MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes

Genomic Instability Is Induced by Persistent Proliferation of Cells Undergoing Epithelial-to-Mesenchymal Transition

TGF-β secreted by tumor stroma induces epithelial-to-mesenchymal transition (EMT) in cancer cells, a reversible phenotype linked to cancer progression and drug resistance. However, exposure to stromal signals may also lead to heritable changes in cancer cells, which are poorly understood. We show that epithelial cells failing to undergo proliferation arrest during TGF-β-induced EMT sustain mitotic abnormalities due to failed cytokinesis, resulting in aneuploidy. This genomic instability is associated with the suppression of multiple nuclear envelope proteins implicated in mitotic regulation and is phenocopied by modulating the expression of LaminB1. While TGF-β-induced mitotic defects in proliferating cells are reversible upon its withdrawal, the acquired genomic abnormalities persist, leading to increased tumorigenic phenotypes. In metastatic breast cancer patients, increased mesenchymal marker expression within single circulating tumor cells is correlated with genomic instability. These observations identify a mechanism whereby microenvironment-derived signals trigger heritable genetic changes within cancer cells, contributing to tumor evolution.

Discovery of Nicotinamide Adenine Dinucleotide Binding Proteins in the Escherichia coli Proteome Using a Combined Energetic- and Structural-Bioinformatics-Based Approach

Protein-ligand interaction plays a critical role in regulating the biochemical functions of proteins. Discovering protein targets for ligands is vital to new drug development. Here, we present a strategy that combines experimental and computational approaches to identify ligand-binding proteins in a proteomic scale. For the experimental part, we coupled pulse proteolysis with filter-assisted sample preparation (FASP) and quantitative mass spectrometry. Under denaturing conditions, ligand binding affected protein stability, which resulted in altered protein abundance after pulse proteolysis. For the computational part, we used the software Patch-Surfer2.0. We applied the integrated approach to identify nicotinamide adenine dinucleotide (NAD)-binding proteins in the Escherichia coli proteome, which has over 4200 proteins. Pulse proteolysis and Patch-Surfer2.0 identified 78 and 36 potential NAD-binding proteins, respectively, including 12 proteins that were consistently detected by the two approaches. Interestingly, the 12 proteins included 8 that are not previously known as NAD binders. Further validation of these eight proteins showed that their binding affinities to NAD computed by AutoDock Vina are higher than their cognate ligands and also that their protein ratios in the pulse proteolysis are consistent with known NAD-binding proteins. These results strongly suggest that these eight proteins are indeed newly identified NAD binders.

The genetic basis and fitness consequences of sperm midpiece size in deer mice

An extensive array of reproductive traits varies among species, yet the genetic mechanisms that enable divergence, often over short evolutionary timescales, remain elusive. Here we examine two sister-species of Peromyscus mice with divergent mating systems. We find that the promiscuous species produces sperm with longer midpiece than the monogamous species, and midpiece size correlates positively with competitive ability and swimming performance. Using forward genetics, we identify a gene associated with midpiece length: Prkar1a, which encodes the R1α regulatory subunit of PKA. R1α localizes to midpiece in Peromyscus and is differentially expressed in mature sperm of the two species yet is similarly abundant in the testis. We also show that genetic variation at this locus accurately predicts male reproductive success. Our findings suggest that rapid evolution of reproductive traits can occur through cell type-specific changes to ubiquitously expressed genes and have an important effect on fitness.

Across species there are large changes in sperm morphology, yet how and why is unclear. Here, the authors show in Peromyscus mice, that the sperm midpiece length influences swimming speed and male fertility, and is regulated by cell-type specific expression of a ubiquitously expressed gene, Prkar1a.

LKB1 loss links serine metabolism to DNA methylation and tumorigenesis

Intermediary metabolism generates substrates for chromatin modification, enabling the potential coupling of metabolic and epigenetic states. Here we identify a network linking metabolic and epigenetic alterations that is central to oncogenic transformation downstream of the liver kinase B1 (LKB1, also known as STK11) tumour suppressor, an integrator of nutrient availability, metabolism and growth. By developing genetically engineered mouse models and primary pancreatic epithelial cells, and employing transcriptional, proteomics, and metabolic analyses, we find that oncogenic cooperation between LKB1 loss and KRAS activation is fuelled by pronounced mTOR-dependent induction of the serine-glycine-one-carbon pathway coupled to S-adenosylmethionine generation. At the same time, DNA methyltransferases are upregulated, leading to elevation in DNA methylation with particular enrichment at retrotransposon elements associated with their transcriptional silencing. Correspondingly, LKB1 deficiency sensitizes cells and tumours to inhibition of serine biosynthesis and DNA methylation. Thus, we define a hypermetabolic state that incites changes in the epigenetic landscape to support tumorigenic growth of LKB1-mutant cells, while resulting in potential therapeutic vulnerabilities.

Quantitative proteomics and terminomics to elucidate the role of ubiquitination and proteolysis in adaptive immunity

Adaptive immunity is the specialized defence mechanism in vertebrates that evolved to eliminate pathogens. Specialized lymphocytes recognize specific protein epitopes through antigen receptors to mount potent immune responses, many of which are initiated by nuclear factor-kappa B activation and gene transcription. Most, if not all, pathways in adaptive immunity are further regulated by post-translational modification (PTM) of signalling proteins, e.g. phosphorylation, citrullination, ubiquitination and proteolytic processing. The importance of PTMs is reflected by genetic or acquired defects in these pathways that lead to a dysfunctional immune response. Here we discuss the state of the art in targeted proteomics and systems biology approaches to dissect the PTM landscape specifically regarding ubiquitination and proteolysis in B- and T-cell activation. Recent advances have occurred in methods for specific enrichment and targeted quantitation. Together with improved instrument sensitivity, these advances enable the accurate analysis of often rare PTM events that are opaque to conventional proteomics approaches, now rendering in-depth analysis and pathway dissection possible. We discuss published approaches, including as a case study the profiling of the N-terminome of lymphocytes of a rare patient with a genetic defect in the paracaspase protease MALT1, a key regulator protease in antigen-driven signalling, which was manifested by elevated linear ubiquitination.This article is part of the themed issue 'Quantitative mass spectrometry'.

The MaxQuant computational platform for mass spectrometry-based shotgun proteomics

MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis. Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms. Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques. This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda. This protocol update describes an adaptation of an existing protocol that substantially modifies the technique. Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs). The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail. Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs. The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores. The software is written in C# and is freely available at http://www.maxquant.org.

Time-resolved Analysis of Proteome Dynamics by Tandem Mass Tags and Stable Isotope Labeling in Cell Culture (TMT-SILAC) Hyperplexing

Recent advances in mass spectrometry have enabled system-wide analyses of protein turnover. By globally quantifying the kinetics of protein clearance and synthesis, these methodologies can provide important insights into the regulation of the proteome under varying cellular and environmental conditions. To facilitate such analyses, we have employed a methodology that combines metabolic isotopic labeling (Stable Isotope Labeling in Cell Culture - SILAC) with isobaric tagging (Tandem Mass Tags - TMT) for analysis of multiplexed samples. The fractional labeling of multiple time-points can be measured in a single mass spectrometry run, providing temporally resolved measurements of protein turnover kinetics. To demonstrate the feasibility of the approach, we simultaneously measured the kinetics of protein clearance and accumulation for more than 3000 proteins in dividing and quiescent human fibroblasts and verified the accuracy of the measurements by comparison to established non-multiplexed approaches. The results indicate that upon reaching quiescence, fibroblasts compensate for lack of cellular growth by globally downregulating protein synthesis and upregulating protein degradation. The described methodology significantly reduces the cost and complexity of temporally-resolved dynamic proteomic experiments and improves the precision of proteome-wide turnover data.

