Unlocking the potential of flavonoid biosynthesis through integrated metabolic engineering

Abstract

Flavonoids are a diverse class of plant polyphenols with essential roles in development, defense, and environmental adaptation, as well as significant applications in medicine, nutrition, and cosmetics. However, their naturally low abundance in plant tissues poses a major barrier to large-scale utilization. This review provides a comprehensive and forward-looking synthesis of flavonoid biosynthesis, regulation, transport, and yield enhancement strategies. We highlight key advances in understanding transcriptional and epigenetic control of flavonoid pathways, focusing on the roles of MYB, bHLH, and WD40 transcription factors and chromatin modifications. We also examine flavonoid transport mechanisms at cellular and tissue levels, supported by emerging spatial metabolomics data. Distinct from conventional reviews, this review explores how plant cell factories, genome editing, environmental optimization, and artificial intelligence (AI)-driven metabolic engineering can be integrated to boost flavonoid production. By bridging foundational plant science with synthetic biology and digital tools, this review outlines a novel roadmap for sustainable, high-yield flavonoid production with broad relevance to both research and industry.

Keywords: artificial intelligence; flavonoid biosynthesis; metabolic engineering; plant cell factory; transcriptional regulation.

Figure 1

Biosynthesis, transport, and regulation of flavonoid compounds. (A) Flavonoids, derived from phenylpropane, are synthesized by various enzymes and transported to the vacuole via the endoplasmic reticulum or Golgi apparatus. (B) Other regulatory methods include the MWB complex binding to target genes, direct regulation by inducers, and gene editing technology for knockout, knock-in, and fine-tuning of gene expression. (C) DNA methylation influences flavonoid synthesis by regulating gene expression. Increased methylation inhibits, while demethylation enhances gene expression. (D) Histone modification, including acetylation and methylation, can also regulate gene expression. (E) siRNA, formed by Dicer cutting double-stranded RNA, binds to the AGO protein and degrades the mRNA of the target gene, thus reducing gene expression.

Figure 2

Production of flavonoids using a plant cell factory. ① Seedling growth: Sterile seeds are planted in a culture medium to grow and obtain sterile seedlings. ② Tissue selection: Suitable tissues are selected from the sterile seedlings to serve as explants. ③ Callus induction: The explants are induced appropriately to form callus tissue. ④ Cell line selection: From a large amount of callus tissue, cell lines that can produce the target compound in large quantities are selected. ⑤ Suspension culture: The selected cell line is cultured in suspension to determine the optimal growth conditions for the cell line. ⑥ Scale-up validation: Pilot-scale bioreactor runs (10 L) confirm stable flavonoid productivity. ⑦ Large-Scale production: The target cell line is produced in large quantities using a fermenter to obtain a large amount of the target compound. ⑧ Separation and purification: The products of the cells after fermentation are separated and purified. ⑨ Commercialization: The obtained target product can finally be applied in medicine, food, and cosmetics.

Figure 3

The potential role of artificial intelligence (AI) in promoting the biogenesis of flavonoids (A) AI enhances flavonoid production by modifying key elements of flavonoid biosynthesis. By altering the expression of genes related to flavonoid metabolism through AI design, adjusting the growth environment of plants or cells, redirecting plant metabolic flow, and editing target genes using CRISPR technology, the physiological state of plants can be optimized to produce target flavonoid metabolites under ideal conditions. (B) Briefly explain how artificial intelligence can promote flavonoid biosynthesis in three elements. (1) Expression of Core Genes: AI can modulate the expression of structural genes and regulatory factors involved in flavonoid synthesis, such as the PAL gene and various transcription factors (TFs). (2) Growth Conditions: AI can optimize growth conditions, including light intensity, temperature, and other environmental factors, to enhance flavonoid production. (3) Metabolic Flow Direction: AI can influence the direction of metabolic flow by increasing the rate of primary metabolite conversion to target flavonoids and reducing the production of other secondary metabolites.