The importance of post-translational modifications in regulating Saccharomyces cerevisiae metabolism

Tannin-Tolerant Saccharomyces cerevisiae Isolated from Traditional Fermented Tea Leaf (Miang) and Application in Fruit Wine Fermentation Using Longan Juice Mixed with Seed Extract as Substrate

This study focused on isolating tannin-tolerant yeasts from Miang, a fermented tea leaf product collected from northern Laos PDR, and investigating related food applications. From 43 Miang samples, six yeast isolates capable of ethanol production were obtained, with five isolates showing growth on YPD agar containing 4% (w/v) tannic acid. Molecular identification revealed three isolates as Saccharomyces cerevisiae (B5-1, B5-2, and C6-3), along with Candida tropicalis and Kazachstania humilis. Due to safety considerations, only Saccharomyces spp. were selected for further tannic acid tolerance study to advance food applications. Tannic acid at 1% (w/v) significantly influenced ethanol fermentation in all S. cerevisiae isolates. Notably, B5-2 and C6-3 showed high ethanol fermentation efficiency (2.5% w/v), while others were strongly inhibited. The application of tannin-tolerant yeasts in longan fruit wine (LFW) fermentation with longan seed extract (LSE) supplementation as a source of tannin revealed that C6-3 had the best efficacy for LFW fermentation. C6-3 showed promising efficacy, particularly with LSE supplementation, enhancing phenolic compounds, antioxidant activity, and inhibiting α-glucosidase activity, indicating potential antidiabetic properties. These findings underscore the potential of tannin-tolerant S. cerevisiae C6-3 for fermenting beverages from tannin-rich substrates like LSE, with implications for functional foods and nutraceuticals promoting health benefits.

IPs-GRUAtt: An attention-based bidirectional gated recurrent unit network for predicting phosphorylation sites of SARS-CoV-2 infection

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has generated tremendous concern and poses a serious threat to international public health. Phosphorylation is a common post-translational modification affecting many essential cellular processes and is inextricably linked to SARS-CoV-2 infection. Hence, accurate identification of phosphorylation sites will be helpful to understand the mechanisms of SARS-CoV-2 infection and mitigate the ongoing COVID-19 pandemic. In the present study, an attention-based bidirectional gated recurrent unit network, called IPs-GRUAtt, was proposed to identify phosphorylation sites in SARS-CoV-2-infected host cells. Comparative results demonstrated that IPs-GRUAtt surpassed both state-of-the-art machine-learning methods and existing models for identifying phosphorylation sites. Moreover, the attention mechanism made IPs-GRUAtt able to extract the key features from protein sequences. These results demonstrated that the IPs-GRUAtt is a powerful tool for identifying phosphorylation sites. For facilitating its academic use, a freely available online web server for IPs-GRUAtt is provided at http://cbcb.cdutcm.edu.cn/phosphory/.

The impact of metabolism on the adaptation of organisms to environmental change

Since Jacob and Monod's discovery of the lac operon ∼1960, the explanations offered for most metabolic adaptations have been genetic. The focus has been on the adaptive changes in gene expression that occur, which are often referred to as "metabolic reprogramming." The contributions metabolism makes to adaptation have been largely ignored. Here we point out that metabolic adaptations, including the associated changes in gene expression, are highly dependent on the metabolic state of an organism prior to the environmental change to which it is adapting, and on the plasticity of that state. In support of this hypothesis, we examine the paradigmatic example of a genetically driven adaptation, the adaptation of E. coli to growth on lactose, and the paradigmatic example of a metabolic driven adaptation, the Crabtree effect in yeast. Using a framework based on metabolic control analysis, we have reevaluated what is known about both adaptations, and conclude that knowledge of the metabolic properties of these organisms prior to environmental change is critical for understanding not only how they survive long enough to adapt, but also how the ensuing changes in gene expression occur, and their phenotypes post-adaptation. It would be useful if future explanations for metabolic adaptations acknowledged the contributions made to them by metabolism, and described the complex interplay between metabolic systems and genetic systems that make these adaptations possible.

Protein kinases on carbon metabolism: potential targets for alternative chemotherapies against toxoplasmosis

The apicomplexan parasite Toxoplasma gondii is the causative agent of toxoplasmosis, a global disease that significantly impacts human health. The clinical manifestations are mainly observed in immunocompromised patients, including ocular damage and neuronal alterations leading to psychiatric disorders. The congenital infection leads to miscarriage or severe alterations in the development of newborns. The conventional treatment is limited to the acute phase of illness, without effects in latent parasites; consequently, a cure is not available yet. Furthermore, considerable toxic effects and long-term therapy contribute to high treatment abandonment rates. The investigation of exclusive parasite pathways would provide new drug targets for more effective therapies, eliminating or reducing the side effects of conventional pharmacological approaches. Protein kinases (PKs) have emerged as promising targets for developing specific inhibitors with high selectivity and efficiency against diseases. Studies in T. gondii have indicated the presence of exclusive PKs without homologs in human cells, which could become important targets for developing new drugs. Knockout of specific kinases linked to energy metabolism have shown to impair the parasite development, reinforcing the essentiality of these enzymes in parasite metabolism. In addition, the specificities found in the PKs that regulate the energy metabolism in this parasite could bring new perspectives for safer and more efficient therapies for treating toxoplasmosis. Therefore, this review provides an overview of the limitations for reaching an efficient treatment and explores the role of PKs in regulating carbon metabolism in Toxoplasma, discussing their potential as targets for more applied and efficient pharmacological approaches.

Genetic Biodiversity and Posttranslational Modifications of Protease Serine Endopeptidase in Different Strains of Sordaria fimicola

Genetic variations (mutation, crossing over, and recombination) act as a source for the gradual alternation in phenotype along a geographic transect where the environment changes. Posttranslational modifications (PTMs) predicted modifications successfully in different and the same species of living organisms. Protein diversity of living organisms is predicted by PTMs. Environmental stresses change nucleotides to produce alternations in protein structures, and these alternations have been examined through bioinformatics tools. The goal of the current study is to search the diversity of genes and posttranslational modifications of protease serine endopeptidase in various strains of Sordaria fimicola. The S. fimicola's genomic DNA was utilized to magnify the protease serine endopeptidase (SP2) gene; the size of the product was 700 and 1400 base pairs. Neurospora crassa was taken as the reference strain for studying the multiple sequence alignment of the nucleotide sequence. Six polymorphic sites of six strains of S. fimicola with respect to N. crassa were under observation. Different bioinformatics tools, i.e., NetPhos 3.1, NetNES 1.1 Server, YinOYang1.2, and Mod Pred, to search phosphorylation sites, acetylation, nuclear export signals, O-glycosylation, and methylation, respectively, were used to predict PTMs. The findings of the current study were 35 phosphorylation sites on the residues of serine for protease SP2 in SFS and NFS strains of S. fimicola and N. crassa. The current study supported us to get the reality of genes involved in protease production in experimental fungi. Our study examined the genetic biodiversity in six strains of S. fimicola which were caused by stressful environments, and these variations are a strong reason for evolution. In this manuscript, we predicted posttranslational modifications of protease serine endopeptidase in S. fimicola obtained from different sites, for the first time, to see the effect of environmental stress on nucleotides, amino acids, and proteases and to study PTMs by using various bioinformatics tools. This research confirmed the genetic biodiversity and PTMs in six strains of S. fimicola, and the designed primers also provided strong evidence for the presence of protease serine endopeptidase in each strain of S. fimicola.

