Phosphoglycerate mutase knock-out mutant Saccharomyces cerevisiae: Physiological investigation and transcriptome analysis

John PC, Kumar N. Bayesian Inference for Integrating Yarrowia lipolytica Multiomics Datasets with Metabolic Modeling

Optimizing the metabolism of microbial cell factories for yields and titers is a critical step for economically viable production of bioproducts and biofuels. In this process, tuning the expression of individual enzymes to obtain the desired pathway flux is a challenging step, in which data from separate multiomics techniques must be integrated with existing biological knowledge to determine where changes should be made. Following a design-build-test-learn strategy, building on recent advances in Bayesian metabolic control analysis, we identify key enzymes in the oleaginous yeast Yarrowia lipolytica that correlate with the production of itaconate by integrating a metabolic model with multiomics measurements. To this extent, we quantify the uncertainty for a variety of key parameters, known as flux control coefficients (FCCs), needed to improve the bioproduction of target metabolites and statistically obtain key correlations between the measured enzymes and boundary flux. Based on the top five significant FCCs and five correlated enzymes, our results show phosphoglycerate mutase, acetyl-CoA synthetase (ACSm), carbonic anhydrase (HCO3E), pyrophosphatase (PPAm), and homoserine dehydrogenase (HSDxi) enzymes in rate-limiting reactions that can lead to increased itaconic acid production.

Construction of engineered RuBisCO Kluyveromyces marxianus for a dual microbial bioethanol production system

Ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO) genes play important roles in CO₂ fixation and redox balancing in photosynthetic bacteria. In the present study, the kefir yeast Kluyveromyces marxianus 4G5 was used as host for the transformation of form I and form II RubisCO genes derived from the nonsulfur purple bacterium Rhodopseudomonas palustris using the Promoter-based Gene Assembly and Simultaneous Overexpression (PGASO) method. Hungateiclostridium thermocellum ATCC 27405, a well-known bacterium for its efficient solubilization of recalcitrant lignocellulosic biomass, was used to degrade Napier grass and rice straw to generate soluble fermentable sugars. The resultant Napier grass and rice straw broths were used as growth media for the engineered K. marxianus. In the dual microbial system, H. thermocellum degraded the biomass feedstock to produce both C₅ and C₆ sugars. As the bacterium only used hexose sugars, the remaining pentose sugars could be metabolized by K. marxianus to produce ethanol. The transformant RubisCO K. marxianus strains grew well in hydrolyzed Napier grass and rice straw broths and produced bioethanol more efficiently than the wild type. Therefore, these engineered K. marxianus strains could be used with H. thermocellum in a bacterium-yeast coculture system for ethanol production directly from biomass feedstocks.

Kluyveromyces marxianus: Current State of Omics Studies, Strain Improvement Strategy and Potential Industrial Implementation

Bioethanol is considered an excellent alternative to fossil fuels, since it importantly contributes to the reduced consumption of crude oil, and to the alleviation of environmental pollution. Up to now, the baker yeast Saccharomyces cerevisiae is the most common eukaryotic microorganism used in ethanol production. The inability of S. cerevisiae to grow on pentoses, however, hinders its effective growth on plant biomass hydrolysates, which contain large amounts of C5 and C12 sugars. The industrial-scale bioprocessing requires high temperature bioreactors, diverse carbon sources, and the high titer production of volatile compounds. These criteria indicate that the search for alternative microbes possessing useful traits that meet the required standards of bioethanol production is necessary. Compared to other yeasts, Kluyveromyces marxianus has several advantages over others, e.g., it could grow on a broad spectrum of substrates (C5, C6 and C12 sugars); tolerate high temperature, toxins, and a wide range of pH values; and produce volatile short-chain ester. K. marxianus also shows a high ethanol production rate at high temperature and is a Crabtree-negative species. These attributes make K. marxianus promising as an industrial host for the biosynthesis of biofuels and other valuable chemicals.

Triosephosphates as Intermediates of the Crabtree Effect

An increase in glucose concentration in the medium rapidly decreases respiration rate in many cell types, including tumor cells. The molecular mechanism of this phenomenon, the Crabtree effect, is still unclear. It was shown earlier that adding the intermediate product of glycolysis fructose-1,6-bisphosphate to isolated mitochondria suppresses their respiration. To study possible roles of glycolytic intermediates in the Crabtree effect, we used a model organism, the yeast Saccharomyces cerevisiae. To have the option to rapidly increase intracellular concentrations of certain glycolytic intermediates, we used mutant cells with glycolysis blocked at different stages. We studied fast effects of glucose addition on the respiration rate in such cells. We found that addition of glucose affected cells with deleted phosphoglycerate mutase (strain gpm1-delta) more strongly than ones with inactivated aldolase or phosphofructokinase. In the case of preincubation of gpm1-delta cells with 2-deoxyglucose, which blocks glycolysis at the stage of 2-deoxyglucosephosphate formation, the effect of glucose addition was absent. This suggests that triosephosphates are intermediates of the Crabtree effect. Apart from this, the incubation of gpm1-delta cells in galactose-containing medium appeared to cause a large increase in their size. It was previously shown that galactose addition did not have any short-term effect on respiration rate of gpm1-delta cells and, at the same time, strongly suppressed their growth rate. Apparently, the influence of increasing triosephosphate concentration on yeast physiology is not limited to the activation of the Crabtree effect.

