Circulating extracellular vesicles have emerged as potential new biomarkers in a wide variety of diseases. Despite the increasing interest, their isolation and purification from body fluids remains challenging. Here we studied human pre-prandial and 4 hours postprandial platelet-free blood plasma samples as well as human platelet concentrates. Using flow cytometry, we found that the majority of circulating particles within the size range of extracellular vesicles lacked common vesicular markers. We identified most of these particles as lipoproteins (predominantly low-density lipoprotein, LDL) which mimicked the characteristics of extracellular vesicles and also co-purified with them. Based on biophysical properties of LDL this finding was highly unexpected. Current state-of-the-art extracellular vesicle isolation and purification methods did not result in lipoprotein-free vesicle preparations from blood plasma or from platelet concentrates. Furthermore, transmission electron microscopy showed an association of LDL with isolated vesicles upon in vitro mixing. This is the first study to show co-purification and in vitro association of LDL with extracellular vesicles and its interference with vesicle analysis. Our data point to the importance of careful study design and data interpretation in studies using blood-derived extracellular vesicles with special focus on potentially co-purified LDL.

In this study we tested whether a protein corona is formed around extracellular vesicles (EVs) in blood plasma. We isolated medium‐sized nascent EVs of THP1 cells as well as of Optiprep‐purified platelets, and incubated them in EV‐depleted blood plasma from healthy subjects and from patients with rheumatoid arthritis. EVs were subjected to differential centrifugation, size exclusion chromatography, or density gradient ultracentrifugation followed by mass spectrometry. Plasma protein‐coated EVs had a higher density compared to the nascent ones and carried numerous newly associated proteins. Interactions between plasma proteins and EVs were confirmed by confocal microscopy, capillary Western immunoassay, immune electron microscopy and flow cytometry. We identified nine shared EV corona proteins (ApoA1, ApoB, ApoC3, ApoE, complement factors 3 and 4B, fibrinogen α‐chain, immunoglobulin heavy constant γ2 and γ4 chains), which appear to be common corona proteins among EVs, viruses and artificial nanoparticles in blood plasma. An unexpected finding of this study was the high overlap of the composition of the protein corona with blood plasma protein aggregates. This is explained by our finding that besides a diffuse, patchy protein corona, large protein aggregates also associate with the surface of EVs. However, while EVs with an external plasma protein cargo induced an increased expression of TNF‐α, IL‐6, CD83, CD86 and HLA‐DR of human monocyte‐derived dendritic cells, EV‐free protein aggregates had no effect. In conclusion, our data may shed new light on the origin of the commonly reported plasma protein ‘contamination’ of EV preparations and may add a new perspective to EV research.

The internal energies of the emitted ions can be modulated in an electrospray source through different experimental conditions. However, the fragmentation pattern depends also on conditions that cannot be controlled by the operator, e.g. the geometry of the source or the mode of transfer of the ions. These differences make difficult the comparison of the electrospray mass spectra obtained with different mass spectrometers. A method for the calibration of the internal energies of ions produced by an electrospray source has been presented previously to study the influence of experimental conditions on the internal energies of the ions. The method permits the calibration of individual working conditions. In this work, new results were obtained with modified values of fragmentation energy taking into account the kinetic shift of the thermometer ions. The internal energy distributions are compared for different instruments with different geometries, and are measured under different accelerating and focusing conditions. # 1998 John Wiley & Sons, Ltd. Received 4 June 1998; Revised 18 September 1998; Accepted 19 September 1998 Electrospray mass spectrometry allows the study of a variety of ion types from weakly bound complexes 1,-4 to fragments resulting from cleavage of strong covalent bonds. 5,6 Generally, it is assumed that the internal energy of the emitted ions can be modulated through the accelerating voltage in the source. However, the fragmentation pattern depends also on conditions that cannot be easily controlled by the operator, e.g. the geometry of the source or the mode of transfer of the ions. These differences make difficult the comparison of the results obtained using different mass spectrometers.A method for the calibration of the internal energy of the ions produced by an electrospray ionization (ESI) source was presented previously, to permit study of the influence of the experimental conditions on the internal energy of the ions. 7,8 The influence of the collision conditions and the composition of the mobile phase on the internal energy distributions was presented. The method is based on the correlation between the survival yieldof the probe ions (benzyl-substituted benzylpyridinium salts) and known appearance energies. In this paper, the appearance energies were calculated by Rice-Rampsberger-Kasser-Marcus (RRKM) theory as a function of the time of flight of the ions after their activation. This statistical theory allows one to take into account the higher internal energy (appearance energy, E app ) necessary to fragment molecules at observable rates in comparison with the critical energy for reaction (E 0 ). This excess energy is the kinetic shift (E ks ):The derivative of the curve obtained by plotting the survival rate as a function of appearance energy becomes an internal energy distribution of ions formed in the ESI source at fixed experimental conditions. This technique is similar to that described before, 7,8 but E 0 as referred to previously 1,8 is changed here to E app . The method develo...

A theoretical framework and an accompanying computer program (MassKinetics, www.chemres.hu/ms/ masskinetics) is developed for describing reaction kinetics under statistical, but non-equilibrium, conditions, i.e. those applying to mass spectrometry. In this model all the important physical processes influencing product distributions are considered: reactions, including the effects of acceleration, collisions and photon exchange. These processes occur simultaneously and are taken into account by the master equation approach. The system is described by (independent) product, kinetic energy and internal energy distributions, and the time development of these distributions is studied using transition probability functions. The product distribution at the end of the experiment corresponds to the mass spectrum. Individual elements in this scheme are mostly well known: internal energy-dependent reaction rates are calculated by transition state theory (RRK or RRKM formalisms). In the course of collisions, energy transfer and other processes may occur (the latter usually resulting in the 'loss' of ion signal). Collisions are characterized by their probability and by energy transfer in a single collision. To describe single collisions, three collision models are used: long-lived collision complexes, partially inelastic collisions and partially inelastic collisions with cooling. The latter type has been developed here, and is capable of accounting for cooling effects occurring in collision cascades. Descriptions of photon absorption and emission are well known in principle, and these are also taken into account, in addition to changes in kinetic energy due to external (electric) fields. These changes in the system occur simultaneously, and are described by master equations (a set of differential equations). The usual form of the master equation (taking into account reactions and collisional excitation) was extended to consider also radiative energy transfer, kinetic energy changes, energy partitioning and ion loss collisions. Initial results show that close to experimental accuracy can be obtained with MassKinetics, using few or no adjustable parameters. The model/program can be used to model almost all types of mass spectrometric experiments (e.g. MIKE, CID, SORI and resonant excitation). Note that it was designed for mass spectrometric applications, but can also be used to study reaction kinetics in other non-equilibrium systems.