ArticleMicrobial biotechnology2008
Internal arsenite bioassay calibration using multiple bioreporter cell lines.
Article in Microbial biotechnology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 46 citations in OpenAlex.
- A Novel Whole-Cell Biosensor for Bioavailable Antimonite in Water and Sediments.Applied and environmental microbiology · 2023Article
- Duckweed: a potential phytosensor for heavy metals.Plant cell reports · 2022Review
- Highly Sensitive Whole-Cell Biosensor for Cadmium Detection Based on a Negative Feedback Circuit.Frontiers in bioengineering and biotechnology · 2021Article
- Sensitive and Specific Whole-Cell Biosensor for Arsenic Detection.Applied and environmental microbiology · 2019Article
- Cascaded amplifying circuits enable ultrasensitive cellular sensors for toxic metals.Nature chemical biology · 2019Article
- Miniaturized Sample Preparation and Rapid Detection of Arsenite in Contaminated Soil Using a Smartphone.Sensors (Basel, Switzerland) · 2018Article
- Design and evaluation of an incoherent feed-forward loop for an arsenic biosensor based on standard iGEM parts.Synthetic biology (Oxford, England) · 2017Article
- Indispensable or toxic? The phosphate versus arsenate debate.Microbial biotechnology · 2013Article
- Where microbiology meets microengineering: design and applications of reporter bacteria.Nature reviews. Microbiology · 2010Review
- Strategies for enhancing bioluminescent bacterial sensor performance by promoter region manipulation.Microbial biotechnology · 2010Article
- Environmental Microbiology meets Microbial Biotechnology.Microbial biotechnology · 2008Article
- Limits in energy generation and biotechnology of primary and secondary products.Microbial biotechnology · 2008Article
- Energy, heat, flavours and aromas of Microbial Biotechnology.Microbial biotechnology · 2008Article
- Strategies for enhancing bioluminescent bacterial sensor performance by promoter region manipulation.Bioengineered bugsArticle
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bioassays with bioreporter bacteria are usually calibrated with analyte solutions of known concentrations that are analysed along with the samples of interest. This is done as bioreporter output (the intensity of light, fluorescence or colour) does not only depend on the target concentration, but also on the incubation time and physiological activity of the cells in the assay. Comparing the bioreporter output with standardized colour tables in the field seems rather difficult and error-prone. A new approach to control assay variations and improve application ease could be an internal calibration based on the use of multiple bioreporter cell lines with drastically different reporter protein outputs at a given analyte concentration. To test this concept, different Escherichia coli-based bioreporter strains expressing either cytochrome c peroxidase (CCP, or CCP mutants) or β-galactosidase upon induction with arsenite were constructed. The reporter strains differed either in the catalytic activity of the reporter protein (for CCP) or in the rates of reporter protein synthesis (for β-galactosidase), which, indeed, resulted in output signals with different intensities at the same arsenite concentration. Hence, it was possible to use combinations of these cell lines to define arsenite concentration ranges at which none, one or more cell lines gave qualitative (yes/no) visible signals that were relatively independent of incubation time or bioreporter activity. The discriminated concentration ranges would fit very well with the current permissive (e.g. World Health Organization) levels of arsenite in drinking water (10 µg l(-1)).
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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.