A Multichannel Pattern-Recognition-Based Protein Sensor with a Fluorophore-Conjugated Single-Stranded DNA Set

Abstract

Recently, pattern-recognition-based protein sensing has received considerable attention because it offers unique opportunities that complement more conventional antibody-based detection methods. Here, we report a multichannel pattern-recognition-based sensor using a set of fluorophore-conjugated single-stranded DNAs (ssDNAs), which can detect various proteins. Three different fluorophore-conjugated ssDNAs were placed into a single microplate well together with a target protein, and the generated optical response pattern that corresponds to each environment-sensitive fluorophore was read via multiple detection channels. Multivariate analysis of the resulting optical response patterns allowed an accurate detection of eight different proteases, indicating that fluorescence signal acquisition from a single compartment containing a mixture of ssDNAs is an effective strategy for the characterization of the target proteins. Additionally, the sensor could identify proteins, which are potential targets for disease diagnosis, in a protease and inhibitor mixture of different composition ratios. As our sensor benefits from simple construction and measurement procedures, and uses accessible materials, it offers a rapid and simple platform for the detection of proteins.

A polymer-based chemical tongue for the non-invasive monitoring of osteogenic stem-cell differentiation by pattern recognition of serum-supplemented spent media

“…In order to quantitatively validate the applicability of the chemical tongue to discriminate the media, two different tests were performed, i.e. , a leave-one-out cross-validation test and a holdout test, 46 which afforded 98% and 96% classification accuracy, respectively (Dataset S2, ESI†). It should also be noted here that this discrimination did not derive solely from the amount of proteins secreted (Fig.…”

A polymer-based chemical tongue for the non-invasive monitoring of osteogenic stem-cell differentiation by pattern recognition of serum-supplemented spent media

“…LDA is a representative pattern-recognition algorithm used to provide graphical output for describing the similarity of the data. 17 In order to quantitatively validate the applicability of the chemical tongue to discriminate the media, two different tests were performed, i.e., a leave-one-out cross-validation test and a holdout test, 46 which afforded 98% and 96% classification accuracy, respectively. It should also be noted here that this discrimination did not derive solely from the amount of proteins secreted (Fig.…”

Protein Recognition Based on Temperature-Stimulated Multiparameter Response Virtual Array Sensing Strategy

“…Fingerprint is formed through pattern recognition, and thus, the target substance can be recognized and classified by combining mathematical statistics. Various array sensors have been reported for the analysis and identification of molecules in organisms, cell surface properties, some specific physiological or pathological molecular mixtures, and screening of drug action mechanisms in the field of biological analysis. − Traditional array sensors always require the construction of multiple sensing units in a small space. Reduction of the number of physical sensor units can not only reduce the size of sensor space but also save the consumption.…”