Multi fragment melting analysis system (MFMAS) for one-step identification of lactobacilli

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dc.authoridgormez, yasin/0000-0001-8276-2030
dc.contributor.authorKesmen, Zulal
dc.contributor.authorKilic, Ozge
dc.contributor.authorGormez, Yasin
dc.contributor.authorCelik, Mete
dc.contributor.authorBakir-Gungor, Burcu
dc.date.accessioned2024-10-26T18:09:00Z
dc.date.available2024-10-26T18:09:00Z
dc.date.issued2020
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractThe accurate identification of lactobacilli is essential for the effective management of industrial practices associated with lactobacilli strains, such as the production of fermented foods or probiotic supplements. For this reason, in this study, we proposed the Multi Fragment Melting Analysis System (MFMAS)-lactobacilli based on high resolution melting (HRM) analysis of multiple DNA regions that have high interspecies heterogeneity for fast and reliable identification and characterization of lactobacilli. The MFMAS-lactobacilli is a new and customized version of the MFMAS, which was developed by our research group. MFMAS-lactobacilli is a combined system that consists of i) a ready-to-use plate, which is designed for multiple HRM analysis, and ii) a data analysis software, which is used to characterize lactobacilli species via incorporating machine learning techniques. Simultaneous HRM analysis of multiple DNA fragments yields a fingerprint for each tested strain and the identification is performed by comparing the fingerprints of unknown strains with those of known lactobacilli species registered in the MFMAS. In this study, a total of 254 isolates, which were recovered from fermented foods and probiotic supplements, were subjected to MFMAS analysis, and the results were confirmed by a combination of different molecular techniques. All of the analyzed isolates were exactly differentiated and accurately identified by applying the single-step procedure of MFMAS, and it was determined that all of the tested isolates belonged to 18 different lactobacilli species. The individual analysis of each target DNA region provided identification with an accuracy range from 59% to 90% for all tested isolates. However, when each target DNA region was analyzed simultaneously, perfect discrimination and 100% accurate identification were obtained even in closely related species. As a result, it was concluded that MFMAS-lactobacilli is a multi-purpose method that can be used to differentiate, classify, and identify lactobacilli species. Hence, our proposed system could be a potential alternative to overcome the inconsistencies and difficulties of the current methods.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [TOVAG116O758]; Erciyes University Scientific and Technological Research Center/Turkey [FDA-2017-7588]
dc.description.sponsorshipThis study was supported by The Scientific and Technological Research Council of Turkey (TUBITAK Project Number TOVAG116O758) and Erciyes University Scientific and Technological Research Center/Turkey (Project Code: FDA-2017-7588). The MFMAS is a patent-protected product of Erciyes Technopark Inc.
dc.identifier.doi10.1016/j.mimet.2020.106045
dc.identifier.issn0167-7012
dc.identifier.issn1872-8359
dc.identifier.pmid32890569
dc.identifier.scopus2-s2.0-85090547673
dc.identifier.scopusqualityQ3
dc.identifier.urihttps://doi.org/10.1016/j.mimet.2020.106045
dc.identifier.urihttps://hdl.handle.net/20.500.12418/29885
dc.identifier.volume177
dc.identifier.wosWOS:000579380400017
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofJournal of Microbiological Methods
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMulti-fragment melting analysis system (MFMAS)
dc.subjectHigh resolution melting (HRM)
dc.subjectLactobacilli
dc.subjectOne-step identification
dc.subjectMachine learning
dc.subjectLogistic regression (LR)
dc.titleMulti fragment melting analysis system (MFMAS) for one-step identification of lactobacilli
dc.typeArticle

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