Yeast Proteome Research Articles

The Cross-and-Capture system: A versatile tool in yeast proteomics

High-throughput technologies such as affinity purification and yeast two-hybrid (Y2H) screening have been applied to explore protein–protein interactions (PPIs) in the model organism Saccharomyces cerevisiae. The “Cross-and-Capture” system is an alternative approach for an assessment of PPIs using two arrayed collections of differentially tagged yeast strains. In its current implementation, Cross-and-Capture encompasses ∼500 endogenously tagged yeast proteins, predominantly with roles in DNA metabolism and maintenance. The tagged arrays can also serve other purposes in yeast proteomics, such as monitoring of protein expression and the detection of posttranslational protein modifications. In this article, I summarize the development of this tool and describe its application to detect protein complexes and to screen for novel PPIs.

Predicting Protein Function by Multi-Label Correlated Semi-Supervised Learning

Assigning biological functions to uncharacterized proteins is a fundamental problem in the postgenomic era. The increasing availability of large amounts of data on protein-protein interactions (PPIs) has led to the emergence of a considerable number of computational methods for determining protein function in the context of a network. These algorithms, however, treat each functional class in isolation and thereby often suffer from the difficulty of the scarcity of labeled data. In reality, different functional classes are naturally dependent on one another. We propose a new algorithm, Multi-label Correlated Semi-supervised Learning (MCSL), to incorporate the intrinsic correlations among functional classes into protein function prediction by leveraging the relationships provided by the PPI network and the functional class network. The guiding intuition is that the classification function should be sufficiently smooth on subgraphs where the respective topologies of these two networks are a good match. We encode this intuition as regularized learning with intraclass and interclass consistency, which can be understood as an extension of the graph-based learning with local and global consistency (LGC) method. Cross validation on the yeast proteome illustrates that MCSL consistently outperforms several state-of-the-art methods. Most notably, it effectively overcomes the problem associated with scarcity of label data. The supplementary files are freely available at http://sites.google.com/site/csaijiang/MCSL.

The temporal analysis of yeast exponential phase using shotgun proteomics as a fermentation monitoring technique

System biology and bioprocess technology can be better understood using shotgun proteomics as a monitoring system during the fermentation. We demonstrated a shotgun proteomic method to monitor the temporal yeast proteome in early, middle and late exponential phases. Our study identified a total of 1389 proteins combining all 2D-LC-MS/MS runs. The temporal Saccharomyces cerevisiae proteome was enriched with proteolysis, radical detoxification, translation, one-carbon metabolism, glycolysis and TCA cycle. Heat shock proteins and proteins associated with oxidative stress response were found throughout the exponential phase. The most abundant proteins observed were translation elongation factors, ribosomal proteins, chaperones and glycolytic enzymes. The high abundance of the H-protein of the glycine decarboxylase complex (Gcv3p) indicated the availability of glycine in the environment. We observed differentially expressed proteins and the induced proteins at mid-exponential phase were involved in ribosome biogenesis, mitochondria DNA binding/replication and transcriptional activator. Induction of tryptophan synthase (Trp5p) indicated the abundance of tryptophan during the fermentation. As fermentation progressed toward late exponential phase, a decrease in cell proliferation was implied from the repression of ribosomal proteins, transcription coactivators, methionine aminopeptidase and translation-associated proteins.

Two strings to the systems biology bow: co-extracting the metabolome and proteome of yeast

Experimental samples are valuable and can represent a significant investment in time and resources. It is highly desirable at times to obtain as much information as possible from a single sample. This is especially relevant for systems biology approaches in which several ‘omics platforms are studied simultaneously. Unfortunately, each platform has a particular extraction methodology which increases sample number and sample volume requirements when multiple ‘omics are analyzed. We evaluated the integration of a yeast extraction method; specifically we explored whether fractions from a single metabolite extraction could be apportioned to multiple downstream ‘omics analytical platforms. In addition, we examined how variations to a chloroform/methanol yeast metabolite extraction regime influence metabolite recoveries. We show that protein suitable for proteomic analysis can be recovered from a metabolite extraction and that recovery of lipids, while reproducible, are not wholly quantitative. Higher quenching solution temperatures (−30 °C) can be used without significant leakage of intracellular metabolites when lower fermentation temperatures (20 °C) are employed. However, extended residence time in quenching solution, in combination with vigorous washing of quenched cell pellets, leads to extensive leakage of intracellular metabolites. Finally, there is minimal difference in metabolite amounts obtained when metabolite extractions are performed at 4 °C compared to extractions at −20 °C. The evaluated extraction method delivers material suitable for metabolomic and proteomic analyses from the same sample preparation.

