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Extracellular vesicles (EVs) are a heterogeneous ensemble of membrane bodies released by all cell types into their environment. Initially dismissed as cell debris, they have since been shown to play a central role in intercellular communication. Specifically, the proteins expressed at the surface of exosomes —EVs sized between 30 and 100 nm—have been identified as biomolecular zip codes and biomarkers. Exosome protein expression and cargo have been probed using various technologies—from mass spectrometry to integrated microfluidic chips—and shown to be linked to the pathogenesis and progression of several conditions, from cancer to neurodegenerative diseases. Antibody microarrays are a powerful and high-throughput technology that has been adapted to multiplexed EV protein expression analysis. However, the microarray platform and its protocol need to be characterized and optimized specially for exosome protein analysis to ensure data quality and reliability. In this work, we optimized an antibody microarray to capture exosomes and probe the membrane protein content of cancer-cell derived exosomes with high intensity and reproducibility. We separately optimized the (i) capture and (ii) detection of exosomes from CD63-GFP-expressing A431 epidermoid carcinoma cells, and combined them into an optimal exosome capture and detection microarray protocol. Microarrays of IgGs targeting exosome protein markers were inkjet-spotted using 29 different printing buffers and successively incubated with exosomes and detection antibodies. Different combinations of capture and detection antibodies targeting surface proteins CD63, CD9, CD81 and EGFR were tested and the fluorescence intensity and coefficient of variation of the intrinsic GFP and detection antibody compared based on the printing buffer used and the proteins targeted. Using the optimized assay protocol, 4 different cancer cell lines were profiled for 15 targets, including exosome marker CD63; integrins αVβ5, α2, α6, β1, and β4; receptors EGFR, CCR5, and PD-1; and transmembrane proteins ADAM10, EpCAM, PD-L1, CD44, CD82 and CD133. Our proposed antibody microarray platform, termed ExAM (Exosome Antibody Microarray), which we showed can phenotype vesicles with strong signal intensity and high reproducibility, may be useful in analyzing exosomes in the context of disease diagnosis and treatment.

Background: The heterogeneity of extracellular vesicles (EVs) requires new tools to characterize subpopulations and elucidate the effects and mechanisms by which they shape cellular processes. Recently, significant progress has been achieved in flow cytometry and fluorescence microscopy for high-throughput analysis of high-abundance markers in single EVs but none have yet been validated for single proteins on single vesicles. Here, we identify exosome-like extracellular vesicle (ELEV) subpopulations from breast cancer cell lines enriched on nanoarrays with single-ELEV resolution and single-molecule sensitivity. Methods: A nanoarray of anti-mouse IgGs was printed onto a glass slide using lift-off nanocontact printing, and the surface was passivated before incubation with mouse monoclonal capture antibodies. The nanoarray consists of 100 nm capture spots spaced 2 m apart that capture single ELEVs by virtue of their small size. ELEV samples, purified from cell supernatant using size exclusion columns, were incubated on the nanoarray overnight and detected using fluorescently tagged detection antibodies. Results: Single ELEV capture was demonstrated on the nanoarray using AFM correlated with fluorescence microscopy. ELEVs could by detected with a single antibody as shown by single molecule photobleaching traces. Known exosome markers, integrins and general cancer markers were probed on exosomes derived from breast cancer cell lines, defining initial subpopulations. Summary/Conclusion: The heterogeneity of EVs calls for methods that can measure single vesicles to allow for an accurate description of vesicle composition. With the nanoarray's ability to enrich single ELEVs of interest in a high-throughput manner, ELEV subpopulations with unique co-expression patterns can now be studied for their distinct effects.

