Evidence map›Paper›PMID 30911179›Full record

ArticleNature chemical biology2019

Cascaded amplifying circuits enable ultrasensitive cellular sensors for toxic metals.

Xinyi Wan, Francesca Volpetti, Ekaterina Petrova, Chris French, Sebastian J Maerkl, Baojun Wang

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Nature chemical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers.

0numbers the graph read from it
0cells of the map it votes in
105citing papers in PubMed
13.1field-weighted citation impact, top 1% 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

105 citing papers in PubMed, 282 citations in OpenAlex.

  1. Review
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  10. Programming Next-Generation Synthetic Biosensors by Genetic Circuit Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  11. Bacteria as living biosensors for DNA.Nature reviews bioengineering · 2026
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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45 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 2 countries.

Xinyi WanSchool of Biological Sciences, University of Edinburgh, Edinburgh, UK.
Francesca VolpettiInstitute of Bioengineering, School of Engineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
Ekaterina PetrovaInstitute of Bioengineering, School of Engineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
Chris FrenchSchool of Biological Sciences, University of Edinburgh, Edinburgh, UK.
Sebastian J MaerklInstitute of Bioengineering, School of Engineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.ORCID http://orcid.org/0000-0003-1917-5268
Baojun WangSchool of Biological Sciences, University of Edinburgh, Edinburgh, UK. baojun.wang@ed.ac.uk.ORCID http://orcid.org/0000-0002-4858-8937
École Polytechnique Fédérale de Lausanne · CHUniversity of Edinburgh · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-based biosensors have great potential to detect various toxic and pathogenic contaminants in aqueous environments. However, frequently they cannot meet practical requirements due to insufficient sensing performance. To address this issue, we investigated a modular, cascaded signal amplifying methodology. We first tuned intracellular sensory receptor densities to increase sensitivity, and then engineered multi-layered transcriptional amplifiers to sequentially boost output expression level. We demonstrated these strategies by engineering ultrasensitive bacterial sensors for arsenic and mercury, and improved detection limit and output up to 5,000-fold and 750-fold, respectively. Coupled by leakage regulation approaches, we developed an encapsulated microbial sensor cell array for low-cost, portable and precise field monitoring, where the analyte can be readily quantified via displaying an easy-to-interpret volume bar-like pattern. The ultrasensitive signal amplifying methodology along with the background regulation and the sensing platform will be widely applicable to many other cell-based sensors, paving the way for their real-world applications.

Indexed as

Biosensing TechniquesCell PhoneMicrofluidic Analytical TechniquesArsenicHumansMetals, HeavyArsenicMetals, Heavy

Identifiers

PMID30911179
OpenAlexW2925106348

What OpenQuestion holds

Textmetadata
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.