Accepted Manuscript Title: A Colorimetric Sensor Array for Detection and Discrimination of Biothiols based on Aggregation of Gold Nanoparticles Author: Forough Ghasemi M.Reza Hormozi-Nezhad Morteza Mahmoudi PII: DOI: Reference: S0003-2670(15)00476-6 http://dx.doi.org/doi:10.1016/j.aca.2015.04.011 ACA 233854 To appear in: Analytica Chimica Acta Received date: Revised date: Accepted date: 27-1-2015 31-3-2015 5-4-2015 Please cite this article as: Forough Ghasemi, M.Reza Hormozi-Nezhad, Morteza Mahmoudi, A Colorimetric Sensor Array for Detection and Discrimination of Biothiols based on Aggregation of Gold Nanoparticles, Analytica Chimica Acta http://dx.doi.org/10.1016/j.aca.2015.04.011 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A Colorimetric Sensor Array for Detection and Discrimination of Biothiols based on Aggregation of Gold Nanoparticles Forough Ghasemi1, M. Reza Hormozi-Nezhad*1, 2 and Morteza Mahmoudi*3, 4, 5 1 Department of Chemistry, Sharif University of Technology, Tehran, 11155-9516, Iran 2 Institute for Nanoscience and Nanotechnology, Sharif University of Technology, Tehran, Iran 3 Department of Nanotechnology and Nanotechnology Research Center, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran 13169-43551, Iran 4 Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California 94305-5101, United States 5 Cardiovascular Institute, Stanford University School of Medicine, Stanford, California 94305-5101, United States *Corresponding authors: (M.R.H) email: hormozi@sharif.edu; (M .M .) email: mahmoudi@stanford.edu 1 Graphical abstract Highlights     We have developed a simple colorimetric sensor array for detection of biological thiols. We obtained discrimination of Cys, GSH and GSSG on a score plotand HCA dendrogram. Visual discrimination is achieved by color difference maps. This approach show high selectivity toward Cys, GSH and GSSG over amino acids. 2 Abstract: Developments of sensitive, rapid, and cheap systems for identification of a wide range of biomolecules have been recognized as critical need in biology field. Here, we introduce a simple colorimetric sensor array for detection of biological thiols, based on aggregation of three types of surface engineered gold nanoparticles (AuNPs). The low-molecular-weight biological thiols shows high affinity to the surface of AuNPs; this causes replacement ofAuNPs’ shells with thiol containing target molecules leading to the aggregation of the AuNPs through intermolecular electrostatic interaction or hydrogen-bonding. As a result of the predetermined aggregation, color and UV-visible spectra of AuNPs are changed. We employed the digital mapping approach to analyze the spectral variations with statistical and chemometric methods, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). The proposed array could successfully differentiate biological molecules (e.g., cysteine, glutathione and glutathione disulfide) from other potential interferences such as amino acids in the concentration range of 10-800 mol L-1. Keywords: Gold nanoparticle, biothiol, aggregation, colorimetric sensor array, chemometric method 3 1. Introduction Biological thiols (e.g., Cysteine (Cys) and Gluthatione (GSH)) are associated with key functions in biological systems [1]. The deficiency of Cys, the only amino acid found in proteins contained thiol group, is caused slow growth in children, depigmentation of hair, edema, lethargy, liver damage, loss of muscle and fat, skin lesions, and weakness [2]. In addition, the elevated concentration of Cys might cause neurotoxicity [3]. Beside Cys, GSH (a tripeptide (L-glutamyl-L-cysteinly glycine)) and the most abundant intracellular nonprotein thiol, plays important roles in cellular defense against oxidative stress [4, 5] and intracellular signal transduction [6]. Oxidative stress condition lead to the formation of glutathione (in reduced form (GSH)) which could be further transformed to the oxidized form, glutathione disulfide (GSSG) [7]. Therefore, GSH to GSSG ratio is an oxidative stress indicator and, thus, can be used as an effective measure of a diseased state [8]. Consequently, one can expect that it is of crucial importance to develop simple and