Extracellular vesicles (EVs) are small, heterogeneous and difficult to measure. Flow cytometry (FC) is a key technology for the measurement of individual particles, but its application to the analysis of EVs and other submicron particles has presented many challenges and has produced a number of controversial results, in part due to limitations of instrument detection, lack of robust methods and ambiguities in how data should be interpreted. These complications are exacerbated by the field's lack of a robust reporting framework, and many EV-FC manuscripts include incomplete descriptions of methods and results, contain artefacts stemming from an insufficient instrument sensitivity and inappropriate experimental design and lack appropriate calibration and standardization. To address these issues, a working group (WG) of EV-FC researchers from ISEV, ISAC and ISTH, worked together as an EV-FC WG and developed a consensus framework for the minimum information that should be provided regarding EV-FC. This framework incorporates the existing Minimum Information for Studies of EVs (MISEV) guidelines and Minimum Information about a FC experiment (MIFlowCyt) standard in an EV-FC-specific reporting framework (MIFlowCyt-EV) that supports reporting of critical information related to sample staining, EV detection and measurement and experimental design in manuscripts that report EV-FC data. MIFlowCyt-EV provides a structure for sharing EV-FC results, but it does not prescribe specific protocols, as there will continue to be rapid evolution of instruments and methods for the foreseeable future. MIFlowCyt-EV accommodates this evolution, while providing information needed to evaluate and compare different approaches. Because MIFlowCyt-EV will ensure consistency in the manner of reporting of EV-FC studies, over time we expect that adoption of MIFlowCyt-EV as a standard for reporting EV-FC studies will improve the ability to quantitatively compare results from different laboratories and to support the development of new instruments and assays for improved measurement of EVs.

Extracellular vesicles (EVs) are attracting attention as vehicles for inter-cellular signaling that may have value as diagnostic or therapeutic targets. EVs are released by many cell types and by different mechanisms, resulting in phenotypic heterogeneity that makes them a challenge to study. Flow cytometry is a popular tool for characterizing heterogeneous mixtures of particles such as cell types within blood, but the small size of EVs makes them difficult to measure using conventional flow cytometry. To address this limitation, a high sensitivity flow cytometer was constructed and EV measurement approaches that allowed them to enumerate and estimate the size of individual EVs, as well as measure the presence of surface markers to identify phenotypic subsets of EVs. Several fluorescent membrane probes were evaluated and it was found that the voltage sensing dye di-8-ANEPPS could produce vesicle fluorescence in proportion to vesicle surface area, allowing for accurate measurements of EV number and size. Fluorescence-labeled annexin V and anti-CD61 antibody was used to measure the abundance of these surface markers on EVs in rat plasma. It was shown that treatment of platelet rich plasma with calcium ionophore resulted in an increase in the fraction of annexin V and CD61-positive EVs. Vesicle flow cytometry using fluorescence-based detection of EVs has the potential to realize the potential of cell-derived membrane vesicles as functional biomarkers for a variety of applications. V C 2015 International Society for Advancement of Cytometry

