370807 High Throughput Digital Video Flow Cytometry

Thursday, November 20, 2014: 10:00 AM
206 (Hilton Atlanta)
Jaime J. Juárez1, Pearlson P. Austin Suthanthiraraj1, Menake Piyasena2, Daniel Kalb1, Frank Fencl1, Bruce S. Edwards3, Steven W. Graves4 and Andrew P. Shreve1, (1)Center for Biomedical Engineering, University of New Mexico, Albuquerque, NM, (2)Department of Chemistry, New Mexico Tech, Socorro, NM, (3)Center of Molecular Studies & Dept. of Pathology, The University of New Mexico, Albuquerque, NM, (4)Center for Biomedical Engineering, The University of New Mexico, Albuquerque, NM

Introduction: Image processing of digital video obtained from microscopy is used to probe the thermodynamics of colloidal self-assembly and associated forces (e.g., van der Waals, electrostatics).1  This measurement technique has its origins in the pioneering work of Jean-Baptiste Perrin who used photography to study diffusion and Brownian motion a century ago.  The technique relies on the identification of particle centers from video frames using image processing to construct trajectories that yield dynamical information (e.g., diffusion coefficient, velocity).  Digital video is an integral part of image cytometry wherein a CMOS or CCD camera is used as a solid-state detector.

Methods: In our present work, we demonstrate the ability to perform high speed image cytometry using a digital CMOS camera.  The CMOS camera is capable of high speed video capture up to 25,000 frames per second using individual pixel elements on the 4 megapixel CMOS sensor as independent detectors.  The CMOS sensor produces 16-bit images with a dynamic range of 33,000:1, providing us with a high degree of sensitivity.   The video we capture is analyzed using image processing algorithms coded in MATLAB.  The CMOS camera in combination with our acoustic focusing technique2 illustrates the merits of combining flow and image cytometry into a single platform.

Results: Measured intensity is calibrated by imaging phycoerythrin (PE) dye in solution at different concentrations.  In imaging mode our platform identifies the trajectories of acoustically focused particles partitioned into streams separated by ~165 µm.  The trajectories enable us to construct a velocity profile (i.e., particle image velocimetry) within the acoustic focusing channel providing us with information that guides device design.  We mix calibration beads with different PE concentrations to evaluate the performance of our device in flow mode.  Model assays based on CD3/CD4 demonstrate the high throughput capacity of our platform by identifying rare events.

Conclusion: We demonstrate the capabilities of this platform to simultaneously perform image and flow cytometry.  In imaging mode, we obtain velocimetry data that further guides the development of our acoustic focusing platform.  Calibration of our imaging mode enables us to perform flow cytometry on a mixture of fluorescent calibration beads.  We expand our flow cytometry capabilities to include high throughput model assays for the identification of rare events.


1.            Crocker, J. C.; Grier, D. G., Methods of Digital Video Microscopy for Colloidal Studies. Journal of Colloid and Interface Science 1996, 179, 298.

2.            Piyasena, M. E.; Austin Suthanthiraraj, P. P.; Applegate, R. W.; Goumas, A. M.; Woods, T. A.; López, G. P.; Graves, S. W., Multinode Acoustic Focusing for Parallel Flow Cytometry. Analytical Chemistry 2012, 84 (4), 1831-1839

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See more of this Session: Experimental Approaches in Systems Biology
See more of this Group/Topical: Food, Pharmaceutical & Bioengineering Division