Exosome RNA Exosome RNA Research & Industry News
Extracellular vesicles (EVs) are small cell bubbles that play a crucial role in how our cells communicate. A recent study published in Science Advances has revealed some fascinating insights into these tiny messengers and their potential in healthcare.
Researchers wanted to understand how cells respond to these extracellular vesicles (EVs) produced by different cell types and in different concentrations.
Research into extracellular vesicles (EV) is relatively new. Researchers previously believed that high concentrations of EVs were necessary for an impact. But this study shows that even a small number of EVs can make a big difference by transferring important information and instructions between cells and revolutionizing the way we use EVs for treatments.
Understanding how EVs communicate between cells gives us a better grasp of how our bodies work on a microscopic level. It’s like learning the secret language that cells use to chat, says the study’s first author Daniel Hagey , a research specialist in the Department of Laboratory Medicine.
Next step
Now we plan to work with better techniques to separate EVs from other things floating around our cells. This will make EV research even more precise, continues Daniel Hagey.
We also want to test different types of EVs on different cell types. This can help reveal more profound ways in which cells communicate, reflecting the complex relationships of our bodies. Essentially, this study reveals the hidden world of EVs and their crucial role in cell communication. It could pave the way for exciting advances in healthcare and our understanding of how our bodies work.
Source – Karolinska Institute
Extracellular vesicles (EVs) have been established to play important roles in cell-cell communication and shown promise as therapeutic agents. However, we still lack a basic understanding of how cells respond upon exposure to EVs from different cell sources at various doses. Thus, Karolinska Institute researchers treated fibroblasts with EVs from 12 different cell sources at doses between 20 and 200,000 per cell, analyzed their transcriptional effects, and functionally confirmed the findings in various cell types in vitro, and in vivo using single-cell RNA sequencing. Unbiased global analysis revealed EV dose to have a more significant effect than cell source, such that high doses down-regulated exocytosis and up-regulated lysosomal activity. However, EV cell source-specific responses were observed at low doses, and these reflected the activities of the EV’s source cells. Last, the researchers assessed EV-derived transcript abundance and found that immune cell-derived EVs were most associated with recipient cells. Together, this study provides important insights into the cellular response to EVs.
EVs produce transcriptional responses reflective of their cell source
(A) tSNE-NN map of control and 20 EV per cell treated fibroblast transcriptomes colored by the cell source group of the EVs they were treated with or by their Infomap cluster. (B) Overlap enrichment scores between samples’ Infomap cluster identity and the EV cell type group they were treated with. (C) Numbers of genes significantly up- or down-regulated by each type of EV at more than one dose and their cell source group. (D) Gene ontology term fold enrichment for genes robustly up-regulated in fibroblasts by each of the EV types, colored on the basis of their cell source group and ordered according to (C). P values for statistically significant terms are inset and negative values without fold change listed show no enrichment. (E) Bright-field images of HUVEC cells during the invasion assay. Scale bars, 100 μm. (F) Quantification of the number of branches formed by HUVEC cells exposed to EVs from different cell sources (n = 14 to 17). (G) Quantification of cell proliferation in HUVEC cells exposed the EVs from different cell sources (n = 8). Sample mean is shown as a large solid dot, SE as a horizontal line, and individual data points as rings, with statistics performed as two-tailed, unpaired t tests.
