Comprehensive Temporal Protein Dynamics during the Diauxic Shift in Saccharomyces cerevisiae

Profiling Proteins and Phosphorylation Sites During T Cell Activation Using an Integrated Thermal Shift Assay

T cell activation is a complex biological process of naïve cells maturing into effector cells. Proteomic and phospho-proteomic approaches have provided critical insights into this process, yet it is not always clear how changes in individual proteins or phosphorylation sites have functional significance. Here, we developed the Phosphorylation Integrated Thermal Shift Assay (PITSA) that combines the measurement of protein or phosphorylation site abundance and thermal stability into a single TMT experiment and apply this method to study T cell activation. We quantified the abundance and thermal stability of over 7,500 proteins and 5,000 phosphorylation sites, and identified significant differences in chromatin-related, TCR signaling, DNA repair, and proliferative phosphoproteins. PITSA may be applied to a wide range of biological contexts to generate hypotheses as to which proteins or phosphorylation sites are functionally regulated in a given system, as well as the mechanisms by which this regulation may occur.

Loss of the yeast transporter Agp2 upregulates the pleiotropic drug-resistant pump Pdr5 and confers resistance to the protein synthesis inhibitor cycloheximide

The transmembrane protein Agp2, initially shown as a transporter of L-carnitine, mediates the high-affinity transport of polyamines and the anticancer drug bleomycin-A5. Cells lacking Agp2 are hyper-resistant to polyamine and bleomycin-A5. In these earlier studies, we showed that the protein synthesis inhibitor cycloheximide blocked the uptake of bleomycin-A5 into the cells suggesting that the drug uptake system may require de novo synthesis. However, our recent findings demonstrated that cycloheximide, instead, induced rapid degradation of Agp2, and in the absence of Agp2 cells are resistant to cycloheximide. These observations raised the possibility that the degradation of Agp2 may allow the cell to alter its drug resistance network to combat the toxic effects of cycloheximide. In this study, we show that membrane extracts from agp2Δ mutants accentuated several proteins that were differentially expressed in comparison to the parent. Mass spectrometry analysis of the membrane extracts uncovered the pleiotropic drug efflux pump, Pdr5, involved in the efflux of cycloheximide, as a key protein upregulated in the agp2Δ mutant. Moreover, a global gene expression analysis revealed that 322 genes were differentially affected in the agp2Δ mutant versus the parent, including the prominent PDR5 gene and genes required for mitochondrial function. We further show that Agp2 is associated with the upstream region of the PDR5 gene, leading to the hypothesis that cycloheximide resistance displayed by the agp2Δ mutant is due to the derepression of the PDR5 gene.

Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae

Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. This study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

Impact of propagation time on yeast physiology during bottle conditioning of beer on an industrial scale

Bottle conditioning occurs when yeast and a fermentable extract are added to beer prior to packaging. Aside from ethanol and carbon dioxide production, this process can minimize the production of off-flavors and increase the shelf-life of beer. The advantages of bottle conditioning rely on the yeast being able to quickly referment the beer and maintain viability during storage. In this study, a commercial ale yeast was propagated in wort on a large scale (30 hL) for 24 h or 72 h and seeded into pale ale beer for bottle conditioning. We found that yeast propagated until the post-diauxic shift (72 h) provided better longevity in the bottle and improved foam stability compared to the 24 h propagated yeast. At the time of seeding, yeast propagated for 72 h showed an upregulation of proteins involved in cellular respiration and general stress pathways that may indicate responses toward mitigating cellular stress levels.

The PP2A-like phosphatase Ppg1 mediates assembly of the Far complex to balance gluconeogenic outputs and enables adaptation to glucose depletion

To sustain growth in changing nutrient conditions, cells reorganize outputs of metabolic networks and appropriately reallocate resources. Signaling by reversible protein phosphorylation can control such metabolic adaptations. In contrast to kinases, the functions of phosphatases that enable metabolic adaptation as glucose depletes are poorly studied. Using a Saccharomyces cerevisiae deletion screen, we identified the PP2A-like phosphatase Ppg1 as required for appropriate carbon allocations towards gluconeogenic outputs-trehalose, glycogen, UDP-glucose, UDP-GlcNAc-after glucose depletion. This Ppg1 function is mediated via regulation of the assembly of the Far complex-a multi-subunit complex that tethers to the ER and mitochondrial outer membranes forming localized signaling hubs. The Far complex assembly is Ppg1 catalytic activity-dependent. Ppg1 regulates the phosphorylation status of multiple ser/thr residues on Far11 to enable the proper assembly of the Far complex. The assembled Far complex is required to maintain gluconeogenic outputs after glucose depletion. Glucose in turn regulates Far complex amounts. This Ppg1-mediated Far complex assembly, and Ppg1-Far complex dependent control of gluconeogenic outputs enables adaptive growth under glucose depletion. Our study illustrates how protein dephosphorylation is required for the assembly of a multi-protein scaffold present in localized cytosolic pools, to thereby alter gluconeogenic flux and enable cells to metabolically adapt to nutrient fluctuations.

Riboproteome remodeling during quiescence exit in Saccharomyces cerevisiae

The quiescent state is the prevalent mode of cellular life in most cells. Saccharomyces cerevisiae is a useful model for studying the molecular basis of the cell cycle, quiescence, and aging. Previous studies indicate that heterogeneous ribosomes show a specialized translation function to adjust the cellular proteome upon a specific stimulus. Using nano LC-MS/MS, we identified 69 of the 79 ribosomal proteins (RPs) that constitute the eukaryotic 80S ribosome during quiescence. Our study shows that the riboproteome is composed of 444 accessory proteins comprising cellular functions such as translation, protein folding, amino acid and glucose metabolism, cellular responses to oxidative stress, and protein degradation. Furthermore, the stoichiometry of both RPs and accessory proteins on ribosome particles is different depending on growth conditions and among monosome and polysome fractions. Deficiency of different RPs resulted in defects of translational capacity, suggesting that ribosome composition can result in changes in translational activity during quiescence.