Effects of altered N-glycan structures of Cryptococcus neoformans mannoproteins, MP98 (Cda2) and MP84 (Cda3), on interaction with host cells

Cryptococcus neoformans is an opportunistic human fungal pathogen causing lethal meningoencephalitis. It has several cell wall mannoproteins (MPs) identified as immunoreactive antigens. To investigate the structure and function of N-glycans assembled on cryptococcal cell wall MPs in host cell interactions, we purified MP98 (Cda2) and MP84 (Cda3) expressed in wild-type (WT) and N-glycosylation-defective alg3 mutant (alg3Δ) strains. HPLC and MALDI-TOF analysis of the MP proteins from the WT revealed protein-specific glycan structures with different extents of hypermannosylation and xylose/xylose phosphate addition. In alg3Δ, MP98 and MP84 had truncated core N-glycans, containing mostly five and seven mannoses (M5 and M7 forms), respectively. In vitro adhesion and uptake assays indicated that the altered core N-glycans did not affect adhesion affinities to host cells although the capacity to induce the immune response of bone-marrow derived dendritic cells (BMDCs) decreased. Intriguingly, the removal of all N-glycosylation sites on MP84 increased adhesion to host cells and enhanced the induction of cytokine secretion from BMDCs compared with that on MP84 carrying WT N-glycans. Therefore, the structure-dependent effects of N-glycans suggested their complex roles in modulating the interaction of MPs with host cells to avoid nonspecific adherence to host cells and host immune response hyperactivation.

The NPR/Hal family of protein kinases in yeasts: biological role, phylogeny and regulation under environmental challenges

Protein phosphorylation is the most common and versatile post-translational modification occurring in eukaryotes. In yeast, protein phosphorylation is fundamental for maintaining cell growth and adapting to sudden changes in environmental conditions by regulating cellular processes and activating signal transduction pathways. Protein kinases catalyze the reversible addition of phosphate groups to target proteins, thereby regulating their activity. In Saccharomyces cerevisiae, kinases are classified into six major groups based on structural and functional similarities. The NPR/Hal family of kinases comprises nine fungal-specific kinases that, due to lack of similarity with the remaining kinases, were classified to the “Other” group. These kinases are primarily implicated in regulating fundamental cellular processes such as maintaining ion homeostasis and controlling nutrient transporters’ concentration at the plasma membrane. Despite their biological relevance, these kinases remain poorly characterized and explored. This review provides an overview of the information available regarding each of the kinases from the NPR/Hal family, including their known biological functions, mechanisms of regulation, and integration in signaling pathways in S. cerevisiae. Information gathered for non-Saccharomyces species of biotechnological or clinical relevance is also included.

Polypeptide N-acetylgalactosamine transferase 3: a post-translational writer on human health

Polypeptide N-acetylgalactosamine transferase 3 (ppGalNAc-T3) is an enzyme involved in the initiation of O-GalNAc glycan biosynthesis. Acting as a writer of frequent post-translational modification (PTM) on human proteins, ppGalNAc-T3 has key functions in the homeostasis of human cells and tissues. We review the relevant roles of this molecule in the biosynthesis of O-GalNAc glycans, as well as in biological functions related to human physiological and pathological conditions. With main emphasis in ppGalNAc-T3, we draw attention to the different ways involved in the modulation of ppGalNAc-Ts enzymatic activity. In addition, we take notice on recent reports of ppGalNAc-T3 having different subcellular localizations, highlight critical intrinsic and extrinsic functions in cellular physiology that are exerted by ppGalNAc-T3-synthesized PTMs, and provide an update on several human pathologies associated with dysfunctional ppGalNAc-T3. Finally, we propose biotechnological tools as new therapeutic options for the treatment of pathologies related to altered ppGalNAc-T3. KEY MESSAGES: ppGalNAc-T3 is a key enzyme in the human O-GalNAc glycans biosynthesis. enzyme activity is regulated by PTMs, lectin domain and protein-protein interactions. ppGalNAc-T3 is located in human Golgi apparatus and cell nucleus. ppGalNAc-T3 has a central role in cell physiology as well as in several pathologies. Biotechnological tools for pathological management are proposed.

Suberoylanilide Hydroxamic Acid (SAHA) Treatment Reveals Crosstalk Among Proteome, Phosphoproteome, and Acetylome in Nasopharyngeal Carcinoma Cells

Suberoylanilide hydroxamic acid (SAHA), a famous histone deacetylase (HDAC) inhibitor, has been utilized in clinical treatment for cutaneous T-cell lymphoma. Previously, the mechanisms underlying SAHA anti-tumor activity mainly focused on acetylome. However, the characteristics of SAHA in terms of other protein posttranslational modifications (PTMs) and the crosstalk between various modifications are poorly understood. Our previous work revealed that SAHA had anti-tumor activity in nasopharyngeal carcinoma (NPC) cells as well. Here, we reported the profiles of global proteome, acetylome, and phosphoproteome of 5–8 F cells upon SAHA induction and the crosstalk between these data sets. Overall, we detected and quantified 6,491 proteins, 2,456 phosphorylated proteins, and 228 acetylated proteins in response to SAHA treatment in 5–8 F cells. In addition, we identified 46 proteins exhibiting both acetylation and phosphorylation, such as WSTF and LMNA. With the aid of intensive bioinformatics analyses, multiple cellular processes and signaling pathways involved in tumorigenesis were clustered, including glycolysis, EGFR signaling, and Myc signaling pathways. Taken together, this study highlighted the interconnectivity of acetylation and phosphorylation signaling networks and suggested that SAHA-mediated HDAC inhibition may alter both acetylation and phosphorylation of viral proteins. Subsequently, cellular signaling pathways were reprogrammed and contributed to anti-tumor effects of SAHA in NPC cells.

Metabolic signatures of regulation by phosphorylation and acetylation

Acetylation and phosphorylation are highly conserved posttranslational modifications (PTMs) that regulate cellular metabolism, yet how metabolic control is shared between these PTMs is unknown. Here we analyze transcriptome, proteome, acetylome, and phosphoproteome datasets in E. coli, S. cerevisiae, and mammalian cells across diverse conditions using CAROM, a new approach that uses genome-scale metabolic networks and machine learning to classify targets of PTMs. We built a single machine learning model that predicted targets of each PTM in a condition across all three organisms based on reaction attributes (AUC>0.8). Our model predicted phosphorylated enzymes during a mammalian cell-cycle, which we validate using phosphoproteomics. Interpreting the machine learning model using game theory uncovered enzyme properties including network connectivity, essentiality, and condition-specific factors such as maximum flux that differentiate targets of phosphorylation from acetylation. The conserved and predictable partitioning of metabolic regulation identified here between these PTMs may enable rational rewiring of regulatory circuits.

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.

Deciphering the mechanism by which the yeast Phaffia rhodozyma responds adaptively to environmental, nutritional, and genetic cues

Phaffia rhodozyma is a basidiomycetous yeast that synthesizes astaxanthin (ASX), which is a powerful and highly valuable antioxidant carotenoid pigment. P. rhodozyma cells accrue ASX and gain an intense red-pink coloration when faced with stressful conditions such as nutrient limitations (e.g., nitrogen or copper), the presence of toxic substances (e.g., antimycin A), or are affected by mutations in the genes that are involved in nitrogen metabolism or respiration. Since cellular accrual of ASX occurs under a wide variety of conditions, this yeast represents a valuable model for studying the growth conditions that entail oxidative stress for yeast cells. Recently, we proposed that ASX synthesis can be largely induced by conditions that lead to reduction-oxidation (redox) imbalances, particularly the state of the NADH/NAD+ couple together with an oxidative environment. In this work, we review the multiple known conditions that elicit ASX synthesis expanding on the data that we formerly examined. When considered alongside the Mitchell's chemiosmotic hypothesis, the study served to rationalize the induction of ASX synthesis and other adaptive cellular processes under a much broader set of conditions. Our aim was to propose an underlying mechanism that explains how a broad range of divergent conditions converge to induce ASX synthesis in P. rhodozyma. The mechanism that links the induction of ASX synthesis with the occurrence of NADH/NAD+ imbalances may help in understanding how other organisms detect any of a broad array of stimuli or gene mutations, and then adaptively respond to activate numerous compensatory cellular processes.

