Raman spectra are molecular structure-specific and hence are employed in applications requiring chemical identification. The advent of efficient handheld and smartphone-based Raman instruments is promoting widespread applications of the technique, which often involve less trained end users. Software modules that enable spectral library searches based on spectral pattern matching is an essential part of such applications. The Raman spectrum recorded by end users will naturally have varying levels of signal to noise (SN), baseline fluctuations, etc., depending on the sample environment. Further, in biological, forensic, food, pharmaceuticals, etc., fields where a vast amount of Raman spectral data is generated, careful removal of background is often impossible. In other words, a 100% match between the library spectrum and user input cannot be often guaranteed or expected. Often, such influences are discounted upon developing mathematical methods for general applications. In this manuscript, we carefully examine how such effects would determine the results of spectral similarity-based library search. We show that several popular mathematical spectral matching approaches give incorrect results under the influence of small changes in the baseline and/or the noise. We also discuss the points to be carefully considered while generating a spectral library. We believe our results will be a guiding note for developing applications of Raman spectroscopy that uses a standard spectral library and mathematical spectral matching.

We demonstrate a novel bio-spectroscopic technique, "simultaneous Raman/GFP microspectroscopy". It enables organelle specific Raman microspectroscopy of living cells. Fission yeast, Schizosaccharomyces pombe, whose mitochondria are green fluorescence protein (GFP) labeled, is used as a test model system. Raman excitation laser and GFP excitation light irradiate the sample yeast cells simultaneously. GFP signal is monitored in the anti-Stokes region where interference from Raman scattering is negligibly small. Of note, 13 568 Raman spectra measured from different points of 19 living yeast cells are categorized according to their GFP fluorescence intensities, with the use of a two-component multivariate curve resolution with alternate least squares (MCR-ALS) analysis in the anti-Stokes region. This categorization allows us to know whether or not Raman spectra are taken from mitochondria. Raman spectra specific to mitochondria are obtained by an MCR-ALS analysis in the Stokes region of 1389 strongly GFP positive spectra. Two mitochondria specific Raman spectra have been obtained. The first one is dominated by protein Raman bands and the second by lipid Raman bands, being consistent with the known molecular composition of mitochondria. In addition, the second spectrum shows a strong band of ergosterol at 1602 cm-1 , previously reported as "Raman spectroscopic signature of life of yeast."

In Japan, the imports of meat products have been increasing every year. Heat processing of meat is the current standard method for ensuring domestic animal health, particularly in case of meat products from areas where infectious diseases are known to have occurred in domestic animals. The Animal Quarantine Service needs to establish a method that detects the temperature at which the meat has been heat-processed (endpoint temperature) to ensure that the standard protocol is followed at the production location. Here, we developed a Raman spectroscopy and multivariate statistics (viz. multivariate curve resolution (MCR))-based simple and rapid method for accurately estimating the end point temperature. We showed that the temperature-dependent secondary structure modification of proteins can serve as an accurate indicator of the temperature of heat processing. This methodology can be easily automated for effective utilization by someone who is not an expert in spectroscopy. We envisage a wider application of this method in food analysis, although the present research investigated the application of this method in chicken meat heat processing analysis.

α-lipoic acid (ALA) is an essential cofactor for many enzyme complexes in aerobic metabolism, especially in mitochondria of eukaryotic cells where respiration takes place. It also has excellent anti-oxidative properties. The acid has two stereo-isomers, R- and S- lipoic acid (R-LA and S-LA), but only the R-LA has biological significance and is exclusively produced in our body. A mutant strain of fission yeast, Δdps1, cannot synthesize coenzyme Q10, which is essential during yeast respiration, leading to oxidative stress. Therefore, it shows growth delay in the minimal medium. We studied anti-oxidant properties of ALA in its free form and their inclusion complexes with γ-cyclodextrin using this mutant yeast model. Both free forms R- and S-LA as well as 1:1 inclusion complexes with γ-cyclodextrin recovered growth of Δdps1 depending on the concentration and form. However, it has no effect on the growth of wild type fission yeast strain at all. Raman microspectroscopy was employed to understand the anti-oxidant property at the molecular level. A sensitive Raman band at 1602cm-1 was monitored with and without addition of ALAs. It was found that 0.5mM and 1.0mM concentrations of ALAs had similar effect in both free and inclusion forms. At 2.5mM ALAs, free forms inhibited the growth while inclusion complexes helped in recovered. 5.0mM ALA showed inhibitory effect irrespective of form. Our results suggest that the Raman band at 1602cm-1 is a good measure of oxidative stress in fission yeast.