Vector-borne Trypanosoma brucei parasites develop in artificial human skin and persist as skin tissue forms

Transmission of Trypanosoma brucei by tsetse flies involves the deposition of the cell cycle-arrested metacyclic life cycle stage into mammalian skin at the site of the fly's bite. We introduce an advanced human skin equivalent and use tsetse flies to naturally infect the skin with trypanosomes. We detail the chronological order of the parasites' development in the skin by single-cell RNA sequencing and find a rapid activation of metacyclic trypanosomes and differentiation to proliferative parasites. Here we show that after the establishment of a proliferative population, the parasites enter a reversible quiescent state characterized by slow replication and a strongly reduced metabolism. We term these quiescent trypanosomes skin tissue forms, a parasite population that may play an important role in maintaining the infection over long time periods and in asymptomatic infected individuals.

Controlling circuitry underlies the growth optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae, cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae. We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae, providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

Genome dilution by cell growth drives starvation-like proteome remodeling in mammalian and yeast cells

Cell size is tightly controlled in healthy tissues and single-celled organisms, but it remains unclear how size influences cell physiology. Increasing cell size was recently shown to remodel the proteomes of cultured human cells, demonstrating that large and small cells of the same type can be biochemically different. Here, we corroborate these results in mouse hepatocytes and extend our analysis using yeast. We find that size-dependent proteome changes are highly conserved and mostly independent of metabolic state. As eukaryotic cells grow larger, the dilution of the genome elicits a starvation-like proteome phenotype, suggesting that growth in large cells is limited by the genome in a manner analogous to a limiting nutrient. We also demonstrate that the proteomes of replicatively-aged yeast are primarily determined by their large size. Overall, our data suggest that genome concentration is a universal determinant of proteome content in growing cells.

Comparative Proteomic Analysis of Two Commonly Used Laboratory Yeast Strains: W303 and BY4742

The yeast Saccharomyces cerevisiae is a powerful model system that is often used to expand our understanding of cellular processes and biological functions. Although many genetically well-characterized laboratory strains of S. cerevisiae are available, they may have different genetic backgrounds which can confound data interpretation. Here, we report a comparative whole-proteome analysis of two common laboratory yeast background strains, W303 and BY4742, in both exponential and stationary growth phases using isobaric-tag-based mass spectrometry to highlight differences in proteome complexity. We quantified over 4400 proteins, hundreds of which showed differences in abundance between strains and/or growth phases. Moreover, we used proteome-wide protein abundance to profile the mating type of the strains used in the experiment, the auxotrophic markers, and associated metabolic pathways, as well as to investigate differences in particular classes of proteins, such as the pleiotropic drug resistance (PDR) proteins. This study is a valuable resource that offers insight into mechanistic differences between two common yeast background strains and can be used as a guide to select a background that is best suited for addressing a particular biological question.

The unfolded protein response of the endoplasmic reticulum supports mitochondrial biogenesis by buffering nonimported proteins

Almost all mitochondrial proteins are synthesized in the cytosol and subsequently targeted to mitochondria. The accumulation of nonimported precursor proteins occurring upon mitochondrial dysfunction can challenge cellular protein homeostasis. Here we show that blocking protein translocation into mitochondria results in the accumulation of mitochondrial membrane proteins at the endoplasmic reticulum, thereby triggering the unfolded protein response (UPRER). Moreover, we find that mitochondrial membrane proteins are also routed to the ER under physiological conditions. The level of ER-resident mitochondrial precursors is enhanced by import defects as well as metabolic stimuli that increase the expression of mitochondrial proteins. Under such conditions, the UPRER is crucial to maintain protein homeostasis and cellular fitness. We propose the ER serves as a physiological buffer zone for those mitochondrial precursors that cannot be immediately imported into mitochondria while engaging the UPRER to adjust the ER proteostasis capacity to the extent of precursor accumulation.

Proteome dynamics during transition from exponential to stationary phase under aerobic and anaerobic conditions in yeast

The yeast Saccharomyces cerevisiae is a widely used eukaryotic model organism and a promising cell factory for industry. However, despite decades of research, the regulation of its metabolism is not yet fully understood, and its complexity represents a major challenge for engineering and optimising biosynthetic routes. Recent studies have demonstrated the potential of resource and proteomic allocation data in enhancing models for metabolic processes. However, comprehensive and accurate proteome dynamics data that can be used for such approaches are still very limited. Therefore, we performed a quantitative proteome dynamics study to comprehensively cover the transition from exponential to stationary phase for both aerobically and anaerobically grown yeast cells. The combination of highly controlled reactor experiments, biological replicates and standardised sample preparation procedures ensured reproducibility and accuracy. Additionally, we selected the CEN.PK lineage for our experiments because of its relevance for both fundamental and applied research. Together with the prototrophic, standard haploid strain CEN.PK113-7D, we also investigated an engineered strain with genetic minimisation of the glycolytic pathway, resulting in the quantitative assessment of 54 proteomes. The anaerobic cultures showed remarkably less proteome-level changes compared to the aerobic cultures, during transition from the exponential to the stationary phase as a consequence of the lack of the diauxic shift in the absence of oxygen. These results support the notion that anaerobically growing cells lack resources to adequately adapt to starvation. This proteome dynamics study constitutes an important step towards better understanding of the impact of glucose exhaustion and oxygen on the complex proteome allocation process in yeast. Finally, the established proteome dynamics data provide a valuable resource for the development of resource allocation models as well as for metabolic engineering efforts.

The phosphorylation status of Hsp82 regulates mitochondrial homeostasis during glucose sensing in Saccharomyces cerevisiae

Sensing extracellular glucose, budding yeast switches from aerobic glycolysis to oxidative phosphorylation to adapt to environmental changes. During the conversion of metabolic mode, mitochondrial function and morphology change significantly. Mitochondria are the main supply factories of energy for various life activities in cells. However, the research on the signal pathways from glucose sensing to changes in mitochondrial function and morphology is still scarce and worthy of further exploration. In this study, we found that in addition to the known involvement of molecular chaperone Hsp82 in stress response during the conversion of metabolic mode, the phosphorylation status of Hsp82 at S485 residue regulates mitochondrial function and morphology to maintain mitochondrial homeostasis. The Hsp82^S485A mutant that mimics dephosphorylation at S485 residue showed abnormal growth phenotypes related to mitochondrial defects, such as the petite phenotype, slow growth rates, and inability to use non-fermentable carbon sources. Further exploring the causes of growth defects, we found that the Hsp82^S485A mutant caused mitochondrial dysfunction, including a decrease in cellular oxygen consumption rate, defects in mitochondrial electron transport chain, decreased mitochondrial membrane potential and complete loss of mtDNA. Furthermore, the Hsp82^S485A mutant displayed fragmented or globular mitochondria, which may be responsible for its mitochondrial dysfunction. Our findings suggested that the phosphorylation status of Hsp82 at S485 residue might regulate mitochondrial function and morphology by affecting the stability of mitochondrial fission and fusion-related proteins. Thus, Hsp82 might be a key molecule in the signal pathway from glucose sensing to changes in mitochondrial function and morphology.

