Detection of peanut using real-time polymerase chain reaction

Hird, Heather; Lloyd, Julie C.; Goodier, R.; Brown, J. Steven; Reece, Paul

doi:10.1007/s00217-003-0726-z

Cited by 104 publications

(38 citation statements)

References 3 publications

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“…Using real-time PCR, the dynamic range of quantization is deWned as the range in which a linear relationship between three additional cycles and ten fold lessening of template quantity exists, in a 100% of eYciency assay (Hird et al, 2003). In order to detect this dynamic range, diVerent dilutions of genomic DNA were employed (from 1:10 to 1:2000 fold); the lower limit of quantiWcation was showed in the range 1:1000-1:2000 fold (corresponding to 98-49 pg/ l).…”

Section: Sensitivity and Dynamic Rangementioning

confidence: 99%

“…We suggest to better investigate this point, strictly related to the optimization of extraction step. The diYculty to optimize the recovery during the extraction has been recently underlined by Hird et al (2003) regarding the optimization of a Taqman assay focused on the peanut detection. As suggested in this recent work, one possible approach to increase the sensitivity and the DNA recovery could be to increase the sample size used for the DNA extraction.…”

Section: Sensitivity and Dynamic Rangementioning

confidence: 99%

“…The use of real-time PCR technique, largely used for the detection and quantiWcation of genetically modiWed organisms (GMOs, Pardigol, Guillet, & Popping, 2003;Ronning, Vaitilingom, Berdal, & Holst-Jensen, 2003) and recently suggested for the peanut detection in foods (Hird, Lloyd, Goodier, Brown, & Reece, 2003), allows rapid and sensitive detection of a speciWc genomic DNA sequence in foods (Klein, 2002;Levin, 2004). The simple chemistry of a realtime assay is based on the use of two Xuorescent dyes: a reporter (R) and a quencher (Q), attached to the 5Ј and 3Ј ends, respectively, of a Taqman speciWc probe (Applied Biosystem).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Detection of hazelnut (Corylus spp.) in processed foods using real-time PCR

et al. 2007

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Section: Sensitivity and Dynamic Rangementioning

confidence: 99%

Section: Sensitivity and Dynamic Rangementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Detection of hazelnut (Corylus spp.) in processed foods using real-time PCR

et al. 2007

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“…The extraction procedure for the second kit, in column format, was modified and resulted in more efficient extraction of DNA from complex food samples, including dumplings, a chocolate snack, a vegetable bouillon cube, and cherry jam. Hird et al (2003) also evaluated the use of a commercial DNA extraction kits based on different technological strategies to extract DNA from diverse matrices, including nuts, meat tissue, fish tissue, dry seeds, and plant tissue. Arlorio et al (2007) evaluated the ability of different commercial extraction kits to extract high-quality hazelnut DNA in relation to traditional phenolchloroform extraction.…”

Section: Recovery Of Dna From Food Matrices and Dna Qualitymentioning

confidence: 99%

Detection of Food Allergens

Diaz‐Amigo

Pöpping

2009

Molecular Biological and Immunological Techniques and Applications for Food Chemists

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“…Therefore, DNA-detection technology has been developed as an alternative for these purposes. Different methods based on real-time Polymerase Chain Reaction have been described for peanut DNA detection (Hird et al, 2003, Watanabe et al, 2006Lopez-Calleja et al, 2012). However, most of them are time-consuming and require expensive equipment.…”

Section: Introductionmentioning

confidence: 99%

Development of a genosensor for peanut allergen ARA h 2 detection and its optimization by surface response methodology

López

Cabanillas

Castañón

et al. 2014

Biosensors and Bioelectronics

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. bealopru@ucm.es AbstractA new selective electrochemical genosensor has been developed for the detection of an 86-mer DNA peanut sequence encoding part of the allergen Ara h 2 (conglutinhomologue protein). The method is based on a sandwich format, which presents two advantages: it permits shortening the capture probe and avoids labeling of the target.Screen-printed gold electrodes have been used as platform for the immobilization of oligonucleotides by the well-known S-Au bond. Mixed self-assembled monolayers (SAM), including thiol-modified capture probe and mercaptohexanol, were prepared to achieve an organized, homogeneous and not too compact SAM in which unspecific adsorption of the capture probe would be prevented. The optimization of the sensing phase was carried out using the Design of Experiments (DoE) approach.Traditionally, response optimization is achieved by changing the value of one factor at a time until there is no further improvement. However, DoE involves regulating the important factors so that the result becomes optimal. Optimized conditions were found to be 1.34 µM for capture probe concentration and 3.15 mM for 2 mercaptohexanol (spacer) concentration. When the optimal conditions were employed the analytical performance of the proposed genosensor improved significantly, showing a sensitivity as high as 3 µA/nM, with a linear range from 5 10 -11 to 5 10 -8 M and a detection limit of 10 pM.

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Detection of peanut using real-time polymerase chain reaction

Cited by 104 publications

References 3 publications

Detection of hazelnut (Corylus spp.) in processed foods using real-time PCR

Detection of hazelnut (Corylus spp.) in processed foods using real-time PCR

Detection of Food Allergens

Development of a genosensor for peanut allergen ARA h 2 detection and its optimization by surface response methodology

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