A Combined Western and Bead-Based Multiplex Platform to Characterize Extracellular Vesicles.

In regenerative medicine, extracellular vesicles (EVs) are considered as a promising cell-free approach. EVs are lipid bilayer-enclosed vesicles secreted by cells and are key players in intercellular communication. EV-based therapeutic approaches have unique advantages over the use of cell-based therapies, such as a high biological, but low immunogenic and tumorigenic potential. To analyze the purity and biochemical composition of EV preparations, the International Society for Extracellular Vesicles (ISEV) has prepared guidelines recommending the analysis of multiple (EV) markers, as well as proteins coisolated/recovered with EVs. Traditional methods for EV characterization, such as Western blotting, require a relatively high EV sample/protein input for the analysis of one protein. We here evaluate a combined Western and bead-based multiplex platform, called DigiWest, for its ability to detect simultaneously multiple EV markers in an EV-containing sample with inherent low protein input. DigiWest analysis was performed on EVs from various sources and species, including mesenchymal stromal cells, notochordal cells, and milk, from human, pig, and dog. The study established a panel of nine antibodies that can be used as cross-species for the detection of general EV markers and coisolates in accordance with the ISEV guidelines. This optimized panel facilitates the parallel evaluation of EV-containing samples, allowing for a comprehensive characterization and assessment of their purity. The total protein input for marker analysis with DigiWest was 1 µg for all nine antibodies, compared with ∼10 µg protein input required for traditional Western blotting for one antibody. These findings demonstrate the potential of the DigiWest technique for characterizing various types of EVs in the regenerative medicine field.

Surface protein profiling of milk and serum extracellular vesicles unveils body fluid-specific signatures.

Cell-derived extracellular vesicles (EVs) are currently in the limelight as potential disease biomarkers. The promise of EV-based liquid biopsy resides in the identification of specific disease-associated EV signatures. Knowing the reference EV profile of a body fluid can facilitate the identification of such disease-associated EV-biomarkers. With this aim, we purified EVs from paired human milk and serum samples and used the MACSPlex bead-based flow-cytometry assay to capture EVs on bead-bound antibodies specific for a certain surface protein, followed by EV detection by the tetraspanins CD9, CD63, and CD81. Using this approach we identified body fluid-specific EV signatures, e.g. breast epithelial cell signatures in milk EVs and platelet signatures in serum EVs, as well as body fluid-specific markers associated to immune cells and stem cells. Interestingly, comparison of pan-tetraspanin detection (simultaneous CD9, CD63 and CD81 detection) and single tetraspanin detection (detection by CD9, CD63 or CD81) also unveiled body fluid-specific tetraspanin distributions on EVs. Moreover, certain EV surface proteins were associated with a specific tetraspanin distribution, which could be indicative of the biogenesis route of this EV subset. Altogether, the identified body fluid-specific EV profiles can contribute to study EV profile deviations in these fluids during disease processes.

Adapter dimer contamination in sRNA-sequencing datasets predicts sequencing failure and batch effects and hampers extracellular vesicle-sRNA analysis.

Small RNA (sRNA) profiling of Extracellular Vesicles (EVs) by Next-Generation Sequencing (NGS) often delivers poor outcomes, independently of reagents, platforms or pipelines used, which contributes to poor reproducibility of studies. Here we analysed pre/post-sequencing quality controls (QC) to predict issues potentially biasing biological sRNA-sequencing results from purified human milk EVs, human and mouse EV-enriched plasma and human paraffin-embedded tissues. Although different RNA isolation protocols and NGS platforms were used in these experiments, all datasets had samples characterized by a marked removal of reads after pre-processing. The extent of read loss between individual samples within a dataset did not correlate with isolated RNA quantity or sequenced base quality. Rather, cDNA electropherograms revealed the presence of a constant peak whose intensity correlated with the degree of read loss and, remarkably, with the percentage of adapter dimers, which were found to be overrepresented sequences in high read-loss samples. The analysis through a QC pipeline, which allowed us to monitor quality parameters in a step-by-step manner, provided compelling evidence that adapter dimer contamination was the main factor causing batch effects. We concluded this study by summarising peer-reviewed published workflows that perform consistently well in avoiding adapter dimer contamination towards a greater likelihood of sequencing success.

Human milk extracellular vesicles target nodes in interconnected signalling pathways that enhance oral epithelial barrier function and dampen immune responses.

Maternal milk is nature's first functional food. It plays a crucial role in the development of the infant's gastrointestinal (GI) tract and the immune system. Extracellular vesicles (EVs) are a heterogeneous population of lipid bilayer enclosed vesicles released by cells for intercellular communication and are a component of milk. Recently, we discovered that human milk EVs contain a unique proteome compared to other milk components. Here, we show that physiological concentrations of milk EVs support epithelial barrier function by increasing cell migration via the p38 MAPK pathway. Additionally, milk EVs inhibit agonist-induced activation of endosomal Toll like receptors TLR3 and TLR9. Furthermore, milk EVs directly inhibit activation of CD4+ T cells by temporarily suppressing T cell activation without inducing tolerance. We show that milk EV proteins target key hotspots of signalling networks that can modulate cellular processes in various cell types of the GI tract.

Extracellular Vesicles Induce Mesenchymal Transition and Therapeutic Resistance in Glioblastomas through NF-κB/STAT3 Signaling.

Glioblastoma (GBM) is the most common primary malignant brain tumor and despite optimal treatment, long-term survival remains uncommon. GBM can be roughly divided into three different molecular subtypes, each varying in aggressiveness and treatment resistance. Recent evidence shows plasticity between these subtypes in which the proneural (PN) glioma stem-like cells (GSCs) undergo transition into the more aggressive mesenchymal (MES) subtype, leading to therapeutic resistance. Extracellular vesicles (EVs) are membranous structures secreted by nearly every cell and are shown to play a key role in GBM progression by acting as multifunctional signaling complexes. Here, it is shown that EVs derived from MES cells educate PN cells to increase stemness, invasiveness, cell proliferation, migration potential, aggressiveness, and therapeutic resistance by inducing mesenchymal transition through nuclear factor-κB/signal transducer and activator of transcription 3 signaling. The findings could potentially help explore new treatment strategies for GBM and indicate that EVs may also play a role in mesenchymal transition of different tumor types.

Glycosylated extracellular vesicles released by glioblastoma cells are decorated by CCL18 allowing for cellular uptake via chemokine receptor CCR8.

Cancer cells release extracellular vesicles (EVs) that contain functional biomolecules such as RNA and proteins. EVs are transferred to recipient cancer cells and can promote tumour progression and therapy resistance. Through RNAi screening, we identified a novel EV uptake mechanism involving a triple interaction between the chemokine receptor CCR8 on the cells, glycans exposed on EVs and the soluble ligand CCL18. This ligand acts as bridging molecule, connecting EVs to cancer cells. We show that glioblastoma EVs promote cell proliferation and resistance to the alkylating agent temozolomide (TMZ). Using in vitro and in vivo stem-like glioblastoma models, we demonstrate that EV-induced phenotypes are neutralised by a small molecule CCR8 inhibitor, R243. Interference with chemokine receptors may offer therapeutic opportunities against EV-mediated cross-talk in glioblastoma.