A facile approach to cross-reactive colorimetric sensor arrays: an application in the recognition of the 20 natural amino acids

Abstract

A very facile approach for the design and fabrication of a colorimetric sensor array, by using only a single indicator–receptor couple at various ratios and concentrations, is described for the first time. As a proof-of-concept application, discrimination and identification of the 20 natural amino acids has been successfully accomplished. Classification analyses demonstrate that the as-fabricated colorimetric sensor array has a high dimensionality and, consequently, has the capability to recognize the 20 natural amino acids. Moreover, the amino acids can be qualitatively and semi-quantitatively detected by combining classification analyses, recognition patterns and corresponding fitting curves. The strategy developed in the current study likely represents a “maximally” simplified approach for design and fabrication of colorimetric sensor arrays, and could be taken full advantage of among investigators in the sensing application field.

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Introduction

The superior features of cross-reactive colorimetric sensor arrays, i.e. those capable of rapid, efficient and simultaneous detection of multiple chemical structures and/or properties of similar analytes, have made them very attractive in the past two decades.^1–5 These systems, based on cross-responsive sensor elements, aim to mimic the mammalian olfactory and gustatory systems by producing composite responses unique to each analyte.^1,2 This kind of molecular recognition does not have to possess specific or selective binding to each target analyte, but instead occurs through a pattern of responses from an array of indicators.^1,3 The design and fabrication of a colorimetric sensor array, however, usually has to select a diverse range of chemically responsive indicators based on detection targets, and this is frequently a laborious and tedious process. Therefore, it is essential to develop a facile approach for design and fabrication of colorimetric sensor arrays so that they can be taken full advantage of in sensing applications.

Indicator displacement assays (IDAs) with simple metal ions or complexes as receptors are typically not very selective, but they are well suited for building colorimetric sensor arrays.^4,5 The arrays previously reported based on IDA were generally designed and fabricated via a number of combinations of selected receptors and indicators to achieve sufficient cross-reactivities for discrimination of multiple chemical structures and/or analytes with analogous properties.⁴ Recently, we noticed that the sensitivity and selectivity of an IDA can be modulated by simply altering ratios and concentrations of a receptor–indicator couple.⁵ These findings can be understood by regarding each combination of a receptor–indicator ratio at a specific concentration as a cross-reactive indicator. This consideration inspired us to explore the possibility, for the first time, to fabricate a colorimetric sensor array by only varying concentrations and ratios of a single indicator–receptor couple. If this approach works, the design and fabrication of a colorimetric sensor array would be “maximally” simplified. A proof-of-concept example of this proposed strategy was carried out by investigating its capability to recognize and discriminate among the 20 natural amino acids.

As key constituents of proteins, amino acids play important roles in many physiological processes,⁶ and their abnormal levels are usually implicated in a variety of diseases.⁷ The affinity of metal ions to amino acids has long been recognized,⁸ and we found that a couple consisting of pyrocatechol violet (PV) and Cu²⁺ can respond to all 20 natural amino acids in pH 7.2 buffer. Thus, the PV–Cu²⁺ couple is an ideal candidate to develop a “maximally” simplified design strategy to fabricate a colorimetric sensor array. Herein, four ratios (a total of twelve combinations) of PV to Cu²⁺ at different concentrations were included to fabricate a 1 × 12 array, and its capabilities for recognizing the 20 natural amino acids were fully investigated. The results of this experiment showed that such a fabricated array can very well discriminate and recognize the 20 natural amino acids at micromolar concentrations in aqueous solution at neutral pH. More importantly, these findings provide evidence for the applicability of the proposed design concept, i.e., simply varying concentrations and ratios of a single indicator–receptor couple, for the fabrication of a colorimetric sensor array.

Experimental

Reagents and materials

Pyrocatechol violet, N-(2-hydroxyethyl)piperazine-N′-(2-ethanesulfonic acid) (HEPES) and the 20 natural amino acids were obtained from Aladdin. Cu²⁺ salt (as perchlorate) was purchased from J&K Scientific. All reagents were of analytical reagent grade and were used as received without any further purification unless otherwise specified. Deionized water was used throughout the experiments.

The concentrations of the stock solutions of pyrocatechol violet and Cu²⁺ were 1.0 mM. The stock solutions of the 20 natural amino acids were as follows: 0.5 mM cysteine (Cys), 0.5 mM histidine (His), 0.5 mM aspartic acid (Asp), 0.5 mM asparagine (Asn), 0.5 mM glutamic acid (Glu), 3.0 mM glycine (Gly), 3.0 mM alanine (Ala), 3.0 mM valine (Val), 3.0 mM leucine (Leu), 3.0 mM isoleucine (Ile), 3.0 mM phenylalanine (Phe), 3.0 mM proline (Pro), 3.0 mM tryptophan (Trp), 3.0 mM serine (Ser), 3.0 mM methionine (Met), 3.0 mM glutamine (Gln), 3.0 mM threonine (Thr), 3.0 mM lysine (Lys), 3.0 mM arginine (Arg) and 200 μM tyrosine (Tyr). A 50 mM stock solution of HEPES at pH 7.2 was prepared by dissolving 1.1916 g HEPES in 80 mL deionized water, and then adjusting the pH to 7.2 by adding an appropriate amount of 1.0 M NaOH; the solution was then diluted to 100 mL with deionized water and mixed thoroughly. The working solutions of all these reagents were diluted from the stock solutions with deionized water.

