The Aggregated State of Amyloid-β Peptide In Vitro Depends on Cu2+ Ion Concentration

Evaluation of Copper(II) Transfer between Amyloid-beta Peptides by Relaxation-Induced Dipolar Modulation Enhancement (RIDME)

In the brains of Alzheimer's disease patients, fibrillar aggregates containing amyloid-beta (Aβ) peptides are found, along with elevated concentrations of Cu(II) ions. The aggregation pathways of Aβ peptides can be modulated by Cu(II) ions and is determined by the formation and nature of the Cu(II)-Aβ complex. If spin-labeled, the Cu(II)-Aβ complex contains two dipolar coupled paramagnetic centers, the spin label and the Cu(II) ion. Measurement of the dipolar coupling between these paramagnetic centers by relaxation-induced dipolar modulation enhancement (RIDME) allows to monitor the complex formation and thus opens a way to follow the Cu(II) transfer between peptides if a mixture of wild-type and spin-labeled ones is used. We evaluate this approach for a specific Cu(II)-Aβ complex, the aggregation-inert Component II. The kinetics of the Cu(II) transfer can be resolved by performing RIDME in a time-dependent manner. A temporal resolution of seconds has been achieved, with the potential to reach milliseconds, using a rapid-freeze quench device to stop the Cu(II) transfer in solution after defined incubation times.

Metal ion mediated aggregation of Alzheimer's disease peptides and proteins in solutions and at surfaces

Although the pathogenesis of Alzheimer's disease (AD) is still unclear, abnormally high concentrations of metal ions, like copper, iron and zinc, were found in senile plaques of AD brain, which inspires extensive studies on the fundamental molecular interactions of metal ions with the pathogenic hallmarks, amyloid-β (Aβ) peptides and tau proteins, respectively forming senile plaques and neurofibrillary tangles (NFTs) in AD brains. Early works concern the concentration effect of the metal ions on Aβ and tau aggregation. Yet, it is obvious that the surrounding environment of the metal ions must also be considered, not just the metal ions as free accessible forms in the solution phase. The most important surrounding environment in vivo is a very large surface area from cell membranes and other macromolecular surfaces. These bio-interfaces make the kinetic pathways of metal ion mediated Aβ and tau aggregation radically different from those in the solution phase. To better understand the role of metal ions in AD peptide and protein aggregation, we summarize and discuss the recent achievements in the research of metal ion mediated Aβ and tau aggregation, particularly the corresponding mechanism differences between the solution phase and the surface environment. The metal ion chelation therapy for AD is also discussed from the point of the surface pool of metal ions.

Hyperfine Decoupling of ESR Spectra Using Wavelet Transform

The objective of spectral analysis is to resolve and extract relevant features from experimental data in an optimal fashion. In continuous-wave (cw) electron spin resonance (ESR) spectroscopy, both g values of a paramagnetic center and hyperfine splitting (A) caused by its interaction with neighboring magnetic nuclei in a molecule provide important structural and electronic information. However, in the presence of g- and/or A-anisotropy and/or large number of resonance lines, spectral analysis becomes highly challenging. Either high-resolution experimental techniques are employed to resolve the spectra in those cases or a range of suitable ESR frequencies are used in combination with simulations to identify the corresponding g and A values. In this work, we present a wavelet transform technique in resolving both simulated and experimental cw-ESR spectra by separating the hyperfine and super-hyperfine components. We exploit the multiresolution property of wavelet transforms that allow the separation of distinct features of a spectrum based on simultaneous analysis of spectrum and its varying frequency. We retain the wavelet components that stored the hyperfine and/or super-hyperfine features, while eliminating the wavelet components representing the remaining spectrum. We tested the method on simulated cases of metal–ligand adducts at L-, S-, and X-band frequencies, and showed that extracted g values, hyperfine and super-hyperfine coupling constants from simulated spectra, were in excellent agreement with the values of those parameters used in the simulations. For the experimental case of a copper(II) complex with distorted octahedral geometry, the method was able to extract g and hyperfine coupling constant values, and revealed features that were buried in the overlapped spectra.