scholarly journals Stress tolerance enhancement via SPT15 base editing in Saccharomyces cerevisiae

2021 ◽  
Author(s):  
Yanfang Liu ◽  
Yuping Lin ◽  
Yufeng Guo ◽  
Fengli Wu ◽  
Yuanyuan Zhang ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Stress Tolerance ◽  
Rna Polymerase Ii ◽  
Convex Surface ◽  
Cytidine Deaminase ◽  
Structure Alignment ◽  
Protein Structure Alignment ◽  
Base Editing ◽  
And Performance

Abstract Background Saccharomyces cerevisiae is widely used in traditional brewing and modern fermentation industries to produce biofuels, chemicals and other bioproducts, but challenged by various harsh industrial conditions, such as hyperosmotic, thermal and ethanol stresses. Thus, its stress tolerance enhancement has been attracting broad interests. Recently, CRISPR/Cas-based genome editing technology offers unprecedented tools to explore genetic modifications and performance improvement of S. cerevisiae. Results Here, we presented that the Target-AID (activation-induced cytidine deaminase) base editor of enabling C-to-T substitutions could be harnessed to generate in situ nucleotide changes on the S. cerevisiae genome, thereby introducing protein point mutation in cells. The general transcription factor gene SPT15 was targeted, and total 36 mutants with diversified stress tolerances were obtained. Among them, the 18 tolerant mutants against hyperosmotic, thermal and ethanol stresses showed more than 1.5-fold increases of fermentation capacities. These mutations were mainly enriched at the N-terminal region and the convex surface of the saddle-shaped structure of Spt15. Comparative transcriptome analysis of three most stress-tolerant (A140G, P169A and R238K) and two most stress-sensitive (S118L and L214V) mutants revealed common and distinctive impacted global transcription reprogramming and transcriptional regulatory hubs in response to stresses, and these five amino acid changes had different effects on the interactions of Spt15 with DNA and other proteins in the RNA Polymerase II transcription machinery according to protein structure alignment analysis. Conclusions Taken together, our results demonstrated that the Target-AID base editor provided a powerful tool for targeted in situ mutagenesis in S. cerevisiae and more potential targets of Spt15 residues for enhancing yeast stress tolerance.

scholarly journals Stress tolerance enhancement via SPT15 base editing in Saccharomyces cerevisiae

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yanfang Liu ◽  
Yuping Lin ◽  
Yufeng Guo ◽  
Fengli Wu ◽  
Yuanyuan Zhang ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Stress Tolerance ◽  
Rna Polymerase Ii ◽  
Convex Surface ◽  
Cytidine Deaminase ◽  
Point Mutations ◽  
Structure Alignment ◽  
Protein Structure Alignment ◽  
Base Editing

Abstract Background Saccharomyces cerevisiae is widely used in traditional brewing and modern fermentation industries to produce biofuels, chemicals and other bioproducts, but challenged by various harsh industrial conditions, such as hyperosmotic, thermal and ethanol stresses. Thus, its stress tolerance enhancement has been attracting broad interests. Recently, CRISPR/Cas-based genome editing technology offers unprecedented tools to explore genetic modifications and performance improvement of S. cerevisiae. Results Here, we presented that the Target-AID (activation-induced cytidine deaminase) base editor of enabling C-to-T substitutions could be harnessed to generate in situ nucleotide changes on the S. cerevisiae genome, thereby introducing protein point mutations in cells. The general transcription factor gene SPT15 was targeted, and total 36 mutants with diversified stress tolerances were obtained. Among them, the 18 tolerant mutants against hyperosmotic, thermal and ethanol stresses showed more than 1.5-fold increases of fermentation capacities. These mutations were mainly enriched at the N-terminal region and the convex surface of the saddle-shaped structure of Spt15. Comparative transcriptome analysis of three most stress-tolerant (A140G, P169A and R238K) and two most stress-sensitive (S118L and L214V) mutants revealed common and distinctive impacted global transcription reprogramming and transcriptional regulatory hubs in response to stresses, and these five amino acid changes had different effects on the interactions of Spt15 with DNA and other proteins in the RNA Polymerase II transcription machinery according to protein structure alignment analysis. Conclusions Taken together, our results demonstrated that the Target-AID base editor provided a powerful tool for targeted in situ mutagenesis in S. cerevisiae and more potential targets of Spt15 residues for enhancing yeast stress tolerance.