sensitive methods for detection and discriminating of these compounds. To this end, various analytical procedures (e.g., electrochemistry [9, 10], high-performance liquid chromatography [11], fluorimetric [12], and spectrophotometry [13]) were developed to detect of the biological thiols. Beside of their good capabilities for detection of different thiols, these methods often suffer from a variety of disadvantages, such as use of sophisticated, expensive instruments and time consuming techniques also require derivatization with synthetic chemodosimeters [14, 15]. Thus, there is a need for development of sensitive, rapid, and cheap systems for identification of biological thiols. By mimicking the human olfactory/ gustatory system, scientist creates artificial nose/tongue for specific recognition of diverse type of analytes using nonspecific interactions profiles [16]. More specifically, chemical tongue/nose approach is used to produce a specific pattern for individual analyte, rather than using selective interactions, to achieve multi-dimensional detection [17-21]. Due to their diverse advantages such as low cost, variety of detection modes (e.g., change in absorbance and color, optical layer thickness, and light polarization) and diversity of collection devices (e.g., CCD, CMOS cameras, photodiodes, scanners, and spectrophotometer) [22], the optical based array sensors (compared to other type of sensor arrays sensor arrays (e.g., fluorescence, potential, resistance, and current)) are able to detect a wide range of analytes (e.g., toxic gases [23-25], explosives [26-28] and organic molecules 4 [29, 30]), complex mixtures (e.g., foods [31, 32], beverages [33-36], and pharmaceutical products [37]). Colloidal plasmonic nanoparticles (NPs), which are mainly based on gold and silver, exhibit highly intensive color in the visible region, mainly due to the localized surface plasmon resonances (LSPR); the LSPR arises from the collective oscillations of conduction band electrons induced by the interaction of electromagnetic radiations [38]. The extremely large molar extinction coefficients of these NPs [39], in the visible region, make them a promising candidate as appropriate probes for colorimetric assays. Colorimetric sensing strategies using plasmonic nanomaterials are usually based on the change of optical properties because of their aggregations and morphology changes [40]. Although aggregation-based detection approaches are simple, rapid, and applicable to a wide range of analytes, it has not enough selectivity to discriminate various type of biomolecules with the same backbone [41, 42]. Accordingly, the development of novel and facile method, that could discriminate analytes with close physical and chemical properties, is desirable. Here, we report a liquid sensor array for detection and classification of biological thiols, based on aggregation of AuNPs with different coatings as sensor elements. Thiol mediated aggregation of AuNPs was visualized via UV-visible spectra, transmission electron microscopy (TEM) and dynamic light scattering (DLS). The spectral changes, as a consequence of aggregation of AuNPs, made a unique pattern of spectra for each analyte and allowed for the selective detection and discrimination of biological molecules such as Cys, GSH and GSSG. In other words, instead of using the spectrum of one kind of AuNP, the spectra of a different kind of AuNPs could make a specific pattern for each thiol. To analyze the cumulative array responses, color difference map and chemometric methods, including hierarchical cluster analysis (HCA) and principal component analysis (PCA), were employed. 5 2. Experimental 2.1. Chemicals Hydrogen tetrachloroaurate (HAuCl4. 3H2O (99.5%), cetyltrimethylammonium bromide (CTAB, 99%), L-ascorbic acid (AA, 99.9%) were obtained from Sigma. Sodium borohydride (NaBH4, 98%), sodium citrate (99%), glutathione (Glu, 98%), Glutathione disulfide (GSSG, 98%), cystine (Cys, 97%) and other amino acids were purchased from Merck. Milli-Q grade water, with resistivity of 18.2 MΩ, was used in all experiments. The human blood plasma sample was obtained from the Tehran Blood Transfusion Service (Tehran, Iran). 