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The elaborate route for UDP-arabinose delivery into the Golgi of plants.

Carsten RautengartenDevon BirdseyeSivakumar PattathilHeather E McFarlaneSusana Saez-AguayoAriel OrellanaStaffan PerssonMichael G HahnHenrik V SchellerJoshua L HeazlewoodBerit Ebert
Published in: Proceedings of the National Academy of Sciences of the United States of America (2017)
In plants, L-arabinose (Ara) is a key component of cell wall polymers, glycoproteins, as well as flavonoids, and signaling peptides. Whereas the majority of Ara found in plant glycans occurs as a furanose ring (Araf), the activated precursor has a pyranose ring configuration (UDP-Arap). The biosynthesis of UDP-Arap mainly occurs via the epimerization of UDP-xylose (UDP-Xyl) in the Golgi lumen. Given that the predominant Ara form found in plants is Araf, UDP-Arap must exit the Golgi to be interconverted into UDP-Araf by UDP-Ara mutases that are located outside on the cytosolic surface of the Golgi. Subsequently, UDP-Araf must be transported back into the lumen. This step is vital because glycosyltransferases, the enzymes mediating the glycosylation reactions, are located within the Golgi lumen, and UDP-Arap, synthesized within the Golgi, is not their preferred substrate. Thus, the transport of UDP-Araf into the Golgi is a prerequisite. Although this step is critical for cell wall biosynthesis and the glycosylation of proteins and signaling peptides, the identification of these transporters has remained elusive. In this study, we present data demonstrating the identification and characterization of a family of Golgi-localized UDP-Araf transporters in Arabidopsis The application of a proteoliposome-based transport assay revealed that four members of the nucleotide sugar transporter (NST) family can efficiently transport UDP-Araf in vitro. Subsequent analysis of mutant lines affected in the function of these NSTs confirmed their role as UDP-Araf transporters in vivo.
Keyphrases
  • cell wall
  • endoplasmic reticulum
  • high throughput
  • electronic health record
  • big data
  • bioinformatics analysis