Infective endocarditis (IE) is an inflammatory disease usually caused by bacteria that enter the bloodstream and establish infections in the inner linings or valves of the heart, including blood vessels. Despite the availability of modern antimicrobial and surgical treatments, IE continues to cause substantial morbidity and mortality. Oral microbiota is considered one of the most significant risk factors for IE. The objective of this study was to evaluate the microbiota present in root canal (RC) and periodontal pocket (PP) clinical samples in cases with combined endo-periodontal lesions (EPL) to detect species related to IE using NGS. Microbial samples were collected from 15 RCs and their associated PPs, also from 05 RCs with vital pulp tissues (negative control, NC). Genomic studies associated with bioinformatics, combined with structuring of a database (genetic sequences of bacteria reported for infective endocarditis), allowed for the assessment of the microbial community at both sites. Functional prediction was conducted using PICRUSt2. Parvimonas, Streptococcus, and Enterococcus were the major genera detected in the RCs and PPs. A total of 79, 96, and 11 species were identified in the RCs, PPs, and NCs, respectively. From them, a total of 34 species from RCs, 53 from PPs, and 2 from NCs were related to IE. Functional inference demonstrated that CR and PP microbiological profiles may not be the only risk factors for IE but may also be associated with systemic diseases, including myocarditis, human cytomegalovirus infection, bacterial invasion of epithelial cells, Huntington's disease, amyotrophic lateral sclerosis, and hypertrophic cardiomyopathy. Additionally, it was possible to predict antimicrobial resistance variants for broad-spectrum drugs, including ampicillin, tetracycline, and macrolides. Microorganisms present in the combined EPL may not be the only risk factor for IE but also for systemic diseases. Antimicrobial resistance variants for broad-spectrum drugs were inferred based on PICRUSt-2. State-of-the-art sequencing combined with bioinformatics has proven to be a powerful tool for conducting studies on microbial communities and could considerably assist in the diagnosis of serious infections. Few studies have investigated the microbiota in teeth compromised by combined endo-periodontal lesions (EPL), but none have correlated the microbiological findings to any systemic condition, particularly IE, using NGS techniques. In such cases, the presence of apical periodontitis and periodontal disease can increase IE risk in susceptible patients.
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