Optimizing the sensitivity and resolution of hyaluronan analysis with solid-state nanopores

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

Glycans, or complex carbohydrates, are information-rich biopolymers critical to many biological processes and with considerable importance in pharmaceutical therapeutics. Our understanding, though, is limited compared to other biomolecules such as DNA and proteins. The greater complexity of glycan structure and the limitations of conventional chemical analysis methods hinder glycan studies. Auspiciously, nanopore single-molecule sensors-commercially available for DNA sequencing-hold great promise as a tool for enabling and advancing glycan analysis. We focus on two key areas to advance nanopore glycan characterization: molecular surface coatings to enhance nanopore performance including by molecular recognition, and high-quality glycan chemical standards for training.

Detection and identification of single ribonucleotide monophosphates using a dual in-plane nanopore sensor made in a thermoplastic via replication

We report the generation of ∼8 nm dual in-plane pores fabricated in a thermoplastic via nanoimprint lithography (NIL). These pores were connected in series with nanochannels, one of which served as a flight tube to allow the identification of single molecules based on their molecular-dependent apparent mobilities (i.e., dual in-plane nanopore sensor). Two different thermoplastics were investigated including poly(methyl methacrylate), PMMA, and cyclic olefin polymer, COP, as the substrate for the sensor both of which were sealed using a low glass transition cover plate (cyclic olefin co-polymer, COC) that could be thermally fusion bonded to the PMMA or COP substrate at a temperature minimizing nanostructure deformation. Unique to these dual in-plane nanopore sensors was two pores flanking each side of the nanometer flight tube (50 × 50 nm, width × depth) that was 10 μm in length. The utility of this dual in-plane nanopore sensor was evaluated to not only detect, but also identify single ribonucleotide monophosphates (rNMPs) by using the travel time (time-of-flight, ToF), the resistive pulse event amplitude, and the dwell time. In spite of the relatively large size of these in-plane pores (∼8 nm effective diameter), we could detect via resistive pulse sensing (RPS) single rNMP molecules at a mass load of 3.9 fg, which was ascribed to the unique structural features of the nanofluidic network and the use of a thermoplastic with low relative dielectric constants, which resulted in a low RMS noise level in the open pore current. Our data indicated that the identification accuracy of individual rNMPs was high, which was ascribed to an improved chromatographic contribution to the nano-electrophoresis apparent mobility. With the ToF data only, the identification accuracy was 98.3%. However, when incorporating the resistive pulse sensing event amplitude and dwell time in conjunction with the ToF and analyzed via principal component analysis (PCA), the identification accuracy reached 100%. These findings pave the way for the realization of a novel chip-based single-molecule RNA sequencing technology.

Improving the Performance of Selective Solid-State Nanopore Sensing Using a Polyhistidine-Tagged Monovalent Streptavidin

Solid-state (SS-) nanopore sensing has gained tremendous attention in recent years, but it has been constrained by its intrinsic lack of selectivity. To address this, we previously established a novel SS-nanopore assay that produces translocation signals only when a target biotinylated nucleic acid fragment binds to monovalent streptavidin (MS), a protein variant with a single high-affinity biotin-binding domain. While this approach has enabled selective quantification of diverse nucleic acid biomarkers, sensitivity enhancements are needed to improve the detection of low-abundance translational targets. Because the translocation dynamics that determine assay efficacy are largely governed by constituent charge characteristics, we here incorporate a polyhistidine-tagged MS (hMS) to alter the component detectability. We investigate the effects of buffer pH, salt concentration, and SS-nanopore diameter on the performance with the alternate reagent, achieve significant improvements in measurement sensitivity and selectivity, and expand the range of device dimensions viable for the assay. We used this improvement to detect as little as 1 nM miRNA spiked into human plasma. Overall, our findings improve the potential for broader applications of SS-nanopores in the quantitative analyses of molecular biomarkers.

High Fidelity Machine-Learning-Assisted False Positive Discrimination in Loop-Mediated Isothermal Amplification Using Nanopore-Based Sizing and Counting

Loop-mediated isothermal amplification (LAMP) is a rapid, sensitive, and cost-effective method for developing point-of-care nucleic acid testing due to its isothermal nature. Yet, LAMP can suffer from the issue of false positives, which can compromise the specificity of the results. LAMP false positives typically arise due to contamination, nonspecific amplification, and nonspecific signal reporting (intercalating dyes, colorimetric, turbidity, etc.). While dye-labeled primers or probes have been introduced for multiplexed detection and enhanced specificity in LAMP assays, they carry the risk of reaction inhibition. This inhibition can result from the labeled primers with fluorophores or quenchers and probes that do not fully dissociate during reaction. This work demonstrated a nanopore-based system for probe-free LAMP readouts by employing amplicon sizing and counting, analogous to an electronic version of gel electrophoresis. We first developed a model to explore LAMP kinetics and verified distinct patterns between true and false positives via gel electrophoresis. Subsequently, we implemented nanopore sized counting and calibrated the event charge deficit (ECD) values and frequencies to ensure a fair analysis of amplicon profiles. This sized counting method, integrated with machine learning, achieved 91.67% accuracy for false positive discrimination, enhancing LAMP's reliability for nucleic acid detection.

