Quantifying murine placental extracellular vesicles across gestation and in preterm birth data with tidyNano: A...

Extracellular vesicles (EVs) are increasingly recognized as important mediators of intercellular communication that carry protein, lipids, and nucleic acids via the circulation to target cells whereupon they mediate physiological changes. In pregnancy, EVs are released in high quantities from the placenta and have been postulated to target multiple cell types, including those of the vascular and immune systems. However, most studies of pregnancy-associated EVs have used clinical samples and in vitro models; to date, few studies have taken advantage of murine models in which pregnancy can be precisely timed and manipulated. In this study, we used a murine model to determine whether the quantity of EVs is altered during healthy pregnancy and during inflammation-associated preterm birth. To facilitate data analysis, we developed a novel software package, tidyNano, an R package that provides functions to import, clean, and quickly summarize raw data generated by the nanoparticle tracking device, NanoSight (Malvern Panalytical). We also developed shinySIGHT, a Shiny web application that allows for interactive exploration and visualization of EV data. In mice, EV concentration in blood increased linearly across pregnancy, with significant rises at GD14.5 and 17.5 relative to EV concentrations in nonpregnant females. Additionally, lipopolysaccharide treatment resulted in a significant reduction in circulating EV concentrations relative to vehicle-treated controls at GD16.5 within 4 hours. Use of tidyNano facilitated rapid analysis of EV data; importantly, this package provides a straightforward framework by which diverse types of large datasets can be simply and efficiently analyzed, is freely available under the MIT license, and is hosted on GitHub (https://nguyens7.github.io/tidyNano/). Our data highlight the utility of the mouse as a model of EV biology in pregnancy, and suggest that placental dysfunction is associated with reduced circulating EVs.