scholarly journals The influence of chemical parameters on the in-situ metal carbonyl complex formation studied with the fast on-line reaction apparatus (FORA)

2021 ◽  
Vol 109 (4) ◽  
pp. 243-260 ◽  
Author(s):  
Yves Wittwer ◽  
Robert Eichler ◽  
Dominik Herrmann ◽  
Andreas Türler
Keyword(s):  
Metal Carbonyl ◽  
Ambient Air ◽  
Single Atom ◽  
Carbonyl Complex ◽  
Carbonyl Complexes ◽  
On Line ◽  
Carrier Gases ◽  
And Performance ◽  
Atom Chemistry

Abstract A new setup named Fast On-line Reaction Apparatus (FORA) is presented which allows for the efficient investigation and optimization of metal carbonyl complex (MCC) formation reactions under various reaction conditions. The setup contains a 252Cf-source producing short-lived Mo, Tc, Ru and Rh isotopes at a rate of a few atoms per second by its 3% spontaneous fission decay branch. Those atoms are transformed within FORA in-situ into volatile metal carbonyl complexes (MCCs) by using CO-containing carrier gases. Here, the design, operation and performance of FORA is discussed, revealing it as a suitable setup for performing single-atom chemistry studies. The influence of various gas-additives, such as CO2, CH4, H2, Ar, O2, H2O and ambient air, on the formation and transport of MCCs was investigated. O2, H2O and air were found to harm the formation and transport of MCCs in FORA, with H2O being the most severe. An exception is Tc, for which about 130 ppmv of H2O caused an increased production and transport of volatile compounds. The other gas-additives were not influencing the formation and transport efficiency of MCCs. Using an older setup called Miss Piggy based on a similar working principle as FORA, it was additionally investigated if gas-additives are mostly affecting the formation or only the transport stability of MCCs. It was found that mostly formation is impacted, as MCCs appear to be much less sensitive to reacting with gas-additives in comparison to the bare Mo, Tc, Ru and Rh atoms.

scholarly journals Spatially Resolved Experimental Modal Analysis on High-Speed Composite Rotors Using a Non-Contact, Non-Rotating Sensor

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4705
Author(s):  
Julian Lich ◽  
Tino Wollmann ◽  
Angelos Filippatos ◽  
Maik Gude ◽  
Juergen Czarske ◽  
...  
Keyword(s):  
High Speed ◽  
Natural Frequencies ◽  
Mode Shapes ◽  
Fiber Reinforced ◽  
Structural Dynamic ◽  
Spatially Resolved ◽  
Glass Fiber Reinforced ◽  
Vibration Responses ◽  
And Performance

Due to their lightweight properties, fiber-reinforced composites are well suited for large and fast rotating structures, such as fan blades in turbomachines. To investigate rotor safety and performance, in situ measurements of the structural dynamic behaviour must be performed during rotating conditions. An approach to measuring spatially resolved vibration responses of a rotating structure with a non-contact, non-rotating sensor is investigated here. The resulting spectra can be assigned to specific locations on the structure and have similar properties to the spectra measured with co-rotating sensors, such as strain gauges. The sampling frequency is increased by performing consecutive measurements with a constant excitation function and varying time delays. The method allows for a paradigm shift to unambiguous identification of natural frequencies and mode shapes with arbitrary rotor shapes and excitation functions without the need for co-rotating sensors. Deflection measurements on a glass fiber-reinforced polymer disk were performed with a diffraction grating-based sensor system at 40 measurement points with an uncertainty below 15 μrad and a commercial triangulation sensor at 200 measurement points at surface speeds up to 300 m/s. A rotation-induced increase of two natural frequencies was measured, and their mode shapes were derived at the corresponding rotational speeds. A strain gauge was used for validation.