Discrimination of Disaccharide Isomers of Different Glycosidic Linkages Using a Modified MspA Nanopore

Disaccharides are composed of two monosaccharide subunits joined by a glycosidic linkage in an α or β configuration. Different combinations of isomeric monosaccharide subunits and different glycosidic linkages result in different isomeric disaccharide products. Thus, direct discrimination of these disaccharide isomers from a mixture is extremely difficult. In this paper, a hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore conjugated with a phenylboronic acid (PBA) adapter was applied for disaccharide sensing, with which three most widely known disaccharides in nature, including sucrose, lactose and maltose, were clearly discriminated. Besides, all six isomeric α-D-glucopyranosyl-D-fructoses, differing only in their glycosidic linkages, were also well resolved. Assisted by a custom machine learning algorithm, a 0.99 discrimination accuracy is achieved. Nanopore discrimination of disaccharide isomers with different glycosidic linkages, which has never been previously demonstrated, is inspiring for nanopore saccharide sequencing. This sensing capacity was also applied in direct identification of isomaltulose additives in a commercial sucrose-free yogurt, from which isomaltulose, lactose and L-lactic acid were simultaneously detected.

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

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.

Identification of Conformational Variants for Bradykinin Biomarker Peptides from a Biofluid Using a Nanopore and Machine Learning

There is a current need to develop methods for the sensitive detection of peptide biomarkers in complex mixtures of molecules, such as biofluids, to enable early disease detection. Moreover, to our knowledge, there is currently no detection method capable of identifying the different conformations of a peptide biomarker differing by a single amino acid. Single-molecule nanopore sensing promises to provide this level of resolution. In order to be able to identify these differences in a biofluid such as serum, it is necessary to carefully characterize electrical parameters to obtain specific signatures of each biomarker population observed. We are interested here in a family of peptide biomarkers, kinins such as bradykinin and des-Arg9 bradykinin, that are involved in many disabling pathologies (allergy, asthma, angioedema, sepsis, or cancer). We show the proof of concept for direct identification of these biomarkers in serum at the single-molecule level using a protein nanopore. Each peptide exhibits two unique electrical signatures attributed to specific conformations in bulk. The same signatures are found in serum, allowing their discrimination and identification in a complex mixture such as biofluid. To extend the utility of our experimental results, we developed a principal component analysis approach to define the most relevant electrical parameters for their identification. Finally, we used semisupervised classification to assign each event type to a specific biomarker at physiological serum concentration. In the future, single-molecule scale analysis of peptide biomarkers using a powerful nanopore coupled with machine learning will facilitate the identification and quantification of other clinically relevant biomarkers from biofluids.

Unveiling Vaginal Fibrosis: A Novel Murine Model Using Bleomycin and Epithelial Disruption

Objective

Develop, validate, and characterize a fibrotic murine vaginal wound healing model using bleomycin instillations and epithelial disruption.

Approach

We tested the effect of repeated bleomycin instillations with mucosal layer disruption on induction of vaginal fibrosis. Tissue samples collected at various time points were analyzed for fibrosis-related gene expression changes and collagen content.

Results

Low (1.5U/kg) and high-dose (2.5U/kg) bleomycin instillations alone did not induce fibrosis, but when high-dose bleomycin was combined with epithelial disruption, increased pro-fibrotic gene expression and trichrome staining were observed. To evaluate spatial and temporal changes in the ECM structure and gene expression, tissue samples were collected at 1 day, 3 weeks, and 6 weeks after bleomycin and epithelial disruption. Data analyses revealed a significant decrease in matrix metabolizing genes and an increase in pro-fibrotic genes and inhibitors of matrix metabolizing genes in the bleomycin plus epithelial disruption group at 3 weeks. Elevated levels of the profibrotic genes Acta2 , Col1a1 , and Col3a were exclusively detected in this group at 3 weeks, and trichrome staining confirmed increased collagen content after 3 weeks. Hydroxyproline levels showed a tendency towards elevation at 3 weeks (p=0.12) and 6 weeks (p=0.14), indicating fibrosis manifestation at 3 weeks and resolution by 6 weeks post-instillation and epithelial disruption.

