J. Renwick Beattie

Confocal Raman microscopy can quantify advanced glycation end product (AGE) modifications in Bruch's membrane leading to accurate, nondestructive prediction of ocular aging.

The modification of proteins by nonen‐zymatic glycation leading to accumulation of advanced glycation end products (AGEs) is a well‐established phenomenon of aging. In the eyes of elderly patients, these adducts have been observed in retinal pigment epithelium (RPE), particularly within the underlying pentalaminar substrate known as Bruchs membrane. AGEs have also been localized to age‐related subcellu‐lar deposits (drusen and basal laminar deposits) and are thought to play a pathogenic role in progression of the major sight‐threatening condition known as age‐related macular degeneration (AMD). The current study has quantified AGEs in Bruchs membrane from postmortem eyes and established age‐related correlations. In particular, we investigated the potential of confocal Raman microscopy to identify and quantify AGEs in Bruchs membrane in a nondestructive, analytical fashion. Bruchs membrane and the innermost layers of the underlying choroid (BM‐Ch) were dissected from fresh postmortem eye‐cups (n=56). AGE adducts were quantified from homogenized tissue using reverse‐phase HPLC and GC/MS in combination with immunohistochemistry. For parallel Raman analysis, BM‐Ch was flat‐mounted on slides and evaluated using a Raman confocal microscope and spectra analyzed by a range of statistical approaches. Quantitative analysis showed that the AGEs pentosidine, carboxym‐ethyllysine (CML), and carboxyethyllysine (CEL) occurred at significantly higher levels in BM‐Ch with age (P<0.05–0.01). Defined Raman spectral “fingerprints” were identified for various AGEs and these were observed in the clinical samples using confocal Raman microscopy. The Raman data set successfully modeled AGEs and not only provided quantitative data that compared with conventional analytical approaches, but also provided new and complementary information via a nondestructive approach with high spatial resolution. It was shown that the Raman approach could be used to predict chronological age of the clinical samples (P< 0.001) and a difference in the Raman spectra between genders was highly significant (P<0.000001). With further development, this Raman‐based approach has the potential for noninvasive examination of AGE adducts in living eyes and ultimately to assess their precise pathogenic role in age‐related diseases.—Glenn, J. V., Beattie, J. R., Barrett, L., Frizzell, N., Thorpe, S. R., Boulton, M. E., McGarvey, J. J., Stitt, A. W. Confocal Raman microscopy can quantify advanced glycation end product (AGE) modifications in Bruchs membrane leading to accurate, nondestructive prediction of ocular aging. FASEB J. 21, 3542–3552 (2007)

A critical evaluation of Raman spectroscopy for the analysis of lipids: fatty acid methyl esters.

The work presented here is aimed at determining the potential and limitations of Raman spectroscopy for fat analysis by carrying out a systematic investigation of C4−C24 FAME. These provide a simple, well-characterized set of compounds in which the effect of making incremental changes can be studied over a wide range of chain lengths and degrees of unsaturation. The effect of temperature on the spectra was investigated over much larger ranges than would normally be encountered in real analytical measurements. It was found that for liquid FAME the best internal standard band was the carbonyl stretching vibration ρ(C=O), whose position is affected by changes in sample chain length and physical state; in the samples studied here, it was found to lie between 1729 and 1748 cm−1. Further, molar unsaturation could be correlated with the ratio of the ρ(C=O) to either ρ(C=C) or δ(H−C=) with R2>0.995. Chain length was correlated with the δ(CH2)tw/ρ(C=O) ratio, (where “tw” indicates twisting) but separate plots for odd- and even-numbered carbon chains were necessary to obtain R2>0.99 for liquid samples. Combining the odd- and even-numbered carbon chain data in a single plot reduced the correlation to R2=0.94–0.96, depending on the band ratios used. For molal unsaturation the band ratio that correlated linearly with unsaturation (R2>0.99) was ρ(C=C)/δ(CH2)sc (where “sc” indicates scissoring). Other band ratios show much more complex behavior with changes in chemical and physical structure. This complex behavior results from the fact that the bands do not arise from simple vibrations of small, discrete regions of the molecules but are due to complex motions of large sections of the FAME so that making incremental changes in structure does not necessarily lead to simple incremental changes in spectra.

Prediction of adipose tissue composition using Raman spectroscopy: average properties and individual fatty acids.

Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R2=0.97, root mean square error of prediction (RMSEP)=4.6% of 4 δ], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (≥2 double bonds per chain) was also well predicted with R2=0.97 and RMSEP=4.0% of 4 δ. Trans unsaturation was not as well modeled (R2=0.52, RMSEP=18% of 4 δ); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R2=0.73; the average RMSEP=11.9% of 4 δ. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP=4.7% of 4 δ). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

Multivariate Prediction of Clarified Butter Composition Using Raman Spectroscopy

Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed that good prediction of the five major (abundance >5%) FA gave R2=0.74–0.92 with a SE of prediction (RMSEP) that was 5–7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was <10% for all but one of the 10 FA present at levels >1.25%. The Raman method has the best prediction ability for unsaturated FA (R2=0.85–0.92), and in particular trans unsaturated FA (best-predicted FA was 18∶1tΔ9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R2=0.80) and solid fat content at low temperature (R2=0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R2=0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.

Multiplex analysis of age-related protein and lipid modifications in human Bruch's membrane

Aging of the human retina is characterized by progressive pathology, which can lead to vision loss. This progression is believed to involve reactive metabolic intermediates reacting with constituents of Bruchs membrane, significantly altering its physiochemical nature and function. We aimed to replace a myriad of techniques following these changes with one, Raman spectroscopy. We used multiplexed Raman spectroscopy to analyze the age-related changes in 7 proteins, 3 lipids, and 8 advanced glycation/lipoxidation endproducts (AGEs/ALEs) in 63 postmortem human donors. We provided an important database for Raman spectra from a broad range of AGEs and ALEs, each with a characteristic fingerprint. Many of these adducts were shown for the first time in human Bruchs membrane and are significantly associated with aging. The study also introduced the previously unreported up-regulation of heme during aging of Bruchs membrane, which is associated with AGE/ALE formation. Selection of donors ranged from ages 32 to 92 yr. We demonstrated that Raman spectroscopy can identify and quantify age-related changes in a single nondestructive measurement, with potential to measure age-related changes in vivo. We present the first directly recorded evidence of the key role of heme in AGE/ALE formation.

Classification of Adipose Tissue Species using Raman Spectroscopy

In this study multivariate analysis of Raman spectra has been used to classify adipose tissue from four different species (chicken, beef, lamb and pork). The adipose samples were dissected from the carcass and their spectra recorded without further preparation. 102 samples were used to create and compare a range of statistical models, which were then tested on 153 independent samples. Of the classical multivariate methods employed, Partial Least Squares Discriminant Analysis (PLSDA) performed best with 99.6% correct classification of species in the test set compared with 96.7% for Principal Component Linear Discrimination Analysis (PCLDA). Kohenen and Feed-forward artificial neural networks compared well with the PLSDA, giving 98.4 and 99.2% correct classification, respectively.

Preliminary investigations on the effects of ageing and cooking on the Raman spectra of porcine longissimus dorsi

The influence of ageing and cooking on the Raman spectrum of porcine longissimus dorsi was investigated. The rich information contained in the Raman spectrum was highlighted, with numerous changes attributed to changes in the environment and conformations of the myofibrillar proteins. Predictions equations for shear force and cooking loss were developed from the Raman spectra of both raw and cooked pork. Good correlations and standard errors of prediction were obtained for both WB shear force and cooking loss, with the raw and the cooked samples showing almost identical results R(2)=0.77, root mean standard error of prediction (RMSEP)% of mean=12% for shear force; R(2)=0.71, RMSEP% of mean=10% for cooking loss. The Raman spectra were also able to predict the extent of cooking that occurred within the pork (R(2)(val)=0.94, RMSEP% of range=5.5%). Raman spectroscopy has considerable potential as a method for non-destructive and rapid determination of pork quality parameters such as tenderness. Raman spectroscopy may provide a means of determining changes during cooking and the extent to which foods have been cooked.

The use of Raman microscopy to determine and localize vitamin E in biological samples.

