Integrated systems biology study of the control of protein synthesis capacity and fitness in a eukaryotic microbe.

Lead Research Organisation: University of Warwick
Department Name: School of Life Sciences


The information contained in the genes of living cells has to be converted into cellular components that form structures and enable biochemical reactions to take place. This process is called gene expression and it is vital to all known life. Gene expression comprises two main steps, called transcription and translation. In transcription, the information in the DNA sequences of the genes is converted into equivalent sequences in so-called messenger RNA (mRNA) molecules. In translation, the mRNA molecules are 'read' by a large molecular structure called the ribosome, which uses the information to dictate the synthesis of proteins. We want to understand how the synthesis of proteins in the living cell is controlled. In order to do this, we are subjecting the protein synthesis process to a new type of analysis that tells us how each component of the machinery that makes proteins contributes to determining how efficiently the system works. We will also be studying how the components of this system interact outside of the cell, so that we obtain detailed information about the ways that these molecules interact with each other. The quantitative data that are generated by these experiments will then be fed into an advanced model set up in a computer. When this model is running and has been fed all of the required information, it will be a very useful resource that can be used by many researchers interested in gene expression. One very useful property will be the ability to predict what happens when there is a defect in the gene expression process - something that can cause disease in humans. The theoretical and experimental technologies developed and applied in this project will be of value to a wide spectrum of researchers in academia and industry, and will help us understand gene expression defects in diseased cells.

Technical Summary

Given the fundamental importance of protein synthesis to living systems, we feel that the full characterisation of the macromolecular machinery responsible for this process in eukaryotes should be a high priority. Since the 1970s, researchers worldwide have accumulated a considerable amount of important knowledge of the structure and function of the eukaryotic translational machinery, but much of this information is qualitative. This means that it is still impossible to develop proper quantitative (and predictive) models for the translation pathway. There remain many fundamental questions relating to the molecular mechanisms underpinning translation and to the control of the system, and an essential strategy to answer a number of these questions is to obtain precise information about the principles of control governing translation machinery. We see this work as a major component of a more general strategy to develop a comprehensive and detailed digital model of eukaryotic translation that incorporates fully quantitative and predictive elements that collectively advance understanding of molecular mechanisms, rate control, system robustness and regulation. Rather than build in silico models on kinetic values for the various steps that have been determined (in vitro) in diverse labs and using diverse methods, we focus here on rate control parameters that are all determined in a consistent manner in living cells. Associated with this project will be a number of technologies that can be applied in diverse ways to biological systems and which will have added value for biotechnology and the understanding of animal and human diseases. This project brings together all the required strands of theoretical and experimental expertise to build a unique capacity to address the challenge of elucidating the nature of translational control at the system level. It will also provide state-of-the-art training for young scientists in a diversity of quantitative bioscience methods.

Planned Impact

Who will benefit from this research? This research will benefit the fundamental research community, those researchers working on biomedical problems, and the biotech industry. How will they benefit from this research? Scientists working on the mechanisms underpinning gene expression in eukaryotic systems will benefit in the very short term because the results will advance our understanding of how eukaryotic cells make proteins and how this process is controlled. There will be mid-term benefit for researchers wishing to apply these results to biomedical and biotechnological problems. An enhanced (quantitative) understanding of the protein synthesis system means that the elucidation of disease mechanisms will be facilitated and that there will be an improved basis for targeting drugs, for example those vs diseases and fungal infections. Moreover, this work will also provide an improved basis for maximising protein yields in the biotech industry. There will also be short- and mid-term benefits in a broader sense since the technologies and strategies developed in this project will be applicable to a wide range of research problems and will find numerous applications of potential medical and commercial interest. More detailed consideration of two key benefits 1. The quantitative data generated by this project will contribute strongly to the development of a digital model of a eukaryotic organism (with direct relevance to man). By inputting the data into a new system model of yeast protein synthesis, we will be able to advance considerably the level of understanding of these systems. Accurate quantitative systems models are critical to our understanding of the molecular basis of disease and to drug-development strategies. 2. This quantitative approach will be of direct benefit to biotech applications involving protein production from fungal (and other eukaryotic) cells. What are the realistic timescales for the benefits to be realised? The technologies being developed and applied and the data generated using them could be transferred to others from 12 months into the project. What will be done to ensure that they have the opportunity to benefit from this research? We will make the results widely known through publications, talks at national and international conferences and via our website. Our reagents will be made available to the wider research community. We will be open to collaborations with other parties and will promote take-up in both the academic and commercial sectors through our frequent workshops, both those organised at Warwick and those organised by the McCarthy group at the international level. Beyond this, we will transfer knowledge and skills related to this research to younger scientists through our frequent advanced training courses (funded by FEBS and industry). The institute in which we work is highly interdisciplinary and very well networked, which means that the communication of such results is both effective and rapid. What research and professional skills will staff working on the project develop which they could apply in all employment sectors? Staff working on this project will acquire important skills in cutting edge technology that can be applied widely in academic research and in industry. They will also learn how to integrate this information into a wider picture. What will be done to ensure that they benefit from this research? They will be fully engaged with all collaborations and receive all appropriate training, and will make presentations on it at national/international conferences. Their CVs will be strengthened thrugh the training in research and technology development they receive, they will be named on publications, and they will be actively involved in discussions with potential industrial partners. Engagement of users and beneficiaries. This will be achieved as outlined above, i.e. via diverse forms of communication and outreach.


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Description We have established a computational model for rate control in protein synthesis in yeast that has been tested using a new approach to in vivo rate control analysis. Using the dual-site rate control method described elsewhere in this report, we have been able to establish that the scanning step in the protein synthesis pathway is a low-rate-control/high-flux step linking the high-rate-control mRNA-40S-ribosomal-subunit recruitment step to the high-rate-control initiation, elongation and termination steps of protein synthesis. A publication on this work will be submitted imminently.
Exploitation Route The existence of such a detailed model allows others to make quantitative predictions about how changes in the activities of components of the protein synthesis machinery will affect protein synthesis and organism competitiveness. The synthetic copper-sensitive promoter will be of use in multiple other studies in yeast - there are very few alternative regulatory promoters that can be controlled in an orthogonal manner.
Sectors Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology

Description As we further develop our digital representation of the translation machinery, we develop tools and understanding that can be utilised in other projects on gene expression rate control. For example, this understanding currently contributes to a collaborative project with Ingenza in which we are optimising rate control in a series of coupled reactions catalysed by cellulose-degrading enzymes.
First Year Of Impact 2015
Sector Manufacturing, including Industrial Biotechology
Impact Types Economic

Title Dual-site rate control assay 
Description We have developed a method for analysing rate control in complex biological systems that uses two, independently regulatable, promoters. One of the promoters is the established tetO7 system, which can be down-regulated using doxycycline. The other promoter is a synthetic construct that has been developed by us and is based on the CTR1 promoter. Insertion of three copies of the Mac1-binding copper response element (CuRE) has allowed us to generate a promoter that has the same dynamic range as the CTR1 promoter but which is overall much stronger. Combining regulation of pairs of genes encoding components of the translation machinery in this way generates valuable quantitative 'titrations' of translation factor activities. The observed relationships can then be used to test the predictions of our newly developed version of the in vivo rate control model for translation reported in Firczuk et al (2013).. 
Type Of Material Technology assay or reagent 
Provided To Others? No  
Impact This method enables us to optimise our digital representation of the translation machinery in yeast, thus contributing towards the establishment of a digital representation of the workings of the entire yeast cell. This will accordingly pave the way to a truly predictive systems biology.