Improvement of Quantitative Measurements in Multiplex Proteomics Using High-Field Asymmetric Waveform Spectrometry

Quantitative proteomics using isobaric reagent tandem mass tags (TMT) or isobaric tags for relative and absolute quantitation (iTRAQ) provides a convenient approach to compare changes in protein abundance across multiple samples. However, the analysis of complex protein digests by isobaric labeling can be undermined by the relative large proportion of co-selected peptide ions that lead to distorted reporter ion ratios and affect the accuracy and precision of quantitative measurements. Here, we investigated the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) in proteomic experiments to reduce sample complexity and improve protein quantification using TMT isobaric labeling. LC-FAIMS-MS/MS analyses of human and yeast protein digests led to significant reductions in interfering ions, which increased the number of quantifiable peptides by up to 68% while significantly improving the accuracy of abundance measurements compared to that with conventional LC-MS/MS. The improvement in quantitative measurements using FAIMS is further demonstrated for the temporal profiling of protein abundance of HEK293 cells following heat shock treatment.

Developing a Multiplexed Quantitative Cross-Linking Mass Spectrometry Platform for Comparative Structural Analysis of Protein Complexes

Cross-linking mass spectrometry (XL-MS) represents a recently popularized hybrid methodology for defining protein-protein interactions (PPIs) and analyzing structures of large protein assemblies. In particular, XL-MS strategies have been demonstrated to be effective in elucidating molecular details of PPIs at the peptide resolution, providing a complementary set of structural data that can be utilized to refine existing complex structures or direct de novo modeling of unknown protein structures. To study structural and interaction dynamics of protein complexes, quantitative cross-linking mass spectrometry (QXL-MS) strategies based on isotope-labeled cross-linkers have been developed. Although successful, these approaches are mostly limited to pairwise comparisons. In order to establish a robust workflow enabling comparative analysis of multiple cross-linked samples simultaneously, we have developed a multiplexed QXL-MS strategy, namely, QMIX (Quantitation of Multiplexed, Isobaric-labeled cross (X)-linked peptides) by integrating MS-cleavable cross-linkers with isobaric labeling reagents. This study has established a new analytical platform for quantitative analysis of cross-linked peptides, which can be directly applied for multiplexed comparisons of the conformational dynamics of protein complexes and PPIs at the proteome scale in future studies.

HSP90 inhibition overcomes ibrutinib resistance in mantle cell lymphoma

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib induces responses in 70% of patients with relapsed and refractory mantle cell lymphoma (MCL). Intrinsic resistance can occur through activation of the nonclassical NF-κB pathway and acquired resistance may involve the BTK C481S mutation. Outcomes after ibrutinib failure are dismal, indicating an unmet medical need. We reasoned that newer heat shock protein 90 (HSP90) inhibitors could overcome ibrutinib resistance by targeting multiple oncogenic pathways in MCL. HSP90 inhibition induced the complete degradation of both BTK and IκB kinase α in MCL lines and CD40-dependent B cells, with downstream loss of MAPK and nonclassical NF-κB signaling. A proteome-wide analysis in MCL lines and an MCL patient-derived xenograft identified a restricted set of targets from HSP90 inhibition that were enriched for factors involved in B-cell receptor and JAK/STAT signaling, the nonclassical NF-κB pathway, cell-cycle regulation, and DNA repair. Finally, multiple HSP90 inhibitors potently killed MCL lines in vitro, and the clinical agent AUY922 was active in vivo against both patient-derived and cell-line xenografts. Together, these findings define the HSP90-dependent proteome in MCL. Considering the disappointing clinical activity of HSP90 inhibitors in other contexts, trials in patients with MCL will be essential for defining the efficacy of and mechanisms of resistance after ibrutinib failure.

High-Sensitivity Mass Spectrometry for Probing Gene Translation in Single Embryonic Cells in the Early Frog (Xenopus) Embryo

Direct measurement of protein expression with single-cell resolution promises to deepen the understanding of the basic molecular processes during normal and impaired development. High-resolution mass spectrometry provides detailed coverage of the proteomic composition of large numbers of cells. Here we discuss recent mass spectrometry developments based on single-cell capillary electrophoresis that extend discovery proteomics to sufficient sensitivity to enable the measurement of proteins in single cells. The single-cell mass spectrometry system is used to detect a large number of proteins in single embryonic cells in the 16-cell embryo of the South African clawed frog (Xenopus laevis) that give rise to distinct tissue types. Single-cell measurements of protein expression provide complementary information on gene transcription during early development of the vertebrate embryo, raising a potential to understand how differential gene expression coordinates normal cell heterogeneity during development.

A Triple Knockout (TKO) Proteomics Standard for Diagnosing Ion Interference in Isobaric Labeling Experiments

Isobaric labeling is a powerful strategy for quantitative mass spectrometry-based proteomic investigations. A complication of such analyses has been the co-isolation of multiple analytes of similar mass-to-charge resulting in the distortion of relative protein abundance measurements across samples. When properly implemented, synchronous precursor selection and triple-stage mass spectrometry (SPS-MS3) can reduce the occurrence of this phenomenon, referred to as ion interference. However, no diagnostic tool is available currently to rapidly and accurately assess ion interference. To address this need, we developed a multiplexed tandem mass tag (TMT)-based standard, termed the triple knockout (TKO). This standard is comprised of three yeast proteomes in triplicate, each from a strain deficient in a highly abundant protein (Met6, Pfk2, or Ura2). The relative abundance patterns of these proteins, which can be inferred from dozens of peptide measurements can demonstrate ion interference in peptide quantification. We expect no signal in channels where the protein is knocked out, permitting maximum sensitivity for measurements of ion interference against a null background. Here, we emphasize the need to investigate further ion interference-generated ratio distortion and promote the TKO standard as a tool to investigate such issues. Graphical Abstract ᅟ.

Role of the B Allele of Influenza A Virus Segment 8 in Setting Mammalian Host Range and Pathogenicity

Two alleles of segment 8 (NS) circulate in nonchiropteran influenza A viruses. The A allele is found in avian and mammalian viruses, but the B allele is viewed as being almost exclusively found in avian viruses. This might reflect the fact that one or both of its encoded proteins (NS1 and NEP) are maladapted for replication in mammalian hosts. To test this, a number of clade A and B avian virus-derived NS segments were introduced into human H1N1 and H3N2 viruses. In no case was the peak virus titer substantially reduced following infection of various mammalian cell types. Exemplar reassortant viruses also replicated to similar titers in mice, although mice infected with viruses with the avian virus-derived segment 8s had reduced weight loss compared to that achieved in mice infected with the A/Puerto Rico/8/1934 (H1N1) parent. In vitro, the viruses coped similarly with type I interferons. Temporal proteomics analysis of cellular responses to infection showed that the avian virus-derived NS segments provoked lower levels of expression of interferon-stimulated genes in cells than wild type-derived NS segments. Thus, neither the A nor the B allele of avian virus-derived NS segments necessarily attenuates virus replication in a mammalian host, although the alleles can attenuate disease. Phylogenetic analyses identified 32 independent incursions of an avian virus-derived A allele into mammals, whereas 6 introductions of a B allele were identified. However, A-allele isolates from birds outnumbered B-allele isolates, and the relative rates of Aves-to-Mammalia transmission were not significantly different. We conclude that while the introduction of an avian virus segment 8 into mammals is a relatively rare event, the dogma of the B allele being especially restricted is misleading, with implications in the assessment of the pandemic potential of avian influenza viruses.

