Aerobic growth physiology of Saccharomyces cerevisiae on sucrose is strain-dependent

Efficient Biosynthesis of Salidroside via Artificial in Vivo enhanced UDP-Glucose System Using Cheap Sucrose as Substrate

Salidroside, a valuable phenylethanoid glycoside, is obtained from plants belonging to the Rhodiola genus, known for its diverse biological properties. At present, salidroside is still far from large-scale industrial production due to its lower titer and higher process cost. In this study, we have for the first time increased salidroside production by enhancing UDP-glucose supply in situ. We constructed an in vivo UDP-glucose regeneration system that works in conjunction with UDP-glucose transferase from Rhodiola innovatively to improve UDP-glucose availability. And a coculture was formed in order to enable de novo salidroside synthesis. Confronted with the influence of tyrosol on strain growth, an adaptive laboratory evolution strategy was implemented to enhance the strain's tolerance. Similarly, salidroside production was optimized through refinement of the fermentation medium, the inoculation ratio of the two microbes, and the inoculation size. The final salidroside titer reached 3.8 g/L. This was the highest titer achieved at the shake flask level in the existing reports. And this marked the first successful synthesis of salidroside in an in situ enhanced UDP-glucose system using sucrose. The cost was reduced by 93% due to the use of inexpensive substrates. This accomplishment laid a robust foundation for further investigations into the synthesis of other notable glycosides and natural compounds.

Functional genetic characterization of stress tolerance and biofilm formation in Nakaseomyces (Candida) glabrata via a novel CRISPR activation system

The overexpression of genes frequently arises in Nakaseomyces (formerly Candida) glabrata via gain-of-function mutations, gene duplication, or aneuploidies, with important consequences on pathogenesis traits and antifungal drug resistance. This highlights the need to develop specific genetic tools to mimic and study genetic amplification in this important fungal pathogen. Here, we report the development, validation, and applications of the first clustered regularly interspaced short palindromic repeats (CRISPR) activation (CRISPRa) system in N. glabrata for targeted genetic overexpression. Using this system, we demonstrate the ability of CRISPRa to drive high levels of gene expression in N. glabrata, and further assess optimal guide RNA targeting for robust overexpression. We demonstrate the applications of CRISPRa to overexpress genes involved in fungal pathogenesis and drug resistance and detect corresponding phenotypic alterations in these key traits, including the characterization of novel phenotypes. Finally, we capture strain variation using our CRISPRa system in two commonly used N. glabrata genetic backgrounds. Together, this tool will expand our capacity for functional genetic overexpression in this pathogen, with numerous possibilities for future applications.IMPORTANCENakaseomyces (formerly Candida) glabrata is an important fungal pathogen that is now the second leading cause of candidiasis infections. A common strategy that this pathogen employs to resist antifungal treatment is through the upregulation of gene expression, but we have limited tools available to study this phenomenon. Here, we develop, optimize, and apply the use of CRISPRa as a means to overexpress genes in N. glabrata. We demonstrate the utility of this system to overexpress key genes involved in antifungal susceptibility, stress tolerance, and biofilm growth. This tool will be an important contribution to our ability to study the biology of this important fungal pathogen.

Elucidating yeast glycolytic dynamics at steady state growth and glucose pulses through kinetic metabolic modeling

Microbial cell factories face changing environments during industrial fermentations. Kinetic metabolic models enable the simulation of the dynamic metabolic response to these perturbations, but their development is challenging due to model complexity and experimental data requirements. An example of this is the well-established microbial cell factory Saccharomyces cerevisiae, for which no consensus kinetic model of central metabolism has been developed and implemented in industry. Here, we aim to bring the academic and industrial communities closer to this consensus model. We developed a physiology informed kinetic model of yeast glycolysis connected to central carbon metabolism by including the effect of anabolic reactions precursors, mitochondria and the trehalose cycle. To parametrize such a large model, a parameter estimation pipeline was developed, consisting of a divide and conquer approach, supplemented with regularization and global optimization. Additionally, we show how this first mechanistic description of a growing yeast cell captures experimental dynamics at different growth rates and under a strong glucose perturbation, is robust to parametric uncertainty and explains the contribution of the different pathways in the network. Such a comprehensive model could not have been developed without using steady state and glucose perturbation data sets. The resulting metabolic reconstruction and parameter estimation pipeline can be applied in the future to study other industrially-relevant scenarios. We show this by generating a hybrid CFD-metabolic model to explore intracellular glycolytic dynamics for the first time. The model suggests that all intracellular metabolites oscillate within a physiological range, except carbon storage metabolism, which is sensitive to the extracellular environment.

