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A Customizable Approach for the Enzymatic Production and Purification of Diterpenoid Natural Products
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AI to enable plant cell metabolic engineering.

Robert G Sears1, Scott C Lenaghan2, C Neal Stewart1

  • 1Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, USA; Center for Agricultural Synthetic Biology, The University of Tennessee, Knoxville, Knoxville, TN, USA.

Trends in Plant Science
|October 1, 2023
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Summary

Artificial intelligence can analyze diverse plant cells for metabolic engineering. This approach accelerates the development of plant metabolic engineering strategies by accounting for unequal cell contributions.

Keywords:
artificial intelligencebioproductscell and tissue-typingmetabolic engineering

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Area of Science:

  • Plant Biology
  • Metabolic Engineering
  • Biotechnology

Background:

  • Metabolite production in plants involves heterogeneous cell types with varying contributions.
  • Current metabolic engineering strategies often overlook cellular heterogeneity.
  • Understanding cell-specific roles is crucial for optimizing metabolite yields.

Purpose of the Study:

  • To explore the application of artificial intelligence (AI) for plant cell characterization.
  • To accelerate the development of plant metabolic engineering strategies.
  • To address the challenge of cellular heterogeneity in metabolite production.

Main Methods:

  • Leveraging AI algorithms originally developed for biomedical applications.
  • Applying AI to characterize diverse plant cell types involved in metabolite synthesis.
  • Analyzing cell-specific data to understand differential metabolite production.

Main Results:

  • AI demonstrates potential for accurate plant cell characterization.
  • The approach can identify and quantify cell-type-specific metabolic activities.
  • AI facilitates a more nuanced understanding of metabolite production pathways.

Conclusions:

  • Artificial intelligence offers a powerful tool for plant cell characterization in metabolic engineering.
  • AI-driven analysis can overcome limitations posed by cellular heterogeneity.
  • This interdisciplinary approach promises to accelerate the design of improved plant metabolic engineering strategies.