Using redox-sensitive mitochondrial cytochrome Raman bands for label-free detection of mitochondrial dysfunction.

Mitochondrial activity is a widely used criterion to judge the metabolic condition of a living specimen. Numerous methods have been developed for related analyses, including the detection of O2 consumption, trans-membrane potential, and ATP production. In this study, we demonstrate that the redox state of cytochromes can serve as a sensitive mitochondrial activity indicator in glutamate-stressed neuronal cells.

Cell type discrimination based on image features of molecular component distribution.

Machine learning-based cell classifiers use cell images to automate cell-type discrimination, which is increasingly becoming beneficial in biological studies and biomedical applications. Brightfield or fluorescence images are generally employed as the classifier input variables. We propose to use Raman spectral images and a method to extract features from these spatial patterns and explore the value of this information for cell discrimination.

Protein expression guided chemical profiling of living cells by the simultaneous observation of Raman scattering and anti-Stokes fluorescence emission.

Our current understanding of molecular biology provides a clear picture of how the genome, transcriptome and proteome regulate each other, but how the chemical environment of the cell plays a role in cellular regulation remains much to be studied. Here we show an imaging method using hybrid fluorescence-Raman microscopy that measures the chemical micro-environment associated with protein expression patterns in a living cell. Simultaneous detection of fluorescence and Raman signals, realised by spectrally separating the two modes through the single photon anti-Stokes fluorescence emission of fluorescent proteins, enables the accurate correlation of the chemical fingerprint of a specimen to its physiological state.

Rapid in vivo lipid/carbohydrate quantification of single microalgal cell by Raman spectral imaging to reveal salinity-induced starch-to-lipid shift.

Background: Lipid/carbohydrate content and ratio are extremely important when engineering algal cells for liquid biofuel production. However, conventional methods for such determination and quantification are not only destructive and tedious, but also energy consuming and environment unfriendly. In this study, we first demonstrate that Raman spectroscopy is a clean, fast, and accurate method to simultaneously quantify the lipid/carbohydrate content and ratio in living microalgal cells.

Non-label immune cell state prediction using Raman spectroscopy.

The acquired immune system, mainly composed of T and B lymphocytes, plays a key role in protecting the host from infection. It is important and technically challenging to identify cell types and their activation status in living and intact immune cells, without staining or killing the cells. Using Raman spectroscopy, we succeeded in discriminating between living T cells and B cells, and visualized the activation status of living T cells without labeling.

Structured line illumination Raman microscopy.

In the last couple of decades, the spatial resolution in optical microscopy has increased to unprecedented levels by exploiting the fluorescence properties of the probe. At about the same time, Raman imaging techniques have emerged as a way to image inherent chemical information in a sample without using fluorescent probes. However, in many applications, the achievable resolution is limited to about half the wavelength of excitation light.

Time-lapse Raman imaging of osteoblast differentiation.

Osteoblastic mineralization occurs during the early stages of bone formation. During this mineralization, hydroxyapatite (HA), a major component of bone, is synthesized, generating hard tissue. Many of the mechanisms driving biomineralization remain unclear because the traditional biochemical assays used to investigate them are destructive techniques incompatible with viable cells.

Visualizing the appearance and disappearance of the attractor of differentiation using Raman spectral imaging.

Using Raman spectral imaging, we visualized the cell state transition during differentiation and constructed hypothetical potential landscapes for attractors of cellular states on a state space composed of parameters related to the shape of the Raman spectra. As models of differentiation, we used the myogenic C2C12 cell line and mouse embryonic stem cells. Raman spectral imaging can validate the amounts and locations of multiple cellular components that describe the cell state such as proteins, nucleic acids, and lipids; thus, it can report the state of a single cell.

Dual-polarization Raman spectral imaging to extract overlapping molecular fingerprints of living cells.

Raman spectral imaging is gaining more and more attention in biological studies because of its label-free characteristic. However, the discrimination of overlapping chemical contrasts has been a major challenge. In this study, we introduce an optical method to simultaneously obtain two orthogonally polarized Raman images from a single scan of the sample.

Visualizing cell state transition using Raman spectroscopy.

System level understanding of the cell requires detailed description of the cell state, which is often characterized by the expression levels of proteins. However, understanding the cell state requires comprehensive information of the cell, which is usually obtained from a large number of cells and their disruption. In this study, we used Raman spectroscopy, which can report changes in the cell state without introducing any label, as a non-invasive method with single cell capability.

On the origin of the 1602 cm-1 Raman band of yeasts; contribution of ergosterol.

The 1602 cm(-1) Raman signature, which we call the "Raman spectroscopic signature of life" in yeasts, is a marker Raman band for cell metabolic activity. Despite the established fact that its intensity sensitively reflects the metabolic status of the cell, its molecular origin remained unclear. In this work, we propose ergosterol as the major contributor of the 1602 cm(-1) Raman signature.

The "Raman spectroscopic signature of life" is closely related to haem function in budding yeasts.

HEM1 gene encodes δ-aminolevulinate synthase that is required for haem synthesis. It is an essential gene for yeast survival. The Raman spectra of HEM1 knockout (hem1Δ) yeast cells lacks a Raman band at 1602 cm(-1) that has been shown to reflect cell metabolic activity.