Targeted Analysis of the Size Distribution of Heavy Chain-Modified Hyaluronan with Solid-State Nanopores

Abstract

The glycosaminoglycan hyaluronan (HA) plays important roles in diverse physiological functions where the distribution of its molecular weight (MW) can influence its behavior and is known to change in response to disease conditions. During inflammation, HA undergoes a covalent modification in which heavy chain subunits of the inter-alpha-inhibitor family of proteins are transferred to its structure, forming heavy chain-HA (HC•HA) complexes. While limited assessments of HC•HA have been performed previously, determining the size distribution of its HA component remains a challenge. Here, we describe a selective method for extracting HC•HA from mixtures that yields material amenable to MW analysis with a solid-state nanopore sensor. After demonstrating the approach in vitro, we validate extraction of HC•HA from osteoarthritic human synovial fluid as a model complex biological matrix. Finally, we apply our technique to pathophysiology by measuring the size distributions of HC•HA and total HA in an equine model of synovitis.

Editors’ Choice—Perspective—Deciphering the Glycan Kryptos by Solid-State Nanopore Single-Molecule Sensing: A Call for Integrated Advancements Across Glyco- and Nanopore Science

“…lectins and boronic acids) and chemical labelling of analytes to characterize a range of glycan samples and characteristics. 35, Recent glycoscience work with SiN x nanopores has resolved hyaluronic acid biopolymer molecular weights, 67,68,80 differentiated between multiple survey sets of samples by chemical composition, 77 and demonstrated the promise of combining solid-state nanopore sensing with machine learning. 75,76 The indispensability of high-quality glycan standards for machine learning training in nanopore glycoscience was underscored in work that differentiated between glycans by unique monomer composition.…”

Unraveling RNA Conformation Dynamics in Mitochondrial Encephalomyopathy, Lactic Acidosis, and Stroke-like Episode Syndrome with Solid-State Nanopores

“…The early work that established the foundations for the nanopore methods include sensing polymers in solution; use of protein nanopores to sequence DNA; − monitor enzyme kinetics; detect damaged DNA; discriminate between polymers based on their size; − discriminate between different metal nanoparticles; detect, quantify, and discriminate between different proteins; − and discriminate between a native protein/point mutants in the same/and post-translational modifications . Additionally, important examples of foundational work on solid-state pores also includes detection of genomic DNA, viral particles, and polysaccharides. − Among these applications, nanopores have shown high promises in identifying the intricate dynamics of RNA in general, − and tRNA in particular, offering a pathway to explore their structural variations that have functional significance.…”