Protein-Metabolite Interactions Shape Cellular Metabolism and Physiology.

Protein-metabolite interactions regulate many important cellular processes but still remain understudied. Recent technological advancements are gradually uncovering the complexity of the protein-metabolite interactome. Here, we highlight some classic and recent examples of how protein metabolite interactions regulate metabolism, both locally and globally, and how this contributes to cellular physiology. We also discuss the importance of these interactions in diseases such as cancer.

When yeast cells change their mind: cell cycle "Start" is reversible under starvation.

Eukaryotic cells decide in late G1 phase of the cell cycle whether to commit to another round of division. This point of cell cycle commitment is termed "Restriction Point" in mammals and "Start" in the budding yeast Saccharomyces cerevisiae. At Start, yeast cells integrate multiple signals such as pheromones and nutrients, and will not pass Start if nutrients are lacking. However, how cells respond to nutrient depletion after the Start decision remains poorly understood. Here, we analyze how post-Start cells respond to nutrient depletion, by monitoring Whi5, the cell cycle inhibitor whose export from the nucleus determines Start. Surprisingly, we find that cells that have passed Start can re-import Whi5 into the nucleus. In these cells, the positive feedback loop activating G1/S transcription is interrupted, and the Whi5 repressor re-binds DNA. Cells which re-import Whi5 become again sensitive to mating pheromone, like pre-Start cells, and CDK activation can occur a second time upon replenishment of nutrients. These results demonstrate that upon starvation, the commitment decision at Start can be reversed. We therefore propose that cell cycle commitment in yeast is a multi-step process, similar to what has been suggested for mammalian cells.

Rewiring of the protein-protein-metabolite interactome during the diauxic shift in yeast.

In budding yeast Saccharomyces cerevisiae, the switch from aerobic fermentation to respiratory growth is separated by a period of growth arrest, known as the diauxic shift, accompanied by a significant metabolic rewiring, including the derepression of gluconeogenesis and the establishment of mitochondrial respiration. Previous studies reported hundreds of proteins and tens of metabolites accumulating differentially across the diauxic shift transition. To assess the differences in the protein-protein (PPIs) and protein-metabolite interactions (PMIs) yeast samples harvested in the glucose-utilizing, fermentative phase, ethanol-utilizing and early stationary respiratory phases were analysed using isothermal shift assay (iTSA) and a co-fractionation mass spectrometry approach, PROMIS. Whereas iTSA monitors changes in protein stability and is informative towards protein interaction status, PROMIS uses co-elution to delineate putative PPIs and PMIs. The resulting dataset comprises 1627 proteins and 247 metabolites, hundreds of proteins and tens of metabolites characterized by differential thermal stability and/or fractionation profile, constituting a novel resource to be mined for the regulatory PPIs and PMIs. The examples discussed here include (i) dissociation of the core and regulatory particle of the proteasome in the early stationary phase, (ii) the differential binding of a co-factor pyridoxal phosphate to the enzymes of amino acid metabolism and (iii) the putative, phase-specific interactions between proline-containing dipeptides and enzymes of central carbon metabolism.

Live cell microscopy: From image to insight.

Live-cell microscopy is a powerful tool that can reveal cellular behavior as well as the underlying molecular processes. A key advantage of microscopy is that by visualizing biological processes, it can provide direct insights. Nevertheless, live-cell imaging can be technically challenging and prone to artifacts. For a successful experiment, many careful decisions are required at all steps from hardware selection to downstream image analysis. Facing these questions can be particularly intimidating due to the requirement for expertise in multiple disciplines, ranging from optics, biophysics, and programming to cell biology. In this review, we aim to summarize the key points that need to be considered when setting up and analyzing a live-cell imaging experiment. While we put a particular focus on yeast, many of the concepts discussed are applicable also to other organisms. In addition, we discuss reporting and data sharing strategies that we think are critical to improve reproducibility in the field.

Global mapping of protein-metabolite interactions in Saccharomyces cerevisiae reveals that Ser-Leu dipeptide regulates phosphoglycerate kinase activity.

Protein-metabolite interactions are of crucial importance for all cellular processes but remain understudied. Here, we applied a biochemical approach named PROMIS, to address the complexity of the protein-small molecule interactome in the model yeast Saccharomyces cerevisiae. By doing so, we provide a unique dataset, which can be queried for interactions between 74 small molecules and 3982 proteins using a user-friendly interface available at https://promis.mpimp-golm.mpg.de/yeastpmi/ . By interpolating PROMIS with the list of predicted protein-metabolite interactions, we provided experimental validation for 225 binding events. Remarkably, of the 74 small molecules co-eluting with proteins, 36 were proteogenic dipeptides. Targeted analysis of a representative dipeptide, Ser-Leu, revealed numerous protein interactors comprising chaperones, proteasomal subunits, and metabolic enzymes. We could further demonstrate that Ser-Leu binding increases activity of a glycolytic enzyme phosphoglycerate kinase (Pgk1). Consistent with the binding analysis, Ser-Leu supplementation leads to the acute metabolic changes and delays timing of a diauxic shift. Supported by the dipeptide accumulation analysis our work attests to the role of Ser-Leu as a metabolic regulator at the interface of protein degradation and central metabolism.