Alpha‐tocopherol (aT), the predominant form of vitamin E in mammals, is thought to prevent oxidation of polyunsaturated fatty acids. In the lung, aT is perceived to be accumulated in alveolar type II cells and secreted together with surfactant into the epithelial lining fluid. Conventionally, determination of aT and related compounds requires extraction with organic solvents. This study describes a new method to determine and image the distribution of aT and related compounds within cells and tissue sections using the light‐scattering technique of Raman microscopy to enable high spatial as well as spectral resolution. This study compared the nondestructive analysis by Raman microscopy of vitamin E, in particular aT, in biological samples with data obtained using conventional HPLC analysis. Raman spectra were acquired at spatial resolutions of 2‐0.8 μm. Multivariate analysis techniques were used for analyses and construction of corresponding maps showing the distribution of aT, alpha‐tocopherol quinone (aTQ), and other constituents (hemes, proteins, DNA, and surfactant lipids). A combination of images enabled identification of colocalized constituents (heme/aTQ and aT/surfactant lipids). Our data demonstrate the ability of Raman microscopy to discriminate between different tocopherols and oxidation products in biological specimens without sample destruction. By enabling the visualization of lipid‐protein interactions, Raman microscopy offers a novel method of investigating biological characterization of lipid‐soluble compounds, including those that may be embedded in biological membranes such as aT. Beattie J. R., Maguire C., Gilchrist S., Barrett L. J., Cross C. E., Possmayer F., Ennis M., Elborn J. S., Curry W. J., McGarvey J. J., Schock B. C. The use of Raman microscopy to determine and localize vitamin E in biological samples FASEB J. 21, 766–776 (2007)

Conformations, vibrational frequencies and Raman intensities of short-chain fatty acid methyl esters using DFT with 6-31G(d) and Sadlej pVTZ basis sets

Abstract Density functional calculations, using B3LPY/6-31G(d) methods, have been used to investigate the conformations and vibrational (Raman) spectra of three short-chain fatty acid methyl esters (FAMEs) with the formula CnH2nO2 (n=3–5). In all three FAMEs, the lowest energy conformer has a simple ‘all-trans’ structure but there are other conformers, with different torsions about the backbone, which lie reasonably close in energy to the global minimum. One result of this is that the solid samples we studied do not appear to consist entirely of the lowest energy conformer. Indeed, to account for the ‘extra’ bands that were observed in the Raman data but were not predicted for the all-trans conformer, it was necessary to add-in contributions from other conformers before a complete set of vibrational assignments could be made. Provided this was done, the agreement between experimental Raman frequencies and 6-31G(d) values (after scaling) was excellent, RSD =12.6 cm −1 . However, the agreement between predicted and observed intensities was much less satisfactory. To confirm the validity of the approach followed by the 6-31G(d) basis set, we used a larger basis set, Sadlej pVTZ, and found that these calculations gave accurate Raman intensities and simulated spectra (summed from two different conformers) that were in quantitative agreement with experiment. In addition, the unscaled Sadlej pVTZ, and the scaled 6-31G(d) calculations gave the same vibrational mode assignments for all bands in the experimental data. This work provides the foundation for calculations on longer-chain FAMEs (which are closer to those found as triglycerides in edible fats and oils) because it shows that scaled 6-31G(d) calculations give equally accurate frequency predictions, and the same vibrational mode assignments, as the much more CPU-expensive Sadlej pVTZ basis set calculations.

DFT studies of long-chain FAMEs: theoretical justification for determining chain length and unsaturation from experimental Raman spectra

Abstract Density functional calculations, using B3LPY/6-31G(d) methods, have been used to investigate the conformations and vibrational (Raman) spectra of a series of long-chain, saturated fatty acid methyl esters (FAMEs) with the formula CnH2nO2 (n=5–21) and two series of unsaturated FAMEs. The calculations showed that the lowest energy conformer within the saturated FAMEs is the simple (all-trans) structure and, in general, it was possible to reproduce experimental data using calculations on only the all-trans conformer. The only exception was C6H12O2, where a second low-lying conformer had to be included in order to correctly simulate the experimental Raman spectrum. The objective of the work was to provide theoretical justification for the methods that are commonly used to determine the properties of the fats and oils, such as chain length and degree of unsaturation, from experimental Raman data. Here it is shown that the calculations reproduce the trends and calibration curves that are found experimentally and also allow the reasons for the failure of what would appear to be rational measurements to be understood. This work shows that although the assumption that each FAME can simply be treated as a collection of functional groups can be justified in some cases, many of the vibrational modes are complex motions of large sections of the molecules and thus would not be expected to show simple linear trends with changes in structure, such as increasing chain length and/or unsaturation. Simple linear trends obtained from experimental data may thus arise from cancellation of opposing effects, rather than reflecting an underlying simplicity.