SERS biosensing of sickle cell hemoglobin from normal hemoglobin

Abstract

Hemoglobinopathies are the most common genetic disorders caused by a mutation in the genes encoding for one of the globin chains and leading to structural (hemoglobin [Hb] variants) or quantitative defects (thalassemias) in hemoglobin. Early diagnosis and characterization of hemoglobinopathies are essential to avoid severe hematological consequences in the offspring of healthy carriers of a mutation. Despite being extensively studied, hemoglobinopathies continue to provide a diagnostic challenge. Sickle-cell hemoglobin (HbS) is the most common and clinically significant hemoglobin variant among all Hb variants. To overcome the challenge of diagnosing Hb variants, we propose the use of Surface-Enhanced Raman Spectroscopy (SERS). SERS is a powerful label-free tool for providing fingerprint structural information of analyses. It can rapidly generate the spectral signature of samples. This study investigates the structural differences between HbS and normal Hb using gold nanopillar SERS substrates with a leaning effect. The SERS spectra of Hb variants showed subtle spectral differences between HbS and normal Hb located in the valine (975 cm-1) and glutamic acid (1547 cm-1) band, reflecting the amino acid substitution in the HbS β-globin chain. We also automated the identification of HbS and normal Hb with principal component analysis (PCA) combined with support vector machine (SVM) and linear discriminant analysis (LDA) classifiers, leading to an accuracy of 98% and 96%, respectively. This study demonstrated that SERS can provide a fast, highly sensitive, noninvasive, and accurate detection module for the diagnosis of Sickle-cell disease and potentially other hemoglobinopathies.