IMPORTANCE

Influenza A virus (IAV) can adapt to poultry and mammalian species, inflicting a great socioeconomic burden on farming and health care sectors. Host adaptation likely involves multiple viral factors. Here, we investigated the role of IAV segment 8. Segment 8 has evolved into two distinct clades: the A and B alleles. The B-allele genes have previously been suggested to be restricted to avian virus species. We introduced a selection of avian virus A- and B-allele segment 8s into human H1N1 and H3N2 virus backgrounds and found that these reassortant viruses were fully competent in mammalian host systems. We also analyzed the currently available public data on the segment 8 gene distribution and found surprisingly little evidence for specific avian host restriction of the B-clade segment. We conclude that B-allele segment 8 genes are, in fact, capable of supporting infection in mammals and that they should be considered during the assessment of the pandemic risk of zoonotic influenza A viruses.

Impact of Microbiota on Resistance to Ocular Pseudomonas aeruginosa-Induced Keratitis

The existence of the ocular microbiota has been reported but functional analyses to evaluate its significance in regulating ocular immunity are currently lacking. We compared the relative contribution of eye and gut commensals in regulating the ocular susceptibility to Pseudomonas aeruginosa–induced keratitis. We find that in health, the presence of microbiota strengthened the ocular innate immune barrier by significantly increasing the concentrations of immune effectors in the tear film, including secretory IgA and complement proteins. Consistent with this view, Swiss Webster (SW) mice that are typically resistant to P. aeruginosa–induced keratitis become susceptible due to the lack of microbiota. This was exemplified by increased corneal bacterial burden and elevated pathology of the germ free (GF) mice when compared to the conventionally maintained SW mice. The protective immunity was found to be dependent on both eye and gut microbiota with the eye microbiota having a moderate, but significant impact on the resistance to infection. These events were IL-1ß–dependent as corneal IL-1ß levels were decreased in the infected GF and antibiotic-treated mice when compared to the SPF controls, and neutralization of IL-1ß increased the ocular bacterial burden in the SPF mice. Monocolonizing GF mice with Coagulase Negative Staphylococcus sp. isolated from the conjunctival swabs was sufficient to restore resistance to infection. Cumulatively, these data underline a previously unappreciated role for microbiota in regulating susceptibility to ocular keratitis. We predict that these results will have significant implications for contact lens wearers, where alterations in the ocular commensal communities may render the ocular surface vulnerable to infections.

Contact lens wear is associated with frequent Pseudomonas aeruginosa–induced keratitis, however the reasons for this association remain unclear. Recent genomics–based approaches revealed that contact lens wearers harbor altered ocular commensal communities when compared to non-lens wearers raising important questions, namely, does wearing of contact lenses increase the frequency of keratitis in patients due to contamination of the contact lenses with species derived from the skin or does ocular microbiota exert immune functions that are required for the maintenance of ocular health? We demonstrate a clear role for ocular microbiota in regulating protection against Pseudomonas aeruginosa–induced infections. At the ocular surface, commensal bacteria provide signals that regulate the magnitude of neutrophil recruitment during infection. These events may be driven by a frequent gram-positive commensal–Coagulase Negative Staphylococcus (CNS) sp. In addition to the impact of ocular microbiota, there is an important contribution of gut microbiota that stimulate neutrophil development in the bone marrow, thereby regulating the pool of mature neutrophils and their activation state. Cumulatively, these data show for the first time a role for microbiota in regulating the susceptibility to P. aeruginosa–keratitis.

Highly Multiplexed Quantitative Mass Spectrometry Analysis of Ubiquitylomes

System-wide quantitative analysis of ubiquitylomes has proven to be a valuable tool for elucidating targets and mechanisms of the ubiquitin-driven signaling systems, as well as gaining insights into neurodegenerative diseases and cancer. Current mass spectrometry methods for ubiquitylome detection require large amounts of starting material and rely on stochastic data collection to increase replicate analyses. We describe a method compatible with cell line and tissue samples for large-scale quantification of 5,000-9,000 ubiquitylation forms across ten samples simultaneously. Using this method, we reveal site-specific ubiquitylation in mammalian brain and liver tissues, as well as in cancer cells undergoing proteasome inhibition. To demonstrate the power of the approach for signal-dependent ubiquitylation, we examined protein and ubiquitylation dynamics for mitochondria undergoing PARKIN- and PINK1-dependent mitophagy. This analysis revealed the largest collection of PARKIN- and PINK1-dependent ubiquitylation targets to date in a single experiment, and it also revealed a subset of proteins recruited to the mitochondria during mitophagy.

Multiple Time-of-Flight/Time-of-Flight Events in a Single Laser Shot for Improved Matrix-Assisted Laser Desorption/Ionization Tandem Mass Spectrometry Quantification

Quantitative matrix-assisted laser desorption/ionization time-of-flight (MALDI TOF) approaches have historically suffered from poor accuracy and precision mainly due to the nonuniform distribution of matrix and analyte across the target surface, matrix interferences, and ionization suppression. Tandem mass spectrometry (MS/MS) can be used to ensure chemical specificity as well as improve signal-to-noise ratios by eliminating interferences from chemical noise, alleviating some concerns about dynamic range. However, conventional MALDI TOF/TOF modalities typically only scan for a single MS/MS event per laser shot, and multiplex assays require sequential analyses. We describe here new methodology that allows for multiple TOF/TOF fragmentation events to be performed in a single laser shot. This technology allows the reference of analyte intensity to that of the internal standard in each laser shot, even when the analyte and internal standard are quite disparate in m/z, thereby improving quantification while maintaining chemical specificity and duty cycle. In the quantitative analysis of the drug enalapril in pooled human plasma with ramipril as an internal standard, a greater than 4-fold improvement in relative standard deviation (<10%) was observed as well as improved coefficients of determination (R²) and accuracy (>85% quality controls). Using this approach we have also performed simultaneous quantitative analysis of three drugs (promethazine, enalapril, and verapamil) using deuterated analogues of these drugs as internal standards.

Comparing the Diagnostic Classification Accuracy of iTRAQ, Peak-Area, Spectral-Counting, and emPAI Methods for Relative Quantification in Expression Proteomics

Diagnostic classification accuracy is critical in expression proteomics to ensure that as many true differences as possible are identified with acceptable false-positive rates. We present a comparison of the diagnostic accuracy of iTRAQ with three label-free methods, peak area, spectral counting, and emPAI, for relative quantification using a spiked proteome standard. We provide the first validation of emPAI for intersample relative quantification and find clear differences among the four quantification approaches that could be considered when designing an experiment. Spectral counting was observed to perform surprisingly well in all regards. Peak area performed best for smaller fold differences and was shown to be capable of discerning a 1.1-fold difference with acceptable specificity and sensitivity. The performance of iTRAQ was dramatically worse than the label-free methods with low abundance proteins. Using the iTRAQ data set for validation, we also demonstrate a novel iTRAQ analysis regime that avoids the use of ratios in significance testing and outperforms a common commercial alternative.

