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Parameter Estimation in Systems Biology

Spatiotemporal Modelling of Intracellular Signalling in Bacterial Chemotaxis

author: Marcus J. Tindall, Mathematical Institute, Centre for Mathematical Biology, University of Oxford

Description

Whilst theoretical models have been used to understand aspects of bacterial chemotaxis systems for the past thirty or so years, little work has focused on the importance that spatial localisation of proteins within the cytoplasm of the cell has on the overall functionality of the intracellular network. In this talk we will examine spatio-temporal models of signal transduction developed to describe the phosphotransfer pathway within E. coli. This model framework will then be extended to examine the importance of protein localisation within R. sphaeroides, a species which contains considerably more phosphotransfer proteins than E. coli and the spatial localisation of which plays a particularly important role in activating certain elements of the phosphotransfer network. The difficulties encountered in obtaining robust parameter estimates for reaction rates within the R. sphaeroides will also be detailed.

Joint work with S. L. Porter, P. K. Maini and J. P. Armitage.

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Slides
0:02 Spatiotemporal Modelling of Intracellular Signalling in Bacterial Chemotaxis
0:40 Outline
1:28 Bacterial chemotaxis
2:44 Bacterial chemotaxis
3:41 Intracellular Signalling in E. coli
5:19 Intracellular Signalling in E. coli
5:40 Intracellular Signalling in E. coli
5:55 What is the importance of protein spatial localisation within a bacterial cell?
5:59 A Spatiotemporal Model of Intracellular Signalling in E. coli
6:37 A Spatiotemporal Model of Intracellular Signalling in E. coli
7:06 A Spatiotemporal Model of Intracellular Signalling in E. coli
7:39 A Spatiotemporal Model of Intracellular Signalling in E. coli
8:22 A Spatiotemporal Model of Intracellular Signalling in E. coli
9:07 Intracellular Signalling in Rhodobacter sphaeroides
10:05 Intracellular Signalling in Rhodobacter sphaeroides
11:12 In vitro Reaction Data
12:49 Determining reaction rates from in vitro data
13:54 Determining reaction rates from in vitro data
14:24 Determining reaction rates from in vitro data
15:11 Determining reaction rates from in vitro data
16:38 Determining reaction rates from in vitro data
17:12 Determining reaction rates from in vitro data

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