Intermittent fasting-induced biomolecular modifications in rat tissues detected by ATR-FTIR spectroscopy and machine learning algorithms

Abstract

This study aimed to reveal the intermittent fasting-induced alterations in biomolecules of the liver, ileum, and colon tissues of rats using Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) algorithms developed on infrared spectrochemical data. LDA prediction accuracies were generally calculated in the range of 95-100%, while training and validation accuracies of SVM were in the range of 91-100% and 83-91%, respectively. The quantitative measurements of spectral bands at the CH (lipids), Amide (proteins), and PO₂ antisymmetric (nucleic acids) stretching regions were performed to monitor modulated metabolic processes. The concentration of biomolecules and phosphorylation rate of proteins were found higher in studied tissues. The altered conformations and low rates of carbonylation (oxidation) were also common in proteins. No significant change was recorded for the length of fatty acid acyl chains (A₂₉₂₂/A₂₉₅₅ band area ratio) in the liver, whereas the shortening of acyl chains was calculated as 23% and 27% in ileum and colon tissues, respectively. Enhanced membrane dynamics (Bw₂₉₂₂/Bw₂₉₅₅ bandwidth ratio) were depicted in the liver (35% increase), while a decline in dynamics was apparent in the ileum (36% decrease) and colon (31% decrease). The study revealed important alterations in major biomolecules of studied tissues.

Keywords: FTIR Spectroscopy; Intermittent fasting (IF); Machine learning; Metabolism; Rat.