2.2. Instrumentation Absorbance measurements were performed on a Lambda (Perkin Elmer, USA) spectrophotometer with the use of 1.0cm glass cell. All the spectra were recorded at room temperature. Measurements of pH were made with a Denver Instrument Model of 270 pH meter equipped with a Metrohm glass electrode. Size distributions of the particles were obtained using Zetasizer Viscotec 802 at ambient temperature. TEM images were employed (PHILIPS MC 10 TH microscope at an acceleration voltage of 100 kV). 2.3. Synthesis of AuNPs with different coatings 2.3.1. Synthesis of CTAB coated AuNPs CTAB coated NPs were prepared according to the procedure described previously with a slightly modification [43, 44]. Typically, seed-1 solution was prepared by the addition of icecold NaBH4 (600 L, 0.01mol L-1) into solution including HAuCl4.3H2O (250 L, 0.01mol L1 ) and CTAB (10mL, 0.1mol L-1). This solution must be stirred for 20min and could be used within 2-5h after preparation. For preparation of AuNPs, 100 L of 0.1mol L-1 ascorbic acid was added to 15mL of growth solution (45mL of 0.1mol L-1 CTAB and 0.500mL of 0.01mol L-1 HAuCl4.3H2O). Then, 5mL seed-1 was added and stirring continued for 10min. The asprepared nanospheres were used as seed-2 to synthesis bigger nanospheres. 45mL of the growth solution was mixed with 250 L of 0.1mol L-1 ascorbic acid solution, then 5.0mL from seed-2 was added and stirring continued for 10min. As-prepared AuNPs exhibited a characteristic surface plasmon band centered at 528nm. 6 2.3.2. Synthesis of citrate coated AuNPs Citrate coated AuNPs were synthesized according to the modified Turkevich method [45, 46]. Briefly, 50mL of HAuCl4 solution (1.0mmol L-1) was heated to boiling and then 5mL of sodium citrate (38.8mmol/L) was added. The solution was refluxed for 30min and then allowed to cool and stored at 4°C temperature. As-prepared AuNPs exhibited a characteristic surface plasmon band centered at 520nm. 2.3.3. Synthesis of NaBH4 coated AuNPs NaBH4 coated AuNPs were synthesized by the reduction of HAuCl4 solution using NaBH4 [47]. Typically, 100 L of HAuCl4/HCl solution (both 50.0mmol L-1) was added to 9.6mL DI water. Then, 400 L of NaBH4/NaOH solution (both 50.0mmol L-1) was added, and further stirred for 15min. As-prepared AuNPs exhibited a characteristic surface plasmon band centered at 513nm. 2.4. Design of nanosensor array 2.4.1. CTAB coated AuNPs: The different concentrations of analyte were added to a solution contained CTAB coated AuNP with a final concentration 0.34nmol L-1 (calculated via Beer– Lambert law[48]), NaCl with a final concentration 100mmol L-1 as the total volume was constant for all experiments with pH 4.2. All spectra were recorded nine minutes after the addition of the last drop of analyte. 2.4.2. Citrate coated AuNPs: A solution contained citrate coated AuNP with a final concentration 1.36nmol L-1, NaCl with final concentration 5mmol L-1 was prepared. After three minutes, the different concentrations of analytes were added as the total volume was constant for all experiments with pH 5.1. All spectra were recorded nine minutes after the addition of the last drop of analyte. 2.4.3. NaBH4 coated AuNPs: A solution contained NaBH4 coated AuNP with a final concentration 508nmol L-1, NaCl with final concentration 20.0mmol L-1 was prepared. After three minutes, the different concentrations of analytes were added as the total volume was constant for all experiments with pH 7.2. The spectra were recorded after nine minutes of adding each analyte. 7 2.5. Preparation of human plasma samples Trichloroacetic acid (TCA) was added to the freshly thawed plasma sample and mixed well to precipitate proteins. After centrifuging at ~14000 rpm for 10 min, the supernatant was diluted 20 times and the subsequent analysis was carried out under the optimized conditions. 