A comprehensive tool for accurate identification of methyl-Glutamine sites

Methylation is a biochemical process involved in nearly all of the human body functions. Glutamine is considered an indispensable amino acid that is susceptible to methylation via post-translational modification (PTM). Modern research has proved that methylation plays a momentous role in the progression of most types of cancers. Therefore, there is a need for an effective method to predict glutamine sites vulnerable to methylation accurately and inexpensively. The motive of this study is the formulation of an accurate method that could predict such sites with high accuracy. Various computationally intelligent classifiers were employed for their formulation and evaluation. Rigorous validations prove that deep learning performs best as compared to other classifiers. The accuracy (ACC) and the area under the receiver operating curve (AUC) obtained by 10-fold cross-validation was 0.962 and 0.981, while with the jackknife testing, it was 0.968 and 0.980, respectively. From these results, it is concluded that the proposed methodology works sufficiently well for the prediction of methyl-glutamine sites. The webserver's code, developed for the prediction of methyl-glutamine sites, is freely available at https://github.com/s20181080001/WebServer.git. The code can easily be set up by any intermediate-level Python user.

Next-Generation Genome-Scale Metabolic Modeling through Integration of Regulatory Mechanisms

Genome-scale metabolic models (GEMs) are powerful tools for understanding metabolism from a systems-level perspective. However, GEMs in their most basic form fail to account for cellular regulation. A diverse set of mechanisms regulate cellular metabolism, enabling organisms to respond to a wide range of conditions. This limitation of GEMs has prompted the development of new methods to integrate regulatory mechanisms, thereby enhancing the predictive capabilities and broadening the scope of GEMs. Here, we cover integrative models encompassing six types of regulatory mechanisms: transcriptional regulatory networks (TRNs), post-translational modifications (PTMs), epigenetics, protein-protein interactions and protein stability (PPIs/PS), allostery, and signaling networks. We discuss 22 integrative GEM modeling methods and how these have been used to simulate metabolic regulation during normal and pathological conditions. While these advances have been remarkable, there remains a need for comprehensive and widespread integration of regulatory constraints into GEMs. We conclude by discussing challenges in constructing GEMs with regulation and highlight areas that need to be addressed for the successful modeling of metabolic regulation. Next-generation integrative GEMs that incorporate multiple regulatory mechanisms and their crosstalk will be invaluable for discovering cell-type and disease-specific metabolic control mechanisms.

Post-translational modifications of proteins associated with yeast peroxisome membrane: An essential mode of regulatory mechanism

Peroxisomes are single membrane‐bound organelles important for the optimum functioning of eukaryotic cells. Seminal discoveries in the field of peroxisomes are made using yeast as a model. Several proteins required for the biogenesis and function of peroxisomes are identified to date. As with proteins involved in other major cellular pathways, peroxisomal proteins are also subjected to regulatory post‐translational modifications. Identification, characterization and mapping of these modifications to specific amino acid residues on proteins are critical toward understanding their functional significance. Several studies have tried to identify post‐translational modifications of peroxisomal proteins and determine their impact on peroxisome structure and function. In this manuscript, we provide an overview of the various post‐translational modifications that govern the peroxisome dynamics in yeast.

Gene expression regulates metabolite homeostasis during the Crabtree effect: Implications for the adaptation and evolution of Metabolism

A key issue in both molecular and evolutionary biology has been to define the roles of genes and phenotypes in the adaptation of organisms to environmental changes. The dominant view has been that an organism's metabolic adaptations are driven by gene expression and that gene mutations, independent of the starting phenotype, are responsible for the evolution of new metabolic phenotypes. We propose an alternate hypothesis, in which the phenotype and genotype together determine metabolic adaptation both in the lifetime of the organism and in the evolutionary selection of adaptive metabolic traits. We tested this hypothesis by flux-balance and metabolic-control analysis of the relative roles of the starting phenotype and gene expression in regulating the metabolic adaptations during the Crabtree effect in yeast, when they are switched from a low- to high-glucose environment. Critical for successful short-term adaptation was the ability of the glycogen/trehalose shunt to balance the glycolytic pathway. The role of later gene expression of new isoforms of glycolytic enzymes, rather than flux control, was to provide additional homeostatic mechanisms allowing an increase in the amount and efficiency of adenosine triphosphate and product formation while maintaining glycolytic balance. We further showed that homeostatic mechanisms, by allowing increased phenotypic plasticity, could have played an important role in guiding the evolution of the Crabtree effect. Although our findings are specific to Crabtree yeast, they are likely to be broadly found because of the well-recognized similarities in glucose metabolism across kingdoms and phyla from yeast to humans.

Global coordination of metabolic pathways in Escherichia coli by active and passive regulation

Microorganisms adjust metabolic activity to cope with diverse environments. While many studies have provided insights into how individual pathways are regulated, the mechanisms that give rise to coordinated metabolic responses are poorly understood. Here, we identify the regulatory mechanisms that coordinate catabolism and anabolism in Escherichia coli. Integrating protein, metabolite, and flux changes in genetically implemented catabolic or anabolic limitations, we show that combined global and local mechanisms coordinate the response to metabolic limitations. To allocate proteomic resources between catabolism and anabolism, E. coli uses a simple global gene regulatory program. Surprisingly, this program is largely implemented by a single transcription factor, Crp, which directly activates the expression of catabolic enzymes and indirectly reduces the expression of anabolic enzymes by passively sequestering cellular resources needed for their synthesis. However, metabolic fluxes are not controlled by this regulatory program alone; instead, fluxes are adjusted mostly through passive changes in the local metabolite concentrations. These mechanisms constitute a simple but effective global regulatory program that coarsely partitions resources between different parts of metabolism while ensuring robust coordination of individual metabolic reactions.

CODY enables quantitatively spatiotemporal predictions on in vivo gut microbial variability induced by diet intervention

Quantitatively understanding and predicting spatiotemporal dynamics of microbiota is imperative for development of tailored microbiome-directed therapeutics treatments. However, the complexity of microbial variations, due to interactions with the host, other microbes, and environmental factors, makes it challenging to identify how microbiota colonize in the human gut. Here, we describe a novel multiscale framework for COmputing the DYnamics of the gut microbiota (CODY), which enables the quantification of spatiotemporal-specific variations of gut microbiome abundance profiles, without a prior knowledge of microbiome interactions. Importantly, the predictive power of CODY is demonstrated using cross-sectional data from two longitudinal metagenomics studies—the microbiota development during early infancy and during short-term diet intervention of obese adults.

