Single Molecule Identification and Quantification of Glycosaminoglycans Using Solid-State Nanopores

Single-Molecule Identification and Quantification of Steviol Glycosides with a Deep Learning-Powered Nanopore Sensor

Steviol glycosides (SGs) are a class of high-potency noncalorie natural sweeteners made up of a common diterpenoid core and varying glycans. Thus, the diversity of glycans in composition, linkage, and isomerism results in the tremendous structural complexity of the SG family, which poses challenges for the precise identification and leads to the fact that SGs are frequently used in mixtures and their variances in biological activity remain largely unexplored. Here we show that a wild-type aerolysin nanopore can detect and discriminate diverse SG species through the modulable electro-osmotic flow effect at varied applied voltages. At low voltages, the neutral SG molecule was drawn and stuck in the pore entrance due to an energy barrier around R220 sites. The ensuing binding events enable the identification of the majority of SG species. Increasing the voltage can break the barrier and cause translocation events, allowing for the unambiguous identification of several pairs of SGs differing by only one hydroxyl group through recognition accumulation from multiple sensing regions and sites. Based on nanopore data of 15 SGs, a deep learning-based artificial intelligence (AI) model was created to process the individual blockage events, achieving the rapid, automated, and precise single-molecule identification and quantification of SGs in real samples. This work highlights the value of nanopore sensing for precise structural analysis of complex glycans-containing glycosides, as well as the potential for sensitive and rapid quality assurance analysis of glycoside products with the use of AI.

Research Progress on Saccharide Molecule Detection Based on Nanopores

Saccharides, being one of the fundamental molecules of life, play essential roles in the physiological and pathological functions of cells. However, their intricate structures pose challenges for detection. Nanopore technology, with its high sensitivity and capability for single-molecule-level analysis, has revolutionized the identification and structural analysis of saccharide molecules. This review focuses on recent advancements in nanopore technology for carbohydrate detection, presenting an array of methods that leverage the molecular complexity of saccharides. Biological nanopore techniques utilize specific protein binding or pore modifications to trigger typical resistive pulses, enabling the high-sensitivity detection of monosaccharides and oligosaccharides. In solid-state nanopore sensing, boronic acid modification and pH gating mechanisms are employed for the specific recognition and quantitative analysis of polysaccharides. The integration of artificial intelligence algorithms can further enhance the accuracy and reliability of analyses. Serving as a crucial tool in carbohydrate detection, we foresee significant potential in the application of nanopore technology for the detection of carbohydrate molecules in disease diagnosis, drug screening, and biosensing, fostering innovative progress in related research domains.

A biological guide to glycosaminoglycans: current perspectives and pending questions

Mammalian glycosaminoglycans (GAGs), except hyaluronan (HA), are sulfated polysaccharides that are covalently attached to core proteins to form proteoglycans (PGs). This article summarizes key biological findings for the most widespread GAGs, namely HA, chondroitin sulfate/dermatan sulfate (CS/DS), keratan sulfate (KS), and heparan sulfate (HS). It focuses on the major processes that remain to be deciphered to get a comprehensive view of the mechanisms mediating GAG biological functions. They include the regulation of GAG biosynthesis and postsynthetic modifications in heparin (HP) and HS, the composition, heterogeneity, and function of the tetrasaccharide linkage region and its role in disease, the functional characterization of the new PGs recently identified by glycoproteomics, the selectivity of interactions mediated by GAG chains, the display of GAG chains and PGs at the cell surface and their impact on the availability and activity of soluble ligands, and on their move through the glycocalyx layer to reach their receptors, the human GAG profile in health and disease, the roles of GAGs and particular PGs (syndecans, decorin, and biglycan) involved in cancer, inflammation, and fibrosis, the possible use of GAGs and PGs as disease biomarkers, and the design of inhibitors targeting GAG biosynthetic enzymes and GAG-protein interactions to develop novel therapeutic approaches.

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.

Nanosensor based approaches for quantitative detection of heparin

Heparin, being a widely employed anticoagulant in numerus clinical complications, requires strict quantification and qualitative screening to ensure the safety of patients from potential threat of thrombocytopenia. However, the intricacy of heparin's chemical structures and low abundance hinders the precise monitoring of its level and quality in clinical settings. Conventional laboratory assays have limitations in sensitivity and specificity, necessitating the development of innovative approaches. In this context, nanosensors emerged as a promising solution due to enhanced sensitivity, selectivity, and ability to detect heparin even at low concentrations. This review delves into a range of sensing approaches including colorimetric, fluorometric, surface-enhanced Raman spectroscopy, and electrochemical techniques using different types of nanomaterials, thus providing insights of its principles, capabilities, and limitations. Moreover, integration of smart-phone with nanosensors for point of care diagnostics has also been explored. Additionally, recent advances in nanopore technologies, artificial intelligence (AI) and machine learning (ML) have been discussed offering specificity against contaminants present in heparin to ensure its quality. By consolidating current knowledge and highlighting the potential of nanosensors, this review aims to contribute to the advancement of efficient, reliable, and economical heparin detection methods providing improved patient care.

