Inter-laboratory multiplex bead-based surface protein profiling of MSC-derived EV preparations identifies MSC-EV surface marker signatures.

Mesenchymal stromal cells (MSCs) are promising regenerative therapeutics that primarily exert their effects through secreted extracellular vesicles (EVs). These EVs - being small and non-living - are easier to handle and possess advantages over cellular products. Consequently, the therapeutic potential of MSC-EVs is increasingly investigated. However, due to variations in MSC-EV manufacturing strategies, MSC-EV products should be considered as highly diverse. Moreover, the diverse array of EV characterisation technologies used for MSC-EV characterisation further complicates reliable interlaboratory comparisons of published data. Consequently, this study aimed to establish a common method that can easily be used by various MSC-EV researchers to characterise MSC-EV preparations to facilitate interlaboratory comparisons. To this end, we conducted a comprehensive inter-laboratory assessment using a novel multiplex bead-based EV flow cytometry assay panel. This assessment involved 11 different MSC-EV products from five laboratories with varying MSC sources, culture conditions, and EV preparation methods. Through this assay panel covering a range of mostly MSC-related markers, we identified a set of cell surface markers consistently positive (CD44, CD73 and CD105) or negative (CD11b, CD45 and CD197) on EVs of all explored MSC-EV preparations. Hierarchical clustering analysis revealed distinct surface marker profiles associated with specific preparation processes and laboratory conditions. We propose CD73, CD105 and CD44 as robust positive markers for minimally identifying MSC-derived EVs and CD11b, CD14, CD19, CD45 and CD79 as reliable negative markers. Additionally, we highlight the influence of culture medium components, particularly human platelet lysate, on EV surface marker profiles, underscoring the influence of culture conditions on resulting EV products. This standardisable approach for MSC-EV surface marker profiling offers a tool for routine characterisation of manufactured EV products in pre-clinical and clinical research, enhances the quality control of MSC-EV preparations, and hopefully paves the way for higher consistency and reproducibility in the emerging therapeutic MSC-EV field.

The EV antibody database: An interactive database of curated antibodies for extracellular vesicle and nanoparticle research.

Antibodies are critical tools for research into extracellular vesicles (EVs) and other extracellular nanoparticles (ENPs), where they can be used for their identification, characterization, and isolation. However, the lack of a centralized antibody platform where researchers can share validation results thus minimizing wasted personnel time and reagents, has been a significant obstacle. Moreover, because the performance of antibodies varies among assay types and conditions, detailed information on assay variables and protocols is also of value. To facilitate sharing of results on antibodies that are relevant to EV/ENP research, the EV Antibody Database has been developed by the investigators of the Extracellular RNA Communication Consortium (ERCC). Hosted by the ExRNA Portal (https://exrna.org/resources/evabdb/), this interactive database aggregates and shares results from antibodies that have been tested by research groups in the EV/ENP field. Currently, the EV Antibody Database includes modules for antibodies tested for western Blot, EV Flow Cytometry, and EV Sandwich Assays, and holds 110 records contributed by 6 laboratories from the ERCC. Detailed information on antibody sources, assay conditions, and results is provided, including negative results. We encourage ongoing expert input and community feedback to enhance the database's utility, making it a valuable resource for comprehensive validation data on antibodies and protocols in EV biology.

MIBlood-EV: Minimal information to enhance the quality and reproducibility of blood extracellular vesicle research.