Microbial variations in the human gut are harbored in temporal and spatial heterogeneity, and quantitative prediction of spatiotemporal dynamic changes in the gut microbiota is imperative for development of tailored microbiome-directed therapeutics treatments, e.g. precision nutrition. Given the high-degree complexity of microbial variations, subject to the dynamic interactions among host, microbial, and environmental factors, identifying how microbiota colonize in the gut represents an important challenge. Here we present COmputing the DYnamics of microbiota (CODY), a multiscale framework that integrates species-level modeling of microbial dynamics and ecosystem-level interactions into a mathematical model that characterizes spatial-specific in vivo microbial residence in the colon as impacted by host physiology. The framework quantifies spatiotemporal resolution of microbial variations on species-level abundance profiles across site-specific colon regions and in feces, independent of a priori knowledge. We demonstrated the effectiveness of CODY using cross-sectional data from two longitudinal metagenomics studies—the microbiota development during early infancy and during short-term diet intervention of obese adults. For each cohort, CODY correctly predicts the microbial variations in response to diet intervention, as validated by available metagenomics and metabolomics data. Model simulations provide insight into the biogeographical heterogeneity among lumen, mucus, and feces, which provides insight into how host physical forces and spatial structure are shaping microbial structure and functionality.

Mitochondrial protein phosphorylation in yeast revisited

Protein phosphorylation is one of the best-known post-translational modifications occurring in all domains of life. In eukaryotes, protein phosphorylation affects all cellular compartments including mitochondria. High-throughput techniques of mass spectrometry combined with cell fractionation and biochemical methods yielded thousands of phospho-sites on hundreds of mitochondrial proteins. We have compiled the information on mitochondrial protein kinases and phosphatases and their substrates in Saccharomyces cerevisiae and provide the current state-of-the-art overview of mitochondrial protein phosphorylation in this model eukaryote. Using several examples, we describe emerging features of the yeast mitochondrial phosphoproteome and present challenges lying ahead in this exciting field.

Tumor-associated macrophage interleukin-β promotes glycerol-3-phosphate dehydrogenase activation, glycolysis and tumorigenesis in glioma cells

Tumor-immune crosstalk within the tumor microenvironment (TME) occurs at all stages of tumorigenesis. Tumor-associated M2 macrophages play a central role in tumor development, but the molecular underpinnings have not been fully elucidated. We demonstrated that M2 macrophages produce interleukin 1β (IL-1β), which activates phosphorylation of the glycolytic enzyme glycerol-3-phosphate dehydrogenase (GPD2) at threonine 10 (GPD2 pT10) through phosphatidylinositol-3-kinase-mediated activation of protein kinase-delta (PKCδ) in glioma cells. GPD2 pT10 enhanced its substrate affinity and increased the catalytic rate of glycolysis in glioma cells. Inhibiting PKCδ or GPD2 pT10 in glioma cells or blocking IL-1β generated by macrophages attenuated the glycolytic rate and proliferation of glioma cells. Furthermore, human glioblastoma tumor GPD2 pT10 levels were positively correlated with tumor p-PKCδ and IL-1β levels as well as intratumoral macrophage recruitment, tumor grade and human glioblastoma patient survival. These results reveal a novel tumorigenic role for M2 macrophages in the TME. In addition, these findings suggest possible treatment strategies for glioma patients through blockade of cytokine crosstalk between M2 macrophages and glioma cells.

Vacuolar H+ -ATPase is involved in preventing heavy metal-induced oxidative stress in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, vacuolar H⁺ -ATPase (V-ATPase) involved in the regulation of intracellular pH homeostasis has been shown to be important for tolerances to cadmium, cobalt and nickel. However, the molecular mechanism underlying the protective role of V-ATPase against these metals remains unclear. In this study, we show that cadmium, cobalt and nickel disturbed intracellular pH balance by triggering cytosolic acidification and vacuolar alkalinization, likely via their membrane permeabilizing effects. Since V-ATPase plays a crucial role in pumping excessive cytosolic protons into the vacuole, the metal-sensitive phenotypes of the Δvma2 and Δvma3 mutants lacking V-ATPase activity were supposed to result from highly acidified cytosol. However, we found that the metal-sensitive phenotypes of these mutants were caused by increased production of reactive oxygen species, likely as a result of decreased expression and activities of manganese superoxide dismutase and catalase. In addition, the loss of V-ATPase function led to aberrant vacuolar morphology and defective endocytic trafficking. Furthermore, the sensitivities of the Δvma mutants to other chemical compounds (i.e. acetic acid, H₂ O₂ , menadione, tunicamycin and cycloheximide) were a consequence of increased endogenous oxidative stress. These findings, therefore, suggest the important role of V-ATPase in preventing endogenous oxidative stress induced by metals and other chemical compounds.

CRAF Methylation by PRMT6 Regulates Aerobic Glycolysis-Driven Hepatocarcinogenesis via ERK-Dependent PKM2 Nuclear Relocalization and Activation

BACKGROUND AND AIMS

Most tumor cells use aerobic glycolysis (the Warburg effect) to support anabolic growth and promote tumorigenicity and drug resistance. Intriguingly, the molecular mechanisms underlying this phenomenon are not well understood. In this work, using gain-of-function and loss-of-function in vitro studies in patient-derived organoid and cell cultures as well as in vivo positron emission tomography-magnetic resonance imaging animal models, we showed that protein arginine N-methyltransferase 6 (PRMT6) regulates aerobic glycolysis in human hepatocellular carcinoma (HCC) through nuclear relocalization of pyruvate kinase M2 isoform (PKM2), a key regulator of the Warburg effect.

APPROACH AND RESULTS

We found PRMT6 to methylate CRAF at arginine 100, interfering with its RAS/RAF binding potential, and therefore altering extracellular signal-regulated kinase (ERK)-mediated PKM2 translocation into the nucleus. This altered PRMT6-ERK-PKM2 signaling axis was further confirmed in both a HCC mouse model with endogenous knockout of PRMT6 as well as in HCC clinical samples. We also identified PRMT6 as a target of hypoxia through the transcriptional repressor element 1-silencing transcription factor, linking PRMT6 with hypoxia in driving glycolytic events. Finally, we showed as a proof of concept the therapeutic potential of using 2-deoxyglucose, a glycolysis inhibitor, to reverse tumorigenicity and sorafenib resistance mediated by PRMT6 deficiency in HCC.

CONCLUSIONS

Our findings indicate that the PRMT6-ERK-PKM2 regulatory axis is an important determinant of the Warburg effect in tumor cells, and provide a mechanistic link among tumorigenicity, sorafenib resistance, and glucose metabolism.

In vitro androgenesis: spontaneous vs. artificial genome doubling and characterization of regenerants

Androgenesis has become the most frequently chosen method of doubled haploid (DH) production in major crops. Theoretically, plantlets derived from in vitro cultured microspore encompass half of the normal chromosome number of donor plants and thus, considered to be haploid. However, depending on species/genotype and the method of haploid production, either via anther or isolated microspore culture, different ratios of spontaneous DHs and diploid (2n) or even polyploid plants originating from somatic tissues or unreduced gametes may also arise in the cultures. Adopting the method of haploid identification, anti-microtubular agent for restoring fertility, and discriminating spontaneous DHs from undesired heterozygote plants will substantially affect the success of androgenesis in breeding programs. The recent advances in the last 2 decades have made it possible to characterize the in vitro regenerants efficiently either prior to genome duplication or using in breeding programs. The herein described approaches and antimicotubular agents are, therefore, expected to improve the efficiency of DH-based breeding pipeline through the in vitro androgenesis.

