Table 1:

List of key COMETS capabilities and application examples.

General category	Specific category	Capability	Example rationale
Spatial capabilities	Biomass motion	Linear diffusion	Run-and-tumble motion
		Non-linear diffusion dependent on local properties, deterministic or stochastic	Metabolite lubrication, surfactant secretion in the environment, cooperative motion
		Convective (pushing) motion, deterministic or stochastic	Colony growth via pushing forces, non-motile motion
		Impenetrable barriers	Barriers such as rocks or beads
		Model mixing or enforced non-overlap	Cells can swim into the same general space, or create layered biofilms which prevents penetration by other cell types
	Metabolite motion	Linear diffusion	Normal property of chemicals
		Impenetrable barriers	Barriers such as rocks or beads
Biological capabilities	Cell growth and death	Growth rate via flux-balance analysis with or without pFBA secondary optimization	Optimal metabolic growth with or without minimized sum of absolute values of all fluxes
		Standard FBA, Monod, or Hill uptake rates	Linear, saturating, or cooperative uptake mechanisms
		Lag phases via activation rate	Variable time to exit from stationary state
		Fixed, species-specific death rates	Cell death, proportional to population size
		Gene cost	Size of the genome represents an energy cost that is applied to lower the biomass growth rate.
		Light absorption	Simulation of photosynthetic organisms
	Stochastic changes	Evolution by generation of related models with altered flux bounds	Mutations arising during ecosystem lifetime
		Stochastic fluctuations (Gaussian or demographic)	Random fluctuations in growth rate due to environmental or demographic fluctuations
Environmental capabilities	Metabolite sources and sinks	Fixed local concentration of a given metabolite	Buffered source of a metabolite, such as oxygen at an air/liquid interface
		Fixed local environmental metabolite replenishment rate	Spatially structured: interaction of community with nutrient-producing host cells Spatially unstructured: Chemostat
		Constant dilution rates (for all biomass and environmental metabolites)	Simulation of bioreactor in chemostat mode
		Time-dependent variation on the abundance of a given extracellular metabolite, according to a predefined function	Periodic availability of light for day-night cycles
	Bottlenecks	Abrupt dilution events of biomass followed by replenishment of nutrients	Batch transfer experiments or seasonality
Other		Extracellular enzyme costly secretion and activity	Secretion of cellulase and cellulolytic activity by diffusing enzymes in the environment
		Capacity to handle many (>>100) stoichiometric models	Simulations of complex communities/microbiomes