Automation assisted anaerobic phenotyping for metabolic engineering

Research output: Contribution to journalArticlepeer-review

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DOI

  • Kaushik Raj
    University of Toronto
  • Naveen Venayak
    University of Toronto
  • Patrick Diep
    University of Toronto
  • Sai Akhil Golla
    University of Toronto
  • Alexander F Yakunin
    University of Toronto
  • Radhakrishnan Mahadevan
    University of Toronto

BACKGROUND: Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for high-throughput laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste.

RESULTS: In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies-an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. We also propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding (t-SNE) in conjunction with our phenotyping platform to effectively cluster similarly performing strains at the bioreactor scale.

CONCLUSIONS: Fixed-tip liquid handling systems can significantly reduce the amount of plastic waste generated in biological laboratories and our decontamination and calibration protocols could facilitate the widespread adoption of such systems. Further, the use of t-SNE in conjunction with our automation platform could serve as an effective scale-down model for bioreactor fermentations. Finally, by integrating an in-house data-analysis pipeline, we were able to accelerate the 'test' phase of the design-build-test-learn cycle of metabolic engineering.

Keywords

  • Anaerobiosis, Automation, Laboratory/methods, Escherichia coli/genetics, Fermentation, High-Throughput Screening Assays/instrumentation, Metabolic Engineering/instrumentation
Original languageEnglish
Pages (from-to)184
JournalMicrobial cell factories
Volume20
Issue number1
DOIs
Publication statusPublished - 23 Sept 2021
Externally publishedYes
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