Engineered strains as living factories: efficient biosynthesis and modification of natural products via synthetic biology and one-pot chemical tandem reactions
Aug 2026· Frontiers in Microbiology· Vol 17· 0 citations· 79 references
TL;DR
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.
Abstract
Natural products are a crucial source for drug discovery, but their traditional development is limited by resource availability, efficiency, chemical complexity, and the difficulty of rapidly diversifying biologically active scaffolds. 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. We examine engineered strains as microbial living factories that construct stereochemically complex cores from renewable feedstocks, and one-pot chemical tandem reactions as complementary tools for post-biosynthetic functionalization, skeletal remodeling, and rapid analog generation. The review compares natural-product classes with distinct bottlenecks, analyzes mass-transfer and oxygen-limitation challenges during industrial translation, and explains domino, multicomponent, and sequential one-pot mechanisms for a microbiology-oriented readership. Recent advances in biocompatible catalysis, chemoenzymatic cascades, artificial metalloenzymes, photobiocatalysis, flow biocatalysis, and cell-free synthetic platforms are discussed as three integration paradigms: post-fermentation modification, one-pot chemoenzymatic coupling, and open cell-free manufacturing. Finally, the review outlines a roadmap for catalyst compatibility, process scale-up, regulatory assessment, and automated design-build-test-learn workflows to promote sustainable natural-product production and lead discovery.
Natural products constitute a vital source for drug discovery, yet extraction from producers is inefficient and chemical synthesis involves complex, low yield routes, limiting sustainable supply. Reconstructing large scale metabolic pathways (≥10 enzymatic steps) in microbial cell factories using synthetic biology offers a promising solution for efficient and sustainable production of high value natural products. This review systematically analyzes core strategies and cutting edge technologies for reconstructing such pathways, including advanced cloning methods, modular pathway design, self assembly approaches (protein/DNA scaffolds and metabolic channeling), division of labor optimization in co culture systems, and dynamic regulation mechanisms (promoter engineering, riboswitches, biosensor based feedback control). We further explore the emerging roles of systems biology modeling and machine learning in retrosynthetic pathway design, rational enzyme engineering, and precise metabolic flux regulation. By integrating intelligent algorithms with multidisciplinary tools, these approaches hold promise for overcoming bottlenecks in the biomanufacturing of complex natural products, thereby accelerating drug development and enabling green, sustainable production. This review highlights the importance of combining rational design, dynamic control, and modular co culture strategies to address challenges such as metabolic burden, pathway imbalance, and host toxicity, ultimately paving the way for scalable and cost effective biosynthesis of natural product pharmaceuticals.
Terpenoids are valuable resources for pharmaceutical research, yet their natural supply remains constrained. While the artificial isoprenol utilization pathway (IUP) has emerged as a promising alternative for terpene precursor supply, its full potential is limited by suboptimal pathway flux and substrate tolerance. Here, we report an efficient scaffold-assisted IUP platform tailored for high-throughput terpenoid discovery and scalable production. By recruiting rate-limiting IUP enzymes and prenyltransferases (PTs) onto self-assembling PduA* protein scaffolds displaying CC-Di-B peptides that specifically interact with CC-Di-A-tagged enzymes, we achieved spatial organization of the biosynthetic machinery. Systematic optimization of promoter configuration, fermentation conditions, and enzyme fusion yielded the optimal system ScMKI4-GS, achieving gram-per-liter-scale production (1.1 g/L) of the eunicellane-type diterpene benditerpe-2,6,15-triene in simple shake-flask fermentation-substantially outperforming scaffold-free controls. The platform demonstrated broad applicability across five structurally distinct eunicellane synthases, with each exhibiting enhanced production upon scaffold incorporation. For lycopene biosynthesis, the scaffold-assisted system produced 729.7 mg/L-a 9-fold improvement over the canonical MVA pathway under identical conditions, representing the highest IUP-based lycopene titer reported in Escherichia coli to date. Finally, by systematic substitution of chain-length-specific PTs, we expanded the platform to efficiently generate C10-C35 terpene precursors, facilitating functional characterization of terpene-related genes. Collectively, this versatile scaffold-assisted IUP platform provides a robust tool to expand terpenoid structural diversity and accelerate their scalable overproduction.