Blood is the most commonly used body fluid for extracellular vesicle (EV) research. The composition of a blood sample and its derivatives (i.e., plasma and serum) are not only donor-dependent but also influenced by collection and preparation protocols. Since there are hundreds of pre-analytical protocols and over forty variables, the development of standard operating procedures for EV research is very challenging. To improve the reproducibility of blood EV research, the International Society for Extracellular Vesicles (ISEV) Blood EV Task Force proposes standardized reporting of (i) the applied blood collection and preparation protocol and (ii) the quality of the prepared plasma and serum samples. Gathering detailed information will provide insight into the performance of the protocols and more effectively identify potential confounders in the prepared plasma and serum samples. To collect this information, the ISEV Blood EV Task Force created the Minimal Information for Blood EV research (MIBlood-EV), a tool to record and report information about pre-analytical protocols used for plasma and serum preparation as well as assays used to assess the quality of these preparations. This tool does not require modifications of established local pre-analytical protocols and can be easily implemented to enhance existing databases thereby enabling evidence-based optimization of pre-analytical protocols through meta-analysis. Taken together, insight into the quality of prepared plasma and serum samples will (i) improve the quality of biobanks for EV research, (ii) guide the exchange of plasma and serum samples between biobanks and laboratories, (iii) facilitate inter-laboratory comparative EV studies, and (iv) improve the peer review process.

Quantitative flow cytometry enables end-to-end optimization of cross-platform extracellular vesicle studies.

Flow cytometry (FCM) is a common method for characterizing extracellular particles (EPs), including viruses and extracellular vesicles (EVs). Frameworks such as MIFlowCyt-EV exist to provide reporting guidelines for metadata, controls, and data reporting. However, tools to optimize FCM for EP analysis in a systematic and quantitative way are lacking. Here, we demonstrate a cohesive set of methods and software tools that optimize FCM settings and facilitate cross-platform comparisons for EP studies. We introduce an automated small-particle optimization (SPOT) pipeline to optimize FCM fluorescence and light scatter detector settings for EP analysis and leverage quantitative FCM (qFCM) as a tool to further enable FCM optimization of fluorophore panel selection, laser power, pulse statistics, and window extensions. Finally, we demonstrate the value of qFCM to facilitate standardized cross-platform comparisons, irrespective of instrument configuration, settings, and sensitivity, in a cross-platform standardization study utilizing a commercially available EV reference material.

Lysosomal processing of sulfatide analogs alters target NKT cell specificity and immune responses in cancer.

In a structure-function study of sulfatides that typically stimulate type II NKT cells, we made an unexpected discovery. We compared analogs with sphingosine or phytosphingosine chains and 24-carbon acyl chains with 0-1-2 double bonds (C or pC24:0, 24:1, or 24:2). C24:1 and C24:2 sulfatide presented by the CD1d monomer on plastic stimulated type II, not type I, NKT cell hybridomas, as expected. Unexpectedly, when presented by bone marrow-derived DCs (BMDCs), C24:2 reversed specificity to stimulate type I, not type II, NKT cell hybridomas, mimicking the corresponding ß-galactosylceramide (ßGalCer) without sulfate. C24:2 induced IFN-γ-dependent immunoprotection against CT26 colon cancer lung metastases, skewed the cytokine profile, and activated conventional DC subset 1 cells (cDC1s). This was abrogated by blocking lysosomal processing with bafilomycin A1, or by sulfite blocking of arylsulfatase or deletion of this enyzme that cleaves off sulfate. Thus, C24:2 was unexpectedly processed in BMDCs from a type II to a type I NKT cell-stimulating ligand, promoting tumor immunity. We believe this is the first discovery showing that antigen processing of glycosylceramides alters the specificity for the target cell, reversing the glycolipid's function from stimulating type II NKT cells to stimulating type I NKT cells, thereby introducing protective functional activity in cancer. We also believe our study uncovers a new role for antigen processing that does not involve MHC loading but rather alteration of which type of cell is responding.

Extracellular Vesicle Refractive Index Derivation Utilizing Orthogonal Characterization.

The analysis of small particles, including extracellular vesicles and viruses, is contingent on their ability to scatter sufficient light to be detected. These detection methods include flow cytometry, nanoparticle tracking analysis, and single particle reflective image sensing. To standardize measurements and enable orthogonal comparisons between platforms, a quantifiable limit of detection is required. The main parameters that dictate the amount of light scattered by particles include size, morphology, and refractive index. To date, there has been a lack of accessible techniques for measuring the refractive index of nanoparticles at a single-particle level. Here, we demonstrate two methods of deriving a small particle refractive index using orthogonal measurements with commercially available platforms. These methods can be applied at either a single-particle or population level, enabling the integration of diameter and scattering cross section values to derive the refractive index using Mie theory.

