Koichi Murayama

Analysis of Near-Infrared Spectra of Complicated Biological Fluids by Two-Dimensional Correlation Spectroscopy: Protein and Fat Concentration-Dependent Spectral Changes of Milk

Generalized two-dimensional (2D) correlation spectroscopy has been applied to analyze near-infrared (NIR) spectra of milk with different protein and fat concentrations. The NIR spectra of milk show rather poor signal-to-noise ratios compared with those of a protein or fat solution and have changing baselines from one spectrum to another. Poor signal-to-noise ratio and variations in baseline are common problems for NIR spectra of real-world samples. This study aims at expanding the utility of generalized 2D correlation spectroscopy to complicated multicomponent biological systems. In order to overcome the above two problems, we have employed multiplicative scatter correction (MSC) and smoothing as pretreatment procedures of the milk spectra selected for the calculation of 2D NIR correlation. 2D synchronous correlation spectra in the 2000–2400 nm region constructed from protein or fat concentration-dependent spectral changes of milk sharply enhance bands assignable to proteins or fats, respectively. It has been found that a power spectrum along the diagonal line in a synchronous spectrum very effectively shows the contribution of a particular component to the NIR spectra of milk. In fact, for example, the power spectrum for the fat concentration-dependent spectral changes of milk is very close to an NIR spectrum of fat itself. Two-dimensional asynchronous correlation spectra demonstrate the existence of bands that cannot be identified even by calculation of second derivatives and chemometrics analysis of the spectra. The asynchronous spectra also elucidate interaction between fats, proteins, and water.

Simultaneous determination of human serum albumin, γ-globulin, and glucose in a phosphate buffer solution by near-infrared spectroscopy with moving window partial least-squares regression

Near-infrared (NIR) spectra in the 12,000-4,000 cm(-1) region were measured for phosphate buffer solutions containing human serum albumin (HSA), gamma-globulin, and glucose with various concentrations at 37 degrees C. Five levels of full factorial design were used to prepare a sample set consisting of 125 samples of three component mixtures. The concentration ranges of HSA, gamma-globulin and glucose were 0.00-6.00 g dl(-1), 0.00-4.00 g dl(-1) and 0.00-2.00 g dl(-1), respectively. The 125 sample data were split into two sets, the calibration set with 95 data and the prediction set with 30 data. The most informative spectral ranges of 4648-4323, 4647-4255 and 4912-4304 cm(-1) were selected by moving window partial least-squares regression (MWPLSR) for HSA, [gamma]-globulin, and glucose in the mixtures, respectively. For HSA, the correlation coefficient (R) of 0.9998 and the root mean square error of prediction (RMSEP) of 0.0289 g dl(-1) were obtained. For [gamma]-globulin, R of 0.9997 and RMSEP of 0.0252 g dl(-1) were obtained. The corresponding statistic values of glucose were 0.9997 and 0.0156 g dl(-1), respectively. These statistical values obtained by MWPLSR are highly significant and better than those calculated by using the regions reported in the literature. The results presented here show that MWPLSR can select the informative regions with a simple procedure and increase the power of NIR spectroscopy for simultaneous determination of the concentrations of HSA, [gamma]-globulin and glucose in the mixture systems.

Comparison between Conventional Spectral Analysis Methods, Chemometrics, and Two-Dimensional Correlation Spectroscopy in the Analysis of Near-Infrared Spectra of Protein

The present study has aimed at comparing three methods for analyzing near-infrared (NIR) spectra: conventional spectral analysis methods, chemometrics, and generalized two-dimensional (2D) correlation spectroscopy. In a comparison of these approaches, NIR spectra were measured for aqueous solutions of human serum albumin (HSA) with the concentration range of 0.5–5.0 wt %. Synchronous and asynchronous 2D correlation spectra were generated from the concentration-dependent NIR spectral variations of HSA in distilled water. The first and second loadings plots were calculated for principal component analysis (PCA) models based upon the above NIR spectral data. It was found that slice spectra calculated from the synchronous spectra are very close to the first loadings plots and that slice spectra from the asynchronous spectra have a close resemblance to the second loadings plots. The reasons why the synchronous and asynchronous spectra bear close resemblance to the first and second loadings plots for the PCA model, respectively, are discussed in the paper.