Achieving selective oxygenation chemistry offers a powerful strategy for streamlining routes to complex target molecules, yet the development of site-selective C-H functionalization reactions is challenging. Several enzyme families are capable of catalyzing C-H hydroxylation reactions and, in principle, provide an attractive solution for achieving selective oxidative transformations. In practice, however, the difficulty of identifying a biocatalyst suited to a specific synthetic target often renders chemoenzymatic strategies impractical. For example, biosynthetic enzymes such as CitB and ClaD can mediate site-selective benzylic hydroxylation, enabling access to select natural products that share structural features with their native substrates. Nonetheless, such approaches typically lack generality and do not readily extend to broader collections of natural products. Here, we explore the previously unstudied natural sequence space surrounding biosynthetic hydroxylases CitB and ClaD to generate a bespoke panel of uncharacterized enzymes that collectively expand the substrate scope of biocatalytic benzylic hydroxylation reactions. Development of this curated biocatalyst panel enabled the hydroxylation of a set of orcinaldehyde-like substrates, which were further elaborated to six natural products.
Gonzalo J Villegas Rodríguez, Evan O Romero, Jonathan C Perkins et al.· Angewandte Chemie· 0 citations
Terpenoids are a class of natural products widely distributed in living organisms, with isoprene as their fundamental structural unit. However, traditional plant extraction and chemical synthesis methods are often limited by low product purity, difficult separation, and complex synthetic steps, making it challenging to meet the demands of large-scale production. Conventional hosts such as Escherichia coli and Saccharomyces cerevisiae are utilized for terpenoid synthesis due to their advantages of short growth cycles and controllable cultivation conditions. Nevertheless, the complexity of terpenoid biosynthetic pathways poses significant challenges for these hosts in producing structurally complex terpenoids. In contrast, microalgae as photosynthetic microorganisms, possess well-developed endogenous terpenoid metabolic pathways, abundant precursor pools, and subcellular structures and regulatory mechanisms similar to those of plants, demonstrating significant advantages in the heterologous production of complex terpenoids. This review systematically summarizes recent advances in the production of heterologously synthesized terpenoids in eukaryotic microalgae, ranging from monoterpenes to triterpenes, and provides an in-depth analysis of key engineering strategies, including MEP/MVA pathway regulation, gene expression optimization, subcellular compartmentalization, and cultivation process intensification. In addition, the application potential of advanced tools such as CRISPR/Cas, microalgae-microorganism co-culture, and artificial intelligence is introduced. Finally, the major bottlenecks faced by microalgae as a sustainable green cell factory for terpenoid production are briefly analyzed, and future research directions are proposed.
Biotransformation plays a crucial role in addressing global challenges related to resource utilization and energy sustainability. Natural processes, such as photosynthesis and microbial metabolism, transform external resources into functional compounds. However, these processes are often constrained by inefficiencies, slow reaction rates, and limited product diversity. Recent advancements across the physical, chemical, and biological sciences have led to the convergence of natural and artificial strategies that effectively tackle these challenges. These developments, alongside progress in artificial photosynthesis, offer solutions for CO2 reduction, N2 fixation, and sustainable chemical production, thereby broadening the scope of biotransformation beyond traditional natural processes. Herein, we first introduce recent representative achievements in resolving the structures and catalytic mechanisms of proteins/protein complexes/enzymes involved in natural biotransformation processes. Our review then highlights natural photosynthesis-inspired organic-biological hybrid systems, focusing on the conversion of CO2 and N2 as well as the diverse range of value-added products they enable. Furthermore, this paper will explore the potential of artificial photosynthesis systems, examining their integration and applications in advancing biotransformation processes. Finally, we discuss key challenges and propose future strategies to advance research in this field. The ongoing advancements in artificial systems hold immense promise for revolutionizing and paving the way for a sustainable future that extends beyond natural biotransformation.
Haotian Bai, Yan Zhang, Xu‐Bing Li et al.· National Science Review· 0 citations
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.
Aakash Kamalesan, K. Kumar, Bharathi Nathan et al.· Antonie van Leeuwenhoek· 0 citations