Aug 2026· Frontiers in Bioengineering and Biotechnology· Vol 14· 0 citations· 130 references
Medicine
Abstract
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.
Chinese hamster ovary (CHO) cells represent the dominant host system for the production of recombinant therapeutic proteins. In recent decades, extensive research has focused on process/media optimization and cell line engineering to improve both the productivity and quality of biopharmaceutical proteins produced in CHO cells. Nevertheless, the inherent complexity of biological pathways and the heterogeneous cellular responses to different environmental conditions have posed substantial challenges to traditional methodologies. Recent advances in omics technologies have enabled comprehensive characterization of CHO cell physiology, providing multidimensional molecular and phenotypic insights that facilitate the enhancement of recombinant protein production. This review first summarizes the methodologies and advances in CHO omics research, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics. It then examines contemporary approaches to integrate and analyze multi-omics data in CHO cells. The review further elucidates how these multi-omics datasets can be strategically applied across various developmental stages, including cell line selection, genetic engineering, expression vector design, and bioprocess optimization. Finally, we explore the transformative potential of integrating multi-omics with artificial intelligence and discuss promising future research directions in CHO cell studies. These emerging paradigms offer novel opportunities for data-driven cell engineering and bioprocess optimization in CHO-based biomanufacturing.
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This review summarizes recent advances in engineering key expression elements underlying heterologous protein production in K. phaffii, with particular emphasis on promoter architecture redesign, signal peptide replacement and sequence engineering, molecular chaperone co-expression, and quantitative regulation of the unfolded protein response.
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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.
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This review systematically summarizes the full technological chain for efficient and high-quality mAb production, focusing on three levels: cell line construction, culture medium development, and process regulation in bioreactors, and highlights their key strategies, mechanisms, and synergistic relationships.
Unknown authors· Chem & Bio Engineering· 0 citations
A multilevel engineering strategy to enhance yeast protein production by optimizing precursor supply, translation machinery, and diploid construction provides both improved protein content and key targets for breeding high-protein microbial strains.
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