Enriching Cysteine-Containing Peptides Using a Sulfhydryl-Reactive Alkylating Reagent with a Phosphonic Acid Group and Immobilized Metal Affinity Chromatography

The reduction of disulfide bonds and their subsequent alkylation are commonplace in typical proteomics workflows. Here, we highlight a sulfhydryl-reactive alkylating reagent with a phosphonic acid group (iodoacetamido-LC-phosphonic acid, 6C-CysPAT) that facilitates the enrichment of cysteine-containing peptides for isobaric tag-based proteome abundance profiling. Specifically, we profile the proteome of the SH-SY5Y human cell line following 24 h treatments with two proteasome inhibitors (bortezomib and MG-132) in a tandem mass tag (TMT)pro9-plex experiment. We acquire three datasets─(1) Cys-peptide enriched, (2) the unbound complement, and (3) the non-depleted control─and compare the peptides and proteins quantified in each dataset, with emphasis on Cys-containing peptides. The data show that enrichment using 6C-Cys phosphonate adaptable tag (6C-CysPAT) can quantify over 38,000 Cys-containing peptides in 5 h with >90% specificity. In addition, our combined dataset provides the research community with a resource of over 9900 protein abundance profiles exhibiting the effects of two different proteasome inhibitors. Overall, the seamless incorporation of alkylation by 6C-CysPAT into a current TMT-based workflow permits the enrichment of a Cys-containing peptide subproteome. The acquisition of this "mini-Cys" dataset can be used to preview and assess the quality of a deep, fractionated dataset.

Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC

Genetically identical cells are known to differ in many physiological parameters such as growth rate and drug tolerance. Metabolic specialization is believed to be a cause of such phenotypic heterogeneity, but detection of metabolically divergent subpopulations remains technically challenging. We developed a proteomics-based technology, termed differential isotope labelling by amino acids (DILAC), that can detect producer and consumer subpopulations of a particular amino acid within an isogenic cell population by monitoring peptides with multiple occurrences of the amino acid. We reveal that young, morphologically undifferentiated yeast colonies contain subpopulations of lysine producers and consumers that emerge due to nutrient gradients. Deconvoluting their proteomes using DILAC, we find evidence for in situ cross-feeding where rapidly growing cells ferment and provide the more slowly growing, respiring cells with ethanol. Finally, by combining DILAC with fluorescence-activated cell sorting, we show that the metabolic subpopulations diverge phenotypically, as exemplified by a different tolerance to the antifungal drug amphotericin B. Overall, DILAC captures previously unnoticed metabolic heterogeneity and provides experimental evidence for the role of metabolic specialization and cross-feeding interactions as a source of phenotypic heterogeneity in isogenic cell populations.

After virus exposure, early bystander naïve CD8 T cell activation relies on NAD+ salvage metabolism

CD8 T cells play a central role in antiviral immunity. Type I interferons are among the earliest responders after virus exposure and can cause extensive reprogramming and antigen-independent bystander activation of CD8 T cells. Although bystander activation of pre-existing memory CD8 T cells is known to play an important role in host defense and immunopathology, its impact on naïve CD8 T cells remains underappreciated. Here we report that exposure to reovirus, both in vitro or in vivo, promotes bystander activation of naïve CD8 T cells within 24 hours and that this distinct subtype of CD8 T cell displays an innate, antiviral, type I interferon sensitized signature. The induction of bystander naïve CD8 T cells is STAT1 dependent and regulated through nicotinamide phosphoribosyl transferase (NAMPT)-mediated enzymatic actions within NAD+ salvage metabolic biosynthesis. These findings identify a novel aspect of CD8 T cell activation following virus infection with implications for human health and physiology.

Protocol for CAROM: A machine learning tool to predict post-translational regulation from metabolic signatures

This protocol describes CAROM, a computational tool that combines genome-scale metabolic networks (GEMs) and machine learning to identify enzyme targets of post-translational modifications (PTMs). Condition-specific enzyme and reaction properties are used to predict targets of phosphorylation and acetylation in multiple organisms. CAROM is influenced by the accuracy of GEMs and associated flux-balance analysis (FBA), which generate the inputs of the model. We demonstrate the protocol using multi-omics data from E. coli. For complete details on the use and execution of this protocol, please refer to Smith et al. (2022).

Quiescence in Saccharomyces cerevisiae

Most cells live in environments that are permissive for proliferation only a small fraction of the time. Entering quiescence enables cells to survive long periods of nondivision and reenter the cell cycle when signaled to do so. Here, we describe what is known about the molecular basis for quiescence in Saccharomyces cerevisiae, with emphasis on the progress made in the last decade. Quiescence is triggered by depletion of an essential nutrient. It begins well before nutrient exhaustion, and there is extensive crosstalk between signaling pathways to ensure that all proliferation-specific activities are stopped when any one essential nutrient is limiting. Every aspect of gene expression is modified to redirect and conserve resources. Chromatin structure and composition change on a global scale, from histone modifications to three-dimensional chromatin structure. Thousands of proteins and RNAs aggregate, forming unique structures with unique fates, and the cytoplasm transitions to a glass-like state.

Genome-wide base editor screen identifies regulators of protein abundance in yeast

Proteins are key molecular players in a cell, and their abundance is extensively regulated not just at the level of gene expression but also post-transcriptionally. Here, we describe a genetic screen in yeast that enables systematic characterization of how protein abundance regulation is encoded in the genome. The screen combines a CRISPR/Cas9 base editor to introduce point mutations with fluorescent tagging of endogenous proteins to facilitate a flow-cytometric readout. We first benchmarked base editor performance in yeast with individual gRNAs as well as in positive and negative selection screens. We then examined the effects of 16,452 genetic perturbations on the abundance of eleven proteins representing a variety of cellular functions. We uncovered hundreds of regulatory relationships, including a novel link between the GAPDH isoenzymes Tdh1/2/3 and the Ras/PKA pathway. Many of the identified regulators are specific to one of the eleven proteins, but we also found genes that, upon perturbation, affected the abundance of most of the tested proteins. While the more specific regulators usually act transcriptionally, broad regulators often have roles in protein translation. Overall, our novel screening approach provides unprecedented insights into the components, scale and connectedness of the protein regulatory network.