Precise Structural Analysis of Neutral Glycans Using Aerolysin Mutant T240R Nanopore

Glycans play vital roles in nearly all life processes of multicellular organisms, and understanding these activities is inseparable from elucidating the biological significance of glycans. However, glycan research has lagged behind that of DNA and protein due to the challenges posed by structural heterogeneity and isomerism (i.e., structures with equal molecular weights) the lack of high-efficiency structural analysis techniques. Nanopore technology has emerged as a sensitive single-molecule biosensor, shining a light on glycan analysis. However, a significant number of glycans are small and uncharged, making it challenging to elicit identifiable nanopore signals. Here we introduce a R-binaphthyl tag into glycans, which enhances the cation-π interaction between the derivatized glycan molecules and the nanopore interface, enabling the detection of neutral glycans with an aerolysin nanopore. This approach allows for the distinction of di-, tri-, and tetrasaccharides with monosaccharide resolution and has the potential for group discrimination, the monitoring of enzymatic transglycosylation reactions. Notably, the aerolysin mutant T240R achieves unambiguous identification of six disaccharide isomers, trisaccharide and tetrasaccharide linkage isomers. Molecular docking simulations reveal that multiple noncovalent interactions occur between residues R282, K238, and R240 and the glycans and R-binaphthyl tag, significantly slowing down their translocation across the nanopore. Importantly, we provide a demonstration of the kinetic translocation process of neutral glycan isomers, establishing a solid theoretical foundation for glycan nanopore analysis. The development of our technology could promote the analysis of glycan structural isomers and has the potential for nanopore-based glycan structural determination and sequencing.

Conformation Influence of DNA on the Detection Signal through Solid-State Nanopores

The detection and identification of nanoscale molecules are crucial, but traditional technology comes with a high cost and requires skilled operators. Solid-state nanopores are new powerful tools for discerning the three-dimensional shape and size of molecules, enabling the translation of molecular structural information into electric signals. Here, DNA molecules with different shapes were designed to explore the effects of electroosmotic forces (EOF), electrophoretic forces (EPF), and volume exclusion on electric signals within solid-state nanopores. Our results revealed that the electroosmotic force was the main driving force for single-stranded DNA (ssDNA), whereas double-stranded DNA (dsDNA) was primarily dominated by electrophoretic forces in nanopores. Moreover, dsDNA caused greater amplitude signals and moved faster through the nanopore due to its larger diameter and carrying more charges. Furthermore, at the same charge level and amount of bases, circular dsDNA exhibited a tighter structure compared to brush DNA, resulting in a shorter length. Consequently, circular dsDNA caused higher current-blocking amplitudes and faster passage speeds. The characterization approach based on nanopores allows researchers to get molecular information about size and shape in real time. These findings suggest that nanopore detection has the potential to streamline nanoscale characterization and analysis, potentially reducing both the cost and complexity.

Characterizing Prion-Like Protein Aggregation: Emerging Nanopore-Based Approaches

Prion-like protein aggregation is characteristic of numerous neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases. This process involves the formation of aggregates ranging from small and potentially neurotoxic oligomers to highly structured self-propagating amyloid fibrils. Various approaches are used to study protein aggregation, but they do not always provide continuous information on the polymorphic, transient, and heterogeneous species formed. This review provides an updated state-of-the-art approach to the detection and characterization of a wide range of protein aggregates using nanopore technology. For each type of nanopore, biological, solid-state polymer, and nanopipette, discuss the main achievements for the detection of protein aggregates as well as the significant contributions to the understanding of protein aggregation and diagnostics.

Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors

Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical task in the fields of chemistry, biology, and medicine. The complexity of biological systems and the explosive growth of biomarker data have driven machine learning to become a powerful tool for mining and processing big data from disease diagnosis sensors. With the development of bioinformatics and artificial intelligence (AI), machine learning models formed by data mining have been able to guide more sensitive and accurate molecular computing. This review presents an overview of big data collection approaches and fundamental machine learning algorithms and discusses recent advances in machine learning and molecular computational disease diagnostic sensors. More specifically, we highlight existing modular workflows and key opportunities and challenges for machine learning to achieve disease diagnosis through big data mining.

Recent advances in nanopore-based analysis for carbohydrates and glycoconjugates

Saccharides are not only the basic constituents and nutrients of living organisms, but also participate in various life activities, and play important roles in cell recognition, immune regulation, development, cancer, etc. The analysis of carbohydrates and glycoconjugates is a necessary means to study their transformations and physiological roles in living organisms. Existing detection techniques can hardly meet the requirements for the analysis of carbohydrates and glycoconjugates in complex matrices as they are expensive, involve complex derivatization, and are time-consuming. Nanopore sensing technology, which is amplification-free and label-free, and is a high-throughput process, provides a new solution for the identification and sequencing of carbohydrates and glycoconjugates. This review highlights recent advances in novel nanopore-based single-molecule sensing technologies for the detection of carbohydrates and glycoconjugates and discusses the advantages and challenges of nanopore sensing technologies. Finally, current issues and future perspectives are discussed with the aim of improving the performance of nanopores in complex media diagnostic applications, as well as providing a new direction for the quantification of glycan chains and the study of glycan chain properties and functions.

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.

Unleashing the potential of tungsten disulfide: Current trends in biosensing and nanomedicine applications

The discovery of graphene ignites a great deal of interest in the research and advancement of two-dimensional (2D) layered materials. Within it, semiconducting transition metal dichalcogenides (TMDCs) are highly regarded due to their exceptional electrical and optoelectronic properties. Tungsten disulfide (WS2) is a TMDC with intriguing properties, such as biocompatibility, tunable bandgap, and outstanding photoelectric characteristics. These features make it a potential candidate for chemical sensing, biosensing, and tumor therapy. Despite the numerous reviews on the synthesis and application of TMDCs in the biomedical field, no comprehensive study still summarizes and unifies the research trends of WS2 from synthesis to biomedical applications. Therefore, this review aims to present a complete and thorough analysis of the current research trends in WS2 across several biomedical domains, including biosensing and nanomedicine, covering antibacterial applications, tissue engineering, drug delivery, and anticancer treatments. Finally, this review also discusses the potential opportunities and obstacles associated with WS2 to deliver a new outlook for advancing its progress in biomedical research.

