Global proteome turnover analyses of the Yeasts S. cerevisiae and S. pombe

Harnessing Yeast Peroxisomes and Cytosol Acetyl-CoA for Sesquiterpene α-Humulene Production

Metabolic engineering of Saccharomyces cerevisiae focusing on the cytoplasm for sustainable terpenoid production is commonly practiced. However, engineering organelles for terpenoid production is rarely reported. Herein, peroxisomes, together with the cytoplasm, were engineered to boost sesquiterpene α-humulene synthesis in S. cerevisiae. The farnesyl diphosphate synthetic pathway and α-humulene synthase were successfully expressed inside yeast peroxisomes to enable high-level α-humulene production with glucose as the sole carbon source. With the combination of peroxisomal and cytoplasmic engineering, α-humulene production was increased by 2.5-fold compared to that in cytoplasm-engineered recombinant strains. Finally, the α-humulene titer of 1726.78 mg/L was achieved by fed-batch fermentation in a 5 L bioreactor. The strategy presented here offers an efficient method for terpenoid production in S. cerevisiae.

Poor old pores-The challenge of making and maintaining nuclear pore complexes in aging

The nuclear pore complex (NPC) is the sole gateway to the nuclear interior, and its function is essential to all eukaryotic life. Controlling the functionality of NPCs is a tremendous challenge for cells. Firstly, NPCs are large structures, and their complex assembly does occasionally go awry. Secondly, once assembled, some components of the NPC persist for an extremely long time and, as a result, are susceptible to accumulate damage. Lastly, a significant proportion of the NPC is composed of intrinsically disordered proteins that are prone to aggregation. In this review, we summarize how the quality of NPCs is guarded in young cells and discuss the current knowledge on the fate of NPCs during normal aging in different tissues and organisms. We discuss the extent to which current data supports a hypothesis that NPCs are poorly maintained during aging of nondividing cells, while in dividing cells the main challenge is related to the assembly of new NPCs. Our survey of current knowledge points toward NPC quality control as an important node in aging of both dividing and nondividing cells. Here, the loss of protein homeostasis during aging is central and the NPC appears to both be impacted by, and to drive, this process.

YQFC: a web tool to compare quantitative biological features between two yeast gene lists

Nowadays high-throughput omics technologies are routinely used in biological research. From the omics data, researchers can easily get two gene lists (e.g. stress-induced genes vs. stress-repressed genes) related to their biological question. The next step would be to apply enrichment analysis tools to identify distinct functional/regulatory features between these two gene lists for further investigation. Although various enrichment analysis tools are already available, two challenges remain to be addressed. First, most existing tools are designed to analyze only one gene list, so they cannot directly compare two gene lists. Second, almost all existing tools focus on identifying the enriched qualitative features (e.g. gene ontology [GO] terms, pathways, domains, etc.). Many quantitative features (e.g. number of mRNA isoforms of a gene, mRNA half-life, protein half-life, transcriptional plasticity, translational efficiency, etc.) are available in the yeast, but no existing tools provide analyses on these quantitative features. To address these two challenges, here we present Yeast Quantitative Features Comparator (YQFC) that can directly compare various quantitative features between two yeast gene lists. In YQFC, we comprehensively collected and processed 85 quantitative features from the yeast literature and yeast databases. For each quantitative feature, YQFC provides three statistical tests (t-test, U test and KS test) to test whether this quantitative feature is statistically different between the two input yeast gene lists. The distinct quantitative features identified by YQFC may help researchers to study the underlying molecular mechanisms that differentiate the two input yeast gene lists. We believe that YQFC is a useful tool to expedite the biological research that uses high-throughput omics technologies.

DATABASE URL

http://cosbi2.ee.ncku.edu.tw/YQFC/.

Yeast systems biology in understanding principles of physiology underlying complex human diseases

Complex human diseases commonly arise from deregulation of cell growth, metabolism, and/or gene expression. Yeast is a eukaryal model organism that is widely used to study these processes. Yeast systems biology benefits from the ability to exert fine experimental control over the cell growth rate and nutrient composition, which allows orthogonal experimental design and generation of multi-omics data at high resolution. This has led to several insights on the principles of cellular physiology, including many cellular processes associated with complex human diseases. Here we review these biological insights together with experimental and modeling approaches developed in yeast to study systems biology. The role of yeast systems biology to further advance systems and personalized therapies for complex diseases is discussed.

Homeostasis in the Central Dogma of molecular biology: the importance of mRNA instability

Cell survival requires the control of biomolecule concentration, i.e. biomolecules should approach homeostasis. With information-carrying macromolecules, the particular concentration variation ranges depend on each type: DNA is not buffered, but mRNA and protein concentrations are homeostatically controlled, which leads to the ribostasis and proteostasis concepts. In recent years, we have studied the particular features of mRNA ribostasis and proteostasis in the model organism S. cerevisiae. Here we extend this study by comparing published data from three other model organisms: E. coli, S. pombe and cultured human cells. We describe how mRNA ribostasis is less strict than proteostasis. A constant ratio appears between the average decay and dilution rates during cell growth for mRNA, but not for proteins. We postulate that this is due to a trade-off between the cost of synthesis and the response capacity. This compromise takes place at the transcription level, but is not possible at the translation level as the high stability of proteins, versus that of mRNAs, precludes it. We hypothesize that the middle-place role of mRNA in the Central Dogma of Molecular Biology and its chemical instability make it more suitable than proteins for the fast changes needed for gene regulation.

Cycles of autoubiquitination and deubiquitination regulate the ERAD ubiquitin ligase Hrd1

Misfolded proteins in the lumen of the endoplasmic reticulum (ER) are retrotranslocated into the cytosol and polyubiquitinated before being degraded by the proteasome. The multi-spanning ubiquitin ligase Hrd1 forms the retrotranslocation channel and associates with three other membrane proteins (Hrd3, Usa1, Der1) of poorly defined function. The Hrd1 channel is gated by autoubiquitination, but how Hrd1 escapes degradation by the proteasome and returns to its inactive ground state is unknown. Here, we show that autoubiquitination of Hrd1 is counteracted by Ubp1, a deubiquitinating enzyme that requires its N-terminal transmembrane segment for activity towards Hrd1. The Hrd1 partner Hrd3 serves as a brake for autoubiquitination, while Usa1 attenuates Ubp1’s deubiquitination activity through an inhibitory effect of its UBL domain. These results lead to a model in which the Hrd1 channel is regulated by cycles of autoubiquitination and deubiquitination, reactions that are modulated by the other components of the Hrd1 complex.