Negative Feedback of Glycolysis and Oxidative Phosphorylation: Mechanisms of and Reasons for It

There are two main pathways of ATP biosynthesis: glycolysis and oxidative phosphorylation. As a rule, the two pathways are not fully active in a single cell. In this review, we discuss mechanisms of glycolytic inhibition of respiration (Warburg and Crabtree effects). What are the reasons for the existence of this negative feedback? It is known that maximal activation of both processes can cause generation of reactive oxygen species. Oxidative phosphorylation is more efficient from the energy point of view, while glycolysis is safer and favors biomass synthesis. This might be the reason why quiescent cells are mainly using oxidative phosphorylation, while the quickly proliferating ones - glycolysis.

Transcriptional analysis of Kluyveromyces marxianus for ethanol production from inulin using consolidated bioprocessing technology

BACKGROUND

Ethanol production from non-crop materials, such as Jerusalem artichokes, would make a great contribution to the energy industry. The non-conventional yeast, Kluyveromyces marxianus, is able to carry out ethanol fermentation of sugar molecules obtained from inulin-containing materials by consolidated bioprocessing. Lower inulin concentrations and micro-aeration can lead to a relatively fast and ideal fermentation process; however, it is unclear what causes the inhibition of higher concentrations of inulin and the promotion effect of aeration.

RESULTS

Next-generation sequencing technology was used to study the global transcriptional response of K. marxianus Y179 under three fermentation conditions, including 120 g/L inulin without aeration (120-N), 230 g/L inulin without aeration (230-N), 230 g/L inulin with aeration by ORP controlling at -130 mV (230-130mV). A total of 35.55 million clean reads were generated from three samples, of which 4,820 predicted that open reading frames were annotated. For differential expression analysis, 950 and 1,452 differentially expressed genes were discovered under the conditions of 230-130mV and 120-N, respectively, and the sample 230-N was used as the control. These genes are mainly associated with the pathways of central carbon metabolism and ethanol formation. Increased expression of inulinase and the low activity of the autophagy-related gene, ATG8, ensured fast and ideal fermentation processes.

CONCLUSIONS

Despite being reported as the "crabtree-negative" species, K. marxianus Y179 could achieve favorable ethanol fermentation profiles under micro-aeration and high inulin concentrations. K. marxianus Y179 cells responded to inulin concentrations and micro-aeration that is involved in the whole ethanol metabolism network. These results will serve as an important foundation for further exploration of the regulatory mechanisms involved in ethanol fermentation from inulin by consolidated bioprocessing and also provide a valuable reference for future studies on optimization and reconstruction of the metabolism network in K. marxianus.

Flux-coupled genes and their use in metabolic flux analysis

As large volumes of omics data have become available, systems biology is playing increasingly important roles in elucidating new biological phenomena, especially through genome-scale metabolic network modeling and simulation. Much effort has been exerted on integrating omics data with metabolic flux simulation, but further development is necessary for more accurate flux estimation. To move one step forward, we adopted the concept of flux-coupled genes (FCGs), which show that their expression transition patterns upon perturbations are correlated with their corresponding flux values, as additional constraints in metabolic flux analysis. It was found that gnd, pfkB, rpe, sdhB, sdhD, sucA, and zwf genes, mostly associated with pentose phosphate pathway and TCA cycle, were the most consistent FCGs in Escherichia coli based on its transcriptome and (13) C-flux data obtained from the chemostat cultivation at five different dilution rates. Consequently, constraints-based flux analyses with FCGs as additional constraints were conducted for the seven single-gene knockout mutants, compared with those obtained without using FCGs. This strategy of constraining the metabolic flux analysis with FCGs is expected to be useful due to the relative ease in obtaining transcriptional information in the functional genomics era.

Evolutionary significance of metabolic network properties

Complex networks have been successfully employed to represent different levels of biological systems, ranging from gene regulation to protein–protein interactions and metabolism. Network-based research has mainly focused on identifying unifying structural properties, such as small average path length, large clustering coefficient, heavy-tail degree distribution and hierarchical organization, viewed as requirements for efficient and robust system architectures. However, for biological networks, it is unclear to what extent these properties reflect the evolutionary history of the represented systems. Here, we show that the salient structural properties of six metabolic networks from all kingdoms of life may be inherently related to the evolution and functional organization of metabolism by employing network randomization under mass balance constraints. Contrary to the results from the common Markov-chain switching algorithm, our findings suggest the evolutionary importance of the small-world hypothesis as a fundamental design principle of complex networks. The approach may help us to determine the biologically meaningful properties that result from evolutionary pressure imposed on metabolism, such as the global impact of local reaction knockouts. Moreover, the approach can be applied to test to what extent novel structural properties can be used to draw biologically meaningful hypothesis or predictions from structure alone.

Fifteen years of large scale metabolic modeling of yeast: developments and impacts

Since the first large-scale reconstruction of the Saccharomyces cerevisiae metabolic network 15 years ago the development of yeast metabolic models has progressed rapidly, resulting in no less than nine different yeast genome-scale metabolic models. Here we review the historical development of large-scale mathematical modeling of yeast metabolism and the growing scope and impact of applications of these models in four different areas: as guide for metabolic engineering and strain improvement, as a tool for biological interpretation and discovery, applications of novel computational framework and for evolutionary studies.