Shot-gun proteomics: why thousands of unidentified signals matter

Mass spectrometry-based proteomics has become a constitutional part of the multi-omics toolbox in yeast research, advancing fundamental knowledge of molecular processes and guiding decisions in strain and product developmental pipelines. Nevertheless, post-translational protein modifications (PTMs) continue to challenge the field of proteomics. PTMs are not directly encoded in the genome; therefore, they require a sensitive analysis of the proteome itself. In yeast, the relevance of post-translational regulators has already been established, such as for phosphorylation, which can directly affect the reaction rates of metabolic enzymes. Whereas, the selective analysis of single modifications has become a broadly employed technique, the sensitive analysis of a comprehensive set of modifications still remains a challenge. At the same time, a large number of fragmentation spectra in a typical shot-gun proteomics experiment remain unidentified. It has been estimated that a good proportion of those unidentified spectra originates from unexpected modifications or natural peptide variants. In this review, recent advancements in microbial proteomics for unrestricted protein modification discovery are reviewed, and recent research integrating this additional layer of information to elucidate protein interaction and regulation in yeast is briefly discussed.

Rewiring of Metabolic Network in Mycobacterium tuberculosis During Adaptation to Different Stresses

Metabolic adaptation of Mycobacterium tuberculosis (M. tuberculosis) to microbicidal intracellular environment of host macrophages is fundamental to its pathogenicity. However, an in-depth understanding of metabolic adjustments through key reaction pathways and networks is limited. To understand how such changes occur, we measured the cellular metabolome of M. tuberculosis subjected to four microbicidal stresses using liquid chromatography-mass spectrometric multiple reactions monitoring (LC-MRM/MS). Overall, 87 metabolites were identified. The metabolites best describing the separation between stresses were identified through multivariate analysis. The coupling of the metabolite measurements with existing genome-scale metabolic model, and using constraint-based simulation led to several new concepts and unreported observations in M. tuberculosis; such as (i) the high levels of released ammonia as an adaptive response to acidic stress was due to increased flux through L-asparaginase rather than urease activity; (ii) nutrient starvation-induced anaplerotic pathway for generation of TCA intermediates from phosphoenolpyruvate using phosphoenolpyruvate kinase; (iii) quenching of protons through GABA shunt pathway or sugar alcohols as possible mechanisms of early adaptation to acidic and oxidative stresses; and (iv) usage of alternate cofactors by the same enzyme as a possible mechanism of rewiring metabolic pathways to overcome stresses. Besides providing new leads and important nodes that can be used for designing intervention strategies, the study advocates the strength of applying flux balance analyses coupled with metabolomics to get a global picture of complex metabolic adjustments.

Protein Complex Identification and quantitative complexome by CN-PAGE

The majority of cellular processes are carried out by protein complexes. Various size fractionation methods have previously been combined with mass spectrometry to identify protein complexes. However, most of these approaches lack the quantitative information which is required to understand how changes of protein complex abundance and composition affect metabolic fluxes. In this paper we present a proof of concept approach to quantitatively study the complexome in the model plant Arabidopsis thaliana at the end of the day (ED) and the end of the night (EN). We show that size-fractionation of native protein complexes by Clear-Native-PAGE (CN-PAGE), coupled with mass spectrometry can be used to establish abundance profiles along the molecular weight gradient. Furthermore, by deconvoluting complex protein abundance profiles, we were able to drastically improve the clustering of protein profiles. To identify putative interaction partners, and ultimately protein complexes, our approach calculates the Euclidian distance between protein profile pairs. Acceptable threshold values are based on a cut-off that is optimized by a receiver-operator characteristic (ROC) curve analysis. Our approach shows low technical variation and can easily be adapted to study in the complexome in any biological system.

Identification of Down-Regulated Proteome in Saccharomyces cerevisiae with the Deletion of Yeast Cathepsin D in Response to Nitrogen Stress

Vacuolar proteinase A (Pep4p) is required for the post-translational precursor maturation of vacuolar proteinases in Saccharomyces cerevisiae, and important for protein turnover after oxidative damage. The presence of proteinase A in brewing yeast leads to the decline of beer foam stability, thus the deletion or inhibition of Pep4p is generally used. However, the influence of Pep4p deletion on cell metabolism in Saccharomyces cerevisiae is still unclear. Herein, we report the identification of differentially down-regulated metabolic proteins in the absence of Pep4p by a comparative proteomics approach. 2D-PAGE (two-dimensional polyacrylamide gel electrophoresis) presented that the number of significantly up-regulated spots (the Pep4p-deficient species versus the wild type) was 183, whereas the down-regulated spots numbered 111. Among them, 35 identified proteins were differentially down-regulated more than 10-fold in the Pep4p-deficient compared to the wild-type species. The data revealed that Pep4p was required for the synthesis and maturation of several glycolytic enzymes and stress proteins, including Eno2p, Fba1p, Pdc1p, Tpi1p, Ssa1, Hsp82p, and Trr1p. The transcription and post-translational modifications of glycolytic enzymes like Eno2p and Fba1p were sensitive to the absence of Pep4p; whereas the depletion of the pep4 gene had a negative impact on mitochondrial and other physiological functions. The finding of this study provides a systematic understanding that Pep4p may serve as a regulating factor for cell physiology and metabolic processes in S. cerevisiae under a nitrogen stress environment.

Identification, characterization, and expressions profile analysis of growth hormone receptors (GHR1 and GHR2) in Hybrid grouper (Epinephelus fuscoguttatus ♀ × Epinephelus polyphekadion ♂)

Growth hormone is an essential hormone that plays essential roles in growth, metabolism, cellular differentiation, immunity and reproduction in fish, by means of the growth hormone receptors. The encoding cDNA growth hormone receptors (GHR1 and GHR2) were cloned and characterized from Hybrid grouper (Epinephelus fuscoguttatus♀ × Epinephelus polyphekadion♂). Sequence analysis of the cloned GHR1 was observed as containing 2176, which comprised an ORF of 1842 bp, 5 UTR of 6 bp and 3 UTR of 328 bp, with 612 amino acids encoding proteins, while GHR2 was observed as containing 1824 bp that encompassed an ORF of 708 bp, 5 UTR of 48 bp and 3 UTR of 1068 bp with 235 amino acids encoding proteins. Relative mRNA expression of GHR1 and GHR2 in the liver and muscle was found to be highest respectively. Our findings provide vital statistics of GHRs likely to play a significant role in the growth of the fish.

Niche-specific metabolic adaptation in biotrophic and necrotrophic oomycetes is manifested in differential use of nutrients, variation in gene content, and enzyme evolution

The use of host nutrients to support pathogen growth is central to disease. We addressed the relationship between metabolism and trophic behavior by comparing metabolic gene expression during potato tuber colonization by two oomycetes, the hemibiotroph Phytophthora infestans and the necrotroph Pythium ultimum. Genes for several pathways including amino acid, nucleotide, and cofactor biosynthesis were expressed more by Ph. infestans during its biotrophic stage compared to Py. ultimum. In contrast, Py. ultimum had higher expression of genes for metabolizing compounds that are normally sequestered within plant cells but released to the pathogen upon plant cell lysis, such as starch and triacylglycerides. The transcription pattern of metabolic genes in Ph. infestans during late infection became more like that of Py. ultimum, consistent with the former's transition to necrotrophy. Interspecific variation in metabolic gene content was limited but included the presence of γ-amylase only in Py. ultimum. The pathogens were also found to employ strikingly distinct strategies for using nitrate. Measurements of mRNA, ¹⁵N labeling studies, enzyme assays, and immunoblotting indicated that the assimilation pathway in Ph. infestans was nitrate-insensitive but induced during amino acid and ammonium starvation. In contrast, the pathway was nitrate-induced but not amino acid-repressed in Py. ultimum. The lack of amino acid repression in Py. ultimum appears due to the absence of a transcription factor common to fungi and Phytophthora that acts as a nitrogen metabolite repressor. Evidence for functional diversification in nitrate reductase protein was also observed. Its temperature optimum was adapted to each organism's growth range, and its K_m was much lower in Py. ultimum. In summary, we observed divergence in patterns of gene expression, gene content, and enzyme function which contribute to the fitness of each species in its niche.

