The evolutionary dynamics of metabolic protocells

Area of Science:

• * Origin of Life Research
• * Theoretical Biology
• * Evolutionary Systems Biology

Background:

• * Protocell models explore vesicle evolution with internal replicating sequences.
• * Genetic load from sequence assortment during division is a key challenge.
• * Existing models often lack realistic links between internal dynamics and protocell fitness.

Purpose of the Study:

• * Investigate how metabolic network features influence protocell evolution.
• * Understand the impact of kinetic and topological metabolism on assortment load.
• * Explore mechanisms for ameliorating genetic load in early protocells.

Main Methods:

• * Developed a protocell model with a fitness function based on metabolic network output flux.
• * Modeled internal sequences as Michaelis-Menten catalysts with saturation.
• * Analyzed the effects of kinetic parameters, stoichiometry, and network architecture on evolution.

Main Results:

• * Catalyst saturation effectively reduces assortment load by increasing sequence redundancy.
• * Modifying kinetic or stoichiometric parameters enhances metabolic flux and ameliorates load.
• * Parallel network motifs and bimolecular catalysts promote metabolic complexity.

Conclusions:

• * Metabolic network dynamics, particularly catalyst saturation, are crucial constraints on protocell evolution.
• * Network architecture influences the ability to manage genetic load and increase complexity.
• * This model provides insights into the co-evolution of metabolism and protocell survival.