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The transport of solutes across the cell membrane is essential for metabolic processes, like maintaining cell size and volume, generating the action potential, exchanging nutrients and gases, etc. Membrane transport can be either passive or active. It can be simple diffusion, facilitated, or mediated transport aided by transport proteins such as transporters and channels.
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Author Spotlight: Expression and Purification of Human Solute Carrier Transporters Using Codon-Optimized Genes
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TranSyT, an innovative framework for identifying transport systems.

Emanuel Cunha1, Davide Lagoa1,2, José P Faria2

  • 1Centre of Biological Engineering, University of Minho, Braga 4704-553, Portugal.

Bioinformatics (Oxford, England)
|August 17, 2023
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Summary

Transport Systems Tracker (TranSyT) automates the integration of transport reactions into metabolic models. This new software enhances genome-scale metabolic model development by providing curated transporter data without manual input.

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Area of Science:

  • Metabolic Engineering
  • Bioinformatics

Background:

  • Genome-scale metabolic models are crucial for understanding cellular metabolism.
  • Automating the integration of transport reactions is essential for efficient model development.
  • Current software solutions for transport system annotation have limitations, particularly regarding manual curation.

Purpose of the Study:

  • To present Transport Systems Tracker (TranSyT), a novel software for the automatic integration of transport reactions into metabolic models.
  • To provide a solution that overcomes the limitations of existing tools by eliminating the need for manual curation.

Main Methods:

  • TranSyT utilizes curated records from the Transporters Classification Database and other data sources to build an internal database.
  • The software compiles information on transporter families and proteins to derive transport reactions.
  • It generates Gene-Protein-Reaction (GPR) associations for all transport reactions.

Main Results:

  • TranSyT enables rapid annotation of transport systems for complete genomes.
  • The tool's internal database is derived from curated records, reducing reliance on manual input.
  • Transport reactions can be exported with identifiers from four different metabolite databases.

Conclusions:

  • TranSyT offers an automated and efficient solution for integrating transport reactions into metabolic models.
  • The software streamlines the development of genome-scale metabolic models.
  • TranSyT is available as a plugin for merlin v4.0 and an app for KBase.