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.

Solid-State Nanopores for Biomolecular Analysis and Detection

Advances in nanopore technology and data processing have rendered DNA sequencing highly accessible, unlocking a new realm of biotechnological opportunities. Commercially available nanopores for DNA sequencing are of biological origin and have certain disadvantages such as having specific environmental requirements to retain functionality. Solid-state nanopores have received increased attention as modular systems with controllable characteristics that enable deployment in non-physiological milieu. Thus, we focus our review on summarizing recent innovations in the field of solid-state nanopores to envision the future of this technology for biomolecular analysis and detection. We begin by introducing the physical aspects of nanopore measurements ranging from interfacial interactions at pore and electrode surfaces to mass transport of analytes and data analysis of recorded signals. Then, developments in nanopore fabrication and post-processing techniques with the pros and cons of different methodologies are examined. Subsequently, progress to facilitate DNA sequencing using solid-state nanopores is described to assess how this platform is evolving to tackle the more complex challenge of protein sequencing. Beyond sequencing, we highlight the recent developments in biosensing of nucleic acids, proteins, and sugars and conclude with an outlook on the frontiers of nanopore technologies.

High Accuracy Protein Identification: Fusion of Solid-State Nanopore Sensing and Machine Learning

Proteins are arguably one of the most important class of biomarkers for health diagnostic purposes. Label-free solid-state nanopore sensing is a versatile technique for sensing and analyzing biomolecules such as proteins at single-molecule level. While molecular-level information on size, shape, and charge of proteins can be assessed by nanopores, the identification of proteins with comparable sizes remains a challenge. Here, solid-state nanopore sensing is combined with machine learning to address this challenge. The translocations of four similarly sized proteins is assessed using amplifiers with bandwidths (BWs) of 100 kHz and 10 MHz, the highest bandwidth reported for protein sensing, using nanopores fabricated in <10 nm thick silicon nitride membranes. F-values of up to 65.9% and 83.2% (without clustering of the protein signals) are achieved with 100 kHz and 10 MHz BW measurements, respectively, for identification of the four proteins. The accuracy of protein identification is further enhanced by classifying the signals into different clusters based on signal attributes, with F-value and specificity of up to 88.7% and 96.4%, respectively, for combinations of four proteins. The combined use of high bandwidth instruments, advanced clustering and machine learning methods allows label-free identification of proteins with high accuracy.

Solid-state nanochannels for bio-marker analysis

Bio-markers, such as ions, small molecules, nucleic acids, peptides, proteins and cells, participate in the construction of living organisms and play important roles in biological processes. It is of great significance to accurately detect these bio-markers for studying their basic functions, the development of molecular diagnosis and to better understand life processes. Solid-state nanochannel-based sensing systems have been demonstrated for the detection of bio-markers, due to their rapid, label-free and high-throughput screening, with high sensitivity and specificity. Generally, studies on solid-state nanochannels have focused on probes on the inner-wall (PIW), ignoring probes on the outer-surface (POS). As a result, the direct detection of cells is difficult to realize by these inner-wall focused nanochannels. Moreover, the sensitivity for detecting ions, small molecules, nucleic acids, peptides and proteins requires further improvement. Recent research has focused on artificial solid-state nanochannels with POS, which have demonstrated the ability to independently regulate ion transport. This design not only contributes to the in situ detection of large analytes, such as cells, but also provides promising opportunities for ultra-high sensitivity detection with a clear mechanism. In this tutorial review, we present an overview of the detection principle used for solid-state nanochannels, inner-wall focused nanochannels and outer-surface focused nanochannels. Furthermore, we discuss the remaining challenges faced by current nanochannel technologies and provide insights into their prospects.

Nanopore Single-molecule Analysis of Biomarkers: Providing Possible Clues to Disease Diagnosis

Biomarker detection has attracted increasing interest in recent years due to the minimally or non-invasive sampling process. Single entity analysis of biomarkers is expected to provide real-time and accurate biological information for early disease diagnosis and prognosis, which is critical to the effective disease treatment and is also important in personalized medicine. As an innovative single entity analysis method, nanopore sensing is a pioneering single-molecule detection technique that is widely used in analytical bioanalytical fields. In this review, we overview the recent progress of nanopore biomarker detection as new approaches to disease diagnosis. In highlighted studies, nanopore was focusing on detecting biomarkers of different categories of communicable and noncommunicable diseases, such as pandemic Covid-19, AIDS, cancers, neurologic diseases, etc. Various sensitive and selective nanopore detecting strategies for different types of biomarkers are summarized. In addition, the challenges, opportunities, and direction for future development of nanopore-based biomarker sensors are also discussed.

