Skip to content
Log in

Similar papers

Review Jul 2026

Advances in engineering microalgae for heterologous terpenoid synthesis: A review.

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.

Yue-Li Yuan, Jv-Liang Dai, Ling Xiao et al. · 0 citations
Review Jul 2026

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.

Aakash Kamalesan, K. Kumar, Bharathi Nathan et al. · 0 citations
Review Open access Aug 2026

Research progress on biosynthesis and regulation of monoterpenoid compounds

Monoterpenoids are an important class of plant volatile natural products with broad applications in the food, fragrance, pharmaceutical, and agricultural industries. However, their conventional production largely relies on plant extraction, which is often constrained by low efficiency, high cost, and limited sustainability. Structurally, monoterpenoids can be classified into acyclic, monocyclic, and bicyclic types, and their structural diversity is closely associated with differences in biosynthetic routes and regulatory mechanisms. Their biosynthesis depends on precursor supply from the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways, followed by terpene synthase (TPS)-mediated scaffold formation and subsequent modification reactions. In addition, monoterpenoid accumulation is regulated by multiple factors, including environmental cues, phytohormone signaling, transcriptional regulation, and epigenetic or post-transcriptional control. Meanwhile, substantial progress has been made in the heterologous production of monoterpenoids in microbial platforms such as Escherichia coli and Saccharomyces cerevisiae through metabolic engineering and synthetic biology. This review summarizes recent advances in monoterpenoid biosynthesis, multilevel regulation, and heterologous production, with particular emphasis on major bottlenecks and optimization strategies for sustainable and efficient biomanufacturing.

Jun-Chi Zhang, Jiale Cui, Shang Li et al. · 0 citations
Review Aug 2026

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Xin-Yue Li, Qi Wang, Hang-Ming Zhang et al. · 0 citations
Review Open access Jul 2026

A Review of Plant-Derived Diterpenoid Biosynthesis: From Structural Scaffold Diversity and Lineage-Associated Distribution to Enzyme Mining and Discovery Strategies

Plant diterpenoids are a diverse class of natural products with important ecological roles and wide applications in the pharmaceutical, agricultural, food additive, and chemical industries. Biosynthesis represents a primary strategy for accessing these valuable compounds. However, the identification of downstream tailoring enzymes (hereafter referred to as tailoring enzymes) involved in diterpenoid biosynthetic pathways remains a major bottleneck, particularly in non-model plant species with limited genomic resources. This review summarizes current strategies for discovering plant diterpenoid biosynthetic pathways and recent advances in elucidating their metabolic routes. We further highlight the lineage-biased distribution of diterpene scaffolds across plant taxa. We propose that scaffold enrichment in specific evolutionary lineages, when integrated with enzyme family expansion and functional divergence, may provide a complementary framework for prioritizing candidate tailoring enzymes. Importantly, scaffold enrichment alone cannot establish enzyme function or evolutionary causality; rather, it provides a complementary layer of evidence that can guide future experimental investigation. Future perspectives include predictive substrate–enzyme mapping, computational and generative design of cytochrome P450 enzymes, and the integration of enzyme discovery, structural modeling, and heterologous chassis engineering.

Yalan Zhao, Mengyao Li, Shasha Zuo et al. · 0 citations

Discovery of new natural products from Actinobacteria using Cas12a-directed cloning

Microbial natural products are the source of over 70% of all known antibiotics, yet the pace of their discovery has slowed significantly since its peak in the mid-20th century. This stagnation is largely due to the repeated isolation of known compounds from readily culturable microorganisms, while the vast majority of microbial biosynthetic gene clusters (BGCs) remain silent and unexpressed under typical laboratory conditions. The convergence of genomics, synthetic biology, and high resolution analytical chemistry now provides a powerful toolkit to unlock this cryptic biosynthetic potential. This thesis presents a strategy that integrates these disciplines to awaken silent BGCs and discover novel bioactive molecules. A genome mining approach was utilised to identify 22 promising BGCs from diverse actinobacteria, prioritised for their predicted novelty. To activate their expression, a suite of synthetic biology and molecular cloning strategies was implemented in both native and engineered heterologous hosts. This systematic activation campaign yielded several significant outcomes: (i) the linking of three known compounds to their previously unknown BGCs; and (ii) the discovery and structural elucidation of two novel natural products. Notably, one of the compounds represents a new class of calcium-dependent antibiotics with potent antimicrobial activity. In conclusion, this research demonstrates the efficacy of a genome-led approach to drug discovery. It has successfully translated genomic data into tangible chemical matter, functionally characterised previously cryptic BGCs, and contributed a novel class of antibiotics to the global pipeline for combating infectious diseases.

Jing Da · 0 citations