De novo synthesis of large-scale metabolic pathways for natural products and their optimization strategies.

Engineered strains as living factories: efficient biosynthesis and modification of natural products via synthetic biology and one-pot chemical tandem reactions

This review addresses the central question of how biosynthetic precision and chemical diversification can be coupled when conventional metabolic engineering alone cannot fully overcome low titers, enzyme promiscuity limits, intermediate toxicity, and scale-up heterogeneity.

Research Progress on Plant Metabolic Pathway Reconstruction Strategies Integrating Gene Editing and Synthetic Biology and Their Application in High-Value Product Synthesis

With the growing demand for green chemicals, biological products and sustainable manufacturing, plant metabolic engineering has gradually become a vital direction for the development of high-value natural products. Plants possess photosynthetic autotrophic capacity, complex organelle structures and abundant endogenous metabolic networks, enabling them to synthesize and accumulate a variety of medicinal natural products, pigments and aromatic compounds. However, plant metabolic pathways are highly complex, characterized by pathway crosstalk, feedback regulation, compartmentalized distribution, isozyme redundancy and tissue specificity, which pose challenges to the targeted synthesis and yield improvement of target products. In recent years, the development of synthetic biology and gene editing technologies has provided new solutions for plant metabolic reconstruction. The combined optimization of modular elements and the CRISPR/Cas gene editing system can regulate the expression of target genes, improve the spatial distribution of enzymes, promote the transport of substrates and products, and reduce the shunting of metabolic flux by competitive pathways. Different chassis platforms such as tobacco, Arabidopsis thaliana , tomato, maize and plant cell suspension culture systems also provide diverse options for metabolic pathway analysis, functional verification and high-value product production. In the future, combined with multi-omics analysis, metabolic modeling, AI-aided design and systematic regulation strategies, plant metabolic engineering is expected to further break through limitations such as flux bottlenecks, unstable expression and product toxicity, and play a greater role in green manufacturing, biomedicine and bioeconomic development.

Metabolic engineering strategies: utilizing different microbial strains and advanced technologies for the synthesis of high-valued terpenoids

Artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools for metabolic engineering by enabling pathway prediction, metabolic flux optimization, enzyme engineering, and identification of bottlenecks throughout terpenoid biosynthesis.

Advancing recombinant protein production in CHO cells through metabolic engineering

Chinese hamster ovary (CHO) cells serve as the predominant platform for producing recombinant therapeutic proteins in biopharmaceutical manufacturing, the production capacity of which relies heavily on efficient protein synthesis, folding, and secretion pathways. However, during high-density and prolonged cultivation, these cells frequently encounter bottlenecks—including excessive lactate and ammonia accumulation, redox imbalance, and endoplasmic reticulum (ER) stress—which ultimately constrain both the yield and quality of target protein. To overcome these limitations, metabolic engineering has emerged as a key strategy; through systematic modification of the CHO cellular metabolic network, it enhances recombinant protein yield, optimizes critical product qualities such as glycosylation, and improves overall process robustness. This review summarizes recent advances in CHO cell metabolic engineering, encompassing the regulation of central metabolic pathways, glycosylation engineering, cell cycle and metabolic reprogramming, culture condition optimization, byproduct accumulation control, and the application of systems biology and artificial intelligence technologies, including genome-scale metabolic modeling, machine learning-guided target prediction, and dynamic process control. These advances have significantly reduced biopharmaceutical production costs, improved scalability, and shortened time-to-market for monoclonal antibodies and other complex biologics. As the field transitions from single-gene manipulation toward multi-target, dynamic, and system-level rational design, metabolic engineering is advancing CHO cells into more efficient and intelligent “cell factories”, thereby providing sustained momentum for the industrial production of biologics.

Application and progress of synthetic biology technology in amino acid production

Recent Advances in Engineering Microbial Cell Factories for Tryptophan-Derived Chemicals.

Tryptophan-derived metabolites are indole-containing compounds with applications in medicine, functional foods, and agriculture. Conventional production via plant extraction or chemical synthesis is often inefficient and unsustainable, prompting the development of microbial biosynthesis. In this review, these metabolites are classified based on reaction sites and the extent of l-tryptophan scaffold remodeling into side-chain-modified compounds, indole ring-functionalized compounds, oxidative coupling products, and complex indole alkaloids, providing a framework to compare biosynthetic logic across pathways. Within this context, recent advances in metabolic engineering focus on improving catalytic performance, pathway balance, and cellular robustness through enzyme engineering combined with high-throughput screening, advanced genetic tools and dynamic regulatory systems, and cellular engineering strategies such as coculture design and membrane or transporter engineering. These developments provide a basis for further integration of artificial intelligence, computational design, and bioprocess optimization to enhance the efficiency and scalability of microbial production.