Aconitum kusnezoffii is a perennial herbaceous medicinal plant of the family Ranunculaceae, with unique medicinal value. Damping off is one of the most important seedling diseases affecting A. kusnezoffii, occurring widely and often causing large-scale seedling death in the field. To clarify the species of the pathogen causing damping off in A. kusnezoffii and to formulate an effective control strategy, this study conducted pathogen identification, research on biological characteristics, and evaluation of fungicide inhibitory activity. Through morphological characteristics, cultural traits, and phylogenetic tree analysis, the pathogen causing damping off in A. kusnezoffii was identified as Rhizoctonia solani, belonging to the AG5 anastomosis group. The optimal temperature for mycelial growth of the pathogen was 25-30 ℃, with OA medium as the most suitable medium, pH 8 as the optimal pH, and sucrose and yeast as the best carbon and nitrogen sources, respectively. The effect of light on mycelial growth was not significant. In evaluating the inhibitory activity of 45 chemical fungicides, including 30% hymexazol, and 4 biogenic fungicides, including 0.3% eugenol, it was found that 30% thifluzamide and 50% fludioxonil had significantly better inhibitory effects on R. solani than other tested agents, with EC_(50) values of 0.129 6,0.220 6 μg·mL~(-1), respectively. Among the biogenic fungicides, 0.3% eugenol also showed an ideal inhibitory effect on the pathogen, with an EC_(50) of 1.668 9 μg·mL~(-1). To prevent the development of resistance in the pathogen and to reduce the use of chemical fungicides, it is recommended that the three fungicides above be used in rotation during production. These findings provide a theoretical basis for the accurate diagnosis and effective control strategy for R. solani causing damping off in A. kusnezoffii.
Fungicides, Industrial/pharmacology* ; Plant Diseases/microbiology* ; Rhizoctonia/growth & development* ; Aconitum/microbiology* ; Phylogeny ; Mycelium/growth & development*

In this study, Saccharomyces cerevisiae R0 was used as the chassis cell to synthesize oleanolic acid from scratch through the heterologous expression of β-amyrin synthase(β-AS) from Glycyrrhiza uralensis, cytochrome P450 enzyme CYP716A154 from Catharanthus roseus, and cytochrome P450 reductase AtCPR from Arabidopsis thaliana. The engineered strain R1 achieved shake flask titres of 5.19 mg·L~(-1). By overexpressing enzymes in the pentose phosphate pathway(PPP)(ZWF1, GND1, TKL1, and TAL), the NADH kinase gene in the mitochondrial matrix(POS5), truncated 3-hydroxy-3-methylglutaryl-CoA reductase(tPgHMGR1) from Panax ginseng, and farnesyl diphosphate synthase gene(SmFPS) from Salvia miltiorrhiza, the precursor supply and intracellular reduced nicotinamide adenine dinucleotide phosphate(NADPH) supply were enhanced, resulting in an 11.4-fold increase in squalene yield and a 3.6-fold increase in oleanolic acid yield. Subsequently, increasing the copy number of the heterologous genes tPgHMGR1, β-AS, CYP716A154, and AtCPR promoted the metabolic flow towards the final product, oleanolic acid, and increased the yield by three times. Shake flask fermentation data showed that, by increasing the copy number, precursor supply, and intracellular NADPH supply, the final engineered strain R3 could achieve an oleanolic acid yield of 53.96 mg·L~(-1), which was 10 times higher than that of the control strain R1. This study not only laid the foundation for the green biosynthesis of oleanolic acid but also provided a reference for metabolic engineering research on other pentacyclic triterpenoids in S. cerevisiae.
Oleanolic Acid/biosynthesis* ; Saccharomyces cerevisiae/metabolism* ; Industrial Microbiology ; Microorganisms, Genetically-Modified/metabolism* ; Plants/enzymology* ; Fermentation ; Metabolic Engineering

Two novel skeleton sesquiterpenoids (1 and 6), along with four new iphionane-type sesquiterpenes (2-5) and six new cyperane-type sesquiterpenes (7-11), were isolated from the whole plant of Artemisia hedinii (A. hedinii). The two novel skeleton compounds (1 and 6) were derived from the decarbonization of iphionane and cyperane-type sesquiterpenes, respectively. Their structures were elucidated through a comprehensive analysis of spectroscopic data, including high-resolution electrospray ionization mass spectrometry (HR-ESI-MS) and 1D and 2D nuclear magnetic resonance (NMR) spectra. The absolute configurations were determined using electronic circular dichroism (ECD) spectra, single-crystal X-ray crystallographic analyses, time-dependent density functional theory (TDDFT) ECD calculation, density functional theory (DFT) NMR calculations, and biomimetic syntheses. The biomimetic syntheses of the two novel skeletons (1 and 6) were inspired by potential biogenetic pathways, utilizing a predominant eudesmane-type sesquiterpene (A) in A. hedinii as the substrate. All compounds were evaluated in LX-2 cells for their anti-hepatic fibrosis activity. Compounds 2, 8, and 10 exhibited significant activity in downregulating the expression of α-smooth muscle actin (α-SMA), a protein involved in hepatic fibrosis.
Artemisia/chemistry* ; Sesquiterpenes/chemical synthesis* ; Molecular Structure ; Humans ; Liver Cirrhosis/genetics* ; Biomimetics ; Plant Extracts/pharmacology*