Optimized Fast and Sensitive Acquisition Methods for Shotgun Proteomics on a Quadrupole Orbitrap Mass Spectrometer

Advances in proteomics are continually driven by the introduction of new mass spectrometric instrumentation with improved performances. The recently introduced quadrupole Orbitrap (Q Exactive) tandem mass spectrometer allows fast acquisition of high-resolution higher-energy collisional dissociation (HCD) tandem mass spectra due to the parallel mode of operation, where the generation, filling, and storage of fragment ions can be performed while simultaneously measuring another ion packet in the Orbitrap mass analyzer. In this study, data-dependent acquisition methods for "fast" or "sensitive" scanning were optimized and assessed by comparing stable isotope labeled yeast proteome coverage. We discovered that speed was the most important parameter for sample loads above 125 ng, where a 95 ms HCD scanning method allowed for identification and quantification of more than 2000 yeast proteins from 1 h of analysis time. At sample loads below 125 ng, a 156 ms HCD acquisition method improved the sensitivity, mass accuracy, and quality of data and enabled us to identify 30% more proteins and peptides than the faster scanning method. A similar effect was observed when the LC gradient was extended to 2 or 3 h for the analysis of complex mammalian whole cell lysates. Using a 3 h LC gradient, the sensitive method enabled identification of more than 4000 proteins from 1 μg of tryptic HeLa digest, which was almost 200 more identifications compared to the faster scanning method. Our results demonstrate that peptide identification on a quadrupole Orbitrap is dependent on sample amounts, acquisition speed, and data quality, which emphasizes the need for acquisition methods tailored for different sample loads and analytical preferences.

Translational Control of Cell Division by Elongator

Elongator is required for the synthesis of the mcm(5)s(2) modification found on tRNAs recognizing AA-ending codons. In order to obtain a global picture of the role of Elongator in translation, we used reverse protein arrays to screen the fission yeast proteome for translation defects. Unexpectedly, this revealed that Elongator inactivation mainly affected three specific functional groups including proteins implicated in cell division. The absence of Elongator results in a delay in mitosis onset and cytokinesis defects. We demonstrate that the kinase Cdr2, which is a central regulator of mitosis and cytokinesis, is under translational control by Elongator due to the Lysine codon usage bias of the cdr2 coding sequence. These findings uncover a mechanism by which the codon usage, coupled to tRNA modifications, fundamentally contributes to gene expression and cellular functions.

Characterization of domain-peptide interaction interface: prediction of SH3 domain-mediated protein-protein interaction network in yeast by generic structure-based models.

Determination of the binding specificity of SH3 domain, a peptide recognition module (PRM), is important to understand their biological functions and reconstruct the SH3-mediated protein-protein interaction network. In the present study, the SH3-peptide interactions for both class I and II SH3 domains were characterized by the intermolecular residue-residue interaction network. We developed generic MIEC-SVM models to infer SH3 domain-peptide recognition specificity that achieved satisfactory prediction accuracy. By investigating the domain-peptide recognition mechanisms at the residue level, we found that the class-I and class-II binding peptides have different binding modes even though they occupy the same binding site of SH3. Furthermore, we predicted the potential binding partners of SH3 domains in the yeast proteome and constructed the SH3-mediated protein-protein interaction network. Comparison with the experimentally determined interactions confirmed the effectiveness of our approach. This study showed that our sophisticated computational approach not only provides a powerful platform to decipher protein recognition code at the molecular level but also allows identification of peptide-mediated protein interactions at a proteomic scale. We believe that such an approach is general to be applicable to other domain-peptide interactions.

A proteomics performance standard to support measurement quality in proteomics

The emergence of MS-based proteomic platforms as a prominent technology utilized in biochemical and biomedical research has increased the need for high-quality MS measurements. To address this need, National Institute of Standards and Technology (NIST) reference material (RM) 8323 yeast protein extract is introduced as a proteomics quality control material for benchmarking the preanalytical and analytical performance of proteomics-based experimental workflows. RM 8323 yeast protein extract is based upon the well-characterized eukaryote Saccharomyces cerevisiae and can be utilized in the design and optimization of proteomics-based methodologies from sample preparation to data analysis. To demonstrate its utility as a proteomics quality control material, we coupled LC-MS/MS measurements of RM 8323 with the NIST MS Quality Control (MSQC) performance metrics to quantitatively assess the LC-MS/MS instrumentation parameters that influence measurement accuracy, repeatability, and reproducibility. Due to the complexity of the yeast proteome, we also demonstrate how NIST RM 8323, along with the NIST MSQC performance metrics, can be used in the evaluation and optimization of proteomics-based sample preparation methods.