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.

Integrated changes in thermal stability and proteome abundance during altered nutrient states in Escherichia coli and human cells

Altered thermal solubility measurement techniques are emerging as powerful tools to assess ligand binding, post-translational modification, protein-protein interactions, and many other cellular processes that affect protein state under various cellular conditions. Thermal solubility or stability profiling techniques are enabled on a global proteomic scale by employing isobaric tagging reagents that facilitate multiplexing capacity required to measure changes in the proteome across thermal gradients. Key among these is thermal proteomic profiling (TPP), which requires 8-10 isobaric tags per gradient and generation of multiple proteomic datasets to measure different replicates and conditions. Furthermore, using TPP to measure protein thermal stability state across different conditions may also require measurements of differential protein abundance. Here, we use the proteome integral stability alteration (PISA) assay, a higher throughput version of TPP, to measure global changes in protein thermal stability normalized to their protein abundance. We explore the use of this approach to determine changes in protein state between logarithmic and stationary phase Escherichia coli as well as glucose-starved human Hek293T cells. We observed protein intensity-corrected PISA changes in 290 and 350 proteins due to stationary phase transition in E. coli and glucose starvation, respectively. These data reveal several examples of proteins that were not previously associated with nutrient states by abundance alone. These include E. coli proteins such as putative acyl-CoA dehydrogenase (aidB) and chaperedoxin (cnoX) as well as human RAB vesicle trafficking proteins and many others which may indicate their involvement in metabolic diseases such as cancer.

Changes to the mtDNA copy number during yeast culture growth

We show that the mitochondrial DNA (mtDNA) copy number in growing cultures of the yeast Saccharomyces cerevisiae increases by a factor of up to 4, being lowest (approx. 10 per haploid genome) and stable during rapid fermentative growth, and highest at the end of the respiratory phase. When yeast are grown on glucose, the onset of the mtDNA copy number increase coincides with the early stages of the diauxic shift, and the increase continues through respiration. A lesser yet still substantial copy number increase occurs when yeast are grown on a nonfermentable carbon source, i.e. when there is no diauxic shift. The mtDNA copy number increase during and for some time after the diauxic shift is not driven by an increase in cell size. The copy number increase occurs in both haploid and diploid strains but is markedly attenuated in a diploid wild isolate that is a ready sporulator. Strain-to-strain differences in mtDNA copy number are least apparent in fermentation and most apparent in late respiration or stationary phase. While changes in mitochondrial morphology and function were previously known to accompany changes in physiological state, it had not been previously shown that the mtDNA copy number changes substantially over time in a clonal growing culture. The mtDNA copy number in yeast is therefore a highly dynamic phenotype.

NAD+ depletion enhances reovirus-induced oncolysis in multiple myeloma

Cancer cell energy metabolism plays an important role in dictating the efficacy of oncolysis by oncolytic viruses. To understand the role of multiple myeloma metabolism in reovirus oncolysis, we performed semi-targeted mass spectrometry-based metabolomics on 12 multiple myeloma cell lines and revealed a negative correlation between NAD+ levels and susceptibility to oncolysis. Likewise, a negative correlation was observed between the activity of the rate-limiting NAD+ synthesis enzyme NAMPT and oncolysis. Indeed, depletion of NAD+ levels by pharmacological inhibition of NAMPT using FK866 sensitized several myeloma cell lines to reovirus-induced killing. The myelomas that were most sensitive to this combination therapy expressed a functional p53 and had a metabolic and transcriptomic profile favoring mitochondrial metabolism over glycolysis, with the highest synergistic effect in KMS12 cells. Mechanistically, U-¹³C-labeled glucose flux, extracellular flux analysis, multiplex proteomics, and cell death assays revealed that the reovirus + FK866 combination caused mitochondrial dysfunction and energy depletion, leading to enhanced autophagic cell death in KMS12 cells. Finally, the combination of reovirus and NAD+ depletion achieved greater antitumor effects in KMS12 tumors in vivo and patient-derived CD138+ multiple myeloma cells. These findings identify NAD+ depletion as a potential combinatorial strategy to enhance the efficacy of oncolytic virus-based therapies in multiple myeloma.

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.

Dual role of Mic10 in mitochondrial cristae organization and ATP synthase-linked metabolic adaptation and respiratory growth

Invaginations of the mitochondrial inner membrane, termed cristae, are hubs for oxidative phosphorylation. The mitochondrial contact site and cristae organizing system (MICOS) and the dimeric F₁F_o-ATP synthase play important roles in controlling cristae architecture. A fraction of the MICOS core subunit Mic10 is found in association with the ATP synthase, yet it is unknown whether this interaction is of relevance for mitochondrial or cellular functions. Here, we established conditions to selectively study the role of Mic10 at the ATP synthase. Mic10 variants impaired in MICOS functions stimulate ATP synthase oligomerization like wild-type Mic10 and promote efficient inner membrane energization, adaptation to non-fermentable carbon sources, and respiratory growth. Mic10's functions in respiratory growth largely depend on Mic10^ATPsynthase, not on Mic10^MICOS. We conclude that Mic10 plays a dual role as core subunit of MICOS and as partner of the F₁F_o-ATP synthase, serving distinct functions in cristae shaping and respiratory adaptation and growth.