This article reviews the review articles and research papers related to biomanufacturing driven by engineered organisms published in the Chinese Journal of Biotechnology from 2023 to 2024. The content covers 26 aspects, including chassis cells; gene (genome) editing; facilities, tools and methods; biosensors; protein design and engineering; peptides and proteins; screening, expression, characterization and modification of enzymes; biocatalysis; bioactive substances; plant natural products; microbial natural products; development of microbial resources and biopesticides; steroidal compounds; amino acids and their derivatives; vitamins and their derivatives; nucleosides; sugars, sugar alcohols, oligosaccharides, polysaccharides and glycolipids; organic acids and monomers of bio-based materials; biodegradation of polymeric materials and biodegradable materials; intestinal microorganisms, live bacterial drugs and synthetic microbiomes; microbial stress resistance engineering; biodegradation and conversion utilization of lignocellulose; C1 biotechnology; bioelectron transfer and biooxidation-reduction; biotechnological environmental protection; risks and regulation of biomanufacturing driven by engineered organisms, with hundreds of technologies and products commented. It is expected to provide a reference for readers to understand the latest progress in research, development and commercialization related to biomanufacturing driven by engineered organisms.
Biotechnology/methods* ; Gene Editing ; Genetic Engineering ; Metabolic Engineering ; Protein Engineering ; Biosensing Techniques

The efficient production of L-glutamate is dependent on the product's rapid efflux, hence researchers have recently concentrated on artificially modifying its transport system and cell membrane wall structure. Considering the unique composition and structure of the cell wall of Corynebacterium glutamicum, we investigated the effects of CmpLs on L-glutamate synthesis and transport in SCgGC7, a constitutive L-glutamate efflux strain. First, the knockout strains of CmpLs were constructed, and it was confirmed that the deletion of CmpL1 and CmpL4 significantly improved the performance of L-glutamate producers. Next, temperature-sensitive L-glutamate fermentation with the CmpL1 and CmpL4 knockout strains were carried out in 5 L bioreactors, where the knockout strains showcased temperature-sensitive characteristics and enhanced capacities for L-glutamate production under high temperatures. Notably, the CmpL1 knockout strain outperformed the control strain in terms of L-glutamate production, showing production and yield increases of 69.2% and 55.3%, respectively. Finally, the intracellular and extracellular metabolites collected at the end of the fermentation process were analyzed. The modification of CmpLs greatly improved the L-glutamate excretion and metabolic flux for both L-glutamate production and transport. Additionally, the CmpL1 knockout strain showed decreased accumulation of downstream metabolites of L-glutamate and intermediate metabolites of tricarboxylic acid (TCA) cycle, which were consistent with its high L-glutamate biosynthesis capacity. In addition to offering an ideal target for improving the stability and performance of the industrial strains for L-glutamate production, the functional complementarity and redundancy of CmpLs provide a novel target and method for improving the transport of other metabolites by modification of the cell membrane and cell wall structures in C. glutamicum.
Corynebacterium glutamicum/genetics* ; Glutamic Acid/biosynthesis* ; Fermentation ; Metabolic Engineering ; Bacterial Proteins/metabolism* ; Bioreactors/microbiology* ; Gene Knockout Techniques

Biomanufacturing is an advanced manufacturing method that integrates biology, chemistry, and engineering. It utilizes renewable biomass and biological organisms as production media to scale up the production of target products through fermentation. Compared with petrochemical routes, biomanufacturing offers significant advantages in reducing CO₂ emissions, lowering energy consumption, and cutting costs. With the development of systems biology and synthetic biology and the accumulation of bioinformatics data, the integration of information technologies such as artificial intelligence, large models, and high-performance computing with biotechnology is propelling biomanufacturing into a data-driven era. This paper reviews the latest research progress on databases, knowledge bases, and large language models for biomanufacturing. It explores the development directions, challenges, and emerging technical methods in this field, aiming to provide guidance and inspiration for scientific research in related areas.
Biotechnology/methods* ; Knowledge Bases ; Synthetic Biology ; Databases, Factual ; Artificial Intelligence ; Systems Biology ; Computational Biology ; Fermentation