HER2 expression identifies dynamic functional states within circulating breast cancer cells

Circulating tumor cells (CTCs) in women with advanced estrogen receptor-positive/HER2-negative breast cancer acquire a HER2-positive subpopulation following multiple courses of therapy^1,2. In contrast to HER2-amplified primary breast cancer, which is highly sensitive to HER2-targeted therapy, the clinical significance of acquired HER2 heterogeneity during the evolution of metastatic breast cancer is unknown. Here, we analyzed CTCs from 19 ER+/HER2− patients, 84% of whom had acquired CTCs expressing HER2. Cultured CTCs maintain discrete HER2+ and HER2− subpopulations: HER2+ CTCs are more proliferative but not addicted to HER2, consistent with activation of multiple signaling pathways. HER2− CTCs show activation of Notch and DNA damage pathways, exhibiting resistance to cytotoxic chemotherapy, but sensitivity to Notch inhibition. HER2+ and HER2− CTCs interconvert spontaneously, with cells of one phenotype producing daughters of the opposite within four cell doublings. While HER2+ and HER2− CTCs have comparable tumor initiating potential, differential proliferation favors the HER2+ state, while oxidative stress or cytotoxic chemotherapy enhances transition to the HER2− phenotype. Simultaneous treatment with paclitaxel and Notch inhibitors achieves sustained suppression of tumorigenesis in orthotopic CTC-derived tumor models. Together, these results point to distinct yet interconverting phenotypes within patient-derived CTCs, contributing to progression of breast cancer and acquisition of drug resistance.

Evaluation and Application of Dimethylated Amino Acids as Isobaric Tags for Quantitative Proteomics of the TGF-β/Smad3 Signaling Pathway

Isobaric labeling has become a widespread tool for quantitative proteomic studies. Here, we report the development and evaluation of several dimethylated amino acids as novel isobaric tags for quantitative proteomics. Four-plex dimethylated alanine (DiAla), valine (DiVal), and leucine (DiLeu) have been synthesized, sharing common features of peptide tagging and reporter ion production. DiAla and DiLeu are shown to achieve complete labeling. These two tags' impacts on peptide fragmentation and quantitation are further evaluated using HEK293 cell lysate. DiAla labeling generates more abundant backbone fragmentation whereas DiLeu labeling produces more intense reporter ions. Nonetheless, both tags enable accurate quantitative analysis of HEK293 cell proteomes. DiAla and DiLeu tags are then applied to study the TGF-β/Smad3 pathway with four differentially treated mouse vascular smooth muscle (MOVAS) cells. Our MS data reveal proteome-wide changes of AdSmad3 as compared to the GFP control, consistent with previous findings of causing smooth muscle cell (SMC) dedifferentiation.1 Additionally, the other two novel mutations on the hub protein Smad3, Y226A, and D408H, show compromised TGF-β/Smad3-dependent gene transcription and reversed phenotypic switch. These results are further corroborated with Western blotting and demonstrate that the novel DiAla and DiLeu isobaric tagging reagents provide useful tools for multiplex quantitative proteomics.

On the Statistical Significance of Compressed Ratios in Isobaric Labeling: A Cross-Platform Comparison

Isobaric labeling is gaining popularity in proteomics due to its multiplexing capacity. However, copeptide fragmentation introduces a bias that undermines its accuracy. Several strategies have been shown to partially and, in some cases, completely solve this issue. However, it is still not clear how ratio compression affects the ability to identify a protein's change of abundance as statistically significant. Here, by using the "two proteomes" approach (E. coli lysates with fixed 2.5 ratios in the presence or absence of human lysates acting as the background interference) and manipulating isolation width values, we were able to model isobaric data with different levels of accuracy and precision in three types of mass spectrometers: LTQ Orbitrap Velos, Impact, and Q Exactive. We determined the influence of these variables on the statistical significance of the distorted ratios and compared them to the ratios measured without impurities. Our results confirm previous findings1-4 regarding the importance of optimizing acquisition parameters in each instrument in order to minimize interference without compromising precision and identification. We also show that, under these experimental conditions, the inclusion of a second replicate increases statistical sensitivity 2-3-fold and counterbalances to a large extent the issue of ratio compression.

Label-free Quantification of Proteins in Single Embryonic Cells with Neural Fate in the Cleavage-Stage Frog (Xenopus laevis) Embryo using Capillary Electrophoresis Electrospray Ionization High-Resolution Mass Spectrometry (CE-ESI-HRMS)

Quantification of protein expression in single cells promises to advance a systems-level understanding of normal development. Using a bottom-up proteomic workflow and multiplexing quantification by tandem mass tags, we recently demonstrated relative quantification between single embryonic cells (blastomeres) in the frog (Xenopus laevis) embryo. In this study, we minimize derivatization steps to enhance analytical sensitivity and use label-free quantification (LFQ) for single Xenopus cells. The technology builds on a custom-designed capillary electrophoresis microflow-electrospray ionization high-resolution mass spectrometry platform and LFQ by MaxLFQ (MaxQuant). By judiciously tailoring performance to peptide separation, ionization, and data-dependent acquisition, we demonstrate an ∼75-amol (∼11 nm) lower limit of detection and quantification for proteins in complex cell digests. The platform enabled the identification of 438 nonredundant protein groups by measuring 16 ng of protein digest, or <0.2% of the total protein contained in a blastomere in the 16-cell embryo. LFQ intensity was validated as a quantitative proxy for protein abundance. Correlation analysis was performed to compare protein quantities between the embryo and n = 3 different single D11 blastomeres, which are fated to develop into the nervous system. A total of 335 nonredundant protein groups were quantified in union between the single D11 cells spanning a 4 log-order concentration range. LFQ and correlation analysis detected expected proteomic differences between the whole embryo and blastomeres, and also found translational differences between individual D11 cells. LFQ on single cells raises exciting possibilities to study gene expression in other cells and models to help better understand cell processes on a systems biology level.

Quantitative mass spectrometry-based multiplexing compares the abundance of 5000 S. cerevisiae proteins across 10 carbon sources

The budding yeast Saccharomyces cerevisiae is a model system for investigating biological processes. Cellular events are known to be dysregulated due to shifts in carbon sources. However, the comprehensive proteomic alterations thereof have not been fully investigated. Here we examined proteomic alterations in S. cerevisiae due to the adaptation of yeast from glucose to nine different carbon sources - maltose, trehalose, fructose, sucrose, glycerol, acetate, pyruvate, lactic acid, and oleate. Isobaric tag-based mass spectrometry techniques are at the forefront of global proteomic investigations. As such, we used a TMT10-plex strategy to study multiple growth conditions in a single experiment. The SPS-MS3 method on an Orbitrap Fusion Lumos mass spectrometer enabled the quantification of over 5000 yeast proteins across ten carbon sources at a 1% protein-level FDR. On average, the proteomes of yeast cultured in fructose and sucrose deviated the least from those cultured in glucose. As expected, gene ontology classification revealed the major alteration in protein abundances occurred in metabolic pathways and mitochondrial proteins. Our protocol lays the groundwork for further investigation of carbon source-induced protein alterations. Additionally, these data offer a hypothesis-generating resource for future studies aiming to investigate both characterized and uncharacterized genes.