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Dual role of Mic10 of mitochondrial contact site and cristae organizing system (MICOS)

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Mic10 binds to mitochondrial ATP synthase and stabilizes higher order assemblies

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Oligomerization of Mic10 is required for its function in MICOS, not at ATP synthase

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Mic10 binding to ATP synthase supports metabolic adaptation and respiratory growth

Rapid selection response to ethanol in Saccharomyces eubayanus emulates the domestication process under brewing conditions

Although the typical genomic and phenotypic changes that characterize the evolution of organisms under the human domestication syndrome represent textbook examples of rapid evolution, the molecular processes that underpin such changes are still poorly understood. Domesticated yeasts for brewing, where short generation times and large phenotypic and genomic plasticity were attained in a few generations under selection, are prime examples. To experimentally emulate the lager yeast domestication process, we created a genetically complex (panmictic) artificial population of multiple Saccharomyces eubayanus genotypes, one of the parents of lager yeast. Then, we imposed a constant selection regime under a high ethanol concentration in 10 replicated populations during 260 generations (6 months) and compared them with propagated controls exposed solely to glucose. Propagated populations exhibited a selection differential of 60% in growth rate in ethanol, mostly explained by the proliferation of a single lineage (CL248.1) that competitively displaced all other clones. Interestingly, the outcome does not require the entire time‐course of adaptation, as four lineages monopolized the culture at generation 120. Sequencing demonstrated that de novo genetic variants were produced in all propagated lines, including SNPs, aneuploidies, INDELs and translocations. In addition, the different propagated populations showed correlated responses resembling the domestication syndrome: genomic rearrangements, faster fermentation rates, lower production of phenolic off‐flavours and lower volatile compound complexity. Expression profiling in beer wort revealed altered expression levels of genes related to methionine metabolism, flocculation, stress tolerance and diauxic shift, likely contributing to higher ethanol and fermentation stress tolerance in the evolved populations. Our study shows that experimental evolution can rebuild the brewing domestication process in ‘fast motion’ in wild yeast, and also provides a powerful tool for studying the genetics of the adaptation process in complex populations.

Categorization of Phosphorylation Site Behavior during the Diauxic Shift in Saccharomyces cerevisiae

Protein phosphorylation has long been recognized as an essential regulator of protein activity, structure, complex formation, and subcellular localization among other cellular mechanisms. However, interpretation of the changes in protein phosphorylation is difficult. To address this difficulty, we measured protein and phosphorylation site changes across 11 points of a time course and developed a method for categorizing phosphorylation site behavior relative to protein level changes using the diauxic shift in yeast as a model and TMT11 sample multiplexing. We classified quantified proteins into behavioral categories that reflected differences in kinase activity, protein complex structure, and growth and metabolic pathway regulation across different phases of the diauxic shift. These data also provide a valuable resource for the study of fermentative versus respiratory growth and set a new benchmark for temporal quantitative proteomics and phosphoproteomics for the diauxic shift in Saccharomyces cerevisiae. Data are available via ProteomeXchange with identifier PXD022741.

Proteome profiling and vector yield optimization in a recombinant adeno-associated virus-producing yeast model

Recent studies on recombinant adeno‐associated viral (rAAV) vector production demonstrated the generation of infectious viral particles in Saccharomyces cerevisiae. Proof‐of‐concept results showed low vector yields that correlated with low AAV DNA encapsidation rates. In an attempt to understand the host cell response to rAAV production, we profiled proteomic changes throughout the fermentation process by mass spectrometry. By comparing an rAAV‐producing yeast strain with a respective non‐producer control, we identified a subset of yeast host proteins with significantly different expression patterns during the rAAV induction period. Gene ontology enrichment and network interaction analyses identified changes in expression patterns associated mainly with protein folding, as well as amino acid metabolism, gluconeogenesis, and stress response. Specific fold change patterns of heat shock proteins and other stress protein markers suggested the occurrence of a cytosolic unfolded protein response during rAAV protein expression. Also, a correlative increase in proteins involved in response to oxidative stress suggested cellular activities to ameliorate the effects of reactive oxygen species or other oxidants. We tested the functional relevance of the identified host proteins by overexpressing selected protein leads using low‐ and high‐copy number plasmids. Increased vector yields up to threefold were observed in clones where proteins SSA1, SSE1, SSE2, CCP1, GTT1, and RVB2 were overexpressed. Recombinant expression of SSA1 and YDJ insect homologues (HSP40 and HSC70, respectively) in Sf9 cells led to a volumetric vector yield increase of 50% relative to control, which validated the importance of chaperone proteins in rAAV‐producing systems. Overall, these results highlight the utility of proteomic‐based tools for the understanding and optimization of rAAV‐producing recombinant strains.

Temporal Proteomic Profiling of SH-SY5Y Differentiation with Retinoic Acid Using FAIMS and Real-Time Searching

The SH-SY5Y cell line is often used as a surrogate for neurons in cell-based studies. This cell line is frequently differentiated with all-trans retinoic acid (ATRA) over a 7-day period, which confers neuron-like properties to the cells. However, no analysis of proteome remodeling has followed the progress of this transition. Here, we quantitatively profiled over 9400 proteins across a 7-day treatment with retinoic acid using state-of-the-art mass spectrometry-based proteomics technologies, including FAIMS, real-time database searching, and TMTpro16 sample multiplexing. Gene ontology analysis revealed that categories with the highest increases in protein abundance were related to the plasma membrane/extracellular space. To showcase our data set, we surveyed the protein abundance profiles linked to neurofilament bundle assembly, neuron projections, and neuronal cell body formation. These proteins exhibited increases in abundance level, yet we observed multiple patterns among the queried proteins. The data presented represent a rich resource for investigating temporal protein abundance changes in SH-SY5Y cells differentiated with retinoic acid. Moreover, the sample preparation and data acquisition strategies used here can be readily applied to any analogous cell line differentiation analysis.

Persistent Activation of mRNA Translation by Transient Hsp90 Inhibition

The heat shock protein 90 (Hsp90) chaperone functions as a protein-folding buffer and plays a role promoting the evolution of new heritable traits. To better understand how Hsp90 can affect mRNA translation, we screen more than 1,600 factors involved in mRNA regulation for physical interactions with Hsp90 in human cells. The mRNA binding protein CPEB2 strongly binds Hsp90 via its prion domain. In a yeast model, transient inhibition of Hsp90 results in persistent activation of a CPEB translation reporter even in the absence of exogenous CPEB that persists for 30 generations after the inhibitor is removed. Ribosomal profiling reveals that some endogenous yeast mRNAs, including HAC1, show a persistent change in translation efficiency following transient Hsp90 inhibition. Thus, transient loss of Hsp90 function can promote a nongenetic inheritance of a translational state affecting specific mRNAs, introducing a mechanism by which Hsp90 can promote phenotypic variation.

Identification of TUBB2A by quantitative proteomic analysis as a novel biomarker for the prediction of distant metastatic breast cancer

Background

Metastasis of breast cancer to distal organs is fatal. However, few studies have identified biomarkers that are associated with distant metastatic breast cancer. Furthermore, the inability of current biomarkers, such as HER2, ER, and PR, to differentiate between distant and nondistant metastatic breast cancers accurately has necessitated the development of novel biomarker candidates.