Water is still mysterious despite intensive and extensive studies over the years. Anomalous behavior of water as a liquid is yet to be fully comprehended. Here we show that the most generally known anomaly of water, the density maximum anomaly, is well accounted for by the formation of nanometersize ice crystallite at low temperatures. We show spectroscopically that, in cold and super-cooled water, this nanometer-size ice crystallite is formed and coexists with the other two forms of water. Multivariate hyperspectral analysis of 140 temperature dependent Raman spectra in the range of -23∼45 °C determines the three distinct vibrational spectra of the three forms of water and their fractions at different temperatures. Simulation based on the determined fractions successfully reproduces the temperature dependence of density with a maximum at the right temperature. The mystery of the density maximum of water has thus been given an unequivocal solution. The nanometer-size ice crystallite might well be called "nano-ice".

Liposomes are closed phospholipid bilayer systems that have profound applications in fundamental cell biology, pharmaceutics and medicine. Depending on the composition (pure or mixture of phospholipids, presence of cholesterol) and preparation protocol; intra- and inter-chain molecular interactions vary leading to changes in the quality (order and packing) of liposomes. So far it is not possible to image conformational disorders and packing densities within a liposome in a straightforward manner. In this study, we utilized confocal Raman microspectroscopy to visualize structural disorders and packingefficiency within a giant multilamellar liposome model by focusing mainly on three regions in the vibrational spectrum (C-C stretching, C-H deformation and C-H stretching). We estimated properties such as trans/gauche isomers and lateral packing probability. Interestingly, our Raman imaging studies revealed gel phase rich domains and heterogeneous lateral packing within the giant multilamellar liposome. (C) 2017 Elsevier B.V. All rights reserved.

The aim of this study is to evaluate the existence of residual calculus on root surfaces by determining the fluorescence/Raman intensity ratio. Thirty-two extracted human teeth, partially covered with calculus on the root surface, were evaluated by using a portable Raman spectrophotometer, and a 785-nm, 100-mW laser was applied for fluorescence/Raman excitation. The collected spectra were normalized to the hydroxyapatite Raman band intensity at 960 cm(-1). Raman spectra were recorded from the same point after changing the focal distance of the laser and the target radiating angle. In seven teeth, the condition of calculus, cementum, and dentin were evaluated. In 25 teeth, we determined the fluorescence/Raman intensity ratio following three strokes of debridement. Raman spectra collected from the dentin, cementum, and calculus were different. After normalization, spectra values were constant. The fluorescence/Raman intensity ratio of calculus region showed significant differences compared to the cementum and dentin (p < 0.05). The fluorescence/Raman intensity ratio decreased with calculus debridement. For this analysis, the delta value was defined as the difference between the values before and after three strokes, with the final 2 delta values close to zero, indicating a gradual asymptotic curve and the change in intensity ratio approximating that of individual constants. Fluorescence/Raman intensity ratio was effectively used to cancel the angle-and distance-dependent fluctuations of fluorescence collection efficiency during measurement. Changes in the fluorescence/Raman intensity ratio near zero suggested that cementum or dentin was exposed, and calculus removed.

