Multiplexed Digital Characterization of Misfolded Protein Oligomers via Solid-State Nanopores

Single molecular profile of proteins sensing by nanopore technology

The characterization of biological macromolecules such as proteins and their interactions are crucial to understanding biological processes, disease diagnosis, and drug design. With the rapid development of proteomics, nanopore technology has emerged potentially as a single-molecule profile for huge amounts of peptides and proteins defined in the biological system, particularly for protein sequencing. This review focuses on recent advances in nanopore sensing of proteins and peptides, involving protein dynamic interactions, protein fingerprinting, and protein sequencing. These progresses will provide new perspectives to decipher the mechanisms of protein structure and function, and serve much more possible applications.

Artificial intelligence based advancements in nanomedicine for brain disorder management: an updated narrative review

Nanomedicines are nanoscale, biocompatible materials that offer promising alternatives to conventional treatment options for brain disorders. The recent technological developments in artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), are transforming the nanomedicine field by improving disease diagnosis, biomarker identification, prognostic assessment and disease monitoring, targeted drug delivery, and therapeutic intervention as well as contributing to computational and methodological developments. These advancements can be achieved by analysis of large clinical datasets and facilitating the design and optimization of nanomaterials for in vivo testing. Such advancement offers exciting possibilities for the improvement in the management of brain disorders, including brain cancer, Alzheimer's disease, Parkinson's disease, and multiple sclerosis, where early diagnosis, targeted delivery, and effective treatment strategies remain a great challenge. This review article provides an overview of recent advances in AI-based nanomedicine development to accelerate effective and quick diagnosis, biomarker identification, prognosis, drug delivery, methodological advancement and patient-specific therapies for managing brain disorders.

Biofunctionalized nanomaterials for Parkinson's disease theranostics: potential for efficient PD biomarker detection and effective therapy

α-Synuclein (α-Syn) is a primary pathological indicator for Parkinson's disease (PD). The α-Syn oligomer is even more toxic and is responsible for PD. Hence, identifying α-Syn and its oligomers is an interesting approach to diagnosing PD. The prevention strategies for oligomer formation could be therapeutic in treating PD. Various conventional strategies have been developed for the management of PD. However, their clinical applications are limited due to toxicity, off-targeting, side effects, and poor bioavailability. Recently, nanomaterials have gained significant attention due to unique physicochemical characteristics such as nanoscale size, large surface area, flexibility of functionalization, and ability to protect and control a loaded payload. Functionalizing the surface of nanoparticles with a desired targeting agent could offer targeted delivery of the payload at the site of action due to specificity and selectivity against complementary molecules. Among various functionalization approaches, biomolecule-functionalized nanomaterials offer benefits such as enhanced bioavailability, improved internalization into target cells through receptor-mediated endocytosis, and delivery of therapeutics across the BBB (blood-brain barrier). In this review, we initially discussed the major milestones related to PD and highlighted the therapeutic strategies focused on clinical trials. The strategies of biomolecule functionalization of nanomaterials and their application in detecting and preventing α-Syn oligomer for the diagnosis and therapy of PD, respectively, have been reviewed comprehensively. Ultimately, we have outlined the conclusions, highlighted the limitations and challenges, and provided insight into future perspectives and alternative approaches that must be investigated.

Controlled Sensing of User-Defined Aptamer-Based Targets Using Scanning Ionic Conductance Spectroscopy

Solid-state nanopores offer the possibility of detecting disease biomarkers in early diagnostic applications. Standard approaches harness fingerprinting, where protein targets are bound to DNA carriers and detected in free translocation with a solid-state nanopore. However, they suffer from several drawbacks, including uncontrolled fast translocations, which lead to low detection accuracy and a low signal-to-noise ratio (SNR). This has hampered their application in clinical settings. Here, we propose a nanopore-based system capable of sensing selected molecules of interest from biological fluids by harnessing programmable aptamer sequences attached to DNA carrier systems that are tethered to glass surfaces. This allows for spatial and velocity control over translocation in the x, y, and z directions and enables the repeated scanning of the same analyte. The scanning ion conductance spectroscopy (SICS) based approach distinguishes itself from standard nanopore-based approaches with its ability to repeatedly scan the same aptamer molecule target site more than 5 times. We designed a DNA carrier with multiple binding sites for different aptamers to increase the yield of the experiment. Our approach achieves a detection rate of up to 74%, significantly higher than the 14% achieved with standard solid-state nanopore measurements. The strong spatial control also allows for significantly increased densities of aptamer target sites along the same DNA carrier, thereby paving the way for multiplexed sensing. The system offers user-defined programmability with different aptamer sequences, potentially expanding the use of our system to sense other disease biomarkers.

