New Advances in Extracellular Vesicle miRNA Research Using High-Throughput Affinity Capture
In this webinar, you will learn about:
- The advantages of using vesicle-surface epitope affinity capture for enriching EVs
- How to combine EV enrichment and RNA isolation into a seamless rapid process
- How to fully automate EV enrichment and downstream analysis to achieve high-throughput sample analysis
Summary
Extracellular vesicles (EVs) are a diverse group of membrane-bound particles ranging from approximately 30 nm up to a few micrometers in diameter. These vesicles are released by cells into the extracellular space and biofluids, carrying molecular signals capable of influencing both proximal and distal cell functions. EV-associated signaling molecules include: nucleic acids; proteins; and lipids that are exposed on the vesicle surface, intercalated in the bi-lipid layer membrane or encapsulated within their lumen. When homoeostasis is challenged, acute adaptive responses may be accompanied by increased release of EVs. Consequently, EV signaling emerges as a crucial pathway for intercellular communication. Intercepting and deciphering these EV signals presents new opportunities for developing more informative, non-invasive diagnostics and effective therapeutic interventions.
The development of accurate and reliable EV-based diagnostics necessitates the identification of disease-associated biomarkers within specific EV subpopulations and the implementation of rapid, reproducible and scalable sample processing. Conventional isolation methods face challenges due to the co-isolation of particles with similar physicochemical properties. Promising alternatives involve methods targeting specific vesicle-surface epitopes, compatible with automated platforms. Join our featured speaker, Dr Greg Rice from INOVIQ, as he identifies challenges associated with translating our understanding of extracellular vesicle (EV) biology into clinically useful applications and to highlight potential solutions.
Speaker
![greg-rice-no-background-v1-125](https://scv10mr-cdnpre-p-cus-00.azureedge.net/-/media/images/resources/speaker-images/2024/greg-rice-no-background-v1-125.jpg?rev=c2a350d777c44faf95c4e0dbaaa0b641&sc_lang=en)
Greg Rice, PhD
Chief Scientific Officer
INOVIQ Limited