Comparative proteome analysis of different Saccharomyces cerevisiae strains during growth on sucrose and glucose

Both the identity and the amount of a carbon source present in laboratory or industrial cultivation media have major impacts on the growth and physiology of a microbial species. In the case of the yeast Saccharomyces cerevisiae, sucrose is arguably the most important sugar used in industrial biotechnology, whereas glucose is the most common carbon and energy source used in research, with many well-known and described regulatory effects, e.g. glucose repression. Here we compared the label-free proteomes of exponentially growing S. cerevisiae cells in a defined medium containing either sucrose or glucose as the sole carbon source. For this purpose, bioreactor cultivations were employed, and three different strains were investigated, namely: CEN.PK113-7D (a common laboratory strain), UFMG-CM-Y259 (a wild isolate), and JP1 (an industrial bioethanol strain). These strains present different physiologies during growth on sucrose; some of them reach higher specific growth rates on this carbon source, when compared to growth on glucose, whereas others display the opposite behavior. It was not possible to identify proteins that commonly presented either higher or lower levels during growth on sucrose, when compared to growth on glucose, considering the three strains investigated here, except for one protein, named Mnp1-a mitochondrial ribosomal protein of the large subunit, which had higher levels on sucrose than on glucose, for all three strains. Interestingly, following a Gene Ontology overrepresentation and KEGG pathway enrichment analyses, an inverse pattern of enriched biological functions and pathways was observed for the strains CEN.PK113-7D and UFMG-CM-Y259, which is in line with the fact that whereas the CEN.PK113-7D strain grows faster on glucose than on sucrose, the opposite is observed for the UFMG-CM-Y259 strain.

Impact of Non-Saccharomyces Wine Yeast Strains on Improving Healthy Characteristics and the Sensory Profile of Beer in Sequential Fermentation

The use of non-Saccharomyces yeasts in brewing is a useful tool for developing new products to meet the growing consumer demand for innovative products. Non-Saccharomyces yeasts can be used both in single and in mixed fermentations with Saccharomyces cerevisiae, as they are able to improve the sensory profile of beers, and they can be used to obtain functional beers (with a low ethanol content and melatonin production). The aim of this study was to evaluate this capacity in eight non-Saccharomyces strains isolated from Madrid agriculture. For this purpose, single fermentations were carried out with non-Saccharomyces strains and sequential fermentations with non-Saccharomyces and the commercial strain SafAle S-04. The Wickerhamomyces anomalus strain CLI 1028 was selected in pure culture for brewing beer with a low ethanol content (1.25% (v/v)) for its fruity and phenolic flavours and the absence of wort flavours. The best-evaluated strains in sequential fermentation were CLI 3 (Hanseniaspora vineae) and CLI 457 (Metschnikowia pulcherrima), due to their fruity notes as well as their superior bitterness, body, and balance. Volatile compounds and melatonin production were analysed by GC and HPLC, respectively. The beers were sensory-analysed by a trained panel. The results of the study show the potential of non-Saccharomyces strains in the production of low-alcohol beers, and as a flavour enhancement in sequential fermentation.

Considering Strain Variation and Non-Type Strains for Yeast Metabolic Engineering Applications

A variety of yeast species have been considered ideal hosts for metabolic engineering to produce value-added chemicals, including the model organism Saccharomyces cerevisiae, as well as non-conventional yeasts including Yarrowia lipolytica, Kluyveromyces marxianus, and Pichia pastoris. However, the metabolic capacity of these microbes is not simply dictated or implied by genus or species alone. Within the same species, yeast strains can display distinct variations in their phenotypes and metabolism, which affect the performance of introduced pathways and the production of interesting compounds. Moreover, it is unclear how this metabolic potential corresponds to function upon rewiring these organisms. These reports thus point out a new consideration for successful metabolic engineering, specifically: what are the best strains to utilize and how does one achieve effective metabolic engineering? Understanding such questions will accelerate the host selection and optimization process for generating yeast cell factories. In this review, we survey recent advances in studying yeast strain variations and utilizing non-type strains in pathway production and metabolic engineering applications. Additionally, we highlight the importance of employing portable methods for metabolic rewiring to best access this metabolic diversity. Finally, we conclude by highlighting the importance of considering strain diversity in metabolic engineering applications.

