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SUMMARY:&quot\;Home depot&quot\; model of evolution of prokaryotic metabol
 ic networks and their regulation - Sergei Maslov\, Brookhaven National Lab
 oratory
DTSTART:20100624T150000Z
DTEND:20100624T160000Z
UID:TALK25306@talks.cam.ac.uk
CONTACT:M. Madan Babu
DESCRIPTION:It has been reported [1] that the number of transcription fact
 ors in a prokaryotic genome is proportional to the *square* of the total n
 umber of genes. As a consequence of this trend the fraction of regulators 
 (the so-called “regulatory overhead”) is less than 1% in small (< 1000
  genes) bacterial genomes\, while in large genomes (~10\,000 genes) it rea
 ches as high as 10%.\n\nWe recently proposed [2] a general explanation of 
 this empirical scaling law and illustrated it using a simple model in whic
 h metabolic and regulatory networks co-evolve together. In our model proka
 ryotic organisms acquire new metabolic functions by the virtue of horizont
 al gene transfer of entire co-regulated metabolic pathways from a shared g
 ene pool (the “universal metabolic network”). This transfer is followe
 d by the removal of redundant enzymes. Pathways can also be lost following
  long-term changes in the environment or lifestyle of the organism.\n\nThe
  whole process can be compared to a homeowner buying sets of tools from a 
 hardware store (hence the “Home Depot” metaphor in the title) and late
 r returning duplicate or unnecessary items. We view the full repertoire of
  metabolic enzymes (or more generally all non-regulatory proteins) encoded
  in the genome of an organism as its collection of tools. Adapting to a ne
 w environmental condition (e.g. learning to use a new nutrient source) inv
 olves acquiring new enzymes as well as reusing some of the enzymes/tools t
 hat are already encoded in the genome. As the toolbox of an organism grows
  larger\, it can reuse its existing tools more often and thus needs to acq
 uire fewer new enzymes to master each new functional task.\n\nFrom this an
 alogy it follows that\, in general\, the number of regulators in the genom
 e should always scale faster than linearly with its total number of protei
 ns. The empirically observed quadratic scaling can be mathematically deriv
 ed for a broad range of universal network topologies. Furthermore\, sizes 
 of pathways in our model have a long-tailed power-law distribution. This o
 ffers a conceptual explanation for the empirically observed broad distribu
 tion of out-degrees of transcription factors in regulatory networks.\n\n[1
 ] E van Nimwegen\, “Scaling laws in the functional content of genomes”
 \, Trends Genet 19:479-84 2003.\n\n[2] S Maslov\, S Krishna\, T Y Pang\, K
  Sneppen\, “Toolbox model of evolution of prokaryotic metabolic networks
  and their regulation”\, PNAS 106 \, 9743-9748 2009.
LOCATION:Structural Studies Seminar Room\, MRC Laboratory of Molecular Bio
 logy\, Cambridge\, UK
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