Label-free analysis of physiological hyaluronan size distribution with a solid-state nanopore sensor

Felipe Rivas, Osama K. Zahid, Heidi L. Reesink, Bridgette T. Peal, Alan J. Nixon, Paul L. DeAngelis, Aleksander Skardal, Elaheh Rahbar () and Adam R. Hall ()
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Felipe Rivas: Wake Forest School of Medicine
Osama K. Zahid: Wake Forest School of Medicine
Heidi L. Reesink: College of Veterinary Medicine, Cornell University
Bridgette T. Peal: College of Veterinary Medicine, Cornell University
Alan J. Nixon: College of Veterinary Medicine, Cornell University
Paul L. DeAngelis: University of Oklahoma Health Sciences Center
Aleksander Skardal: Wake Forest School of Medicine
Elaheh Rahbar: Wake Forest School of Medicine
Adam R. Hall: Wake Forest School of Medicine

Nature Communications, 2018, vol. 9, issue 1, 1-9

Abstract: Abstract Hyaluronan (or hyaluronic acid, HA) is a ubiquitous molecule that plays critical roles in numerous physiological functions in vivo, including tissue hydration, inflammation, and joint lubrication. Both the abundance and size distribution of HA in biological fluids are recognized as robust indicators of various pathologies and disease progressions. However, such analyses remain challenging because conventional methods are not sufficiently sensitive, have limited dynamic range, and/or are only semi-quantitative. Here we demonstrate label-free detection and molecular weight discrimination of HA with a solid-state nanopore sensor. We first employ synthetic HA polymers to validate the measurement approach and then use the platform to determine the size distribution of as little as 10 ng of HA extracted directly from synovial fluid in an equine model of osteoarthritis. Our results establish a quantitative method for assessment of a significant molecular biomarker that bridges a gap in the current state of the art.

Date: 2018
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DOI: 10.1038/s41467-018-03439-x

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