Model-assisted DoE software: optimization of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses.
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ABSTRACT:
SUBMITTER: Moser A
PROVIDER: S-EPMC7997827 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Resource optimization in protein synthesis is often looked at from the perspective of translation efficiency-the rate at which proteins are synthesized from a single transcript. The higher the rate of protein synthesis, the more efficiently a transcript is translated. However, the production of a ribosome consumes significantly more cellular resources than an mRNA molecule. Therefore, there should be a stronger selection pressure for optimizing ribosome usage than translation efficiency. This paper reports strong evidence of such optimization which becomes more prominent in highly expressed transcripts that consume a significant amount of cellular resources. The ribosome usage is optimized by the biases in codon usage and translation initiation rates. This optimization significantly reduces the ribosome requirement in Saccharomyces cerevisiae. We also find that a low ribosome density on mRNA transcripts helps optimize ribosome utilization. Therefore, protein synthesis occurs in a low ribosome density regime where translation-initiation is the rate-limiting step. Our results suggest that optimizing ribosome usage is one of the major forces shaping evolutionary selection pressure, and thus provide a new perspective to resource optimization in protein synthesis.
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Project description:Microbial synthesis of carotenoids is a highly desirable alternative to plant extraction and chemical synthesis. In this study, we investigated multidimensional strategies to improve the carotenoid synthesis in the industrial workhorse of Saccharomyces cerevisiae. First, we rewired the yeast central metabolism by optimizing non-oxidative glycolysis pathway for an improved acetyl-CoA supply. Second, we restricted the consumption of farnesyl pyrophosphate (FPP) by the down-regulation of squalene synthase using the PEST degron. Third, we further explored the human lipid binding/transfer protein saposin B (hSapB)-mediated metabolic sink for an enhanced storage of lipophilic carotenoids. Last, the copper-induced GAL expression system was engineered to function in the yeast-peptone-dextrose medium for an increased biomass accumulation. By combining the abovementioned strategies, the final engineered yeast produced 166.79 ± 10.43 mg/l β-carotene in shake flasks, which was nearly 5-fold improvement of the parental carotenoid-producing strain. Together, we envision that multidimensional strategies reported here might be applicable to other hosts for the future industrial development of carotenoid synthesis from renewable feedstocks.
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Project description:Metagenomic profiling of the human gut microbiome has discovered DNA from dietary yeasts like Saccharomyces cerevisiae. However, it is unknown if the S. cerevisiae detected by common metagenomic methods are from dead dietary sources, or from live S. cerevisiae colonizing the gut similar to their close relative Candida albicans. While S. cerevisiae can adapt to minimal oxygen and acidic environments, it has not been explored whether this yeast can metabolize mucin, the large, gel-forming, highly glycosylated proteins representing a major source of carbon in the gut mucosa. We reveal that S. cerevisiae can utilize mucin as their main carbon source, as well as perform both a transcriptome analysis and a chemogenomic screen to identify biological pathways required for this yeast to grow optimally in mucin. In total, 739 genes demonstrate significant differential expression in mucin culture, and deletion of 21 genes impact growth in mucin. Both screens suggest that mitochondrial function is required for proper growth in mucin, and through secondary assays we determine that mucin exposure induces mitogenesis and cellular respiration. We further show that deletion of an uncharacterized ORF, YCR095W-A, led to dysfunction in mitochondrial morphology and oxygen consumption in mucin. Finally, we demonstrate that Yps7, an aspartyl protease and homolog to mucin-degrading proteins in C. albicans, is important for growth on mucin. Collectively, our work serves as the initial step toward establishing how this common dietary fungus can survive in the mucus environment of the human gut.
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Project description:Amino acids are essential metabolites but can also be toxic when present at high levels intracellularly. Substrate-induced downregulation of amino acid transporters in Saccharomyces cerevisiae is thought to be a mechanism to avoid this toxicity. It has been shown that unregulated uptake by the general amino acid permease Gap1 causes cells to become sensitive to amino acids. Here, we show that overexpression of eight other amino acid transporters (Agp1, Bap2, Can1, Dip5, Gnp1, Lyp1, Put4, or Tat2) also induces a growth defect when specific single amino acids are present at concentrations of 0.5-5 mM. We can now state that all proteinogenic amino acids, as well as the important metabolite ornithine, are growth inhibitory to S. cerevisiae when transported into the cell at high enough levels. Measurements of initial transport rates and cytosolic pH show that toxicity is due to amino acid accumulation and not to the influx of co-transported protons. The amino acid sensitivity phenotype is a useful tool that reports on the in vivo activity of transporters and has allowed us to identify new transporter-specific substrates.