A new technology employing Raman spectroscopy is attracting attention as a powerful biochemical technique for the detection of beneficial and functional food nutrients, such as carotenoids and unsaturated fatty acids. This technique allows for the dynamic characterization of food nutrient substances for the rapid determination of food quality. In this study, we attempt to detect and measure astaxanthin from salmon fillets using this technology. The Raman spectra showed specific bands corresponding to the astaxanthin present in salmon and the value of astaxanthin (Raman band, 1518 cm(-1)) relative to those of protein/lipid (Raman band, 1446 cm(-1)) in the spectra increased in a dose-dependent manner. A standard curve was constructed by the standard addition method using astaxanthin as the reference standard for its quantification by Raman spectroscopy. The calculation formula was established using the Raman bands typically observed for astaxanthin (i.e., 1518 cm(-1)). In addition, we examined salmon fillets of different species (Atlantic salmon, coho salmon, and sockeye salmon) and five fillets obtained from the locations (from the head to tail) of an entire Atlantic salmon. Moreover, the sockeye salmon fillet exhibited the highest astaxanthin concentration (14.2 mg/kg), while coho salmon exhibited an intermediate concentration of 7.0 mg/kg. The Raman-based astaxanthin concentration in the five locations of Atlantic salmon was more strongly detected from the fillet closer to the tail. From the results, a rapid, convenient Raman spectroscopic method was developed for the detection of astaxanthin in salmon fillets.

We have recently demonstrated a methodology to estimate the percent crystallinity (PC) of polymers directly with Raman spectroscopy and multivariate curve resolution (MCR) by alternating least-squares (ALS). In the MCR-ALS methodology, the Raman spectrum of a semicrystalline polymer is separated into two constituent components (crystalline and molten/amorphous) and their corresponding concentrations. The methodology necessitates that the Raman spectrum at any temperature be a linear combination of two MCR spectral components (one molten and one crystalline). This is true in the case of simple systems such as crystalline pendant alkyl domains in polymers (Samuel et al. Anal. Chem. 2016, 88, 4644). However, in the case of main chain polymer crystals (e.g., polyethylene), the situation can be complicated owing to several molecular changes in the lattice in addition to conformational reorganizations during melting. Under this circumstance, a simple two-state model may not be adequate and we describe the modifications required to treat such systems, keeping the basic principles of the proposed methodology unchanged. A comparative study with wide-angle X-ray scattering (WAXS) and Raman spectroscopy is also performed to substantiate our findings. In addition to estimating percent crystallinity (PC), our methodology is capable of revealing additional information, such as interchain interactions in crystal lattice, that in principle will help distinguishing polymorphic transformations, subtle changes in lamellar lattice dimensions, and other phase changes in polymers.

Eosinophilic esophagitis (EoE) is believed to be a rare pathological condition that is characterized by dense infiltration of eosinophils in esophageal epithelial layer. Occurrence of this disease worldwide has started increasing rapidly in the last decade. Routine endoscopic observations can help in diagnosis only if clear longitudinal furrows or multiple concentric rings are observed but does not give any definitive conclusion in the early stages. Hence esophageal tissue samples are collected from multiple sites by biopsy and the number of eosinophils is counted after staining. Such a procedure is time consuming and has an inherent risk of bleeding, eventually damaging esophagus. Hence we developed a resonance Raman spectroscopy based approach to detect eosinophils in esophagus using mouse models. Our results show the presence of eosinophils in mice esophageal tissues suffering from inflammation by administering interleukin-33 while there are none in control mice. We believe this method can be used in clinical application for diagnosing EoE in the near future. (C) 2016 Elsevier B.V. All rights reserved.

Fungal cell walls are medically important since they represent a drug target site for antifungal medication. So far there is no method to directly visualize structurally similar cell wall components such as alpha-glucan, beta-glucan and mannan with high specificity, especially in a label-free manner. In this study, we have developed a Raman spectroscopy based molecular imaging method and combined multivariate curve resolution analysis to enable detection and visualization of multiple polysaccharide components simultaneously at the single cell level. Our results show that vegetative cell and ascus walls are made up of both alpha- and beta-glucans while spore wall is exclusively made of alpha-glucan. Co-localization studies reveal the absence of mannans in ascus wall but are distributed primarily in spores. Such detailed picture is believed to further enhance our understanding of the dynamic spore wall architecture, eventually leading to advancements in drug discovery and development in the near future.

