Raman Spectroscopic Studies on Screening of Myopathies

Gautam, Rekha; Vanga, Sandeep; Madan, Aditi; Gayathri, Narayanappa; Nongthomba, Upendra; Umapathy, Siva

doi:10.1021/ac503647x

Cited by 35 publications

(40 citation statements)

References 52 publications

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“…One such promising non-invasive technique is Raman spectroscopy, which provides specific molecular signatures of a variety of materials, including biological samples [9,10,11]. Other important aspects of Raman spectroscopy are that it needs minimal sample preparation and is relatively insensitive to interference from water and hence easily applicable for in vivo studies of biological samples.…”

Section: Introductionmentioning

confidence: 99%

Different Phases of Breast Cancer Cells: Raman Study of Immortalized, Transformed, and Invasive Cells

Chaturvedi

Balaji

et al. 2016

Biosensors

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Breast cancer is the most prevalent cause of cancer-associated death in women the world over, but if detected early it can be treated successfully. Therefore, it is important to diagnose this disease at an early stage and to understand the biochemical changes associated with cellular transformation and cancer progression. Deregulated lipid metabolism has been shown to contribute to cell transformation as well as cancer progression. In this study, we monitored the biomolecular changes associated with the transformation of a normal cell into an invasive cell associated with breast cancer using Raman microspectroscopy. We have utilized primary normal breast cells, and immortalized, transformed, non-invasive, and invasive breast cancer cells. The Raman spectra were acquired from all these cell lines under physiological conditions. The higher wavenumber (2800–3000 cm−1) and lower wavenumber (700–1800 cm−1) range of the Raman spectrum were analyzed and we observed increased lipid levels for invasive cells. The Raman spectral data were analyzed by principal component–linear discriminant analysis (PC-LDA), which resulted in the formation of distinct clusters for different cell types with a high degree of sensitivity. The subsequent testing of the PC-LDA analysis via the leave-one-out cross validation approach (LOOCV) yielded relatively high identification sensitivity. Additionally, the Raman spectroscopic results were confirmed through fluorescence staining tests with BODIPY and Nile Red biochemical assays. Furthermore, Raman maps from the above mentioned cells under fixed conditions were also acquired to visualize the distribution of biomolecules throughout the cell. The present study shows the suitability of Raman spectroscopy as a non-invasive, label-free, microspectroscopic technique, having the potential of probing changes in the biomolecular composition of living cells as well as fixed cells.

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Section: Introductionmentioning

confidence: 99%

Different Phases of Breast Cancer Cells: Raman Study of Immortalized, Transformed, and Invasive Cells

Chaturvedi

Balaji

et al. 2016

Biosensors

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“…Raman spectroscopy is based on the principle of inelastic scattering of light upon interaction with the molecules and provides a fingerprint of the molecular composition of the sample under investigation. [12][13][14][15][16] The Raman spectrum is sensitive to changes in the structure and the chemical environment of the molecule.…”

Section: Introductionmentioning

confidence: 99%

Ascorbate Protects Neurons against Oxidative Stress: A Raman Microspectroscopic Study

Dutta¹,

Gautam²,

Chatterjee³

et al. 2015

ACS Chem. Neurosci.