Viral Immune signatures from cerebrospinal fluid extracellular vesicles and particles in HAM and other chronic neurological diseases.

Background and objectives: Extracellular vesicles and particles (EVPs) are released from virtually all cell types, and may package many inflammatory factors and, in the case of infection, viral components. As such, EVPs can play not only a direct role in the development and progression of disease but can also be used as biomarkers. Here, we characterized immune signatures of EVPs from the cerebrospinal fluid (CSF) of individuals with HTLV-1-associated myelopathy (HAM), other chronic neurologic diseases, and healthy volunteers (HVs) to determine potential indicators of viral involvement and mechanisms of disease. Methods: We analyzed the EVPs from the CSF of HVs, individuals with HAM, HTLV-1-infected asymptomatic carriers (ACs), and from patients with a variety of chronic neurologic diseases of both known viral and non-viral etiologies to investigate the surface repertoires of CSF EVPs during disease. Results: Significant increases in CD8+ and CD2+ EVPs were found in HAM patient CSF samples compared to other clinical groups (p = 0.0002 and p = 0.0003 compared to HVs, respectively, and p = 0.001 and p = 0.0228 compared to MS, respectively), consistent with the immunopathologically-mediated disease associated with CD8+ T-cells in the central nervous system (CNS) of HAM patients. Furthermore, CD8+ (p < 0.0001), CD2+ (p < 0.0001), CD44+ (p = 0.0176), and CD40+ (p = 0.0413) EVP signals were significantly increased in the CSF from individuals with viral infections compared to those without. Discussion: These data suggest that CD8+ and CD2+ CSF EVPs may be important as: 1) potential biomarkers and indicators of disease pathways for viral-mediated neurological diseases, particularly HAM, and 2) as possible meditators of the disease process in infected individuals.

The NanoFlow Repository.

MOTIVATION: Extracellular particles (EPs) are the focus of a rapidly growing area of exploration due to the widespread interest in understanding their roles in health and disease. However, despite the general need for EP data sharing and established community standards for data reporting, no standard repository for EP flow cytometry data captures rigor and minimum reporting standards such as those defined by MIFlowCyt-EV (https://doi.org/10.1080/20013078.2020.1713526). We sought to address this unmet need by developing the NanoFlow Repository. RESULTS: We have developed The NanoFlow Repository to provide the first implementation of the MIFlowCyt-EV framework. AVAILABILITY AND IMPLEMENTATION: The NanoFlow Repository is freely available and accessible online at https://genboree.org/nano-ui/. Public datasets can be explored and downloaded at https://genboree.org/nano-ui/ld/datasets. The NanoFlow Repository's backend is built using the Genboree software stack that powers the ClinGen Resource, specifically the Linked Data Hub (LDH), a REST API framework written in Node.js, developed initially to aggregate data within ClinGen (https://ldh.clinicalgenome.org/ldh/ui/about). NanoFlow's LDH (NanoAPI) is available at https://genboree.org/nano-api/srvc. NanoAPI is supported by a Node.js Genboree authentication and authorization service (GbAuth), a graph database called ArangoDB, and an Apache Pulsar message queue (NanoMQ) to manage data inflows into NanoAPI. The website for NanoFlow Repository is built with Vue.js and Node.js (NanoUI) and supports all major browsers.

Exosomes, microvesicles, and other extracellular vesicles-a Keystone Symposia report.

Extracellular vesicles (EVs) are small, lipid-bilayer-bound particles released by cells that can contain important bioactive molecules, including lipids, RNAs, and proteins. Once released in the extracellular environment, EVs can act as messengers locally as well as to distant tissues to coordinate tissue homeostasis and systemic responses. There is a growing interest in not only understanding the physiology of EVs as signaling particles but also leveraging them as minimally invasive diagnostic and prognostic biomarkers (e.g., they can be found in biofluids) and drug-delivery vehicles. On October 30-November 2, 2022, researchers in the EV field convened for the Keystone symposium "Exosomes, Microvesicles, and Other Extracellular Vesicles" to discuss developing standardized language and methodology, new data on the basic biology of EVs and potential clinical utility, as well as novel technologies to isolate and characterize EVs.

