Establishing the hierarchies in regulation .... in time

Lead Research Organisation: University of Manchester
Department Name: Chem Eng and Analytical Science


Humans, animals, plants and even living creatures so small that we can not see them with our naked eye (such as the yeasts that make our bread and beer), can adapt remarkably well to changes in their environment. The latter include changes in temperature, food supply, and exposure to toxic chemicals such as nicotin and alcohol. The adaptation is often much better than the adaptation of man-made systems. Hence we are eager to learn from Biology how the adaptation can be so effective. One might think that this should be easy now, with 'DNA-sequencing based functional genomics' delivering so many experimental results. However, the amounts of new results are so staggering that it is hard to see the forest for the trees. The scientists are in need of straightforward ways to interpret those results in terms of what they imply for adaptation and the regulation thereof. We recently obtained evidence suggesting that biological adaptation is so effective because it invokes a succession of regulatory mechanisms. The mechanisms that come into play first may be ones that are always on stand-bye but less efficient. The ones that are onvoked subsequently, may be more effective ultimately but are too 'expensive' to keep on stand-bye all the time. We here propose a research project that will establish a precise method to prove this experimentally. The new method that we shall develop here is called time-dependent regulation analysis. It will be demonstrated completely for yeast cells that are adapting to a shortage of nitrogen (or sugar). We expect to learn how Biology still beats man-made systems in terms of subtle and efficient regulation. This has the perspective of improving man-made control systems, as well as the environmentally friendly production of beer, bread and new biologicals.

Technical Summary

The continued functioning of living organisms depends on optimal responses to dynamic variations in various external and internal conditions. This is particularly so for unicellular microorganisms, such as baker's yeast. The corresponding regulation of the various processes that make up a living cell's function must proceed in significant coherence. This view does not sit easily with the traditional paradigms for studying regulation, which focus either on metabolic or on transcriptional regulation. Although results in functional genomics now suggest that for many processes regulation is not confined to the level of transcription, there has been no method to quantify how much regulation is metabolic and how much transcriptional, at various points in time. We will here develop and apply such a method. The method proposed is different from metabolic control analysis, as are the issues the two methods address. Yet, the new method is also fortified by theorems that will be proven mathematically, demonstrated numerically, and put to practice experimentally. The analysis includes regulation at the levels of mRNA life time, translation, protein modification, and protein stability. The method will be applied to the regulatory events of central carbon and energy metabolism in yeast that occur when growth conditions change dynamically. We shall here further improve the precision at which process rates and mRNA and protein concentrations/modifications are measured. Deliverables include insight into the extent to which the various regulatory mechanisms in the cell contribute at various successive phases of dynamic regulatory transients. They will suggest new ways of engineering cellular processes by interfering at the best possible time at various points of the cell's regulation, rather than by interfering once then being thwarted by the subsequent adaptations of the cell.


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Albert, M. -A. (2006) Exploiting metabolic and gene-expression networks for drug design in ICOPA XI: Proceedings of the 11th International Congress of Parasitology

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Armitage, Emily (2012) Systems biology of chemotherapy in hypoxia environments in Mutagenesis

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Armitage, Emily (2012) Systems biology of HIF metabolism in cancer in Mutagenesis

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Bakker, B. (2006) Hierarchical regulation in Comparative Biochemistry and Physiology a-Molecular & Integrative Physiology

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Bevilacqua A (2008) Vertical systems biology: from DNA to flux and back. in SEB experimental biology series

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Boogerd, Fred C (2007) Introduction to systems biology. in Exs

Description In science there has been a strong tendency to focus, and with considerable success. In terms of regulation of cell function, this focus has been on transcription regulation by some and on metabolic regulation by others. We here discovered that regulation need not be (and is not often) confined to either transcription or metabolism. More often some regulation is in each, additional regulation is at the translation level, and at the levels of the stability of proteins and mRNA's. We discovered that this varies with time as well. We also devised a mathematical way of dealing with these phenomena so that experimental data can be interpreted precisely so as to determine how much of each regulation occurs at each of the various levels. This work contributed to the development of systems biology, relating transcription networking to metabolic networking.
Exploitation Route Through the publications. And through application oriented projects where the output of a product is co-regulated at both the transcription and the metabolic level.
Sectors Agriculture, Food and Drink,Education,Pharmaceuticals and Medical Biotechnology,Other

Description The findings have been used by reading of our publications (see their citations) in research projects by other academic groups. We suspect that biotechnology industry is also using our methodologies, but are not being told.
Sector Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Education,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology,Other
Impact Types Economic

Title Candidate pathway finding 
Description Steatosis or fatty liver disease is an important disease sometimes leading to hepatocarcinoma. Most researchers engaged in genomics are searching for so-called candidate genes in their data, which then should identify single-gene causes and single target strategies. We have developed a way to identify/examine 'candidate pathways'. More inn general, the portfolio of projects ahs led to a great increase in number of detailed kinetic models of metabolic pathways (as reported in JWS-Online). these are now of great use for other organisms and the same pathways or other pathways in the same organisms. All these models are also of use for the development of the Infrastructure Systems Biology Europe (ISBE). 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2016 
Provided To Others? Yes  
Impact This is now used in multiple research projects. Through JWS online and BioModels our models are used by many. 
Description Snoep 
Organisation University of Stellenbosch
Country South Africa 
Sector Academic/University 
PI Contribution Ideas, models, data
Collaborator Contribution Ideas, models, data management
Impact Publications Models Grant proposals
Description VU Amsterdam 
Organisation Free University of Amsterdam
Country Netherlands 
Sector Academic/University 
PI Contribution Expertise, information, data
Collaborator Contribution Expertise, information, data
Impact Publications Grant proposals Learned students Understanding of Biology