Identification of Influenza Therapeutic Interfering Particles, by Geoffrey Zath, Chem & Bio Engr
- Thursday, August 9, 2018 from 10:00am to 11:00am
- Barnard Hall, 126 - view map
The influenza virus infects millions of people every year, causing over 300,000 deaths worldwide. The current form of treatment is through vaccinations of the public; however, vaccinations are a passive approach and are not able to adapt with the virus over the course of a flu season. A proposed method for dealing with a mutating virus, such as influenza, is to engineer Therapeutic Interfering Particles (TIPs) that co-evolve with the virus and outcompete for the same essential viral components within the host’s cells. The primary challenge is finding a TIP candidate that remains effective in fighting a virus over the course of an infection. We aim to use drop-based microfluidics to improve the throughput of TIP candidate identification and candidate diversity when compared to traditional bench-scale passaging methods. The encapsulation of cells and viruses into drops provides the unique ability to observe interactions at a single cell level in picoliter volumes. The decreased sample volume in drops will allow for high throughput identification of TIP candidates through fluorescent detection at kilohertz rates. TIP candidate diversity will be increased by isolating infection events within a drop, thereby decreasing competition, and increasing the potential sample size over what is possible at the bench scale (>107 drops/mL). Our plan is twofold: first, develop a drop-based microfluidic method for the passaging of viruses with host Madin-Darby Canine Kidney (MDCK) cells in drops, and second, develop a drop-based quantitative polymerase chain reaction (qPCR) method to quantify viruses and TIPs in drops after each passage. We plan to use these devices for up to five cell passages and compare our results to parallel bulk experiments performed in a well plate.
- Department of Chemical and Biological Engineering