A compendium of single extracellular vesicle flow cytometry.

Flow cytometry (FCM) offers a multiparametric technology capable of characterizing single extracellular vesicles (EVs). However, most flow cytometers are designed to detect cells, which are larger than EVs. Whereas cells exceed the background noise, signals originating from EVs partly overlap with the background noise, thereby making EVs more difficult to detect than cells. This technical mismatch together with complexity of EV-containing fluids causes limitations and challenges with conducting, interpreting and reproducing EV FCM experiments. To address and overcome these challenges, researchers from the International Society for Extracellular Vesicles (ISEV), International Society for Advancement of Cytometry (ISAC), and the International Society on Thrombosis and Haemostasis (ISTH) joined forces and initiated the EV FCM working group. To improve the interpretation, reporting, and reproducibility of future EV FCM data, the EV FCM working group published an ISEV position manuscript outlining a framework of minimum information that should be reported about an FCM experiment on single EVs (MIFlowCyt-EV). However, the framework contains limited background information. Therefore, the goal of this compendium is to provide the background information necessary to design and conduct reproducible EV FCM experiments. This compendium contains background information on EVs, the interaction between light and EVs, FCM hardware, experimental design and preanalytical procedures, sample preparation, assay controls, instrument data acquisition and calibration, EV characterization, and data reporting. Although this compendium focuses on EVs, many concepts and explanations could also be applied to FCM detection of other particles within the EV size range, such as bacteria, lipoprotein particles, milk fat globules, and viruses.

Connexins and Glucose Metabolism in Cancer.

Connexins are a family of transmembrane proteins that regulate diverse cellular functions. Originally characterized for their ability to mediate direct intercellular communication through the formation of highly regulated membrane channels, their functions have been extended to the exchange of molecules with the extracellular environment, and the ability to modulate numerous channel-independent effects on processes such as motility and survival. Notably, connexins have been implicated in cancer biology for their context-dependent roles that can both promote or suppress cancer cell function. Moreover, connexins are able to mediate many aspects of cellular metabolism including the intercellular coupling of nutrients and signaling molecules. During cancer progression, changes to substrate utilization occur to support energy production and biomass accumulation. This results in metabolic plasticity that promotes cell survival and proliferation, and can impact therapeutic resistance. Significant progress has been made in our understanding of connexin and cancer biology, however, delineating the roles these multi-faceted proteins play in metabolic adaptation of cancer cells is just beginning. Glucose represents a major carbon substrate for energy production, nucleotide synthesis, carbohydrate modifications and generation of biosynthetic intermediates. While cancer cells often exhibit a dependence on glycolytic metabolism for survival, cellular reprogramming of metabolic pathways is common when blood perfusion is limited in growing tumors. These metabolic changes drive aggressive phenotypes through the acquisition of functional traits. Connections between glucose metabolism and connexin function in cancer cells and the surrounding stroma are now apparent, however much remains to be discovered regarding these relationships. This review discusses the existing evidence in this area and highlights directions for continued investigation.

Phase 2 of extracellular RNA communication consortium charts next-generation approaches for extracellular RNA research.

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

Analytical Considerations of Large-Scale Aptamer-Based Datasets for Translational Applications.

