ArticleScientific reports2019
A method of predicting the in vitro fibril formation propensity of Aβ40 mutants based on their inclusion body levels in E. coli.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Aβ-42 Side Chain Deamidation at Q15 or N27 Modulates Protein Aggregation and Alters Microglial Cytokines and CD68.ACS chemical neuroscience · 2026Article
- Asparagine Deamidation Attenuates Toxicity, Aggregation, and Microglial Responses of Alzheimer's Amyloid-β.ACS chemical neuroscience · 2025Article
- Fundamental insights in early-stage inclusion body formation.Microbial biotechnology · 2023Article
- Role of Hydrophobicity at the N-Terminal Region of Aβ42 in Secondary Nucleation.ACS chemical neuroscience · 2022Article
- High intracellular stability of the spidroin N-terminal domain in spite of abundant amyloidogenic segments revealed by in-cell hydrogen/deuterium exchange mass spectrometry.The FEBS journal · 2020Article
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Authors and funding
11 authors at 3 institutions in 3 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Overexpression of recombinant proteins in bacteria may lead to their aggregation and deposition in inclusion bodies. Since the conformational properties of proteins in inclusion bodies exhibit many of the characteristics typical of amyloid fibrils. Based on these findings, we hypothesize that the rate at which proteins form amyloid fibrils may be predicted from their propensity to form inclusion bodies. To establish a method based on this concept, we first measured by SDS-PAGE and confocal microscopy the level of inclusion bodies in E. coli cells overexpressing the 40-residue amyloid-beta peptide, Aβ40, wild-type and 24 charge mutants. We then compared these results with a number of existing computational aggregation propensity predictors as well as the rates of aggregation measured in vitro for selected mutants. Our results show a strong correlation between the level of inclusion body formation and aggregation propensity, thus demonstrating the power of this approach and its value in identifying factors modulating aggregation kinetics.
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