There is a growing experience demonstrating benefit of mesenchymal stromal cell (MSC)-based cell therapies in preclinical models of asthma. In the current study, conditioned media (CM) and, in particular, the extracellular vesicle fraction obtained from the CM were as potent as the MSCs themselves in mitigating Th2/Th17-mediated allergic airway inflammation in a mouse model of severe refractory clinical asthma. Moreover, human MSC CM and extracellular vesicles were effective in this immunocompetent mouse model. These data add to a growing scientific basis for initiating clinical trials of MSCs or extracellular vesicles derived from MSCs in severe refractory asthma and provide further insight into the mechanisms by which the MSCs may ameliorate the asthma.

Growing interest in extracellular vesicles (EV) has necessitated development of protocols to improve EV characterization as a precursor for myriad downstream investigations. Identifying expression of EV surface epitopes can aid in determining EV enrichment and allow for comparisons of sample phenotypes. This study was designed to test a rigorous method of indirect fluorescent immunolabeling of single EV with subsequent evaluation using nanoparticle tracking analysis (NTA) to simultaneously determine EV concentration, particle size distribution, and surface immunophenotype. In this study, EV were isolated from canine and human cell cultures for immunolabeling and characterized using NTA, transmission electron microscopy, and Western blotting. Indirect fluorescent immunolabeling utilizing quantum dots (Qd) resulted in reproducible detection of individual fluorescently labeled EV using NTA. Methods were proposed to evaluate the success of immunolabeling based on paired particle detection in NTA light scatter and fluorescent modes. Bead-assisted depletion and size-exclusion chromatography improved specificity of Qd labeling. The described method for indirect immunolabeling of EV and single vesicle detection using NTA offers an improved method for estimating the fraction of EV that express a specific epitope, while approximating population size distribution and concentration.

Myxomatous mitral valve disease (MMVD) is functionally and histologically identical to mitral valve prolapse (MVP) in humans. Currently, there are no medical treatments that can delay the progression of this valvular disease or associated cardiac remodelling. Therefore, there is a need to understand the molecular pathology associated with MMVD and MVP better, and thus identify potential therapeutic targets. Circulating exosomes contain small RNA, including miRNA, which reflect cell physiology and pathology. This study explored the association between circulating exosomal miRNA (ex-miRNA) content and MMVD, heart failure due to MMVD (MMVD-CHF) and ageing, which is strongly associated with MMVD. Ex-miRNA was isolated from old normal/healthy dogs (n = 6), young normal dogs (n = 7), dogs with MMVD (n = 7) and dogs with MMVD-CHF (n = 7). Separately, total plasma miRNA was isolated from normal dogs (n = 8), dogs with MMVD (n = 8) and dogs with MMVD-CHF (n = 11). Using reverse transcription quantitative polymerase chain reaction, exosomal miR-181c (p = 0.003) and miR-495 (p = 0.0001) significantly increased in dogs with MMVD-CHF compared to the other three groups. Exosomal miR-9 (p = 0.002) increased in dogs with MMVD and MMVD-CHF compared to age-matched (old) normal dogs. Exosomal miR-599 (p = 0.002) decreased in dogs with MMVD compared to old normal dogs. In total plasma, 58 miRNA were deemed significantly different (p < 0.04) between normal dogs, dogs with MMVD and dogs with MMVD-CHF. However, in contrast to ex-miRNA, none of the miRNA in total plasma remained statistically significant if the false discovery rate was <15%. Changes in ex-miRNA are observed in dogs as they age (miR-9, miR-495 and miR-599), develop MMVD (miR-9 and miR-599) and progress from MMVD to CHF (miR-181c and miR-495). Ex-miRNA expression-level changes appear to be more specific to disease states than total plasma miRNA.RESPONSIBLE EDITOR Elena Aikawa, Harvard Medical School, USA

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