Detection of protein oligomers with nanopores

Powerful single-molecule approaches have been developed for the accurate measurement of protein oligomers, but they are often low throughput and limited to the measurement of specific systems. To overcome this problem, nanopore-based detection holds the promise of providing the high throughput, broad applicability, and accuracy necessary to characterize protein oligomers in a variety of contexts. Nanopores provide accuracy comparable with that of state-of-the-art single-molecule detection methods, but with the added potential for fast and accurate measurements that may be amenable to industrial-scale manufacture. Key to enabling this expansion is combination with other emerging technologies such as DNA nanostructure tagging, machine learning-enabled signal analysis, and innovative detection device manufacture. Together, these technologies could enable widespread adoption of nanopore-based sensing in oligomer detection, revolutionizing diagnostics and biomarker detection in protein misfolding diseases.

Accurate Molecular Sensing based on a Modular and Customizable CRISPR/Cas-Assisted Nanopore Operational Nexus (CANON)

Solid-state nanopore is a promising single molecular detection technique, but is largely limited by relatively low resolution to small-size targets and laborious design of signaling probes. Here we establish a universal, CRISPR/Cas-Assisted Nanopore Operational Nexus (CANON), which can accurately transduce different targeting sources/species into different DNA structural probes via a "Signal-ON" mode. Target recognition activates the cleavage activity of a Cas12a/crRNA system and then completely digest the blocker of an initiator. The unblocked initiator then triggers downstream DNA assembly reaction and generate a large-size structure easy for nanopore detection. Such integration of Cas12a/crRNA with DNA assembly establishes an accurate correspondence among the input targets, output DNA structures, and the ultimate nanopore signals. We demonstrated dsDNA, long RNA (i.e., Flu virus gene), short microRNA (i.e., let-7d) and non-nucleic acids (i.e., Pb2+) as input paradigms. Various structural assembly reactions, such as hybridization chain reaction (HCR), G-HCR and duplex polymerization strategy (DPS), are adapted as outputs for nanopore signaling. Simultaneous assay is also verified via transferring FluA and FluB genes into HCR and G-HCR, respectively. CANON is thus a modular sensing platform holding multiple advantages such as high accuracy, high resolution and high universality, which can be easily customized into various application scenes.

Solid-State Nanopore Real-Time Assay for Monitoring Cas9 Endonuclease Reactivity

The field of nanopore sensing is now moving beyond nucleic acid sequencing. An exciting avenue is the use of nanopore platforms for the monitoring of biochemical reactions. Biological nanopores have been used for this application, but solid-state nanopore approaches have lagged. This is due to the necessity of using higher salt conditions (e.g., 4 M LiCl) to improve the signal-to-noise ratio which completely abolish the activities of many biochemical reactions. We pioneered a polymer electrolyte solid-state nanopore approach that maintains a high signal-to-noise ratio even at a physiologically relevant salt concentration. Here, we report the monitoring of the restriction enzyme SwaI and CRISPR-Cas9 endonuclease activities under physiological salt conditions and in real time. We investigated the dsDNA cleavage activity of these enzymes in a range of digestion buffers and elucidated the off-target activity of CRISPR-Cas9 ribonucleoprotein endonuclease in the presence of single base pair mismatches. This approach enables the application of solid-state nanopores for the dynamic monitoring of biochemical reactions under physiological salt conditions.

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.

Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning

Machine learning methods hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been particularly challenging. To address this problem, we describe here a machine learning approach to identify small molecule inhibitors of α-synuclein aggregation, a process implicated in Parkinson's disease and other synucleinopathies. Because the proliferation of α-synuclein aggregates takes place through autocatalytic secondary nucleation, we aim to identify compounds that bind the catalytic sites on the surface of the aggregates. To achieve this goal, we use structure-based machine learning in an iterative manner to first identify and then progressively optimize secondary nucleation inhibitors. Our results demonstrate that this approach leads to the facile identification of compounds two orders of magnitude more potent than previously reported ones.

Nanoconfined Electrokinetic Chromatography (NEC): Gradient Separation and Sensing of Short DNA Fragments at the Single-Molecule Level

Glass nanopipets have been demonstrated to be a powerful tool for the sensing and discrimination of biomolecules, such as DNA strands with different lengths or configurations. Despite progress made in nanopipet-based sensors, it remains challenging to develop effective strategies that separate and sense in one operation. In this study, we demonstrate an agarose gel-filled nanopipet that enables hyphenated length-dependent separation and electrochemical sensing of short DNA fragments based on the electrokinetic flow of DNA molecules in the nanoconfined channel at the tip of the nanopipet. This nanoconfined electrokinetic chromatography (NEC) method is used to distinguish the mixture of DNA strands without labels, and the ionic current signals measured in real time show that the mixed DNA strands pass through the tip hole in order according to the molecular weight. With NEC, gradient separation and electrochemical measurement of biomolecules can be achieved simultaneously at the single-molecule level, which is further applied for programmable gene delivery into single living cells. Overall, NEC provides a multipurpose platform integrating separation, sensing, single-cell delivery, and manipulation, which may bring new insights into advanced bioapplication.