A key feature of disease is the pathogen's consumption of host metabolites to support its growth and multiplication. Understanding how host nutrients are used by pathogens may lead to strategies for limiting disease, for example by developing inhibitors of metabolic pathways needed for pathogen growth. Feeding strategies of plant pathogens range between two extremes: necrotrophs kill host cells and consume the released nutrients, while biotrophs do not injure host cells but instead acquire nutrients from extracellular spaces in the plant. In this study, a comparison was made between the metabolism of Phytophthora infestans (the infamous Irish Famine pathogen) and Pythium ultimum during potato tuber colonization. These microbes have close evolutionary histories, but while Py. ultimum is a necrotroph, Ph. infestans is a biotroph for most of the disease cycle. It was discovered that distinct patterns of metabolic gene expression, gene content, and enzyme behavior underlie these lifestyles. For example, genes for utilizing compounds that are normally stored within plant cells were expressed more by Py. ultimum, while Ph. infestans appeared to synthesize more biosubstances from precursors. Several differences in carbon and nitrogen metabolism were linked to variation in enzyme content and gene expression regulators in the two species.

Macrophage-Associated PGK1 Phosphorylation Promotes Aerobic Glycolysis and Tumorigenesis

Macrophages are a dominant leukocyte population in the tumor microenvironment and actively promote cancer progression. However, the molecular mechanism underlying the role of macrophages remains poorly understood. Here we show that polarized M2 macrophages enhance 3-phosphoinositide-dependent protein kinase 1 (PDPK1)-mediated phosphoglycerate kinase 1 (PGK1) threonine (T) 243 phosphorylation in tumor cells by secreting interleukin-6 (IL-6). This phosphorylation facilitates a PGK1-catalyzed reaction toward glycolysis by altering substrate affinity. Inhibition of PGK1 T243 phosphorylation or PDPK1 in tumor cells or neutralization of macrophage-derived IL-6 abrogates macrophage-promoted glycolysis, proliferation, and tumorigenesis. In addition, PGK1 T243 phosphorylation correlates with PDPK1 activation, IL-6 expression, and macrophage infiltration in human glioblastoma multiforme (GBM). Moreover, PGK1 T243 phosphorylation also correlates with malignance and prognosis of human GBM. Our findings demonstrate a novel mechanism of macrophage-promoted tumor growth by regulating tumor cell metabolism, implicating the therapeutic potential to disrupt the connection between macrophages and tumor cells by inhibiting PGK1 phosphorylation.

Tyrosine phosphorylation activates 6-phosphogluconate dehydrogenase and promotes tumor growth and radiation resistance

6-Phosphogluconate dehydrogenase (6PGD) is a key enzyme that converts 6-phosphogluconate into ribulose-5-phosphate with NADP⁺ as cofactor in the pentose phosphate pathway (PPP). 6PGD is commonly upregulated and plays important roles in many human cancers, while the mechanism underlying such roles of 6PGD remains elusive. Here we show that upon EGFR activation, 6PGD is phosphorylated at tyrosine (Y) 481 by Src family kinase Fyn. This phosphorylation enhances 6PGD activity by increasing its binding affinity to NADP⁺ and therefore activates the PPP for NADPH and ribose-5-phosphate, which consequently detoxifies intracellular reactive oxygen species (ROS) and accelerates DNA synthesis. Abrogating 6PGD Y481 phosphorylation (pY481) dramatically attenuates EGF-promoted glioma cell proliferation, tumor growth and resistance to ionizing radiation. In addition, 6PGD pY481 is associated with Fyn expression, the malignancy and prognosis of human glioblastoma. These findings establish a critical role of Fyn-dependent 6PGD phosphorylation in EGF-promoted tumor growth and radiation resistance.

6-phosphogluconate dehydrogenase is commonly upregulated in cancers. Here, the authors show that activation of EGFR induces phosphorylation of this enzyme at Y481 to activate the pentose phosphate pathway, which consequently reduces ROS and accelerates DNA synthesis to promote tumor growth and radioresistance.

Purification and characterization of a urea sensitive lactate dehydrogenase from skeletal muscle of the African clawed frog, Xenopus laevis

The African clawed frog, Xenopus laevis endures whole body dehydration which can increase its reliance on anaerobic glycolysis for energy production. This makes the regulation of the terminal enzyme of glycolysis, lactate dehydrogenase (LDH), crucial to stress survival. We investigated the enzymatic properties and posttranslational modification state of purified LDH from the skeletal muscle of control and dehydrated (30% total body water loss) X. laevis. LDH from the muscle of dehydrated frogs showed a 93% reduction in phosphorylation on threonine residues and an 80% reduction of protein nitrosylation. LDH from dehydrated muscle also showed a 74% lower V_max in the pyruvate oxidizing direction and a 78% decrease in V_max in the lactate reducing direction along with a 33% lower K_m for pyruvate and a 40% higher K_m for lactate. In the presence of higher levels of urea and molecular crowding by polyethylene glycol, used to mimic conditions in the cells of dehydrated animals, the K_m values of control and dehydrated LDH demonstrated opposite responses. In the pyruvate oxidizing direction, control muscle LDH was unaffected by these additives, whereas the affinity for pyruvate dropped further for LDH from dehydrated muscle. The opposite effect was more pronounced in the lactate reducing direction as control LDH showed an increased affinity for lactate, whereas LDH from dehydrated animals showed a further reduction in affinity. The physiological consequences of dehydration-induced LDH regulation appear to poise the enzyme towards lactate production when urea levels are high and lactate catabolism when urea levels are low, perhaps helping to maintain glycolysis under dehydrating conditions whilst providing for the ability to recycle lactate upon rehydration.

Predicting bacterial growth conditions from mRNA and protein abundances

Cells respond to changing nutrient availability and external stresses by altering the expression of individual genes. Condition-specific gene expression patterns may thus provide a promising and low-cost route to quantifying the presence of various small molecules, toxins, or species-interactions in natural environments. However, whether gene expression signatures alone can predict individual environmental growth conditions remains an open question. Here, we used machine learning to predict 16 closely-related growth conditions using 155 datasets of E. coli transcript and protein abundances. We show that models are able to discriminate between different environmental features with a relatively high degree of accuracy. We observed a small but significant increase in model accuracy by combining transcriptome and proteome-level data, and we show that measurements from stationary phase cells typically provide less useful information for discriminating between conditions as compared to exponentially growing populations. Nevertheless, with sufficient training data, gene expression measurements from a single species are capable of distinguishing between environmental conditions that are separated by a single environmental variable.

Post-translational modifications in MeHg-induced neurotoxicity

Mercury (Hg) exposure remains a major public health concern due to its widespread distribution in the environment. Organic mercurials, such as MeHg, have been extensively investigated especially because of their congenital effects. In this context, studies on the molecular mechanism of MeHg-induced neurotoxicity are pivotal to the understanding of its toxic effects and the development of preventive measures. Post-translational modifications (PTMs) of proteins, such as phosphorylation, ubiquitination, and acetylation are essential for the proper function of proteins and play important roles in the regulation of cellular homeostasis. The rapid and transient nature of many PTMs allows efficient signal transduction in response to stress. This review summarizes the current knowledge of PTMs in MeHg-induced neurotoxicity, including the most commonly PTMs, as well as PTMs induced by oxidative stress and PTMs of antioxidant proteins. Though PTMs represent an important molecular mechanism for maintaining cellular homeostasis and are involved in the neurotoxic effects of MeHg, we are far from understanding the complete picture on their role, and further research is warranted to increase our knowledge of PTMs in MeHg-induced neurotoxicity.

