A sentinel protein assay for simultaneously quantifying cellular processes

The regulatory landscape of the yeast phosphoproteome

The cellular ability to react to environmental fluctuations depends on signaling networks that are controlled by the dynamic activities of kinases and phosphatases. Here, to gain insight into these stress-responsive phosphorylation networks, we generated a quantitative mass spectrometry-based atlas of early phosphoproteomic responses in Saccharomyces cerevisiae exposed to 101 environmental and chemical perturbations. We report phosphosites on 59% of the yeast proteome, with 18% of the proteome harboring a phosphosite that is regulated within 5 min of stress exposure. We identify shared and perturbation-specific stress response programs, uncover loss of phosphorylation as an integral early event, and dissect the interconnected regulatory landscape of kinase-substrate networks, as we exemplify with target of rapamycin signaling. We further reveal functional organization principles of the stress-responsive phosphoproteome based on phosphorylation site motifs, kinase activities, subcellular localizations, shared functions and pathway intersections. This information-rich map of 25,000 regulated phosphosites advances our understanding of signaling networks.

A Multipathway Phosphopeptide Standard for Rapid Phosphoproteomics Assay Development

Recent advances in methodology have made phosphopeptide analysis a tractable problem for many proteomics researchers. There are now a wide variety of robust and accessible enrichment strategies to generate phosphoproteomes while free or inexpensive software tools for quantitation and site localization have simplified phosphoproteome analysis workflow tremendously. As a research group under the Association for Biomolecular Resource Facilities umbrella, the Proteomics Standards Research Group has worked to develop a multipathway phosphopeptide standard based on a mixture of heavy-labeled phosphopeptides designed to enable researchers to rapidly develop assays. This mixture contains 131 mass spectrometry vetted phosphopeptides specifically chosen to cover as many known biologically interesting phosphosites as possible from seven different signaling networks: AMPK signaling, death and apoptosis signaling, ErbB signaling, insulin/insulin-like growth factor-1 signaling, mTOR signaling, PI3K/AKT signaling, and stress (p38/SAPK/JNK) signaling. Here, we describe a characterization of this mixture spiked into a HeLa tryptic digest stimulated with both epidermal growth factor and insulin-like growth factor-1 to activate the MAPK and PI3K/AKT/mTOR pathways. We further demonstrate a comparison of phosphoproteomic profiling of HeLa performed independently in five labs using this phosphopeptide mixture with data-independent acquisition. Despite different experimental and instrumentation processes, we found that labs could produce reproducible, harmonized datasets by reporting measurements as ratios to the standard, while intensity measurements showed lower consistency between labs even after normalization. Our results suggest that widely available, biologically relevant phosphopeptide standards can act as a quantitative "yardstick" across laboratories and sample preparations enabling experimental designs larger than a single laboratory can perform. Raw data files are publicly available in the MassIVE dataset MSV000090564.

Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics

Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth. These strategies increased the sensitivity, data completeness and proteome coverage over twofold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport, similarly across both treatment conditions. This covariation is coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at http://scp.slavovlab.net/pSCoPE .

Fungal resilience and host-pathogen interactions: Future perspectives and opportunities

We are constantly exposed to the threat of fungal infection. The outcome-clearance, commensalism or infection-depends largely on the ability of our innate immune defences to clear infecting fungal cells versus the success of the fungus in mounting compensatory adaptive responses. As each seeks to gain advantage during these skirmishes, the interactions between host and fungal pathogen are complex and dynamic. Nevertheless, simply compromising the physiological robustness of fungal pathogens reduces their ability to evade antifungal immunity, their virulence, and their tolerance against antifungal therapy. In this article I argue that this physiological robustness is based on a 'Resilience Network' which mechanistically links and controls fungal growth, metabolism, stress resistance and drug tolerance. The elasticity of this network probably underlies the phenotypic variability of fungal isolates and the heterogeneity of individual cells within clonal populations. Consequently, I suggest that the definition of the fungal Resilience Network represents an important goal for the future which offers the clear potential to reveal drug targets that compromise drug tolerance and synergise with current antifungal therapies.

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

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

Quantitative Cell Proteomic Atlas: Pathway-Scale Targeted Mass Spectrometry for High-Resolution Functional Profiling of Cell Signaling

In spite of extensive studies of cellular signaling, many fundamental processes such as pathway integration, cross-talk, and feedback remain poorly understood. To enable integrated and quantitative measurements of cellular biochemical activities, we have developed the Quantitative Cell Proteomics Atlas (QCPA). QCPA consists of panels of targeted mass spectrometry assays to determine the abundance and stoichiometry of regulatory post-translational modifications of sentinel proteins from most known physiologic and pathogenic signaling pathways in human cells. QCPA currently profiles 1 913 peptides from 469 effectors of cell surface signaling, apoptosis, stress response, gene expression, quiescence, and proliferation. For each protein, QCPA includes triplets of isotopically labeled peptides covering known post-translational regulatory sites to determine their stoichiometries and unmodified protein regions to measure total protein abundance. The QCPA framework incorporates analytes to control for technical variability of sample preparation and mass spectrometric analysis, including TrypQuant, a synthetic substrate for accurate quantification of proteolysis efficiency for proteins containing chemically modified residues. The ability to precisely and accurately quantify most known signaling pathways should enable improved chemoproteomic approaches for the comprehensive analysis of cell signaling and clinical proteomics of diagnostic specimens. QCPA is openly available at https://qcpa.mskcc.org.

Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

Background

Starch, a vital plant-derived polysaccharide comprised of branched glucans, is essential in nutrition and many industrial applications. Starch is often modified post-extraction to alter its structure and enhance its functionality. Targeted metabolic engineering of crops to produce valuable and versatile starches requires knowledge of the relationships between starch biosynthesis, structure, and properties, but systematic studies to obtain this knowledge are difficult to conduct in plants. Here we used Saccharomyces cerevisiae as a testbed to dissect the functions of plant starch biosynthetic enzymes and create diverse starch-like polymers.

Results

We explored yeast promoters and terminators to tune the expression levels of the starch-biosynthesis machinery from Arabidopsis thaliana. We systematically modulated the expression of each starch synthase (SS) together with a branching enzyme (BE) in yeast. Protein quantification by parallel reaction monitoring (targeted proteomics) revealed unexpected effects of glucan biosynthesis on protein abundances but showed that the anticipated broad range of SS/BE enzyme ratios was maintained during the biosynthetic process. The different SS/BE ratios clearly influenced glucan structure and solubility: The higher the SS/BE ratio, the longer the glucan chains and the more glucans were partitioned into the insoluble fraction. This effect was irrespective of the SS isoform, demonstrating that the elongation/branching ratio controls glucan properties separate from enzyme specificity.

Conclusions

Our results provide a quantitative framework for the in silico design of improved starch biosynthetic processes in plants. Our study also exemplifies a workflow for the rational tuning of a complex pathway in yeast, starting from the selection and evaluation of expression modules to multi-gene assembly and targeted protein monitoring during the biosynthetic process.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01408-x.

Antifungal Thiazolidines: Synthesis and Biological Evaluation of Mycosidine Congeners

Novel derivatives of Mycosidine (3,5-substituted thiazolidine-2,4-diones) are synthesized by Knoevenagel condensation and reactions of thiazolidines with chloroformates or halo-acetic acid esters. Furthermore, 5-Arylidene-2,4-thiazolidinediones and their 2-thioxo analogs containing halogen and hydroxy groups or di(benzyloxy) substituents in 5-benzylidene moiety are tested for antifungal activity in vitro. Some of the synthesized compounds exhibit high antifungal activity, both fungistatic and fungicidal, and lead to morphological changes in the Candida yeast cell wall. Based on the use of limited proteomic screening and toxicity analysis in mutants, we show that Mycosidine activity is associated with glucose transport. This suggests that this first-in-class antifungal drug has a novel mechanism of action that deserves further study.

A highly multiplexed quantitative phosphosite assay for biology and preclinical studies

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.

Targeted mass spectrometry for monitoring of neural differentiation

Human multipotent neural stem cells could effectively be used for the treatment of a variety of neurological disorders. However, a defining signature of neural stem cell lines that would be expandable, non-tumorigenic, and differentiate into desirable neuronal/glial phenotype after in vivo grafting is not yet defined. Employing a mass spectrometry approach, based on selected reaction monitoring, we tested a panel of well-described culture conditions, and measured levels of protein markers routinely used to probe neural differentiation, i.e. POU5F1 (OCT4), SOX2, NES, DCX, TUBB3, MAP2, S100B, GFAP, GALC, and OLIG1. Our multiplexed assay enabled us to simultaneously identify the presence of pluripotent, multipotent, and lineage-committed neural cells, thus representing a powerful tool to optimize novel and highly specific propagation and differentiation protocols. The multiplexing capacity of this method permits the addition of other newly identified cell type-specific markers to further increase the specificity and quantitative accuracy in detecting targeted cell populations. Such an expandable assay may gain the advantage over traditional antibody-based assays, and represents a method of choice for quality control of neural stem cell lines intended for clinical use.

Mapping specificity, cleavage entropy, allosteric changes and substrates of blood proteases in a high-throughput screen

Proteases are among the largest protein families and critical regulators of biochemical processes like apoptosis and blood coagulation. Knowledge of proteases has been expanded by the development of proteomic approaches, however, technology for multiplexed screening of proteases within native environments is currently lacking behind. Here we introduce a simple method to profile protease activity based on isolation of protease products from native lysates using a 96FASP filter, their analysis in a mass spectrometer and a custom data analysis pipeline. The method is significantly faster, cheaper, technically less demanding, easy to multiplex and produces accurate protease fingerprints. Using the blood cascade proteases as a case study, we obtain protease substrate profiles that can be used to map specificity, cleavage entropy and allosteric effects and to design protease probes. The data further show that protease substrate predictions enable the selection of potential physiological substrates for targeted validation in biochemical assays.