Nucleic acid elements are essential functional sequences that play critical roles in regulating gene expression, optimizing pathways, and enabling gene editing to enhance the production of target products in biomanufacturing. Therefore, the design and optimization of these elements are crucial in constructing efficient cell factories. Artificial intelligence (AI) provides robust support for biomanufacturing by accurately predicting functional nucleic acid elements, designing and optimizing sequences with quantified functions, and elucidating the operating mechanisms of these elements. In recent years, AI has significantly accelerated the progress in biomanufacturing by reducing experimental workloads through the design and optimization of promoters, ribosome-binding sites, terminators, and their combinations. Despite these advancements, the application of AI in biomanufacturing remains limited due to the complexity of biological systems and the lack of highly quantified training data. This review summarizes the various nucleic acid elements utilized in biomanufacturing, the tools developed for predicting and designing these elements based on AI algorithms, and the case studies showcasing the applications of AI in biomanufacturing. By integrating AI with synthetic biology and high-throughput techniques, we anticipate the development of more efficient tools for designing nucleic acid elements and accelerating the application of AI in biomanufacturing.
Artificial Intelligence ; Synthetic Biology ; Nucleic Acids/genetics* ; Algorithms ; Gene Editing ; Promoter Regions, Genetic ; Biotechnology/methods*

Energy metabolism regulation plays a pivotal role in metabolic engineering. It mainly achieves the balance of material and energy metabolism or maximizes the utilization of materials and energy by regulating the supply intensity and mode of ATP and reducing electron carriers in cells. On the one hand, the production efficiency can be increased by changing the distribution of material metabolic flow. On the other hand, the thermodynamic parameters of enzyme-catalyzed reactions can be altered to affect the reaction balance, and thus the production costs are reduced. Therefore, energy metabolism regulation is expected to become a favorable tool for the modification of microbial cell factories, thereby increasing the production of target metabolites and reducing production costs. This article introduces the commonly used energy metabolism regulation methods and their effects on cell factories, aiming to provide a reference for the efficient construction of microbial cell factories.
Energy Metabolism/physiology* ; Metabolic Engineering/methods* ; Adenosine Triphosphate/metabolism* ; Industrial Microbiology/methods*

Biomanufacturing has emerged as a crucial driving force for efficient material conversion through engineered cells or cell-free systems. However, the intrinsic spatiotemporal heterogeneity, complexity, and dynamic characteristics of these processes pose significant challenges to systematic understanding, optimization, and regulation. This review summarizes essential methodologies for multi-omics data acquisition and analyses for bioprocesses and outlines modelling approaches based on multi-omics data. Furthermore, we explore practical applications of multi-omics and modelling in fine-tuning process parameters, improving fermentation control, elucidating stress response mechanisms, optimizing nutrient supplementation, and enabling real-time monitoring and adaptive adjustment. The substantial potential offered by integrating multi-omics with computational modelling for precision bioprocessing is also discussed. Finally, we identify current challenges in bioprocess optimization and propose the possible solutions, the implementation of which will significantly deepen understanding and enhance control of complex bioprocesses, ultimately driving the rapid advancement of biomanufacturing.
Fermentation ; Genomics/methods* ; Biotechnology/methods* ; Proteomics/methods* ; Models, Biological ; Metabolomics/methods* ; Bioreactors ; Multiomics

As a strategic emerging industry, biomanufacturing faces core challenges in achieving precise optimization and efficient scale-up of fermentation processes. This review focuses on two critical aspects of fermentation-real-time sensing and intelligent control-and systematically summarizes the advancements in online monitoring technologies, artificial intelligence (AI)-driven optimization strategies, and digital twin applications. First, online monitoring technologies, ranging from conventional parameters (e.g., temperature, pH, and dissolved oxygen) to advanced sensing systems (e.g., online viable cell sensors, spectroscopy, and exhaust gas analysis), provide a data foundation for real-time microbial metabolic state characterization. Second, conventional static control relying on expert experience is evolving toward AI-driven dynamic optimization. The integration of machine learning technologies (e.g., artificial neural networks and support vector machines) and genetic algorithms significantly enhances the regulation efficiency of feeding strategies and process parameters. Finally, digital twin technology, integrating real-time sensing data with multi-scale models (e.g., cellular metabolic kinetics and reactor hydrodynamics), offers a novel paradigm for lifecycle optimization and rational scale-up of fermentation. Future advancements in closed-loop control systems based on intelligent sensing and digital twin are expected to accelerate the industrialization of innovative achievements in synthetic biology and drive biomanufacturing toward higher efficiency, intelligence, and sustainability.
Artificial Intelligence ; Fermentation ; Bioreactors/microbiology* ; Neural Networks, Computer ; Algorithms ; Biotechnology/methods*