BIOLOGICAL SIGNIFICANCE

We investigate the proteomic alterations in S. cerevisiae resulting from adaptation of yeast from glucose to nine different carbon sources - maltose, trehalose, fructose, sucrose, glycerol, acetate, pyruvate, lactic acid, and oleate. SPS-MS3 TMT10plex analysis is used for quantitative proteomic analysis. We showcase a technique that allows the quantification of over 5000 yeast proteins, the highest number to date in S. cerevisiae, across 10 growth conditions in a single experiment. As expected, gene ontology classification of proteins with the major alterations in abundances occurred in metabolic pathways and mitochondrial proteins, reflecting the degree of metabolic stress when cellular machinery shifts from growth on glucose to an alternative carbon source. Our protocol lays the groundwork for further investigation of carbon source-induced protein alterations. Improving depth of coverage - measuring abundance changes of over 5000 proteins - increases our understanding of difficult-to-study genes in the model system S. cerevisiae and by homology human cell biology. We submit this highly comprehensive dataset as a hypothesis generating resource for targeted studies on uncharacterized genes.

Proteomic Analysis of Human Brown Adipose Tissue Reveals Utilization of Coupled and Uncoupled Energy Expenditure Pathways

Human brown adipose tissue (BAT) has become an attractive target to combat the current epidemical spread of obesity and its associated co-morbidities. Currently, information on its functional role is primarily derived from rodent studies. Here, we present the first comparative proteotype analysis of primary human brown adipose tissue versus adjacent white adipose tissue, which reveals significant quantitative differences in protein abundances and in turn differential functional capabilities. The majority of the 318 proteins with increased abundance in BAT are associated with mitochondrial metabolism and confirm the increased oxidative capacity. In addition to uncoupling protein 1 (UCP1), the main functional effector for uncoupled respiration, we also detected the mitochondrial creatine kinases (CKMT1A/B, CKMT2), as effective modulators of ATP synthase coupled respiration, to be exclusively expressed in BAT. The abundant expression and utilization of both energy expenditure pathways in parallel highlights the complex functional involvement of BAT in human physiology.

Improved 6-Plex Tandem Mass Tags Quantification Throughput Using a Linear Ion Trap-High-Energy Collision Induced Dissociation MS(3) Scan

The use of tandem mass tags (TMT) as an isobaric labeling strategy is a powerful method for quantitative proteomics, yet its accuracy has traditionally suffered from interference. This interference can be largely overcome by selecting MS(2) fragment precursor ions for high-energy collision induced dissociation (HCD) MS(3) analysis in an Orbitrap scan. While this approach minimizes the interference effect, sensitivity suffers due to the high AGC targets and long acquisition times associated with MS(3) Orbitrap detection. We investigated whether acquiring the MS(3) scan in a linear ion trap with its lower AGC target would increase overall quantification levels with a minimal effect on precision and accuracy. Trypsin-digested proteins from Saccharomyces cerevisiae were tagged with 6-plex TMT reagents. The sample was subjected to replicate analyses using either the Orbitrap or the linear ion trap for the HCD MS(3) scan. HCD MS(3) detection in the linear ion trap vs Orbitrap increased protein identification by 66% with minor loss in precision and accuracy. Thus, the use of a linear ion trap-HCD MS(3) scan during a 6-plex TMT experiment can improve overall identification levels while maintaining the power of multiplexed quantitative analysis.

PTP1B controls non-mitochondrial oxygen consumption by regulating RNF213 to promote tumour survival during hypoxia

Tumours exist in a hypoxic microenvironment and must limit excessive oxygen consumption. Hypoxia-inducible factor (HIF) controls mitochondrial oxygen consumption, but how/if tumours regulate non-mitochondrial oxygen consumption (NMOC) is unknown. Protein-tyrosine phosphatase-1B (PTP1B) is required for Her2/Neu-driven breast cancer (BC) in mice, although the underlying mechanism and human relevance remain unclear. We found that PTP1B-deficient HER2(+) xenografts have increased hypoxia, necrosis and impaired growth. In vitro, PTP1B deficiency sensitizes HER2(+) BC lines to hypoxia by increasing NMOC by α-KG-dependent dioxygenases (α-KGDDs). The moyamoya disease gene product RNF213, an E3 ligase, is negatively regulated by PTP1B in HER2(+) BC cells. RNF213 knockdown reverses the effects of PTP1B deficiency on α-KGDDs, NMOC and hypoxia-induced death of HER2(+) BC cells, and partially restores tumorigenicity. We conclude that PTP1B acts via RNF213 to suppress α-KGDD activity and NMOC. This PTP1B/RNF213/α-KGDD pathway is critical for survival of HER2(+) BC, and possibly other malignancies, in the hypoxic tumour microenvironment.

Mitochondrial unfolded protein response controls matrix pre-RNA processing and translation

The mitochondrial matrix is unique in that it must integrate the folding and assembly of proteins derived from the nuclear and mitochondrial genomes. In Caenorhabditis elegans, the mitochondrial unfolded protein response (UPRmt) senses matrix protein misfolding and induces a program of nuclear gene expression, including mitochondrial chaperonins, to promote mitochondrial proteostasis. While misfolded mitochondrial-matrix-localized ornithine transcarbamylase induces chaperonin expression, our understanding of mammalian UPRmt is rudimentary, reflecting a lack of acute triggers for UPRmt activation. This limitation has prevented analysis of the cellular responses to matrix protein misfolding and the effects of UPRmt on mitochondrial translation to control protein folding loads. Here we combine pharmacological inhibitors of matrix-localized HSP90/TRAP1 (ref. 8) or LON protease, which promote chaperonin expression, with global transcriptional and proteomic analysis to reveal an extensive and acute response of human cells to UPRmt. This response encompasses widespread induction of nuclear genes, including matrix-localized proteins involved in folding, pre-RNA processing and translation. Functional studies revealed rapid but reversible translation inhibition in mitochondria occurring concurrently with defects in pre-RNA processing caused by transcriptional repression and LON-dependent turnover of the mitochondrial pre-RNA processing nuclease MRPP3 (ref. 10). This study reveals that acute mitochondrial protein folding stress activates both increased chaperone availability within the matrix and reduced matrix-localized protein synthesis through translational inhibition, and provides a framework for further dissection of mammalian UPRmt.

Defining the consequences of genetic variation on a proteome-wide scale

Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein-protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice.

Mass Spectrometry Applied to Bottom-Up Proteomics: Entering the High-Throughput Era for Hypothesis Testing

Proteins constitute a key class of molecular components that perform essential biochemical reactions in living cells. Whether the aim is to extensively characterize a given protein or to perform high-throughput qualitative and quantitative analysis of the proteome content of a sample, liquid chromatography coupled to tandem mass spectrometry has become the technology of choice. In this review, we summarize the current state of mass spectrometry applied to bottom-up proteomics, the approach that focuses on analyzing peptides obtained from proteolytic digestion of proteins. With the recent advances in instrumentation and methodology, we show that the field is moving away from providing qualitative identification of long lists of proteins to delivering highly consistent and accurate quantification values for large numbers of proteins across large numbers of samples. We believe that this shift will have a profound impact for the field of proteomics and life science research in general.