Microenvironmental control of glucose metabolism in tumors by regulation of pyruvate dehydrogenase

During malignant progression cancer cells undergo a series of changes, which promote their survival, invasiveness and metastatic process. One of them is a change in glucose metabolism. Unlike normal cells, which mostly rely on the tricarboxylic acid cycle (TCA), many cancer types rely on glycolysis. Pyruvate dehydrogenase complex (PDC) is the gatekeeper enzyme between these two pathways and is responsible for converting pyruvate to acetyl-CoA, which can then be processed further in the TCA cycle. Its activity is regulated by PDP (pyruvate dehydrogenase phosphatases) and PDHK (pyruvate dehydrogenase kinases). Pyruvate dehydrogenase kinase exists in 4 tissue specific isoforms (PDHK1-4), the activities of which are regulated by different factors, including hormones, hypoxia and nutrients. PDHK1 and PDHK3 are active in the hypoxic tumor microenvironment and inhibit PDC, resulting in a decrease of mitochondrial function and activation of the glycolytic pathway. High PDHK1/3 expression is associated with worse prognosis in patients, which makes them a promising target for cancer therapy. However, a better understanding of PDC's enzymatic regulation in vivo and of the mechanisms of PDHK-mediated malignant progression is necessary for the design of better PDHK inhibitors and the selection of patients most likely to benefit from such inhibitors.

Targeting posttranslational modifications of RIOK1 inhibits the progression of colorectal and gastric cancers

RIOK1 has recently been shown to play important roles in cancers, but its posttranslational regulation is largely unknown. Here we report that RIOK1 is methylated at K411 by SETD7 methyltransferase and that lysine-specific demethylase 1 (LSD1) reverses its methylation. The mutated RIOK1 (K411R) that cannot be methylated exhibits a longer half-life than does the methylated RIOK1. FBXO6 specifically interacts with K411-methylated RIOK1 through its FBA domain to induce RIOK1 ubiquitination. Casein kinase 2 (CK2) phosphorylates RIOK1 at T410, which stabilizes RIOK1 by antagonizing K411 methylation and impeding the recruitment of FBXO6 to RIOK1. Functional experiments demonstrate the RIOK1 methylation reduces the tumor growth and metastasis in mice model. Importantly, the protein levels of CK2 and LSD1 show an inverse correlation with FBXO6 and SETD7 expression in human colorectal cancer tissues. Together, this study highlights the importance of a RIOK1 methylation-phosphorylation switch in determining colorectal and gastric cancer development.

In vivo protein allylation to capture protein methylation candidates

An approach combining in vivo protein allylation, chemical tagging and affinity enrichment was devised to capture protein methylation candidates in yeast S. cerevisiae. The study identified 167 hits, covering many proteins with known methylation events on different types of amino acid residues.

Curated protein information in the Saccharomyces genome database

Due to recent advancements in the production of experimental proteomic data, the Saccharomyces genome database (SGD; www.yeastgenome.org) has been expanding our protein curation activities to make new data types available to our users. Because of broad interest in post-translational modifications (PTM) and their importance to protein function and regulation, we have recently started incorporating expertly curated PTM information on individual protein pages. Here we also present the inclusion of new abundance and protein half-life data obtained from high-throughput proteome studies. These new data types have been included with the aim to facilitate cellular biology research.

Database URL: www.yeastgenome.org

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community's traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.

Estimating the total number of phosphoproteins and phosphorylation sites in eukaryotic proteomes

Background

Phosphorylation is the most frequent post-translational modification made to proteins and may regulate protein activity as either a molecular digital switch or a rheostat. Despite the cornucopia of high-throughput (HTP) phosphoproteomic data in the last decade, it remains unclear how many proteins are phosphorylated and how many phosphorylation sites (p-sites) can exist in total within a eukaryotic proteome. We present the first reliable estimates of the total number of phosphoproteins and p-sites for four eukaryotes (human, mouse, Arabidopsis, and yeast).

Results

In all, 187 HTP phosphoproteomic datasets were filtered, compiled, and studied along with two low-throughput (LTP) compendia. Estimates of the number of phosphoproteins and p-sites were inferred by two methods: Capture-Recapture, and fitting the saturation curve of cumulative redundant vs. cumulative non-redundant phosphoproteins/p-sites. Estimates were also adjusted for different levels of noise within the individual datasets and other confounding factors. We estimate that in total, 13 000, 11 000, and 3000 phosphoproteins and 230 000, 156 000, and 40 000 p-sites exist in human, mouse, and yeast, respectively, whereas estimates for Arabidopsis were not as reliable.

Conclusions

Most of the phosphoproteins have been discovered for human, mouse, and yeast, while the dataset for Arabidopsis is still far from complete. The datasets for p-sites are not as close to saturation as those for phosphoproteins. Integration of the LTP data suggests that current HTP phosphoproteomics appears to be capable of capturing 70 % to 95 % of total phosphoproteins, but only 40 % to 60 % of total p-sites.

Flux control through protein phosphorylation in yeast

Protein phosphorylation is one of the most important mechanisms regulating metabolism as it can directly modify metabolic enzymes by the addition of phosphate groups. Attributed to such a rapid and reversible mechanism, cells can adjust metabolism rapidly in response to temporal changes. The yeast Saccharomyces cerevisiae, a widely used cell factory and model organism, is reported to show frequent phosphorylation events in metabolism. Studying protein phosphorylation in S. cerevisiae allows for gaining new insight into the function of regulatory networks, which may enable improved metabolic engineering as well as identify mechanisms underlying human metabolic diseases. Here we collect functional phosphorylation events of 41 enzymes involved in yeast metabolism and demonstrate functional mechanisms and the application of this information in metabolic engineering. From a systems biology perspective, we describe the development of phosphoproteomics in yeast as well as approaches to analysing the phosphoproteomics data. Finally, we focus on integrated analyses with other omics data sets and genome-scale metabolic models. Despite the advances, future studies improving both experimental technologies and computational approaches are imperative to expand the current knowledge of protein phosphorylation in S. cerevisiae.

Integrative proteomics and biochemical analyses define Ptc6p as the Saccharomyces cerevisiae pyruvate dehydrogenase phosphatase

The pyruvate dehydrogenase complex (PDC) is the primary metabolic checkpoint connecting glycolysis and mitochondrial oxidative phosphorylation and is important for maintaining cellular and organismal glucose homeostasis. Phosphorylation of the PDC E1 subunit was identified as a key inhibitory modification in bovine tissue ∼50 years ago, and this regulatory process is now known to be conserved throughout evolution. Although Saccharomyces cerevisiae is a pervasive model organism for investigating cellular metabolism and its regulation by signaling processes, the phosphatase(s) responsible for activating the PDC in S. cerevisiae has not been conclusively defined. Here, using comparative mitochondrial phosphoproteomics, analyses of protein-protein interactions by affinity enrichment-mass spectrometry, and in vitro biochemistry, we define Ptc6p as the primary PDC phosphatase in S. cerevisiae Our analyses further suggest additional substrates for related S. cerevisiae phosphatases and describe the overall phosphoproteomic changes that accompany mitochondrial respiratory dysfunction. In summary, our quantitative proteomics and biochemical analyses have identified Ptc6p as the primary-and likely sole-S. cerevisiae PDC phosphatase, closing a key knowledge gap about the regulation of yeast mitochondrial metabolism. Our findings highlight the power of integrative omics and biochemical analyses for annotating the functions of poorly characterized signaling proteins.

