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Quantitative and context-specific Ras-effector networks in health and disease

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On Monday the 21st of September 2020 Christina Kiel of University College Dublin will give a seminar entitled Quantitative and context-specific Ras-effector networks in health and disease. The seminar is open to members of the Department, other academic staff, students and members of Collegio A Volta and will be delivered online. The link for access is available on the poster that can be downloaded here.

Network-based approaches offer the potential to deliver comprehensive understanding of the molecular basis underlying diseases. Ras-effector interactions and related concepts of quantitative network biology will be introduced with a focus on how binding affinities and interaction competition between network components impacts downstream signalling responses [1]. Next, the role of tissue context for the ‘wiring landscape’ of Ras-effector interactions will be discussed. Indeed, simply considering effector-specific binding affinities together with tissue-specific protein abundances influences the number of individual effectors in complex with Ras [2, 3]. However, the by far greater impact on Ras-effector complex formation arises from additional domains present in effectors that can be recruited to the plasma membrane, where Ras is localized [known as “piggy back” mechanism [4]) (e.g. in response to external stimuli) [3]. This is a highly physiologically relevant scenario, as cells in their normal tissue microenvironment are constantly experiencing a variety of stimuli that reach out to receptors situated on the plasma membranes. It is, therefore, critical to consider those additional stimuli present through paracrine signalling of the tissue stroma environment when experimentally contextualizing networks. Finally, our current efforts to predict and experimentally analyse how different types of oncogenic Ras mutations (e.g. G12D, G12V, Q61L) cause distinct phenotypes, including metabolic reprogramming will be presented. Here, we are using COnstraint-Based Reconstruction and Analysis (COBRA) methods to generate metabolic models for a subset of RAS oncogenic mutations with the aim of generating a mechanistic understanding of the principles of RAS-mediated oncogenic metabolic rewiring.

1. Kiel C, Verschueren E, Yang JS, Serrano L. Integration of protein abundance and structure data reveals competition in the ErbB signaling network. Sci Signal. 2013 Dec 17;6(306):ra109.
2. Ibáňez Gaspar V, Catozzi S, Ternet C, Luthert PJ, Kiel C. Analysis of Ras-effector interaction competition in large intestine and colorectal cancer context. Small GTPases. 2020 Feb 14:1-17.
3. Catozzi S, Halasz M, Kiel C. Predicted ‘wiring landscape’ of Ras-effector interactions in 29 human tissues. NPJ Systems Biology and Applications, in revision (2020).
4. Kholodenko BN, Hoek JB, Westerhoff HV. Why cytoplasmic signalling proteins should be recruited to cell membranes. Trends Cell Biol. 2000 May;10(5):173-8.

Christina Kiel is a Principal Investigator leading a combined experimental/ computational research group in the School of Medicine at University College Dublin with affiliations at Systems Biology Ireland and the UCD Charles Institute of Dermatology. Her research focuses on the quantitative and systems analysis of signalling networks with the ambition of understanding context-specific (re)wiring in health and disease. Her approaches combine and integrate protein engineering, 3D structural modelling, experimental network biology, and computational network modelling techniques. Christina has built her career around developing an understanding of how networks function. Early on she demonstrated how small perturbations of binding affinities (‘kinetic perturbations’ mutations) can impact downstream signalling responses, establishing how knowledge of the topology of a network alone is not enough to predict its function. To this end, a large part of her previous work has focused on characterizing protein interfaces and interactions on a quantitative level, e.g. using in vitro experimental thermodynamic characterizations of binding, in silico protein engineering-based quantitative predictions, or a combination of both computational and experimental/ engineering approaches. She received her education at the University of Bochum (Germany) with a Master in Biochemistry and a Doctorate Degree at the Max-Planck Institute of Molecular Physiology (Dortmund, Germany). For her postdoctoral work, she joined the lab of Luis Serrano at EMBL in Heidelberg (Germany). This was followed by a position as a staff scientist at CRG Barcelona (Spain). She was recruited to University College Dublin (Ireland) in September 2017 in the context of the “President of Ireland Future Research Leaders” award.

The structure of cultural networks bears many similarities with that of molecular networks.

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