Multi Fragment Melting Analysis System (MFMAS) for One-Step Identification of Lactobacilli

dc.contributor.author Kesmen, Zulal
dc.contributor.author Kilic, Ozge
dc.contributor.author Gormez, Yasin
dc.contributor.author Celik, Mete
dc.contributor.author Bakir-Gungor, Burcu
dc.date.accessioned 2025-09-25T10:51:08Z
dc.date.available 2025-09-25T10:51:08Z
dc.date.issued 2020
dc.description Gormez, Yasin/0000-0001-8276-2030; en_US
dc.description.abstract The 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. en_US
dc.description.sponsorship Scientific and Technological Research Council of Turkey (TUBITAK) [TOVAG116O758]; Erciyes University Scientific and Technological Research Center/Turkey [FDA-2017-7588] en_US
dc.description.sponsorship This 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. en_US
dc.identifier.doi 10.1016/j.mimet.2020.106045
dc.identifier.issn 0167-7012
dc.identifier.issn 1872-8359
dc.identifier.scopus 2-s2.0-85090547673
dc.identifier.uri https://doi.org/10.1016/j.mimet.2020.106045
dc.identifier.uri https://hdl.handle.net/20.500.12573/4238
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartof Journal of Microbiological Methods en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Multi-Fragment Melting Analysis System (MFMAS) en_US
dc.subject High Resolution Melting (HRM) en_US
dc.subject Lactobacilli en_US
dc.subject One-Step Identification en_US
dc.subject Machine Learning en_US
dc.subject Logistic Regression (LR) en_US
dc.title Multi Fragment Melting Analysis System (MFMAS) for One-Step Identification of Lactobacilli en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Gormez, Yasin/0000-0001-8276-2030
gdc.author.scopusid 8668024500
gdc.author.scopusid 57200856680
gdc.author.scopusid 57195222392
gdc.author.scopusid 14024176500
gdc.author.scopusid 25932029800
gdc.author.wosid Kesmen, Zülal/B-2020-2016
gdc.author.wosid Görmez, Yasin/Jef-8096-2023
gdc.author.wosid Kılıç Tosun, Özge/Ado-7171-2022
gdc.author.wosid Celik, Mete/Z-2986-2019
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department Abdullah Gül University en_US
gdc.description.departmenttemp [Kesmen, Zulal; Kilic, Ozge] Erciyes Univ, Engn Fac, Dept Food Engn, Kayseri, Turkey; [Gormez, Yasin] Cumhuriyet Univ, Fac Econ & Adm Sci, Sivas, Turkey; [Celik, Mete] Erciyes Univ, Engn Fac, Dept Comp Engn, Kayseri, Turkey; [Bakir-Gungor, Burcu] Abdullah Gul Univ, Fac Engn, Dept Comp Engn, Kayseri, Turkey en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q3
gdc.description.startpage 106045
gdc.description.volume 177 en_US
gdc.description.woscitationindex Science Citation Index Expanded
gdc.description.wosquality Q3
gdc.identifier.openalex W3083504631
gdc.identifier.pmid 32890569
gdc.identifier.wos WOS:000579380400017
gdc.index.type WoS
gdc.index.type Scopus
gdc.index.type PubMed
gdc.oaire.diamondjournal false
gdc.oaire.impulse 0.0
gdc.oaire.influence 2.532154E-9
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gdc.oaire.keywords DNA, Bacterial
gdc.oaire.keywords Bacteriological Techniques
gdc.oaire.keywords Probiotics
gdc.oaire.keywords Sequence Analysis, DNA
gdc.oaire.keywords Polymerase Chain Reaction
gdc.oaire.keywords Machine Learning
gdc.oaire.keywords Lactobacillus
gdc.oaire.keywords Logistic Models
gdc.oaire.keywords Genes, Bacterial
gdc.oaire.keywords Food Microbiology
gdc.oaire.keywords Software
gdc.oaire.popularity 2.8385239E-9
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gdc.oaire.sciencefields 0301 basic medicine
gdc.oaire.sciencefields 0303 health sciences
gdc.oaire.sciencefields 03 medical and health sciences
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gdc.plumx.mendeley 16
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gdc.scopus.citedcount 3
gdc.virtual.author Güngör, Burcu
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