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Trade-offs in engineering sugar utilization pathways for titratable control.

Taliman Afroz1, Konstantinos Biliouris, Kelsey E Boykin

  • 1Department of Chemical and Biomolecular Engineering North Carolina State University Raleigh, North Carolina 27695, United States.

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Summary
This summary is machine-generated.

Modifying sugar utilization pathways in microbes can improve gene expression control. Constitutively expressing a high-affinity transporter offers a simple way to achieve uniform and linear gene induction for metabolic engineering.

Keywords:
Escherichia colicarbon catabolismfeedbackinducible systemslinearizationsystems biology

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Area of Science:

  • Microbiology
  • Metabolic Engineering
  • Synthetic Biology

Background:

  • Titratable systems are crucial for metabolic engineering, often utilizing inducible sugar utilization pathways in microorganisms.
  • These pathways can display problematic single-cell variations, hindering precise gene expression control.

Purpose of the Study:

  • To investigate how altering sugar utilization pathways impacts inducible gene expression control in microorganisms.
  • To identify design principles for optimizing these pathways for metabolic engineering applications.

Main Methods:

  • Mathematical modeling and single-cell measurements were employed using L-arabinose utilization in Escherichia coli.
  • Various pathway modifications were tested, including catabolism removal, altered transporter expression, and transporter deletions.

Main Results:

  • Pathway alterations present specific trade-offs; for example, removing catabolism improves response uniformity but requires higher inducer concentrations.
  • Constitutive expression of a high-affinity transporter alone can achieve uniform and linear gene expression control.
  • Similar results were observed with the D-xylose utilization pathway, indicating broad applicability.

Conclusions:

  • There is no universal optimal alteration for co-opting natural sugar pathways for titratable control.
  • Design rules for pathway manipulation can advance genetic studies and microbial metabolic engineering for chemical production.