Just like factories make mistakes when producing products, cells make mistakes when producing proteins. In cells, a compartment called the endoplasmic reticulum is where about one third of all proteins are produced, and where new proteins undergo quality control. Damaged or misfolded proteins are removed by a process called endoplasmic reticulum-associated degradation (ERAD for short), because if damaged proteins accumulate, cells become stressed.

One type of ERAD is driven by a protein called Hrd1. Together with other components, Hrd1 labels damaged proteins with a ubiquitin tag that acts as a flag for degradation. Hrd1 has a paradoxical feature, however. To be active, Hrd1 tags itself with ubiquitin but this also makes it more prone to becoming degraded. How does Hrd1 remain active while avoiding its own degradation?

To address this question, Peterson et al. forced budding yeast cells to produce high levels of 23 different enzymes that remove ubiquitin tags. One of these enzymes, called Ubp1, was able remove the ubiquitin tag from Hrd1, though it had not been seen in the ERAD pathway before. Further experiments also showed that Ubp1 was able to regulate Hrd1 activity, making Ubp1 a regulator of Hrd1 dependent protein quality control.

Without protein quality control, damaged proteins can contribute to various diseases. ERAD is a common quality control system for proteins, present in many different species, ranging from yeast to animals. Therefore, understanding how ERAD works in budding yeast may also increase understanding of how human cells deal with damaged proteins.

Multiplexed proteome profiling of carbon source perturbations in two yeast species with SL-SP3-TMT

Saccharomyces cerevisiae and Schizosaccharomyces pombe are the most commonly studied yeast model systems, yet comparisons of global proteome remodeling between these yeast species are scarce. Here, we profile the proteomes of S. cerevisiae and S. pombe cultured with either glucose or pyruvate as the sole carbon source to define common and distinctive alterations in the protein landscape across species. In addition, we develop an updated streamlined-tandem mass tag (SL-TMT) strategy that substitutes chemical-based precipitation with more versatile bead-based protein aggregation method (SP3) prior to enzymatic digestion and TMT labeling. Our new workflow, SL-SP3-TMT, allow for near-complete proteome profiles in a single experiment for each species. The data reveal expected alterations in protein abundance and differences between species, highlighted complete canonical biochemical pathways, and provided insight into previously uncharacterized proteins. The techniques used herein, namely SL-SP3-TMT, can be applied to virtually any experiment aiming to study remodeling of the proteome using a high-throughput, comprehensive, yet streamlined mass spectrometry-based strategy. SIGNIFICANCE: Saccharomyces cerevisiae and Schizosaccharomyces pombe are single-celled eukaryotes that diverged from a common ancestor over a period of 100 million years, such that evolution has driven fundamental differences between the two species. Cellular metabolism and the regulation thereof are vital for living organisms. Here, we hypothesize that large scale proteomic alterations are prevalent upon the substitution of glucose with another carbon source, in this case pyruvate. To efficiently process our samples, we developed an updated streamlined-tandem mass tag (SL-TMT) strategy with more versatile bead-based protein aggregation. The data revealed expected alterations in protein abundance and illustrated differences between species. We highlighted complete canonical biochemical pathways and provided insight into previously uncharacterized proteins.

Big data in yeast systems biology

Systems biology uses computational and mathematical modeling to study complex interactions in a biological system. The yeast Saccharomyces cerevisiae, which has served as both an important model organism and cell factory, has pioneered both the early development of such models and modeling concepts, and the more recent integration of multi-omics big data in these models to elucidate fundamental principles of biology. Here, we review the advancement of big data technologies to gain biological insight in three aspects of yeast systems biology: gene expression dynamics, cellular metabolism and the regulation network between gene expression and metabolism. The role of big data and complementary modeling approaches, including the expansion of genome-scale metabolic models and machine learning methodologies, are discussed as key drivers in the rapid advancement of yeast systems biology.

Ste20 and Cla4 modulate the expression of the glycerol biosynthesis enzyme Gpd1 by a novel MAPK-independent pathway

p21-activated kinases (PAKs) are important signalling molecules with a wide range of functions. In budding yeast, the main PAKs Ste20 and Cla4 regulate the response to hyperosmotic stress, which is an excellent model for the adaptation to changing environmental conditions. In this pathway, the only known function of Ste20 and Cla4 is the activation of a mitogen-activated protein kinase (MAPK) cascade through Ste11. This eventually leads to increased transcription of glycerol biosynthesis genes, the most important response to hyperosmotic shock. Here, we show that Ste20 and Cla4 not only stimulate transcription, they also bind to the glycerol biosynthesis enzymes Gpd1, Gpp1 and Gpp2. Protein levels of Gpd1, the enzyme that catalyzes the rate limiting step in glycerol synthesis, positively correlate with glucose availability. Using a chemical genetics approach, we find that simultaneous inactivation of STE20 and CLA4 reduces the glucose-induced increase of Gpd1 levels, whereas the deletion of either STE20 or CLA4 alone has no effect. This is also observed for the hyperosmotic stress-induced increase of Gpd1 levels. Importantly, under both conditions the deletion of STE11 has no effect on Gpd1 induction. These observations suggest that Ste20 and Cla4 not only have a role in the transcriptional regulation of GPD1 through Ste11. They also seem to modulate GPD1 expression at another level such as translation or protein degradation.

