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

Author

Listed:
  • 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
    Wake Forest School of Medicine
    Wake Forest School of Medicine)

  • Elaheh Rahbar

    (Wake Forest School of Medicine)

  • Adam R. Hall

    (Wake Forest School of Medicine
    Wake Forest School of Medicine
    Wake Forest School of Medicine)

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.

Suggested Citation

  • Felipe Rivas & Osama K. Zahid & Heidi L. Reesink & Bridgette T. Peal & Alan J. Nixon & Paul L. DeAngelis & Aleksander Skardal & Elaheh Rahbar & Adam R. Hall, 2018. "Label-free analysis of physiological hyaluronan size distribution with a solid-state nanopore sensor," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03439-x
    DOI: 10.1038/s41467-018-03439-x
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    Cited by:

    1. Gerardo Patiño-Guillén & Jovan Pešović & Marko Panić & Dušanka Savić-Pavićević & Filip Bošković & Ulrich Felix Keyser, 2024. "Single-molecule RNA sizing enables quantitative analysis of alternative transcription termination," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Parisa Bayat & Charlotte Rambaud & Bernard Priem & Matthieu Bourderioux & Mélanie Bilong & Salomé Poyer & Manuela Pastoriza-Gallego & Abdelghani Oukhaled & Jérôme Mathé & Régis Daniel, 2022. "Comprehensive structural assignment of glycosaminoglycan oligo- and polysaccharides by protein nanopore," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Minmin Li & Yuting Xiong & Yuchen Cao & Chen Zhang & Yuting Li & Hanwen Ning & Fan Liu & Han Zhou & Xiaonong Li & Xianlong Ye & Yue Pang & Jiaming Zhang & Xinmiao Liang & Guangyan Qing, 2023. "Identification of tagged glycans with a protein nanopore," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

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