Methods

An integrated proteomics approach that combined filter-aided sample preparation, tandem mass tag labeling (TMT), high pH fractionation, and high-resolution MS was applied to acquire in-depth proteomic data from FFPE distant metastatic breast cancer tissues. A bioinformatics analysis was performed with regard to gene ontology and signaling pathways using differentially expressed proteins (DEPs) to examine the molecular characteristics of distant metastatic breast cancer. In addition, real-time polymerase chain reaction (RT-PCR) and invasion/migration assays were performed to validate the differential regulation and function of our protein targets.

Results

A total of 9441 and 8746 proteins were identified from the pooled and individual sample sets, respectively. Based on our criteria, TUBB2A was selected as a novel biomarker candidate. The metastatic activities of TUBB2A were subsequently validated. In our bioinformatics analysis using DEPs, we characterized the overall molecular features of distant metastasis and measured differences in the molecular functions of distant metastatic breast cancer between breast cancer subtypes.

Conclusions

Our report is the first study to examine the distant metastatic breast cancer proteome using FFPE tissues. The depth of our dataset allowed us to discover a novel biomarker candidate and a proteomic characteristics of distant metastatic breast cancer. Distinct molecular features of various breast cancer subtypes were also established. Our proteomic data constitute a valuable resource for research on distant metastatic breast cancer.

Absolute yeast mitochondrial proteome quantification reveals trade-off between biosynthesis and energy generation during diauxic shift

This work offers a unique portrayal of yeast mitochondria through the characterization of its absolute proteome. The study of biophysical changes in the mitochondrial network associated with proteome profiling, throughout yeast growth and the transition from fermentative to respiratory metabolism, lays out the crucial role this organelle has in balancing the overall metabolic status of the cell. Using proteomic mass spectrometry, state of the art fluorescence microscopy, and lipidomics analysis, these data provide a highly quantitative description of key mitochondrial processes across three states of metabolism. In particular, the work highlights the significant contribution of functional and structural remodeling occurring during the diauxic shift of this subcellular organelle.

Saccharomyces cerevisiae constitutes a popular eukaryal model for research on mitochondrial physiology. Being Crabtree-positive, this yeast has evolved the ability to ferment glucose to ethanol and respire ethanol once glucose is consumed. Its transition phase from fermentative to respiratory metabolism, known as the diauxic shift, is reflected by dramatic rearrangements of mitochondrial function and structure. To date, the metabolic adaptations that occur during the diauxic shift have not been fully characterized at the organelle level. In this study, the absolute proteome of mitochondria was quantified alongside precise parametrization of biophysical properties associated with the mitochondrial network using state-of-the-art optical-imaging techniques. This allowed the determination of absolute protein abundances at a subcellular level. By tracking the transformation of mitochondrial mass and volume, alongside changes in the absolute mitochondrial proteome allocation, we could quantify how mitochondria balance their dual role as a biosynthetic hub as well as a center for cellular respiration. Furthermore, our findings suggest that in the transition from a fermentative to a respiratory metabolism, the diauxic shift represents the stage where major structural and functional reorganizations in mitochondrial metabolism occur. This metabolic transition, initiated at the mitochondria level, is then extended to the rest of the yeast cell.

Analysis of the S. pombe Meiotic Proteome Reveals a Switch from Anabolic to Catabolic Processes and Extensive Post-transcriptional Regulation

Meiotic progression in S. pombe is regulated by stage-specific gene expression and translation, changes in RNA stability, expression of anti-sense transcripts, and targeted proteolysis of regulatory proteins. We have used SILAC labeling to examine the relative levels of proteins in diploid S. pombe cells during meiosis. Among the 3,268 proteins quantified at all time points, the levels of 880 proteins changed at least 2-fold; the majority of proteins showed stepwise increases or decreases during the meiotic divisions, while some changed transiently. Overall, we observed reductions in proteins involved in anabolism and increases in proteins involved in catabolism. We also observed increases in the levels of proteins of the ESCRT-III complex and revealed a role for ESCRT-III components in chromosome segregation and spore formation. Correlation with studies of meiotic gene expression and ribosome occupancy reveals that many of the changes in steady-state protein levels are post-transcriptional.

Mmi1, the Yeast Ortholog of Mammalian Translationally Controlled Tumor Protein (TCTP), Negatively Affects Rapamycin-Induced Autophagy in Post-Diauxic Growth Phase

Translationally controlled tumor protein (TCTP) is a multifunctional and highly conserved protein from yeast to humans. Recently, its role in non-selective autophagy has been reported with controversial results in mammalian and human cells. Herein we examine the effect of Mmi1, the yeast ortholog of TCTP, on non-selective autophagy in budding yeast Saccharomyces cerevisiae, a well-established model system to monitor autophagy. We induced autophagy by nitrogen starvation or rapamycin addition and measured autophagy by using the Pho8Δ60 and GFP-Atg8 processing assays in WT, mmi1Δ, and in autophagy-deficient strains atg8Δ or atg1Δ. Our results demonstrate that Mmi1 does not affect basal or nitrogen starvation-induced autophagy. However, an increased rapamycin-induced autophagy is detected in mmi1Δ strain when the cells enter the post-diauxic growth phase, and this phenotype can be rescued by inserted wild-type MMI1 gene. Further, the mmi1Δ cells exhibit significantly lower amounts of reactive oxygen species (ROS) in the post-diauxic growth phase compared to WT cells. In summary, our study suggests that Mmi1 negatively affects rapamycin-induced autophagy in the post-diauxic growth phase and supports the role of Mmi1/TCTP as a negative autophagy regulator in eukaryotic cells.

VSClust: feature-based variance-sensitive clustering of omics data

Motivation

Data clustering is indispensable for identifying biologically relevant molecular features in large-scale omics experiments with thousands of measurements at multiple conditions. Optimal clustering results yield groups of functionally related features that may include genes, proteins and metabolites in biological processes and molecular networks. Omics experiments typically include replicated measurements of each feature within a given condition to statistically assess feature-specific variation. Current clustering approaches ignore this variation by averaging, which often leads to incorrect cluster assignments.

