Lahore University of Management Sciences

Dr. Aziz Mithani Talks at Ohio State University

May 24, 2012

Share this page on Facebook Share this page on Twitter LUMS Official Vimeo Channel LUMS Official YouTube Channel

 

Dr. Aziz Mithani, Assistant Professor at the Department of Biology, LUMS School of Science and Engineering (SBASSE) delivered a talk titled, “A stochastic model for the evolution of metabolic network using neighbor dependence” at a workshop on Algebraic Methods in Systems and Evolutionary Biology. The workshop was held at at Mathematical Biosciences Institute, Ohio State University.

The talk was on the availability of genomes of many closely related bacteria with diverse metabolic capabilities that offered the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions) or complex (incorporating dependencies among reactions) stochastic models of metabolic evolution, studying how metabolic networks evolve over time is now possible. The metabolic network evolution was described as a discrete space continuous time Markov process. Also, a neighbour-dependent model were introduced for the evolution of metabolic networks where the rates with which reactions are added or removed depend on the fraction of neighbouring reactions present in the network.

The model also allowed estimation of the strength of the neighbourhood effect during the course of evolution. During the session, Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral Pseudomonas.

The results suggested that pathway maps that are conserved across the Pseudomonas Phylogeny have a stronger neighbourhood structure than those which have a variable distribution of reactions across the Phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks.