Non-destructive molecular FTIR spectromicroscopy for real time assessment of redox metallodrugs

Recognition of breast cancer subtypes using FTIR hyperspectral data

Fourier-transform infrared spectroscopy (FTIR) is a powerful, non-destructive, highly sensitive and a promising analytical technique to provide spectrochemical signatures of biological samples, where markers like carbohydrates, proteins, and phosphate groups of DNA can be recognized in biological micro-environment. However, method of measurements of large cells need an excessive time to achieve high quality images, making its clinical use difficult due to speed of data-acquisition and lack of optimized computational procedures. To address such challenges, Machine Learning (ML) based technologies can assist to assess an accurate prognostication of breast cancer (BC) subtypes with high performance. Here, we applied FTIR spectroscopy to identify breast cancer subtypes in order to differentiate between luminal (BT474) and non-luminal (SKBR3) molecular subtypes. For this reason, we tested multivariate classification technique to extract feature information employing three-dimension (3D)-discriminant analysis approach based on 3D-principle component analysis-linear discriminant analysis (3D-PCA-LDA) and 3D-principal component analysis-quadratic discriminant analysis (3D-PCA-QDA), showing an improvement in sensitivity (98%), specificity (94%) and accuracy (98%) parameters compared to conventional unfolded methods. Our results evidence that 3D-PCA-LDA and 3D-PCA-QDA are potential tools for discriminant analysis of hyperspectral dataset to obtain superior classification assessment.

Exploring Enzymatic Conformational Dynamics at Surfaces through μ-FTIR Spectromicroscopy

Immobilization of proteins onto solid supports has critical industrial, technological, and medical applications, and is a daily task in chemical research. Significant conformational rearrangements often occur due to enzyme-surface interactions, and it is of broad interest to develop methods to probe and better understand these molecular-level changes that contribute to the enzyme's catalytic activity and stability. While circular dichroism is a common method for solution-phase conformational study, the application to surface-supported proteins is not trivial and spatial mapping is not viable. On the other hand, a nonlinear laser spectroscopy technique used to analyze surfaces and interfaces is not often found in most laboratories, therefore requiring an alternative and reliable method. Here, we employed high-dimensional data spectromicroscopy analysis in the infrared region (μ-FTIR) to investigate the enzyme's conformational change when adsorbed onto solid matrices, across a ca. 20 mm2 area. Alcohol dehydrogenase (ADH) enzyme was adopted as a model enzyme to interact with CaF2, Au, and Au-thiol model substrates, strategically chosen for mapping the enzyme dynamics on solid surfaces with different polarity/hydrophobicity properties and extendable to other materials. Two-dimensional chemical maps indicate that the enzyme adsorbs with different patterns in which secondary structures dynamically adjust to optimize interprotein and enzyme-surface interactions. The results suggest an experimental approach to identify and map enzyme conformational dynamics onto different solid surfaces across space and provide insights into immobilized protein structure investigations for areas such as biosensing and bioenergy.

Dual detection high-speed capillary electrophoresis for simultaneous serum protein analysis and immunoassays

Serum protein electrophoresis (SPE) separates serum proteins into bands whose shape and amplitude can alert clinicians to a range of disorders. This is followed by more specific immunoassays to quantify important antigens and confirm a diagnosis. Here we develop a high-speed capillary electrophoresis (HSCE) platform capable of simultaneous SPE and immunoassay measurements. A single laser excitation source is focused into the detection zone of the capillary to measure both refractive index (SPE) and fluorescence signals (immunoassays). The refractive index signal measures characteristic SPE profiles for human serum separated in 100 mM boric acid (pH 10), 100 mM arginine (pH 11), and 20 mM CHES (pH 10). For the immunoassay, the fluorescence electropherograms reveal that CHES provides the optimal buffer for measuring the immunocomplex and separating it from the free antigen. Immunoassays in CHES yield a LOD of 23 nM and a LOQ of 70 nM for the detection of fluorescein. The high pH reduces protein adsorption but reduces antibody affinity. Preliminary studies carried out in 50 mM barbital at pH 8 show improved stability of the immunocomplex and better separation for immunoassay quantification. Further optimization will open new capabilities for measuring orthogonal diagnostic signals in seconds with HSCE.