Supporting Information

Transcription

1 Supporting Information Wiley-VCH Weinheim, Germany

2 Colorimetric Identification of Carbohydrates by a ph indicator/ph change inducer ensemble Jae Wook Lee, Jun-Seok Lee, Young-Tae Chang* Department of Chemistry, New York University, New York, General: The spectroscopy grade of dimethyl sulfoxide (DMSO, 99.9% purity) was purchased from Acros. Sodium hydroxide pellets (NaOH, 99.99% purity) and phosphoric acid (H 3 PO 4, 85 wt. %, % purity) were purchased from Sigma. 23 carbohydrates, Phenylboronic acid (97% purity) and boric acid (99.999% purity) were purchased from Aldrich. De-ionized water was prepared using the Picosystem (filtering system) from Hydro service and supplied company. All solutions were prepared with de-ionized water. Phosphate buffer (50 mm, ph 9.0) was prepared using phosphoric acid by titrating with NaOH solution. The solutions of phenylboronic acid (50 mm) and boric acid (50 mm) were prepared in the above phosphate buffer. Without further ph adjustment, we used boric acid and phenylboronic acid phosphate buffer solution for further test. Solutions of the carbohydrates (200 mm) were prepared in de-ionized water (Table S2). ph indicators were purchased from Chem Service, Sigma, Fluka, Kodak, Janssen and Aldrich. Polystyrene 384 well plates (clear flat bottom) were purchased from Corning Inc. ph indicator solution (10-100mM) were prepared in DMSO and diluted in H 2 O. Instrument and Computer Software: All graphic data were recorded using CCD camera (Cannon; Power Shot G5) equipped with Spectroline model CC-88 analysis cabinet. All UV-VIS spectrum data were recorded from 350 nm to 750 nm using plate reader (Molecular Device; Spectra Max Plus 384). All image analyses were performed using Adobe Photoshop v7.0. Principal component analyses were performed using MatLab v6.5 Array Preparation and Data acquisition: The ph indicator solutions were placed in 384-well plate (30 µl each). In this format, each dye occupies 24 x 4 blocks. Then, boric acid solution (50 mm) in phosphate buffer solutions were added to the upper two rows (20 µl each), and phenylboronic acid (50 mm) in phosphate buffer solutions were added to next two rows (20 µl each). The identical two columns provided duplicate experimental data. 23 kinds of carbohydrate solutions (200 mm, 50 µl each) including water were added. After 10 seconds of mixing on plate reader, the plate was allowed 10 min for full color development. The visual image of the plate was recorded by CCD camera (Power Shot G5, Cannon) and absorbance spectra were recorded by the plate reader ( nm with 10 nm interval). To confirm the reproducibility of the generated data, the same experiment was repeated using another independent plate in different day. Thus, total 10 sets of data points were collected and analyzed. Absorbance spectra data processing and multivariate analysis: For the analysis of absorbance spectra, we followed our previous methods. The absorbance values for 41 wavelengths ( nm, every 10 nm) were extracted from the spectral data. Each analyte treated data were compared to those of control in the last two rows from the last second column (Figure S2B). We extracted the absorbance values from λ max. The ph indicator probes were divided into two classes depending on their responses to analytes. Chlorophenol red changed their absorbance intensity without significant λ max change. Other ph indicators showed changes both in absorbance intensity and maximum wavelength. 1

3 Figure S1. Fold change determination from spectral data. Black line is spectrum of dye with water. (A) For dyes which changes only in intensity, not in λmax (Red line). (B) Dyes which changes both for intensity and λ max value (Blue line). For the first class of dyes (Class I), we used the absorbance values at λ max (λ 0 ) for fold change calculation (Figure S1A). Where the intensity of analyte test is I ' and that of control is 0 I 0, the fold change F is as follow (Eq. 1). I' F = 0 (1) I 0 For the second class of dyes (Class II), there are two λ max : one for control (λ 1 ) and a new peak appeared in test solution (λ 2 ) (Figure S1B). The effective fold change will be calculated as follow (Eq. 2). I 1 I ' 2 F = (2) I 2 I ' 1 I 1 and I' refer to the absorbance values at λ 1 1, and I 2 and I' at λ 2 2, where I' values are for test solution I 1 and I values for control. In the Eq. 2, term is a normalization factor, with witch non-responding I2 dye will give F = 1 (no change). The λ 0, λ 1, λ 2 preset values were summarized in Table S1. 2

