Nanoparticle tracking analysis characterizes microvesicles as potential biomarkers
Researchers at the University of Colorado at Boulder have applied nanoparticle tracking analysis (NTA) to characterizing microvesicles (a biological nanoparticle) as potential biomarkers of tumor progression and cancer metastasis.
Researchers at the University of Colorado at Boulder (Boulder, CO) have applied nanoparticle tracking analysis (NTA) to characterizing microvesicles (a biological nanoparticle) as potential biomarkers of tumor progression and cancer metastasis.
Led by Professor Hang (Hubert) Yin, whose lab focuses on structure-based drug design, cell signaling, biochemistry, biotechnology development, and membrane protein simulations, the research team's goal is to identify and design peptides that sense membrane curvature to better understand protein/peptide-lipid interactions and potentially create noninvasive probes to detect highly curved extracellular vesicles. These nanoparticles are shed into bodily fluids targeting other cells in the body and are vital for intercellular communication.
Their experimental protocol involves lipid vesicle preparation by pressure-controlled extrusion through different membrane pore sizes. Different lipid vesicle sizes are prepared in order to mimic the size range of the microvesicles that are shed into the extracellular matrix. Following vesicle extrusion, it is important to validate the vesicle size. By using Nanoparticle Tracking Analysis (NTA) technology (NanoSight; Salisbury, England), the results provide an accurate quantification of different populations of vesicle sizes present in the sample.
Prior to NTA, the group mostly used dynamic light scattering (DLS) to determine the sizes of their synthetic lipid vesicles. NTA enabled detection ranges from 10 to 2000 nm for vesicle sizes, which covered their liposome size of interest, explains Yin. And flow cytometry has a lower limit detection of ~200 nm to accurately measure particle sizes, which did not meet their lower requirement, while DLS measures the average size of all the particles present in the sample rather than accurately distinguish different pools of vesicle sizes, often creating a bias towards larger particles, he says.
The team's work appears in the Journal of Visualized Experiments; for more information, please visit http://www.jove.com/video/4151/constant-pressure-controlled-extrusion-method-for-the-preparation-of-nano-sized-lipid-vesicles.
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