Phenylboronic acid-modified polyethyleneimine assisted neutral polysaccharide detection and weight-resolution analysis with a nanopipette

In this work, an innovative method based on a nanopipette assisted with o-phenylboronic acid-modified polyethyleneimine (PEI-oBA) is proposed to detect neutral polysaccharides with different degrees of polymerization. Herein, dextran is used as the research target. Dextran, with its low molecular weight (10⁴ < MW < 10⁵ Da), has important applications in medicine and is one of the best plasma substitutes at present. Through the interaction between the boric acid group and a hydroxyl group, the synthesized high-charge polymer molecule PEI-oBA combines with dextran, increasing the electrophoretic force and exclusion volume of the target molecule to obtain a high signal-to-noise ratio for nanopore detection. These results show that the current amplitude increased significantly with the increase of dextran molecular weight. Furthermore, an aggregation-induced emission (AIE) molecule was introduced to adsorb onto PEI-oBA to verify that PEI-oBA combined with a polysaccharide entered the nanopipette together and was driven by electrophoresis. With the introduction of the modifiability of polymer molecules, the proposed method is conducive to improving the nanopore detection sensitivity of other important molecules with low charges and low molecular weights.

Analysis of starch dissolved in ionic liquid by glass nanopore at single molecular level

In this paper, the glass nanopore technology was proposed to detect a single molecule of starch dissolved in ionic liquid [1-butyl-3-methylimidazolium chloride (BmimCl)]. Firstly, the influence of BmimCl on nanopore detection is discussed. It is found that a certain amount of strong polar ionic liquids will disturb the charge distribution in nanopores and increase the detection noise. Then, by analysis of the characteristic current signal of the conical nanopore, the motion behaviour of starch near the entrance of the nanopore was studied and analysis the dominant ion of starch in the BmimCl dissolution process. Finally, based on nuclear magnetic resonance (NMR) and Fourier transform infrared (FTIR) spectroscopy simply discussed the mechanism of amylose and amylopectin dissolved in BmimCl. These results confirm that branched chain structure would affect the dissolution of polysaccharides in ionic liquids and the contribution of anions to the dissolution of polysaccharides are dominant. It is further proved that the current signal can be used to judge the charge and structure information of the analyte, and the dissolution mechanism can be assist analyzed at the single molecule level.

Identification of tagged glycans with a protein nanopore

Structural complexity of glycans derived from the diversities in composition, linage, configuration, and branching considerably complicates structural analysis. Nanopore-based single-molecule sensing offers the potential to elucidate glycan structure and even sequence glycan. However, the small molecular size and low charge density of glycans have restricted direct nanopore detection of glycan. Here we show that glycan sensing can be achieved using a wild-type aerolysin nanopore by introducing a facile glycan derivatization strategy. The glycan molecule can induce impressive current blockages when moving through the nanopore after being connected with an aromatic group-containing tag (plus a carrier group for the neutral glycan). The obtained nanopore data permit the identification of glycan regio- and stereoisomers, glycans with variable monosaccharide numbers, and distinct branched glycans, either independently or with the use of machine learning methods. The presented nanopore sensing strategy for glycans paves the way towards nanopore glycan profiling and potentially sequencing.

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.

Glycosaminoglycan Analysis: Purification, Structural Profiling, and GAG-Protein Interactions

Glycosaminoglycans (GAGs) are long, linear polysaccharides that are ubiquitously expressed on the cell surface and in the extracellular matrix of all animal cells. These complex carbohydrates are composed of alternating glucosamine and uronic acids that can be heterogeneously N- and O-sulfated. The arrangement and orientation of the sulfated sugar residues specify the location of distinct ligand binding sites on the cell surface, and their capacity to bind ligands impacts cell growth and development, the ability to form tissues and organs, and normal physiology. The heterogeneous nature of GAGs and their inherent structural diversity across different tissues, cell types, and disease states creates challenges to characterizing their structure and function. Here, we describe detailed methods to investigate GAG-protein interactions in vitro and evaluate the structural composition of two classes of sulfated GAGs, heparan sulfate and chondroitin/dermatan sulfate, using liquid chromatography, mass spectrometry, and radiolabeling techniques. Overall, these methods facilitate the evaluation of GAG structure and function to uncover the unique roles these molecules play in cell biology and human disease.

Comprehensive structural assignment of glycosaminoglycan oligo- and polysaccharides by protein nanopore

Glycosaminoglycans are highly anionic functional polysaccharides with information content in their structure that plays a major role in the communication between the cell and the extracellular environment. The study presented here reports the label-free detection and analysis of glycosaminoglycan molecules at the single molecule level using sensing by biological nanopore, thus addressing the need to decipher structural information in oligo- and polysaccharide sequences, which remains a major challenge for glycoscience. We demonstrate that a wild-type aerolysin nanopore can detect and characterize glycosaminoglycan oligosaccharides with various sulfate patterns, osidic bonds and epimers of uronic acid residues. Size discrimination of tetra- to icosasaccharides from heparin, chondroitin sulfate and dermatan sulfate was investigated and we show that different contents and distributions of sulfate groups can be detected. Remarkably, differences in α/β anomerization and 1,4/1,3 osidic linkages can also be detected in heparosan and hyaluronic acid, as well as the subtle difference between the glucuronic/iduronic epimers in chondroitin and dermatan sulfate. Although, at this stage, discrimination of each of the constituent units of GAGs is not yet achieved at the single-molecule level, the resolution reached in this study is an essential step toward this ultimate goal.