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Project description:BackgroundRNA-seq studies have an important role for both large-scale analysis of gene expression and for transcriptome reconstruction. However, the lack of software specifically developed for the analysis of the transcriptome structure in lower eukaryotes, has so far limited the comparative studies among different species and strains.ResultsIn order to fill this gap, an innovative software called ORA (Overlapped Reads Assembler) was developed. This software allows a simple and reliable analysis of the transcriptome structure in organisms with a low number of introns. It can also determine the size and the position of the untranslated regions (UTR) and of polycistronic transcripts. As a case study, we analyzed the transcriptional landscape of six S. cerevisiae strains in two different key steps of the fermentation process. This comparative analysis revealed differences in the UTR regions of transcripts. By extending the transcriptome analysis to yeast species belonging to the Saccharomyces genus, it was possible to examine the conservation level of unknown non-coding RNAs and their putative functional role.ConclusionsBy comparing the results obtained using ORA with previous studies and with the transcriptome structure determined with other software, it was proven that ORA has a remarkable reliability. The results obtained from the training set made it possible to detect the presence of transcripts with variable UTRs between S. cerevisiae strains. Finally, we propose a regulatory role for some non-coding transcripts conserved within the Saccharomyces genus and localized in the antisense strand to genes involved in meiosis and cell wall biosynthesis.
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Project description:BackgroundMannosylglycerate (MG) is one of the most widespread compatible solutes among marine microorganisms adapted to hot environments. This ionic solute holds excellent ability to protect proteins against thermal denaturation, hence a large number of biotechnological and clinical applications have been put forward. However, the current prohibitive production costs impose severe constraints towards large-scale applications. All known microbial producers synthesize MG from GDP-mannose and 3-phosphoglycerate via a two-step pathway in which mannosyl-3-phosphoglycerate is the intermediate metabolite. In an early work, this pathway was expressed in Saccharomyces cerevisiae with the goal to confirm gene function (Empadinhas et al. in J Bacteriol 186:4075-4084, 2004), but the level of MG accumulation was low. Therefore, in view of the potential biotechnological value of this compound, we decided to invest further effort to convert S. cerevisiae into an efficient cell factory for MG production.ResultsTo drive MG production, the pathway for the synthesis of GDP-mannose, one of the MG biosynthetic precursors, was overexpressed in S. cerevisiae along with the MG biosynthetic pathway. MG production was evaluated under different cultivation modes, i.e., flask bottle, batch, and continuous mode with different dilution rates. The genes encoding mannose-6-phosphate isomerase (PMI40) and GDP-mannose pyrophosphorylase (PSA1) were introduced into strain MG01, hosting a plasmid encoding the MG biosynthetic machinery. The resulting engineered strain (MG02) showed around a twofold increase in the activity of PMI40 and PSA1 in comparison to the wild-type. In batch mode, strain MG02 accumulated 15.86 mgMG g DCW -1 , representing a 2.2-fold increase relative to the reference strain (MG01). In continuous culture, at a dilution rate of 0.15 h-1, there was a 1.5-fold improvement in productivity.ConclusionIn the present study, the yield and productivity of MG were increased by overexpression of the GDP-mannose pathway and optimization of the mode of cultivation. A maximum of 15.86 mgMG g DCW -1 was achieved in batch cultivation and maximal productivity of 1.79 mgMG g DCW -1 h-1 in continuous mode. Additionally, a positive correlation between MG productivity and growth rate/dilution rate was established, although this correlation is not observed for MG yield.