Regulation of trehalase activity by multi-site phosphorylation and 14-3-3 interaction.

Protein phosphorylation enables a rapid adjustment of cellular activities to diverse intracellular and environmental stimuli. Many phosphoproteins are targeted on more than one site, which allows the integration of multiple signals and the implementation of complex responses. However, the hierarchy and interplay between multiple phospho-sites are often unknown. Here, we study multi-site phosphorylation using the yeast trehalase Nth1 and its activator, the 14-3-3 protein Bmh1, as a model. Nth1 is known to be phosphorylated by the metabolic kinase PKA on four serine residues and by the cell cycle kinase CDK on one residue. However, how these five phospho-sites adjust Nth1 activity remains unclear. Using a novel reporter construct, we investigated the contribution of the individual sites for the regulation of the trehalase and its 14-3-3 interactor. In contrast to the constitutively phosphorylated S20 and S83, the weaker sites S21 and S60 are only phosphorylated by increased PKA activity. For binding Bmh1, S83 functions as the high-affinity "gatekeeper" site, but successful binding of the Bmh1 dimer and thus Nth1 activation requires S60 as a secondary site. Under nutrient-poor conditions with low PKA activity, S60 is not efficiently phosphorylated and the cell cycle dependent phosphorylation of S66 by Cdk1 contributes to Nth1 activity, likely by providing an alternative Bmh1 binding site. Additionally, the PKA sites S20 and S21 modulate the dephosphorylation of Nth1 on downstream Bmh1 sites. In summary, our results expand our molecular understanding of Nth1 regulation and provide a new aspect of the interaction of 14-3-3 proteins with their targets.

Multiple Layers of Phospho-Regulation Coordinate Metabolism and the Cell Cycle in Budding Yeast.

The coordination of metabolism and growth with cell division is crucial for proliferation. While it has long been known that cell metabolism regulates the cell division cycle, it is becoming increasingly clear that the cell division cycle also regulates metabolism. In budding yeast, we previously showed that over half of all measured metabolites change concentration through the cell cycle indicating that metabolic fluxes are extensively regulated during cell cycle progression. However, how this regulation is achieved still remains poorly understood. Since both the cell cycle and metabolism are regulated to a large extent by protein phosphorylation, we here decided to measure the phosphoproteome through the budding yeast cell cycle. Specifically, we chose a cell cycle synchronization strategy that avoids stress and nutrient-related perturbations of metabolism, and we grew the yeast on ethanol minimal medium to force cells to utilize their full biosynthetic repertoire. Using a tandem-mass-tagging approach, we found over 200 sites on metabolic enzymes and transporters to be phospho-regulated. These sites were distributed among many pathways including carbohydrate catabolism, lipid metabolism, and amino acid synthesis and therefore likely contribute to changing metabolic fluxes through the cell cycle. Among all one thousand sites whose phosphorylation increases through the cell cycle, the CDK consensus motif and an arginine-directed motif were highly enriched. This arginine-directed R-R-x-S motif is associated with protein-kinase A, which regulates metabolism and promotes growth. Finally, we also found over one thousand sites that are dephosphorylated through the G1/S transition. We speculate that the phosphatase Glc7/PP1, known to regulate both the cell cycle and carbon metabolism, may play an important role because its regulatory subunits are phospho-regulated in our data. In summary, our results identify extensive cell cycle dependent phosphorylation and dephosphorylation of metabolic enzymes and suggest multiple mechanisms through which the cell division cycle regulates metabolic signaling pathways to temporally coordinate biosynthesis with distinct phases of the cell division cycle.

Fueling the Cycle: CDKs in Carbon and Energy Metabolism.

Cyclin-dependent kinases (CDKs) are the central regulators of the eukaryotic cell cycle, and are conserved across eukaryotes. Their main and well-studied function lies in the regulation and the time-keeping of cell cycle entry and progression. Additionally, more and more non canonical functions of CDKs are being uncovered. One fairly recently discovered role of CDKs is the coordination of carbon and energy metabolism with proliferation. Evidence from different model organisms is accumulating that CDKs can directly and indirectly control fluxes through metabolism, for example by phosphorylating metabolic enzymes. In this mini-review, we summarize the emerging role of CDKs in regulating carbon and energy metabolism and discuss examples in different models from yeast to cancer cells.

