eprintid: 200
rev_number: 4
eprint_status: archive
userid: 6
dir: disk0/00/00/02/00
datestamp: 2009-01-08
lastmod: 2015-05-29 19:49:16
status_changed: 2009-04-08 16:55:51
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Ward, John
creators_name: Moulin, Michael
creators_name: Feugier, Francois
creators_name: Hazledine, Saul
contributors_name: Middleton, Alistair
contributors_name: Norris, Eleanor
contributors_name: Owen, Markus
contributors_name: Wattis, Jonathan
contributors_name: Green, Ed
title: A mathematical model of the tetrapyrrole biosynthesis pathway
ispublished: pub
subjects: other
studygroups: mpssg1
companyname: Unilever
full_text_status: public
abstract: The tetrapyrrole biosynthesis pathway is a key part in chlorophyll production and is essential for plant survival. It involves numerous interacting compounds and, crucially, light. The understanding of the complex regulation processes involved has been the focus of extensive experimental research providing a large source of data. A particular set of data, concerned with the modelling described in this report, involves 24 hour timecourse data from seedlings exposed to constant light, following a three day period of growth from seed in darkness. This data includes the levels of key components such as chlorophyll, ATP, chlorophyllide and proto-chlorophyllide. Amongst the questions posed in the study-group were: i) Can the timecourse data be predicted by a model? ii) Can it predict the dierences in levels of various components in found mutant strains.

To address these questions, we present in this report a model consisting of a coupled system of nonlinear ODEs that describes a simplied version of the tetrapyrrole pathway based on mass action laws. Model simulations produced results that agree qualitatively well with most, but not all, of the available timecourse data obtained from wild-type and mutant strains. Nearly all of the model's parameters are not known, so the values used in these simulations are based on estimates of the relative timescales of the reactions. An attempt at improving these estimates using data tting techniques is also discussed.
problem_statement: Tea researchers aim to understand the genetic and biochemical connections that govern the flavour and aroma of tea, given a specified set of growth conditions. Conventional crop breeding is often used as a tool to improve crop varieties, but, tea plants have a life-cycle of one century, so crop breeding is not an option for improving tea aroma. This proposal focuses only on the aroma aspect of this work, and we are concentrating on terpenoid / isoprenoid pathways, as these show most transcriptional changes.

   1. Can we produce a simple dynamical model of terpenoid and isoprenoid biosynthesis that can account for the changes in floral notes that correspond to the levels of metabolites, and build on this model to account for observations?
   2. Can we use a predictive mathematical model to define parts of the pathway that are amenable to change using the manufacturing process in order to produce new types of tea with desirable characteristics (e.g. floral notes)?
   3. How should the manufacturing process be changed so that the final product is the same irrespective of the differences in picked tea leaves from one year to the next?
   4. How might growth conditions and manufacturing process be changed to produce new aroma profiles for the preferences of the consumer?
date: 2007-12
date_type: published
pages: 16
citation:   Ward, John and Moulin, Michael and Feugier, Francois and Hazledine, Saul  (2007) A mathematical model of the tetrapyrrole biosynthesis pathway.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/200/1/report4.pdf