Raman Spectroscopy Cell-based Biosensors

Abstract

One of the main challenges faced by biodetection systems is the ability to detect and identify a large range of toxins at low concentrations and in short times. Cell-based biosensors rely on detecting changes in cell behaviour, metabolism, or induction of cell death following exposure of live cells to toxic agents. Raman spectroscopy is a powerful technique for studying cellular biochemistry. Different toxic chemicals have different effects on living cells and induce different time-dependent biochemical changes related to cell death mechanisms. Cellular changes start with membrane receptor signalling leading to cytoplasmic shrinkage and nuclear fragmentation. The potential advantage of Raman spectroscopy cell-based systems is that they are not engineered to respond specifically to a single toxic agent but are free to react to many biologically active compounds. Raman spectroscopy biosensors can also provide additional information from the time-dependent changes of cellular biochemistry. Since no cell labelling or staining is required, the specific time dependent biochemical changes in the living cells can be used for the identification and quantification of the toxic agents. Thus, detection of biochemical changes of cells by Raman spectroscopy could overcome the limitations of other biosensor techniques, with respect to detection and discrimination of a large range of toxic agents. Further developments of this technique may also include integration of cellular microarrays for high throughput in vitro toxicological testing of pharmaceuticals and in situ monitoring of the growth of engineered tissues.

Extracted Key Phrases

9 Figures and Tables

02040201020112012201320142015201620172018
Citations per Year

118 Citations

Semantic Scholar estimates that this publication has 118 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{Notingher2007RamanSC, title={Raman Spectroscopy Cell-based Biosensors}, author={Ioan Notingher}, year={2007} }