Instrumentation

For all sensing experiments, imaging of the arrays was performed with a flatbed scanner (Epson Perfection V300). The pH measurements were performed using a PHS-3C pH meter. 96-well plates (Corning 3632) were obtained from Genetimes Technology.

Experimental procedures

Control solutions containing various concentrations of pyrocatechol violet and Cu²⁺ in 10 mM HEPES at pH 7.2 were prepared. Then, 300 μL of each control solution was added to a 96-well plate and the “before” images were acquired with an Epson Perfection V300 flatbed scanner. Working solutions composed of corresponding concentrations of pyrocatechol violet and Cu²⁺, 10 mM HEPES at pH 7.2 and various concentrations of amino acids were prepared. Similarly, 300 μL of each working solution was added to a 96-well plate and the “after” images were then obtained.

All the analyses of the amino acid samples were conducted in quadruplicate experiments. For each experiment, a profile of the changes of color was obtained by subtracting the “before” image from the “after” image using Photoshop. Difference maps were acquired by taking the difference of the red, green and blue (RGB) values from the centre of every indicator spot from the “before” and “after” images. Subtraction of the images yielded a difference vector of 3N dimensions, where N is total number of spots (for our 1 × 12 array, this difference vector is 36-dimensional).

The color change profiles were then compiled into a database library of 36-dimensional vectors (twelve RGB values) and represented a unique fingerprint for each amino acid. Hierarchical cluster analysis and principal component analysis were performed on the database library using the minimum variance for classification.

Results and discussion

Design concept and fabrication of colorimetric sensor arrays

Previous reports have shown that the sensitivity and selectivity of an IDA can be modulated by simply altering ratios and concentrations of a receptor–indicator couple.⁵ Consequently, we decided to examine the possibility, for the first time, to fabricate a colorimetric sensor array by only varying concentrations and ratios of a single indicator–receptor couple. Such a design and fabrication would “maximally” simplify the process of development of a colorimetric sensor array for specific sensing purposes.

To demonstrate the applicability of the above proposed design concept, we employed a pyrocatechol violet (PV) and Cu²⁺ couple, which had been found to respond to all 20 natural amino acids in neutral aqueous solution (pH 7.2 buffer). Herein, a 1 × 12 array was fabricated simply by mixing PV and Cu²⁺ buffer solution at different concentrations and ratios and loading them into the wells of a commercially available 96-well plate (see Fig. 1 for details). To further simplify the sensing process, an ordinary flatbed scanner was used to obtain the array's images. A detailed description of the acquisition and analysis of the data is presented in the Experimental section.⁹

Fig. 1 The chemical structure of pyrocatechol violet (PV) and the selected concentrations of PV and Cu²⁺ for fabricating the 1 × 12 array.

Array's responses to the 20 natural amino acids at 100 μM

First, an extensive test of the array's responses to the 20 natural amino acids (their chemical structures and abbreviations are shown in the (ESI) Fig. S1†), each at a concentration of 100 μM, was carried out. As demonstrated by the difference maps shown in ESI Fig. S2,† this colorimetric sensor array is successful in identifying each amino acid. Even by the naked eye (without statistical analysis), the array responds with a unique pattern to each amino acid. For quantitative comparisons of the color changes of the array, however, we define a 36-dimensional vector (i.e. twelve changes in RGB values of the 1 × 12 array) for each experiment. The high dispersion of the colorimetric sensor array data requires a classification algorithm that uses the full dimensionality of the data. Herein, hierarchical cluster analysis (HCA),¹⁰ which is a model-free method based on the grouping of the analyte vectors according to their spatial distances in their full vector space, is employed. Based on the clustering of the array response data in the 36 dimensional ΔRGB color space, dendrograms formed by HCA are depicted in ESI Fig. S3.† Remarkably, in the quadruplicate experiments, each of the 20 natural amino acids at 100 μM and a control are accurately identified, with no error or misidentification in any of the 84 cases. Principal component analysis (PCA)¹¹ was also performed to provide further evidence for the array's identification capability. As can be seen in Fig. 2, the obtained two-dimensional plot shows excellent separation of the results for each of the 20 natural amino acids, i.e. the results for every amino acid are found in a different location of the plot.

Fig. 2 Two-dimensional principal component analysis plot of the array for the 20 natural amino acids at 100 μM and a control. All of the experiments were performed in quadruplicate in aqueous solution at neutral pH (10 mM HEPES buffer at pH 7.2).

Responses of the array to the 20 natural amino acids at 50 μM

To further evaluate the capability of the array in the recognition of the 20 natural amino acids, the amino acids were also investigated at a lower concentration, i.e. at 50 μM. ESI Fig. S4† shows the corresponding colorimetric response difference maps of the array to the amino acids, and these maps again provide unique patterns that can effectively identify all the amino acids at this concentration. The HCA and PCA (see ESI Figu. S5 and S6†) results at 50 μM are similar with those at 100 μM, i.e. the results for all amino acids and a control are accurately distinguished from one another with no error or misclassifications out of 84 cases (HCA), and are located clearly in separate areas of the PCA plot.

