Baumler_guestlecture

Baumler_guestlecture - 10/20/2011 Metabolic Modeling of...

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10/20/2011 1 Metabolic Modeling of Bacteria Dr. David J. Baumler CIBM Postdoctoral Fellow Primary mentor: Prof. Nicole T. Perna Secondary mentor: Prof. Jennifer L. Reed dbaumler@wisc.edu (Bringing Advanced Computational Techniques to Energy Research) " I think the next century (21st) will be the century of complexity. " Stephen Hawking What is a network? Systems biology is an approach to connect all information about the biology of an organism into a network
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10/20/2011 2 Systems biology = Systems engineering + biology? Talk outline: #1) background on the existing E. coli metabolic network #2) update the existing E. coli K-12 metabolic model #3) construct a E. coli pangenome metabolic network #4) construct additional metabolic models for five E. coli strains, four of which are human pathogens #5) Validate the computational metabolic models with comparison to experimental data #6) Evaluate strains in an evolutionary perspective
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10/20/2011 3 Constructing genome-scale metabolic networks For E. coli K-12 the current metabolic model consists of ~ 2,300 reactions and ~1,100 metabolites (Thiele I. et al . 2009 PLOS Comp. Biol.) Reactions Flux Balance Analysis (FBA): FBA calculates the flow of metabolites through this metabolic network, thereby making it possible to predict the growth rate of an organism or the rate of production of a biotechnologically important metabolite. -With no constraints, the flux distribution of a biological network may lie at any point in a solution space. -When mass balance constraints imposed by the stoichiometric matrix S and capacity constraints imposed by the lower and upper bounds ( a i and b i ) are applied to a network, it defines an allowable solution space. -Through optimization of an objective function, FBA can identify a single optimal flux distribution that lies on the edge of the allowable solution space. (Orth, Thiele, and Palsson Nat. Biotech 2010)
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10/20/2011 4 The successive addition of constraints will shrink the solution space by eliminating biologically infeasible steady-state solutions. Complete knowledge would reduce the steady- state solution space to a single solution. Since complete knowledge is not available for the majority of biochemical reaction networks the investigation of properties and capabilities of the solution space is very useful. (Feist A.F. and B.O Palsson (2008) Nature Biotechnology) The Iterative reconstruction and history of the E. coli metabolic network
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10/20/2011 5 Feist and Palsson (2008) Nature Biotechnology 26:659-667 Applications of the genome-scale model of E. coli
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10/20/2011 6 E. coli genomes sequenced at UW-Madison E. coli K-12 genome MG1655 (Blattner et al . Science 1997) E. coli O157:H7 strain 933 EDL (Perna et al . Nature 2001) Enterohemorrhagic (EHEC) Causes bloody diarrhea, HUS, renal kidney failure, and death E. coli CFT073 (Welch et al. PNAS 2002) Extraintestinal , uropathogenic (UPEC), isolated from a patient with a urinary tract infection (https://asap.ahabs.wisc.edu/asap/logon.php)
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Baumler_guestlecture - 10/20/2011 Metabolic Modeling of...

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