Commercial Low Molecular Weight Heparins - Patent Ecosystem and Technology Paradigm for Quality Characterization

Heparin is a subject of ever-growing interest for laboratory researchers and pharmaceutical industry. One of the driving factors is its critical life-saving drug status, which during the COVID-19 pandemic has assumed a central role in disease treatment and/or prevention. Apart, heparin is one amongst few drugs enjoying a "demand constant" status. In 2020, heparin market size was valued to US$6.5 bn., and given the ongoing stability in the COVID-19 health crisis, it is expected to reach US$11.43 bn. by 2027 with yearly growth rate momentum (CAGR) of 3.9% during the forecast period (Pepi et al., Mol Cell Proteomics 20:100,025, 2021). As patent is a limited monopoly, every year, many patents on low molecular weight heparin (LMWH; a chemically or enzymatically degraded product of unfractionated heparin) are losing market exclusivity worldwide, inviting the generic/biosimilar drug manufacturers to capture market share with cheaper drug products. By tracking patent expiration, drugs in patent litigation, regulatory setbacks for innovator companies (such as those seeking data exclusivity or patent term extension), or other unexpected events affecting market demand and competition, generics can make investment decisions in manufacturing off-patent LMWH drug products of commercial significance. However, given the US Food and Drug Administration (FDA), European Medicine Agency (EMA), Drug Regulatory Authority of Pakistan (DRAP), and other regulatory authorities scientifically rigorous standards for generic/biosimilar LMWH drug products marketing approval, the market is secured and momentous for drug makers that could demonstrate through scientific and clinical dataset that the generic/biosimilar LMWH drug product is of the same quality and purity as the innovator drug product. This study presents an overview of the patent landscape of commercially available LMWHs and advanced analytical techniques for their structural and biochemical characterization for quality control and quality assurance during manufacturing and post-marketing. The study also covers FDA, EMA, Health Canada, and DRAP's current approaches to evaluating the generic/biosimilar LMWH drug products for quality, safety including immunogenicity, and efficacy.

A Nanopore-Based Saccharide Sensor

Saccharides play critical roles in many forms of cellular activities. Saccharide structures are however complicated and similar, setting a technical hurdle for direct identification. Nanopores, which are emerging single molecule tools sensitive to minor structural differences between analytes, can be engineered to identity saccharides. A hetero-octameric Mycobacterium smegmatis porin A nanopore containing a phenylboronic acid was prepared, and was able to clearly identify nine monosaccharide types, including D-fructose, D-galactose, D-mannose, D-glucose, L-sorbose, D-ribose, D-xylose, L-rhamnose and N-acetyl-D-galactosamine. Minor structural differences between saccharide epimers can also be distinguished. To assist automatic event classification, a machine learning algorithm was developed, with which a general accuracy score of 0.96 was achieved. This sensing strategy is generally suitable for other saccharide types and may bring new insights to nanopore saccharide sequencing.

Protein and DNA Yield Current Enhancements, Slow Translocations, and an Enhanced Signal-to-Noise Ratio under a Salt Imbalance

Nanopores are a promising single-molecule sensing device class that captures molecular-level information through resistive or conductive pulse sensing (RPS and CPS). The latter has not been routinely utilized in the nanopore field despite the benefits it could provide, specifically in detecting subpopulations of a molecule. A systematic study was conducted here to study the CPS-based molecular discrimination and its voltage-dependent characteristics. CPS was observed when the cation movement along both electrical and chemical gradients was favored, which led to an ∼3× improvement in SNR (i.e., signal-to-noise ratio) and an ∼8× increase in translocation time. Interestingly, a reversal of the salt gradient reinstates the more conventional resistive pulses and may help elucidate RPS-CPS transitions. The asymmetric salt conditions greatly enhanced the discrimination of DNA configurations including linear, partially folded, and completely folded DNA states, which could help detect subpopulations in other molecular systems. These findings were then utilized for the detection of a Cas9 mutant, Cas9d10a─a protein with broad utilities in genetic engineering and immunology─bound to DNA target strands and the unbound Cas9d10a + sgRNA complexes, also showing significantly longer event durations (>1 ms) than typically observed for proteins.

Selective Translocation of Cyclic Sugars through Dynamic Bacterial Transporter

The selective translocation of molecules through membrane pores is an integral process in cells. We present a bacterial sugar transporter, CymA of unusual structural conformation due to a dynamic N terminus segment in the pore, reducing its diameter. We quantified the translocation kinetics of various cyclic sugars of different charge, size, and symmetry across native and truncated CymA devoid of the N terminus using single-channel recordings. The chemically divergent cyclic hexasaccharides bind to the native and truncated pore with high affinity and translocate effectively. Specifically, these sugars bind and translocate rapidly through truncated CymA compared to native CymA. In contrast, larger cyclic heptasaccharides and octasaccharides do not translocate but bind to native and truncated CymA with distinct binding kinetics highlighting the importance of molecular charge, size and symmetry in translocation consistent with liposome assays. Based on the sugar-binding kinetics, we suggest that the N terminus most likely resides inside the native CymA barrel, regulating the transport rate of cyclic sugars. Finally, we present native CymA as a large nanopore sensor for the simultaneous single-molecule detection of various sugars at high resolution, establishing its functional versatility. This natural pore is expected to have several applications in nanobiotechnology and will help further our understanding of the fundamental mechanism of molecular transport.