Mapping the Hsp90 Genetic Interaction Network in Candida albicans Reveals Environmental Contingency and Rewired Circuitry

The molecular chaperone Hsp90 regulates the folding of diverse signal transducers in all eukaryotes, profoundly affecting cellular circuitry. In fungi, Hsp90 influences development, drug resistance, and evolution. Hsp90 interacts with ∼10% of the proteome in the model yeast Saccharomyces cerevisiae, while only two interactions have been identified in Candida albicans, the leading fungal pathogen of humans. Utilizing a chemical genomic approach, we mapped the C. albicans Hsp90 interaction network under diverse stress conditions. The chaperone network is environmentally contingent, and most of the 226 genetic interactors are important for growth only under specific conditions, suggesting that they operate downstream of Hsp90, as with the MAPK Hog1. Few interactors are important for growth in many environments, and these are poised to operate upstream of Hsp90, as with the protein kinase CK2 and the transcription factor Ahr1. We establish environmental contingency in the first chaperone network of a fungal pathogen, novel effectors upstream and downstream of Hsp90, and network rewiring over evolutionary time.

Perfluorooctanoic acid and ammonium perfluorooctanoate: volatile surfactants for proteome analysis?

Fluorinated surfactants are being explored as mass spectrometry (MS)-friendly alternatives to sodium dodecyl sulfate (SDS) for proteome analysis. Previous work demonstrates perfluorooctanoic acid (PFOA) to be compatible with electrospray ionization (ESI)-MS. The high volatility of PFOA provides an intrinsic approach to potentially eliminate the surfactant during ESI, or alternatively through solvent evaporation prior to MS. The ammonium salt of PFOA, ammonium perfluorooctanoate (APFO), is likely favored for proteome experiments; the MS and liquid chromatography (LC)/MS tolerance of APFO has not been established for proteome applications. Standard proteins and peptides, as well as a yeast proteome mixture, were individually spiked with surfactants (APFO, PFOA, SDS), and subjected to direct infusion ESI-MS, LC/MS/MS and LC/UV. The level of fluorinated surfactant remaining after solvent evaporation under varying conditions (time, pH, salt and protein content) was quantified and compared to the threshold tolerance level of the surfactant in an MS experiment (determined herein). Whereas PFOA is found ineffective at assisting protein solubilization, APFO is as effective as SDS for resolubilization of acetone-precipitated yeast proteins (~100% recovery). Unfortunately, the LC and MS threshold tolerance of APFO is only minimally greater than SDS (~2-fold higher concentration to cause 50% suppression). Nonetheless, the benefits of APFO in a proteome experiment are realized following a one-step evaporation protocol for removal of the surfactant in acidified solvent. APFO is considered a favoured alternative to SDS for proteome solubilization. Strictly speaking, APFO is not an 'MS-friendly' surfactant for proteome characterization; the detergent not only suppresses ESI signals at high concentration, but also perturbs reversed phase separation. However, the simplicity of APFO removal ahead of LC/MS justifies its use over the conventional SDS.

Proteomics for biomedicine: a half‐completed journey

Proteomics for biomedicine: a half‐completed journey

Mapping Yeast N-Glycosites with Isotopically Recoded Glycans

Asparagine-linked glycosylation is a common post-translational modification of proteins; in addition to participating in key macromolecular interactions, N-glycans contribute to protein folding, trafficking, and stability. Despite their importance, few N-glycosites have been experimentally mapped in the Saccharomyces cerevisiae proteome. Factors including glycan heterogeneity, low abundance, and low occupancy can complicate site mapping. Here, we report a novel mass spectrometry-based strategy for detection of N-glycosites in the yeast proteome. Our method imparts N-glycopeptide mass envelopes with a pattern that is computationally distinguishable from background ions. Isotopic recoding is achieved via metabolic incorporation of a defined mixture of N-acetylglucosamine isotopologs into N-glycans. Peptides bearing the recoded envelopes are specifically targeted for fragmentation, facilitating high confidence site mapping. This strategy requires no chemical modification of the N-glycans or stringent sample enrichment. Further, enzymatically simplified N-glycans are preserved on peptides. Using this approach, we identify 133 N-glycosites spanning 58 proteins, nearly doubling the number of experimentally observed N-glycosites in the yeast proteome.

