Yeast increases glycolytic flux to support higher growth rates accompanied by decreased metabolite regulation and lower protein phosphorylation

Supply of Gibbs free energy and precursors are vital for cellular function and cell metabolism have evolved to be tightly regulated to balance their supply and consumption. Precursors and Gibbs free energy are generated in the central carbon metabolism (CCM), and fluxes through these pathways are precisely regulated. However, how fluxes through CCM pathways are affected by posttranslational modification and allosteric regulation remains poorly understood. Here, we integrated multi-omics data collected under nine different chemostat conditions to explore how fluxes in the CCM are regulated in the yeast Saccharomyces cerevisiae. We deduced a pathway- and metabolism-specific CCM flux regulation mechanism using hierarchical analysis combined with mathematical modeling. We found that increased glycolytic flux associated with an increased specific growth rate was accompanied by a decrease in flux regulation by metabolite concentrations, including the concentration of allosteric effectors, and a decrease in the phosphorylation level of glycolytic enzymes

Proteome allocations change linearly with the specific growth rate of Saccharomyces cerevisiae under glucose limitation

Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis. Understanding how yeast organizes its functional proteome is a fundamental task in systems biology. Here, the authors conduct a multiomics analysis on yeast cells cultured with different growth rates, identifying a linear dependence of the functional proteome on the growth rate

Flux regulation through glycolysis and respiration is balanced by inositol pyrophosphates in yeast

Although many prokaryotes have glycolysis alternatives, it\u27s considered as the only energy-generating glucose catabolic pathway in eukaryotes. Here, we managed to create a hybrid-glycolysis yeast. Subsequently, we identified an inositol pyrophosphatase encoded by OCA5 that could regulate glycolysis and respiration by adjusting 5-diphosphoinositol 1,2,3,4,6-pentakisphosphate (5-InsP7) levels. 5-InsP7 levels could regulate the expression of genes involved in glycolysis and respiration, representing a global mechanism that could sense ATP levels and regulate central carbon metabolism. The hybrid-glycolysis yeast did not produce ethanol during growth under excess glucose and could produce 2.68 g/L free fatty acids, which is the highest reported production in shake flask of Saccharomyces cerevisiae. This study demonstrated the significance of hybrid-glycolysis yeast and determined Oca5 as an inositol pyrophosphatase controlling the balance between glycolysis and respiration, which may shed light on the role of inositol pyrophosphates in regulating eukaryotic metabolism

Adenovirus-mediated stromal cell-derived factor-1 alpha gene transfer improves cardiac structure and function after experimental myocardial infarction through angiogenic and antifibrotic actions

Stromal cell-derived factor 1α (SDF-1) is not only a major chemotactic factor, but also an inducer of angiogenesis. The effects of SDF-1α on the left ventricular remodeling in a rat myocardial infarction (MI) model were analyzed. Myocardial infarction was induced by ligation of the left coronary artery in rats. 0.5 × 1010 pfu/ml AdV-SDF-1 or 0.5 × 1010 pfu/ml Adv-LacZ were immediately injected into the infarcted myocardium, 120 μl cell-free PBS were injected into the infarcted region or the myocardial wall in control, and sham group, respectively. We found that AdV-SDF-1 group had higher LVSP and ±dP/dtmax, lower LVEDP compared to control or Adv-LacZ group. The number of c-Kit+ stem cells, and gene expression of SDF-1, VEGF and bFGF were obviously increased, which was associated with reduced infarct size, thicker left ventricle wall, greater vascular density and cardiocytes density in infarcted hearts of AdV-SDF-1 group. Furthermore, the expression of collagen type I and type III mRNA, and collagen accumulation in the infarcted area was lower, which was associated with decreased TGF-β1, TIMP-1 and TIMP-2 expression in AdV-SDF-1 group. Conclusion: SDF-1α could improve cardiac structure and function after Myocardial infarction through angiogenic and anti-fibrotic actions

