A research group including Associate Professor Hideyuki Mitomo at the Research Institute for Electronic Science, Hokkaido University, and Doctoral Student Md Abdul Kaiyum at the Graduate School of Life Science at the same university, developed a new analytical substrate "c-AuTAG" capable of acquiring information reflecting 3D structures of proteins with high sensitivity from trace samples. The findings were published in ACS Sensors.
(b) Schematic illustration of the chiral analytical platform (c-AuTAG), fabricated by transferring a self-assembled monolayer of peptide-functionalized triangular gold nanoplate arrays onto a hydrogel, and protein loading using the Gel Filter Trapping (GFT) method.
(c) Schematic illustration of Raman measurements and differential spectral analysis for obtaining molecular structural information reflecting the three-dimensional structures of proteins.
Provided by Professor Hideyuki Mitomo, Hokkaido University
State changes such as 3D structures and sugar modifications of proteins are deeply related to various diseases starting with Alzheimer's disease and diabetes. There is a call for analytical technologies capable of evaluating them easily and with high sensitivity. Conventionally, as a method for obtaining information reflecting 3D structures of proteins, Raman optical activity (ROA) using left-handed and right-handed circularly polarized light has been known. Because ROA requires a dedicated polarization optical system and signals are also extremely weak, high-concentration samples or long-time measurements were necessary.
The research group had previously developed AuTAG, an analytical substrate combining gels and plasmonic nanostructures, and the GFT (Gel-Filled Trapping) method, a sample introduction method guiding proteins to hotspots utilizing swelling and shrinking of gels. In the GFT method, through efficiently guiding proteins to hotspots where Raman signals are strongly enhanced, strong SERS signals can be obtained from trace samples.
This time, developing this analytical substrate AuTAG further, they developed an analytical substrate c-AuTAG in which triangular gold nanoparticles modified with L-form and D-form peptides are regularly arranged. In c-AuTAG, because chiral near-fields (optical environments reflecting chirality) are formed inside hotspots, Raman responses reflecting 3D structures of proteins can be detected with high sensitivity. Furthermore, by measuring the same sample with L-form and D-form substrates and comparing the respective Raman spectra using an ROA-like approach, they realized a new analytical method capable of acquiring protein chirality information such as that obtained in conventional ROA from trace samples in a short time.
Using this method, when measuring hemoglobin (Hb) and concanavalin A (ConA), characteristic SERS spectra were obtained, showing that molecular structure information can be acquired with high sensitivity from trace proteins. Furthermore, by analyzing differences in spectra obtained with L-form substrates and D-form substrates, characteristic ROA-like signals were obtained respectively, and responses reflecting differences in 3D structures of proteins were observed.
On the other hand, as a result of analyzing glycated hemoglobin (HbA1c), which is an important diagnostic indicator for diabetes, they clarified that in addition to structural information derived from proteins, differences derived from sugar modifications can also be detected with high sensitivity. In blood, Hb and HbA1c coexist, and their proportion is utilized for diagnosis and management of diabetes. This time, while confirming that sugar modification signals derived from HbA1c change according to proportions of HbA1c, they showed the possibility that proportions of HbA1c can be evaluated quantitatively using the signals.
The developed analytical method is expected to be applied to protein research and quality evaluation of biopharmaceuticals as a new measurement technology capable of rapidly evaluating state changes of proteins from small-amount samples. In addition, possibilities exist to detect state changes of proteins related to diseases such as sugar modifications and aggregation with high sensitivity. In the future, development into analysis of biomarkers related to neurodegenerative diseases such as Alzheimer's disease and diabetes, and into new analytical technologies supporting health checkups and early diagnosis, is expected.
Journal Information
Publication: ACS Sensors
Title: Peptide-Induced Chiral Plasmonic Hotspots for Ultrasensitive Chirality-Dependent Raman Analysis of Proteins
https://pubs.acs.org/ascefj/article/doi/10.1021/acssensors.6c03237/5259475/Peptide-Induced-Chiral-Plasmonic-Hotspots-for
This article has been translated by JST with permission from The Science News Ltd. (https://sci-news.co.jp/). Unauthorized reproduction of the article and photographs is prohibited.