A novel biomarker for detection of Listeria species in food processing factory. (March 2017)
- Record Type:
- Journal Article
- Title:
- A novel biomarker for detection of Listeria species in food processing factory. (March 2017)
- Main Title:
- A novel biomarker for detection of Listeria species in food processing factory
- Authors:
- Phraephaisarn, Chirapiphat
Khumthong, Rabuesak
Takahashi, Hajime
Ohshima, Chihiro
Kodama, Kanako
Techaruvichit, Punnida
Vesaratchavest, Mongkol
Taharnklaew, Rutjawate
Keeratipibul, Suwimon - Abstract:
- Abstract: A biomarker-based PCR amplification method has been proved to be an effective tool for rapid and accurate detection of Listeria contamination in food factories. However, the current biomarkers (such as iap, hly genes) used for the detection of Listeria have a problem of detection efficiency for some Listeria species, including 7 recently recognized species. Therefore, in this study, a new comprehensive biomarker was developed for the effective detection of all Listeria species. The study employed a novel in-silico scheme to explore and characterize the alternative biomarkers. Biomarker BE-LisAll was identified against 34 Listeria and over 2700 other bacterial complete genomes by in-silico scheme. Specificity of biomarker BE-LisAll was then evaluated with 17 different Listeria species and 58 non- Listeria bacteria isolates. The result showed 100% specificity to Listeria species, and the biomarker could differentiate Listeria species from a variety of non- Listeria bacteria. Finally, the PCR amplification with BE-LisAll was compared with the conventional culture method for detection of Listeria spp. using 60 swab samples collected from a food-processing factory to verify the biomarker's applicability. The result demonstrated 100% correspondence to the results of the conventional culture method. The BE-LisAll biomarker-based PCR amplification is presented for rapid and comprehensive detection of all Listeria species with a high degree of accuracy and sensitivity. ItAbstract: A biomarker-based PCR amplification method has been proved to be an effective tool for rapid and accurate detection of Listeria contamination in food factories. However, the current biomarkers (such as iap, hly genes) used for the detection of Listeria have a problem of detection efficiency for some Listeria species, including 7 recently recognized species. Therefore, in this study, a new comprehensive biomarker was developed for the effective detection of all Listeria species. The study employed a novel in-silico scheme to explore and characterize the alternative biomarkers. Biomarker BE-LisAll was identified against 34 Listeria and over 2700 other bacterial complete genomes by in-silico scheme. Specificity of biomarker BE-LisAll was then evaluated with 17 different Listeria species and 58 non- Listeria bacteria isolates. The result showed 100% specificity to Listeria species, and the biomarker could differentiate Listeria species from a variety of non- Listeria bacteria. Finally, the PCR amplification with BE-LisAll was compared with the conventional culture method for detection of Listeria spp. using 60 swab samples collected from a food-processing factory to verify the biomarker's applicability. The result demonstrated 100% correspondence to the results of the conventional culture method. The BE-LisAll biomarker-based PCR amplification is presented for rapid and comprehensive detection of all Listeria species with a high degree of accuracy and sensitivity. It is hoped that commercial food processing industries are able to employ this developed biomarker as a Listeria -detection tool in their factories to prevent or reduce economic losses due to Listeria contamination. Highlights: The in-silico scheme is a very useful tool for rapid exploration of new biomarker. The in-silico developed biomarker was specific to all 17 Listeria species. Result accuracy was 100% corresponding to results of conventional culture methods. … (more)
- Is Part Of:
- Food control. Volume 73:Part B(2017)
- Journal:
- Food control
- Issue:
- Volume 73:Part B(2017)
- Issue Display:
- Volume 73, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 73
- Issue:
- 2
- Issue Sort Value:
- 2017-0073-0002-0000
- Page Start:
- 1032
- Page End:
- 1038
- Publication Date:
- 2017-03
- Subjects:
- Biomarker -- In silico -- Listeria -- Detection method -- Food contamination
Food -- Quality -- Periodicals
Food -- Analysis -- Periodicals
Food handling -- Periodicals
Food industry and trade -- Quality control -- Periodicals
Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques
Aliments -- Qualité -- Périodiques
Aliments -- Analyse -- Périodiques
Hygiène alimentaire -- Périodiques
Food -- Analysis
Food handling
Food -- Quality
Periodicals
Electronic journals
664.07 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09567135 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.foodcont.2016.10.001 ↗
- Languages:
- English
- ISSNs:
- 0956-7135
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3977.291500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5674.xml