Noise Spectroscopy Analysis for Estimation of a Specific Biomolecule in a Complex Mixture Using Solid-State Nanopore
| Autor: | Aneesh M. Joseph, Hrilina Ghosh, N. Das, N. Samanta, Chirasree RoyChaudhuri |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
chemistry.chemical_classification
Silicon Chemistry Biomolecule Analytical chemistry Solid-state chemistry.chemical_element Noise spectroscopy 02 engineering and technology 010402 general chemistry 021001 nanoscience & nanotechnology 01 natural sciences 0104 chemical sciences Computer Science Applications Nanopore Antigen Electrical and Electronic Engineering 0210 nano-technology Spectroscopy Constant (mathematics) |
| Zdroj: | IEEE Transactions on Nanotechnology. 17:1138-1145 |
| ISSN: | 1941-0085 1536-125X |
| DOI: | 10.1109/tnano.2018.2866870 |
| Popis: | This paper presents a noise spectroscopy analysis of the current traces recorded in a functionalized silicon oxide nanopore in presence of specific antigen (Hep-B), nonspecific antigen (BSA), and their complex mixture for the first time. It is observed that though the on and off dwell times can differentiate nonspecific antigen from specific antigen in pure buffer, an approximate quantification of the specific antigen with low-dissociation constant of the receptor–ligand pair, becomes almost impossible in complex mixture. This has been ascribed to the significant overlap in the current blockade sensitivity values between the different concentration ranges of the specific antigen. On the contrary, a noise spectroscopy analysis shows a Lorentzian spectrum in presence of specific antigen with a distinct shift in the roll-off frequency, such that upto 1-nM BSA concentration; it has been possible to estimate the concentration of the specific antigen even for 1-pM Hep-B. However, for BSA concentration greater than 1 nM, the roll-off frequency for a particular concentration of specific antigen starts deviating from its value in pure buffer and overlaps with other concentration range. This problem has been addressed by processing the fractional change in current blockade and roll-off frequency by a partial least square-discriminant analysis based multivariate statistical model. It has been observed that the learning model yields 91.5% correct classification with the solutions, and has been able to predict the concentration of Hep-B quite closely even for a low value of 1 pM in presence of 100 nM concentration of BSA. |
| Databáze: | OpenAIRE |
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