University of Birmingham > Talks@bham > Applied Mathematics Seminar Series > Microbiology’s N-body Problem: Interspecies Metabolite Transfer in Spatially-Structured Populations

## Microbiology’s N-body Problem: Interspecies Metabolite Transfer in Spatially-Structured PopulationsAdd to your list(s) Download to your calendar using vCal - Rob Clegg (University of Birmingham)
- Thursday 02 October 2014, 16:00-17:00
- Muirhead 118.
If you have a question about this talk, please contact Alexandra Tzella. Room changed No microbe is an island: exchange of metabolites between microbes is crucial to nutrient cycles in both natural and man-made environments. However, even when it is experimentally possible, directly measuring or modelling the rate of exchange within observed populations is difficult. In a sense, this is comparable to the N-body problem of planetary motion, where predicting the long- term effects of gravitational pull between heavenly bodies becomes increasingly difficult the more numerous they are. As metabolites are often transported by diffusion, reducing the physical distance between partners can greatly increase the rate of exchange and so also increase the productivity of the population. For example, degradation of organic matter to methane in lake sediments and sewage treatment plants often requires rapid transfer of acetate or hydrogen from producers to consumers. Ecologists and engineers interested in this problem have estimated the rate of metabolite exchange between groups using the average distance between a cell of one type and its nearest neighbour of the other. This statistic is a valid estimator in the detection and classification of spatial patterns, but its reliability in estimation of exchange rate is untested. The uncertainty in estimating rate of exchange is an issue affecting many topics in microbial ecology and biochemical engineering, and our computational approach seeks to correct this. The rate of exchange is both solved numerically, and estimated using spatial statistics such as the distance to nearest neighbour. These estimates can then be compared to the numerical solution. The overall aim of this project is to determine the most reliable statistical estimator in a scientifically rigorous manner, so that those studying these systems in the field can make predictions in confidence. This talk is part of the Applied Mathematics Seminar Series series. ## This talk is included in these lists:Note that ex-directory lists are not shown. |
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