Degradation rate uniformity determines success of oscillations in repressive feedback regulatory networks

Ring oscillators are biochemical circuits consisting of a ring of interactions capable of sustained oscillations. The nonlinear interactions between genes hinder the analytical insight into their function, usually requiring computational exploration. Here, we show that, despite the apparent complexity, the stability of the unique steady state in an incoherent feedback ring depends only on the degradation rates and a single parameter summarizing the feedback of the circuit. Concretely, we show that the range of regulatory parameters that yield oscillatory behaviour is maximized when the degradation rates are equal. Strikingly, this result holds independently of the regulatory functions used or number of genes. We also derive properties of the oscillations as a function of the degradation rates and number of nodes forming the ring. Finally, we explore the role of mRNA dynamics by applying the generic results to the specific case with two naturally different degradation timescales.

Structure, Function, and Regulation of the Hsp90 Machinery

Heat shock protein 90 (Hsp90) is a molecular chaperone involved in the maturation of a plethora of substrates ("clients"), including protein kinases, transcription factors, and E3 ubiquitin ligases, positioning Hsp90 as a central regulator of cellular proteostasis. Hsp90 undergoes large conformational changes during its ATPase cycle. The processing of clients by cytosolic Hsp90 is assisted by a cohort of cochaperones that affect client recruitment, Hsp90 ATPase function or conformational rearrangements in Hsp90. Because of the importance of Hsp90 in regulating central cellular pathways, strategies for the pharmacological inhibition of the Hsp90 machinery in diseases such as cancer and neurodegeneration are being developed. In this review, we summarize recent structural and mechanistic progress in defining the function of organelle-specific and cytosolic Hsp90, including the impact of individual cochaperones on the maturation of specific clients and complexes with clients as well as ways of exploiting Hsp90 as a drug target.

A molecular toolbox for studying protein degradation in mammalian cells

Protein degradation is a crucial regulatory process in maintaining cellular proteostasis. The selective degradation of intracellular proteins controls diverse cellular and biochemical processes in all kingdoms of life. Targeted protein degradation is implicated in controlling the levels of regulatory proteins as well as eliminating misfolded and any otherwise abnormal proteins. Deregulation of protein degradation is concomitant with the progression of various neurodegenerative disorders such as Parkinson's and Alzheimer's diseases. Thus, methods of measuring metabolic half-lives of proteins greatly influence our understanding of the diverse functions of proteins in mammalian cells including neuronal cells. Historically, protein degradation rates have been studied via exploiting methods that estimate overall protein degradation or focus on few individual proteins. Notably, with the recent technical advances and developments in proteomic and imaging techniques, it is now possible to measure degradation rates of a large repertoire of defined proteins and analyze the degradation profile in a detailed spatio-temporal manner, with the aim of determining proteome-wide protein stabilities upon different physiological conditions. Herein, we discuss some of the classical and novel methods for determining protein degradation rates highlighting the crucial role of some state of art approaches in deciphering the global impact of dynamic nature of targeted degradation of cellular proteins. This article is part of the Special Issue "Proteomics".

Proteomics Links Ubiquitin Chain Topology Change to Transcription Factor Activation

A surprising complexity of ubiquitin signaling has emerged with identification of different ubiquitin chain topologies. However, mechanisms of how the diverse ubiquitin codes control biological processes remain poorly understood. Here, we use quantitative whole-proteome mass spectrometry to identify yeast proteins that are regulated by lysine 11 (K11)-linked ubiquitin chains. The entire Met4 pathway, which links cell proliferation with sulfur amino acid metabolism, was significantly affected by K11 chains and selected for mechanistic studies. Previously, we demonstrated that a K48-linked ubiquitin chain represses the transcription factor Met4. Here, we show that efficient Met4 activation requires a K11-linked topology. Mechanistically, our results propose that the K48 chain binds to a topology-selective tandem ubiquitin binding region in Met4 and competes with binding of the basal transcription machinery to the same region. The change to K11-enriched chain architecture releases this competition and permits binding of the basal transcription complex to activate transcription.

Zinc-dependent activation of the Pho8 alkaline phosphatase in Schizosaccharomyces pombe

Genome-wide analyses have revealed that during metal ion starvation, many cells undergo programmed changes in their transcriptome or proteome that lower the levels of abundant metalloproteins, conserving metal ions for more critical functions. Here we investigated how changes in cellular zinc status affect the expression and activity of the zinc-requiring Pho8 alkaline phosphatase from fission yeast (Schizosaccharomyces pombe). In S. pombe, Pho8 is a membrane-tethered and processed glycoprotein that resides in the vacuole. Using alkaline phosphatase activity assays along with various biochemical analyses, we found that Pho8 is active when zinc is plentiful and inactive when zinc is limited. Although Pho8 activity depended on zinc, we also found that higher levels of pho8 mRNAs and Pho8 protein accumulate in zinc-deficient cells. To gain a better understanding of the inverse relationship between pho8 mRNA levels and Pho8 activity, we examined the effects of zinc on the stability and processing of the Pho8 protein. We show that Pho8 is processed regardless of zinc status and that mature Pho8 accumulates under all conditions. We also noted that alkaline phosphatase activity is rapidly restored when zinc is resupplied to cells, even in the presence of the protein synthesis inhibitor cycloheximide. Our results suggest that S. pombe cells maintain inactive pools of Pho8 proteins under low-zinc conditions and that these pools facilitate rapid restoration of Pho8 activity when zinc ions become available.

Quantitative Analyses of the Yeast Oxidative Protein Folding Pathway In Vitro and In Vivo

Aims: Efficient oxidative protein folding (OPF) in the endoplasmic reticulum (ER) is a key requirement of the eukaryotic secretory pathway. In particular, protein folding linked to the formation of disulfide bonds, an activity dependent on the enzyme protein disulfide isomerase (PDI), is crucial. For the de novo formation of disulfide bonds, reduced PDI must be reoxidized by an ER-located oxidase (ERO1). Despite some knowledge of this pathway, the kinetic parameters with which these components act and the importance of specific parameters, such as PDI reoxidation by Ero1, for the overall performance of OPF in vivo remain poorly understood. Results: We established an in vitro system using purified yeast (Saccharomyces cerevisiae) PDI (Pdi1p) and ERO1 (Ero1p) to investigate OPF. This necessitated the development of a novel reduction/oxidation processing strategy to generate homogenously oxidized recombinant yeast Ero1p. This new methodology enabled the quantitative assessment of the interaction of Pdi1p and Ero1p in vitro by measuring oxygen consumption and reoxidation of reduced RNase A. The resulting quantitative data were then used to generate a simple model that can describe the oxidizing capacity of Pdi1p and Ero1p in vitro and predict the in vivo effect of modulation of the levels of these proteins. Innovation: We describe a model that can be used to explore the OPF pathway and its control in a quantitative way. Conclusion: Our study informs and provides new insights into how OPF works at a molecular level and provides a platform for the design of more efficient heterologous protein expression systems in yeast.