3. Results and discussion 3.1. Design criteria The main aim of this research was to design an optical sensor array for detection and discrimination of bio-thiol compounds including Cys, GSH, and GSSH. Biological thiols have high affinity towards the surface of AuNPs [40, 49-53] that can be finely described by the hard–soft acid-base (HSAB) theory [49]. It is well recognized that the displacement of the citrate, NaBH4 and CTAB group shells, which have lower affinity to surface of AuNPs, with biological thiols (e. g. Cys, GSH and GSSH) induces the aggregation process; the aggregations were happened because of the hydrogen binding or electrostatic interaction between non-covalently adsorbed thiols. As a result of aggregation, changes in color and UVvisible spectra of AuNPs were observed. Since interactions between AuNPs and thiols were not specific, we used AuNPs with different coatings (i.e., CTAB, citrate and NaBH4) and sizes as cross-responsive sensor elements; using such a sensor, we could obtain a distinct pattern of colorimetric responses for selective detection and discrimination among Cys, GSH, and GSSH. In order to assess the AuNP aggregation in different pH ranges (acidic and neutral), the particles were coated with different stabilizers. As the citrate and NaBH4 coated AuNPs were stable only in neutral and basic pH, the CTAB coated NPs were used to study the sensor responses at acidic pH. The as-prepared AuNPs were characterized by UV–Vis spectroscopy, DLS and TEM. UV-Vis spectra and TEM images of AuNPs with different coatings are presented in Figure 1. It is worth mentioning that to avoid the problem of false peaks in DLS results [54], particle number and intensity size distribution were used to investigate the average size of AuNPs before and after aggregation processes, respectively. TEM images demonstrated the formation of monodispersed NPs with the mean diameter of 15, 20, and 2.5 8 nm for citrate-, CTAB-, and NaBH4-coated AuNPs, respectively. The results of DLS measurements for all NPs are shown in Figure S1 of the supporting information (SI). Since the NPs are sensitive to their environment [55, 56], it was required to provide particular conditions that the sensor could only respond to the targeted analytes. Therefore, the effective parameters on sensor response including pH and ionic strength were investigated to find optimum circumstances. 3.1.1 Effect of pH Due to the presence of hydroxyl (–OH), carboxyl (–COOH), and amine (–NH2) groups in biomolecules structure, pH had a crucial role in the aggregation process. The as-prepared citrate coated AuNPs were stable at pH above 4.5 providing columbic repulsion between negatively charged AuNPs [57]. In basic and neutral pH, insignificant spectral and color evolutions were observed even with high concentrations of biothiols. Therefore, pH of 5.1 was selected as an optimal pH to provide both NPs stability (see Figure S2 of SI) and significant aggregation for biothiols. CTAB coated AuNPs were used at pH 4.2 because we expected to have considerable aggregation at low pH values. The pH of as-prepared NaBH4 coated AuNPs was 9.3. No aggregation was observed at that pH; we also noticed that NPs were unstable at pH values below 7.0. Taken together, by considering these limitations, pH 7.2 was selected for further experiments relating to NaBH4 coated AuNPs. 3.1.2 Effect of NaCl Concentration SPR band and aggregation process could be affected by the concentration of electrolyte [58, 59]. To determine the best concentration of NaCl (as electrolyte), different concentrations of NaCl were added to AuNPs and UV-visible spectra were recorded over time. The concentrations of 5mmol L-1, 20mmol L-1, and 100mmol L-1 were selected as optimized salt for citrate, NaBH4 and CTAB coated AuNPs, respectively. There were no trace of spectral changes in AuNPs after adding mentioned concentrations of NaCl (see Figure S3 of SI); it is noteworthy that citrate and NaBH4 coated AuNPs, no further aggregation were detected after three min upon addition of NaCl. Thus, we added the analyts 3min after addition of NaCl. 3.2. Colorimetric sensor array responses Biomolecules with different concentrations ranging from 10 to 800 mol L-1 were exposed to different types of AuNPs solutions and the spectral responses were recorded (400 to 780 nm wavelength range, see Figure S4 of SI). As representative, the responses of various AuNPs to 9 the different thiols (500 mol L-1) are shown in Figure 2. In general, the colors of the solutions were changed from reddish