Blocking mitophagy does not significantly improve fuel ethanol production in bioethanol yeast Saccharomyces cerevisiae

Ethanolic fermentation is frequently performed under conditions of low nitrogen. In Saccharomyces cerevisiae, nitrogen limitation induces macroautophagy, including the selective removal of mitochondria, also called mitophagy. Shiroma and co-workers (2014) showed that blocking mitophagy by deletion of the mitophagy specific gene ATG32 increased the fermentation performance during the brewing of Ginjo sake. In this study, we tested if a similar strategy could enhance alcoholic fermentation in the context of fuel ethanol production from sugarcane in Brazilian biorefineries. Conditions that mimic the industrial fermentation process indeed induce Atg32-dependent mitophagy in cells of S. cerevisiae PE-2, a strain frequently used in the industry. However, after blocking mitophagy, no significant differences in CO₂ production, final ethanol titres or cell viability were observed after five rounds of ethanol fermentation, cell recycling and acid treatment, as commonly performed in sugarcane biorefineries. To test if S. cerevisiae's strain background influences this outcome, cultivations were carried out in a synthetic medium with strains PE-2, Ethanol Red (industrial) and BY (laboratory), with and without a functional ATG32 gene, under oxic and oxygen restricted conditions. Despite the clear differences in sugar consumption, cell viability and ethanol titres, among the three strains, we could not observe any significant improvement in fermentation performance related to the blocking of mitophagy. We conclude with caution that results obtained with Ginjo sake yeast is an exception and cannot be extrapolated to other yeast strains and that more research is needed to ascertain the role of autophagic processes during fermentation. Importance Bioethanol is the largest (per volume) ever biobased bulk chemical produced globally. The fermentation process is very well established, and industries regularly attain nearly 85% of maximum theoretical yields. However, because of the volume of fuel produced, even a small improvement will have huge economic benefits. To this end, besides already implemented process improvements, various free energy conservation strategies have been successfully exploited at least in laboratory strains to increase ethanol yields and decrease by-product formation. Cellular housekeeping processes have been an almost unexplored territory in strain improvement. Shiroma and co-workers previously reported that blocking mitophagy by deletion of the mitophagy receptor gene ATG32 in Saccharomyces cerevisiae led to a 2.1% increase in final ethanol titres during Japanese sake fermentation. We found in two commercially used bioethanol strains (PE-2 and Ethanol Red) that ATG32 deficiency does not lead to a significant improvement in cell viability or ethanol levels during fermentation with molasses or in a synthetic complete medium. More research is required to ascertain the role of autophagic processes during fermentation conditions.

Kinetic Modeling of Saccharomyces cerevisiae Central Carbon Metabolism: Achievements, Limitations, and Opportunities

Central carbon metabolism comprises the metabolic pathways in the cell that process nutrients into energy, building blocks and byproducts. To unravel the regulation of this network upon glucose perturbation, several metabolic models have been developed for the microorganism Saccharomyces cerevisiae. These dynamic representations have focused on glycolysis and answered multiple research questions, but no commonly applicable model has been presented. This review systematically evaluates the literature to describe the current advances, limitations, and opportunities. Different kinetic models have unraveled key kinetic glycolytic mechanisms. Nevertheless, some uncertainties regarding model topology and parameter values still limit the application to specific cases. Progressive improvements in experimental measurement technologies as well as advances in computational tools create new opportunities to further extend the model scale. Notably, models need to be made more complex to consider the multiple layers of glycolytic regulation and external physiological variables regulating the bioprocess, opening new possibilities for extrapolation and validation. Finally, the onset of new data representative of individual cells will cause these models to evolve from depicting an average cell in an industrial fermenter, to characterizing the heterogeneity of the population, opening new and unseen possibilities for industrial fermentation improvement.