scholarly journals New Strategies to Overcome Present CRISPR/Cas9 Limitations in Apple and Pear: Efficient Dechimerization and Base Editing

2020 ◽  
Vol 22 (1) ◽  
pp. 319
Author(s):  
Jaiana Malabarba ◽  
Elisabeth Chevreau ◽  
Nicolas Dousset ◽  
Florian Veillet ◽  
Julie Moizan ◽  
...  
Keyword(s):  
Target Genes ◽  
Cytidine Deaminase ◽  
Acetolactate Synthase ◽  
Nucleotide Substitutions ◽  
Discrete Variation ◽  
Adventitious Regeneration ◽  
Base Editing ◽  
Perennial Plants ◽  
Guide Rnas ◽  
Albino Phenotype

Despite recent progress, the application of CRISPR/Cas9 in perennial plants still has many obstacles to overcome. Our previous results with CRISPR/Cas9 in apple and pear indicated the frequent production of phenotypic and genotypic chimeras, after editing of the phytoene desaturase (PDS) gene conferring albino phenotype. Therefore, our first objective was to determine if adding an adventitious regeneration step from leaves of the primary transgenic plants (T0) would allow a reduction in chimerism. Among hundreds of adventitious buds regenerated from a variegated T0 line, 89% were homogeneous albino. Furthermore, the analysis of the target zone sequences of twelve of these regenerated lines (RT0 for “regenerated T0” lines) indicated that 99% of the RT0 alleles were predicted to produce a truncated target protein and that 67% of RT0 plants had less heterogeneous editing profiles than the T0. Base editors are CRISPR/Cas9-derived new genome-editing tools that allow precise nucleotide substitutions without double-stranded breaks. Hence, our second goal was to demonstrate the feasibility of CRISPR/Cas9 base editing in apple and pear using two easily scorable genes: acetolactate synthase—ALS (conferring resistance to chlorsulfuron) and PDS. The two guide RNAs under MdU3 and MdU6 promoters were coupled into a cytidine base editor harboring a cytidine deaminase fused to a nickase Cas9. Using this vector; we induced C-to-T DNA substitutions in the target genes; leading to discrete variation in the amino-acid sequence and generating new alleles. By co-editing ALS and PDS genes; we successfully obtained chlorsulfuron resistant and albino lines in pear. Overall; our work indicates that a regeneration step can efficiently reduce the initial chimerism and could be coupled with the application of base editing to create accurate genome edits in perennial plants.

scholarly journals Underproduction of the Largest Subunit of RNA Polymerase II Causes Temperature Sensitivity, Slow Growth, and Inositol Auxotrophy in Saccharomyces cerevisiae

Genetics ◽  
1996 ◽  
Vol 142 (3) ◽  
pp. 737-747 ◽  
Author(s):  
Jacques Archambault ◽  
David B Jansma ◽  
James D Friesen
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Steady State ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Reporter Gene ◽  
Growth Medium ◽  
Temperature Sensitivity ◽  
Slow Growth ◽  
Yeast Saccharomyces Cerevisiae ◽  
Genes Encoding

Abstract In the yeast Saccharomyces cerevisiae, mutations in genes encoding subunits of RNA polymerase II (RNAPII) often give rise to a set of pleiotropic phenotypes that includes temperature sensitivity, slow growth and inositol auxotrophy. In this study, we show that these phenotypes can be brought about by a reduction in the intracellular concentration of RNAPII. Underproduction of RNAPII was achieved by expressing the gene (RPO21), encoding the largest subunit of the enzyme, from the LEU2 promoter or a weaker derivative of it, two promoters that can be repressed by the addition of leucine to the growth medium. We found that cells that underproduced RPO21 were unable to derepress fully the expression of a reporter gene under the control of the INO1 UAS. Our results indicate that temperature sensitivity, slow growth and inositol auxotrophy is a set of phenotypes that can be caused by lowering the steady-state amount of RNAPII; these results also lead to the prediction that some of the previously identified RNAPII mutations that confer this same set of phenotypes affect the assembly/stability of the enzyme. We propose a model to explain the hypersensitivity of INO1 transcription to mutations that affect components of the RNAPII transcriptional machinery.