to blue (or purple) after adding thiols to colloidal gold solutions, as a result of NP aggregation. As seen in Figure 2, the observed differences in the NP responses were mainly related to the intensity of aggregation and the spectral evolution. Analyte-mediated aggregations were measured by DLS (see Figure S5-7 of SI). For Cysteine as a model, TEM images of AuNPs after aggregation are shown in Figure S8 of SI. In the case of citrate coated AuNPs, GSSG induced higher aggregates compared to GSH (see Figure S4a of SI). After adding GSH, the average diameter of the citrate coated particles was increased to ~170 nm (Figure S6c of SI), while it was enhanced to ~1200nm by exposure to GSSG (Figure S6d of SI). Due to their unique structures, each GSSG has more chances to link two NPs compared to GSH and, hence, GSSG mediated more aggregation when they were used in the exact same concentrations. Thus, we suggest that the higher aggregation mediated by GSSG (compared to GSH) is related to their more functional groups like –NH2 and –COOH. No significant aggregation was observed upon addition of GSSG to CTAB coated AuNPs (Figure S5c of SI). It can be suggested that large size of the GSSG could prohibit its replacement with CTAB bilayer at the surface of AuNPs. Compared to GSH and GSSG, Cys caused more aggregation in all kinds of AuNPs. Thiol group in Cys structure, with lower spatial hindrance, can quickly bind to the surface of the AuNPs and lead to the formation of extra aggregation [40]. Furthermore, in the case of citrate coated AuNPs (~ pH 5), Cys is in its zwitterionic form which is the best form to interact with AuNPs through electrostatic interactions [60]. For CTAB and citrate coated AuNPs, the intensity of SPR band was changed and a new broad band was appeared because of the near-field coupling in the resonant wavelength peak of the interacting particles [61]. In the case of NaBH4 coated AuNPs, band broadening and red shift of SPR were observed (Figure 2). These differences could be related to variation in sizes of individual NPs and arrangement of NPs in the aggregates [62]. Transverse and longitudinal SPR, two SPR modes, were located around SPR position of individual AuNPs and longer wavelengths, respectively [63]. The longitudinal SPR was attributed to linear-chainlike aggregates of AuNPs [64, 65]. Thus, based on the UV-visible spectra, linear-chainlike aggregates can be expected for CTAB and citrate coated AuNPs; similarly, non-linear aggregates were achieved for NaBH4 coated AuNPs. Wenfang Sun et al. [62] investigated aggregation of AuNPs, with different size and 10 the same coating, induced by electrolytes. They only observed shift and broadening of SPR was found for 5nm AuNPs together with developing of a new band at longer wavelength for 20nm AuNPs. Citrate and CTAB coated AuNPs with a size of >10nm showed the second band in longer wavelengths and NaBH4 coated AuNPs with a size <10nm did not show this band. To confirm the effect of size, we employed seed-2 (NPs used in the synthesis of CTAB coated AuNPs) having smaller size compared to the CTAB coated AuNP in sensor. As can be seen in Figure 3, the spectral evolution of seed-2 was similar to NaBH4 coated AuNPs regarding to broadening and shift of SPR. To this end, the different spectral evolution of AuNPs with different coating can be attributed to their sizes. In general, a facile and rapid way for identification and discrimination of thiols was provided using the spectral changes of AuNPs after interaction with thiols. 3.3. Detection and discrimination of biomolecules 3.3.1 Statistical analysis Standard chemometric techniques, HCA and PCA, were employed not only to analysis the obtained data but also to measure the array response. HCA method produces a two dimentional pictural representation of the clustering process and illustrates the final result as a dendrogram. PCA reduce the dimensionality of a parameter space and accommodate data graphically in two dimensions[66]. Data matrix is consisted of A values (i.e., difference between absorbance after adding analyte and absorbance of AuNPs, as blank), at the wavelengths from 400 to780 nm. HCA was performed using the minimum