Inhibition of MNK pathways enhances cancer cell response to chemotherapy with temozolomide and targeted radionuclide therapy

Current standard-of-care treatment for malignant cancers includes radiotherapy and adjuvant chemotherapy. Here, we report increased MAP kinase-interacting kinase (MNK)-regulated phosphorylation of translation initiation factor 4E (eIF4E) in glioma cells upon temozolomide (TMZ) treatment and in medullary thyroid carcinoma (MTC) cells in response to targeted radionuclide therapy. Depletion of MNK activity by using two MNK inhibitors, CGP57380 or cercosporamide, as well as by MNK1-specific knockdown sensitized glioblastoma (GBM) cells and GBM-derived spheres to TMZ. Furthermore, CGP57380 treatment enhanced response of MTC cells to (177)Lu-labeled gastrin analogue. In order to understand how MNK signaling pathways support glioma survival we analyzed putative MNK substrates by quantitative phosphoproteomics in normal condition and in the presence of TMZ. We identified MNK inhibitor-sensitive phosphorylation sites on eIF4G1, mutations of which either influenced eIF4E phosphorylation or glioma cell response to TMZ, pointing to altered regulation of translation initiation as a resistance mechanism. Pharmacological inhibition of overexpressed MNK1 by CGP57380 reduced eIF4E phosphorylation and induced association of inactive MNK1 with eIF4G1. Taken together, our data show an activation of MNK-mediated survival mechanisms in response to either glioma chemotherapy or MTC targeted radiation and suggest that inhibition of MNK activity represents an attractive sensitizing strategy for cancer treatments.

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis.

Sub-cellular localisation of proteins is critical to their function in all cellular processes; proteins localising to their intended micro-environment, e.g organelles, vesicles or macro-molecular complexes, will meet the interaction partners and biochemical conditions suitable to pursue their molecular function. Therefore, sound data and methods to reliably and systematically study protein localisation, and hence their mis-localisation and the disruption of protein trafficking, that are relied upon by the cell biology community, are essential. Here we present a method to infer protein localisation relying on the optimal integration of experimental mass spectrometry-based data and auxiliary sources, such as GO annotation, outputs from third-party software, protein-protein interactions or immunocytochemistry data. We found that the application of transfer learning algorithms across these diverse data sources considerably improves on the quantity and reliability of sub-cellular protein assignment, compared to single data classifiers previously applied to infer sub-cellular localisation using experimental data only. We show how our method does not compromise biologically relevant experimental-specific signal after integration with heterogeneous freely available third-party resources. The integration of different data sources is an important challenge in the data intensive world of biology and we anticipate the transfer learning methods presented here will prove useful to many areas of biology, to unify data obtained from different but complimentary sources.

Uncovering a Dual Regulatory Role for Caspases During Endoplasmic Reticulum Stress-induced Cell Death

Many diseases are associated with endoplasmic reticulum (ER) stress, which results from an accumulation of misfolded proteins. This triggers an adaptive response called the "unfolded protein response" (UPR), and prolonged exposure to ER stress leads to cell death. Caspases are reported to play a critical role in ER stress-induced cell death but the underlying mechanisms by which they exert their effect continue to remain elusive. To understand the role caspases play during ER stress, a systems level approach integrating analysis of the transcriptome, proteome, and proteolytic substrate profile was employed. This quantitative analysis revealed transcriptional profiles for most human genes, provided information on protein abundance for 4476 proteins, and identified 445 caspase substrates. Based on these data sets many caspase substrates were shown to be downregulated at the protein level during ER stress suggesting caspase activity inhibits their cellular function. Additionally, RNA sequencing revealed a role for caspases in regulation of ER stress-induced transcriptional pathways and gene set enrichment analysis showed expression of multiple gene targets of essential transcription factors to be upregulated during ER stress upon inhibition of caspases. Furthermore, these transcription factors were degraded in a caspase-dependent manner during ER stress. These results indicate that caspases play a dual role in regulating the cellular response to ER stress through both post-translational and transcriptional regulatory mechanisms. Moreover, this study provides unique insight into progression of the unfolded protein response into cell death, which may help identify therapeutic strategies to treat ER stress-related diseases.

Mitochondrial ROS regulate thermogenic energy expenditure and sulfenylation of UCP1

Brown adipose tissue (BAT) can dissipate chemical energy as heat through thermogenic respiration, which requires uncoupling protein 1 (UCP1)^1,2. Thermogenesis from BAT and beige adipose can combat obesity and diabetes³, encouraging investigation of factors that control UCP1-dependent respiration in vivo. Herein we show that acutely activated BAT thermogenesis is defined by a substantial increase in mitochondrial reactive oxygen species (ROS) levels. Remarkably, this process supports in vivo BAT thermogenesis, as pharmacological depletion of mitochondrial ROS results in hypothermia upon cold exposure, and inhibits UCP1-dependent increases in whole body energy expenditure. We further establish that thermogenic ROS alter BAT cysteine thiol redox status to drive increased respiration, and Cys253 of UCP1 is a key target. UCP1 Cys253 is sulfenylated during thermogenesis, while mutation of this site desensitizes the purine nucleotide inhibited state of the carrier to adrenergic activation and uncoupling. These studies identify BAT mitochondrial ROS induction as a mechanism that drives UCP1-dependent thermogenesis and whole body energy expenditure, which opens the way to develop improved therapeutic strategies for combating metabolic disorders.

Open-gate mutants of the mammalian proteasome show enhanced ubiquitin-conjugate degradation

When in the closed form, the substrate translocation channel of the proteasome core particle (CP) is blocked by the convergent N termini of α-subunits. To probe the role of channel gating in mammalian proteasomes, we deleted the N-terminal tail of α3; the resulting α3ΔN proteasomes are intact but hyperactive in the hydrolysis of fluorogenic peptide substrates and the degradation of polyubiquitinated proteins. Cells expressing the hyperactive proteasomes show markedly elevated degradation of many established proteasome substrates and resistance to oxidative stress. Multiplexed quantitative proteomics revealed ∼200 proteins with reduced levels in the mutant cells. Potentially toxic proteins such as tau exhibit reduced accumulation and aggregate formation. These data demonstrate that the CP gate is a key negative regulator of proteasome function in mammals, and that opening the CP gate may be an effective strategy to increase proteasome activity and reduce levels of toxic proteins in cells.

The proteasome plays a key role in proteostasis by mediating the degradation of ubiquitinated substrates. Here the authors show that an open-gate mutant of the proteasome is hyperactive towards a subset of substrates and can effectively delay the accumulation of toxic protein aggregates.

A Biologist's Field Guide to Multiplexed Quantitative Proteomics

High-throughput genomic and proteomic studies have generated near-comprehensive catalogs of biological constituents within many model systems. Nevertheless, static catalogs are often insufficient to fully describe the dynamic processes that drive biology. Quantitative proteomic techniques address this need by providing insight into closely related biological states such as the stages of a therapeutic response or cellular differentiation. The maturation of quantitative proteomics in recent years has brought about a variety of technologies, each with their own strengths and weaknesses. It can be difficult for those unfamiliar with this evolving landscape to match the experiment at hand with the best tool for the job. Here, we outline quantitative methods for proteomic mass spectrometry and discuss their benefits and weaknesses from the perspective of the biologist aiming to generate meaningful data and address mechanistic questions.