scholarly journals The rye Mutants Identify a Role for Ssn/Srb Proteins of the RNA Polymerase II Holoenzyme During Stationary Phase Entry in Saccharomyces cerevisiae

Genetics ◽  
2001 ◽  
Vol 157 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Ya-Wen Chang ◽  
Susie C Howard ◽  
Yelena V Budovskaya ◽  
Jasper Rine ◽  
Paul K Herman
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Cell Growth ◽  
Rna Polymerase ◽  
Stationary Phase ◽  
Yeast Cell ◽  
Rna Polymerase Ii ◽  
Transcriptional Response ◽  
Nutrient Deprivation ◽  
Ras Signaling ◽  
Rna Polymerase Ii Holoenzyme

Abstract Saccharomyces cerevisiae cells enter into a distinct resting state, known as stationary phase, in response to specific types of nutrient deprivation. We have identified a collection of mutants that exhibited a defective transcriptional response to nutrient limitation and failed to enter into a normal stationary phase. These rye mutants were isolated on the basis of defects in the regulation of YGP1 expression. In wild-type cells, YGP1 levels increased during the growth arrest caused by nutrient deprivation or inactivation of the Ras signaling pathway. In contrast, the levels of YGP1 and related genes were significantly elevated in the rye mutants during log phase growth. The rye defects were not specific to this YGP1 response as these mutants also exhibited multiple defects in stationary phase properties, including an inability to survive periods of prolonged starvation. These data indicated that the RYE genes might encode important regulators of yeast cell growth. Interestingly, three of the RYE genes encoded the Ssn/Srb proteins, Srb9p, Srb10p, and Srb11p, which are associated with the RNA polymerase II holoenzyme. Thus, the RNA polymerase II holoenzyme may be a target of the signaling pathways responsible for coordinating yeast cell growth with nutrient availability.

scholarly journals Screening and Genetic Network Analysis of Genes Involved in Freezing and Thawing Resistance in DaMDHAR—Expressing Saccharomyces cerevisiae Using Gene Expression Profiling

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 219
Author(s):  
Il-Sup Kim ◽  
Woong Choi ◽  
Jonghyeon Son ◽  
Jun Hyuck Lee ◽  
Hyoungseok Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Transcription Factors ◽  
Stress Tolerance ◽  
Genetic Network ◽  
Yeast Cells ◽  
Enzymatic Antioxidants ◽  
Freezing And Thawing ◽  
Metal Ion Homeostasis ◽  
Transgenic Yeast

