Multiplex Single-Molecule Kinetics of Nanopore-Coupled Polymerases

Abstract

DNA polymerases have revolutionized the biotechnology field due to their ability to precisely replicate stored genetic information. Screening variants of these enzymes for specific properties gives the opportunity to identify polymerases with different features. We have previously developed a singlemolecule DNA sequencing platform by coupling a DNA polymerase to an α-hemolysin pore on a nanopore array. Here, we use this approach to demonstrate a single-molecule method that enables rapid screening of polymerase variants in a multiplex manner. In this approach, barcoded DNA strands are complexed with polymerase variants and serve as templates for nanopore sequencing. Nanopore sequencing of the barcoded DNA reveals both the barcode identity and kinetic properties of the polymerase variant associated with the cognate barcode, allowing for multiplexed investigation of many polymerase variants in parallel on a single nanopore array. Further, we develop a robust classification algorithm that discriminates kinetic characteristics of the different polymerase mutants. As a proof of concept, we demonstrate the utility of our approach by screening a library of ∼100 polymerases to identify variants for potential applications of biotechnological interest. We anticipate our screening method to be broadly useful for applications that require polymerases with altered physical properties.

Machine Learning Assisted Simultaneous Structural Profiling of Differently Charged Proteins in a Mycobacterium smegmatis Porin A (MspA) Electroosmotic Trap

“…Unlike nucleic acids, proteins have diverse charge properties and uneven charge distribution, compact structures, and different shapes. Some recently reported strategies involve conjugation between DNA and peptides to achieve a controlled ratcheting motion of the target peptide for protein sequencing. − In some cases, polymers can serve as nanopore-addressable barcodes, simplifying protein identification. − There have also been many label-free attempts by introducing charged amino acids in the pore lumen to generate electroosmotic flow (EOF). The EOF has a considerable influence on the molecular transport through the nanopore, as it has no preference for the charge of the analytes. − However, charge modifications performed by site-directed mutagenesis may cause severe structural disorder of the nanopore and may lead to a significantly reduced yield of nanopore preparation. , Moreover, unfavorable electrostatic and steric interactions between the negatively charged protein and the positively charged nanopore inner surface may limit the application of the nanopore in simultaneous sensing of proteins with conflicting charge properties .…”

Profiling single-molecule reaction kinetics under nanopore confinement

“…Their reaction rate is calculated by concentration-dependent experiment 26 . This kinetics model has also been expanded to study interactions between the transported analyte and the nanopore, including the electrostatic interaction between ssDNA and DNA polymerase 27 , the hydrophobic interaction between DNA and graphene nanopore 28 and even hydrogen bond of paired bases inside a nanopore 29 . Continuous efforts have been made to understand the contribution of driving force on the interaction kinetics under nanopore confinement [30][31][32][33] .…”

Machine Learning: A Suitable Method for Biocatalysis

“…PCA: bacterial cell behaviour in the presence of organic solvents [104], bioreactor monitoring [105,106], protein sequence clusters [107], enzyme screening [108], mode of action of antibiotics and discovery of new bioactive compounds [109] and analysis of cereals [110] MLR: prediction of secondary protein structure [111], screening of protease inhibitors [112]; LR: effect of active metabolites in a population [113], effect of linear transformation on the input features, as achieved via placing an amino acid at each position or the presence or absence of a mutation [93]; effects of blocks of sequence in a library of chimeric proteins made through recombination [94]. PLS: monitoring [114] and control of bioreactors [115]; development of a biosensor device for analysis of binary mixtures of phenols [116]; and prediction of steroid diffusion across artificial membranes [117].…”