Binding of tyrosine kinase inhibitor to epidermal growth factor receptor: surface-enhanced infrared absorption microscopy reveals subtle protein secondary structure variations.

Surface-Enhanced Infrared Absorption (SEIRA) has been proposed as a valuable tool for protein binding studies, but its performances have been often proven on model proteins undergoing severe secondary structure rearrangements, while ligand binding only marginally involves the protein backbone in the vast majority of the biologically relevant cases. In this study we demonstrate the potential of SEIRA microscopy for highlighting the very subtle secondary structure modifications associated with the binding of Lapatinib, a tyrosine kinase inhibitor (TKI), to epidermal growth factor receptor (EGFR), a well-known driver of tumorigenesis in pathological settings such as lung, breast and brain cancers. By boosting the performances of Mid-IR plasmonic devices based on nanoantennas cross-geometry, accustoming the protein purification protocols, carefully tuning the protein anchoring methodology and optimizing the data analysis, we were able to detect EGFR secondary structure modification associated with few amino acids. A nano-patterned platform with this kind of sensitivity bridges biophysical and structural characterization methods, thus opening new possibilities in studying of proteins of biomedical interest, particularly for drug-screening purposes.

Investigation of genomic DNA methylation by ultraviolet resonant Raman spectroscopy.

Cytosine plays a preeminent role in DNA methylation, an epigenetic mechanism that regulates gene expression, the misregulation of which can lead to severe diseases. Several methods are nowadays employed for assessing the global DNA methylation levels, but none of them combines simplicity, high sensitivity, and low operating costs to be translated into clinical applications. Ultraviolet (UV) resonant Raman measurements at excitation wavelengths of 272 nm, 260 nm, 250 nm, and 228 nm have been carried out on isolated deoxynucleoside triphosphates (dNTPs), on a dNTP mixture as well as on genomic DNA (gDNA) samples, commercial from salmon sperm and non-commercial from B16 murine melanoma cell line. The 228 nm excitation wavelength was identified as the most suitable energy for enhancing cytosine signals over the other DNA bases. The UV Raman measurements performed at this excitation wavelength on hyper-methylated and hypo-methylated DNA from Jurkat leukemic T-cell line have revealed significant spectral differences with respect to gDNA isolated from salmon sperm and mouse melanoma B16 cells. This demonstrates how the proper choice of the excitation wavelength, combined with optimized extraction protocols, makes UV Raman spectroscopy a suitable technique for highlighting the chemical modifications undergone by cytosine nucleotides in gDNA upon hyper- and hypo-methylation events.

Contribution of Ribonucleic Acid (RNA) to the Fourier Transform Infrared (FTIR) Spectrum of Eukaryotic Cells.

We report on an optimized protocol for the digestion of cellular RNA, which minimally affects the cell membrane integrity, maintaining substantially unaltered the vibrational contributions of the other cellular macromolecules. The design of this protocol allowed us to collect the first Fourier transform infrared (FTIR) spectra of intact hydrated B16 mouse melanoma cells deprived of RNA and to highlight the in-cell diagnostic spectral features of it. Complementing the cellular results with the FTIR analysis of extracted RNA, ds-DNA, ss-cDNA and isolated nuclei, we verified that the spectral component centered at ∼1220 cm-1 is a good qualitative and semiquantitative marker of cellular DNA, since it is minimally affected by cellular RNA removal. Conversely, the band centered at ∼1240 cm-1, conventionally attributed to RNA, is only a qualitative marker of it, since its intensity is majorly influenced by other macromolecules containing diverse phosphate groups, such as phospholipids and phosphorylated proteins. On the other hand, we proved that the spectral contribution centered at ∼1120 cm-1 is the most reliable indicator of variations in cellular RNA levels, that better correlates with cellular metabolic activity. The achievement of these results have been made possible also by the implementation of new methods for baseline correction and automated peak fitting, presented in this paper.