The cryoprotection of cell activity is a key determinant in frozen-dough technology. Although several factors that contribute to freezing tolerance have been reported, the mechanism underlying the manner in which yeast cells respond to freezing and thawing (FT) stress is not well established. Therefore, the present study demonstrated the relationship between DaMDHAR encoding monodehydroascorbate reductase from Antarctic hairgrass Deschampsia antarctica and stress tolerance to repeated FT cycles (FT2) in transgenic yeast Saccharomyces cerevisiae. DaMDHAR-expressing yeast (DM) cells identified by immunoblotting analysis showed high tolerance to FT stress conditions, thereby causing lower damage for yeast cells than wild-type (WT) cells with empty vector alone. To detect FT2 tolerance-associated genes, 3′-quant RNA sequencing was employed using mRNA isolated from DM and WT cells exposed to FT (FT2) conditions. Approximately 332 genes showed ≥2-fold changes in DM cells and were classified into various groups according to their gene expression. The expressions of the changed genes were further confirmed using western blot analysis and biochemical assay. The upregulated expression of 197 genes was associated with pentose phosphate pathway, NADP metabolic process, metal ion homeostasis, sulfate assimilation, β-alanine metabolism, glycerol synthesis, and integral component of mitochondrial and plasma membrane (PM) in DM cells under FT2 stress, whereas the expression of the remaining 135 genes was partially related to protein processing, selenocompound metabolism, cell cycle arrest, oxidative phosphorylation, and α-glucoside transport under the same condition. With regard to transcription factors in DM cells, MSN4 and CIN5 were activated, but MSN2 and MGA1 were not. Regarding antioxidant systems and protein kinases in DM cells under FT stress, CTT1, GTO, GEX1, and YOL024W were upregulated, whereas AIF1, COX2, and TRX3 were not. Gene activation represented by transcription factors and enzymatic antioxidants appears to be associated with FT2-stress tolerance in transgenic yeast cells. RCK1, MET14, and SIP18, but not YPK2, have been known to be involved in the protein kinase-mediated signalling pathway and glycogen synthesis. Moreover, SPI18 and HSP12 encoding hydrophilin in the PM were detected. Therefore, it was concluded that the genetic network via the change of gene expression levels of multiple genes contributing to the stabilization and functionality of the mitochondria and PM, not of a single gene, might be the crucial determinant for FT tolerance in DaMDAHR-expressing transgenic yeast. These findings provide a foundation for elucidating the DaMDHAR-dependent molecular mechanism of the complex functional resistance in the cellular response to FT stress.

scholarly journals Identification of abnormal tribological regimes using a microphone and semi-supervised machine-learning algorithm

Friction ◽  
2021 ◽  
Author(s):  
Vigneashwara Pandiyan ◽  
Josef Prost ◽  
Georg Vorlaufer ◽  
Markus Varga ◽  
Kilian Wasmer
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Industrial Applications ◽  
Supervised Machine Learning ◽  
Normal Operation ◽  
Promising Alternative ◽  
Wear And Tear ◽  
Validation Procedure ◽  
And Performance

AbstractFunctional surfaces in relative contact and motion are prone to wear and tear, resulting in loss of efficiency and performance of the workpieces/machines. Wear occurs in the form of adhesion, abrasion, scuffing, galling, and scoring between contacts. However, the rate of the wear phenomenon depends primarily on the physical properties and the surrounding environment. Monitoring the integrity of surfaces by offline inspections leads to significant wasted machine time. A potential alternate option to offline inspection currently practiced in industries is the analysis of sensors signatures capable of capturing the wear state and correlating it with the wear phenomenon, followed by in situ classification using a state-of-the-art machine learning (ML) algorithm. Though this technique is better than offline inspection, it possesses inherent disadvantages for training the ML models. Ideally, supervised training of ML models requires the datasets considered for the classification to be of equal weightage to avoid biasing. The collection of such a dataset is very cumbersome and expensive in practice, as in real industrial applications, the malfunction period is minimal compared to normal operation. Furthermore, classification models would not classify new wear phenomena from the normal regime if they are unfamiliar. As a promising alternative, in this work, we propose a methodology able to differentiate the abnormal regimes, i.e., wear phenomenon regimes, from the normal regime. This is carried out by familiarizing the ML algorithms only with the distribution of the acoustic emission (AE) signals captured using a microphone related to the normal regime. As a result, the ML algorithms would be able to detect whether some overlaps exist with the learnt distributions when a new, unseen signal arrives. To achieve this goal, a generative convolutional neural network (CNN) architecture based on variational auto encoder (VAE) is built and trained. During the validation procedure of the proposed CNN architectures, we were capable of identifying acoustics signals corresponding to the normal and abnormal wear regime with an accuracy of 97% and 80%. Hence, our approach shows very promising results for in situ and real-time condition monitoring or even wear prediction in tribological applications.

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