"Tools for Understanding Biology: Microfluidics and Separations Science"

Mark A. Hayes, Professor

Arizona State University, School of Molecular Sciences

Hosted by: Dr. Robbyn Anand

Abstract: Biology is a complex beast from an analytics point of view. We need all the imaging and chemical/biochemical identification tools in the world to even begin to parse out the underlying molecular mechanisms. Yet understanding these mechanisms is paramount for so many reasons: diagnostics and therapeutics, origins of life, search for life in the solar system and understanding the environment. Even though we exist on the meters-scale and live for years, everything important happens at the molecular scale very quickly.

How do we begin to analyze these systems and where does microfluidics and separations science shine in the world of bioanalytics? It complements the myriad of imaging techniques and amplifies spectroscopies and mass spectrometries. The small scale of the devices allows examination of smaller volumes and shorter timescales, and the improved separations amplifies the amount of information that can be gathered from existing instruments. Using thoughtfully shaped flow and electric fields on the small platform gives strong fields and gradients that foundationally improve separations. Our group has focused on demonstrating extreme separations on cellular, meso-scale and molecular systems. 

Early demonstrations showed that even antibiotic-resistant and susceptible bacteria could be cleanly separated by purely biophysical differences—no labels, no induced metabolism. The system is deterministic and reproducible based on foundational (and simple) principles. More recently, the same approach has been extended to viruses, exosomes, and proteins, pointing toward a new route to both fundamental biological insights and the development of a distinct diagnostic platform. 

At its core, this strategy allows purification, isolation, and concentration of cells and bioparticles to true homogeneity based solely on their intrinsic properties. This capability inherently allows more information to be extracted from smaller samples over shorter time contributing accurate and precise data to feed our models of biology. The accuracy and precision of the data will drive more useful outcomes from these models, the most popular current ones being AI-driven.

Relevant blogs

The LCGC Blog: Curing My Personal Ignorance, One Day at a Time. OnLine-Collaborative Blog w LCGC and ACS AD SCSC August 1, 2022. https://www.chromatographyonline.com/view/curing-my-personal-ignorance-…

The LCGC Blog: The Future of Separation Science: Goodbye Old Friends. Chromatography OnLine-Collaborative Blog w LCGC and ACS AD SCSC June 24, 2021. https://www.chromatographyonline.com/view/the-lcgc-blog-she-separates-t….

Cites

Insulator-based dielectrophoresis-assisted separation of insulin secretory vesicles. Mahta Barekatain*, Yameng Liu*, Ashley Archambeau, Vadim Cherezov, Scott E. Fraser, Kate L White, and Mark A. Hayes eLife 2024, 13 e74989 DOI 10.7554/eLife.74989.

Biophysical Separation of Staphylococcus epidermidis Strains Based on Antibiotic Resistance. Paul V. Jones, Shannon Huey, Paige Davis, Ryan McLemore, Alex McLaren, Ryan Yanashima, and Mark A. Hayes*Analyst 2015, 140, 5152-5161. DOI: 10.1039/C5AN00906E.

Concentration of Sindbis Virus with Optimized Gradient Insulator-based Dielectrophoresis. Jie Ding, Robert Lawrence, Paul V. Jones, Brenda G. Hogue, and Mark A. Hayes* Analyst 2016, 141, 1997-2008 DOI: 10.1039/C5AN02430G.

Interfacing microfluidics with information-rich detection systems for cells, bioparticles, and molecules. Smithers JP, Hayes MA. Analytical and Bioanalytical Chemistry 2022, 414(16) 4575-89. DOI 10.1007/s00216-022-04043-1.

Development of the Resolution Theory for Electrophoretic Exclusion. Stacy M. Kenyon, Michael W. Keebaugh, & Mark A. Hayes Electrophoresis, 2014, 35, 2551-2559 DOI 10.1002/elps.201300572.

Development of the Resolution Theory for Gradient insulator-based Dielectrophoresis. Mark A. Hayes & Paul V. Jones Electrophoresis 2015, 36(9-10), 1098-1106, DOI: 10.1002/elps.201400504

Identification of Neural Stem and Progenitor Cell Subpopulations using DC Insulator-based Dielectrophoresis. Yameng Liu, Alan Jiang, Estelle Kim, Clarissa Ro, Tayloria Adams, Lisa A. Flanagan, Thomas J. Taylor & Mark A. Hayes* Analyst 2019, 144, 4066 - 4072 PMI:31165125 DOI: 10.1039/c9an00456d.