Endosome and Golgi-associated degradation (EGAD) of membrane proteins regulates sphingolipid metabolism

Cellular homeostasis requires the ubiquitin-dependent degradation of membrane proteins. This was assumed to be mediated exclusively either by endoplasmic reticulum-associated degradation (ERAD) or by endosomal sorting complexes required for transport (ESCRT)-dependent lysosomal degradation. We identified in Saccharomyces cerevisiae an additional pathway that selectively extracts membrane proteins at Golgi and endosomes for degradation by cytosolic proteasomes. One endogenous substrate of this endosome and Golgi-associated degradation pathway (EGAD) is the ER-resident membrane protein Orm2, a negative regulator of sphingolipid biosynthesis. Orm2 degradation is initiated by phosphorylation, which triggers its ER export. Once on Golgi and endosomes, Orm2 is poly-ubiquitinated by the membrane-embedded "Defective in SREBP cleavage" (Dsc) ubiquitin ligase complex. Cdc48/VCP then extracts ubiquitinated Orm2 from membranes, which is tightly coupled to the proteasomal degradation of Orm2. Thereby, EGAD prevents the accumulation of Orm2 at the ER and in post-ER compartments and promotes the controlled de-repression of sphingolipid biosynthesis. Thus, the selective degradation of membrane proteins by EGAD contributes to proteostasis and lipid homeostasis in eukaryotic cells.

The functional complexity of the RNA-binding protein Yra1: mRNA biogenesis, genome stability and DSB repair

The mRNA export adaptor Yra1 is essential in S. cerevisiae, and conserved from yeast to human (ALY/REF). It is well characterized for its function during transcription elongation, 3' processing and mRNA export. Recently, different studies linked Yra1 to genome stability showing that Yra1 overexpression causes DNA Double Strand Breaks through DNA:RNA hybrids stabilization, and that Yra1 depletion affects DSB repair. However, the mechanisms through which Yra1 contributes to genome stability maintenance are not fully understood. Interestingly, our results showed that the Yra1 C-box domain is required for Yra1 recruitment to an HO-induced irreparable DSB following extensive resection, and that it is essential to repair an HO-induced reparable DSB. Furthermore, we defined that the C-box domain of Yra1 plays a crucial role in DSB repair through homologous recombination but not through non-homologous end joining. Future studies aim at deciphering the mechanism by which Yra1 contributes to DSB repair by searching for Yra1 partners important for this process. This review focuses on the functional complexity of the Yra1 protein, not only summarizing its role in mRNA biogenesis but also emphasizing its auto-regulation and implication in genome integrity either through DNA:RNA hybrids stabilization or DNA double strand break repair in S. cerevisiae.

Protein synthesis rates and ribosome occupancies reveal determinants of translation elongation rates

Although protein synthesis dynamics has been studied both with theoretical models and by profiling ribosome footprints, the determinants of ribosome flux along open reading frames (ORFs) are not fully understood. Combining measurements of protein synthesis rate with ribosome footprinting data, we here inferred translation initiation and elongation rates for over a 1,000 ORFs in exponentially growing wild-type yeast cells. We found that the amino acid composition of synthesized proteins is as important a determinant of translation elongation rate as parameters related to codon and transfer RNA (tRNA) adaptation. We did not find evidence of ribosome collisions curbing the protein output of yeast transcripts, either in high translation conditions associated with exponential growth, or in strains in which deletion of individual ribosomal protein (RP) genes leads to globally increased or decreased translation. Slow translation elongation is characteristic of RP-encoding transcripts, which have markedly lower protein output compared with other transcripts with equally high ribosome densities.

Proteolytic regulation of mitochondrial dynamics

Spatiotemporal changes in the abundance, shape, and cellular localization of the mitochondrial network, also known as mitochondrial dynamics, are now widely recognized to play a key role in mitochondrial and cellular physiology as well as disease states. This process involves coordinated remodeling of the outer and inner mitochondrial membranes by conserved dynamin-like guanosine triphosphatases and their partner molecules in response to various physiological and stress stimuli. Although the core machineries that mediate fusion and partitioning of the mitochondrial network have been extensively characterized, many aspects of their function and regulation are incompletely understood and only beginning to emerge. In the present review we briefly summarize current knowledge about how the key mitochondrial dynamics-mediating factors are regulated via selective proteolysis by mitochondrial and cellular proteolytic machineries.

Not quite the SSAme: unique roles for the yeast cytosolic Hsp70s

The Heat Shock Protein 70s (Hsp70s) are an essential family of proteins involved in folding of new proteins and triaging of damaged proteins for proteasomal-mediated degradation. They are highly conserved in all organisms, with each organism possessing multiple highly similar Hsp70 variants (isoforms). These isoforms have been previously thought to be identical in function differing only in their spatio-temporal expression pattern. The model organism Saccharomyces cerevisiae (baker's yeast) expresses four Hsp70 isoforms Ssa1, 2, 3 and 4. Here, we review recent findings that suggest that despite their similarity, Ssa isoforms may have unique cellular functions.

The proteasome biogenesis regulator Rpn4 cooperates with the unfolded protein response to promote ER stress resistance

Misfolded proteins in the endoplasmic reticulum (ER) activate the unfolded protein response (UPR), which enhances protein folding to restore homeostasis. Additional pathways respond to ER stress, but how they help counteract protein misfolding is incompletely understood. Here, we develop a titratable system for the induction of ER stress in yeast to enable a genetic screen for factors that augment stress resistance independently of the UPR. We identify the proteasome biogenesis regulator Rpn4 and show that it cooperates with the UPR. Rpn4 abundance increases during ER stress, first by a post-transcriptional, then by a transcriptional mechanism. Induction of RPN4 transcription is triggered by cytosolic mislocalization of secretory proteins, is mediated by multiple signaling pathways and accelerates clearance of misfolded proteins from the cytosol. Thus, Rpn4 and the UPR are complementary elements of a modular cross-compartment response to ER stress.