Solvability of a Class of Generalized Neumann Boundary Value Problems for Second-Order Nonlinear Difference Equations

This paper is motivated by Rachnkovab and Tisdell (2006) and Anderson et al. (2007). New sufficient conditions for the existence of at least one solution of the generalized Neumann boundary value problems for second order nonlinear difference equations ∇Δx(k)=f(k,x(k),x(k+1)), k∈[1,n−1], x(0)=ax(1), x(n)=bx(n−1), are established

The Impact of Systems Biology on Bioprocessing

Bioprocessing offers a sustainable and green approach to the production of chemicals. However, a bottleneck in introducing bioprocesses is cell factory development, which is costly and time-consuming. A systems biology approach can expedite cell factory design by using genome-wide analyses alongside mathematical modeling to characterize and predict cellular physiology. This approach can drive cycles of design, build, test, and learn implemented by metabolic engineers to optimize the cell factory performance. Streamlining of the design phase requires a clearer understanding of metabolism and its regulation, which can be achieved using quantitative and integrated omic characterization, alongside more advanced analytical methods. We discuss here the current impact of systems biology and challenges of closing the gap between bioprocessing and more traditional methods of chemical production

Multi-omics analyses of the transition to the Crabtree effect in S. cerevisiae reveals a key role for the citric acid shuttle

The article investigates the Crabtree effect under dynamic process which have never been reported, and find the citric acid shuttles to support higher demand of alpha-ketoglutarate under Crabtree effect. The Crabtree effect in the yeast, Saccharomyces cerevisiae, has been extensively studied, but only few studies have analyzed the dynamic conditions across the critical specific growth rate where the Crabtree effect sets in. Here, we carried out a multi-omics analysis of S. cerevisiae undergoing a specific growth rate transition from 0.2 h(-1) to 0.35 h(-1). The extracellular metabolome, the transcriptome and the proteome were analyzed in an 8-h transition period after the specific growth rate shifted from 0.2 h(-1) to 0.35 h(-1). The changing trends of both the transcriptome and proteome were analyzed using principal component analysis, which showed that the transcriptome clustered together after 60 min, while the proteome reached steady-state much later. Focusing on central carbon metabolism, we analyzed both the changes in the transcriptome and proteome, and observed an interesting changing pattern in the tricarboxylic acid (TCA) pathway, which indicates an important role for citric acid shuttling across the mitochondrial membrane for alpha-ketoglutarate accumulation during the transition from respiratory to respiro-fermentative metabolism. This was supported by a change in the oxaloacetate and malate shuttle. Together, our findings shed new light into the onset of the Crabtree effect in S. cerevisiae

Construction and testing of Yarrowia lipolytica recombinant protein expression chassis cells based on the high-throughput screening and secretome

Abstract Background In the recombinant protein market with broad economic value, the rapid development of synthetic biology has made it necessary to construct an efficient exocrine expression system for the different heterologous proteins. Yarrowia lipolytica possesses unique advantages in nascent protein transport and glycosylation modification, so it can serve as a potential protein expression platform. Although the Po1 series derived from W29 is often used for the expression of the various heterologous proteins, the ability of W29 to secrete proteins has not been verified and the Po1 series has been found to be not convenient for further gene editing. Results A total of 246 Y. lipolytica strains were evaluated for their secretory capacity through performing high-throughput screening in 48-well plate. Thereafter, following two rounds of shake flask re-screening, a high-secreting protein starting strain DBVPG 5851 was obtained. Subsequently, combined with the extracellular protein types and relative abundance information provided by the secretome of the starting strain, available chassis cell for heterologous protein expression were preliminarily constructed, and it was observed that the most potential signal peptide was derived from YALI0D20680g. Conclusions This study offers a novel perspective on the diversification of Y. lipolytica host cells for the heterologous protein expression and provides significant basis for expanding the selection space of signal peptide tools in the future research