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Deciphering complex protein interaction kinetics using Interaction Map
Biotechnologie et signalisation cellulaire, Université de Strasbourg, France.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Biomedical Radiation Sciences.
Ridgeview Instruments AB, Uppsala, Sweden.
Biotechnologie et signalisation cellulaire, Université de Strasbourg, France.
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2012 (English)In: Biochemical and Biophysical Research Communications - BBRC, ISSN 0006-291X, E-ISSN 1090-2104, Vol. 428, no 1, 74-79 p.Article in journal (Refereed) Published
Abstract [en]

Cellular receptor systems are expected to present complex ligand interaction patterns that cannot beevaluated assuming a simple one ligand:one receptor interaction model. We have previously evaluatedheterogeneous interactions using an alternative method to regression analysis, called Interaction Map(IM). IM decomposes a time-resolved binding curve into its separate components. By replacing the reductionistic,scalar kinetic association rate constant ka and dissociation rate constant kd with a two-dimensionaldistribution of ka and kd, it is possible to display heterogeneous data as a map where each peakcorresponds to one of the components that contribute to the cumulative binding curve. Here we challengethe Interaction Map approach by artificially generating heterogeneous data from two known interactions,on either LigandTracer or Surface Plasmon Resonance devices. We prove the ability of IM toaccurately decompose these man-made heterogeneous binding curves composed of two different interactions.We conclude that the Interaction Map approach is well suited for the analysis of complex bindingdata and forecast that it has a potential to resolve previously uninterpretable data, in particular thosegenerated in cell-based assays.

Place, publisher, year, edition, pages
2012. Vol. 428, no 1, 74-79 p.
Keyword [en]
Real-time analysis, Kinetics, Heterogeneity, LigandTracer, SPR
National Category
Medical and Health Sciences
Research subject
Molecular Biotechnology
Identifiers
URN: urn:nbn:se:uu:diva-183869DOI: 10.1016/j.bbrc.2012.10.008ISI: 000311523200013OAI: oai:DiVA.org:uu-183869DiVA: diva2:564878
Available from: 2012-11-05 Created: 2012-11-05 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Novel Methods for Analysis of Heterogeneous Protein-Cell Interactions: Resolving How the Epidermal Growth Factor Binds to Its Receptor
Open this publication in new window or tab >>Novel Methods for Analysis of Heterogeneous Protein-Cell Interactions: Resolving How the Epidermal Growth Factor Binds to Its Receptor
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cells are complex biological units with advanced signalling systems, a dynamic capacity to adapt to its environment, and the ability to divide and grow. In fact, they are of such high level of complexity that it has deemed extremely difficult or even impossible to completely understand cells as complete units. The search for comprehending the cell has instead been divided into small, relatively isolated research fields, in which simplified models are used to explain cell biology. The result produced through these reductionistic investigations is integral for our current description of biology. However, there comes a time when it is possible to go beyond such simplifications and investigate cell biology at a higher level of complexity. That time is now.

This thesis describes the development of mathematical tools to investigate intricate biological systems, with focus on heterogeneous protein interactions. By the use of simulations, real-time measurements and kinetic fits, standard assays for specificity measurements and receptor quantification were scrutinized in order to find optimal experimental settings and reduce labour time as well as reagent cost. A novel analysis platform, called Interaction Map, was characterized and applied on several types of interactions. Interaction Map decomposes a time-resolved binding curve and presents information on the kinetics and magnitude of each interaction that contributed to the curve. This provides a greater understanding of parallel interactions involved in the same biological system, such as a cell. The heterogeneity of the epidermal growth factor receptor (EGFR) system was investigated with Interaction Map applied on data from the instrument LigandTracer, together with complementing manual assays. By further introducing disturbances to the system, such as tyrosine kinase inhibitors and variation in temperature, information was obtained about dimerization, internalization and degradation rates.

In the long term, analysis of binding kinetics and combinations of parallel interactions can improve the understanding of complex biomolecular mechanisms in cells and may explain some of the differences observed between cell lines, medical treatments and groups of patients.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. 65 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 854
Keyword
Heterogeneity, Kinetics, EGFR, HER2, LigandTracer, Interaction Map, Internalization, Specificity
National Category
Medical Biotechnology Cell and Molecular Biology
Research subject
Medical Science
Identifiers
urn:nbn:se:uu:diva-183872 (URN)978-91-554-8570-2 (ISBN)
Public defence
2013-02-15, Rudbeck Hall, Rudbeck Laboratory, Dag Hammarskjöldsväg 20, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2013-01-24 Created: 2012-11-05 Last updated: 2013-02-11Bibliographically approved

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Publisher's full texthttp://www.sciencedirect.com/science/article/pii/S0006291X12019328

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Björkelund, HannaStrandgård, JohnMalmqvist, MagnusAndersson, Karl

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