| S-EPMC6240254 | biostudies-literature
Project description:Curcumin, a polyphenol derived from turmeric, is an ancient therapeutic used in India for centuries to treat a wide array of ailments. Interest in curcumin has increased recently, with ongoing clinical trials exploring curcumin as an anticancer therapy and as a protectant against neurodegenerative diseases. In vitro, curcumin chelates metal ions. However, although diverse physiological effects have been documented for this compound, curcumin's mechanism of action on mammalian cells remains unclear. This study uses yeast as a model eukaryotic system to dissect the biological activity of curcumin. We found that yeast mutants lacking genes required for iron and copper homeostasis are hypersensitive to curcumin and that iron supplementation rescues this sensitivity. Curcumin penetrates yeast cells, concentrates in the endoplasmic reticulum (ER) membranes, and reduces the intracellular iron pool. Curcumin-treated, iron-starved cultures are enriched in unbudded cells, suggesting that the G(1) phase of the cell cycle is lengthened. A delay in cell cycle progression could, in part, explain the antitumorigenic properties associated with curcumin. We also demonstrate that curcumin causes a growth lag in cultured human cells that is remediated by the addition of exogenous iron. These findings suggest that curcumin-induced iron starvation is conserved from yeast to humans and underlies curcumin's medicinal properties.
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Project description:Using an eGFP-RBD3 probe, which specifically binds Ras-GTP, we recently showed that the fluorescent probe was localized to the plasma membrane and to the nucleus in wild type cells growing exponentially on glucose medium, indicating the presence of active Ras in these cellular compartments. To investigate the nuclear function of Ras-GTP, we generated a strain where Ras2 is fused to the nuclear export signal (NES) from the HIV virus, in order to exclude this protein from the nucleus. Our results show that nuclear active Ras2 is required for invasive growth development in haploid yeast, while the expression of the NES-Ras2 protein does not cause growth defects either on fermentable or non-fermentable carbon sources and does not influence protein kinase A (PKA) activity related phenotypes analysed. Moreover, we show that the cAMP/PKA pathway controls invasive growth influencing the localization of active Ras. In particular, we show that PKA activity plays a role in the localization of active Ras and influences the ability of the cells to invade the agar: high PKA activity leads to a predominant nuclear accumulation of active Ras and induces invasive growth, while low PKA activity leads to plasma membrane localization of active Ras and to a defective invasive growth phenotype.
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Project description:BackgroundModel organisms are used for research because they provide a framework on which to develop and optimize methods that facilitate and standardize analysis. Such organisms should be representative of the living beings for which they are to serve as proxy. However, in practice, a model organism is often selected ad hoc, and without considering its representativeness, because a systematic and rational method to include this consideration in the selection process is still lacking.Methodology/principal findingsIn this work we propose such a method and apply it in a pilot study of strengths and limitations of Saccharomyces cerevisiae as a model organism. The method relies on the functional classification of proteins into different biological pathways and processes and on full proteome comparisons between the putative model organism and other organisms for which we would like to extrapolate results. Here we compare S. cerevisiae to 704 other organisms from various phyla. For each organism, our results identify the pathways and processes for which S. cerevisiae is predicted to be a good model to extrapolate from. We find that animals in general and Homo sapiens in particular are some of the non-fungal organisms for which S. cerevisiae is likely to be a good model in which to study a significant fraction of common biological processes. We validate our approach by correctly predicting which organisms are phenotypically more distant from S. cerevisiae with respect to several different biological processes.Conclusions/significanceThe method we propose could be used to choose appropriate substitute model organisms for the study of biological processes in other species that are harder to study. For example, one could identify appropriate models to study either pathologies in humans or specific biological processes in species with a long development time, such as plants.
| S-EPMC3032731 | biostudies-literature
Project description:SummaryHere, we introduce YeastMate, a user-friendly deep learning-based application for automated detection and segmentation of Saccharomyces cerevisiae cells and their mating and budding events in microscopy images. We build upon Mask R-CNN with a custom segmentation head for the subclassification of mother and daughter cells during lifecycle transitions. YeastMate can be used directly as a Python library or through a standalone application with a graphical user interface (GUI) and a Fiji plugin as easy-to-use frontends.Availability and implementationThe source code for YeastMate is freely available at https://github.com/hoerlteam/YeastMate under the MIT license. We offer installers for our software stack for Windows, macOS and Linux. A detailed user guide is available at https://yeastmate.readthedocs.io.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9048668 | biostudies-literature