We demonstrate a methodology to estimate the percent crystallinity of polymers directly with Raman spectroscopy and multivariate curve resolution (MCR) by alternating least-squares (ALS). In this methodology, the Raman spectrum of semicrystalline polymer is separated into two constituent components (crystalline and molten) and their corresponding concentrations. The percent crystallinity can be estimated as the change in area intensity of the molten spectral-component when polymer cools from a temperature above melting point to room temperature. The number of carbons in the crystalline lattice has also been estimated from the position of longitudinal acoustic (LA) Raman bands with the correlation established by Mizushima and Simanouti [Mizushima, S.; Simanouti, T. J. Am. Chem. Soc. 1949, 71, 1320]. The new method allows direct Raman estimation of absolute percent crystallinity of polymers. Until now, Raman spectroscopic estimation of percent crystallinity was possible only in conjunction with other techniques or by using internal standards.

The crystalline states of fats, i.e., the crystallinity and crystal polymorphic types, strongly influence their physical properties in fat-based foods. Imaging of fat crystalline states has thus been a subject of abiding interest, but conventional techniques cannot image crystallinity and polymorphic types all at once. This article demonstrates a new technique using Raman microspectroscopy for simultaneously imaging the crystallinity and polymorphic types of fats. The crystallinity and beta' crystal polymorph, which contribute to the hardness of fat-based food products, were quantitatively visualized in a model fat (porcine adipose tissue) by analyzing several key Raman bands. The emergence of the beta crystal polymorph, which generally results in food product deterioration, was successfully imaged by analyzing the whole fingerprint regions of Raman spectra using multivariate curve resolution alternating least squares analysis. The results demonstrate that the crystalline states of fats can be nondestructively visualized and analyzed at the molecular level, in situ, without laborious sample pretreatments. (C) 2015 Elsevier Ltd. All rights reserved.

We have developed an automatic and objective method for detecting human oral squamous cell carcinoma (OSCC) tissues with Raman microspectroscopy. We measure 196 independent Raman spectra from 196 different points of one oral tissue sample and globally analyze these spectra using a Multivariate Curve Resolution (MCR) analysis. Discrimination of OSCC tissues is automatically and objectively made by spectral matching comparison of the MCR decomposed Raman spectra and the standard Raman spectrum of keratin, a well-established molecular marker of OSCC. We use a total of 24 tissue samples, 10 OSCC and 10 normal tissues from the same 10 patients, 3 OSCC and 1 normal tissues from different patients. Following the newly developed protocol presented here, we have been able to detect OSCC tissues with 77 to 92% sensitivity (depending on how to define positivity) and 100% specificity. The present approach lends itself to a reliable clinical diagnosis of OSCC substantiated by the "molecular fingerprint" of keratin.

Acute hepatopancreatic necrosis disease (AHPND), also called early mortality syndrome (EMS), is a recently emergent shrimp bacterial disease that has resulted in substantial economic losses since 2009. AHPND is known to be caused by strains of Vibrio parahaemolyticus that contain a unique virulence plasmid, but the pathology of the disease is still unclear. In this study, we show that AHPND-causing strains of V. parahaemolyticus secrete the plasmid encoded binary toxin PirAB(vp) into the culture medium. We further determined that, after shrimp were challenged with AHPND-causing bacteria, the bacteria initially colonized the stomach, where they started to produce PirAB(vp) toxin. At the same early time point (6 hpi), PirB(vp) toxin, but not PirA(vp) toxin, was detected in the hepatopancreas, and the characteristic histopathological signs of AHPND, including sloughing of the epithelial cells of the hepatopancreatic tubules, were also seen. Although some previous studies have found that both components of the binary PirAB(vp) toxin are necessary to induce a toxic effect, our present results are consistent with other studies which have suggested that PirB(vp) alone may be sufficient to cause cellular damage. At later time points, the bacteria and PirA(vp) and PirB(vp) toxins were all detected in the hepatopancreas. We also show that Raman spectroscopy "Whole organism fingerprints" were unable to distinguish between AHPND-causing and non-AHPND causing strains. Lastly, by using minimum inhibitory concentrations, we found that both virulent and non-virulent V. parahaemolyticus strains were resistant to several antibiotics, suggesting that the use of antibiotics in shrimp culture should be more strictly regulated. (C) 2015 Elsevier Ltd. All rights reserved.