4 Table S1. Selected ph indicators and their tested wavelength(s) and concentration (λ 0, λ 1, and λ 2 values were obtained after addition of boric and phenylboroic acid-phosphate buffer solution). λ 0 λ 1 λ 2 concentration DMSO # name (nm) (nm) (nm) (mm) (%) 1 Brilliant yellow Neutral red Rosolic acid Chlorophenol red Thymol blue Cresol red Nitrazine Yellow Bromothymol Blue, Na Phenol red Bromocresol Purple m-cresol Purple Xylenol Orange Based on the preset wavelengths, the corresponding absorbance data were extracted out using macro function of Excel program, and the fold changes were calculated according to Eqs. 1 & 2. The log value of fold change, log(f) was used for multivariate analysis. 3

5 Table S2. Name and structure of 23 carbohydrates list Name MW Structure 1 D-( )-Arabinose Deoxy-D-lyxohexose Deoxy-D-ribose D-( )-Fructose L-( )-Fucose D-(+)-Galactose D-Glucose

6 8 D-( )-Lyxose D-(+)-Mannose L-Rhamnose D-( )-Ribose L( )-Sorbose myo-inositol D-(+)-Xylose D-(+)-Cellobiose

7 16 β-d-lactose D-Maltose Melibiose Palatinose Sucrose D-Trehalose D-(+)-Melezitose D-Raffinose

8 Figure S2. The representative picture of carbohydrate detecting array. Cresol Red (6), Nitrazine Yellow (7), Bromonthylmol Blue Na salt (8), and m-cresol Purple (11) were used for sensing carbohydrates. A) Picture of array before addition of analytes. B) Picture of array after addition of analytes. C) The picture of analytes map. Each number represents carbohydrates (Table S2) c is water only. 200 mm of carbohydrates solution were added each well (100 mm for final concentration). B and P are boric acid in buffer, and phenylboronic acid in buffer. D) Difference picture between A) and B) generating by photoshop software. A) Before addition of analytes Dye 6 Dye 7 Dye 8 Dye 11 B) After addition of analytes D) Difference CCD image subtraction C) Analytes map 7

9 LDA of boric acid-ph indicator pair and phenyl boronic acid-ph indicotor pair Using 10 independent measurement data of phenyl boronic acid-ph indicator pair data and boric acid-ph indicator pair data, a linear discrimination analysis was performed using Classical Discrimination Analysis in SYSTAT(version 11.0). In the discrimination analysis, we built the best model which has high prediction ability. The variable s F value (in our case ph indicator/ph change inducer pair is variable) indicates its statistical significance in the discrimination between groups. F value means which a variable has a unique contribution to the prediction of carbohydrates. Forward stepwise analysis is that a model of discrimination is built up step-by-step. In the each build up step, all variables are evaluated again to determine which one is crucial variable. (i) Forward stepwise variable selection iteration number 6 with F-to-enter 4.00 and F-to remove= Variable F-to-remove Tolerance DYE7(boric acid) DYE11(boric acid) DYE1(phenyl boronic acid) DYE6(phenyl boronic acid) DYE7(phenyl boronic acid) DYE12(phenyl boronic acid) (ii) Jack-knife classification s correction percentage. % correct Sugar1 100 Sugar2 100 Sugar3 100 Sugar4 100 Sugar5 100 Sugar6 100 Sugar7 100 Sugar8 100 Sugar9 100 Sugar Sugar Sugar Sugar Sugar Sugar Sugar Sugar Sugar Sugar Sugar Sugar Sugar Sugar control 100 Overall 100 8