Aerolysin Nanopore Identification of Single Nucleotides Using the AdaBoost Model

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.

An ultra-low noise amplifier array system for high throughput single entity analysis

Electrochemical measurements at the single entity level provide ultra-sensitive tools for the precise diagnosis and understanding of basic biological and chemical processes. By decoding current signatures, single-entity electrochemistry provides abundant information on charges, sizes, shapes, catalytic performances and compositions. The accuracy of single-entity electrochemistry highly relies on advanced instrumentation to achieve the amperometric resolution at the sub-picoampere level and the temporal resolution at the sub-microsecond level. Currently, it is still a challenge for paralleling amplifiers to allow low-noise and high bandwidth single-entity electrochemical measurements. Herein, we developed a low-noise four-channel electrochemical instrumentation that integrates an Au electrode array with amplifiers in the circuit board. With this amplifier array, we achieved a high bandwidth (>100 kHz) electrochemical measurement. The further practical experiments proved the capability of this amplifier array system in acquiring transient signals from both single-molecule detection with an aerolysin nanopore and single Pt nanoparticle catalysis during the dynamic collision process. Paired with appropriate microfluidic array systems, our instrumentation will enable an extraordinarily high-throughput feature for single-entity sensing.

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.

Recent advances in biological nanopores for nanopore sequencing, sensing and comparison of functional variations in MspA mutants

Biological nanopores are revolutionizing human health by the great myriad of detection and diagnostic skills. Their nano-confined area and ingenious shape are suitable to investigate a diverse range of molecules that were difficult to identify with the previous techniques. Additionally, high throughput and label-free detection of target analytes instigated the exploration of new bacterial channel proteins such as Fragaceatoxin C (FraC), Cytolysin A (ClyA), Ferric hydroxamate uptake component A (FhuA) and Curli specific gene G (CsgG) along with the former ones, like α-hemolysin (αHL), Mycobacterium smegmatis porin A (MspA), aerolysin, bacteriophage phi 29 and Outer membrane porin G (OmpG). Herein, we discuss some well-known biological nanopores but emphasize on MspA and compare the effects of site-directed mutagenesis on the detection ability of its mutants in view of the surface charge distribution, voltage threshold and pore-analyte interaction. We also discuss illustrious and latest advances in biological nanopores for past 2-3 years due to limited space. Last but not the least, we elucidate our perspective for selecting a biological nanopore and propose some future directions to design a customized nanopore that would be suitable for DNA sequencing and sensing of other nontrivial molecules in question.