Background: Knowledge of the protein content of exosome-like extracellular vesicles (ELEVs) can be leveraged for profiling and identification of biomarkers. While transmembrane protein studies are often performed on whole ELEVs, most current methods, such as ELISA, employ lysis when looking at exosome intravesicular proteins. Here, we propose a microarray-based, minimally disruptive method that allows vesicles with specific markers to be enriched on microarray spots and probed for intravesicular proteins, making it straightforward to correlate extravesicular and intravesicular markers. Methods: IgGs targeting known transmembrane exosome markers (i.e. CD63, CD9, CD81) were inkjet-printed on an aldehyde-functionalized glass slide in a microarray format. The slide was passivated with BSA and incubated overnight with size exclusion chromatography-purified ELEV samples from CD63-GFP-expressing A431 cells. After washing, the captured vesicles were fixed and permeabilized, and intravesicular proteins were detected using oligonucleotide-conjugated IgGs. Padlock probe-based rolling circle amplification and hybridization with fluorescently labelled probes was performed, followed by imaging using a fluorescent microarray scanner. Results: The intravesicular GFP tag was detected in proof-of-concept experiments to validate the proposed method. The GFP detection signal of vesicles captured on antibody spots was quantified and compared with the direct GFP signal. Seven capture combinations involving antibodies against CD63, CD9 and CD81 were thus tested, and a clear correlation was shown between the GFP fluorescence and the amplified fluorescent detection signal. Summary/conclusion: The intravesicular GFP tag of A431-GFP ELEVs was quantified and compared to known transmembrane markers with a method enabling signal amplification and minimal disruption. This new approach has the potential to open the way to more efficient detection of internal targets in ELEV biomarker research.

Proteins are found both outside and inside of extracellular vesicles (EVs) and govern the properties and functions of EVs, while also constituting a signature of the cell of origin and of biological function and disease. Outer proteins on EVs can be directly bound by antibodies to either enrich EVs, or probe the expression of a protein on EVs, including in a combinatorial manner. However, co-profiling of inner proteins remains challenging. Here, we present the high-throughput, multiplexed analysis of extracellular vesicle inner and outer proteins (EVPio). We describe the optimization of fixation and heat-induced protein epitope retrieval for EVs, along with oligo-barcoded antibodies and branched DNA signal amplification for sensitive, multiplexed and high-throughput assays. We captured 4 subpopulations of EVs from colorectal cancer cell lines HT29 and SW403 based on EpCAM, CD9, CD63 and CD81 expression, and quantified the co-expression of 8 outer (integrins and tetraspanins) and 4 inner (heat shock, endosomal and inner leaflet) proteins. The differences in co-expression patterns were consistent with the literature and known biological function. In conclusion, EVPio analysis can simultaneously detect multiple inner and outer proteins in EVs immobilized on a surface, opening the way to extensive combinatorial protein profiles for both discovery and clinical translation.

Extracellular vesicles (EVs) are nanometric lipid vesicles that shuttle cargo between cells. Their analysis could shed light on health and disease conditions, but EVs must first be preserved, extracted and often pre-concentrated. Here we firstly compare plasma preservation agents, and secondly, using both plasma and cell supernatant, four EV-extraction methods including (i) ultracen-trifugation (UC), (ii) size exclusion chromatography (SEC), (iii) centrifugal filtration (LoDF), and (iv) accousto-sorting (AcS). We benchmarked them by characterizing integrity, size-distribution, concentration, purity and the expression profiles for nine proteins of EVs, as well as overall throughput, time-to-result and cost. We found that the difference between EDTA and citrate anticoagulants vary with the extraction method. In our hands, ultracentrifugation produced a high yield of EVs with low contamination; SEC is low-cost, fast, and easy to implement, but the purity of EVs is lower; LoDF and AcS are both compatible with process automation, small volume requirement, and rapid processing times. When using plasma, the LoDF was susceptible to clogging and sample contamination, while the AcS featured high purity but a lower yield of extraction. Analysis of protein profiles suggest that extraction methods extract different sub-population of EVs. Our study highlights the strength and weakness of sample preprocessing methods, and the variability in concentration, purity, and EV expression profiles of the extracted EVs. Pre-analytical parameters such as collection or pre-processing protocols must be considered as part of the entire process in order to address EV diversity and their use as clinically actionable indicators.

