Iron-binding cellular profile of transferrin using label-free Raman hyperspectral imaging and singular value decomposition (SVD)

Tubbesing, Kate; Khoo, Ting Chean; Jangjoo, Shahab Bahreini; Barroso, Margarida; Khmaladze, Alexander

doi:10.1016/j.freeradbiomed.2021.04.030

Cited by 10 publications

(14 citation statements)

References 33 publications

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“…Raman spectroscopy is often used on complex biological samples to identify chemical signatures and changes produced by alterations in the environment, such as through cell treatment [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. Inelastic Raman scattering, which occurs when there is an energy exchange between an incident photon and a molecule, results in scattered photons of different wavelengths than the original ones.…”

Section: Resultsmentioning

confidence: 99%

Telomere Length Shortening in Microglia: Implication for Accelerated Senescence and Neurocognitive Deficits in HIV

et al. 2021

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The widespread use of combination antiretroviral therapy (cART) has led to the accelerated aging of the HIV-infected population, and these patients continue to have a range of mild to moderate HIV-associated neurocognitive disorders (HAND). Infection results in altered mitochondrial function. The HIV-1 viral protein Tat significantly alters mtDNA content and enhances oxidative stress in immune cells. Microglia are the immune cells of the central nervous system (CNS) that exhibit a significant mitotic potential and are thus susceptible to telomere shortening. HIV disrupts the normal interplay between microglia and neurons, thereby inducing neurodegeneration. HIV cART contributes to the inhibition of telomerase activity and premature telomere shortening in activated peripheral blood mononuclear cells (PBMC). However, limited information is available on the effect of cART on telomere length (TL) in microglia. Although it is well established that telomere shortening induces cell senescence and contributes to the development of age-related neuro-pathologies, the effect of HIV-Tat on telomere length in human microglial cells and its potential contribution to HAND are not well understood. It is speculated that in HAND intrinsic molecular mechanisms that control energy production underlie microglia-mediated neuronal injury. TL, telomerase and mtDNA expression were quantified in microglial cells using real time PCR. Cellular energetics were measured using the Seahorse assay. The changes in mitochondrial function were examined by Raman Spectroscopy. We have also examined TL in the PBMC obtained from HIV-1 infected rapid progressors (RP) on cART and those who were cART naïve, and observed a significant decrease in telomere length in RP on cART as compared to RP’s who were cART naïve. We observed a significant decrease in telomerase activity, telomere length and mitochondrial function, and an increase in oxidative stress in human microglial cells treated with HIV Tat. Neurocognitive impairment in HIV disease may in part be due to accelerated neuro-pathogenesis in microglial cells, which is attributable to increased oxidative stress and mitochondrial dysfunction.

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Section: Resultsmentioning

confidence: 99%

Telomere Length Shortening in Microglia: Implication for Accelerated Senescence and Neurocognitive Deficits in HIV

et al. 2021

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“…Statistical tests for peak ratio analysis included single-factor ANOVA with a Dunnett’s post hoc and Student’s t -test with Bonferroni correction (statistical values provided in Additional file 1 : Tables). In-house MATLAB code was used to implement the SVD analysis [ 19 ]. The MATLAB code took stacked Raman spectra as the input n × m matrix, where n is the number of points in the spectrum and m is the number of Raman spectra in the dataset.…”

Section: Methodsmentioning

confidence: 99%

Raman microspectroscopy fingerprinting of organoid differentiation state

et al. 2022

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Background Organoids, which are organs grown in a dish from stem or progenitor cells, model the structure and function of organs and can be used to define molecular events during organ formation, model human disease, assess drug responses, and perform grafting in vivo for regenerative medicine approaches. For therapeutic applications, there is a need for nondestructive methods to identify the differentiation state of unlabeled organoids in response to treatment with growth factors or pharmacologicals. Methods Using complex 3D submandibular salivary gland organoids developed from embryonic progenitor cells, which respond to EGF by proliferating and FGF2 by undergoing branching morphogenesis and proacinar differentiation, we developed Raman confocal microspectroscopy methods to define Raman signatures for each of these organoid states using both fixed and live organoids. Results Three separate quantitative comparisons, Raman spectral features, multivariate analysis, and machine learning, classified distinct organoid differentiation signatures and revealed that the Raman spectral signatures were predictive of organoid phenotype. Conclusions As the organoids were unlabeled, intact, and hydrated at the time of imaging, Raman spectral fingerprints can be used to noninvasively distinguish between different organoid phenotypes for future applications in disease modeling, drug screening, and regenerative medicine.

