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Flavonoids exhibit various bioactivities including anti-oxidant, anti-tumor, anti-inflammatory, and anti-viral properties. Methylated flavonoids are particularly significant due to their enhanced oral bioavailability, improved intestinal absorption, and greater stability. The heterologous production of plant flavonoids in bacterial factories involves the need for enough biosynthetic precursors to allow for high production levels. These biosynthetic precursors are malonyl-CoA and l-tyrosine. In this work, to enhance flavonoid biosynthesis in Streptomyces albidoflavus, we conducted a transcriptomics study for the identification of candidate genes involved in l-tyrosine catabolism. The hypothesis was that the bacterial metabolic machinery would detect an excess of this amino acid if supplemented with the conventional culture medium and would activate the genes involved in its catabolism towards energy production. Then, by inactivating those overexpressed genes (under an excess of l-tyrosine), it would be possible to increase the intracellular pools of this precursor amino acid and eventually the final flavonoid titers in this bacterial factory. The RNAseq data analysis in the S. albidoflavus wild-type strain highlighted the hppD gene encoding 4-hydroxyphenylpyruvate dioxygenase as a promising target for knock-out, exhibiting a 23.2-fold change (FC) in expression upon l-tyrosine supplementation in comparison to control cultivation conditions. The subsequent knock-out of the hppD gene in S. albidoflavus resulted in a 1.66-fold increase in the naringenin titer, indicating enhanced flavonoid biosynthesis. Leveraging the improved strain of S. albidoflavus, we successfully synthesized the methylated flavanones hesperetin, homoeriodictyol, and homohesperetin, achieving titers of 2.52 mg/L, 1.34 mg/L, and 0.43 mg/L, respectively. In addition, the dimethoxy flavanone homohesperetin was produced as a byproduct of the endogenous metabolism of S. albidoflavus. To our knowledge, this is the first time that hppD deletion was utilized as a strategy to augment the biosynthesis of flavonoids. Furthermore, this is the first report where hesperetin and homoeriodictyol have been synthesized from l-tyrosine as a precursor. Therefore, transcriptomics is, in this case, a successful approach for the identification of catabolism reactions affecting key precursors during flavonoid biosynthesis, allowing the generation of enhanced production strains. [ABSTRACT FROM AUTHOR]

Background: Integrated metabolic engineering approaches that combine system and synthetic biology tools enable the efficient design of microbial cell factories for synthesizing high-value products. In this study, we utilized in silico design algorithms on the yeast genome-scale model to predict genomic modifications that could enhance the production of early-step Taxol® in engineered Saccharomyces cerevisiae cells. Results: Using constraint-based reconstruction and analysis (COBRA) methods, we narrowed down the solution set of genomic modification candidates. We screened 17 genomic modifications, including nine gene deletions and eight gene overexpressions, through wet-lab studies to determine their impact on taxadiene production, the first metabolite in the Taxol® biosynthetic pathway. Under different cultivation conditions, most single genomic modifications resulted in increased taxadiene production. The strain named KM32, which contained four overexpressed genes (ILV2, TRR1, ADE13, and ECM31) involved in branched-chain amino acid biosynthesis, the thioredoxin system, de novo purine synthesis, and the pantothenate pathway, respectively, exhibited the best performance. KM32 achieved a 50% increase in taxadiene production, reaching 215 mg/L. Furthermore, KM32 produced the highest reported yields of taxa-4(20),11-dien-5α-ol (T5α-ol) at 43.65 mg/L and taxa-4(20),11-dien-5-α-yl acetate (T5αAc) at 26.2 mg/L among early-step Taxol® metabolites in S. cerevisiae. Conclusions: This study highlights the effectiveness of computational and integrated approaches in identifying promising genomic modifications that can enhance the performance of yeast cell factories. By employing in silico design algorithms and wet-lab screening, we successfully improved taxadiene production in engineered S. cerevisiae strains. The best-performing strain, KM32, achieved substantial increases in taxadiene as well as production of T5α-ol and T5αAc. These findings emphasize the importance of using systematic and integrated strategies to develop efficient yeast cell factories, providing potential implications for the industrial production of high-value isoprenoids like Taxol®. [ABSTRACT FROM AUTHOR]