Capability of the array to discriminate between the 20 natural amino acids

The response of a colorimetric sensor array depends primarily on equilibrium interactions between the indicators and the analytes. Consequently, different concentrations of the same analyte present different array responses. By combining the data sets at 50 and 100 μM, we can differentiate the array responses to the same analytes at different concentrations. The HCA for the full database at 50 and 100 μM (ESI Table S1†) indicates that the array can not only accurately identify each amino acid, but can also indicate for each amino acid whether the concentration is 50 or 100 μM, except for Cys, which is believed to have reached an equilibrium with the array at 50 μM (Fig. 3). All the above-described statistical analyses (HCA and PCA) demonstrate that the as-fabricated colorimetric sensor array can effectively identify and discriminate between the 20 natural amino acids at 50 and 100 μM.

Fig. 3 Hierarchical cluster analysis for 20 natural amino acids at 50, 100 μM and a control. All the experiments were performed in quadruplicate in aqueous solution at neutral pH (10 mM HEPES buffer at pH 7.2).

Sensing properties of the array to a single natural amino acid

In the colorimetric sensor array assay, each of the two concentrations of the analyte generally yielded a different unique pattern. This property was tested further, specifically using His and Cys at a greater number of different concentrations. These two amino acids exhibited different recognition patterns at all the investigated concentrations except Cys at 50–100 μM (vide supra, ESI Fig. S7†). HCA shows that His at 5, 10, 20, 30, 50, 80, 100 μM and a control are accurately identified with no error or misclassifications out of 32 cases (Fig. 4). Moreover, PCA reveals that all the investigated concentrations of His and a control are located in well-separated areas of the plot (ESI Fig. S8†). We next examined the color changes of the array (indicated by the total Euclidean distances (ED), i.e. the square root of the sums of the squares of the ΔRGB values) as a function of His concentration. As shown in Fig. 5, the ED increases gradually as the concentration of His increases, and a nice sigmoidal fit can be obtained.

Fig. 4 Hierarchical cluster analysis for His at different concentrations and a control. All of the experiments were performed in quadruplicate in aqueous solution at neutral pH (10 mM HEPES buffer at pH 7.2).

Fig. 5 The total Euclidean distances of the array plotted against different concentrations of His. All experiments were performed in quadruplicate in aqueous solution at neutral pH (10 mM HEPES buffer at pH 7.2); the error bars shown are the standard deviations of the quadruplicate experiments.

The capability of the array to respond to different concentrations of Cys is similar to the capability for His, but only at the lower concentration range of 0–50 μM. HCA shows that 5, 10, 20, 30 and 50 μM of Cys and a control are each accurately identified with no error or misclassifications out of 24 cases (ESI Fig. S9†); PCA displays each of these five concentrations of Cys and a control in well-separated locations of the plot (ESI Fig. S10†); and the color changes of the array (total ED) increase gradually as Cys concentration increases from 0 to 50 μM, with a nice sigmoidal fit obtained (ESI Fig. S11†). In contrast, the responses to Cys at the higher concentrations, between 50 and 100 μM, are highly similar due to the interaction with the array reaching equilibrium.

Taken together, these results indicate that the as-fabricated colorimetric sensor array may be employed for recognition of the 20 amino acids over a broad range of concentrations, and even allow for a semi-quantitative analysis (based on the corresponding fit between the color changes of the array (total ED) and the concentrations of the amino acid).

Conclusions

In conclusion, we have successfully developed a particularly facile approach for the design and fabrication of a colorimetric sensor array by including only a single indicator–receptor couple (CV–Cu²⁺ herein), with the two components at various ratios and concentrations. As a proof-of-concept application of this design strategy, discrimination among, and identification of, the 20 natural amino acids in aqueous solution at neutral pH was successful. Classification analyses (HCA and PCA) demonstrate that the as-fabricated colorimetric sensor array has a high dimensionality and, consequently, can distinctively recognize each of the 20 natural amino acids. Moreover, qualitative and semi-quantitative detection of the amino acids, tested for His and Cys, could be realized by combining HCA/PCA, recognition patterns and corresponding fitting curves. The strategy developed in this current study represents what we consider to be a “maximally” simplified approach for design and fabrication of colorimetric sensor arrays, and can be taken full advantage of among investigators in the sensing field. Further applications of this strategy, such as for peptide and protein detection, are underway in our laboratory.

Acknowledgements

This work was supported by the Natural Science Foundation of China (no. 21277149), Natural Science Foundation of Zhejiang Province of China (no. LR13B050001) and the starting research fund of “Team Talent” from NIMTE (no. Y20402RA03).

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Footnote

† Electronic supplementary information (ESI) available: Chemical structures of the 20 natural amino acids; colorimetric difference maps; HCA; PCA; database for 20 natural amino acids at different concentrations and a control, Fig. S1 to S11 and Table S1. See DOI: 10.1039/c4ra05004e

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