Editorial on Special Topic: Sirtuins in Metabolism, Aging, and Disease

Editorial on Special Topic: Sirtuins in Metabolism, Aging, and Disease

Evaluation of High-Content Screening Fluorescence Correlation Spectroscopic (HCS-FCS) Data

High-content screening fluorescence correlation spectroscopy (HCS-FCS) determines diffusion properties, local concentrations and molecular interactions of biologically relevant proteins in thousands of individual S. cerevisiae cells. We automated one color auto-correlation fluorescence spectroscopy to investigate the properties of the yeast proteome. We also used two-color cross-correlation for interaction screens.For the proteome wide one-color yeast screen, we investigated more than 4000 of the approximately 6000 proteins known in S. cerevisiae. This resulted in over 200,500 measurements on more than 50,000 individual cells. This amount of data required automated tools for data quality control and analysis. Our pipeline started with the evaluation of transmitted light images of the measured cells. We extracted features from these images and trained a support vector machine (SVM) to classify them into healthy yeast cells and samples we wanted to exclude from further analysis. A similar approach enabled us to classify raw fluctuation data taken from the remaining cells and the auto-correlation curves we derived from them. As training sets, we used measured and simulated data.To analyze the correlation curves obtained from the fluctuation data, we fitted different diffusion models. We used mixed-effects models to extract averaged fit parameters for the same protein measured in multiple cells. To select the most appropriate diffusion model we used Akaike's ‘An Information Criterion’ (AIC).This approach not only allows the analysis of large data-sets as they occur in our HCS-FCS experiments and camera based FCS described in literature, but has the additional advantage of reducing the human bias.

Nuclear Envelope Phosphatase 1-Regulatory Subunit 1 (Formerly TMEM188) Is the Metazoan Spo7p Ortholog and Functions in the Lipin Activation Pathway

Lipin-1 catalyzes the formation of diacylglycerol from phosphatidic acid. Lipin-1 mutations cause lipodystrophy in mice and acute myopathy in humans. It is heavily phosphorylated, and the yeast ortholog Pah1p becomes membrane-associated and active upon dephosphorylation by the Nem1p-Spo7p membrane complex. A mammalian ortholog of Nem1p is the C-terminal domain nuclear envelope phosphatase 1 (CTDNEP1, formerly "dullard"), but its Spo7p-like partner is unknown, and the need for its existence is debated. Here, we identify the metazoan ortholog of Spo7p, TMEM188, renamed nuclear envelope phosphatase 1-regulatory subunit 1 (NEP1-R1). CTDNEP1 and NEP1-R1 together complement a nem1Δspo7Δ strain to block endoplasmic reticulum proliferation and restore triacylglycerol levels and lipid droplet number. The two human orthologs are in a complex in cells, and the amount of CTDNEP1 is increased in the presence of NEP1-R1. In the Caenorhabditis elegans embryo, expression of nematode CTDNEP1 and NEP1-R1, as well as lipin-1, is required for normal nuclear membrane breakdown after zygote formation. The expression pattern of NEP1-R1 and CTDNEP1 in human and mouse tissues closely mirrors that of lipin-1. CTDNEP1 can dephosphorylate lipins-1a, -1b, and -2 in human cells only in the presence of NEP1-R1. The nuclear fraction of lipin-1b is increased when CTDNEP1 and NEP1-R1 are co-expressed. Therefore, NEP1-R1 is functionally conserved from yeast to humans and functions in the lipin activation pathway.

Sirtuins as Regulators of the Yeast Metabolic Network

There is growing evidence that the metabolic network is an integral regulator of cellular physiology. Dynamic changes in metabolite concentrations, metabolic flux, or network topology act as reporters of biological or environmental signals, and are required for the cell to trigger an appropriate biological reaction. Changes in the metabolic network are recognized by specific sensory macromolecules and translated into a transcriptional or translational response. The protein family of sirtuins, discovered more than 30 years ago as regulators of silent chromatin, seems to fulfill the role of a metabolic sensor during aging and conditions of caloric restriction. The archetypal sirtuin, yeast silent information regulator2 (SIR2), is an NAD+ dependent protein deacetylase that interacts with metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and alcohol dehydrogenase, as well as enzymes involved in NAD(H) synthesis, that provide or deprive NAD+ in its close proximity. This influences sirtuin activity, and facilitates a dynamic response of the metabolic network to changes in metabolism with effects on physiology and aging. The molecular network downstream Sir2, however, is complex. In just two orders, Sir2’s metabolism related interactions span half of the yeast proteome, and are connected with virtually every physiological process. Thus, although it is fundamental to analyze single molecular mechanisms, it is at the same time crucial to consider this genome-scale complexity when correlating single molecular events with complex phenotypes such as aging, cell growth, or stress resistance.