Visualization is a key aspect of the analysis of omics data. Although many tools can generate pathway maps for visualization of yeast metabolism, they fail in reconstructing genome‐scale metabolic diagrams of compartmentalized metabolism. Here we report on the yeastGemMap, a process diagram of whole yeast metabolism created to assist data analysis in systems‐metabolic studies. The map was manually reconstructed with reactions from a compartmentalized genome‐scale metabolic model, based on biochemical process diagrams typically found in educational and specialized literature. The yeastGemMap consists of 3815 reactions representing 1150 genes, 2742 metabolites, and 14 compartments. Computational functions for adapting the graphical representation of the map are also reported. These functions modify the visual representation of the map to assist in three systems‐metabolic tasks: illustrating reaction networks, interpreting metabolic flux data, and visualizing omics data. The versatility of the yeastGemMap and algorithms to assist visualization of systems‐metabolic data was demonstrated in various tasks, including for single lethal reaction evaluation, flux balance analysis, and transcriptomic data analysis. For instance, visual interpretation of metabolic transcriptomes of thermally evolved and parental yeast strains allowed to demonstrate that evolved strains activate a preadaptation response at 30°C, which enabled thermotolerance. A quick interpretation of systems‐metabolic data is promoted with yeastGemMap visualizations. [ABSTRACT FROM AUTHOR]

Lactose assimilation is a relatively rare trait in yeasts, and Kluyveromyces yeast species have long served as model organisms for studying lactose metabolism. Meanwhile, the metabolic strategies of most other lactose-assimilating yeasts remain unknown. In this work, we have elucidated the genetic determinants of the superior lactose-growing yeast Candida intermedia. Through genomic and transcriptomic analyses, we identified three interdependent gene clusters responsible for the metabolism of lactose and its hydrolysis product galactose: the conserved LAC cluster (LAC12, LAC4) for lactose uptake and hydrolysis, the conserved GAL cluster (GAL1, GAL7, and GAL10) for galactose catabolism through the Leloir pathway, and a "GALLAC" cluster containing the transcriptional activator gene LAC9, second copies of GAL1 and GAL10, and a XYL1 gene encoding an aldose reductase involved in carbon overflow metabolism. Bioinformatic analysis suggests that the GALLAC cluster is unique to C. intermedia and has evolved through gene duplication and divergence, and deletion mutant phenotyping proved that the cluster is indispensable for C. intermedia's growth on lactose and galactose. We also show that the regulatory network in C. intermedia, governed by Lac9 and Gal1 from the GALLAC cluster, differs significantly from the galactose and lactose regulons in Saccharomyces cerevisiae, Kluyveromyces lactis, and Candida albicans. Moreover, although lactose and galactose metabolism are closely linked in C. intermedia, our results also point to important regulatory differences. IMPORTANCE This study paves the way to a better understanding of lactose and galactose metabolism in the non-conventional yeast C. intermedia. Notably, the unique GALLAC cluster represents a new, interesting example of metabolic network rewiring and likely helps to explain how C. intermedia has evolved into an efficient lactose-assimilating yeast. With the Leloir pathway of budding yeasts acting like a model system for understanding the function, evolution, and regulation of eukaryotic metabolism, this work provides new evolutionary insights into yeast metabolic pathways and regulatory networks. In extension, the results will facilitate future development and use of C. intermedia as a cell-factory for conversion of lactose-rich whey into value-added products. [ABSTRACT FROM AUTHOR]

Itaconic acid is an emerging platform chemical with extensive applications. Itaconic acid is currently produced by Aspergillus terreus through biological fermentation. However, A. terreus is a fungal pathogen that needs additional morphology controls, making itaconic acid production on industrial scale problematic. Here, we reprogrammed the Generally Recognized As Safe (GRAS) yeast Yarrowia lipolytica for competitive itaconic acid production. After preventing carbon sink into lipid accumulation, we evaluated itaconic acid production both inside and outside the mitochondria while fine-tuning its biosynthetic pathway. We then mimicked the regulation of nitrogen limitation in nitrogen-replete conditions by down-regulating NAD+-dependent isocitrate dehydrogenase through weak promoters, RNA interference, or CRISPR interference. Ultimately, we optimized fermentation parameters for fed-batch cultivations and produced itaconic acid titers of 130.1 grams per liter in 1-liter bioreactors and 94.8 grams per liter in a 50-liter bioreactor on semipilot scale. Our findings provide effective approaches to harness the GRAS microorganism Y. lipolytica for competitive industrial-scale production of itaconic acid. [ABSTRACT FROM AUTHOR]

