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Abscisic acid (ABA) is a phytohormone with applications in agriculture and human health. ABA can be produced by Botrytis cinerea , a plant pathogenic filamentous fungus. However, the cultivation process is lengthy and strain improvement by genetic engineering is difficult. Therefore, we engineered the oleaginous yeast Yarrowia lipolytica as an alternative host for ABA production. First, we expressed five B. cinerea genes involved in ABA biosynthesis (BcABA1 , BcABA2 , BcABA3 , BcABA4 and BcCPR1) in a Y. lipolytica chassis with optimized mevalonate flux. The strain produced 59.2 mg/L of ABA in small-scale cultivation. Next, we expressed an additional copy of each gene in the strain, but only expression of additional copy of BcABA1 gene increased the ABA titer to 168.5 mg/L. We then integrated additional copies of the mevalonate pathway and ABA biosynthesis encoding genes, and we expressed plant ABA transporters resulting in an improved strain producing 263.5 mg/L and 9.1 mg/g dry cell weight (DCW) ABA. Bioreactor cultivation resulted in a specific yield of 12.8 mg/g DCW ABA; however, surprisingly, the biomass level obtained in bioreactors was only 10.5 g DCW/L, with a lower ABA titer of 133.6 mg/L. While further optimization is needed, this study confirms Y. lipolytica as a potential alternative host for the ABA production. [ABSTRACT FROM AUTHOR]

Streptomycetes serve as major producers of various pharmacologically and industrially important natural products. Although CRISPR-Cas9 systems have been developed for more robust genetic manipulations, concerns of genome instability caused by the DNA double-strand breaks (DSBs) and the toxicity of Cas9 remain. To overcome these limitations, here we report development of the DSB-free, single-nucleotide-resolution genome editing system CRISPR-BEST (CRISPR-Base Editing SysTem), which comprises a cytidine (CRISPR-cBEST) and an adenosine (CRISPRaBEST) deaminase-based base editor. Specifically targeted by an sgRNA, CRISPR-cBEST can efficiently convert a C:G base pair to a T:A base pair and CRISPR-aBEST can convert an A:T base pair to a G:C base pair within a window of approximately 7 and 6 nucleotides, respectively. CRISPR-BEST was validated and successfully used in different Streptomyces species. Particularly in nonmodel actinomycete Streptomyces collinus Tü365, CRISPR-cBEST efficiently inactivated the 2 copies of kirN gene that are in the duplicated kirromycin biosynthetic pathways simultaneously by STOP codon introduction. Generating such a knockout mutant repeatedly failed using the conventional DSB-based CRISPR-Cas9. An unbiased, genome-wide off-target evaluation indicates the high fidelity and applicability of CRISPR-BEST. Furthermore, the system supports multiplexed editing with a single plasmid by providing a Csy4-based sgRNA processing machinery. To simplify the protospacer identification process, we also updated the CRISPy-web (https://crispy.secondarymetabolites.org), and now it allows designing sgRNAs specifically for CRISPR-BEST applications. [ABSTRACT FROM AUTHOR]

In natural-product drug discovery, finding new compounds is the main task, and thus fast dereplication of known compounds is essential. This is usually performed by manual liquid chromatography-ultraviolet (LC-UV) or visible light-mass spectroscopy (Vis-MS) interpretation of detected peaks, often assisted by automated identification of previously identified compounds. We used a 15 min high-performance liquid chromatography-diode array detection (UHPLC-DAD)-high-resolution MS method (electrospray ionization (ESI) or ESI), followed by 10-60 s of automated data analysis for up to 3000 relevant elemental compositions. By overlaying automatically generated extracted-ion chromatograms from detected compounds on the base peak chromatogram, all major potentially novel peaks could be visualized. Peaks corresponding to compounds available as reference standards, previously identified compounds, and major contaminants from solvents, media, filters etc. were labeled to differentiate these from compounds only identified by elemental composition. This enabled fast manual evaluation of both known peaks and potential novel-compound peaks, by manual verification of: the adduct pattern, UV-Vis, retention time compared with log D, co-identified biosynthetic related compounds, and elution order. System performance, including adduct patterns, in-source fragmentation, and ion-cooler bias, was investigated on reference standards, and the overall method was used on extracts of Aspergillus carbonarius and Penicillium melanoconidium, revealing new nitrogen-containing biomarkers for both species. [ABSTRACT FROM AUTHOR]

The article discusses a study on the methods of identifying and predicting microbial fungi genes responsible in the biosynthesis of secondary metabolites (SMs). The study involves the collection of gene expression of Aspergillus nidulans, in which the member genes of biosynthetic clusters were identified using statistical method. It reveals that the efficiency of method relies on the diversity and number of sampling conditions in the gene expression analysis.