Bioreactor Simulator: Microbial Growth Kinetics & Monod Model

simulator intermediate ~12 min
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Doubling time = 1.39 h — μmax = 0.5 h⁻¹, Monod growth

With μmax = 0.5 h⁻¹ and 10 g/L initial glucose, the culture reaches a maximum biomass of 4.0 g/L with a doubling time of 1.39 hours during exponential phase.

Formula

μ = μmax × S/(Ks + S) (Monod equation)
dX/dt = μ × X (biomass growth rate)
dS/dt = -(μ × X)/Yx/s (substrate consumption rate)

Living Factories

Bioreactors are controlled vessels where living cells — bacteria, yeast, mammalian cells, or algae — convert substrates into valuable products: insulin, monoclonal antibodies, vaccines, biofuels, and food ingredients. The biopharmaceutical industry alone operates over $300 billion worth of bioreactor capacity worldwide. Understanding growth kinetics is essential for optimizing these living factories and predicting production yields from bench scale to 20,000-liter manufacturing vessels.

Monod Growth Kinetics

Jacques Monod's 1949 model remains the foundation of microbial growth theory. The hyperbolic relationship μ = μmax × S/(Ks + S) captures how cells grow at maximum rate when substrate is abundant and decelerate as nutrients deplete. The half-saturation constant Ks — the substrate concentration at half-maximal growth rate — characterizes how efficiently the organism scavenges nutrients. This simulation integrates the coupled differential equations for biomass and substrate, showing the classic batch growth curve with lag, exponential, deceleration, and stationary phases.

Yield & Efficiency

The biomass yield coefficient Yx/s quantifies how efficiently cells convert substrate to biomass. Aerobic E. coli on glucose achieves Yx/s ≈ 0.5 g/g, meaning half the sugar carbon is incorporated into new cells. Anaerobic conditions dramatically reduce yield because fermentation extracts far less energy per glucose molecule. For product formation, the product yield Yp/s is often more important — some products like ethanol are growth-associated, while others like antibiotics are produced mainly in stationary phase.

Scale-Up Challenges

A process optimized in a 1-liter flask may fail catastrophically in a 10,000-liter production bioreactor. As volume increases, mixing time grows from seconds to minutes, creating gradients in pH, temperature, dissolved oxygen, and substrate concentration. Cells cycling through these gradients experience metabolic stress. The simulation models how oxygen transfer rate, agitation power, and vessel geometry interact, letting you explore scale-up strategies: constant kLa, constant power per volume, or constant impeller tip speed — each optimizing different transport phenomena.

FAQ

What is the Monod growth model?

The Monod model describes microbial growth rate as a function of substrate concentration: μ = μmax × S/(Ks + S). It resembles Michaelis-Menten enzyme kinetics. At high substrate (S >> Ks), growth is at maximum rate. As substrate depletes toward Ks, growth slows. The model captures the transition from exponential to stationary phase in batch cultures.

What is the doubling time?

Doubling time (td) is how long it takes for the cell population to double during exponential growth: td = ln(2)/μ. E. coli doubles in ~20 minutes under optimal conditions (μmax ≈ 2.1 h⁻¹), while mammalian cells take 18-24 hours (μmax ≈ 0.03 h⁻¹). Doubling time is a key parameter for predicting production timelines.

What is the biomass yield coefficient?

The yield coefficient Yx/s is the mass of cells produced per mass of substrate consumed. For aerobic glucose metabolism in E. coli, Yx/s ≈ 0.4-0.5 g/g. Higher yields mean more efficient substrate conversion. The theoretical maximum is limited by thermodynamics — some energy must dissipate as heat for growth to be spontaneous.

How do you scale up a bioreactor?

Scale-up from lab (1-10 L) to production (10,000+ L) maintains key parameters like oxygen transfer rate (kLa), power per volume, and mixing time. However, large vessels have longer mixing times and potential gradients in pH, dissolved oxygen, and substrate concentration. Scale-up criteria (constant kLa, constant tip speed, or constant P/V) each optimize different aspects.

Sources

Embed

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