Covalent Labeling Denaturation Mass Spectrometry for Sensitive Localized Higher Order Structure Comparisons

Protein higher order structure (HOS) describes the three-dimensional folding arrangement of a given protein and plays critical roles in structure/function relationships. As such, it is a key product quality attribute that is monitored during biopharmaceutical development. Covalent labeling of surface residues, combined with mass spectrometry analysis, has increasingly played an important role in characterizing localized protein HOS. Since the label can potentially induce conformation changes, protocols generally use a small amount of label to ensure that the integrity of the protein HOS is not disturbed. The present study, however, describes a method that purposely uses high amounts of isobaric label (levels that induce denaturation) to enhance the sensitivity and resolution for detecting localized structural differences between two or more biological products. The method proved to be highly discriminative, detecting differences in HOS affecting as little as 2.5-5% of the molecular population, levels at which circular dichroism and nuclear magnetic resonance spectroscopy fingerprinting, both gold standard HOS techniques, were unable to adequately differentiate. The methodology was shown to have comparable sensitivity to differential scanning calorimetry for detecting HOS differences. In addition, the workflow presented herein can also quantify other product attributes such as post-translational modifications and site-specific glycosylation, using a single liquid chromatography-tandem mass spectrometry (LC-MS/MS) run with automated data analysis. We applied this technique to characterize a large (>90 kDa), multiply glycosylated therapeutic protein under different heat stress conditions and aggregation states.

A draft map of the mouse pluripotent stem cell spatial proteome

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data.

Multiplexed Quantitative Proteomics for High-Throughput Comprehensive Proteome Comparisons of Human Cell Lines

The proteome is the functional entity of the cell, and perturbations of a cellular system almost always cause changes in the proteome. These changes are a molecular fingerprint, allowing characterization and a greater understanding of the effect of the perturbation on the cell as a whole. Monitoring these changes has therefore given great insight into cellular responses to stress and disease states, and analytical platforms to comprehensively analyze the proteome are thus extremely important tools in biological research. Mass spectrometry has evolved as the most relevant technology to characterize proteomes in a comprehensive way. However, due to a lack of throughput capacity of mass spectrometry-based proteomics, researchers frequently use measurement of mRNA levels to approximate proteome changes. Growing evidence of substantial differences between mRNA and protein levels as well as recent improvements in mass spectrometry-based proteomics are heralding an increased use of mass spectrometry for comprehensive proteome mapping. Here we describe the use of multiplexed quantitative proteomics using isobaric labeling with tandem mass tags (TMT) for the simultaneous quantitative analysis of five cancer cell proteomes in biological duplicates in one mass spectrometry experiment.

Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0

PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for the analysis of shotgun proteomic data. The contained modules allow for formatting of sequence databases, peptide spectrum matching, statistical filtering and data organization, extracting quantitative information from label-free and chemically labeled data, and analyzing statistics for differential proteomics. PatternLab also has modules to perform similarity-driven studies with de novo sequencing data, to evaluate time-course experiments and to highlight the biological significance of data with regard to the Gene Ontology database. The PatternLab for proteomics 4.0 package brings together all of these modules in a self-contained software environment, which allows for complete proteomic data analysis and the display of results in a variety of graphical formats. All updates to PatternLab, including new features, have been previously tested on millions of mass spectra. PatternLab is easy to install, and it is freely available from http://patternlabforproteomics.org.

Cold Temperature Induces the Reprogramming of Proteolytic Pathways in Yeast

Despite much evidence of the involvement of the proteasome-ubiquitin signaling system in temperature stress response, the dynamics of the ubiquitylome during cold response has not yet been studied. Here, we have compared quantitative ubiquitylomes from a strain deficient in proteasome substrate recruitment and a reference strain during cold response. We have observed that a large group of proteins showing increased ubiquitylation in the proteasome mutant at low temperature is comprised by reverses suppressor of Ty-phenotype 5 (Rsp5)-regulated plasma membrane proteins. Analysis of internalization and degradation of plasma membrane proteins at low temperature showed that the proteasome becomes determinant for this process, whereas, at 30 °C, the proteasome is dispensable. Moreover, our observations indicate that proteasomes have increased capacity to interact with lysine 63-polyubiquitylated proteins during low temperature in vivo. These unanticipated observations indicate that, during cold response, there is a proteolytic cellular reprogramming in which the proteasome acquires a role in the endocytic-vacuolar pathway.

Quantitation of protein post-translational modifications using isobaric tandem mass tags

Post-translational modifications (PTMs) of proteins are known to modulate many cellular processes and their qualitative and quantitative evaluation is fundamental for understanding the mechanisms of biological events. Over the past decade, improvements in sample preparation techniques and enrichment strategies, the development of quantitative labeling strategies, the launch of a new generation of mass spectrometers and the creation of bioinformatics tools for the interrogation of ever larger datasets has established MS-based quantitative proteomics as a powerful workflow for global proteomics, PTM analysis and the elucidation of key biological mechanisms. With the advantage of their multiplexing capacity and the flexibility of an ever-growing family of different peptide-reactive groups, isobaric tandem mass tags facilitate quantitative proteomics and PTM experiments and enable higher sample throughput. In this review, we focus on the technical concept and utility of the isobaric tandem mass tag labeling approach to PTM analysis, including phosphorylation, glycosylation and S-nitrosylation.

On the Relationship of Protein and mRNA Dynamics in Vertebrate Embryonic Development

A biochemical explanation of development from the fertilized egg to the adult requires an understanding of the proteins and RNAs expressed over time during embryogenesis. We present a comprehensive characterization of protein and mRNA dynamics across early development in Xenopus. Surprisingly, we find that most protein levels change little and duplicated genes are expressed similarly. While the correlation between protein and mRNA levels is poor, a mass action kinetics model parameterized using protein synthesis and degradation rates regresses protein dynamics to RNA dynamics, corrected for initial protein concentration. This study provides detailed data for absolute levels of ∼10,000 proteins and ∼28,000 transcripts via a convenient web portal, a rich resource for developmental biologists. It underscores the lasting impact of maternal dowry, finds surprisingly few cases where degradation alone drives a change in protein level, and highlights the importance of transcription in shaping the dynamics of the embryonic proteome.

Multiplexed, Proteome-Wide Protein Expression Profiling: Yeast Deubiquitylating Enzyme Knockout Strains

Characterizing a protein's function often requires a description of the cellular state in its absence. Multiplexing in mass spectrometry-based proteomics has now achieved the ability to globally measure protein expression levels in yeast from 10 cell states simultaneously. We applied this approach to quantify expression differences in wild type and nine deubiquitylating enzyme (DUB) knockout strains with the goal of creating "information networks" that might provide deeper, mechanistic insights into a protein's biological role. In total, more than 3700 proteins were quantified with high reproducibility across three biological replicates (30 samples in all). DUB mutants demonstrated different proteomics profiles, consistent with distinct roles for each family member. These included differences in total ubiquitin levels and specific chain linkages. Moreover, specific expression changes suggested novel functions for several DUB family members. For instance, the ubp3Δ mutant showed large expression changes for members of the cytochrome C oxidase complex, consistent with a role for Ubp3 in mitochondrial regulation. Several DUBs also showed broad expression changes for phosphate transporters as well as other components of the inorganic phosphate signaling pathway, suggesting a role for these DUBs in regulating phosphate metabolism. These data highlight the potential of multiplexed proteome-wide analyses for biological investigation and provide a framework for further study of the DUB family. Our methods are readily applicable to the entire collection of yeast deletion mutants and may help facilitate systematic analysis of yeast and other organisms.