variance (Ward’s) method for different thiols at concentrations ranging from 10 to 800 mol L-1 for Cys and 200 to 700 mol L-1 for GSSG and GSH (see Figure 4 for details). Biomolecules were accurately classified without any misclassification (in triplicate trials). Distinct patterns at all mentioned concentrations of thiols demonstrated an easy method to quantify thiol concentration. In addition, we obtained excellent discrimination of analytes on a two-dimensional PCA plot (see Figure 5). In the scores plot, the horizontal PC1 axis captured 87.7% of the variance and the vertical PC3 axis captured 2.5% of the variance. Spacing between classes demonstrates recognition capability of the sensor. We determined degree-of-class-separation [67] between clusters on a PCA scores plot for both PC1 versus PC2 and PC1 versus PC3 (see Table S1 of SI). The degree-of-class-separation between GSH and GSSH samples was negligible using the first two principal components (see scores plot in Figure S9 of SI). Therefore, the PCA 11 scores plot depicted from PC1 versus PC3 were chosen to increase the degree-of-classseparation between GSH and GSSH classes. The rate of aggregation for biomolecules is varied mainly because of the differences in the number and structure of functional groups in biomolecule structures [40]. Taking advantage of differences in rate of aggregation, the spectral responses were recorded in time intervals of 3 min, after insertion of biomolecules. The most degree of response difference in sensor and its corresponding discrimination obtained at aggregation of NPs after 9min interactions with biomolecules. Besides all effective parameters causing differences in the intensity of aggregation and the spectral evolution (discussed in section 3.2.), differences in kinetics of aggregation enabled us to discriminate the biothiols with close structure and in wide range of concentrations. 3.3.2. Selectivity To verify specific pattern-based response in practical application, the response of sensor to other amino acids was tested. The results confirmed no or negligible changes in the UVvisible spectrum of AuNPs in the presence of other amino acids at a concentration of 700 mol L-1 (see Figure S10 of SI). As can be seen in Figures 4 and 5, all amino acids had been separately classified. 3.3.3. Color change profiles A color difference map, which is a useful approach for visualization of the achieved data, was performed by subtraction of the light absorbance before and after exposure to the three selected visible wavelengths (i.e., 665, 612 and 530 nm). As shown in Figures 6, the resulting color difference patterns provide a robust fingerprint for each thiol at different concentrations. According to the maps, one can easily distinguish the type of thiols even without need to any statistical techniques. As mentioned before, the colorimetric sensor array has also been tested against interference of amino acids (concentration 700 mol L-1), as control cases. In this regard, negligible responses were observed in the selected wavelengths. The values of limit of detection (LOD) and limit of recognition (LOR) [23], based on the colorimetric maps, are presented in Table 1. It is noticeable that the reported mean concentrations of GSSG, GSH, and Cys ranges in blood/serum are 1-500 mol L-1, 150-1500 mol L-1, and ~250 mol L-1, respectively [68, 69]. 12 3.3.4. The total Euclidean distances-biomolecule concentration correlation The relationship between the overall array response (i.e., square root of sums of squares of A AuNPs solution after and before addition of the thiols) as a function of thiol concentration was probed (Figure 7). A calibration plot was observed over a linear range of 10−300 mol L-1 and 400-800 mol L-1 for GSSG and 10−100 mol L-1 and 200-800 mol L1 for GSH (also presented in Table 1). These results proved that our colorimetric sensor array can be used for quantitative and semi quantitative analysis of thiols using HCA, color difference map, and calibration curves. 