The Balancing Act of Intrinsically Disordered Proteins: Enabling Functional Diversity while Minimizing Promiscuity

Intrinsically disordered proteins (IDPs) or regions (IDRs) perform diverse cellular functions, but are also prone to forming promiscuous and potentially deleterious interactions. We investigate the extent to which the properties of, and content in, IDRs have adapted to enable functional diversity while limiting interference from promiscuous interactions in the crowded cellular environment. Information on protein sequences, their predicted intrinsic disorder, and 3D structure contents is related to data on protein cellular concentrations, gene co-expression, and protein-protein interactions in the well-studied yeast Saccharomyces cerevisiae. Results reveal that both the protein IDR content and the frequency of "sticky" amino acids in IDRs (those more frequently involved in protein interfaces) decrease with increasing protein cellular concentration. This implies that the IDR content and the amino acid composition of IDRs experience negative selection as the protein concentration increases. In the S. cerevisiae protein-protein interaction network, the higher a protein's IDR content, the more frequently it interacts with IDR-containing partners, and the more functionally diverse the partners are. Employing a clustering analysis of Gene Ontology terms, we newly identify ~600 putative multifunctional proteins in S. cerevisiae. Strikingly, these proteins are enriched in IDRs and contribute significantly to all the observed trends. In particular, IDRs of multi-functional proteins feature more sticky amino acids than IDRs of their non-multifunctional counterparts, or the surfaces of structured yeast proteins. This property likely affords sufficient binding affinity for the functional interactions, commonly mediated by short IDR segments, thereby counterbalancing the loss in overall IDR conformational entropy upon binding.

Systematic analysis reveals the prevalence and principles of bypassable gene essentiality

Gene essentiality is a variable phenotypic trait, but to what extent and how essential genes can become dispensable for viability remain unclear. Here, we investigate 'bypass of essentiality (BOE)' - an underexplored type of digenic genetic interaction that renders essential genes dispensable. Through analyzing essential genes on one of the six chromosome arms of the fission yeast Schizosaccharomyces pombe, we find that, remarkably, as many as 27% of them can be converted to non-essential genes by BOE interactions. Using this dataset we identify three principles of essentiality bypass: bypassable essential genes tend to have lower importance, tend to exhibit differential essentiality between species, and tend to act with other bypassable genes. In addition, we delineate mechanisms underlying bypassable essentiality, including the previously unappreciated mechanism of dormant redundancy between paralogs. The new insights gained on bypassable essentiality deepen our understanding of genotype-phenotype relationships and will facilitate drug development related to essential genes.

A systematic approach to identify recycling endocytic cargo depending on the GARP complex

Proteins and lipids of the plasma membrane underlie constant remodeling via a combination of the secretory- and the endocytic pathway. In the yeast endocytic pathway, cargo is sorted for recycling to the plasma membrane or degradation in vacuoles. Previously we have shown a role for the GARP complex in sphingolipid sorting and homeostasis (Fröhlich et al. 2015). However, the majority of cargo sorted in a GARP dependent process remain largely unknown. Here we use auxin induced degradation of GARP combined with mass spectrometry based vacuolar proteomics and lipidomics to show that recycling of two specific groups of proteins, the amino-phospholipid flippases and cell wall synthesis proteins depends on a functional GARP complex. Our results suggest that mis-sorting of flippases and remodeling of the lipid composition are the first occurring defects in GARP mutants. Our assay can be adapted to systematically map cargo of the entire endocytic pathway.

Mapping Degradation Signals and Pathways in a Eukaryotic N-terminome

Most eukaryotic proteins are N-terminally acetylated. This modification can be recognized as a signal for selective protein degradation (degron) by the N-end rule pathways. However, the prevalence and specificity of such degrons in the proteome are unclear. Here, by systematically examining how protein turnover is affected by N-terminal sequences, we perform a comprehensive survey of degrons in the yeast N-terminome. We find that approximately 26% of nascent protein N termini encode cryptic degrons. These degrons exhibit high hydrophobicity and are frequently recognized by the E3 ubiquitin ligase Doa10, suggesting a role in protein quality control. In contrast, N-terminal acetylation rarely functions as a degron. Surprisingly, we identify two pathways where N-terminal acetylation has the opposite function and blocks protein degradation through the E3 ubiquitin ligase Ubr1. Our analysis highlights the complexity of N-terminal degrons and argues that hydrophobicity, not N-terminal acetylation, is the predominant feature of N-terminal degrons in nascent proteins.

Precise Post-translational Tuning Occurs for Most Protein Complex Components during Meiosis

Protein degradation is known to be a key component of expression regulation for individual genes, but its global impact on gene expression has been difficult to determine. We analyzed a parallel gene expression dataset of yeast meiotic differentiation, identifying instances of coordinated protein-level decreases to identify new cases of regulated meiotic protein degradation, including of ribosomes and targets of the meiosis-specific anaphase-promoting complex adaptor Ama1. Comparison of protein and translation measurements over time also revealed that, although meiotic cells are capable of synthesizing protein complex members at precisely matched levels, they typically do not. Instead, the members of most protein complexes are synthesized imprecisely, but their protein levels are matched, indicating that wild-type eukaryotic cells routinely use post-translational adjustment of protein complex partner levels to achieve proper stoichiometry. Outlier cases, in which specific complex components show divergent protein-level trends, suggest timed regulation of these complexes.

