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PCR-free quantification of multiple splice variants in a cancer gene by surface-enhanced Raman spectroscopy.

ABSTRACT: We demonstrate a surface-enhanced Raman spectroscopy (SERS) based array platform to monitor gene expression in cancer cells in a multiplex and quantitative format without amplification steps. A strategy comprising DNA/RNA hybridization, S1 nuclease digestion, and alkaline hydrolysis was adopted to obtain DNA targets specific to two splice junction variants, Delta(9,10) and Delta(5), of the breast cancer susceptibility gene 1 from MCF-7 and MDA-MB-231 breast cancer cell lines. These two targets were identified simultaneously, and their absolute quantities were estimated by a SERS strategy utilizing the inherent plasmon-phonon Raman mode of gold nanoparticle probes as a self-referencing standard to correct for the variability in surface enhancement. The results were then validated by reverse-transcription polymerase chain reaction. Our proposed methodology could be expanded to a higher level of multiplexing for quantitative gene expression analysis of any gene without any amplification steps.

SUBMITTER: Sun L

PROVIDER: S-EPMC2765795 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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PCR-free quantification of multiple splice variants in a cancer gene by surface-enhanced Raman spectroscopy.

Sun Lan L Irudayaraj Joseph J

The journal of physical chemistry. B 20091001 42

We demonstrate a surface-enhanced Raman spectroscopy (SERS) based array platform to monitor gene expression in cancer cells in a multiplex and quantitative format without amplification steps. A strategy comprising DNA/RNA hybridization, S1 nuclease digestion, and alkaline hydrolysis was adopted to obtain DNA targets specific to two splice junction variants, Delta(9,10) and Delta(5), of the breast cancer susceptibility gene 1 from MCF-7 and MDA-MB-231 breast cancer cell lines. These two targets w ...[more]

PMID: 19780515

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Project description:Metabolomics is an emerging field of cell biology that aims at the comprehensive identification of metabolite levels in biological fluids or cells in a specific functional state. Currently, the major tools for determining metabolite concentrations are mass spectrometry coupled with chromatographic techniques and nuclear magnetic resonance, which are expensive, time consuming and destructive for the samples. Here, we report a time resolved approach to monitor metabolite dynamics in cell cultures, based on Surface Enhanced Raman Scattering (SERS). This method is label-free, easy to use and provides the opportunity to simultaneously study a broad range of molecules, without the need to process the biological samples. As proof of concept, NIH/3T3 cells were cultured in vitro, and the extracellular medium was collected at different time points to be analyzed with our engineered SERS substrates. By identifying individual peaks of the Raman spectra, we showed the simultaneous detection of several components of the conditioned medium, such as L-tyrosine, L-tryptophan, glycine, L-phenylalanine, L-histidine and fetal bovine serum proteins, as well as their intensity changes during time. Furthermore, analyzing the whole Raman data set with the Principal Component Analysis (PCA), we demonstrated that the Raman spectra collected at different days of culture and clustered by similarity, described a well-defined trajectory in the principal component plot. This approach was then utilized to determine indirectly the functional state of the macrophage cell line Raw 264.7, stimulated with the lipopolysaccharide (LPS) for 24 hours. The collected spectra at different time points, clustered by the PCA analysis, followed a well-defined trajectory, corresponding to the functional change of cells toward the activated pro-inflammatory state induced by the LPS. This study suggests that our engineered SERS surfaces can be used as a versatile tool both for the characterization of cell culture conditions and the functional state of cells over time.

Dataset Information

PCR-free quantification of multiple splice variants in a cancer gene by surface-enhanced Raman spectroscopy.

Publications

PCR-free quantification of multiple splice variants in a cancer gene by surface-enhanced Raman spectroscopy.

Similar Datasets

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