3.3.5. Analysis of Mixtures To probe the ability of the developed colorimetric sensor array for discrimination of individual thiols from their mixtures, the respond of the sensor on the combination of thiols (four thiols at concentrations of 250 and 100µmol L-1 for each thiol) were analyzed. We found that the binary and ternary mixtures of thiols had different absorbance responses compared to their single form (see Figure S11 of SI). In all cases, the rate of AuNPs aggregation in the presence of both Cys and GSH was slower than that of the solely Cys. This happened because of the high affinity of the GSH, compared to the Cys, for attachment to the surface of AuNPs [70]. PCA analysis of the thiols’ mixture demonstrated their well discrimination from the individual thios (see Figure 8). In addition to the PCA analysis, using color difference maps one could easily distinguish the mixture and the individual thiols with naked eye (Figure S12 of SI). 3.3.6. Blood Plasma Analysis To evaluate the efficacy of the array in analysis of sample with huge amount of biomolecules, the human plasma was employed. The responses of various AuNPs to spiked (with 600 and 200 mol L-1 of thiols) and none-spiked plasmas is shown in Figures S13 and S14 of SI. PCA analysis demonstrated fine discrimination of specific thiols (see Figure 9) with no significant changes in the degree-of-class-separation (presented in Table S2 of SI). 13 4. Conclusions We have developed a colorimetric sensor array consisting three AuNPs with different surface coatings. This NPs-based detection system had capability of detection and discrimination of biological thiols in aqueous solution with excellent specificity. Using spectra variations of AuNPs, induced by thiols, we could discriminate various thiols of different concentrations (i.e., 10-800 mol L-1 for cysteine, 200-700 mol L-1 for both GSH and GSSG). Furthermore, the proposed sensor array could efficiently discriminate the individual thiols and their mixtures. Finally, it was found that the array was accurately successful to detect various thiols in complex situation. 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Vollset, Plasma total cysteine as a risk factor for vascular disease The European Concerted Action Project, Circulation, 103 (2001) 2544-2549. Y. Li, P. Wu, H. Xu, H. Zhang, X. Zhong, Anti-aggregation of gold nanoparticle-based colorimetric sensor for glutathione with excellent selectivity and sensitivity, Analyst, 136 (2010) 196-200. Figure 1. TEM images of (a) CTAB-, (b) Citrate-, and (c) NaBH4-coated AuNPs and (d) their UV-Vis spectra (with the concentrations used in sensor array). Figure 2. Colorimetric responses and corresponding UV-vis spectra of AuNPs and their aggregates induced by Cys, GSH and GSSG (at concentration 500 mol L-1) on (a) CTAB-, (b) Citrate-, and (c) NaBH4-coated AuNPs. Figure 3. UV-vis spectra of seed-2 (used in the synthesis of CTAB coated AuNPs) and its aggregates induced by Cys, GSH and GSSG (at concentration 500 mol L-1). Figure 4. (a) HCA dendrogram with ward linkage showing the Euclidean distance between trials. Figure 5. Two-dimensional score plot, showing PC3 versus PC1 illustrating the ability of differential array to discriminate various thiols. Figure 6. Color difference maps for various concentrations of Cys, GSH, GSSG and 8 amino acids as interference. Figure 7. The total Euclidean distance (T.E.D) of the array color change plotted versus different concentrations of Cys, GSH and GSSG. Figure 8. Two-dimensional score plot, showing discrimination of individual thiols from their mixtures, at thiol concentrations of (a) 250µmol L-1 and (b) 100µmol L-1. Figure 9. Two-dimensional score plot, showing PC3 versus PC1 after combining the test set (real sample) with the training set data. Plasma was spiked with thiols at concentrations of 600 and 200 mol L-1 (shown in black-line markers). 18 Table 1. The values of LOD and LOR for thiols calculated based on the results of color difference maps. The values of the linear range were estimated according to the total Euclidean distancesbiomolecule concentration correlation. Cys GSH GSSG - 10-100 and 200-800 10-300 and 400-800 LOR( mol L-1) 0.5 50 50 LOD( mol L-1) <0.5 10 10 Linear range( mol L-1) Figure 1. 19 Figure 2. 20 Figure 3. 21 Figure 4. 22 Figure 5. 23 Figure 6. 24 Figure 7. 25 (a) (b) Figure 8. 26 Figure 9. 27