The Pivotal Role of Protein Phosphorylation in the Control of Yeast Central Metabolism

Protein phosphorylation is the most frequent eukaryotic post-translational modification and can act as either a molecular switch or rheostat for protein functions. The deliberate manipulation of protein phosphorylation has great potential for regulating specific protein functions with surgical precision, rather than the gross effects gained by the over/underexpression or complete deletion of a protein-encoding gene. In order to assess the impact of phosphorylation on central metabolism, and thus its potential for biotechnological and medical exploitation, a compendium of highly confident protein phosphorylation sites (p-sites) for the model organism Saccharomyces cerevisiae has been analyzed together with two more datasets from the fungal pathogen Candida albicans. Our analysis highlights the global properties of the regulation of yeast central metabolism by protein phosphorylation, where almost half of the enzymes involved are subject to this sort of post-translational modification. These phosphorylated enzymes, compared to the nonphosphorylated ones, are more abundant, regulate more reactions, have more protein–protein interactions, and a higher fraction of them are ubiquitinated. The p-sites of metabolic enzymes are also more conserved than the background p-sites, and hundreds of them have the potential for regulating metabolite production. All this integrated information has allowed us to prioritize thousands of p-sites in terms of their potential phenotypic impact. This multi-source compendium should enable the design of future high-throughput (HTP) mutation studies to identify key molecular switches/rheostats for the manipulation of not only the metabolism of yeast, but also that of many other biotechnologically and medically important fungi and eukaryotes.

Untargeted metabolomics unravels functionalities of phosphorylation sites in Saccharomyces cerevisiae

Background

Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection.

Results

Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics. We show that metabolomics largely outperforms growth analysis and recovers 10 out of the 13 previously characterized phosphosites and suggests functionality for several novel sites, including S79 on the TOR regulatory protein Tip41. We analyze metabolic profiles to identify consequences underlying regulatory phosphorylation events and detecting glycerol metabolism to have a so far unknown influence on arginine metabolism via phosphoregulation of the glycerol dehydrogenases. Further, we also find S508 in the MAPKK Pbs2 as a potential link for cross-talking between HOG signaling and the cell wall integrity pathway.

Conclusions

We demonstrate that metabolic profiles can be exploited for gaining insight into regulatory consequences and biological roles of phosphosites. Altogether, untargeted metabolomics is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of phosphosites.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0350-8) contains supplementary material, which is available to authorized users.

Modulation of gluconeogenesis and lipid production in an engineered oleaginous Saccharomyces cerevisiae transformant

We previously created an oleaginous Saccharomyces cerevisiae transformant as a dga1 mutant overexpressing Dga1p lacking 29 amino acids at the N-terminal (Dga1∆Np). Because we have already shown that dga1 disruption decreases the expression of ESA1, which encodes histone acetyltransferase, the present study was aimed at exploring how Esa1p was involved in lipid accumulation. We based our work on the previous observation that Esa1p acetylates and activates phosphoenolpyruvate carboxykinase (PEPCK) encoded by PCK1, a rate-limiting enzyme in gluconeogenesis, and subsequently evaluated the activation of Pck1p by yeast growth with non-fermentable carbon sources, thus dependent on gluconeogenesis. This assay revealed that the ∆dga1 mutant overexpressing Dga1∆Np had much lower growth in a glycerol-lactate (GL) medium than the wild-type strain overexpressing Dga1∆Np. Moreover, overexpression of Esa1p or Pck1p in mutants improved the growth, indicating that the ∆dga1 mutant overexpressing Dga1∆Np had lower activities of Pck1p and gluconeogenesis due to lower expression of ESA1. In vitro PEPCK assay showed the same trend in the culture of the ∆dga1 mutant overexpressing Dga1∆Np with 10 % glucose medium, indicating that Pck1p-mediated gluconeogenesis decreased in this oleaginous transformant under the lipid-accumulating conditions introduced by the glucose medium. The growth of the ∆dga1 mutant overexpressing Dga1∆Np in the GL medium was also improved by overexpression of acetyl-CoA synthetase, Acs1p or Acs2p, indicating that supply of acetyl-CoA was crucial for Pck1p acetylation by Esa1p. In addition, the ∆dga1 mutant without Dga1∆Np also showed better growth in the GL medium, indicating that decreased lipid accumulation was enhancing Pck1p-mediated gluconeogenesis. Finally, we found that overexpression of Ole1p, a fatty acid ∆9-desaturase, in the ∆dga1 mutant overexpressing Dga1∆Np improved its growth in the GL medium. Although the exact mechanisms leading to the effects of Ole1p were not clearly defined, changes of palmitoleic and oleic acid contents appeared to be critical. This observation was supported by experiments using exogenous palmitoleic and oleic acids or overexpression of elongases. Our findings provide new insights on lipid accumulation mechanisms and metabolic engineering approaches for lipid production.

Systematic Identification of Protein-Metabolite Interactions in Complex Metabolite Mixtures by Ligand-Detected Nuclear Magnetic Resonance Spectroscopy

Protein-metabolite interactions play a vital role in the regulation of numerous cellular processes. Consequently, identifying such interactions is a key prerequisite for understanding cellular regulation. However, the noncovalent nature of the binding between proteins and metabolites has so far hampered the development of methods for systematically mapping protein-metabolite interactions. The few available, largely mass spectrometry-based, approaches are restricted to specific metabolite classes, such as lipids. In this study, we address this issue and show the potential of ligand-detected nuclear magnetic resonance (NMR) spectroscopy, which is routinely used in drug development, to systematically identify protein-metabolite interactions. As a proof of concept, we selected four well-characterized bacterial and mammalian proteins (AroG, Eno, PfkA, and bovine serum albumin) and identified metabolite binders in complex mixes of up to 33 metabolites. Ligand-detected NMR captured all of the reported protein-metabolite interactions, spanning a full range of physiologically relevant Kd values (low micromolar to low millimolar). We also detected a number of novel interactions, such as promiscuous binding of the negatively charged metabolites citrate, AMP, and ATP, as well as binding of aromatic amino acids to AroG protein. Using in vitro enzyme activity assays, we assessed the functional relevance of these novel interactions in the case of AroG and show that l-tryptophan, l-tyrosine, and l-histidine act as novel inhibitors of AroG activity. Thus, we conclude that ligand-detected NMR is suitable for the systematic identification of functionally relevant protein-metabolite interactions.

Sugar and Glycerol Transport in Saccharomyces cerevisiae

In Saccharomyces cerevisiae the process of transport of sugar substrates into the cell comprises a complex network of transporters and interacting regulatory mechanisms. Members of the large family of hexose (HXT) transporters display uptake efficiencies consistent with their environmental expression and play physiological roles in addition to feeding the glycolytic pathway. Multiple glucose-inducing and glucose-independent mechanisms serve to regulate expression of the sugar transporters in yeast assuring that expression levels and transporter activity are coordinated with cellular metabolism and energy needs. The expression of sugar transport activity is modulated by other nutritional and environmental factors that may override glucose-generated signals. Transporter expression and activity is regulated transcriptionally, post-transcriptionally and post-translationally. Recent studies have expanded upon this suite of regulatory mechanisms to include transcriptional expression fine tuning mediated by antisense RNA and prion-based regulation of transcription. Much remains to be learned about cell biology from the continued analysis of this dynamic process of substrate acquisition.