Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions.

Area of Science:

• Biotechnology
• Algal Biotechnology
• Bioprocess Engineering

Background:

• Microalgae are valuable for producing high-value products, biomass, animal feed, and biofuels.
• Efficient cultivation is key to unlocking the full potential of microalgae.

Purpose of the Study:

• To develop and validate a high-throughput automated screening system for optimizing microalgae production.
• To identify optimal nutrient conditions for maximizing microalgae growth rates and product yields.

Main Methods:

• A miniaturized 1,728 multiwell format was employed for simultaneous screening of multiple microalgae strains.
• A two-step process was used: Step 1 optimized primary nutrients (nitrogen, phosphorus), and Step 2 utilized Box-Behnken analysis for other nutrients (Ca, Mg, Fe, Mn, Zn, Cu, B, Se, V, Si).
• Specific growth rates and maximum OD750 values were measured to assess culture performance.

Main Results:

• The screen successfully identified the primary effects of 12 key nutrients on microalgae growth.
• Significant pairwise nutrient interactions, such as Ca-Mg, were elucidated.
• Optimal production conditions within the tested statistical space were determined.

Conclusions:

• The developed screening system provides a robust method for optimizing algae cultivation conditions.
• Findings facilitate targeted experimental designs for maximizing algae biomass and product yields.
• This approach supports the advancement of microalgae as a sustainable production platform.