A straightforward in vivo monitoring technique for biomolecules would be an advantageous approach for understanding their spatiotemporal dynamics in living cells. However, the lack of adequate probes has hampered the quantitative determination of the chemical composition and metabolomics of cellular lipids at single-cell resolution. Here, we describe a method for the rapid, direct, and quantitative determination of lipid molecules from living cells using single-cell Raman imaging. In vivo localization of lipids in the form of triacylglycerol (TAG) within oleaginous microalga and their molecular compositions are monitored with high spatial resolution in a non-destructive and label-free manner. This method can provide quantitative and real-time information on compositions, chain lengths, and degree of unsaturation of fatty acids in living cells for improving the cultivating parameters or for determining the harvest timing during large-scale cultivations for microalgal lipid accumulation toward biodiesel production. Therefore, this technique is a potential tool for in vivo lipidomics for understanding the dynamics of lipid metabolisms in various organisms.

The study of spatial distribution of secondary metabolites within microbial cells facilitates the screening of candidate strains from marine environments for functional metabolites and allows for the subsequent assessment of the production of metabolites, such as antibiotics. This paper demonstrates the first application of Raman microspectroscopy for in situ detection of the antifungal antibiotic amphotericin B (AmB) produced by actinomycetes-Streptomyces nodosus. Raman spectra measured from hyphae of S. nodosus show the specific Raman bands, caused by resonance enhancement, corresponding to the polyene chain of AmB. In addition, Raman microspectroscopy enabled us to monitor the time-dependent change of AmB production corresponding to the growth of mycelia. The Raman images of S. nodosus reveal the heterogeneous distribution of AmB within the mycelia and individual hyphae. Moreover, the molecular association state of AmB in the mycelia was directly identified by observed Raman spectral shifts. These findings suggest that Raman microspectroscopy could be used for in situ monitoring of antibiotic production directly in marine microorganisms with a method that is non-destructive and does not require labeling.

Label-free Raman microspectroscopy combined with a multivariate curve resolution (MCR) analysis can be a powerful tool for studying a wide range of biomedical molecular systems. The MCR with the alternating least squares (MCR-ALS) technique, which retrieves the pure component spectra from complicatedly overlapped spectra, has been successfully applied to in vivo and molecular-level analysis of living cells. The principles of the MCR-ALS analysis are reviewed with a model system of titanium oxide crystal polymorphs, followed by two examples of in vivo Raman imaging studies of living yeast cells, fission yeast, and budding yeast. Due to the non-negative matrix factorization algorithm used in the MCR-ALS analysis, the spectral information derived from this technique is just ready for physical and/or chemical interpretations. The corresponding concentration profiles provide the molecular component distribution images (MCDIs) that are vitally important for elucidating life at the molecular level, as stated by Schroedinger in his famous book, "What is life?" Without any a priori knowledge about spectral profiles, time- and space-resolved Raman measurements of a dividing fission yeast cell with the MCR-ALS elucidate the dynamic changes of major cellular components (lipids, proteins, and polysaccharides) during the cell cycle. The MCR-ALS technique also resolves broadly overlapped OH stretch Raman bands of water, clearly indicating the existence of organelle-specific water structures in a living budding yeast cell. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

The inclusion complex of coenzyme Q10 (CoQ10) by gamma-cyclodextrin (gamma-CD), CoQ10-CD complex, was recently developed. The addition of the CoQ10-CD complex recovered the growth of a fission yeast mutant strain, Delta dps1, which otherwise cannot grow well due to the lack of coenzyme Q producing ability. However, the oxygen consumption rate of this strain was not restored by the addition of the CoQ10-CD complex. The addition of two other anti-oxidative reagents, glutathione and ascorbic acid, also recovered the growth of the Delta dps1 strain as well. These results indicated that the recovery of the growth of Delta dps1 was brought about by the anti-oxidative property of CoQ10. The intensity of Raman spectra of Delta dps1 at 1602 cm(-1), which is prominently observed for the wild type of the fission yeast, was compared between before and after addition of the CoQ10-CD complex. The signal was very weakly observed for Delta dps1 and did not increase in intensity by the addition of the CoQ10-CD complex. These results suggested the recovery of the growth of Delta dps1 was brought about not by the restoration of respiration function of Delta dps1 but by the anti-oxidative property of CoQ10 to result in the decrease in the oxidative stress. (c) 2013 Elsevier B.V. All rights reserved.

