The focus of my research is to obtain the critical confirmation information of amyloid beta 1-40 when it's absorbed over the gold nanoparticle surface and taking place reversible aggregation process. The challenge we are facing in this research field is to obtain thermal, chemical, and dynamical information of the reverse aggregation process. The great finding of this project is that we are able to identify the particular motion or vibration mode contributing to folded or unfolded confirmation of amyloid beta 1-40 when they are absorbed over the gold nanoparticle surface.
The great advantage of using SERS, surface-enhanced Raman scattering spectroscopy, is to detect very small, weak scattering signals to identify the mode which is critical to cause folding and unfolding. At the same time, we are able to pinpoint the morphology of the aggregates. The findings that we are able to produce from this project is the key interaction of protein-protein interaction, which will be important for causing the oligomer and which will be leading to the fibrogenesis.
To begin, using a micropipette, add one milliliter of distilled deionized water to one milligram of lyophilized amyloid beta, or A beta 1-40. Mix the solution with a vortex mixer for approximately 30 seconds. Ensure no solid particles remain in the solution at room temperature, approximately 20 degrees Celsius.
Next, prepare peptide stock solutions using deionized and distilled water. Determine the peptide concentration by spectroscopically measuring tyrosine absorption at 275 nanometers. Store the A beta 1-40 stock solutions at minus 80 degrees Celsius.
Thaw the peptide stock solution approximately five minutes before data collection. In a 15 milliliter centrifuge tube, mix eight microliters of the peptide solution with 800 microliters of gold colloidal particles. Add 4.2 milliliters of deionized distilled water, then vortex the sample for 10 seconds.
Fix the concentration of A beta 1-40 peptides at 1.8 nanomolar, and adjust the ratio of peptides to gold colloidal particles within the specific range. Using the temperature control unit of the UV visible spectrophotometer, set the solution at room temperature, approximately 22 degrees Celsius. Monitor the initial pH of the sample solution using a pH meter and adjust it to slightly below pH seven.
Collect the absorption spectrum within the range of 400 to 800 nanometers. Then, adjust the pH of the sample to approximately pH four by adding 1.0 microliter increments of 1.0 molar hydrochloric acid. Collect the absorption spectrum across the same range of 400 to 800 nanometers.
Next, adjust the pH of the sample to approximately pH 10 by adding approximately 1.5 microliter increments of 1.0 molar sodium hydroxide. Collect the absorption spectrum within the same wavelength range of 400 to 800 nanometers. After that, change the pH between pH four and pH 10 10 times by adding either hydrochloric acid or sodium hydroxide.
Continuously collect the absorption spectrum at 25 degrees Celsius. Obtain the ASCII dataset of wavelengths as a function of absorbance. Use the PeakFit program to extract the average positions of the band peaks.
Using the plot function, plot the dataset to visualize the optical density as a function of wavelength. Identify and mark the initial peak wavelengths, lambda one and lambda two, by selecting their approximate positions in the plotted data. Fit the data using the peak fit function of the origin program.
Obtain the graph displaying the central peak positions for each lambda labeled as XCI, along with the corresponding band areas, denoted as AI.Export the extracted peak positions and corresponding areas to a spreadsheet program for analysis. Calculate the weighting factor, AI, for each peak center by comparing the area of the band to the total area of the entire bands using the displayed formula. Then, extract the average peak position using the equation displayed on the screen.
To generate a reversibility plot, tabulate the average peak positions as a function of the operation number N.Assign operation number N as mentioned on the screen. Analyze the peak position at N using the displayed formula. Transfer the calculated dataset into the origin software and plot it.
Select non-linear curve fitting of analysis, input the initial values for A, B, C, D, and E, and click run to complete the curve fitting process. To perform Raman imaging, for each sample at operation number N, place 100 microliters of solution on a mica disc having a diameter of one centimeter. Allow the samples to dry overnight before measurement.
Next, collect white light images for each operation number N.Prepare the separate sample on a new mica disc as pH is continuously altered between four and 10. Collect the Raman image for each operation number, and using the mentioned specifications of a laser with a wavelength of 633 nanometers. Capture images in a 100 by 100 pixel grid with a specific integration time, focusing on the desired spectral region.
Plot the representative spectrum for each operation number N aligned as a function of N.Construct a three-dimensional surface-enhanced Raman spectroscopy, or SERS spectrum, as a function of N for A beta 1-40-coated 20 nanometer gold. Utilize the top view of the spectrum as a contour map to extract the specific modes associated with a particular pH condition. Identify spectral features enhanced exclusively at only even or odd operation numbers.
The SPR band of A beta 1-40-coated gold nanoparticles shifted from 530 nanometers to about 650 nanometers when the solution was made more acidic. This corresponded to the formation of gold colloid aggregates with unfolded A beta 1-40 monomers as observed by TEM. The pH-dependent color change of A beta 1-40-coated gold was also evident.
The reversible pH-dependent shift of the average band peaked between a shorter and longer wavelength, and the alternate dispersed and aggregate morphology observed in TEM confirmed the quasi-reversible nature of the process. White light imaging showed a clear, reversible aggregation pattern corresponding to the pH shifts, while the SERS spectra displayed subtle pH-dependent changes in the fingerprint region.
