Abstract
AIMS: In infective endocarditis (IE), a severe inflammatory disease of the endocardium with an unchanged incidence and mortality rate over the past decades, only 1% of the cases have been described as polymicrobial infections based on microbiological approaches. The aim of this study was to identify potential biodiversity of bacterial species from infected native and prosthetic valves. Furthermore, we compared the ultrastructural micro-environments to detect the localization and distribution patterns of pathogens in IE. MATERIAL AND METHODS: Using next-generation sequencing (NGS) of 16S rDNA, which allows analysis of the entire bacterial community within a single sample, we investigated the biodiversity of infectious bacterial species from resected native and prosthetic valves in a clinical cohort of 8 IE patients. Furthermore, we investigated the ultrastructural infected valve micro-environment by focused ion beam scanning electron microscopy (FIB-SEM). RESULTS: Biodiversity was detected in 7 of 8 resected heart valves. This comprised 13 bacterial genera and 16 species. In addition to 11 pathogens already described as being IE related, 5 bacterial species were identified as having a novel association. In contrast, valve and blood culture-based diagnosis revealed only 4 species from 3 bacterial genera and did not show any relevant antibiotic resistance. The antibiotics chosen on this basis for treatment, however, did not cover the bacterial spectra identified by our amplicon sequencing analysis in 4 of 8 cases. In addition to intramural distribution patterns of infective bacteria, intracellular localization with evidence of bacterial immune escape mechanisms was identified. CONCLUSION: The high frequency of polymicrobial infections, pathogen diversity, and intracellular persistence of common IE-causing bacteria may provide clues to help explain the persistent and devastating mortality rate observed for IE. Improved bacterial diagnosis by 16S rDNA NGS that increases the ability to tailor antibiotic therapy may result in improved outcomes.