The identification of cystic fibrosis (CF) cells and their pharmacological correction by mid-infrared microspectroscopy and unsupervised data analysis methods

We aimed at demonstrating that non-cystic fibrosis (CF) cells and isogenic, CF bronchial epithelial cell lines can be correctly classified by Fourier transform (FT) mid-infrared (IR) absorbance spectra and unsupervised methods for multivariate data analysis such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). CF cells were exposed “ex vivo” to VRT-325, a chemical corrector of defective anion transporter Cystic Fibrosis Transmembrane conductance Regulator (CFTR) caused by the F508del mutation. Unstained epithelial cells from CF patients and a healthy control were deposited on ZnSe window and analyzed with an IR interferometer connected to a FTIR microscope (microFTIR). In order to explain spectral variability reflecting biochemical differences between CF and non-CF cells, we applied PCA to dataset of untreated cells and cells treated for 24 hours with 1x10-5 M VRT-325. The information achieved with IR analysis was cross validated by the findings on CFTR expression and by the results of functional CFTR bioassays carried out in replicate samples. We conclude suggesting the possibility to utilize IR spectra analysis to recognize CF cells and the effect of pharmacological treatment aimed to correct the basic defect of CF