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Size determination of hyaluronan and multivariate analysis of amyloid prone proteins
Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics. (Göran Larsson)
2011 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Storleksbestämning av hyaluronan och multivariat analys av amyloid benägna proteiner (Swedish)
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.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1441
Keyword [en]
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
Identifiers
URN: urn:nbn:se:umu:diva-46601ISBN: 978-91-7459-273-3 (print)OAI: oai:DiVA.org:umu-46601DiVA: diva2:439314
Public defence
2011-09-30, KB3B1, KBC, Umeå Universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2011-09-09 Created: 2011-09-07 Last updated: 2011-09-12Bibliographically approved
List of papers
1. Growth factor PDGF-BB stimulates cultured cardiomyocytes to synthesize the extracellular matrix component hyaluronan
Open this publication in new window or tab >>Growth factor PDGF-BB stimulates cultured cardiomyocytes to synthesize the extracellular matrix component hyaluronan
Show others...
2010 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 5, no 12, e14393- p.Article in journal (Refereed) Published
Abstract [en]

Co-cultivation of cardiomyocytes and fibroblasts (80%/20%) increased HA concentration far more that can be explained by HA synthesis by the two cell types separately, revealing a crosstalk between cardiomyocytes and fibroblasts that induces HA synthesis. We conclude that dynamic changes of the myocardium, such as in cardiac hypertrophy, do not depend on the cardiomyocyte alone, but are achieved when both cardiomyocytes and fibroblasts are present.

Identifiers
urn:nbn:se:umu:diva-39573 (URN)10.1371/journal.pone.0014393 (DOI)000285576900008 ()21200430 (PubMedID)
Available from: 2011-02-01 Created: 2011-02-01 Last updated: 2017-12-11Bibliographically approved
2. Size determination of hyaluronan using a gas-phase electrophoretic mobility molecular analysis
Open this publication in new window or tab >>Size determination of hyaluronan using a gas-phase electrophoretic mobility molecular analysis
2012 (English)In: Glycobiology, ISSN 0959-6658, E-ISSN 1460-2423, Vol. 22, no 1, 7-11 p.Article in journal (Refereed) Published
Abstract [en]

Hyaluronan (HA) is a linear non-sulfated polysaccharide mainly found in the extracellular matrix. The size of HA can vary from a fewq saccharides up to at least 25,000 units, reaching molecular weights of 10x103 kDa. HA has mainly biological functions, and both its size and tissue concentration play an important role in many physiological and phatological processes. It is relatively easy ti determine the HA concentration using enzyme-linked binding protein assays, but the molecular weight of HA has so far been shown to be a more challenging task to measure. Here, we present a method for size determination of HA using gas-phase electrophoretic mobility molecular analysis (GEMMA), which utilizes the electrophoretic mobility of molecules in air to estimate the molecular weight of the analyte. We show that this method gives reliable molecular weight estimations of HA in the range 30-2400 kDa, which covers almost its whole biological range. The average measuring time for one GEMMA spectrum is between 5 and 10 min using only 6 pg of HA. In addition the peak area in a GEMMA spectrum can be used to estimate the HA concentration in the sample. The high sensitivity and small sample volumes make GEMMA an excellent tool for both size determination and estimation of concentration of samples with low HA concentration, as is the case for HA extracted from small tissue samples.

Place, publisher, year, edition, pages
Oxford: Oxford University Press, 2012
Keyword
Hyaluronan, gas-phase electrophotretic mobility molecular analyzer, HA size, molecular weight
National Category
Physical Chemistry
Research subject
Medical Biochemistry
Identifiers
urn:nbn:se:umu:diva-46590 (URN)10.1093/glycob/cwr096 (DOI)000297864400003 ()21752866 (PubMedID)
Available from: 2011-09-09 Created: 2011-09-07 Last updated: 2017-12-08Bibliographically approved
3. Predicting amyloid aggregation rates of proteins using multivariate analysis
Open this publication in new window or tab >>Predicting amyloid aggregation rates of proteins using multivariate analysis
(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
Multivariate analyis, amyloid aggregation, OPLS, AcP
Identifiers
urn:nbn:se:umu:diva-46591 (URN)
Available from: 2011-09-09 Created: 2011-09-07 Last updated: 2013-04-30Bibliographically approved

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