Production of Protein-Complex Components Is Stoichiometric and Lacks General Feedback Regulation in Eukaryotes

Constituents of multiprotein complexes are required at well-defined levels relative to each other. However, it remains unknown whether eukaryotic cells typically produce precise amounts of subunits, or instead rely on degradation to mitigate imprecise production. Here, we quantified the production rates of multiprotein complexes in unicellular and multicellular eukaryotes using ribosome profiling. By resolving read-mapping ambiguities, which occur for a large fraction of ribosome footprints and distort quantitation accuracy in eukaryotes, we found that obligate components of multiprotein complexes are produced in proportion to their stoichiometry, indicating that their abundances are already precisely tuned at the synthesis level. By systematically interrogating the impact of gene dosage variations in budding yeast, we found a general lack of negative feedback regulation protecting the normally precise rates of subunit synthesis. These results reveal a core principle of proteome homeostasis and highlight the evolution toward quantitative control at every step in the central dogma.

Distinct adaptive mechanisms drive recovery from aneuploidy caused by loss of the Ulp2 SUMO protease

In response to acute loss of the Ulp2 SUMO-specific protease, yeast become disomic for chromosome I (ChrI) and ChrXII. Here we report that ChrI disomy, which creates an adaptive advantage in part by increasing the dosage of the Ccr4 deadenylase, was eliminated by extended passaging. Loss of aneuploidy is often accompanied by mutations in essential SUMO-ligating enzymes, which reduced polySUMO-conjugate accumulation. The mRNA levels for almost all ribosomal proteins increase transiently upon initial loss of Ulp2, but elevated Ccr4 levels limit excess ribosome formation. Notably, extended passaging leads to increased levels of many small nucleolar RNAs (snoRNAs) involved in ribosome biogenesis, and higher dosage of three linked ChrXII snoRNA genes suppressed ChrXII disomy in ulp2Δ cells. Our data reveal that aneuploidy allows rapid adaptation to Ulp2 loss, but long-term adaptation restores euploidy. Cellular evolution restores homeostasis through countervailing mutations in SUMO-modification pathways and regulatory shifts in ribosome biogenesis.

Active degradation of MarA controls coordination of its downstream targets

Several key transcription factors have unusually short half-lives compared to other cellular proteins. Here, we explore the utility of active degradation in shaping how the multiple antibiotic resistance activator MarA coordinates its downstream targets. MarA controls a variety of stress response genes in Escherichia coli. We modify its half-life either by knocking down the protease that targets it via CRISPRi or by engineering MarA to protect it from degradation. Our experimental and analytical results indicate that active degradation can impact both the rate of coordination and the maximum coordination that downstream genes can achieve. In the context of multi-gene regulation, trade-offs between these properties show that perfect information fidelity and instantaneous coordination cannot coexist.

Waveforms of molecular oscillations reveal circadian timekeeping mechanisms

Circadian clocks play a pivotal role in orchestrating numerous physiological and developmental events. Waveform shapes of the oscillations of protein abundances can be informative about the underlying biochemical processes of circadian clocks. We derive a mathematical framework where waveforms do reveal hidden biochemical mechanisms of circadian timekeeping. We find that the cost of synthesizing proteins with particular waveforms can be substantially reduced by rhythmic protein half-lives over time, as supported by previous plant and mammalian data, as well as our own seedling experiment. We also find that previously enigmatic, cyclic expression of positive arm components within the mammalian and insect clocks allows both a broad range of peak time differences between protein waveforms and the symmetries of the waveforms about the peak times. Such various peak-time differences may facilitate tissue-specific or developmental stage-specific multicellular processes. Our waveform-guided approach can be extended to various biological oscillators, including cell-cycle and synthetic genetic oscillators.

Hang-Hyun Jo et al. derive a mathematical framework for analyzing circadian clock waveforms. Using data from plants and animals, they find that waveforms of clock protein profiles provide important information about the biochemical mechanisms of circadian timekeeping.

Effects of acclimation time and epigenetic mechanisms on growth of Neurospora in fluctuating environments

Reaction norms or tolerance curves have often been used to predict how organisms deal with fluctuating environments. A potential drawback is that reaction norms measured in different constant environments may not capture all aspects of organismal responses to fluctuating environments. We examined growth of the filamentous fungus Neurospora crassa in fluctuating temperatures and tested if growth in fluctuating temperatures can be explained simply by the growth in different constant temperatures or if more complex models are needed. In addition, as previous studies on fluctuating environments have revealed that past temperatures that organisms have experienced can affect their response to current temperature, we tested the roles of different epigenetic mechanisms in response to fluctuating environments using different mutants. We found that growth of Neurospora can be predicted in fluctuating temperatures to some extent if acclimation times are taken into account in the model. Interestingly, while fluctuating environments have been linked with epigenetic responses, we found only some evidence of involvement of epigenetic mechanisms on tolerating fluctuating temperatures. Mutants which lacked H3K4 or H3K36 methylation had slightly impaired response to temperature fluctuations, in addition the H3K4 methylation mutant and a mutant in the RNA interference pathway had altered acclimation times.

Proteome-scale relationships between local amino acid composition and protein fates and functions

Proteins with low-complexity domains continue to emerge as key players in both normal and pathological cellular processes. Although low-complexity domains are often grouped into a single class, individual low-complexity domains can differ substantially with respect to amino acid composition. These differences may strongly influence the physical properties, cellular regulation, and molecular functions of low-complexity domains. Therefore, we developed a bioinformatic approach to explore relationships between amino acid composition, protein metabolism, and protein function. We find that local compositional enrichment within protein sequences is associated with differences in translation efficiency, abundance, half-life, protein-protein interaction promiscuity, subcellular localization, and molecular functions of proteins on a proteome-wide scale. However, local enrichment of related amino acids is sometimes associated with opposite effects on protein regulation and function, highlighting the importance of distinguishing between different types of low-complexity domains. Furthermore, many of these effects are discernible at amino acid compositions below those required for classification as low-complexity or statistically-biased by traditional methods and in the absence of homopolymeric amino acid repeats, indicating that thresholds employed by classical methods may not reflect biologically relevant criteria. Application of our analyses to composition-driven processes, such as the formation of membraneless organelles, reveals distinct composition profiles even for closely related organelles. Collectively, these results provide a unique perspective and detailed insights into relationships between amino acid composition, protein metabolism, and protein functions.

