Infective endocarditis is a life-threatening infection of heart valves and adjacent structures characterized by vegetations on valves and other endocardial surfaces, with tissue destruction and risk of embolization. We used high-resolution mass spectrometry to define the proteome of staphylococcal and non-staphylococcal vegetations and Terminal Amine Isotopic Labeling of Substrates (TAILS) to define their proteolytic landscapes. These approaches identified over 2000 human proteins in staphylococcal and non-staphylococcal vegetations. Individual vegetation proteomes demonstrated comparable profiles of quantitatively major constituents that overlapped with serum, platelet, and neutrophil proteomes. Staphylococcal vegetation proteomes resembled one another more than the proteomes of non-staphylococcal vegetations. TAILS demonstrated extensive proteolysis within vegetations, with numerous previously undescribed cleavages. Several proteases and pathogen-specific proteins, including virulence factors, were identified in most vegetations. Proteolytic peptides in fibronectin and complement C3 were identified as potential infective endocarditis biomarkers. Overlap of staphylococcal and non-staphylococcal vegetation proteomes suggests a convergent thrombotic and immune response to endocardial infection by diverse pathogens. However, the differences between staphylococcal and non-staphylococcal vegetations and internal variance within the non-staphylococcal group indicate that additional pathogen- or patient-specific effects exist. Pervasive proteolysis of vegetation components may arise from vegetation-intrinsic proteases and destabilize vegetations, contributing to embolism.
Daniel R. Martin, James C. Witten, Carmela D. Tan, E. Rene Rodriguez, Eugene H. Blackstone, Gosta B. Pettersson, Deborah E. Seifert, Belinda B. Willard, Suneel S. Apte
Usage data is cumulative from June 2020 through August 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.