The development and advancement of aptamer technology has opened a new realm of possibilities for unlocking the biocomplexity available within proteomics. With ultra-high-throughput and multiplexing, alongside remarkable specificity and sensitivity, aptamers could represent a powerful tool in disease-specific research, such as supporting the discovery and validation of clinically relevant biomarkers. One of the fundamental challenges underlying past and current proteomic technology has been the difficulty of translating proteomic datasets into standards of practice. Aptamers provide the capacity to generate single panels that span over 7000 different proteins from a singular sample. However, as a recent technology, they also present unique challenges, as the field of translational aptamer-based proteomics still lacks a standardizing methodology for analyzing these large datasets and the novel considerations that must be made in response to the differentiation amongst current proteomic platforms and aptamers. We address these analytical considerations with respect to surveying initial data, deploying proper statistical methodologies to identify differential protein expressions, and applying datasets to discover multimarker and pathway-level findings. Additionally, we present aptamer datasets within the multi-omics landscape by exploring the intersectionality of aptamer-based proteomics amongst genomics, transcriptomics, and metabolomics, alongside pre-existing proteomic platforms. Understanding the broader applications of aptamer datasets will substantially enhance current efforts to generate translatable findings for the clinic.

MPAPASS software enables stitched multiplex, multidimensional EV repertoire analysis and a standard framework for reporting bead-based assays.

Extracellular vesicles (EVs) of various types are released or shed from all cells. EVs carry proteins and contain additional protein and nucleic acid cargo that relates to their biogenesis and cell of origin. EV cargo in liquid biopsies is of widespread interest owing to its ability to provide a retrospective snapshot of cell state at the time of EV release. For the purposes of EV cargo analysis and repertoire profiling, multiplex assays are an essential tool in multiparametric analyte studies but are still being developed for high-parameter EV protein detection. Although bead-based EV multiplex analyses offer EV profiling capabilities with conventional flow cytometers, the utilization of EV multiplex assays has been limited by the lack of software analysis tools for such assays. To facilitate robust EV repertoire studies, we developed multiplex analysis post-acquisition analysis (MPAPASS) open-source software for stitched multiplex analysis, EV database-compatible reporting, and visualization of EV repertoires.

EV Translational Horizons as Viewed Across the Complex Landscape of Liquid Biopsies.

Extracellular Vesicle (EV)-based diagnostic and therapeutic tools are an area of intensive study and substantial promise, but EVs as liquid biopsies have advanced years ahead of EVs as therapeutic tools. EVs are emerging as a promising approach for detecting tumors, evaluating the molecular profiles of known disease, and monitoring treatment responses. Although correlative assays based on liquid biopsies are already having an impact on translational studies and clinical practice, much remains to be learned before these assays will be optimized for clinical correlations, functional biological studies, and therapeutic use. What follows is an overview of current evidence supporting the investigation and use of liquid biopsies, organized by specific liquid biopsy components available for analysis, along with a summary of what challenges must be overcome before these assays will provide functional biological insights into the pathogenesis and treatment of disease. The same challenges must also be overcome before it will be feasible to measure and monitor the dosing, distribution, pharmacokinetics, and delivery of EV therapeutics and their cargo in complex biofluids where EVs and circulate with and are co-isolated with a number of other nanoscale materials, including lipoproteins (LPPs), ribonucleoprotein complexes (RNPs), and cell free nucleic acids (cfNA).

A simple, high-throughput method of protein and label removal from extracellular vesicle samples.

Evidence continues to increase of the clinical utility extracellular vesicles (EVs) as translational biomarkers. While a wide variety of EV isolation and purification methods have been implemented, few techniques are high-throughput and scalable for removing excess fluorescent reagents (e.g. dyes, antibodies). EVs are too small to be recovered from routine cell-processing procedures, such as filtration or centrifugation. The lack of suitable methods for removing unbound labels, especially in optical assays, is a major roadblock to accurate EV phenotyping and utilization of EV assays in a translational or clinical setting. Therefore, we developed a method for using a multi-modal resin, referred to as EV-Clean, to remove unbound labels from EV samples, and we demonstrate improvement in flow cytometric EV analysis with the use of this EV-Clean method.

Glucose-limiting conditions induce an invasive population of MDA-MB-231 breast cancer cells with increased connexin 43 expression and membrane localization.

