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. 2019 Jan 9;10(2):500-513.
doi: 10.1364/BOE.10.000500. eCollection 2019 Feb 1.

Label-free detection of hydrogen peroxide-induced oxidative stress in human retinal pigment epithelium cells via laser tweezers Raman spectroscopy

Affiliations

Label-free detection of hydrogen peroxide-induced oxidative stress in human retinal pigment epithelium cells via laser tweezers Raman spectroscopy

Yang Chen et al. Biomed Opt Express. .

Abstract

Human retinal pigment epithelium cells under hydrogen peroxide-induced oxidative stress and a ligustrazine-based protective effect were investigated using laser tweezers Raman spectroscopy. Protein and lipid were significantly affected by oxidative damage, along with increased reactive oxygen species (ROS) level within cells. The effects of ligustrazine against the reaction of ROS with protein seemed to be able to inhibit such damages but were limited during the desamidization of amides, along with additional effect on nucleic acid base and DNA phosphoric acid skeleton. This work laid the basis for both understanding the molecular mechanisms of oxidative stress-induced injury and highlighting possible biomarkers in retinal diseases.

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Conflict of interest statement

The authors declare that there are no conflicts of interest related to this article.

Figures

Fig. 1
Fig. 1
Schematic of the home-made laser tweezers Raman spectroscopy (LTRS) system. Diode laser beam of 785 nm was delivered to an inverted microscope for both trapping RPE cells and generating Raman signals from cells. Backwards Raman scattering light was recorded by a back-illuminated and deep-depletion near-infrared intensified CCD. M: mirror; L: lens; PH: pinhole; BF: band-pass filter; DM: dichroic mirror; NF: notch filter.
Fig. 2
Fig. 2
Measurement of ROS production by fluorescence microscopy. (A) Visualization and (B) Integral optical density (IOD) value of fluorescent product for different groups.
Fig. 3
Fig. 3
Pair-comparison of normalized mean Raman spectra from (A) the control group and the oxidative stress challenge group, (B) the control and ligustrazine group, (C) the oxidative stress challenge group and the ligustrazine group. The shaded areas (grey and green) represent the standard deviations of the means. Also shown at the bottom is the difference spectrum.
Fig. 4
Fig. 4
Score plots of the first two principal components by analysis of (A) whole Raman data and (B) bands data, along with the loading plots for (C) PC1 and (D) PC2.
Fig. 5
Fig. 5
Importance of independent Raman bands in the CRT models executed for (A) all three groups, (B) control vs. high oxidative stress, (C) control vs. ligustrazine, (D) high oxidative stress vs. ligustrazine. The band importance means a contribution of each band to the establishment of the model as a variable.
Fig. 6
Fig. 6
Relative quantitation of three cellular macromolecules that comes from (A) protein, (B) nucleic acid, and (C) lipid, respectively. X-axis: ratio of Raman bands; *: p<0.05: **: p<0.01.

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