Al momento, questa pagina non è disponibile nella lingua scelta. È possibile visualizzare una traduzione automatica realizzata con Google Translate. Renishaw declina qualsiasi responsabilità relativa alla fornitura di tale servizio e specifica di non avere controllato la traduzione.
È possibile contattarci per richiedere ulteriore assistenza.

Study cell biology with Raman microscopy

Raman spectroscopy is a non-invasive and label-free technique. Extract chemical information without the need to manipulate genes, or use stains or antibodies. This helps ensure the results reflect the true chemistry of the cells.

Identify cells

Use Renishaw Raman systems to identify and distinguish, for example:

cancer cells from normal cells
stem cells from differentiated cells
different sub-states in a cell population (e.g. stem and progenitor cells)

You can identify cells without known markers, based on their inherent chemical profiles. There is no need to conjugate with antibodies or manipulate genes.

See fine biological detail

With high spatial resolution confocal Raman analyses you can examine:

intracellular structures and biomolecules in individual cells, in situ
the chemical contents of inclusions in yeast cells
the lipid contents in cancer cells, to better understand lipid metabolism

Study individual cells within a population and determine cell-to-cell variability. For example, you can analyse the distribution of lipids and DNA in healthy and abnormal cells.

Raman image of human osteosarcoma (bone cancer) cells.

Raman image of human osteosarcoma (bone cancer) cells.

Raman image of human osteosarcoma (bone cancer) cells, showing the nuclei (green), nucleoli (red), membrane bound organelles (cyan) and the cell body (yellow – thick region, blue – membranous area). Renishaw thanks Dr Frederick Coffman, Rutgers New Jersey Medical School, USA, for providing the cell sample.
[886 x 575] [249kB]

Study live cells

You can equip your Renishaw Raman system with a cell incubator. This chamber can control temperature, CO₂ concentration, and humidity to keep cells in their normal physiological states during analysis.

Live cell data provides a better representation of any dynamic processes than end point experiments. For example, you can monitor the cells' response to changes in their environment or drugs. These responses may manifest themselves as metabolic or morphological changes, or cell death (apoptosis), all of which are detectable by Raman spectroscopy.

Resolve changes within cells in 3-D

Gather chemical information and produce 3-D views of your samples, and use these to verify the uptake of materials by cells. You can also determine the volumes of the cell and its organelles.

Images of glioma cells

Images of glioma cells

a) section from a 3D Raman volume map of a glioma cell. It shows the distribution of the organelles: white/grey (cell body); yellow/orange (nucleus); blue (lipid droplets / membrane-bound organelles). Renishaw thanks Dr Matthew Baker, University of Central Lancashire, UK, for providing the cell sample. b) Raman volume image, showing the nucleus (red) and lipid droplets / membrane-bound organelles, such as Golgi apparatus, endoplasmic reticulum and mitochondria (blue). Renishaw thanks: Dr Alex Berquand, Bruker Nano GmbH, Germany, for collecting and processing the AFM data; Dr Matthew Baker, University of Central Lancashire, UK, for providing the cell sample.
[1000 x 371] [161kB]

We're here when you need us

To find out more about this application area, or an application that isn't covered here, contact our applications team.

Contact our applications team

Webinar – Resonance Raman spectroscopy for redox biology research

Resonance Raman (RR) spectroscopy is the ideal tool for redox biology research. Not only does it demonstrate high sensitivity to haem proteins, it can also elucidate their oxidation and oxygenation states in situ (solution, organelles, cells and tissues). RR imaging provides both chemical and spatial information, enabling correlations between haem protein distribution, oxidation state, and protein/cell function to be made.

Watch the webinar

Download document

Application note: Classification of brain glioma tumours using the Renishaw Biological Analyser

This case study shows how you can use the RA816 analyser to discriminate between diseased and healthy brain tissue using. We analysed Raman spectra with data classification models to differentiate between brain glioma subtypes.

AN176(EN)-01-C Cell imaging with the inVia confocal Raman microscope Thumbnail

Application note: Cell imaging with the inVia confocal Raman microscope

With an inVia microscope, you can identify and characterise biological cells to obtain chemical, spatial and structural information on multiple biomolecules, without labelling. Get high-resolution chemical images with high specificity to study intracellular structures.

AN190(EN)-01-A SERS imaging using inVia Thumbnail

Application note: Surface enhanced Raman spectroscopy (SERS) imaging using the inVia confocal Raman microscope

The SERS technique uses colloidal silver or gold nanoparticles or roughened metallic substrates to amplify the Raman scattering intensity of adsorbed molecules. You can use SERS imaging to evaluate the efficacy of delivery of nanoparticles (NPs) into cells and animals. SERS measurements can also be used for biosensing, multiplexing and theranostics.

Application note: Redox biology with the inVia confocal Raman microscope

You can use Raman spectroscopy to study the redox biology of haem proteins, without the need for isolation or staining. The redox of haem proteins is closely linked to their protein functions – oxygen transport and storage, electron transport, and scavenging of free radicals. By using Raman spectroscopy to elucidate redox states within biological systems, we can understand redox dynamics and its effects on health regulation and disease.

Portrait of a dying cell

First published in 'The Pathologist,’ this article describes confocal Raman spectroscopy as a non-invasive way of studying cells during autophagy, apoptosis and cancer. Ultimately, this research may lead to a better understanding of cancer.

You may be interested in these papers:

Lau et al (2014) Biomedical Spectroscopy and Imaging 3: 237-247
McAughtrie et al (2013) Chem Sci 4: 3566-72
Kim et al (2010) Anal Bioanal Chem 398: 3051-3061