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An automated DIY framework for experimental evolution of Pseudomonas putida.

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We developed a DIY automated system for adaptive laboratory evolution (ALE) in Pseudomonas putida. This system successfully selected for faster D-xylose metabolism by identifying key genomic changes.

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Area of Science:

  • Microbiology
  • Metabolic Engineering
  • Synthetic Biology

Background:

  • Adaptive laboratory evolution (ALE) is crucial for optimizing microbial strains.
  • Tailoring ALE conditions to specific microorganisms like Pseudomonas putida is essential.
  • Existing methods may lack flexibility and automation for long-term experiments.

Purpose of the Study:

  • To create a flexible, automated, do-it-yourself (DIY) framework for ALE.
  • To optimize Pseudomonas putida for enhanced metabolic capabilities.
  • To investigate genomic adaptations during ALE.

Main Methods:

  • Implemented a dual-chamber semi-continuous log-phase bioreactor.
  • Incorporated an anti-biofilm layout for long-term cultivation.
  • Utilized an automated 42-day iterative regrowth protocol.

Main Results:

  • Successfully selected for fast-growing P. putida variants.
  • Engineered strain efficiently metabolized D-xylose as a sole carbon source.
  • Identified genomic changes, particularly involving RNA polymerase.

Conclusions:

  • The DIY ALE framework is effective for Pseudomonas putida.
  • The system facilitates the selection of improved metabolic phenotypes.
  • RNA polymerase plays a significant role in adapting to new carbon sources.