PNP Nanofluidic Transistor with Actively Tunable Current Response and Ionic Signal Amplification

Inspired by electronic transistors, electric field gating has been adopted to manipulate ionic currents of smart nanofluidic devices. Here, we report a PNP nanofluidic bipolar junction transistor (nBJT) consisting of one polyaniline (PANI) layer sandwiched between two polyethylene terephthalate (PET) nanoporous membranes. The PNP nBJT exhibits three different responses of currents (quasi-linear, rectification, and sigmoid) due to the counterbalance between surface charge distribution and base voltage applied in the nanofluidic channels; thus, they can be switched by base voltage. Four operating modes (cutoff, active, saturation, and breakdown mode) occur in the collector response currents. Under optimal conditions, the PNP nBJT exhibits an average current gain of up to 95 in 100 mM KCl solution at a low base voltage of 0.2 V. The present nBJT is promising for fabrication of nanofluidic devices with logical-control functions for analysis of single molecules.

Spatiotemporal diversity and regulation of glycosaminoglycans in cell homeostasis and human disease

Glycosaminoglycans (GAGs) are long, linear polysaccharides that are ubiquitously expressed on the cell surface and in the extracellular matrix of all animal cells. These complex carbohydrates play important roles in many cellular processes and have been implicated in many disease states, including cancer, inflammation, and genetic disorders. GAGs are among the most complex molecules in biology with enormous information content and extensive structural and functional heterogeneity. GAG biosynthesis is a nontemplate-driven process facilitated by a large group of biosynthetic enzymes that have been extensively characterized over the past few decades. Interestingly, the expression of the enzymes and the consequent structure and function of the polysaccharide chains can vary temporally and spatially during development and under certain pathophysiological conditions, suggesting their assembly is tightly regulated in cells. Due to their many key roles in cell homeostasis and disease, there is much interest in targeting the assembly and function of GAGs as a therapeutic approach. Recent advances in genomics and GAG analytical techniques have pushed the field and generated new perspectives on the regulation of mammalian glycosylation. This review highlights the spatiotemporal diversity of GAGs and the mechanisms guiding their assembly and function in human biology and disease.

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

Hyaluronan (HA) is an essential carbohydrate in vertebrates that is a potentially robust bioindicator due to its critical roles in diverse physiological functions in health and disease. The intricate size-dependent function that exists for HA and its low abundance in most biological fluids have highlighted the need for sensitive technologies to provide accurate and quantitative assessments of polysaccharide molecular weight and concentration. We have demonstrated that solid state (SS-) nanopore technology can be exploited for this purpose, given its molecular sensitivity and analytical capacity, but there remains a need to further understand the impacts of experimental variables on the SS-nanopore signal for optimal interpretation of results. Here, we use model quasi-monodisperse HA polymers to determine the dependence of HA signal characteristics on a range of SS-nanopore measurement conditions, including applied voltage, pore diameter, and ionic buffer asymmetry. Our results identify important factors for improving the signal-to-noise ratio, resolution, and sensitivity of HA analysis with SS-nanopores.

Solid-state and polymer nanopores for protein sensing: A review

In two decades, the solid state and polymer nanopores became attractive method for the protein sensing with high specificity and sensitivity. They also allow the characterization of conformational changes, unfolding, assembly and aggregation as well the following of enzymatic reaction. This review aims to provide an overview of the protein sensing regarding the technique of detection: the resistive pulse and ionic diodes. For each strategy, we report the most significant achievement regarding the detection of peptides and protein as well as the conformational change, protein-protein assembly and aggregation process. We discuss the limitations and the recent strategies to improve the nanopore resolution and accuracy. A focus is done about concomitant problematic such as protein adsorption and nanopore lifetime.

A Guide to Signal Processing Algorithms for Nanopore Sensors

Nanopore technology holds great promise for a wide range of applications such as biomedical sensing, chemical detection, desalination, and energy conversion. For sensing performed in electrolytes in particular, abundant information about the translocating analytes is hidden in the fluctuating monitoring ionic current contributed from interactions between the analytes and the nanopore. Such ionic currents are inevitably affected by noise; hence, signal processing is an inseparable component of sensing in order to identify the hidden features in the signals and to analyze them. This Guide starts from untangling the signal processing flow and categorizing the various algorithms developed to extracting the useful information. By sorting the algorithms under Machine Learning (ML)-based versus non-ML-based, their underlying architectures and properties are systematically evaluated. For each category, the development tactics and features of the algorithms with implementation examples are discussed by referring to their common signal processing flow graphically summarized in a chart and by highlighting their key issues tabulated for clear comparison. How to get started with building up an ML-based algorithm is subsequently presented. The specific properties of the ML-based algorithms are then discussed in terms of learning strategy, performance evaluation, experimental repeatability and reliability, data preparation, and data utilization strategy. This Guide is concluded by outlining strategies and considerations for prospect algorithms.

Nanoconfinement Effect for Signal Amplification in Electrochemical Analysis and Sensing

Owing to the urgent need for electrochemical analysis and sensing of trace target molecules in various fields such as medical diagnosis, agriculture and food safety, and environmental monitoring, signal amplification is key to promoting analysis and sensing performance. The nanoconfinement effect, derived from nanoconfined spaces and interfaces with sizes approaching those of target molecules, has witnessed rapid development for ultra-sensitive analyzing and sensing. In this review, the two main types of nanoconfinement systems - confined nanochannels and planes - are assessed and recent progress is highlighted. The merits of each nanoconfinement system, the nanoconfinement effect mechanisms, and applications for electrochemical analysis and sensing are summarized and discussed. This review aims to help deepen the understanding of nanoconfinement devices and their effects in order to develop new analysis and sensing applications for researchers in various fields.

