Department of Systems & Computational Biology


Thesis Seminar


On the evolutionary dynamics of chemical reaction networks: from early life to extant biology 

Ximo Pechuan Jorge 

Advisor: Dr. Aviv Bergman 

Wednesday, February 21, 2018

Price Center LeFrak Auditorium 



Abstract: Living systems are an exquisitely complex set of chemical reactions that have been tuned by the evolutionary process to exhibit robust adaptation to both internal and external fluctuations over a manifold of timescales. From the early forms of life to extant biology, our aim is to increase the understanding of how the evolutionary process has shaped the dynamical properties and architecture of chemical and metabolic reaction networks. For this purpose, we decided to investigate how dynamical features can be related to network topology at the very origin of life, during early stages of evolution and, finally, to address the influence of environmental constraints in evolving extant organisms. The chemical reaction networks hypothesized to be operating at the dawn of life have been traditionally regarded as a highly diverse and complex chemical ecosystem. In order for a biosphere to emerge on a planet, these reaction networks have to transition from a high to a moderate complexity state in which a subset of the possible chemical flows within the system dominate. We investigated how some putatively relevant dynamical properties that could have played a role in this transition can be derived from topological considerations using the chemical reaction network theory approach. After the first life forms emerged, the primitive organization of these protobiotic systems must have imposed severe constraints in the metabolic networks that they were able to encode. A solid hypothetical candidate for a primordial organization of life is the RNA ribocell or more commonly denominated the protocell. The protocell model encapsulates a set of replicating sequences that are both enzymes and genes, modeling a likely scenario given the RNA world theory in which RNA constituted both the catalytic and the informational component of living systems. The need to perform both functions in the context of the populations dynamics of the protocell establishes severe constraints that determine the metabolic networks that can be encapsulated. To address the effect of these constraints, we developed an intermediate complexity model of metabolism that captures enzyme saturation and evaluated how different network organizations evolve in the protocell model. Additionally, we considered the evolution of networks under fluctuating environments by performing a laboratory evolution experiment with Escherichia coli to determine the genetic adaptations under different types of environmental fluctuations and their effect in the overall phenotypic signature in each. 

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