Full text
2,023 characters
· extracted from
oa-doi-fallback
· click to expand
Abstract
The accumulation of amyloid-beta (Aβ) plaques is a hallmark of Alzheimer’s disease (AD), with Aβ42 representing the predominant and most aggregation-prone isoform. Reliable preparation of monomeric Aβ42 is essential for investigating the kinetics and mechanisms of its aggregation into oligomers and fibrils. This study provides a direct comparison of two monomerization protocols for recombinantly expressed Aβ42: one incorporating size-exclusion chromatography (SEC) and the other relying solely on chemical denaturation, using agents such as NaOH and NH4OH. Aβ42 was produced in E. coli, purified through urea solubilization followed by HPLC, and subjected to monomerization via the respective methods. Monomeric preparations were evaluated using Thioflavin T (ThT) fluorescence to assess aggregation kinetics, TEM to detect fibrils and preformed aggregates, and NMR spectroscopy. SEC-isolated monomers displayed sigmoidal aggregation profiles in ThT assays, featuring distinct lag, growth, and plateau phases consistent with secondary nucleation-dominated models as determined by AmyloFit analysis. Increasing the initial peptide concentration resulted in higher fibril yields, which was further supported by TEM images showing extensive fibrillization following incubation. In contrast, non-SEC preparations containing pre-existing aggregates detectable by TEM and showed attenuated NMR signals, leading to impaired aggregation behavior. NaOH-denatured samples predominantly exhibited flat ThT curves, whereas NH4OH-denatured samples displayed extended lag phases. NH4OH performance better than NaOH, likely because its gradual pH neutralization reduced peptide structural perturbation. Overall, these findings demonstrate that SEC is critical for obtaining highly pure monomeric Aβ42 and improving the reproducibility of aggregation assays, highlighting the importance of standardized monomer preparation protocols in AD research.
Competing Interest Statement
The authors have declared no competing interest.
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.