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Predicting amyloid aggregation rates of proteins using multivariate analysis
Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics. (Göran Larsson)
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Several diseases have been linked to the presence of extracellular protein deposits of β-rich aggregates, known as amyloid fibrils. The formation of these fibrils and their precursors has been identified as key players in the development of these diseases. It is therefore desirable to gain a deeper understanding of the mechanism of amyloid aggregation.In this study we have used multivariate analysis to elucidate the most important physicochemical and structural factors of amino acids that are important for the amyloid aggregation. We used a combination of principal component analysis, orthogonal partial least squares and auto- and cross-covariance to investigate a database consisting of amyloid aggregation rate measurements of 77 AcP mutants.Our results show that changes in hydrophobic patterns, charge and β-sheet propensity is common for mutants with the largest changes in amyloid propensity. In addition, we can also, with reasonable accuracy, predict the amyloid aggregation rate of a test set of AcP mutants that were not used to create the initial aggregation model. Thus, the multivariate approach used in this study is shown to be powerful tools to extract important factors of protein amyloid aggregation that are hidden in the growing pool of available experimental data of amyloid aggregation.

Keyword [en]
Multivariate analyis, amyloid aggregation, OPLS, AcP
URN: urn:nbn:se:umu:diva-46591OAI: diva2:439273
Available from: 2011-09-09 Created: 2011-09-07 Last updated: 2013-04-30Bibliographically approved
In thesis
1. Size determination of hyaluronan and multivariate analysis of amyloid prone proteins
Open this publication in new window or tab >>Size determination of hyaluronan and multivariate analysis of amyloid prone proteins
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Storleksbestämning av hyaluronan och multivariat analys av amyloid benägna proteiner
Abstract [en]

Background.The extracellular matrix surrounds all cells within our bodies. The glycosaminoglycan hyaluronan is a major component in the extracellular matrix. Despite its structural simplicity it has been shown to be involved in several important functions. It is a lubricant and shock absorber, as well as an important player in inflammation and tumor invasion. Many of its functions are closely related to its size and concentration in tissues. Therefore methods for measuring these properties are of great importance to properly understand the role that hyaluronan play in different events. Proteins are found both inside and outside cells, and they have a wide variety of functions. The protein structure and function is determined by the properties of their building blocks, the amino acids. Several diseases have been linked to changes in the amino acid sequence of certain proteins by mutations, causing the proteins to form extracellular deposits of structures called amyloid aggregates. The aim of this thesis is to investigate the function of hyaluronan in cell cultures, develop new methods for size determination hyaluronan and to use multivariate methods to provide prediction and better understanding of factors driving protein amyloid aggregation.

Methods.Cardiomyocytes and fibroblast were cultured and stimulated by different growth factors. Hyaluronan was purified and its size and concentration were measured. Crosstalk between cardiomyocytes and fibroblast were investigated and gene expression of hyaluronan synthases was determined. A new method for size measurement of hyaluronan was developed. The amyloid aggregation rate of different mutants of acylphosphatase was predicted by multivariate analysis.

Results. Cardiomyocytes stimulated by PDGF-BB produced hyaluronan. Cardiomyocytes could induce fibroblast to increase its hyaluronan production, through an unknown soluble factor. The cardiomyocyte gene expression changed when stimulated by hyaluronan. GEMMA was presented as a new method for size determination of hyaluronan. Amyloid aggregation of different acylphosphatase mutants could be predicted using a multivariate regression model of the physicochemical and structural properties of the amino acid sequence.

Conclusion. It was shown that cardiomyocytes are not only able to produce hyaluronan, but also induce an increased hyaluronan production in other cells. GEMMA was proven suitable for size determination of hyaluronan at very low concentrations. Multivariate analysis showed that hydrophobic patterns and charge where the most important factors for amyloid aggregation of acylphosphatase.

Place, publisher, year, edition, pages
Umeå: Umeå university, 2011. 40 p.
Umeå University medical dissertations, ISSN 0346-6612 ; 1441
Hyaluronan, Dynamic Light Scattering, GEMMA, Amyloid Aggregation, Multivariate Analysis
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Medical Biochemistry; Physical Chemistry
urn:nbn:se:umu:diva-46601 (URN)978-91-7459-273-3 (ISBN)
Public defence
2011-09-30, KB3B1, KBC, Umeå Universitet, Umeå, 13:00 (English)
Available from: 2011-09-09 Created: 2011-09-07 Last updated: 2011-09-12Bibliographically approved

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Malm, LinusAntti, HenrikSjöström, MichaelLarsson, Göran
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