Six bacterial strains, Mut1 T , Mut2, Alt1, Alt2, Alt3 T , and Alt4, were isolated from soil samples collected in parks in Gothenburg, Sweden, based on their ability to utilize the insoluble polysaccharides α-1,3-glucan (mutan; Mut strains) or the mixed-linkage α-1,3/α-1,6-glucan (alternan; Alt strains). Analysis of 16S rRNA gene sequences identified all strains as members of the genus Streptomyces . The genomes of the strains were sequenced and subsequent phylogenetic analyses identified Mut2 as a strain of Streptomyces laculatispora and Alt1, Alt2 and Alt4 as strains of Streptomyces poriferorum, while Mut1 T and Alt3 T were most closely related to the type strains Streptomyces drozdowiczii NBRC 101007 T and Streptomyces atroolivaceus NRRL ISP-5137 T , respectively. Comprehensive genomic and biochemical characterizations were conducted, highlighting typical features of Streptomyces , such as large genomes (8.0-9.6 Mb) with high G+C content (70.5-72.0%). All six strains also encode a wide repertoire of putative carbohydrate-active enzymes, indicating a capability to utilize various complex polysaccharides as carbon sources such as starch, mutan, and cellulose, which was confirmed experimentally. Based on phylogenetic and phenotypic characterization, our study suggests that strains Mut1 T and Alt3 T represent novel species in the genus Streptomyces for which the names Streptomyces castrisilvae sp. nov. and Streptomyces glycanivorans sp. nov. are proposed, with strains Mut1 T (=DSM 117248 T =CCUG 77596 T ) and Alt3 T (=DSM 117252 T =CCUG 77600 T ) representing the respective type strains.

Itaconic acid is an emerging platform chemical with extensive applications. Itaconic acid is currently produced by Aspergillus terreus through biological fermentation. However, A. terreus is a fungal pathogen that needs additional morphology controls, making itaconic acid production on industrial scale problematic. Here, we reprogrammed the Generally Recognized As Safe (GRAS) yeast Yarrowia lipolytica for competitive itaconic acid production. After preventing carbon sink into lipid accumulation, we evaluated itaconic acid production both inside and outside the mitochondria while fine-tuning its biosynthetic pathway. We then mimicked the regulation of nitrogen limitation in nitrogen-replete conditions by down-regulating NAD + -dependent isocitrate dehydrogenase through weak promoters, RNA interference, or CRISPR interference. Ultimately, we optimized fermentation parameters for fed-batch cultivations and produced itaconic acid titers of 130.1 grams per liter in 1-liter bioreactors and 94.8 grams per liter in a 50-liter bioreactor on semipilot scale. Our findings provide effective approaches to harness the GRAS microorganism Y. lipolytica for competitive industrial-scale production of itaconic acid.

Yarrowia lipolytica naturally saves excess carbon as storage lipids. Engineering efforts allow redirecting the high precursor flux required for lipid synthesis toward added-value chemicals such as polyketides, flavonoids, and terpenoids. To redirect precursor flux from storage lipids to other products, four genes involved in triacylglycerol and sterol ester synthesis (DGA1, DGA2, LRO1, and ARE1) can be deleted. To elucidate the effect of the deletions on cell physiology and regulation, we performed chemostat cultivations under carbon and nitrogen limitations, followed by transcriptome analysis. We found that storage lipid-free cells show an enrichment of the unfolded protein response, and several biological processes related to protein refolding and degradation are enriched. Additionally, storage lipid-free cells show an altered lipid class distribution with an abundance of potentially cytotoxic free fatty acids under nitrogen limitation. Our findings not only highlight the importance of lipid metabolism on cell physiology and proteostasis, but can also aid the development of improved chassy strains of Y. lipolytica for commodity chemical production., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society of Industrial Microbiology and Biotechnology.)

Genome-scale metabolic models (GEMs) provide a useful framework for modeling the metabolism of microorganisms. While the applications of GEMs are wide and far reaching, the reconstruction and continuous curation of such models can be perceived as a tedious and time-consuming task. Using RAVEN, a MATLAB-based toolbox designed to facilitate the reconstruction analysis of metabolic networks, this protocol practically demonstrates how researchers can create their own GEMs using a homology-based approach. To provide a complete example, a draft GEM for the industrially relevant yeast Hansenula polymorpha is reconstructed., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)