Graphical AbstractHighlights d exRNA sequencing complexity and reproducibility varies across isolation methods d Deconvolution shows differential access to exRNA carriers by different methods d Performance of exRNA isolation methods vary across biofluids and RNA species d miRDaR enables customized selection of optimal exRNA isolation methods SUMMARYPoor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and highdensity lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and repro-ducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

Exosomes, which are membranous nanovesicles, are actively released by cells and have been attributed to roles in cell-cell communication, cancer metastasis, and early disease diagnostics. The small size (30–100 nm) along with low refractive index contrast of exosomes makes direct characterization and phenotypical classification very difficult. In this work we present a method based on Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS) that allows multiplexed phenotyping and digital counting of various populations of individual exosomes (>50 nm) captured on a microarray-based solid phase chip. We demonstrate these characterization concepts using purified exosomes from a HEK 293 cell culture. As a demonstration of clinical utility, we characterize exosomes directly from human cerebrospinal fluid (hCSF). Our interferometric imaging method could capture, from a very small hCSF volume (20 uL), nanoparticles that have a size compatible with exosomes, using antibodies directed against tetraspanins. With this unprecedented capability, we foresee revolutionary implications in the clinical field with improvements in diagnosis and stratification of patients affected by different disorders.

Rapid, chip-scale, and cost-effective single particle detection of biological agents is of great importance to human health and national security. We report real-time, high-throughput detection and sizing of individual, low-index polystyrene nanoparticles and H1N1 virus. Our widefield, common path interferometer detects nanoparticles and viruses over a very large sensing area, orders of magnitude larger than competing techniques. We demonstrate nanoparticle detection and sizing down to 70 nm in diameter. We clearly size discriminate nanoparticles with diameters of 70, 100, 150, and 200 nm. We also demonstrate detection and size characterization of hundreds of individual H1N1 viruses in a single experiment.

Extracellular vesicles (EVs) including plasma membrane–derived microvesicles and endosomal-derived exosomes aggregate by unknown mechanisms, forming microcalcifications that promote cardiovascular disease, the leading cause of death worldwide. Here, we show a framework for assessing cell-independent EV mechanisms in disease by suggesting that annexin A1 (ANXA1)–dependent tethering induces EV aggregation and microcalcification. We present single-EV microarray, a method to distinguish microvesicles from exosomes and assess heterogeneity at a single-EV level. Single-EV microarray and proteomics revealed increased ANXA1 primarily on aggregating and calcifying microvesicles. ANXA1 vesicle aggregation was suppressed by calcium chelation, altering pH, or ANXA1 neutralizing antibody. ANXA1 knockdown attenuated EV aggregation and microcalcification formation in human cardiovascular cells and acellular three-dimensional collagen hydrogels. Our findings explain why microcalcifications are more prone to form in vulnerable regions of plaque, regulating critical cardiovascular pathology, and likely extend to other EV-associated diseases, including autoimmune and neurodegenerative diseases and cancer.

Rapid, sensitive, and direct label-free capture and characterization of nanoparticles from complex media such as blood or serum will broadly impact medicine and the life sciences. We demonstrate identification of virus particles in complex samples for replication-competent wild-type vesicular stomatitis virus (VSV), defective VSV, and Ebola- and Marburg-pseudotyped VSV with high sensitivity and specificity. Size discrimination of the imaged nanoparticles (virions) allows differentiation between modified viruses having different genome lengths and facilitates a reduction in the counting of non-specifically bound particles to achieve a limit-of-detection (LOD) of 5×103 pfu/mL for the Ebola and Marburg VSV pseudotypes. We demonstrate the simultaneous detection of multiple viruses in a single sample (composed of serum or whole blood) for screening applications and uncompromised detection capabilities in samples contaminated with high levels of bacteria. By employing affinity-based capture, size discrimination, and a “digital” detection scheme to count single virus particles, we show that a robust and sensitive virus/nanoparticle sensing assay can been established for targets in complex samples. The nanoparticle microscopy system is termed the Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS) and is capable of high-throughput and rapid sizing of large numbers of biological nanoparticles on an antibody microarray for research and diagnostic applications.

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Extracellular Vesicles (EVs) have been intensively explored for therapeutic delivery of proteins. However, methods to quantify cargo proteins loaded into engineered EVs are lacking. Here, we describe a workflow for EV analysis at the single‐vesicle and single‐molecule level to accurately quantify the efficiency of different EV‐sorting proteins in promoting cargo loading into EVs. Expi293F cells were engineered to express EV‐sorting proteins fused to green fluorescent protein (GFP). High levels of GFP loading into secreted EVs was confirmed by Western blotting for specific EV‐sorting domains, but quantitative single‐vesicle analysis by Nanoflow cytometry detected GFP in less than half of the particles analysed, reflecting EV heterogeneity. Anti‐tetraspanin EV immunostaining in ExoView confirmed a heterogeneous GFP distribution in distinct subpopulations of CD63 + , CD81 + , or CD9 + EVs. Loading of GFP into individual vesicles was quantified by Single‐Molecule Localization Microscopy. The combined results demonstrated TSPAN14, CD63 and CD63/CD81 fused to the PDGFRβ transmembrane domain as the most efficient EV‐sorting proteins, accumulating on average 50–170 single GFP molecules per vesicle. In conclusion, we validated a set of complementary techniques suitable for high‐resolution analysis of EV preparations that reliably capture their heterogeneity, and propose highly efficient EV‐sorting proteins to be used in EV engineering applications.