Results

We present VSClust that accounts for feature-specific variance. Based on an algorithm derived from fuzzy clustering, VSClust unifies statistical testing with pattern recognition to cluster the data into feature groups that more accurately reflect the underlying molecular and functional behavior. We apply VSClust to artificial and experimental datasets comprising hundreds to >80 000 features across 6-20 different conditions including genomics, transcriptomics, proteomics and metabolomics experiments. VSClust avoids arbitrary averaging methods, outperforms standard fuzzy c-means clustering and simplifies the data analysis workflow in large-scale omics studies.

Availability and implementation

Download VSClust at https://bitbucket.org/veitveit/vsclust or access it through computproteomics.bmb.sdu.dk/Apps/VSClust.

Supplementary information

Supplementary data are available at Bioinformatics online.

Therapy-Induced MHC I Ligands Shape Neo-Antitumor CD8 T Cell Responses during Oncolytic Virus-Based Cancer Immunotherapy

Oncolytic viruses (OVs), known for their cancer-killing characteristics, also overturn tumor-associated defects in antigen presentation through the MHC class I pathway and induce protective neo-antitumor CD8 T cell responses. Nonetheless, whether OVs shape the tumor MHC-I ligandome remains unknown. Here, we investigated if an OV induces the presentation of novel MHC I-bound tumor antigens (termed tumor MHC-I ligands). Using comparative mass spectrometry (MS)-based MHC-I ligandomics, we determined differential tumor MHC-I ligand expression following treatment with oncolytic reovirus in a murine ovarian cancer model. In vitro, we found that reovirus changes the tumor ligandome of cancer cells. Concurrent multiplexed quantitative proteomics revealed that the reovirus-induced changes in tumor MHC-I ligand presentation were mostly independent of their source proteins. In an in vivo model, tumor MHC-I ligands induced by reovirus were detectable not only in tumor tissues but also the spleens (a source of antigen-presenting cells) of tumor-bearing mice. Most importantly, therapy-induced MHC-I ligands stimulated antigen-specific IFNγ responses in antitumor CD8 T cells from mice treated with reovirus. These data show that therapy-induced MHC-I ligands may shape underlying neo-antitumor CD8 T cell responses. As such, they should be considered in strategies promoting the efficacy of OV-based cancer immunotherapies.

Inhibition of Pyruvate Dehydrogenase Kinase Enhances the Antitumor Efficacy of Oncolytic Reovirus

Oncolytic viruses (OV) such as reovirus preferentially infect and kill cancer cells. Thus, the mechanisms that dictate the susceptibility of cancer cells to OV-induced cytotoxicity hold the key to their success in clinics. Here, we investigated whether cancer cell metabolism defines its susceptibility to OV and if OV-induced metabolic perturbations can be therapeutically targeted. Using mass spectrometry-based metabolomics and extracellular flux analysis on a panel of cancer cell lines with varying degrees of susceptibility to reovirus, we found that OV-induced changes in central energy metabolism, pyruvate metabolism, and oxidative stress correlate with their susceptibility to reovirus. In particular, reovirus infection accentuated Warburg-like metabolic perturbations in cell lines relatively resistant to oncolysis. These metabolic changes were facilitated by oxidative stress-induced inhibitory phosphorylation of pyruvate dehydrogenase (PDH) that impaired the routing of pyruvate into the tricarboxylic acid cycle and established a metabolic state unsupportive of OV replication. From the therapeutic perspective, reactivation of PDH in cancer cells that were weakly sensitive for reovirus, either through PDH kinase (PDK) inhibitors dichloroacetate and AZD7545 or short hairpin RNA-specific depletion of PDK1, enhanced the efficacy of reovirus-induced oncolysis in vitro and in vivo. These findings identify targeted metabolic reprogramming as a possible combination strategy to enhance the antitumor effects of OV in clinics. SIGNIFICANCE: This study proposes targeted metabolic reprogramming as a valid combinatorial strategy to enhance the translational efficacy of oncolytic virus-based cancer therapies.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/15/3824/F1.large.jpg.

HDAC6 differentially regulates autophagy in stem-like versus differentiated cancer cells

Cancer stem-like cells (CSCs), a small population of pluripotent cells residing within heterogeneous tumor mass, remain highly resistant to various chemotherapies as compared to the differentiated cancer cells. It is being postulated that CSCs possess unique molecular mechanisms, such as autophagic homeostasis, that allow CSCs to withstand the therapeutic assaults. Here we demonstrate that HDAC6 inhibition differentially modulates macroautophagy/autophagy in CSCs as compared to that of differentiated cancer cells. Using human and murine CSC models and differentiated cells, we show that the inhibition or knockdown (KD) of HDAC6 decreases CSC pluripotency by downregulating major pluripotency factors POU5F1, NANOG and SOX2. This decreased HDAC6 expression increases ACTB, TUBB3 and CSN2 expression and promotes differentiation in CSCs in an apoptosis-independent manner. Mechanistically, HDAC6 KD in CSCs decreases pluripotency by promoting autophagy, whereas the inhibition of pluripotency via retinoic acid treatment, POU5F1 or autophagy-related gene (ATG7 and ATG12) KD in CSCs decreases HDAC6 expression and promotes differentiation. Interestingly, HDAC6 KD-mediated CSC growth inhibition is further enhanced in the presence of autophagy inducers Tat-Beclin 1 peptide and rapamycin. In contrast to the results observed in CSCs, HDAC6 KD in differentiated breast cancer cells downregulates autophagy and increases apoptosis. Furthermore, the autophagy regulator p-MTOR, upstream negative regulators of p-MTOR (TSC1 and TSC2) and downstream effectors of p-MTOR (p-RPS6KB and p-EIF4EBP1) are differentially regulated in CSCs versus differentiated cancer cells following HDAC6 KD. Overall these data identify the differential regulation of autophagy as a molecular link behind the differing chemo-susceptibility of CSCs and differentiated cancer cells.

Multiplexed Relative Quantitation with Isobaric Tagging Mass Spectrometry Reveals Class I Major Histocompatibility Complex Ligand Dynamics in Response to Doxorubicin

MHC-I peptides are intracellular-cleaved peptides, usually 8-11 amino acids in length, which are presented on the cell surface and facilitate CD8⁺ T cell responses. Despite the appreciation of CD8⁺ T-cell antitumor immune responses toward improvement in patient outcomes, the MHC-I peptide ligands that facilitate the response are poorly described. Along these same lines, although many therapies have been recognized for their ability to reinvigorate antitumor CD8⁺ T-cell responses, whether these therapies alter the MHC-I peptide repertoire has not been fully assessed due to the lack of quantitative strategies. We develop a multiplexing platform for screening therapy-induced MHC-I ligands by employing tandem mass tags (TMTs). We applied this approach to measuring responses to doxorubicin, which is known to promote antitumor CD8⁺ T-cell responses during its therapeutic administration in cancer patients. Using both in vitro and in vivo systems, we show successful relative quantitation of MHC-I ligands using TMT-based multiplexing and demonstrate that doxorubicin induces MHC-I peptide ligands that are largely derived from mitotic progression and cell-cycle proteins. This high-throughput MHC-I ligand discovery approach may enable further explorations to understand how small molecules and other therapies alter MHC-I ligand presentation that may be harnessed for CD8⁺ T-cell-based immunotherapies.