Low-complexity domains in protein sequences are regions that are composed of only a few amino acids in the protein “alphabet”. These domains often have unique chemical properties and play important biological roles in both normal and disease-related processes. While a number of approaches have been developed to define low-complexity domains, these methods each possess conceptual limitations. Therefore, we developed a complementary approach that focuses on local amino acid composition (i.e. the amino acid composition within small regions of proteins). We find that high local composition of individual amino acids is associated with pervasive effects on protein metabolism, subcellular localization, and molecular function on a proteome-wide scale. Importantly, the nature of the effects depend on the type of amino acid enriched within the examined domains, and are observable in the absence of classically-defined low-complexity (and related) domains. Furthermore, we define the compositions of proteins involved in the formation of membraneless, protein-rich organelles such as stress granules and P-bodies. Our results provide a coherent view and unprecedented resolution of the effects of local amino acid enrichment on protein biology.

Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts

A challenge in solving the genotype-to-phenotype relationship is to predict a cell’s metabolome, believed to correlate poorly with gene expression. Using comparative quantitative proteomics, we found that differential protein expression in 97 Saccharomyces cerevisiae kinase deletion strains is non-redundant and dominated by abundance changes in metabolic enzymes. Associating differential enzyme expression landscapes to corresponding metabolomes using network models provided reasoning for poor proteome-metabolome correlations; differential protein expression redistributes flux control between many enzymes acting in concert, a mechanism not captured by one-to-one correlation statistics. Mapping these regulatory patterns using machine learning enabled the prediction of metabolite concentrations, as well as identification of candidate genes important for the regulation of metabolism. Overall, our study reveals that a large part of metabolism regulation is explained through coordinated enzyme expression changes. Our quantitative data indicate that this mechanism explains more than half of metabolism regulation and underlies the interdependency between enzyme levels and metabolism, which renders the metabolome a predictable phenotype.

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The proteome of kinase knockouts is dominated by enzyme abundance changes

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The enzyme expression profiles of kinase knockouts are non-redundant

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Metabolism is regulated by many expression changes acting in concert

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Machine learning accurately predicts the metabolome from enzyme abundance

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).

Making sense of snapshot data: ergodic principle for clonal cell populations

Population growth is often ignored when quantifying gene expression levels across clonal cell populations. We develop a framework for obtaining the molecule number distributions in an exponentially growing cell population taking into account its age structure. In the presence of generation time variability, the average acquired across a population snapshot does not obey the average of a dividing cell over time, apparently contradicting ergodicity between single cells and the population. Instead, we show that the variation observed across snapshots with known cell age is captured by cell histories, a single-cell measure obtained from tracking an arbitrary cell of the population back to the ancestor from which it originated. The correspondence between cells of known age in a population with their histories represents an ergodic principle that provides a new interpretation of population snapshot data. We illustrate the principle using analytical solutions of stochastic gene expression models in cell populations with arbitrary generation time distributions. We further elucidate that the principle breaks down for biochemical reactions that are under selection, such as the expression of genes conveying antibiotic resistance, which gives rise to an experimental criterion with which to probe selection on gene expression fluctuations.

Sequence features governing aggregation or degradation of prion-like proteins

Enhanced protein aggregation and/or impaired clearance of aggregates can lead to neurodegenerative disorders such as Alzheimer's Disease, Huntington's Disease, and prion diseases. Therefore, many protein quality control factors specialize in recognizing and degrading aggregation-prone proteins. Prions, which generally result from self-propagating protein aggregates, must therefore evade or outcompete these quality control systems in order to form and propagate in a cellular context. We developed a genetic screen in yeast that allowed us to explore the sequence features that promote degradation versus aggregation of a model glutamine/asparagine (Q/N)-rich prion domain from the yeast prion protein, Sup35, and two model glycine (G)-rich prion-like domains from the human proteins hnRNPA1 and hnRNPA2. Unexpectedly, we found that aggregation propensity and degradation propensity could be uncoupled in multiple ways. First, only a subset of classically aggregation-promoting amino acids elicited a strong degradation response in the G-rich prion-like domains. Specifically, large aliphatic residues enhanced degradation of the prion-like domains, whereas aromatic residues promoted prion aggregation without enhancing degradation. Second, the degradation-promoting effect of aliphatic residues was suppressed in the context of the Q/N-rich prion domain, and instead led to a dose-dependent increase in the frequency of spontaneous prion formation. Degradation suppression correlated with Q/N content of the surrounding prion domain, potentially indicating an underappreciated activity for these residues in yeast prion domains. Collectively, these results provide key insights into how certain aggregation-prone proteins may evade protein quality control degradation systems.

Glucose-Dependent Promoters for Dynamic Regulation of Metabolic Pathways

For an industrial fermentation process, it can be advantageous to decouple cell growth from product formation. This decoupling would allow for the rapid accumulation of biomass without inhibition from product formation, after which the fermentation can be switched to a mode where cells would grow minimally and primarily act as catalysts to convert substrate into desired product. The switch in fermentation mode should preferably be accomplished without the addition of expensive inducers. A common cell factory Saccharomyces cerevisiae is a Crabtree-positive yeast and is typically fermented at industrial scale under glucose-limited conditions to avoid the formation of ethanol. In this work, we aimed to identify and characterize promoters that depend on glucose concentration for use as dynamic control elements. Through analysis of mRNA data of S. cerevisiae grown in chemostats under glucose excess or limitation, we identified 34 candidate promoters that strongly responded to glucose presence or absence. These promoters were characterized in small-scale batch and fed-batch cultivations using a quickly maturing rapidly degrading green fluorescent protein yEGFP3-Cln2_PEST as a reporter. Expressing 3-hydroxypropionic acid (3HP) pathway from a set of selected regulated promoters allowed for suppression of 3HP production during glucose-excess phase of a batch cultivation with subsequent activation in glucose-limiting conditions. Regulating the 3HP pathway by the ICL1 promoter resulted in 70% improvement of 3HP titer in comparison to PGK1 promoter.

