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Automation assisted anaerobic phenotyping for metabolic engineering
Kaushik Raj1, Naveen Venayak1, Patrick Diep1
1Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, M5S 3E5, Canada.
Microbial Cell Factories
|September 24, 2021
Summary
This study introduces an eco-friendly automation workflow for metabolic engineering, reducing plastic waste and costs. It enables efficient high-throughput screening and effective scale-down modeling for microbial chemical production.
Area of Science:
- Biotechnology
- Metabolic Engineering
- Synthetic Biology
Background:
- Metabolic engineering aims to produce valuable chemicals using microorganisms.
- High-throughput screening is crucial for selecting optimal microbial strains.
- Current methods face high costs and generate significant plastic waste.
Purpose of the Study:
- Develop an eco-friendly, cost-effective automation workflow for high-throughput microbial strain phenotyping.
- Establish reliable methods for anaerobic cultivation in microplates.
- Create an effective scale-down model for bioreactor fermentations.
Main Methods:
- Utilized fixed-tip liquid handling systems with novel decontamination and calibration protocols.
- Developed inexpensive methods for establishing anaerobic conditions in microplates.
- Employed t-distributed stochastic neighbors embedding (t-SNE) for dimensionality reduction and strain clustering.
Main Results:
- Significantly reduced plastic waste associated with liquid handling.
- Successfully validated the platform through anaerobic enzyme and microbial phenotypic screens.
- Demonstrated comparable microbial phenotypes between scaled-down and 0.5 L bioreactor systems.
- Showcased t-SNE's effectiveness in clustering bioreactor-scale strains.
Conclusions:
- Fixed-tip systems and associated protocols can decrease laboratory plastic waste.
- The developed platform serves as an effective scale-down model for bioreactor fermentations.
- Integrated data analysis accelerates the design-build-test-learn cycle in metabolic engineering.