To the editor:Obtaining diffraction-quality crystals is a major bottleneck in protein X-ray crystallography. For example, the current success rate for protein structure solution at the Midwest Center for Structural Genomics (starting from purified protein) is ~10%. Protein crystallization is influenced by many factors, and many methods have been developed to enhance crystallization. In particular, reductive methylation of proteins has been successfully applied to obtain high-quality crystals 1-4 . Several studies 3,5,6 have indicated that methylating the solvent-exposed ε-amino group of lysines changes protein properties (pI, solubility and hydropathy) 7,8 , which may promote crystallization via improving crystal packing. Reductive methylation of proteins is a simple, generic method; it is fast, specific and requires few steps under relatively mild buffer and chemical conditions and can be executed for several proteins in parallel. Native and methylated proteins have very similar structures, and, in most cases, methylated proteins maintain their biochemical function 2,5,9 . Some proteins can only be crystallized after methylation 3,10 , and crystals of modified proteins often diffract to higher resolution 3,9 . The efficacy of the method has been previously tested on 10 proteins, with a 30% success rate 3 .Here we investigated the application of reductive methylation on a large scale. We applied a previously described reductive methylation protocol 2,11 (Supplementary Methods online) to 370 sequence-diverse proteins selected from protein families that had no structural homologs with >30% sequence identity. We expressed 370 recombinant proteins and purified them using standard methods 12 and screened them using standard crystal screening methods (Supplementary Methods). Of the 370 proteins, 269 proteins had not previously yielded crystals suitable for structure determination (crystals were too small, poorly ordered, twinned, highly mosaic or multiple), 85 proteins had previously failed to crystallize and 16 proteins were a reference set (not previously screened for crystallization; Table 1 and Supplementary Tables 1 and 2 online). After reductive methylation, we obtained diffraction-quality crystals for 40 of the 370 proteins, and so far we solved 26 crystal structures ( NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptWe also determined the structures of 4 proteins in their native as well as their methylated states (Supplementary Methods). By comparing these structures, we obtained insight into how methylation affects protein crystallization. We observed a decrease in the isotropic B factor (Fig. 1), which is likely a result of more ordered crystal packing and which leads to better diffraction limits. Indeed, the resolution of the methylated structures (average, 2.07 Å) was better than that of their native counterparts (average, 3.05 Å; Supplementary Table 1). The methylated lysines were engaged in various intra-and intermolecular interactions with protein and solvent (carboxylates and ...

Extracellular vesicles (EVs) have emerged as a promising biomarker platform for glioblastoma patients. However, the optimal method for quantitative assessment of EVs in clinical bio-fluid remains a point of contention. Multiple high-resolution platforms for quantitative EV analysis have emerged, including methods grounded in diffraction measurement of Brownian motion (NTA), tunable resistive pulse sensing (TRPS), vesicle flow cytometry (VFC), and transmission electron microscopy (TEM). Here we compared quantitative EV assessment using cerebrospinal fluids derived from glioblastoma patients using these methods. For EVs <150 nm in diameter, NTA detected more EVs than TRPS in three of the four samples tested. VFC particle counts are consistently 2–3 fold lower than NTA and TRPS, suggesting contribution of protein aggregates or other non-lipid particles to particle count by these platforms. While TEM yield meaningful data in terms of the morphology, its particle count are consistently two orders of magnitude lower relative to counts generated by NTA and TRPS. For larger particles (>150 nm in diameter), NTA consistently detected lower number of EVs relative to TRPS. These results unveil the strength and pitfalls of each quantitative method alone for assessing EVs derived from clinical cerebrospinal fluids and suggest that thoughtful synthesis of multi-platform quantitation will be required to guide meaningful clinical investigations.

We examined the extracellular vesicle (EV) and RNA composition of pooled normal cerebrospinal fluid (CSF) samples and CSF from five major neurological disorders: Alzheimer’s disease (AD), Parkinson’s disease (PD), low-grade glioma (LGG), glioblastoma multiforme (GBM), and subarachnoid haemorrhage (SAH), representing neurodegenerative disease, cancer, and severe acute brain injury. We evaluated: (I) size and quantity of EVs by nanoparticle tracking analysis (NTA) and vesicle flow cytometry (VFC), (II) RNA yield and purity using four RNA isolation kits, (III) replication of RNA yields within and between laboratories, and (IV) composition of total and EV RNAs by reverse transcription–quantitative polymerase chain reaction (RT-qPCR) and RNA sequencing (RNASeq). The CSF contained ~106 EVs/μL by NTA and VFC. Brain tumour and SAH CSF contained more EVs and RNA relative to normal, AD, and PD. RT-qPCR and RNASeq identified disease-related populations of microRNAs and messenger RNAs (mRNAs) relative to normal CSF, in both total and EV fractions. This work presents relevant measures selected to inform the design of subsequent replicative CSF studies. The range of neurological diseases highlights variations in total and EV RNA content due to disease or collection site, revealing critical considerations guiding the selection of appropriate approaches and controls for CSF studies.

