Principal Investigator Joel Voldman
The development of new techniques to separate and characterize cells with high throughput has been essential to many of the advances in biology and biotechnology over the past few decades. We are developing a novel method for the simultaneous separation and characterization of cells based upon their electrical properties. This method, iso-dielectric separation (IDS), uses dielectrophoresis (DEP, the force on a polarizable object) and a medium with spatially varying conductivity to sort electrically distinct cells while measuring their effective conductivity. It is similar to iso-electric focusing, except that it uses DEP instead of electrophoresis to concentrate cells and particles to the region in a conductivity gradient where their polarization charge vanishes.
Sepsis is an uncontrolled activation of the immune system that causes an excessive inflammatory response. There is an unmet need to develop tools to monitor sepsis progression, which occurs quickly and provides few clues to indicate if treatment is effective. Previously, we have found the electrical profile of leukocytes changes with activation state, and we have applied IDS to characterize the electrical profile of leukocytes for monitor sepsis. After working with neutrophils, we also found that IDS can be used to distinguish different types of leukocytes having different dielectric properties. Once cell properties such as size, permittivity and conductivity of each part change, Clausius-Mossotti (CM) factor changes and it explains the reason why we can distinguish different types of cells in IDS. We could distinguish neutrophils and T-cells (the majority of lymphocytes) at the frequency of 5 MHz and the area under ROC curve was 0.8473. To advance the automation of the system and reduction sample preparation for clinical deployment, we could integrate the upstream separator such as inertial microfluidic sorter for removal of red blood cells (RBC) from the patient’s blood samples. It might be possible to monitor sepsis from patients in pseudo-real time.