|DATE||June 04 (Tue), 2019|
|SPEAKER||Mi Jin Lee|
|HOST||Bak, Ji Hyun|
|TITLE||Evolution of metabolic networks in a growing ecosystem|
Considering that the roles of the cellular metabolism are well-defined and common to all living organisms and that, in contrast, individual metabolic reactions are executing a wide range of different functions, it might look unsurprising that the reaction popularity follows a broad, power-law distribution with exponent one while the number of reactions in an individual species is narrowly distributed. These empirical findings, however, can be a key to understanding the metabolism evolution and speciation in a unifying framework. Here we propose an evolving ecosystem in which the metabolic network of each species grows by recruiting a new reaction or the new reaction replaces an old similar reaction, giving birth to a new mutant species. Though much simplified, the proposed model captures the essential mechanism responsible for the empirical findings mentioned above. Due to the finiteness of external nutrient compounds, the set of recruited metabolic reactions grows exponentially first but then linearly with time, and we show that the latter behavior underlies the empirical power-law distribution of reaction popularity. We present extensive simulation and analytic results of the model and discuss their implications.