# Towards a Holistic View of the Orchestration Between Sugar Transporters in Cereal Crops

## TL;DR

This paper explores how sugar transporters in cereal crops work together, using new AI and omics tools to improve crop yields.

## Contribution

The paper highlights how AI-enabled protein analysis and multi-omics can revolutionize understanding sugar transporter orchestration in crops.

## Key findings

- Sugar transporters like SWEET and STP show conserved substrate specificity and transport direction.
- AI and multi-omics technologies offer new ways to study sugar transporter coordination in plants.
- Integrating functional knowledge with AI and omics can enhance crop development and yield.

## Abstract

Soluble sugars are the key photo-assimilates in higher plants, playing critical roles in growth, development, and stress regulation. The transport of sugars in plants involves the coordinated action between several sugar transporter families, including the SUT, STP, pGlcT, VGT, TMT, INT, PLT, SFP, and SWEET families. Over recent decades, numerous studies have elucidated the molecular functions of major sugar transporters. Phylogenetic and evolutionary analyses support the conservation of substrate specificity and transport direction, at least to some extent. Structural analyses have provided key insights into the structural–function relationships of important transporters (e.g., OsSWEET2b and AtSTP10), which can be effectively leveraged for artificial intelligence (AI)-enabled protein structure prediction and rational design. Advances in omics technologies now enable low-cost, routine transcriptome profiling and cutting-edge techniques (e.g., single-cell multi-omics and spatiotemporal RNA-seq), providing unprecedented ways to understand how sugar transporters function coordinately at multiple levels. Here, we describe the classification of major sugar transporters in plants and summarize established functional knowledge. We emphasize that recent groundbreaking advances in AI-enabled protein analyses and multi-omics will revolutionize molecular physiology in crops. Specifically, the integration of functional knowledge, AI-based protein analyses, and multi-omics will help unravel the orchestration of different sugar transporters, thereby enhancing our understanding of how sugar transportation and source–sink interactions contribute to crop development, yield formation, and beyond, ultimately boosting carbohydrate transport- related crop improvement.