The paracaspase MALT1 cleaves HOIL1 reducing linear ubiquitination by LUBAC to dampen lymphocyte NF-κB signalling

Antigen receptor signalling activates the canonical NF-κB pathway via the CARD11/BCL10/MALT1 (CBM) signalosome involving key, yet ill-defined roles for linear ubiquitination. The paracaspase MALT1 cleaves and removes negative checkpoint proteins, amplifying lymphocyte responses in NF-κB activation and in B-cell lymphoma subtypes. To identify new human MALT1 substrates, we compare B cells from the only known living MALT1(mut/mut) patient with healthy MALT1(+/mut) family members using 10-plex Tandem Mass Tag TAILS N-terminal peptide proteomics. We identify HOIL1 of the linear ubiquitin chain assembly complex as a novel MALT1 substrate. We show linear ubiquitination at B-cell receptor microclusters and signalosomes. Late in the NF-κB activation cycle HOIL1 cleavage transiently reduces linear ubiquitination, including of NEMO and RIP1, dampening NF-κB activation and preventing reactivation. By regulating linear ubiquitination, MALT1 is both a positive and negative pleiotropic regulator of the human canonical NF-κB pathway-first promoting activation via the CBM--then triggering HOIL1-dependent negative-feedback termination, preventing reactivation.

From raw data to biological discoveries: a computational analysis pipeline for mass spectrometry-based proteomics

In the last two decades, computational tools for mass spectrometry-based proteomics data analysis have evolved from a few stand-alone software solutions serving specific goals, such as the identification of amino acid sequences based on mass spectrometry spectra, to large-scale complex pipelines integrating multiple computer programs to solve a collection of problems. This software evolution has been mostly driven by the appearance of novel technologies that allowed the community to tackle complex biological problems, such as the identification of proteins that are differentially expressed in two samples under different conditions. The achievement of such objectives requires a large suite of programs to analyze the intricate mass spectrometry data. Our laboratory addresses complex proteomics questions by producing and using algorithms and software packages. Our current computational pipeline includes, among other things, tools for mass spectrometry raw data processing, peptide and protein identification and quantification, post-translational modification analysis, and protein functional enrichment analysis. In this paper, we describe a suite of software packages we have developed to process mass spectrometry-based proteomics data and we highlight some of the new features of previously published programs as well as tools currently under development. Graphical Abstract ᅟ.

Proteomic Analysis Identifies Ribosome Reduction as an Effective Proteotoxic Stress Response

Stress responses are adaptive cellular programs that identify and mitigate potentially dangerous threats. Misfolded proteins are a ubiquitous and clinically relevant stress. Trivalent metalloids, such as arsenic, have been proposed to cause protein misfolding. Using tandem mass tag-based mass spectrometry, we show that trivalent arsenic results in widespread reorganization of the cell from an anabolic to a catabolic state. Both major pathways of protein degradation, the proteasome and autophagy, show increased abundance of pathway components and increased functional output, and are required for survival. Remarkably, cells also showed a down-regulation of ribosomes at the protein level. That this represented an adaptive response and not an adverse toxic effect was indicated by enhanced survival of ribosome mutants after arsenic exposure. These results suggest that a major source of toxicity of trivalent arsenic derives from misfolding of newly synthesized proteins and identifies ribosome reduction as a rapid, effective, and reversible proteotoxic stress response.

Quantitative phosphoproteomics reveals new roles for the protein phosphatase PP6 in mitotic cells

Protein phosphorylation is an important regulatory mechanism controlling mitotic progression. Protein phosphatase 6 (PP6) is an essential enzyme with conserved roles in chromosome segregation and spindle assembly from yeast to humans. We applied a baculovirus-mediated gene silencing approach to deplete HeLa cells of the catalytic subunit of PP6 (PP6c) and analyzed changes in the phosphoproteome and proteome in mitotic cells by quantitative mass spectrometry-based proteomics. We identified 408 phosphopeptides on 272 proteins that increased and 298 phosphopeptides on 220 proteins that decreased in phosphorylation upon PP6c depletion in mitotic cells. Motif analysis of the phosphorylated sites combined with bioinformatics pathway analysis revealed previously unknown PP6c-dependent regulatory pathways. Biochemical assays demonstrated that PP6c opposed casein kinase 2-dependent phosphorylation of the condensin I subunit NCAP-G, and cellular analysis showed that depletion of PP6c resulted in defects in chromosome condensation and segregation in anaphase, consistent with dysregulation of condensin I function in the absence of PP6 activity.

Generation of multiple reporter ions from a single isobaric reagent increases multiplexing capacity for quantitative proteomics

Isobaric labeling strategies for mass spectrometry-based proteomics enable multiplexed simultaneous quantification of samples and therefore substantially increase the sample throughput in proteomics. However, despite these benefits, current limits to multiplexing capacity are prohibitive for large sample sizes and impose limitations on experimental design. Here, we introduce a novel mechanism for increasing the multiplexing density of isobaric reagents. We present Combinatorial Isobaric Mass Tags (CMTs), an isobaric labeling architecture with the unique ability to generate multiple series of reporter ions simultaneously. We demonstrate that utilization of multiple reporter ion series improves multiplexing capacity of CMT with respect to a commercially available isobaric labeling reagent with preserved quantitative accuracy and depth of coverage in complex mixtures. We provide a blueprint for the realization of 16-plex reagents with 1 Da spacing between reporter ions and up to 28-plex at 6 mDa spacing using only 5 heavy isotopes per reagent. We anticipate that this improvement in multiplexing capacity will further advance the application of quantitative proteomics, particularly in high-throughput screening assays.

The Nuclear Proteome of a Vertebrate

The composition of the nucleoplasm determines the behavior of key processes such as transcription, yet there is still no reliable and quantitative resource of nuclear proteins. Furthermore, it is still unclear how the distinct nuclear and cytoplasmic compositions are maintained. To describe the nuclear proteome quantitatively, we isolated the large nuclei of frog oocytes via microdissection and measured the nucleocytoplasmic partitioning of ∼9,000 proteins by mass spectrometry. Most proteins localize entirely to either nucleus or cytoplasm; only ∼17% partition equally. A protein's native size in a complex, but not polypeptide molecular weight, is predictive of localization: partitioned proteins exhibit native sizes larger than ∼100 kDa, whereas natively smaller proteins are equidistributed. To evaluate the role of nuclear export in maintaining localization, we inhibited Exportin 1. This resulted in the expected re-localization of proteins toward the nucleus, but only 3% of the proteome was affected. Thus, complex assembly and passive retention, rather than continuous active transport, is the dominant mechanism for the maintenance of nuclear and cytoplasmic proteomes.