How yeast coordinates metabolism, growth and division.

All cells, especially single cell organisms, need to adapt their metabolism, growth and division coordinately to the available nutrients. This coordination is mediated by extensive cross-talk between nutrient signaling, metabolism, growth, and the cell division cycle, which is only gradually being uncovered: Nutrient signaling not only controls entry into the cell cycle at the G1/S transition, but all phases of the cell cycle. Metabolites are even sensed directly by cell cycle regulators to prevent cell cycle progression in absence of sufficient metabolic fluxes. In turn, cell cycle regulators such as the cyclin-dependent kinase directly control metabolic fluxes during cell cycle progression. In this review, I highlight some recent advances in our understanding of how metabolism and the cell division cycle are coordinated in the model organism Saccharomyces cerevisiae.

The Yeast Cyclin-Dependent Kinase Routes Carbon Fluxes to Fuel Cell Cycle Progression.

Cell division entails a sequence of processes whose specific demands for biosynthetic precursors and energy place dynamic requirements on metabolism. However, little is known about how metabolic fluxes are coordinated with the cell division cycle. Here, we examine budding yeast to show that more than half of all measured metabolites change significantly through the cell division cycle. Cell cycle-dependent changes in central carbon metabolism are controlled by the cyclin-dependent kinase (Cdk1), a major cell cycle regulator, and the metabolic regulator protein kinase A. At the G1/S transition, Cdk1 phosphorylates and activates the enzyme Nth1, which funnels the storage carbohydrate trehalose into central carbon metabolism. Trehalose utilization fuels anabolic processes required to reliably complete cell division. Thus, the cell cycle entrains carbon metabolism to fuel biosynthesis. Because the oscillation of Cdk activity is a conserved feature of the eukaryotic cell cycle, we anticipate its frequent use in dynamically regulating metabolism for efficient proliferation.

A genetically encoded Förster resonance energy transfer sensor for monitoring in vivo trehalose-6-phosphate dynamics.

Trehalose-6-phosphate is a pivotal regulator of sugar metabolism, growth, and osmotic equilibrium in bacteria, yeasts, and plants. To directly visualize the intracellular levels of intracellular trehalose-6-phosphate, we developed a series of specific Förster resonance energy transfer (FRET) sensors for in vivo microscopy. We demonstrated real-time monitoring of regulation in the trehalose pathway of Escherichia coli. In Saccharomyces cerevisiae, we could show that the concentration of free trehalose-6-phosphate during growth on glucose is in a range sufficient for inhibition of hexokinase. These findings support the hypothesis of trehalose-6-phosphate as the effector of a negative feedback system, similar to the inhibition of hexokinase by glucose-6-phosphate in mammalian cells and controlling glycolytic flux.

Cell size control in yeast.

Cell size is an important adaptive trait that influences nearly all aspects of cellular physiology. Despite extensive characterization of the cell-cycle regulatory network, the molecular mechanisms coupling cell growth to division, and thereby controlling cell size, have remained elusive. Recent work in yeast has reinvigorated the size control field and suggested provocative mechanisms for the distinct functions of setting and sensing cell size. Further examination of size-sensing models based on spatial gradients and molecular titration, coupled with elucidation of the pathways responsible for nutrient-modulated target size, may reveal the fundamental principles of eukaryotic cell size control.

Engineering genetically encoded nanosensors for real-time in vivo measurements of citrate concentrations.

Citrate is an intermediate in catabolic as well as biosynthetic pathways and is an important regulatory molecule in the control of glycolysis and lipid metabolism. Mass spectrometric and NMR based metabolomics allow measuring citrate concentrations, but only with limited spatial and temporal resolution. Methods are so far lacking to monitor citrate levels in real-time in-vivo. Here, we present a series of genetically encoded citrate sensors based on Förster resonance energy transfer (FRET). We screened databases for citrate-binding proteins and tested three candidates in vitro. The citrate binding domain of the Klebsiella pneumoniae histidine sensor kinase CitA, inserted between the FRET pair Venus/CFP, yielded a sensor highly specific for citrate. We optimized the peptide linkers to achieve maximal FRET change upon citrate binding. By modifying residues in the citrate binding pocket, we were able to construct seven sensors with different affinities spanning a concentration range of three orders of magnitude without losing specificity. In a first in vivo application we show that E. coli maintains the capacity to take up glucose or acetate within seconds even after long-term starvation.

In vivo biochemistry: quantifying ion and metabolite levels in individual cells or cultures of yeast.

