Cardiac troponin T in extracellular vesicles as a novel biomarker in human cardiovascular disease

Abstract

Dear Editor,Soluble cardiac troponin T (cTnT), an indicator of myocardial injury and stress, is used in decision management for patients with cardiovascular disease (CVD). As highly sensitive assays can detect elevated concentrations of cTnT even in healthy individuals (e.g. outside of myocardial necrosis, electrocardiographic changes or angina) and cannot distinguish among disease conditions, 1,2 a comprehensive understanding of the cTnT-secretome is an unmet need.Within the secretome, cTnT is not only present as a soluble factor but may also be contained within extracellular vesicles (EVs). 3 EVs are nanoscale particles secreted by all cells, the cargoes of which can reflect the molecular composition of the cells of origin 4 and indicate disease or injury. 5 As EVs are easily sampled from plasma, 6 they are being developed as a 'liquid' biopsy reflecting the disease state from the tissue of origin. Here, we advanced a fluorescence-based super-resolution microscopy technique, quantitative single-molecule localization microscopy (qSMLM), to robustly characterize cTnT-positive EVs. Importantly, we provide the first report of cTnT-secretome across a spectrum of CVDs.EVs were purified from induced pluripotent stem cellderived cardiomyocyte cell media (CCM), representing a source of cardiomyocyte-derived EVs (Figure S1), and patient plasma (Figures S2): healthy subjects (n = 5), patients with heart failure (HF; n = 5), hypertrophic cardiomyopathy (n = 3), type 1 myocardial infarction (MI-TI, n = 5) or type 2 myocardial infarction (MI-TII; n = 5) and chronic kidney disease (CKD; n = 5). In all cases (Figures S1 and S2), EVs had intact morphology and contained canonical EV markers (tetraspanins CD9, CD63, CD81; luminal marker TSG101) with low amounts of soluble proteins. According to dot blots (Figure S2C), the CD81 content of patient EVs was highly variable, whereas combined tetraspanins had more uniform expression. Table S1 shows patient characteristics. Control patients wereThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Single Extracellular VEsicle Nanoscopy

“…We first assessed the distribution of CD9, CD63 and CD81 on tetraspanin-enriched EVs from pooled human plasma (these EVs were first SEC-enriched, Figure 2). We detected EV membrane (CF568-maleimide dye covalently attaches to exposed cysteine residues on EV membrane, providing excellent coverage of EV membrane (Lennon et al, 2022), in yellow) and tetraspanins on the EV membrane (AF647-labelled anti-TSPAN Abs affinity attach to CD9, CD63 and CD81, in red), Figure 3a, left. Most EVs show an excellent overlap between two channels, with the Gaussian distribution of centroid shifts in both x-and y-direction (Figure 3a, right).…”

Protocol to separate small and large extracellular vesicles from mouse and human cardiac tissues

“… 16 , 17 Cardiac EVs are also enriched in Troponin T which can be used as a marker in the Western Blot to confirm the separation of EVs secreted by cardiac myocytes. 18 In addition, proteomic analysis is valuable in identifying the composition of the EVs and their cargo. This allows investigators to evaluate if the cargo is different in disease.…”

Syntenin and CD63 Promote Exosome Biogenesis from the Plasma Membrane by Blocking Cargo Endocytosis

“…All antibodies were fluorescently labeled as described previously at a molar ratio of ~1 ( 74)). Samples were fixed and stored as described previously (75,76).…”

“…Images were acquired using NIS-Elements software (Nikon Instruments). SMLM images were processed using N-STORM Offline Analysis Module of the NIS-Elements software to localize peaks as described before (75). The localization data were analyzed with the Nanometrix software (version 1.0.4.61; Nanometrix Ltd, Oxford, UK) using a density-based spatial clustering of applications with noise (DBSCAN) algorithm.…”