Near-infrared spectra of serum albumin and γ-globulin and determination of their concentrations in phosphate buffer solutions by partial least squares regression

Abstract Near-infrared (NIR) spectra have been measured for albumin and γ-globulin in a powder state as well as in phosphate buffer solutions. The second derivative spectra of powder samples have been used to make assignments of NIR bands of the proteins. The second derivative spectra of albumin and γ-globulin are significantly different from each other in the band frequencies and relative intensities. The NIR spectra in the 1300–1850 nm region of the solutions have been subjected to partial least squares (PLS) regression analysis to develop chemometrics models which predict the concentrations of the proteins. The calibration for the albumin solutions in the concentration range of 0.1–8.0 g/dl has yielded a correlation coefficient ( R ) of 0.9995 and a standard error of calibration (SEC) of 0.207 g/dl. For the γ-globulin solutions in the concentration range of 0.1–6.0 g/dl, R of 0.9946 and SEC of 0.128 g/dl have been obtained. Regression coefficients (RCs) for the calibration models have been calculated for the first four factors. These RCs reflect the spectral variations in bands due to the proteins and in a water band near 1400 nm caused by the dissolution of the proteins. Moreover, the RCs have been compared with the NIR spectra of the proteins in the powder state. The positions of peaks in the RCs correspond well to those of bands in the NIR spectra of the proteins in the powder state. This suggests that the chemometrics models can pick up effectively the information about albumin and γ-globulin, even if the models have been constructed from the spectra of the proteins in the dilute solutions.

Temperature-dependent near-infrared spectra of bovine serum albumin in aqueous solutions: spectral analysis by principal component analysis and evolving factor analysis.

Fourier transform near-infrared (FT-NIR) spectra have been measured for bovine serum albumin (BSA) in an aqueous solution (pH 6.8) with a concentration of 5.0 wt % over a temperature range of 45–85 °C. Not only conventional spectral analysis methods, such as second-derivative spectra and difference spectra, but also chemometrics, such as principal component analysis (PCA) and evolving factor analysis (EFA), have been employed to analyze the temperature-dependent NIR spectra in the 7500–5500 and 4900–4200 cm−1 regions of the BSA aqueous solution. Intensity changes of bands in the 7200–6600 cm−1 and 4650–4500 cm−1 regions in the difference spectra indicate variations of the hydration and secondary structure of BSA in the aqueous solution, respectively. The plot of a band intensity at 7080 cm−1 in the different spectra shows a clear turning point at 63 °C, revealing that a significant change in the hydration occurs at about 63 °C. The forward and backward eigenvalues (EVs) from EFA suggest that marked changes in the hydration and secondary structure of BSA take place in the temperature ranges of 61–65 °C and 59–63 °C, respectively. In addition, the temperature of 71 °C marked in the EFA plots may correspond to the onset temperature of increase in the intermolecular β-sheet structure.

Two-Dimensional Attenuated Total Reflection/Infrared Correlation Spectroscopy Studies on Concentration and Heat-Induced Structural Changes of Human Serum Albumin in Aqueous Solutions

Attenuated total reflection (ATR)/FT-IR spectra were measured for human serum albumin (HSA) in aqueous solutions (pH 6.6) with concentrations of 1.0, 2.0, 3.0, 4.0, and 5.0 wt % over a temperature range of 45–80 °C. Generalized two-dimensional (2D) correlation spectroscopy was employed to explore concentration and heat-induced structural variations of HSA in aqueous solutions. To generate 2D correlation spectra, the raw spectra were subjected to the appropriate pretreatment procedure involving ATR correction, subtraction of the spectrum of an aqueous solution, and smoothing. The synchronous and asynchronous correlation spectra were calculated for the concentration-dependent IR spectral variations in the amide I region at various temperatures. The two-dimensional ATR/IR correlation spectra greatly enhance band separation in the region and provide information about the correlation between the amide bands of HSA arising from the same and different secondary structure components. Based on the correlation investigated and previously proposed relationship between the secondary structure elements and the amide band frequencies, we have proposed the detailed assignments in the amide I region at 45 and 80 °C. The proposed assignments are compared with those based on the results of second derivative and Fourier self-deconvolution (FSD) of the ATR/IR spectra. The asynchronous spectrum generated from the concentration-dependent spectral variations at 45 °C show that side chains, the random coil, and extended chains are more sensitive than the α-helices and β-turns to the concentration change. On the other hand, the corresponding spectrum at 80 °C reveals that the conformation changes in side chains and β-turns (or β-strands) of HSA start before those in extended chain, random coil structures, and α-helices.

