Characterization of microRNA-125b expression in MCF7 breast cancer cells by ATR-FTIR spectroscopy

MicroRNAs (miRNAs), are similar to 22 nucleotides long, non-coding RNAs that control gene expression post-transcriptionally by binding to their target mRNA's 3'UTRs (untranslated regions). Due to their roles in various important regulatory processes and pathways, miRNAs have been implicated in disease mechanisms such as tumorigenesis when their expression is deregulated. To date, a significant number of miRNAs and their target messenger RNAs (mRNAs) have been identified and verified. It is generally accepted that miRNAs can potentially bind to many mRNAs, which brings the requirement of validation of these interactions. While understanding that such individual interactions is crucial to delineate the role of a specific miRNA, we took a holistic approach and analyzed global changes in the cell due to expression of a miRNA in a model cell line system. Our model consisted of MCF7 cells stably transfected with miR-125b (MCF7-125b) and empty vector (MCF7-EV). MiR-125b is one of the known down-regulated miRNAs in breast cancers. In this study we examined the global structural changes in MCF7 cells lacking and expressing miR-125b by Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy and investigated the dynamic changes by more sensitive spin-labelling Electron Spin Resonance (ESR) spectroscopy. Our results revealed less RNA, protein, lipid, and glycogen content in MCF7-125b compared to MCF7-EV cells. Membrane fluidity and proliferation rate were shown to be lower in MCF7-125b cells. Based on these changes, MCF7-125b and MCF7-EV cells were discriminated successfully by cluster analysis. Here, we provide a novel means to understand the global effects of miRNAs in cells. Potential applications of this approach are not only limited to research purposes. Such a strategy is also promising to pioneer the development of future diagnostic tools for deregulated miRNA expression in patient samples

Evaluation and discrimination of simvastatin-induced structural alterations in proteins of different rat tissues by FTIR spectroscopy and neural network analysis

Statins are commonly used to control hypercholesterolemia and to prevent cardiovascular diseases. Among the statins, Simvastatin is one of the most frequently prescribed statins because of its efficacy in reducing LDL lipoprotein cholesterol levels, its tolerability, and its reduction of cardiovascular risk and mortality. Conflicting results have been reported with regard to benefits (pleiotropic effects) as well as risks (adverse effects) of simvastatin on different soft and hard tissues. In the current study, Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy was used to obtain detailed information about protein conformational changes due to simvastatin therapy of soft tissues namely liver, testis, sciatic nerve and hard tissues such as femur and tibia. Protein secondary structural changes were predicted by intensity calculations from second derivative spectra and neural network (NN) analysis, using the amide I band (1700-1600 cm(-1)) of FTIR spectra. Moreover, based on protein secondary structural differences, hierarchial cluster analysis was carried out in the 1700-1600 cm(-1) region. The results of our study in liver, testis and sciatic nerve tissues revealed that simvastatin treatment significantly decreased alpha helix structure and beta sheet structure at 1638 cm(-1), while increased the anti-parallel and aggregated beta sheet and random coil structures implying a simvastatin-induced protein denaturation in treated groups. Different to soft tissues, the results of hard tissue studies on femur and tibia bones revealed increased alpha helix structure and decreased anti-parallel beta sheet, aggregated beta sheet and random coil structures implying more strengthened bone tissues in simvastatin-treated groups. Finally, the simvastatin-treated and control groups for all soft and bone tissues were successfully differentiated using cluster analysis. According to the heterogeneity values in the cluster analysis of these tissues, the sciatic nerve tissue was found to be the most affected tissue from simvastatin treatment among the studied soft tissues. In addition, the high heterogeneity value implied high secondary structural difference between control and simvastatin-treated groups in tibia bone tissues. These findings reveal that FTIR spectroscopy with bioinformatic analyses such as neural network and hierarchical clustering, allowed us to determine the simvastatin-induced protein conformational changes as adverse and pleitropic effects of the drug on different soft and hard tissues