Vesicle transport is a fundamental mechanism of communication in the CNS. In this study we characterized a novel type of vesicle released by murine brain microglial cells: microglial exosomes. Analysis of their protein content identified several enzymes, chaperones, tetraspanins, and membrane receptors previously reported in B cells and dendritic cell-derived exosomes. Additionally, microglia-derived exosomes expressed the aminopeptidase CD13 and the lactate transporter MCT-1. Exosomal CD13 was metabolically active in cleaving leucine- and methionine-enkephalins peptides by releasing the N-terminal tyrosine. Cleaved neuropeptides were unable to bind to the neuronal opioid receptor as assessed by cAMP response. Microglial exosomal vesicles may represent an important, previously unrecognized, cellular communication system in an organ in which cell motility is highly restricted.

Exosomes shed by tumor cells have been recognized as promising biomarkers for cancer diagnostics due to their unique composition and functions. Quantification of low concentrations of specific exosomes present in very small volumes of clinical samples may be used for noninvasive cancer diagnosis and prognosis. We developed an immunosorbent assay for digital qualification of target exosomes using droplet microfluidics. The exosomes were immobilized on magnetic microbeads through sandwich ELISA complexes tagged with an enzymatic reporter that produces a fluorescent signal. The constructed beads were further isolated and encapsulated into a sufficient number of droplets to ensure only a single bead was encapsulated in a droplet. Our droplet-based single-exosome-counting enzyme-linked immunoassay (droplet digital ExoELISA) approach enables absolute counting of cancer-specific exosomes to achieve unprecedented accuracy. We were able to achieve a limit of detection (LOD) down to 10 enzyme-labeled exosome complexes per microliter (∼10 M). We demonstrated the application of the droplet digital ExoELISA platform in quantitative detection of exosomes in plasma samples directly from breast cancer patients. We believe our approach may have the potential for early diagnosis of cancer and accelerate the discovery of cancer exosomal biomarkers for clinical diagnosis.

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