The study of intracellular water in living cells is a challenge of fundamental importance. While the critical roles of water in maintaining and propagating life have been widely recognized and accepted, our understanding of water/biomolecule interactions is surprisingly limited. Using Raman microspectroscopic imaging of a living yeast cell followed by a multivariate analysis in form of the nonnegative matrix factorization method, we successfully resolve organelle-specific water structures. The intensities and the band profiles of the segregated water OH stretch spectra yield important and otherwise unobtainable information on the extensive effect of the water/biomolecule interactions in a given organelle on the hydrogen-bonding network of water molecules. Copyright (C) 2012 John Wiley & Sons, Ltd.

Cellular processes are intrinsically complex and dynamic, in which a myriad of cellular components including nucleic acids, proteins, membranes, and organelles are involved and undergo spatiotemporal changes. Label-free Raman imaging has proven powerful for studying such dynamic behaviors in vivo and at the molecular level. To construct Raman images, univariate data analysis has been commonly employed, but it cannot be free from uncertainties due to severely overlapped spectral information. Here, we demonstrate multivariate curve resolution analysis for time-lapse Raman imaging of a single dividing yeast cell. A four-dimensional (spectral variable, spatial positions in the two-dimensional image plane, and time sequence) Raman data "hypercube" is unfolded. to a two-way array and then analyzed globally using multivariate curve resolution. The multivariate Raman imaging thus accomplished successfully disentangles dynamic changes of both concentrations and distributions of major cellular components (lipids, proteins, and polysaccharides) during the cell cycle of the yeast cell. The results show a drastic decrease in the amount of lipids by similar to 50% after cell division and uncover a protein-associated component that has not been detected with previous univariate approaches.

We have constructed a 1064 nm deep near-infrared (NIR) excited multichannel Raman microspectrometer using an InP/InGaAsP multichannel detector. This microspectrometer achieves high sensitivity suitable for in vivo measurements of single living cells with lateral resolution of 0.7 mu m and depth resolution of 3.1 mu m. It has been applied to the structural analysis of living cyanobacterial cells, well-known model organisms for photosynthesis research, which are too photolabile to be measured with visible laser excitation. High signal-to-noise ratio (SIN) Raman spectra have been obtained from carotenoid, chlorophyll a, and phycocyanin in a single living cyanobacterial cell with no appreciable interference from autofluorescence or photodamage. Sub-micrometer mapping of Raman intensities provides clear distribution images of the three pigments inside the cell.

Food safety requires the development of reliable techniques that ensure the origin of animal fats. In the present work, we try to verify the efficacy of using the polymorphic features of fats for discriminating animal-fat origins. We use Raman spectroscopy to collect the structural information of fat crystals. It is shown that a single Raman band at 1417 cm(-1) successfully differentiates pork fats from beef fats. This band is known to be characteristic of the beta'-polymorph of fats. Pork fats show this band because they contain the beta'-polymorph after rapid cooling to 0 degrees C. In beef pork-fat mixtures, this hand is not detected even in the presence of 50% pork fat; an addition of beef fat to pork fat is likely to produce a mixed fat with a completely different polymorphic behavior. This method seems to have the potential to detect beef products contaminated with pork-adipose tissue.

The 'Raman spectroscopic signature of life' is a Raman band at 1602 cm(-1) that sharply reflects the metabolic activity of cell mitochondria. Here we report the study of thissignature in isolated yeast mitochondria. The existence and behaviour of the 1602 cm(-1) band in isolated mitochondria have been confirmed to be the same as in living yeast cells: the intensity of the band decreases with timewhen a respiration inhibitor, sodium azide, is added. The present study shows the significance of isolated mitochondria in elucidating the origin of this still unassigned Raman band. Copyright (C). 2009 John Wiley & Sons, Ltd.