Integrated omics of Saccharomyces cerevisiae CENPK2-1C reveals pleiotropic drug resistance and lipidomic adaptations to cannabidiol.

Yeast metabolism can be engineered to produce xenobiotic compounds, such as cannabinoids, the principal isoprenoids of the plant Cannabis sativa, through heterologous metabolic pathways. However, yeast cell factories continue to have low cannabinoid production. This study employed an integrated omics approach to investigate the physiological effects of cannabidiol on S. cerevisiae CENPK2-1C yeast cultures. We treated the experimental group with 0.5 mM CBD and monitored CENPK2-1C cultures. We observed a latent-stationary phase post-diauxic shift in the experimental group and harvested samples in the inflection point of this growth phase for transcriptomic and metabolomic analysis. We compared the transcriptomes of the CBD-treated yeast and the positive control, identifying eight significantly overexpressed genes with a log fold change of at least 1.5 and a significant adjusted p-value. Three notable genes were PDR5 (an ABC-steroid and cation transporter), CIS1, and YGR035C. These genes are all regulated by pleiotropic drug resistance linked promoters. Knockout and rescue of PDR5 showed that it is a causal factor in the post-diauxic shift phenotype. Metabolomic analysis revealed 48 significant spectra associated with CBD-fed cell pellets, 20 of which were identifiable as non-CBD compounds, including fatty acids, glycerophospholipids, and phosphate-salvage indicators. Our results suggest that mitochondrial regulation and lipidomic remodeling play a role in yeast's response to CBD, which are employed in tandem with pleiotropic drug resistance (PDR). We conclude that bioengineers should account for off-target product C-flux, energy use from ABC-transport, and post-stationary phase cell growth when developing cannabinoid-biosynthetic yeast strains.

Foldseek reveals a CBGA prenylating enzyme GlyMa_02G168000 from Glycine max.

The present research provides an application for an aromatic prenyltransferase from Glycine max for use in heterologous microorganism expression to generate cannabinoids. The known cannabinoid prenyltransferase CsPT04 was queried in FoldSeek. An enzyme derived from Glycine max known as GLYMA_02G168000, which is a predicted homogentisate solanyltransferase, was identified and found to have affinity for the prenylation of geranyldiphosphate (GPP) and olivetolic acid (OA) to produce cannabigerolic acid (CBGA) and cannabigerol (CBG). The in vitro production of CBGA was accomplished through the heterologous expression of this prenyltransferase in Saccharomyces cerevisiae. After growing the yeast cells, a purified microsomal fraction was harvested, which was rich in the membrane-bound prenyltransferase GlyMa_02G168000. Addition of purified microsomal fraction to a reaction matrix facilitated the successful prenylation of externally supplied OA with GPP, culminating in the production of CBGA. Structural comparisons revealed a notably closer similarity between GLYMA_02G168000 and CsPT04, compared to the similarity of other cannabinoid prenyltransferases with CsPT04. Herein, a novel application for a homogentisate solanyltransferase has been established towards the production of cannabinoids.

Synthetic Strategies for Rare Cannabinoids Derived from Cannabis sativa.

Efficient syntheses of eight key cannabinoids were established and optimized. Predominant cannabinoids such as cannabigerol (CBG-C5) and cannabidiol (CBD-C5) were prepared from olivetol via regioselective condensation. Further treatments of CBD led to Δ9-tetrahydrocannabinol (THC-C5), Δ8-iso-tetrahydrocannabinol (iso-THC-C5), and cannabinol (CBN-C5). Alternatively, a [3 + 3] annulation between olivetol and citral yielded the minor cannabinoid cannabichromene (CBC-C5), which was converted into two very rare polycycles, cannabicyclol (CBL-C5) and cannabicitran (CBT-C5), in a one-pot reaction. Finally, all eight syntheses were extended by utilizing resorcinol and two phenolic analogues, achieving a cannabinoid group with more than 30 compounds through a facile synthesis strategy.

Evaluating long-read de novo assembly tools for eukaryotic genomes: insights and considerations.

BACKGROUND: Assembly algorithm choice should be a deliberate, well-justified decision when researchers create genome assemblies for eukaryotic organisms from third-generation sequencing technologies. While third-generation sequencing by Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) has overcome the disadvantages of short read lengths specific to next-generation sequencing (NGS), third-generation sequencers are known to produce more error-prone reads, thereby generating a new set of challenges for assembly algorithms and pipelines. However, the introduction of HiFi reads, which offer substantially reduced error rates, has provided a promising solution for more accurate assembly outcomes. Since the introduction of third-generation sequencing technologies, many tools have been developed that aim to take advantage of the longer reads, and researchers need to choose the correct assembler for their projects. RESULTS: We benchmarked state-of-the-art long-read de novo assemblers to help readers make a balanced choice for the assembly of eukaryotes. To this end, we used 12 real and 64 simulated datasets from different eukaryotic genomes, with different read length distributions, imitating PacBio continuous long-read (CLR), PacBio high-fidelity (HiFi), and ONT sequencing to evaluate the assemblers. We include 5 commonly used long-read assemblers in our benchmark: Canu, Flye, Miniasm, Raven, and wtdbg2 for ONT and PacBio CLR reads. For PacBio HiFi reads , we include 5 state-of-the-art HiFi assemblers: HiCanu, Flye, Hifiasm, LJA, and MBG. Evaluation categories address the following metrics: reference-based metrics, assembly statistics, misassembly count, BUSCO completeness, runtime, and RAM usage. Additionally, we investigated the effect of increased read length on the quality of the assemblies and report that read length can, but does not always, positively impact assembly quality. CONCLUSIONS: Our benchmark concludes that there is no assembler that performs the best in all the evaluation categories. However, our results show that overall Flye is the best-performing assembler for PacBio CLR and ONT reads, both on real and simulated data. Meanwhile, best-performing PacBio HiFi assemblers are Hifiasm and LJA. Next, the benchmarking using longer reads shows that the increased read length improves assembly quality, but the extent to which that can be achieved depends on the size and complexity of the reference genome.