Gap junctional intercellular communication (GJIC) is a homeostatic process mediated by membrane channels composed of a protein family known as connexins. Alterations to channel activity can modulate suppression or facilitation of cancer progression. These varying roles are influenced by the cancer cell genetic profile and the context-dependent mechanisms of a dynamic extracellular environment that encompasses fluctuations to nutrient availability. To better explore the effects of altered cellular metabolism on GJIC in breast cancer, we generated a derivative of the triple-negative breast cancer cell line MDA-MB-231 optimized for growth in low-glucose. Reduced availability of glucose is commonly encountered during tumor development and leads to metabolic reprogramming in cancer cells. MDA-MB-231 low-glucose adapted cells exhibited a larger size with improved cell-cell contact and upregulation of cadherin-11. Additionally, increased protein levels of connexin 43 and greater plasma membrane localization were observed with a corresponding improvement in GJIC activity compared to the parental cell line. Since GJIC has been shown to affect cellular invasion in multiple cancer cell types, we evaluated the invasive qualities of these cells using multiple three-dimensional Matrigel growth models. Results of these experiments demonstrated a significantly more invasive phenotype. Moreover, a decrease in invasion was noted when GJIC was inhibited. Our results indicate a potential response of triple-negative breast cancer cells to reduced glucose availability that results in changes to GJIC and invasiveness. Delineation of this relationship may help elucidate mechanisms by which altered cancer cell metabolism affects GJIC and how cancer cells respond to nutrient availability in this regard.

Genome-wide methylation profiling of glioblastoma cell-derived extracellular vesicle DNA allows tumor classification.

BACKGROUND: Genome-wide DNA methylation profiling has recently been developed into a tool that allows tumor classification in central nervous system tumors. Extracellular vesicles (EVs) are released by tumor cells and contain high molecular weight DNA, rendering EVs a potential biomarker source to identify tumor subgroups, stratify patients and monitor therapy by liquid biopsy. We investigated whether the DNA in glioblastoma cell-derived EVs reflects genome-wide tumor methylation and mutational profiles and allows noninvasive tumor subtype classification. METHODS: DNA was isolated from EVs secreted by glioblastoma cells as well as from matching cultured cells and tumors. EV-DNA was localized and quantified by direct stochastic optical reconstruction microscopy. Methylation and copy number profiling was performed using 850k arrays. Mutations were identified by targeted gene panel sequencing. Proteins were differentially quantified by mass spectrometric proteomics. RESULTS: Genome-wide methylation profiling of glioblastoma-derived EVs correctly identified the methylation class of the parental cells and original tumors, including the MGMT promoter methylation status. Tumor-specific mutations and copy number variations (CNV) were detected in EV-DNA with high accuracy. Different EV isolation techniques did not affect the methylation profiling and CNV results. DNA was present inside EVs and on the EV surface. Proteome analysis did not allow specific tumor identification or classification but identified tumor-associated proteins that could potentially be useful for enriching tumor-derived circulating EVs from biofluids. CONCLUSIONS: This study provides proof of principle that EV-DNA reflects the genome-wide methylation, CNV, and mutational status of glioblastoma cells and enables their molecular classification.

Detection and Sorting of Extracellular Vesicles and Viruses Using nanoFACS.

Extracellular vesicles (EVs) are sub-micron-sized membranous spheres secreted by cells. EVs play a functional role as intercellular communicators and are associated with a number of diseases. Research into EVs is an area of growing interest due their many potential uses as therapeutic agents, as diagnostic and theranostic biomarkers, and as regulators of cellular biology. Flow cytometry is a popular method for enumerating and phenotyping EVs, even though the majority of EVs are below the detection sensitivity of most commercially available flow cytometers. Here, we present optimized protocols for EV labeling that increase the signal-to-noise ratio of EVs by removing residual antibody. Protocols for alignment of high-resolution jet-in-air flow cytometers are also provided. Published 2020. U.S. Government. Basic Protocol 1: Bulk EV staining with CFSE protein binding dye Basic Protocol 2: Antigen-specific staining of EV markers with fluorochrome-conjugated antibodies Basic Protocol 3: Astrios EQ instrument setup and sample acquisition Basic Protocol 4: Counting particles and EVs on Astrios EQ with spike-in reference beads.