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Development of an automated flow-based spectrophotometric immunoassay for continuous detection of zearalenone

Jantra, Jongjit LU ; Zór, Kinga LU ; Sanders, Melanie ; De Saeger, Sarah ; Hedström, Martin LU and Mattiasson, Bo LU (2020) In Biotechnology and Applied Biochemistry 67(3). p.375-382
Abstract

Considering the widespread contaminations of food products with mycotoxins, it is important to develop, robust, time- and cost-effective detection methods. We developed and optimized an immunoassay using a continuous flow system for the detection of zearalenone (ZEN). The assay was performed in a flow mode using an automated sequential injection system. Time for an assay cycle was 18 Min. Under optimal conditions, the limit for quantification for ZEN was 0.40 µg L−1 with a linear dependency between concentration and signal amplitude between 0.10 and 10 µg L−1. The assay proved to be robust and reliable with 13% relative standard deviation between measurements. By dissociating the antigen–antibody complex using a... (More)

Considering the widespread contaminations of food products with mycotoxins, it is important to develop, robust, time- and cost-effective detection methods. We developed and optimized an immunoassay using a continuous flow system for the detection of zearalenone (ZEN). The assay was performed in a flow mode using an automated sequential injection system. Time for an assay cycle was 18 Min. Under optimal conditions, the limit for quantification for ZEN was 0.40 µg L−1 with a linear dependency between concentration and signal amplitude between 0.10 and 10 µg L−1. The assay proved to be robust and reliable with 13% relative standard deviation between measurements. By dissociating the antigen–antibody complex using a regeneration solution, we showed 50 times reusability of the immobilized antibodies without affecting the antigen-binding properties.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
bioanalysis, flow-ELISA, immunoassay, mycotoxin, sequential injection, zearalenone
in
Biotechnology and Applied Biochemistry
volume
67
issue
3
pages
8 pages
publisher
Wiley
external identifiers
  • pmid:31876320
  • scopus:85077857817
ISSN
0885-4513
DOI
10.1002/bab.1876
language
English
LU publication?
yes
id
858c256b-e2a5-4014-94c1-3d4b7f18b6c1
date added to LUP
2021-01-14 15:26:02
date last changed
2024-06-13 05:12:38
@article{858c256b-e2a5-4014-94c1-3d4b7f18b6c1,
  abstract     = {{<p>Considering the widespread contaminations of food products with mycotoxins, it is important to develop, robust, time- and cost-effective detection methods. We developed and optimized an immunoassay using a continuous flow system for the detection of zearalenone (ZEN). The assay was performed in a flow mode using an automated sequential injection system. Time for an assay cycle was 18 Min. Under optimal conditions, the limit for quantification for ZEN was 0.40 µg L<sup>−1</sup> with a linear dependency between concentration and signal amplitude between 0.10 and 10 µg L<sup>−1</sup>. The assay proved to be robust and reliable with 13% relative standard deviation between measurements. By dissociating the antigen–antibody complex using a regeneration solution, we showed 50 times reusability of the immobilized antibodies without affecting the antigen-binding properties.</p>}},
  author       = {{Jantra, Jongjit and Zór, Kinga and Sanders, Melanie and De Saeger, Sarah and Hedström, Martin and Mattiasson, Bo}},
  issn         = {{0885-4513}},
  keywords     = {{bioanalysis; flow-ELISA; immunoassay; mycotoxin; sequential injection; zearalenone}},
  language     = {{eng}},
  month        = {{05}},
  number       = {{3}},
  pages        = {{375--382}},
  publisher    = {{Wiley}},
  series       = {{Biotechnology and Applied Biochemistry}},
  title        = {{Development of an automated flow-based spectrophotometric immunoassay for continuous detection of zearalenone}},
  url          = {{http://dx.doi.org/10.1002/bab.1876}},
  doi          = {{10.1002/bab.1876}},
  volume       = {{67}},
  year         = {{2020}},
}