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“…The SVD analysis facilitates the unbiased processing of large spectral datasets. The spectra with similar features will cluster together on the SVD scatter plot, while the SVD components provide insight into the specific spectral regions that differentiate the samples [10]. A line systematically placed in each SVD scatter plot (Figures 3L, 3O & 3R) is perpendicular and equidistant to the individual mean of each cluster; it is used to quantify the separation of treatments (Figures 3M, 3P & 3S).…”

Section: Fgf2 Treated Organoids Have a Raman Signature Which Is Distinct From Untreated Or Egf Treated Organoidsmentioning

confidence: 99%

“…Peak ratio analysis was completed with a normalized spectral dataset in a spreadsheet (Excel, Microsoft). In-house Matlab code was used to implement the SVD analysis [10]. The Matlab code took stacked Raman spectra as the input n×m matrix, where n is the number of points in the spectrum and m is the number of Raman spectra in the dataset.…”

Section: Spectral Analysis: Peak Ratios and Singular Value Decomposition (Svd)mentioning

confidence: 99%

“…In clinical settings, low-resolution fiber-based Raman measurements allow the discrimination of healthy tissue regions from disease-or tumor-burdened regions [8,9]. The higher resolution approaches implemented with Raman micro-spectroscopy can be used to gain information on sub-cellular or cellular populations, with the scale determined by the numerical aperture of the microscope objective and the confocal settings of the instrument [10][11][12][13]. Importantly, while Raman spectroscopy is often compared to Fourier transform infrared (FTIR) spectroscopy, the hydrated biological samples are better suited for Raman measurements that do not have the interference from water [14].…”

Section: Main Text Introductionmentioning

confidence: 99%

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Unlabeled salivary gland organoids have distinct Raman signatures following FGF2-induced proacinar cell differentiation

Tubbesing

Moskwa

Khoo

et al. 2021

Preprint

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Organoids are self-organized three-dimensional (3D) tissue cultures that model the structure and function of organs to provide insights into signaling during organ formation and have translational applications in disease modeling and assessing drug responses. Due to their heterogeneity, there is a need for non-destructive methods to identify the differentiation state, or the phenotype, of organoids. As organoids often contain complex mixtures of basement membrane and/or extracellular matrix proteins, which are often highly auto-fluorescent, it typically makes low-resolution Raman measurements a challenge. We developed Raman confocal micro-spectroscopy methods to avoid and minimize the matrix signal and define specific Raman signatures for growth factor-differentiated and non-differentiated organoids. In complex, branched salivary gland organoids derived from mouse embryonic epithelial and stromal cells embedded within the laminin-rich basement membrane matrix, Matrigel, we identified specific Raman spectral signatures for organoids in different differentiation states. We report that either comparison of spectral signatures or multivariate SVD analysis can be used to distinguish between organoids treated with FGF2, organoids treated with EGF, and non-treated controls. Raman spectral signatures can be used to non-invasively distinguish between different phenotypes in the 3D context of unlabeled organoids.

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Iron-binding cellular profile of transferrin using label-free Raman hyperspectral imaging and singular value decomposition (SVD)

Cited by 10 publications

References 33 publications

Telomere Length Shortening in Microglia: Implication for Accelerated Senescence and Neurocognitive Deficits in HIV

Telomere Length Shortening in Microglia: Implication for Accelerated Senescence and Neurocognitive Deficits in HIV

Raman microspectroscopy fingerprinting of organoid differentiation state

Unlabeled salivary gland organoids have distinct Raman signatures following FGF2-induced proacinar cell differentiation

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