Using synthetic biology methods allows for the more efficient production of highly complex drug molecules compared to traditional chemical methods, with increased stability and controllability. Many drug components are currently produced using expensive and unstable manufacturing methods, such as cultivating medicinal plants, leading to frequent drug shortages. By utilizing highly engineered microorganisms for microbial fermentation, the production of drug components involves multiple complex heterologous biosynthetic steps and the participation of various enzymes. The strategy of discovering drug molecules from microorganisms has led to the identification of a variety of biologically active natural products, including antibiotics such as penicillin, cholesterol-lowering drug lovastatin, and immunosuppressant cyclosporine. Many drugs on the FDA’s list can be manufactured using bioproduction technologies. If these drug components can enter large-scale, highly engineered production, it will completely transform the existing pharmaceutical supply chain.
A research team published a study titled “Efficient exploration of terpenoid biosynthetic gene clusters in filamentous fungi” in Nature Catalysis. Using synthetic biology tools, they employed the fungus Aspergillus oryzae (AO) as a chassis for the biosynthesis of anti-inflammatory terpenoid compounds. Terpenoids are key components of drugs and the largest family of natural products. Fungi are important sources of terpenoids, but many corresponding biosynthetic gene clusters (BGCs) are silent under laboratory conditions. Strategies such as homologous activation and heterologous expression are often used to activate individual clusters, but their efficiency is low. Therefore, selecting suitable chassis cells, developing automated and high-throughput (auto-HTP) biological workflows are necessary for effective genome mining, characterization of BGCs, and identification of biologically active fungal terpenoids. Additionally, studying engineered strains reveals potential biosynthetic pathways, providing a foundation for optimizing biosynthetic pathways for the overproduction of terpenoids.
Bioinformatic Analysis of Terpenoid BGCs
The AO provides a conducive cellular environment for exploring fungal natural products. Researchers used CRISPR-Cas9 to mine individual terpene cyclases or entire BGCs from filamentous fungi. However, limited precursor supply hinders obtaining sufficient terpenoid compounds for further biochemical and functional studies, especially for late-stage derivatives requiring multiple biosynthetic steps. The researchers adopted AO NSAR1 as the chassis 1.0 strain for a new genome mining strategy.
Specific strategy: Predict BGCs from internal sequencing of filamentous fungi, eliminate those lacking known conserved domains or incomplete functional domains. Divide BGCs into upstream terpene synthase, midstream P450 oxidation, and downstream modification modules for assembly. Place functional genes under pre-characterized strong constitutive (hlyA) and inducible (amyB, glaA) promoters. Place genes in the same module in separate plasmids or collectively construct them into one plasmid for all possible combinations. Based on combinations of plasmids from different modules, using terpene synthase genes as a starting point, add downstream genes from the same BGC to reconstruct BGCs into a strain library.
Automated and High-throughput Workflow
With the help of an auto-HTP workflow, researchers reconstructed 39 BGC combinations, from PCR amplification to the final construction of AO strains, obtaining 166 (96%) plasmids and 195 (96%) AO strains. Finally, engineered AO strains were cultured for 2 weeks at 30°C in 24-well plates. Fermentation products were extracted from the cultures using acetone and ethyl acetate, and concentrated to produce crude extracts. GC-MS and HR-ESI-MS detected 185 different terpenoid compounds in AO strains, including 23 sesquiterpenes, 59 diterpenes, and 103 sesterterpenoids (with 22 reported compounds).
Screening of Terpenoid Compounds
Researchers treated RAW 264.7 mouse macrophage cells with lipopolysaccharide (LPS) to initiate the inflammatory pathway and monitored the release of nitric oxide (NO). The ability of crude extracts to reduce NO levels served as a measure for screening terpenoid compounds. Tests indicated that 16% of fermentation extracts exhibited significant anti-inflammatory activity, reducing NO levels to below 20% of untreated controls. Strains AO-Y52 and Y5658 showed particularly high activity, both containing genes from the FgMS-BGC, predicted to synthesize the reported anti-inflammatory sesterterpenoid compounds mangicols. Researchers traced all strains containing these genes, AO-Y51 to AO-Y62, purified the corresponding compounds, and characterized them through NMR spectroscopy. The known molecule was mangicol E, and the new sesterterpenoids were named mangicol H-L. In vitro tests showed that mangicol J had the highest NO inhibitory activity, more effective and non-cytotoxic than the positive controls L-NMMA (NO synthase inhibitor) and indomethacin (IMC, nonsteroidal anti-inflammatory drug). Subsequently, researchers evaluated the anti-inflammatory activity of mangicol J in vivo using a mouse ear edema model, finding that it inhibited PMA-induced swelling to the same extent as the drug IMC. In a mouse model stimulated with LPS, mangicol J at 10 mg/kg significantly reduced serum levels of IL-6, IL-10, IFN-γ, IL-17A, and TNF-α. Western blot also showed that mangicol J reduced the expression levels of phosphorylated signaling STAT 3 downstream of IL-6 in human cells.
Terpenoid Biosynthetic Pathway
Reconstructed gene clusters enable the rapid assessment of specific genes required for the synthesis of the target compound. As mentioned earlier, strains capable of producing mangicol J all included genes from the FgMS cluster, with known MgcD (FgMS) identified as a terpene cyclase. Through the identification of Mangicol E and Mangicol H-J from different AO strains, it is inferred that MgcE is a multifunctional P450 capable of catalyzing hydroxylation and epoxidation reactions at the tail (C17-C20) of mangicdiene; MgcC can catalyze the ring-opening hydrolysis of the C19, C20 epoxide of Mangicol J, acting as an epoxide hydrolase; P450 MgcF acts on the core structure of these terpenoid compounds. Combining these results successfully predicted the possible biosynthetic pathway of mangicol H-L.
To scale up compound production, researchers systematically designed AO’s MVA pathway, establishing an efficient chassis 2.0 for overproducing mangicdiene and mangicol J. Initially, a CRISPR-Cas9-mediated site-specific integration system was developed. Plasmids containing the entire endogenous MVA pathway, an additional three copies of tHMG1, and mgcD were randomly integrated into AO NSAR1’s chromosome, obtaining strains AO-S81 to AO-S84. Integrating the entire MVA pathway and four additional copies of tHMG1 into different HS loci of AO produced strain AO-S95. Subsequently, one copy of mgcD was integrated into HS801 of AO-S95 to produce strain AO-S96. Compared to the parental strain AO-Y51, the titer of mangicdiene increased from 0.66 mg/L to 27.38 mg/L in AO-S96, a 41-fold increase, and in AO-S84, it reached 87.84 mg/L, a 133-fold increase. These titers were significantly higher than those detected in Escherichia coli and Bacillus cereus. Using random insertion, two copies of mgcE were inserted into the chromosome of AO-S84, yielding strain AO-S94. Using site-specific integration, one copy of mgcD and two copies of mgcE were integrated into HS801 of AO-S95, producing strain AO-S97. Compared to strain AO-Y52, the titer of mangicol J in AO-S98 reached 8.93 mg/L, a 112-fold increase, and in AO-S94, it reached 12.09 mg/L, a 151-fold increase. Finally, mgcD was knocked out from strain AO-S84 to produce AO-S85, serving as a universal chassis 2.0 for characterizing genes and terpenoid structures. Compared to chassis 1.0, titers of oxidized and glycosylated products were significantly increased.
References:
- Yuan, Y., et al., Efficient exploration of terpenoid biosynthetic gene clusters in filamentous fungi, Nature Catalysis, 2022, 5, 277-287.