of rational approaches to tune response curves, the performance of biosensors has rapidly improved and there are now many biosensors capable of sensing with the required performance. This has stimulated an increased interest in biosensors and their commercial potential. However the reliability, long term stability and biosecurity of these sensors are still barriers to commercial application and public acceptance. Research into overcoming these issues remains active. Here we present the state-of-the-art tools offered by synthetic biology to allow construction of cell-based biosensors with customisable performance to meet the real world requirements in terms of sensitivity and dynamic range and discuss the research progress to overcome the challenges in terms of the sensor stability and biosecurity fears.

Indexed as

Biosensing TechniquesCell EngineeringSynthetic BiologyBacteriaHumanscell-based biosensorgenetic circuitsrational approachesresponse curvesynthetic biology

Identifiers

PMID31585026
PMCPMC7004036

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.