Publication: MALDI-TOF mass spectrometry typing for predominant serovars of non-typhoidal Salmonella in a Thai broiler industry
dc.contributor.author | Suthee Mangmee | en_US |
dc.contributor.author | Onrapak Reamtong | en_US |
dc.contributor.author | Thareerat Kalambaheti | en_US |
dc.contributor.author | Sittiruk Roytrakul | en_US |
dc.contributor.author | Piengchan Sonthayanon | en_US |
dc.contributor.other | Mahidol University | en_US |
dc.contributor.other | Thailand National Center for Genetic Engineering and Biotechnology | en_US |
dc.date.accessioned | 2020-03-26T04:26:07Z | |
dc.date.available | 2020-03-26T04:26:07Z | |
dc.date.issued | 2020-07-01 | en_US |
dc.description.abstract | © 2020 The Authors Rapid and reliable detection of non-typhoidal Salmonella (NTS) is essential for effective monitoring and controlling in broiler industries. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been reported as a sensitive and accurate method for microbial investigations at genus and species level while subspecies level is still obscure. Here, we developed a MALDI-TOF MS-based method to improve the simultaneous identification of species, subspecies, and serovars of NTS isolated from broiler samples in a Thai slaughtering and processing factory. Whole-cell peptide patterns from 142 NTS isolates were integrated with the commercial database for species and subspecies identification based on weighted pattern (subtyping MSP) matching. Serovar-specific peaks were searched and determined using the machine-learning analysis. The classification tree was created for detection of the five predominant NTS serovars (i.e., Albany, Agona, Typhimurium/I 4,[5],12:i:-, Altona, and Enteritidis). One hundred and forty-five NTS isolates were evaluated and yielded all accurate identification at species and subspecies level corresponding to conventional methods. Besides, the serovar classification was achieved with 99.3% accuracy when compared with serotyping. This method would be useful for large scale screening of NTS serovars in food industries where cost-effectiveness, rapid and highly accurate methods are required. | en_US |
dc.identifier.citation | Food Control. Vol.113, (2020) | en_US |
dc.identifier.doi | 10.1016/j.foodcont.2020.107188 | en_US |
dc.identifier.issn | 09567135 | en_US |
dc.identifier.other | 2-s2.0-85080980666 | en_US |
dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/53511 | |
dc.rights | Mahidol University | en_US |
dc.rights.holder | SCOPUS | en_US |
dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85080980666&origin=inward | en_US |
dc.subject | Agricultural and Biological Sciences | en_US |
dc.subject | Biochemistry, Genetics and Molecular Biology | en_US |
dc.title | MALDI-TOF mass spectrometry typing for predominant serovars of non-typhoidal Salmonella in a Thai broiler industry | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85080980666&origin=inward | en_US |