Event Details

Date:
Monday, 10 December 2012
Time:
11:00 am - 12:00 pm
Room:
Level 4 Seminar Room, AIBN, Building 75
UQ Location:
Australian Institute for Bioengineering and Nanotechnology (St Lucia)
Event category(s):

Event Contact

Name:
Dr Robert Speight
Phone:
63158
Email:
r.speight@uq.edu.au
Org. Unit:
Australian Institute for Bioengineering and Nanotechnology

Event Description

Full Description:
Abstract:
Elementary mode (EM) analysis is an established tool in metabolic engineering, as it allows for an unbiased decomposition of metabolic networks in biologically meaningful pathways. An EM is a minimal set of reactions that operates under steady state conditions, while obeying all (ir-)reversibility constraints on the reactions. By systematically deleting unwanted EM, networks of minimal functionality can be created.

However, there are three main problems with EM analysis: (i) currently, EM can only be calculated for small networks as their number explodes with systems size; (ii) even if all EM are available, their huge number hinders analysis; and (iii) gene-enzyme-reaction mapping further complicates the determination of biologically meaningful and feasible deletion strategies. We will present solutions to all three problems.

We introduce a novel approach to speed up the calculation of EM by including transcriptional regulatory information into the analysis of metabolic networks. Taking into account gene regulation dramatically reduces the number of feasible EM. Computational costs, such as runtime, memory usage, and disk space, are considerably reduced. These modifications allow using EM analysis on medium scale metabolic networks.

To address the second and third problem, we demonstrate that -- despite the huge number of EM -- an EM analysis is ideally suited for rational strain design. We show that by linear optimization we are able to identify all sets of knockouts, which result in the repression of undesirable network states fully taking cellular regulation into account. Our method explicitly favors experimentally feasible gene knockouts and remains manageable even if billions of EM enter the analysis.

We validate our approach by designing the most efficient ethanol producing E. coli strain and compare our predictions to in vivo results.

Juergen Zanghellini got his master in electrical engineering at the Vienna University of Technology. During his PhD he moved to Ottawa, ON, Canada where he modeled laser driven ionization processes in atoms and small molecules. He received his PhD in theoretical physics in 2004. After returning to Austria he joined the Institute of Chemistry (Graz University, Austria) and focused his work on modeling fat metabolism in yeast. In 2010 he did a post-doc at the Australian Centre for Plant Functional Genomics (ACPFG), Adelaide, SA. Since 2011 Juergen Zanghellini is leading the junior group on metabolic modelling at Austrian Centre of Industrial Biotechnology (ACIB). His research interest focuses on the analysis of (metabolic) networks using methods from systems biology.

Directions to UQ

Google Map:
Directions:
To St Lucia Campus, UQ Ipswich, and UQ Gatton.

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