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.

乳酸菌的准确鉴定对于有效管理与乳酸菌菌株相关的工业实践（例如生产发酵食品或益生菌补品）至关重要。因此，在这项研究中，我们基于具有高种间异质性的多个DNA区域的高分辨率熔解（HRM）分析，提出了多片段熔解分析系统（MFMAS）-乳杆菌，以快速，可靠地鉴定和鉴定乳杆菌。MFMAS-乳杆菌是MFMAS的新版本和定制版本，由我们的研究小组开发。MFMAS-乳杆菌是一个组合系统，包括：i）现成的板，可用于多种HRM分析，以及ii）数据分析软件，用于通过结合机器学习技术来表征乳酸菌种类。多个DNA片段的同时HRM分析可为每个测试菌株产生指纹，并通过将未知菌株的指纹与MFMAS中注册的已知乳杆菌物种的指纹进行比较来进行鉴定。在这项研究中，从发酵食品和益生菌补品中回收的总共254个分离物进行了MFMAS分析，结果通过多种分子技术的结合得到了证实。通过使用MFMAS的单步方法，可以对所有分析的分离物进行精确区分和准确鉴定，并且确定所有测试的分离物都属于18种不同的乳酸菌。对每个靶DNA区域的单独分析提供了对所有测试分离株的准确度范围为59％至90％的鉴定。但是，当同时分析每个目标DNA区域时，即使在密切相关的物种中也能获得完美的区分和100％的准确识别。结果，得出结论，MFMAS-乳杆菌是可用于区分，分类和鉴定乳杆菌种类的多用途方法。因此，我们提出的系统可能是克服当前方法的不一致和困难的潜在选择。即使在密切相关的物种中，也能获得完美的区分和100％的准确识别。结果，得出结论，MFMAS-乳杆菌是可用于区分，分类和鉴定乳杆菌种类的多用途方法。因此，我们提出的系统可能是克服当前方法的不一致和困难的潜在选择。即使在密切相关的物种中，也能获得完美的区分和100％准确的识别。结果，得出结论，MFMAS-乳杆菌是可用于区分，分类和鉴定乳杆菌种类的多用途方法。因此，我们提出的系统可能是克服当前方法的不一致和困难的潜在选择。