Evidence map›Paper›PMID 37366955›Full record

ArticleBiosensors2023

MoBioS: Modular Platform Technology for High-Throughput Construction and Characterization of Tunable Transcriptional Biological Sensors.

Wouter Demeester, Jasmine De Baets, Dries Duchi, Marjan De Mey, Brecht De Paepe

Abstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
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  5. Review
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

5 authors.

Wouter DemeesterCentre for Synthetic Biology (CSB), Ghent University, 9000 Ghent, Belgium.ORCID 0000-0003-3528-6304
Jasmine De BaetsCentre for Synthetic Biology (CSB), Ghent University, 9000 Ghent, Belgium.ORCID 0000-0002-5409-7050
Dries DuchiCentre for Synthetic Biology (CSB), Ghent University, 9000 Ghent, Belgium.ORCID 0000-0002-7891-2400
Marjan De MeyCentre for Synthetic Biology (CSB), Ghent University, 9000 Ghent, Belgium.ORCID 0000-0002-8134-9436
Brecht De PaepeCentre for Synthetic Biology (CSB), Ghent University, 9000 Ghent, Belgium.ORCID 0000-0003-2858-3749

Funding

Industrial Research Fund IOF-ConcepTT F2019/IOF-CONCEPTT/264Research Foundation - Flanders 1246323NResearch Foundation - Flanders 1S29521NResearch Foundation - Flanders 1SC6820NSpecial Research Fund iBOF iBOF/21/092
6 · The paper itself

Abstract

All living organisms have evolved and fine-tuned specialized mechanisms to precisely monitor a vast array of different types of molecules. These natural mechanisms can be sourced by researchers to build Biological Sensors (BioS) by combining them with an easily measurable output, such as fluorescence. Because they are genetically encoded, BioS are cheap, fast, sustainable, portable, self-generating and highly sensitive and specific. Therefore, BioS hold the potential to become key enabling tools that stimulate innovation and scientific exploration in various disciplines. However, the main bottleneck in unlocking the full potential of BioS is the fact that there is no standardized, efficient and tunable platform available for the high-throughput construction and characterization of biosensors. Therefore, a modular, Golden Gate-based construction platform, called MoBioS, is introduced in this article. It allows for the fast and easy creation of transcription factor-based biosensor plasmids. As a proof of concept, its potential is demonstrated by creating eight different, functional and standardized biosensors that detect eight diverse molecules of industrial interest. In addition, the platform contains novel built-in features to facilitate fast and efficient biosensor engineering and response curve tuning.

Indexed as

Biosensing TechniquesTechnologyFluorescencehigh-throughput constructionplasmid construction platformprokaryotestranscriptional biosensors

Identifiers

PMID37366955
PMCPMC10296306

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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.