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Oxidative stress due to excessive accumulation of reactive oxygen or nitrogen species in the brain as seen in certain neurodegenerative diseases can have deleterious effects on neurons. Hydrogen peroxide, endogenously generated in neurons under normal physiological conditions, can produce an excess of hydroxyl radical via a Fenton mediated mechanism. This may induce acute oxidative injury if not scavenged or removed effectively by antioxidants. There are several biochemical assay methods to estimate oxidative injury in cells; however, they do not provide information on the biochemical changes as the cells get damaged progressively under oxidative stress. Raman microspectroscopy offers the possibility of real time monitoring of the chemical composition of live cells undergoing oxidative stress under physiological conditions. In the present study, a hippocampal neuron coculture was used to observe the acute impact of hydroxyl radicals generated by hydrogen peroxide in the presence of Fe(2+) (Fenton reaction). Raman peaks related to nucleic acids (725, 782, 1092, 1320, 1340, 1420, and 1576 cm(-1)) showed time-dependent changes over the experimental period (60 min), indicating the breakdown of the phosphodiester backbone as well as nuclear bases. Interestingly, ascorbic acid (a potent antioxidant) when cotreated with Fenton reactants showed protection of cells as inferred from the Raman spectra, presumably by scavenging hydroxyl radicals. Little or no change in the Raman spectra was observed for untreated control cells and for cells exposed to Fe(2+) only, H2O2 only, and ascorbate only. A live-dead assay study also supported the current observations. Hence, Raman microspectroscopy has the potential to be an excellent noninvasive tool for early detection of oxidative stress that is seen in neurodegenerative diseases.

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“…In the literature, many studies have been conducted where the PC-LDA model is used for classification purposes [38,45,47,58,71]. We have also performed a PC-LDA analysis on the preprocessed Raman spectra from Drosophila muscles to differentiate between 2-and 12-days old flies using MatLab (Math Works, 2010) and R (Team, 2012) [9]. Raman spectra were recorded using a commercial Raman micro-spectrometer (Renishaw, InVia system) at 785 nm excitation wavelength, which was focused onto the muscles using 50x (NA = 0.75) objective for an integration time of 150 s. As a first preprocessing step cosmic ray removal was done after acquiring each spectrum using Renishaw WiRE 3.2 software.…”

Section: A) Linear Discriminant Analysis (Lda)mentioning

confidence: 99%

“…So, it is interesting to observe what happens to performance metrics like "sensitivity" and "specificity" as this threshold is varied from '0' to '1'. The ROC curves capture this behavior by plotting "sensitivity" against "FPR (1-specificity, which indicates false alarms)" for the different possible probability thresholds of a classification model [9,38,68,95]. It exhibits the tradeoff between "sensitivity" and "specificity" i.e.…”

Section: Receiver Operating Characteristics (Roc) Curvesmentioning

confidence: 99%

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Review of multidimensional data processing approaches for Raman and infrared spectroscopy

et al. 2015

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Raman and Infrared (IR) spectroscopies provide information about the structure, functional groups and environment of the molecules in the sample. In combination with a microscope, these techniques can also be used to study molecular distributions in heterogeneous samples. Over the past few decades Raman and IR microspectroscopy based techniques have been extensively used to understand fundamental biology and responses of living systems under diverse physiological and pathological conditions. The spectra from biological systems are complex and diverse, owing to their heterogeneous nature consisting of bio-molecules such as proteins, lipids, nucleic acids, carbohydrates etc. Sometimes minor differences may contain critical information. Therefore, interpretation of the results obtained from Raman and IR spectroscopy is difficult and to overcome these intricacies and for deeper insight we need to employ various data mining methods. These methods must be suitable for handling large multidimensional data sets and for exploring the complete spectral information simultaneously. The effective implementation of these multivariate data analysis methods requires the pretreatment of data. The preprocessing of raw data helps in the elimination of noise (unwanted signals) and the enhancement of discriminating features. This review provides an outline of the state-of-the-art data processing tools for multivariate analysis and the various preprocessing methods that are widely used in Raman and IR spectroscopy including imaging for better qualitative and quantitative analysis of biological samples.

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Raman Spectroscopic Studies on Screening of Myopathies

Cited by 35 publications

References 52 publications

Different Phases of Breast Cancer Cells: Raman Study of Immortalized, Transformed, and Invasive Cells

Different Phases of Breast Cancer Cells: Raman Study of Immortalized, Transformed, and Invasive Cells

Ascorbate Protects Neurons against Oxidative Stress: A Raman Microspectroscopic Study

Review of multidimensional data processing approaches for Raman and infrared spectroscopy

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