Innovation

We combined bleomycin instillations with epithelial disruption to induce fibrosis and understand the mechanisms of the vaginal repair process.

Conclusions

Epithelial disruption combined with bleomycin induces murine vaginal fibrosis within three weeks, characterized by increased collagen synthesis. Remarkably, the vaginal tissue fully recovers within six weeks, elucidating the regenerative capacity of the vagina.

Age related changes in hyaluronan expression leads to Meibomian gland dysfunction

The prevalence of dry eye disease (DED) ranges from ∼5 to 50 % and its associated symptoms decrease productivity and reduce the quality of life. Approximately 85 % of all DED cases are caused by Meibomian gland dysfunction (MGD). As humans and mice age, their Meibomian glands (MGs) undergo age-related changes resulting in age related-MGD (ARMGD). The precise cause of ARMGD remains elusive, which makes developing therapies extremely challenging. We previously demonstrated that a hyaluronan (HA)-rich matrix exists surrounding the MG, regulating MG morphogenesis and homeostasis. Herein, we investigated whether changes to the HA matrix in the MG throughout life contributes towards ARMGD, and whether altering this HA matrix can prevent ARMGD. For such, HA synthase (Has) knockout mice were aged and compared to age matched wild type (wt) mice. MG morphology, lipid production, PPARγ expression, basal cell proliferation, stem cells, presence of atrophic glands and MG dropout were analyzed at 8 weeks, 6 months, 1 year and 2 years of age and correlated with the composition of the HA matrix. We found that as mice age, there is a loss of HA expression in and surrounding the MGs of wt mice, while, in contrast, Has1-/-Has3-/- mice present a significant increase in HA expression through Has2 upregulation. At 1 year, Has1-/-Has3-/- mice present significantly enlarged MGs, compared to age-matched wt mice and compared to all adult mice. Thus, Has1-/-Has3-/- mice continue to develop new glandular tissue as they age, instead of suffering MG atrophy. At 2 years, Has1-/-Has3-/- mice continue to present significantly larger MGs compared to age-matched wt mice. Has1-/-Has3-/- mice present increased lipid production, increased PPARγ expression and an increase in the number of proliferating cells when compared to wt mice at all-time points analyzed. Taken together, our data shows that a loss of the HA matrix surrounding the MG as mice age contributes towards ARMGD, and increasing Has2 expression, and consequently HA levels, prevents ARMGD in mice.

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.

A quartz crystal microbalance method to quantify the size of hyaluronan and other glycosaminoglycans on surfaces

Hyaluronan (HA) is a major component of peri- and extra-cellular matrices and plays important roles in many biological processes such as cell adhesion, proliferation and migration. The abundance, size distribution and presentation of HA dictate its biological effects and are also useful indicators of pathologies and disease progression. Methods to assess the molecular mass of free-floating HA and other glycosaminoglycans (GAGs) are well established. In many biological and technological settings, however, GAGs are displayed on surfaces, and methods to obtain the size of surface-attached GAGs are lacking. Here, we present a method to size HA that is end-attached to surfaces. The method is based on the quartz crystal microbalance with dissipation monitoring (QCM-D) and exploits that the softness and thickness of films of grafted HA increase with HA size. These two quantities are sensitively reflected by the ratio of the dissipation shift (ΔD) and the negative frequency shift (- Δf) measured by QCM-D upon the formation of HA films. Using a series of size-defined HA preparations, ranging in size from ~ 2 kDa tetrasaccharides to ~ 1 MDa polysaccharides, we establish a monotonic yet non-linear standard curve of the ΔD/ - Δf ratio as a function of HA size, which reflects the distinct conformations adopted by grafted HA chains depending on their size and surface coverage. We demonstrate that the standard curve can be used to determine the mean size of HA, as well as other GAGs, such as chondroitin sulfate and heparan sulfate, of preparations of previously unknown size in the range from 1 to 500 kDa, with a resolution of better than 10%. For polydisperse samples, our analysis shows that the process of surface-grafting preferentially selects smaller GAG chains, and thus reduces the average size of GAGs that are immobilised on surfaces comparative to the original solution sample. Our results establish a quantitative method to size HA and other GAGs grafted on surfaces, and also highlight the importance of sizing GAGs directly on surfaces. The method should be useful for the development and quality control of GAG-based surface coatings in a wide range of research areas, from molecular interaction analysis to biomaterials coatings.