Identification of root canal microbiota profiles of periapical tissue diseases using matrix-assisted laser desorption/ionization time-of-flight mass spectrometer

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Mete Ahlat , Cumhur Aydin , Sinem Kaya , Mehmet Baysallar
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引用次数: 0

Abstract

Objectives

The purpose of this study was to identify microorganisms isolated from various periapical tissue diseases using Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF-MS) and classify them via an unsupervised machine learning approach.

Methods

A total of 150 patients with various apical conditions and teeth in need of endodontic retreatment were divided into five groups, including Retreatment, Acute Apical Abscess, Chronic Apical Abscess, Acute Apical Periodontitis, and Chronic Apical Periodontitis. Samples were collected from root canals using paper points after agitating with a #10 K file then microorganisms were identified using MALDI-TOF-MS. Data were analyzed using a hierarchical clustering method. Quadruple clusters and dendrograms were formed according to similarities and dissimilarities.

Results

A total of 80 species were identified under six different phyla. The most similar microorganism species were identified ''Enterococcus faecalis'' between 21 and 23-year-old female cases in Retreatment group; ''Lactobacillus rhamnosus'' between 20 and 18-year-old male cases in Symptomatic Apical Abscess cases; ''Lactobacillus paracasei'' between 26 and 40-year-old male cases in Asymptomatic Apical Abscess cases; ''Enterococcus faecalis'' between 48 and 50-year-old female cases in Symptomatic Apical Periodontitis cases; ''Lactobacillus rhamnosus'' between 48 and 60-year-old male cases in Asymptomatic Apical Periodontitis cases.

Conclusions

MALDI-TOF MS can be considered a fast and high-throughput screening technique for microbial species identification in endodontics. Thus, it will provide valuable data for future research designs regarding periapical tissue diseases. As the MALDI-TOF MS database expands and comprehensive data becomes available, the relationship between microbial profiles and disease progression will become increasingly apparent.

使用基质辅助激光解吸/电离飞行时间质谱仪鉴定根尖周组织疾病的根管微生物群图谱。
目的:本研究的目的是使用基质辅助激光解吸电离飞行时间质谱法(MALDI-TOF-MS)鉴定从各种根尖周组织疾病中分离的微生物,并通过无监督的机器学习方法对其进行分类。方法:将150例不同根尖条件和牙齿需要根管再治疗的患者分为5组,分别为再治疗组、急性根尖脓肿组、慢性根尖脓肿组,急性根尖牙周炎组和慢性根尖牙周炎组。在用#10搅拌后,使用纸点从根管中收集样品 K文件,然后使用MALDI-TOF-MS鉴定微生物。使用层次聚类方法对数据进行分析。根据相似性和不同性形成了四重聚类和树状图。结果:共鉴定出6个不同门下的80个种。在再治疗组的21至23岁女性病例中,发现了最相似的微生物种类“粪肠球菌”鼠李糖乳杆菌“20至18岁男性症状性根尖脓肿病例;”副干酪乳杆菌“”26至40岁男性病例,无症状根尖脓肿病例粪肠球菌“48至50岁女性症状性根尖牙周炎病例;”48至60岁男性无症状根尖牙周炎病例中的鼠李糖乳杆菌。结论:MALDI-TOF MS是一种快速、高通量的牙髓病微生物菌种鉴定筛选技术。因此,它将为未来关于根尖周组织疾病的研究设计提供有价值的数据。随着MALDI-TOF MS数据库的扩展和全面数据的可用,微生物特征与疾病进展之间的关系将变得越来越明显。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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