Over the past decade, we have learned that cellular processes, including signalling and metabolism, are highly compartmentalized, and that relevant changes in metabolic state can occur at sub-second timescales. Moreover, we have learned that individual cells in populations, or as part of a tissue, exist in different states. If we want to understand metabolic processes and signalling better, it will be necessary to measure biochemical and biophysical responses of individual cells with high temporal and spatial resolution. Fluorescence imaging has revolutionized all aspects of biology since it has the potential to provide information on the cellular and subcellular distribution of ions and metabolites with sub-second time resolution. In the present review we summarize recent progress in quantifying ions and metabolites in populations of yeast cells as well as in individual yeast cells with the help of quantitative fluorescent indicators, namely FRET metabolite sensors. We discuss the opportunities and potential pitfalls and the controls that help preclude misinterpretation.

Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains.

The field of systems biology is often held back by difficulties in obtaining comprehensive, high-quality, quantitative data sets. In this paper, we undertook an interlaboratory effort to generate such a data set for a very large number of cellular components in the yeast Saccharomyces cerevisiae, a widely used model organism that is also used in the production of fuels, chemicals, food ingredients and pharmaceuticals. With the current focus on biofuels and sustainability, there is much interest in harnessing this species as a general cell factory. In this study, we characterized two yeast strains, under two standard growth conditions. We ensured the high quality of the experimental data by evaluating a wide range of sampling and analytical techniques. Here we show significant differences in the maximum specific growth rate and biomass yield between the two strains. On the basis of the integrated analysis of the high-throughput data, we hypothesize that differences in phenotype are due to differences in protein metabolism.

Prediction of kinetic parameters from DNA-binding site sequences for modeling global transcription dynamics in Escherichia coli.

The majority of dynamic gene regulatory network (GRN) models are comprised of only a few genes and do not take multiple transcription regulation into account. The models are conceived in this way in order to minimize the number of kinetic parameters. In this paper, we propose a new approach for predicting kinetic parameters from DNA-binding site sequences by correlating the protein-DNA-binding affinities with nucleotide sequence conservation. We present the dynamic modeling of the cra modulon transcription in Escherichia coli during glucose-limited fed-batch cultivation. The concentration of the Cra regulator protein inhibitor, fructose 1,6-bis(phosphate), decreases sharply, eventually leading to the repression of transcription. Total RNA concentration data indicate a strong regulation of transcription through the availability of RNA polymerase. A critical assessment of the results of the model simulations supports this finding. This new approach for the prediction of transcription dynamics may improve the metabolic engineering of gene regulation processes.

In vitro synthesis and characterization of guanosine 3',5'-bis(diphosphate).

The intracellular alarmone guanosine 3',5'-bis(diphosphate) (ppGpp) has been thoroughly investigated over the past 40 years and has become one of the best-known effectors in bacterial physiology. ppGpp is also of great importance for biotechnological applications. Systems biology research, involving experimental and mathematical approaches, has contributed a great deal to uncovering the alarmone's complex regulatory effects. HPLC analysis and UV detection are used to quantify intracellular ppGpp. The samples analyzed also contain other phosphorylated guanine nucleotides and, therefore, are spiked with a standard ppGpp solution. A rapidly growing number of laboratories are turning to synthesizing the nucleotide in vitro involving time-consuming protocols and yielding only low amounts of ppGpp. The current article provides a protocol for the preparation of large quantities of a ribosome extract that contains high ppGpp synthesis activity. The demonstrated upscaling from shaking flask to bioreactor cultivation involves the continuous and refrigerated harvest of the biomass. (13)C NMR analysis enabled the structural characterization of the synthesis product and was complemented by mass spectrometry and methods that are commonly used to identify ppGpp.

Quantification of rRNA in Escherichia coli using capillary gel electrophoresis with laser-induced fluorescence detection.

Over the past 10 years, sophisticated powerful techniques have been developed for the quantification of messenger RNA (mRNA) and ribosomal RNA (rRNA), enabling researchers in science, industry, and molecular medicine to explore gene expression. These techniques require the (reverse) transcription of analyte RNA, hybridization with synthetic oligonucleotides, and other additional steps that make them costly, time-consuming, and quantitatively difficult to perform. The current work demonstrates how 16S and 23S rRNA can be quantified precisely using capillary gel electrophoresis with laser-induced fluorescence detection (CGE-LIF) directly after the extraction of total RNA without requiring further reactions or calibration. CGE-LIF normally is used for the qualitative examination of RNA preparations. Its quantitative performance could be improved significantly using MS2 bacteriophage RNA as an internal standard. The entire analytical procedure was validated for linearity, repeatability, reproducibility, and recovery. This validation also included total RNA extraction from bacterial cells, an aspect examined for the first time in absolute RNA quantification. Recovery is close to 100%, and the analytical precision was increased 10-fold (CV<3%), as compared with similar approaches. The demonstrated method is simple and opens up new possibilities for the absolute quantification of not only rRNA but also individual mRNAs.