Microfluidic Device Design for Selective Enrichment of Biocolloids Based on their Deformability and Polarization

Varhue, Walter, Electrical Engineering - School of Engineering and Applied Science, University of Virginia
Swami, Nathan, Department of Electrical and Computer Engineering, University of Virginia


The development of methods to achieve the selective enrichment and separation of biocolloids based on particle size, shape, biomechanical properties, cell phenotype, and biomolecular conformation is of great interest towards application in tissue regeneration and bioanalytical systems. Microfluidic systems enable the selective translation of particles by hydrodynamic means based on size, shape and deformability. Furthermore, separation can be achieved through the integration of electrokinetic methods such as dielectrophoresis (DEP), which enables frequency selective translation of bioparticles based on dielectric parameters, including intracellular electrophysiology, surface topology, and bimolecular conformation. Herein we develop microfluidic device platforms for two clinically significant applications: (1) deformability-based separation of pancreatic islets of Langerhans from exocrine acinar tissue; and (2) simultaneous enrichment and detection of proteomic biomarkers in physiological media.

Diabetes remains the seventh leading cause of death among Americans. A potential cure for the type-1 variant, which is currently managed through lifelong exogenous insulin administration, can be achieved through transplantation of pancreatic islet of Langerhans to restore normal endocrinal function. However, endocrine islet tissue forms a small proportion of the pancreas (~1%), and must be isolated from the contaminating exocrine acinar tissue that makes up the majority of the organ. Herein, we demonstrate that the density gradient based method that is currently used to separate islets from acinar tissue causes the islets to be sparsely distributed across a wide array of centrifuged sample bins of varying purity. The resulting transplant plug contains significantly high levels of contaminating exocrine acinar tissue (~40% of transplant volume), thereby exacerbating immune responses and requiring the life-long administration of immune suppressants after transplantation. In comparison to the significant size and density overlaps between the islet and acinar tissue populations, we demonstrate that their deformability overlaps are minimal. Utilizing this feature, we demonstrate a microfluidic separation strategy, wherein tangential flows enable selective deformation of acinar populations towards the waste stream and sequential switching of hydrodynamic resistance enables the collection of rigid islet cell aggregates. This system is shown to be capable of enriching islets from relatively dilute starting levels up to purity levels that meet transplant criteria, as well as towards enhancing islet purity from the starting samples obtained after density gradient based separation.

The electrokinetic trapping of nanoscale biocolloids and biomolecules within nanoslit devices enables high degrees of enrichment and overcomes mass transport limitations within various sensing modalities. Such nanoslit device architectures are applied to enable the simultaneous trapping and detection of two important proteomic biomarkers: (i) Neuropeptide Y (NPY), which offers noninvasive diagnostic information on stress, depression and neurotrauma; and (ii) prostate specific antigen, an important biomarker for diagnosis prostate cancer. Herein, we demonstrate the fabrication and assembly of nanoslit devices for the electrokinetic enrichment of these biomarkers through frequency selective dielectrophoresis (DEP), which is integrated with a graphene modified surface for electrochemical detection post-enrichment.

PHD (Doctor of Philosophy)
Microfluidics, Dielectrophoresis, Pancreatic Islets, Type 1 Diabetes , Pancreatic Islet transplantation, Cell Aggregate sorting, Deformability based sorting, Nanofluidics, DEP preconcentration, Prostate Specific Antigen, Neuropeptide Y, Islets of Langerhans
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