Robust Analysis of the Yeast Proteome under 50 kDa by Molecular-Mass-Based Fractionation and Top-Down Mass Spectrometry

As the process of top-down mass spectrometry continues to mature, we benchmark the next installment of an improving methodology that incorporates a tube-gel electrophoresis (TGE) device to separate intact proteins by molecular mass. Top-down proteomics is accomplished in a robust fashion to yield the identification of hundreds of unique proteins, many of which correspond to multiple protein forms. The TGE platform separates 0-50 kDa proteins extracted from the yeast proteome into 12 fractions prior to automated nanocapillary LC-MS/MS in technical triplicate. The process may be completed in less than 72 h. From this study, 530 unique proteins and 1103 distinct protein species were identified and characterized, thus representing the highest coverage to date of the Saccharomyces cerevisiae proteome using top-down proteomics. The work signifies a significant step in the maturation of proteomics based on direct measurement and fragmentation of intact proteins.

Using the scan-x Web site to predict protein post-translational modifications.

The recent plethora of proteomic mass spectrometry data is providing evidence that almost every protein in the cell undergoes some form of post-translational modification. We describe a protocol to use the scan-x Web site to view predicted acetylation sites in the human proteome and predicted phosphorylation sites in the human, mouse, fly, and yeast proteomes with high specificity. This tool is accessible from virtually any computer with a Web browser. The only requirement is a means of searching for a protein of interest in one of the represented organisms.

Proteome Turnover in the Green Alga Ostreococcus tauri by Time Course 15N Metabolic Labeling Mass Spectrometry

Protein synthesis and degradation determine the cellular levels of proteins, and their control hence enables organisms to respond to environmental change. Experimentally, these are little known proteome parameters; however, recently, SILAC-based mass spectrometry studies have begun to quantify turnover in the proteomes of cell lines, yeast, and animals. Here, we present a proteome-scale method to quantify turnover and calculate synthesis and degradation rate constants of individual proteins in autotrophic organisms such as algae and plants. The workflow is based on the automated analysis of partial stable isotope incorporation with (15)N. We applied it in a study of the unicellular pico-alga Ostreococcus tauri and observed high relative turnover in chloroplast-encoded ATPases (0.42-0.58% h(-1)), core photosystem II proteins (0.34-0.51% h(-1)), and RbcL (0.47% h(-1)), while nuclear-encoded RbcS2 is more stable (0.23% h(-1)). Mitochondrial targeted ATPases (0.14-0.16% h(-1)), photosystem antennae (0.09-0.14% h(-1)), and histones (0.07-0.1% h(-1)) were comparatively stable. The calculation of degradation and synthesis rate constants k(deg) and k(syn) confirms RbcL as the bulk contributor to overall protein turnover. This study performed over 144 h of incorporation reveals dynamics of protein complex subunits as well as isoforms targeted to different organelles.

The effect of selenium enrichment on baker's yeast proteome.

The use of regular yeast (RY) and selenium-enriched yeast (SEY) as dietary supplement is of interest because the Nutritional Prevention of Cancer (NPC) trial revealed that SEY but not RY decreased the incidence of prostate cancer (PC). Using two-dimensional difference in gel electrophoresis (2D-DIGE)-tandem mass spectrometry (MS/MS) approach, we performed proteomic analysis of RY and SEY to identify proteins that are differentially expressed as a result of selenium enrichment. 2D-DIGE revealed 96 candidate protein spots that were differentially expressed (p≤0.05) between SEY and RY. The 96 spots were selected, sequenced by LC/MS/MS and 37 proteins were unequivocally identified. The 37 identified proteins were verified with ProteinProphet software and mapped to existing Gene Ontology categories. Furthermore, the expression profile of 5 of the proteins with validated or putative roles in the carcinogenesis process, and for which antibodies against human forms of the proteins are available commercially was verified by western analysis. This study provides evidence for the first time that SEY contains higher levels of Pyruvate Kinase, HSP70, and Elongation factor 2 and lower levels of Eukaryotic Translation Initiation Factor 5A-2 and Triosephosphate Isomerase than those found in RY.