Understanding the molecular structures of amyloid-β (Aβ) oligomers and underlying assembly pathways will advance our understanding of Alzheimer’s disease (AD) at the molecular level. This understanding could contribute to disease prevention, diagnosis, and treatment strategies, as oligomers play a central role in AD pathology. We have recently presented a procedure for production of 150 kDa oligomeric samples of Aβ(1–42) (the 42-residue variant of the Aβ peptide) that are compatible with solid state NMR analysis, and we have shown that these oligomers and amyloid fibrils differ in intermolecular arrangement of β-strands. Here we report new solid state NMR constraints that indicate antiparallel intermolecular alignment of β-strands within the oligomers. Specifically, 150 kDa Aβ(1–42) oligomers with uniform 13C and 15N isotopic labels at I32, M35, G37 and V40 exhibit β-strand secondary chemical shifts in 2D fpRFDR NMR spectra, spatial proximities between I32 and V40 as well as between M35 and G37 in 2D DARR spectra, and close proximity between M35 Hα and G37 Hα in 2D CHHC spectra. Furthermore, 2D DARR analysis of an oligomer sample prepared with 30% labeled peptide indicates that the I32-V40 and M35-G37 contacts are between residues on different molecules. We employ molecular modeling to compare the newly derived experimental constraints with previously proposed geometries for arrangement of Aβ molecules into oligomers.
Endogenous amyloid-β (Aβ) oligomeric aggregates have been proposed as toxic agents in Alzheimer's disease (AD). Knowledge of their structures not only may provide insight into the basis of their neurotoxicities but also may reveal new targets for therapeutic drugs and diagnostic tools. However, the low levels of these Aβ oligomers have impeded structural characterization. Evidence suggests that the endogenous oligomers are covalently modified in vivo. In this report, we demonstrate an established mass spectrometry (MS) methodology called precursor ion mapping (PIM) that potentially may be applied to endogenous oligomer characterization. First, we illustrate the use of this PIM technique with a synthetic Aβ(1-40) monomer sample that had been cross-linked with transglutaminase (TGase) and digested with pepsin. From PIM analysis of an Aβ(4-13) MS/MS fragment, precursor ions were identified that corresponded to peptic fragments of three TGase cross-linked species: Aβ(4-19)--(4-19), Aβ(4-19)--(20-34), and Aβ(1-19)--(20-34). Next, we demonstrate the applicability of the PIM technique to an endogenous Aβ sample that had been purified and concentrated by immunoaffinity chromatography. Without pepsin digestion, we successfully identified the full length and C-terminally truncated monomeric Aβ species 1-35 to 1-42, along with select methionine-oxidized counterparts. Because PIM focuses only on a subpopulation of ions, namely the related precursor ions, the resulting spectra are of increased specificity and sensitivity. Therefore, this methodology shows great promise for structural analysis and identification of post-translational modification(s) in endogenous Aβ oligomers.
On simple intelligibility measures, high-quality synthesiser output now scores almost as well as natural speech. Nevertheless, it is widely agreed that perception of synthetic speech is a harder task for listeners than perception of natural speech; in particular, it has been hypothesized that listeners have difficulty identifying phonemes in synthetic speech. If so, a simple measure of the speed with which a phoneme can be identified should prove a useful tool for comparing perception of synthetic and natural speech. The phoneme detection task was here used in three experiments comparing perception of natural and synthetic speech. In the first, response times to synthetic and natural targets were not significantly different, but in the second and third experiments response times to synthetic targets were significantly slower than to natural targets. A speed-accuracy tradeoff in the third experiment suggests that an important factor in this task is the response criterion adopted by subjects. It is concluded that the phoneme detection task is a useful tool for investigating phonetic processing of synthetic speech input, but subjects must be encouraged to adopt a response criterion which emphasizes rapid responding. When this is the case, significantly longer response times for synthetic targets can indicate a processing disadvantage for synthetic speech at an early level of phonetic analysis
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