Extracellular vesicles (EVs) are released by cells and can be found in cell culture supernatants and biofluids. EVs carry proteins, nucleic acids, and other cellular components and can deliver these to nearby or distant cells, making EVs of interest as both disease biomarkers and therapeutic targets. EVs in biofluids are heterogeneous, coming from different cell types and from different sources with the cell, which limits the usefulness of bulk EV analysis methods that report the average features of all EVs present. Single-particle measurements such as flow cytometry would be preferred, but the small size and low abundance of surface antigens challenges conventional flow cytometry approaches, leading to the development of vesicle-specific assays and experimental design. Among the key issues that have emerged are: (a) judicious choice of detection (triggering) approach; (b) appropriate control experiments to confirm the vesicular nature of the detected events and the contribution of coincidence (aka swarm detection); and (c) the importance of fluorescence calibration to allow data to be compared over time and between laboratories. We illustrate these issues in the context of fluorescence-triggered Vesicle Flow Cytometry (VFC), a general approach to the quantitative measurement of EV number, size, and surface marker expression.

Fluorescence is a mainstay of bioanalytical methods, offering sensitive and quantitative reporting, often in multiplexed or multiparameter assays. Perhaps the best example of the latter is flow cytometry, where instruments equipped with multiple lasers and detectors allow measurement of 15 or more different fluorophores simultaneously, but increases beyond this number are limited by the relatively broad emission spectra. Surface enhanced Raman scattering (SERS) from metal nanoparticles can produce signal intensities that rival fluorescence, but with narrower spectral features that allow a greater degree of multiplexing. We are developing nanoparticle SERS tags as well as Raman flow cytometers for multiparameter single cell analysis of suspension or adherent cells. SERS tags are based on plasmonically active nanoparticles (gold nanorods) whose plasmon resonance can be tuned to give optimal SERS signals at a desired excitation wavelength. Raman resonant compounds are adsorbed on the nanoparticles to confer a unique spectral fingerprint on each SERS tag, which are then encapsulated in a polymer coating for conjugation to antibodies or other targeting molecules. Raman flow cytometry employs a high resolution spectral flow cytometer capable of measuring the complete SERS spectra, as well as conventional flow cytometry measurements, from thousands of individual cells per minute. Automated spectral unmixing algorithms extract the contributions of each SERS tag from each cell to generate high content, multiparameter single cell population data. SERS-based cytometry is a powerful complement to conventional fluorescence-based cytometry. The narrow spectral features of the SERS signal enables more distinct probes to be measured in a smaller region of the optical spectrum with a single laser and detector, allowing for higher levels of multiplexing and multiparameter analysis.

Methamphetamine (MA) is the largest drug threat across the globe, with health effects including neurotoxicity and cardiovascular disease. Recent studies have begun to link microRNAs (miRNAs) to the processes related to MA use and addiction. Our studies are the first to analyse plasma EVs and their miRNA cargo in humans actively using MA (MA‐ACT) and control participants (CTL). In this cohort we also assessed the effects of tobacco use on plasma EVs. We used vesicle flow cytometry to show that the MA‐ACT group had an increased abundance of EV tetraspanin markers (CD9, CD63, CD81), but not pro‐coagulant, platelet‐, and red blood cell‐derived EVs. We also found that of the 169 plasma EV miRNAs, eight were of interest in MA‐ACT based on multiple statistical criteria. In smokers, we identified 15 miRNAs of interest, two that overlapped with the eight MA‐ACT miRNAs. Three of the MA‐ACT miRNAs significantly correlated with clinical features of MA use and target prediction with these miRNAs identified pathways implicated in MA use, including cardiovascular disease and neuroinflammation. Together our findings indicate that MA use regulates EVs and their miRNA cargo, and support that further studies are warranted to investigate their mechanistic role in addiction, recovery, and recidivism.