Extracellular Vesicles (EVs) carry cell-derived proteins that confer functionality and selective cell uptake. However, whether proteins are packaged stochastically or co-enriched within individual EVs, and whether co-enrichment fluctuates under homeostasis and disease, has not been measured. EV abundance and protein global relative expression have been qualified by bulk analysis. Meanwhile, co-enrichment is not directly accessible via bulk measurement and has not been reported for single EV analysis. Here, we introduce the normalized index of co-enrichment (NICE) to measure protein co-enrichment. NICE was derived by (i) capturing EVs based on the expression of a membrane-bound protein, (ii) probing for the co-expression of a second protein at the population level - EV integrity underwrites the detection of single EV co-expression without the need to resolve single EVs - and (iii) normalizing measured values using two universal normalization probes. Axiomatically, NICE = 1 for stochastic inclusion or no overall co-enrichment, while for positive and negative co-enrichment NICE > 1 or < 1, respectively. We quantified the NICE of tetraspanins, growth factor receptors and integrins in EVs of eight breast cancer cell lines of varying metastatic potential and organotropism, combinatorially mapping up to 104 protein pairs. Our analysis revealed protein enrichment and co-expression patterns consistent with previous findings. For the organotropic cell lines, most protein pairs were co-enriched on EVs, with the majority of NICE values between 0.2 to 11.5, and extending from 0.037 to 80.4. Median NICE were either negative, neutral or positive depending on the cells. NICE analysis is easily multiplexed and is compatible with microarrays, bead-based and single EV assays. Additional studies are needed to deepen our understanding of the potential and significance of NICE for research and clinical uses.

This work combines a particle injection system with our proposed magnetic resonance navigation (MRN) sequence with the intention of validating MRN in a two-bifurcation phantom for endovascular treatment of hepatocellular carcinoma (HCC). A theoretical physical model used to calculate the most appropriate size of the magnetic drug-eluting bead (MDEB, 200 μm) aggregates was proposed. The aggregates were injected into the phantom by a dedicated particle injector while a trigger signal was automatically sent to the MRI to start MRN which consists of interleaved tracking and steering sequences. When the main branch of the phantom was parallel to B0, the aggregate distribution ratio in the (left–left, left–right, right–left and right–right divisions was obtained with results of 8, 68, 24 and 0% respectively at baseline (no MRN) and increased to 84%, 100, 84 and 92% (p < 0.001, p = 0.004, p < 0.001, p < 0.001) after implementing our MRN protocol. When the main branch was perpendicular to B0, the right-left branch, having the smallest baseline distribution rate of 0%, reached 80% (p < 0.001) after applying MRN. Moreover, the success rate of MRN was always more than 92% at the 1st bifurcation in the experiments above.

Plasma levels of fungal antigen (1→3)-β-D-Glucan are elevated during early and chronic human immunodeficiency virus (HIV) infection and do not normalize despite long-term antiretroviral therapy. Such elevation is associated with immune activation in a well-defined cohort of untreated and treated people living with HIV. Abstract Background Microbial translocation from the gut to systemic circulation contributes to immune activation during human immunodeficiency virus (HIV) infection and is usually assessed by measuring plasma levels of bacterial lipopolysaccharide (LPS). Fungal colonization in the gut increases during HIV-infection and people living with HIV (PLWH) have increased plasma levels of fungal polysaccharide (1→3)-β-D-Glucan (βDG). We assessed the contribution of circulating DG to systemic immune activation in PLWH. Methods Cross-sectional and longitudinal assessments of plasma βDG levels were conducted along with markers of HIV disease progression, epithelial gut damage, bacterial translocation, proinflammatory cytokines, and βDG-specific receptor expression on monocytes and natural killer (NK) cells. Results Plasma βDG levels were elevated during early and chronic HIV infection and persisted despite long-term antiretroviral therapy (ART). βDG increased over 24 months without ART but remained unchanged after 24 months of treatment. βDG correlated negatively with CD4 T-cell count and positively with time to ART initiation, viral load, intestinal fatty acid–binding protein, LPS, and soluble LPS receptor soluble CD14 (sCD14). Elevated βDG correlated positively with indoleamine-2,3-dioxygenase-1 enzyme activity, regulatory T-cell frequency, activated CD38+Human Leukocyte Antigen - DR isotype (HLA-DR)+ CD4 and CD8 T cells and negatively with Dectin-1 and NKp30 expression on monocytes and NK cells, respectively. Conclusions PLWH have elevated plasma βDG in correlation with markers of disease progression, gut damage, bacterial translocation, and inflammation. Early ART initiation prevents further βDG increase. This fungal antigen contributes to immune activation and represents a potential therapeutic target to prevent non–acquired immunodeficiency syndrome events.