Two-dimensional infrared correlation spectroscopy studies on secondary structures and hydrogen bondings of side chains of proteins

This review paper reports usefulness of two-dimensional (2D) correlation spectroscopy in analyzing infrared (IR) spectra of proteins in aqueous solutions. In the 2D approach, spectral peaks are spread over the second dimension, thereby simplifying the visualization of complex spectra consisting of many overlapped bands, and enhancing spectral resolution. 2D correlation spectroscopy has a powerful deconvolution ability for highly overlapped amide I, amide II, and amide III bands of proteins, enabling these bands to be assigned to various secondary structures. It also provides the specific order of the spectral intensity changes taking place during the measurement on the value of controlling variable affecting the spectra. Therefore, one can monitor the order of secondary structure variations in proteins by using 2D IR correlation spectroscopy. 2D correlation spectroscopy also provides new insight into the hydrogen bondings of side chains of proteins. In this review the principles and advantages of 2D correlation spectroscopy are outlined first and then three examples of the applications of 2D IR spectroscopy to protein research are presented.

Study of Thermal Dynamics of Defatted Bovine Serum Albumin in D2O Solution by Fourier Transform Infrared Spectra and Evolving Factor Analysis

Fourier transform infrared (FT-IR) spectra have been measured for defatted bovine serum albumin (BSA) in D2O with a concentration of 2.0 wt % over a temperature range of 26–90 °C and the corresponding difference spectra have been calculated by subtracting the contribution of D2O at the same temperature. Evolving factor analysis (EFA) by selecting two factors and three factors has been employed to analyze the temperature-dependent difference IR spectra in the 1700–1600 cm−1 spectral region of the defatted BSA in D2O solution. Three-factor EFA has been employed to determine the distinction of the three protein species involved in the process of temperature elevation: native, transitional, and denatured protein. The temperature profiles obtained from three-factor EFA indicate that heat-induced conformational change in the secondary structures of defatted BSA in D2O undergoes two two-state transitions, a drastic transition and a slight transition, which occur in the temperature ranges of 68–82 °C and 56–76 °C, respectively.

Multivariate determination of human serum albumin and γ-globulin in a phosphate buffer solution by near infrared spectroscopy

Near infrared (NIR) spectra in the 1300–1850 nm region were measured for phosphate buffer solutions containing both human serum albumin and γ-globulin with various concentrations. The concentrations of albumin and γ-globulin were determined by partial least squares (PLS) regression analysis. The calibration for albumin in the concentration ranges of 0.100–8.000 g dL−1 yielded the correlation coefficient (R) of 0.998, the standard error of calibration (SEC) of 0.124 g dL−1, and the standard error of prediction (SEP) of 0.152 g dL−1, respectively. Those for γ-globulin in the concentration ranges of 0.100–6.000 g dL−1 yielded were 0.998, 0.110 g dL−1 and 0.118 g dL−1, respectively. The regression coefficients (RCs) of PLS factors for albumin were compared with those for γ-globulin. The differences were discussed for each RC between albumin and γ-globulin. The coefficient of variation (CV) was calculated to be 0.0388 and 0.0374 for albumin and γ-globulin, respectively. The ratio of standard derivation of reference data in prediction set to SEP (RPD) are 13.4 and 16.4 for them. These values obtained in the present study satisfy the demands of clinical analysis of blood. The present results demonstrate that it is possible to determine the concentrations of the two kinds of proteins in the solution simultaneously by use of NIR and PLS regression.

FcεRI-induced mast cell cytokine production critically involves an aspartic acid residue (D234) in the C-terminal intracellular domain of the FcεRIβ chain.

The high affinity IgE Fc receptor (FcεRI) β chain is well implicated as a signal amplifier through the immunoreceptor tyrosine-based activation motif (ITAM) in its C-terminal intracellular region. Our previous study, however, demonstrated that mutation in all of the three tyrosine residues within the FcεRIβ ITAM did not impair FcεRI-induced cytokine production, suggesting a possible functional region other than the ITAM. To investigate the ITAM-independent mechanism by which FcεRIβ regulates FcεRI-induced cytokine production, mouse mast cells expressing various FcεRIβ mutants were generated. We observed that truncation of the FcεRIβ C-terminus downstream of the ITAM resulted in a considerable decrease in FcεRI-induced IL-6 production but not degranulation. Furthermore, mutagenesis of a single C-terminal aspartic acid (D234) to alanine (β-D234A) also significantly impaired IL-6 production. In addition, the similarity between the circular dichroism (CD) spectra of the wild type and β-D234A suggests that the secondary structure of the FcεRIβ C-terminus was not affected by the D234A mutation. Consistently, we did not observe any effect of this mutation on FcεRI-induced tyrosine phosphorylation of FcεRIβ. These observations strongly suggest a novel signaling pathway mediated by the cytoplasmic tail downstream of the FcεRIβ ITAM.