Fast Fabrication of Solid-State Nanopores for DNA Molecule Analysis

Solid-state nanopores have been developed as a prominent tool for single molecule analysis in versatile applications. Although controlled dielectric breakdown (CDB) is the most accessible method for a single nanopore fabrication, it is still necessary to improve the fabrication efficiency and avoid the generation of multiple nanopores. In this work, we treated the SiNx membranes in the air–plasma before the CDB process, which shortened the time-to-pore-formation by orders of magnitude. λ-DNA translocation experiments validated the functionality of the pore and substantiated the presence of only a single pore on the membrane. Our fabricated pore could also be successfully used to detect short single-stranded DNA (ssDNA) fragments. Using to ionic current signals, ssDNA fragments with different lengths could be clearly distinguished. These results will provide a valuable reference for the nanopore fabrication and DNA analysis.

Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection

High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SARS-CoV-2. However, RT-PCR requires the extraction of viral RNA from clinical specimens to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity by using nanopores together with artificial intelligence, a relatively simple procedure that does not require RNA extraction. Our final platform, which we call the artificially intelligent nanopore, consists of machine learning software on a server, a portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. We show that artificially intelligent nanopores are successful in accurately identifying four types of coronaviruses similar in size, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2. Detection of SARS-CoV-2 in saliva specimen is achieved with a sensitivity of 90% and specificity of 96% with a 5-minute measurement.

Plasmonic Biosensors for Single-Molecule Biomedical Analysis

The rapid spread of epidemic diseases (i.e., coronavirus disease 2019 (COVID-19)) has contributed to focus global attention on the diagnosis of medical conditions by ultrasensitive detection methods. To overcome this challenge, increasing efforts have been driven towards the development of single-molecule analytical platforms. In this context, recent progress in plasmonic biosensing has enabled the design of novel detection strategies capable of targeting individual molecules while evaluating their binding affinity and biological interactions. This review compiles the latest advances in plasmonic technologies for monitoring clinically relevant biomarkers at the single-molecule level. Functional applications are discussed according to plasmonic sensing modes based on either nanoapertures or nanoparticle approaches. A special focus was devoted to new analytical developments involving a wide variety of analytes (e.g., proteins, living cells, nucleic acids and viruses). The utility of plasmonic-based single-molecule analysis for personalized medicine, considering technological limitations and future prospects, is also overviewed.

Synthetic heparan sulfate standards and machine learning facilitate the development of solid-state nanopore analysis

The application of solid-state (SS) nanopore devices to single-molecule nucleic acid sequencing has been challenging. Thus, the early successes in applying SS nanopore devices to the more difficult class of biopolymer, glycosaminoglycans (GAGs), have been surprising, motivating us to examine the potential use of an SS nanopore to analyze synthetic heparan sulfate GAG chains of controlled composition and sequence prepared through a promising, recently developed chemoenzymatic route. A minimal representation of the nanopore data, using only signal magnitude and duration, revealed, by eye and image recognition algorithms, clear differences between the signals generated by four synthetic GAGs. By subsequent machine learning, it was possible to determine disaccharide and even monosaccharide composition of these four synthetic GAGs using as few as 500 events, corresponding to a zeptomole of sample. These data suggest that ultrasensitive GAG analysis may be possible using SS nanopore detection and well-characterized molecular training sets.

A solid-state nanopore-based single-molecule approach for label-free characterization of plant polysaccharides

Polysaccharides are important biomacromolecules existing in all plants, most of which are integrated into a fibrillar structure called the cell wall. In the absence of an effective methodology for polysaccharide analysis that arises from compositional heterogeneity and structural flexibility, our knowledge of cell wall architecture and function is greatly constrained. Here, we develop a single-molecule approach for identifying plant polysaccharides with acetylated modification levels. We designed a solid-state nanopore sensor supported by a free-standing SiN x membrane in fluidic cells. This device was able to detect cell wall polysaccharide xylans at concentrations as low as 5 ng/μL and discriminate xylans with hyperacetylated and unacetylated modifications. We further demonstrated the capability of this method in distinguishing arabinoxylan and glucuronoxylan in monocot and dicot plants. Combining the data for categorizing polysaccharide mixtures, our study establishes a single-molecule platform for polysaccharide analysis, opening a new avenue for understanding cell wall structures, and expanding polysaccharide applications.

Analysis of the Glycosaminoglycan Chains of Proteoglycans

Glycosaminoglycans (GAGs) are heterogeneous, negatively charged, macromolecules that are found in animal tissues. Based on the form of component sugar, GAGs have been categorized into four different families: heparin/heparan sulfate, chondroitin/dermatan sulfate, keratan sulfate, and hyaluronan. GAGs engage in biological pathway regulation through their interaction with protein ligands. Detailed structural information on GAG chains is required to further understanding of GAG-ligand interactions. However, polysaccharide sequencing has lagged behind protein and DNA sequencing due to the non-template-driven biosynthesis of glycans. In this review, we summarize recent progress in the analysis of GAG chains, specifically focusing on techniques related to mass spectroscopy (MS), including separation techniques coupled to MS, tandem MS, and bioinformatics software for MS spectrum interpretation. Progress in the use of other structural analysis tools, such as nuclear magnetic resonance (NMR) and hyphenated techniques, is included to provide a comprehensive perspective.