Evolutionary Convergence of Pathway-Specific Enzyme Expression Stoichiometry

Coexpression of proteins in response to pathway-inducing signals is the founding paradigm of gene regulation. However, it remains unexplored whether the relative abundance of co-regulated proteins requires precise tuning. Here, we present large-scale analyses of protein stoichiometry and corresponding regulatory strategies for 21 pathways and 67-224 operons in divergent bacteria separated by 0.6-2 billion years. Using end-enriched RNA-sequencing (Rend-seq) with single-nucleotide resolution, we found that many bacterial gene clusters encoding conserved pathways have undergone massive divergence in transcript abundance and architectures via remodeling of internal promoters and terminators. Remarkably, these evolutionary changes are compensated post-transcriptionally to maintain preferred stoichiometry of protein synthesis rates. Even more strikingly, in eukaryotic budding yeast, functionally analogous proteins that arose independently from bacterial counterparts also evolved to convergent in-pathway expression. The broad requirement for exact protein stoichiometries despite regulatory divergence provides an unexpected principle for building biological pathways both in nature and for synthetic activities.

Stochastic tuning of gene expression enables cellular adaptation in the absence of pre-existing regulatory circuitry

Cells adapt to familiar changes in their environment by activating predefined regulatory programs that establish adaptive gene expression states. These hard-wired pathways, however, may be inadequate for adaptation to environments never encountered before. Here, we reveal evidence for an alternative mode of gene regulation that enables adaptation to adverse conditions without relying on external sensory information or genetically predetermined cis-regulation. Instead, individual genes achieve optimal expression levels through a stochastic search for improved fitness. By focusing on improving the overall health of the cell, the proposed stochastic tuning mechanism discovers global gene expression states that are fundamentally new and yet optimized for novel environments. We provide experimental evidence for stochastic tuning in the adaptation of Saccharomyces cerevisiae to laboratory-engineered environments that are foreign to its native gene-regulatory network. Stochastic tuning operates locally at individual gene promoters, and its efficacy is modulated by perturbations to chromatin modification machinery.

Loss of mRNA surveillance pathways results in widespread protein aggregation

Eukaryotic cells contain translation-associated mRNA surveillance pathways which prevent the production of potentially toxic proteins from aberrant mRNA translation events. We found that loss of mRNA surveillance pathways in mutants deficient in nonsense-mediated decay (NMD), no-go decay (NGD) and nonstop decay (NSD) results in increased protein aggregation. We have isolated and identified the proteins that aggregate and our bioinformatic analyses indicates that increased aggregation of aggregation-prone proteins is a general occurrence in mRNA surveillance mutants, rather than being attributable to specific pathways. The proteins that aggregate in mRNA surveillance mutants tend to be more highly expressed, more abundant and more stable proteins compared with the wider proteome. There is also a strong correlation with the proteins that aggregate in response to nascent protein misfolding and an enrichment for proteins that are substrates of ribosome-associated Hsp70 chaperones, consistent with susceptibility for aggregation primarily occurring during translation/folding. We also identified a significant overlap between the aggregated proteins in mRNA surveillance mutants and ageing yeast cells suggesting that translation-dependent protein aggregation may be a feature of the loss of proteostasis that occurs in aged cell populations.

Scikit-ribo Enables Accurate Estimation and Robust Modeling of Translation Dynamics at Codon Resolution

Ribosome profiling (Ribo-seq) is a powerful technique for measuring protein translation; however, sampling errors and biological biases are prevalent and poorly understood. Addressing these issues, we present Scikit-ribo (https://github.com/schatzlab/scikit-ribo), an open-source analysis package for accurate genome-wide A-site prediction and translation efficiency (TE) estimation from Ribo-seq and RNA sequencing data. Scikit-ribo accurately identifies A-site locations and reproduces codon elongation rates using several digestion protocols (r = 0.99). Next, we show that the commonly used reads per kilobase of transcript per million mapped reads-derived TE estimation is prone to biases, especially for low-abundance genes. Scikit-ribo introduces a codon-level generalized linear model with ridge penalty that correctly estimates TE, while accommodating variable codon elongation rates and mRNA secondary structure. This corrects the TE errors for over 2,000 genes in S. cerevisiae, which we validate using mass spectrometry of protein abundances (r = 0.81), and allows us to determine the Kozak-like sequence directly from Ribo-seq. We conclude with an analysis of coverage requirements needed for robust codon-level analysis and quantify the artifacts that can occur from cycloheximide treatment.

Simplification of Markov chains with infinite state space and the mathematical theory of random gene expression bursts

Here we develop an effective approach to simplify two-time-scale Markov chains with infinite state spaces by removal of states with fast leaving rates, which improves the simplification method of finite Markov chains. We introduce the concept of fast transition paths and show that the effective transitions of the reduced chain can be represented as the superposition of the direct transitions and the indirect transitions via all the fast transition paths. Furthermore, we apply our simplification approach to the standard Markov model of single-cell stochastic gene expression and provide a mathematical theory of random gene expression bursts. We give the precise mathematical conditions for the bursting kinetics of both mRNAs and proteins. It turns out that random bursts exactly correspond to the fast transition paths of the Markov model. This helps us gain a better understanding of the physics behind the bursting kinetics as an emergent behavior from the fundamental multiscale biochemical reaction kinetics of stochastic gene expression.

Regulation of Mitochondrial Dynamics by Proteolytic Processing and Protein Turnover

The mitochondrial network is a dynamic organization within eukaryotic cells that participates in a variety of essential cellular processes, such as adenosine triphosphate (ATP) synthesis, central metabolism, apoptosis and inflammation. The mitochondrial network is balanced between rates of fusion and fission that respond to pathophysiologic signals to coordinate appropriate mitochondrial processes. Mitochondrial fusion and fission are regulated by proteins that either reside in or translocate to the inner or outer mitochondrial membranes or are soluble in the inter-membrane space. Mitochondrial fission and fusion are performed by guanosine triphosphatases (GTPases) on the outer and inner mitochondrial membranes with the assistance of other mitochondrial proteins. Due to the essential nature of mitochondrial function for cellular homeostasis, regulation of mitochondrial dynamics is under strict control. Some of the mechanisms used to regulate the function of these proteins are post-translational proteolysis and/or turnover, and this review will discuss these mechanisms required for correct mitochondrial network organization.