Analysis of autophagy activated during changes in carbon source availability in yeast cells

Autophagy is a conserved intracellular degradation system in eukaryotes. Recent studies have revealed that autophagy can be induced not only by nitrogen starvation but also by many other stimuli. However, questions persist regarding the types of conditions that induce autophagy, as well as the particular kinds of autophagy that are induced under these specific conditions. In experimental studies, abrupt nutrient changes are often used to induce autophagy. In this study, we investigated autophagy induction in batch culture on low-glucose medium, in which growth of yeast (Saccharomyces cerevisiae) cells is clearly reflected exclusively by carbon source state. In this medium, cells pass sequentially through three stages: glucose-utilizing, ethanol-utilizing, and ethanol-depleted phases. Using GFP cleavage assay by immunoblotting methods, fluorescence microscopy, and transmission electron microscopy ultrastructural analysis, we found that bulk autophagy and endoplasmic reticulum-phagy are induced starting at the ethanol-utilizing phase, and bulk autophagy is activated to a greater extent in the ethanol-depleted phase. Furthermore, we found that mitophagy is induced by ethanol depletion. Microautophagy occurred after glucose depletion and involved incorporation of cytosolic components and lipid droplets into the vacuolar lumen. Moreover, we observed that autophagy-deficient cells grow more slowly in the ethanol-utilizing phase and exhibit a delay in growth resumption when they are shifted to fresh medium from the ethanol-depleted phase. Our findings suggest that distinct types of autophagy are induced in yeast cells undergoing gradual changes in carbon source availability.

TAp73 Modifies Metabolism and Positively Regulates Growth of Cancer Stem-Like Cells in a Redox-Sensitive Manner

PURPOSE

Stem-like cancer cells, with characteristic self-renewal abilities, remain highly refractory to various clinical interventions. As such, stemness-inhibiting entities, such as tumor suppressor p53, are therapeutically pursued for their anticancer activities. Interestingly, similar implications for tumor suppressor TAp73 in regulating stemness features within stem-like cancer cells remain unknown.Experimental Design: This study utilizes various in vitro molecular biology techniques, including immunoblotting, qRT-PCR, and mass spectrometry-based proteomics, and metabolomics approaches to study the role of TAp73 in human and murine embryonal carcinoma stem-like cells (ECSLC) as well as human breast cancer stem-like cells (BCSLC). These findings were confirmed using patient-derived brain tumor-initiating cells (BTIC) and in vivo xenograft models.

RESULTS

TAp73 inhibition decreases the expression of stem cell transcription factors Oct4, Nanog, and Sox-2, as well as tumorsphere formation capacity in ECSLCs. In vivo, TAp73-deficient ECSLCs and BCSLCs demonstrate decreased tumorigenic potential when xenografted in mice. Mechanistically, TAp73 modifies the proline regulatory axis through regulation of enzymes GLS, OAT, and PYCR1 involved in the interconversion of proline-glutamine-ornithine. Further, TAp73 deficiency exacerbates glutamine dependency, enhances accumulation of reactive oxygen species through reduced superoxide dismutase 1 (SOD1) expression, and promotes differentiation by arresting cell cycle and elevating autophagy. Most importantly, the knockdown of TAp73 in CD133^HI BTICs, separated from three different glioblastoma patients, strongly decreases the expression of prosurvival factors Sox-2, BMI-1, and SOD1, and profoundly decreases their self-renewal capacity as evidenced through their reduced tumorsphere formation ability.

CONCLUSIONS

Collectively, we reveal a clinically relevant aspect of cancer cell growth and stemness regulation through TAp73-mediated redox-sensitive metabolic reprogramming.

Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources

Cells constantly adapt to environmental fluctuations. These physiological changes require time and therefore cause a lag phase during which the cells do not function optimally. Interestingly, past exposure to an environmental condition can shorten the time needed to adapt when the condition re-occurs, even in daughter cells that never directly encountered the initial condition. Here, we use the molecular toolbox of Saccharomyces cerevisiae to systematically unravel the molecular mechanism underlying such history-dependent behavior in transitions between glucose and maltose. In contrast to previous hypotheses, the behavior does not depend on persistence of proteins involved in metabolism of a specific sugar. Instead, presence of glucose induces a gradual decline in the cells' ability to activate respiration, which is needed to metabolize alternative carbon sources. These results reveal how trans-generational transitions in central carbon metabolism generate history-dependent behavior in yeast, and provide a mechanistic framework for similar phenomena in other cell types.

Complete Native Stable Isotope Labeling by Amino Acids of Saccharomyces cerevisiae for Global Proteomic Analysis

Knowledge about the functions of individual proteins on a system-wide level is crucial to fully understand molecular mechanisms underlying cellular processes. A considerable part of the proteome across all organisms is still poorly characterized. Mass spectrometry is an efficient technology for the global study of proteins. One of the most prominent methods for accurate proteome-wide comparative quantification is stable isotope labeling by amino acids in cell culture (SILAC). However, application of SILAC to prototrophic organisms such as Saccharomyces cerevisiae, also known as baker's yeast, is compromised since they are able to synthesize all amino acids on their own. Here, we describe an advanced strategy, termed 2nSILAC, that allows for in vivo labeling of prototrophic baker's yeast using heavy arginine and lysine under fermentable and respiratory growth conditions, making it a suitable tool for the global study of protein functions. This generic 2nSILAC strategy allows for directly using and systematically screening yeast mutant strain collections available to the scientific community. We exemplarily demonstrate its high potential by analyzing the effects of mitochondrial gene deletions in mitochondrial fractions using quantitative mass spectrometry revealing the role of Coi1 for the assembly of cytochrome c oxidase (respiratory chain complex IV).