A Salt Stimulus-Responsive Nanohydrogel for Controlled Fishing Low-Density Lipoprotein with Superior Adsorption Capacity

A salt-responsive nanoplatform is constructed through a simple tactic by tethering zwitterionic nanohydrogels (NGs) on a carboxylated silica (SiO₂-COOH) framework. Chondroitin sulfate (CS), with a specific recognition effect for low-density lipoprotein (LDL), is modified to NGs by amidation reaction. Water retention and swelling properties of NGs are greatly enhanced in a saline environment attributed to the anti-polyelectrolyte effect. It endows the SiO₂-NGs-CS framework a sensitive salt-responsive property, and thus, more CS moieties are exposed. The controlled adsorption of LDL with an adsorption efficiency of 7.2 to 93% is achieved by adjusting the concentration of MgCl₂ from 0 to 0.1 mol L^-1. SiO₂-NGs-CS exhibits excellent adsorption capacity for fishing LDL, acquiring the highest adsorption capacity of 898.1 mg g^-1. Moreover, SiO₂-NGs-CS shows superior selectivity to the other three proteins with similar isoelectric points (pIs) to LDL. The captured LDL is readily stripped by 0.2% (m/m) SDS with a recovery of 95.4%. The superior separation performance of SiO₂-NGs-CS is demonstrated by the isolation and selective discrimination of LDL from the simulated serum of hypercholesterolemia patients, as illustrated by sodium dodecyl sulfate polyacrylamide gel electrophoresis assays.

Enabling nanopore technology for sensing individual amino acids by a derivatization strategy

Nanopore technology holds remarkable promise for sequencing proteins and peptides. To achieve this, it is necessary to establish a characteristic profile for each individual amino acid through the statistical description of its translocation process. However, the subtle molecular differences among all twenty amino acids along with their unpredictable conformational changes at the nanopore sensing region result in very low distinguishability. Here we report the electrical sensing of individual amino acids using an α-hemolysin nanopore based on a derivatization strategy. Using derivatized amino acids as detection surrogates not only prolongs their interactions with the sensing region, but also improves their conformational variation. Furthermore, we show that distinct characteristics including current blockades and dwell times can be observed among all three classes of amino acids after 2,3-naphthalenedicarboxaldehyde (NDA)- and 2-naphthylisothiocyanate (NITC)-derivatization, respectively. These observable characteristics were applied towards the identification and differentiation of 9 of the 20 natural amino acids using their NITC derivatives. The method demonstrated herein will pave the way for the identification of all amino acids and further protein and peptide sequencing.

Chemically tailoring nanopores for single-molecule sensing and glycomics

A nanopore can be fairly-but uncharitably-described as simply a nanofluidic channel through a thin membrane. Even this simple structural description holds utility and underpins a range of applications. Yet significant excitement for nanopore science is more readily ignited by the role of nanopores as enabling tools for biomedical science. Nanopore techniques offer single-molecule sensing without the need for chemical labelling, since in most nanopore implementations, matter is its own label through its size, charge, and chemical functionality. Nanopores have achieved considerable prominence for single-molecule DNA sequencing. The predominance of this application, though, can overshadow their established use for nanoparticle characterization and burgeoning use for protein analysis, among other application areas. Analyte scope continues to be expanded, and with increasing analyte complexity, success will increasingly hinge on control over nanopore surface chemistry to tune the nanopore, itself, and to moderate analyte transport. Carbohydrates are emerging as the latest high-profile target of nanopore science. Their tremendous chemical and structural complexity means that they challenge conventional chemical analysis methods and thus present a compelling target for unique nanopore characterization capabilities. Furthermore, they offer molecular diversity for probing nanopore operation and sensing mechanisms. This article thus focuses on two roles of chemistry in nanopore science: its use to provide exquisite control over nanopore performance, and how analyte properties can place stringent demands on nanopore chemistry. Expanding the horizons of nanopore science requires increasing consideration of the role of chemistry and increasing sophistication in the realm of chemical control over this nanoscale milieu.

Single-molecule biosensors: Recent advances and applications

Single-molecule biosensors serve the unmet need for real time detection of individual biological molecules in the molecular crowd with high specificity and accuracy, uncovering unique properties of individual molecules which are hidden when measured using ensemble averaging methods. Measuring a signal generated by an individual molecule or its interaction with biological partners is not only crucial for early diagnosis of various diseases such as cancer and to follow medical treatments but also offers a great potential for future point-of-care devices and personalized medicine. This review summarizes and discusses recent advances in nanosensors for both in vitro and in vivo detection of biological molecules offering single-molecule sensitivity. In the first part, we focus on label-free platforms, including electrochemical, plasmonic, SERS-based and spectroelectrochemical biosensors. We review fluorescent single-molecule biosensors in the second part, highlighting nanoparticle-amplified assays, digital platforms and the utilization of CRISPR technology. We finally discuss recent advances in the emerging nanosensor technology of important biological species as well as future perspectives of these sensors.

Real-Time Label-Free Kinetics Monitoring of Trypsin-Catalyzed Ester Hydrolysis by a Nanopore Sensor

Trypsin is an important proteolytic enzyme in the digestive system and its activity is a major indicator for evaluating diseases such as chronic pancreatitis. Here, we present a novel label-free method to detect trypsin kinetics using a nanopore technique. A mutant α-hemolysin (M113R)₇ protein nanopore equipped with a polyamine decorated β-cyclodextrin (am₇β-CD) was employed as a sensing platform for the real-time monitoring of the process of trypsin enzymatic cleavage of a substrate Nα-benzoyl-l-arginine ethyl ester (BAEE) at the single molecule level. Significantly, this sensor can exclusively respond to the current modulation caused by the product and prevent interference from the substrate, thus improving detection sensitivity, and it provides a new scheme to detect enzyme activity for cleaving small molecules.