Label‐free quantitative chemical imaging and classification analysis of adipogenesis using mouse embryonic stem cells

Abstract

Stem cells have received much attention recently for their potential utility in regenerative medicine. The identification of their differentiated progeny often requires complex staining procedures, and is challenging for intermediary stages which are a priori unknown. In this work, the ability of label-free quantitative coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy to identify populations of intermediate cell states during the differentiation of murine embryonic stem cells into adipocytes is assessed. Cells were imaged at different days of differentiation by hyperspectral CARS, and images were analysed with an unsupervised factorization algorithm providing Raman-like spectra and spatially resolved maps of chemical components. Chemical decomposition combined with a statistical analysis of their spatial distributions provided a set of parameters that were used for classification analysis. The first 2 principal components of these parameters indicated 3 main groups, attributed to undifferentiated cells, cells differentiated into committed white pre-adipocytes, and differentiating cells exhibiting a distinct protein globular structure with adjacent lipid droplets. An unsupervised classification methodology was developed, separating undifferentiated cell from cells in other stages, using a novel method to estimate the optimal number of clusters. The proposed unsupervised classification pipeline of hyperspectral CARS data offers a promising new tool for automated cell sorting in lineage analysis.

Label-Free Volumetric Quantitative Imaging of the Human Somatic Cell Division by Hyperspectral Coherent Anti-Stokes Raman Scattering

“…We have developed an algorithm to analyze CARS hyperspectral images which determines quantitative spectra and absolute concentration images of separate chemical components without prior knowledge, called FSC 3 (factorization into spectra and concentrations of chemical components). , In this method the hyperspectral data are factorized as D = ∑ i C i × S i + E , with C i and S i being the non-negative concentration distribution and spectrum of the i th component, respectively, and E is the error, the norm of which is minimized. This method was recently used to quantitatively measure the lipid uptake in human adipose derived stem cells, , to investigate the differentiation of stem cells, and toward high-throughput imaging using a Bessel beam and sparse sampling . It was also shown to be suited for the quantitative determination of the absolute volume of chemical components in three-dimensional imaging, using polystyrene beads as proof-of-principle .…”

Raman microspectroscopy reveals unsaturation heterogeneity at the lipid droplet level and validates an in vitro model of bone marrow adipocyte subtypes

“…This approach allowed us to focus lipid composition analysis exclusively on mature adipocytes and not on the remaining unlipidated stromal component. Previous studies have shown t h e a p p l i c a t i o n o f C o h e r e n t a n t i -S t o k e s R a m a n microspectroscopy to embryonic stem cells undergoing adipogenic differentiation, showing a measure of chemical lipid saturation composition and an increase in LD accumulation with differentiation (71,72). While, very interestingly, individual LDs within one adipocyte appear to have an inhomogeneity in their chemical composition, this was not further analyzed.…”

Raman microspectroscopy reveals unsaturation heterogeneity at the lipid droplet level and validates anin vitromodel of bone marrow adipocyte subtypes

“…This approach allowed us to focus lipid composition analysis exclusively on mature adipocytes and not on the remaining unlipidated stromal component. Previous studies have shown the application of Coherent anti-Stokes Raman microspectroscopy to embryonic stem cells undergoing adipogenic differentiation, showing a measure of chemical lipid saturation composition and an increase in LD accumulation with differentiation (71, 72). While, very interestingly, individual LDs within one adipocyte appear to have an inhomogeneity in their chemical composition, this was not further analyzed.…”