Characterizing proteases in their native environment is still challenging. Here, the authors develop a proteomics workflow for analyzing protease-specific peptides from cell lysates in 96-well format, providing mechanistic insights into blood proteases and enabling the prediction of protease substrates.

Single-cell proteomic analysis

The ability to comprehensively profile proteins in every individual cell of complex biological systems is crucial to advance our understanding of normal physiology and disease pathogenesis. Conventional bulk cell experiments mask the cell heterogeneity in the population, while the single-cell imaging methods suffer from the limited multiplexing capacities. Recent advances in microchip-, mass spectrometry-, and reiterative staining-based technologies have enabled comprehensive protein profiling in single cells. These approaches will bring new insights into a variety of biological and biomedical fields, such as signaling network regulation, cell heterogeneity, tissue architecture, disease diagnosis, and treatment monitoring. In this article, we will review the recent advances in the development of single-cell proteomic technologies, describe their advantages, discuss the current limitations and challenges, and propose potential solutions. We will also highlight the wide applications of these technologies in biology and medicine. This article is categorized under: Cancer > Molecular and Cellular Physiology.

R2-P2 rapid-robotic phosphoproteomics enables multidimensional cell signaling studies

Recent developments in proteomics have enabled signaling studies where > 10,000 phosphosites can be routinely identified and quantified. Yet, current analyses are limited in throughput, reproducibility, and robustness, hampering experiments that involve multiple perturbations, such as those needed to map kinase-substrate relationships, capture pathway crosstalks, and network inference analysis. To address these challenges, we introduce rapid-robotic phosphoproteomics (R2-P2), an end-to-end automated method that uses magnetic particles to process protein extracts to deliver mass spectrometry-ready phosphopeptides. R2-P2 is rapid, robust, versatile, and high-throughput. To showcase the method, we applied it, in combination with data-independent acquisition mass spectrometry, to study signaling dynamics in the mitogen-activated protein kinase (MAPK) pathway in yeast. Our results reveal broad and specific signaling events along the mating, the high-osmolarity glycerol, and the invasive growth branches of the MAPK pathway, with robust phosphorylation of downstream regulatory proteins and transcription factors. Our method facilitates large-scale signaling studies involving hundreds of perturbations opening the door to systems-level studies aiming to capture signaling complexity.

Proteomics-Based Monitoring of Pathway Activity Reveals that Blocking Diacylglycerol Biosynthesis Rescues from Alpha-Synuclein Toxicity

Proteinaceous inclusions containing alpha-synuclein (α-Syn) have been implicated in neuronal toxicity in Parkinson's disease, but the pathways that modulate toxicity remain enigmatic. Here, we used a targeted proteomic assay to simultaneously measure 269 pathway activation markers and proteins deregulated by α-Syn expression across a panel of 33 Saccharomyces cerevisiae strains that genetically modulate α-Syn toxicity. Applying multidimensional linear regression analysis to these data predicted Pah1, a phosphatase that catalyzes conversion of phosphatidic acid to diacylglycerol at the endoplasmic reticulum membrane, as an effector of rescue. Follow-up studies demonstrated that inhibition of Pah1 activity ameliorates the toxic effects of α-Syn, indicate that the diacylglycerol branch of lipid metabolism could enhance α-Syn neuronal cytotoxicity, and suggest a link between α-Syn toxicity and the biology of lipid droplets.

High-Throughput Assessment of Kinome-wide Activation States

Aberrant kinase activity has been linked to a variety of disorders; however, methods to probe kinase activation states in cells have been lacking. Until now, kinase activity has mainly been deduced from either protein expression or substrate phosphorylation levels. Here, we describe a strategy to directly infer kinase activation through targeted quantification of T-loop phosphorylation, which serves as a critical activation switch in a majority of protein kinases. Combining selective phosphopeptide enrichment with robust targeted mass spectrometry, we provide highly specific assays for 248 peptides, covering 221 phosphosites in the T-loop region of 178 human kinases. Using these assays, we monitored the activation of 63 kinases through 73 T-loop phosphosites across different cell types, primary cells, and patient-derived tissue material. The sensitivity of our assays is highlighted by the reproducible detection of TNF-α-induced RIPK1 activation and the detection of 46 T-loop phosphorylation sites from a breast tumor needle biopsy.

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Robust targeted MS assays permit observation of conserved kinome activation sites

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178 human kinases are characterized in high-throughput assays

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Kinase activation states are observed in human primary cells and needle biopsy

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Specific kinase activation states are induced during cell death and drug resistance

Systems NMR: single-sample quantification of RNA, proteins and metabolites for biomolecular network analysis

Cellular behavior is controlled by the interplay of diverse biomolecules. Most experimental methods, however, can monitor only a single molecule class or reaction type at a time. We developed an in vitro Nuclear Magnetic Resonance spectroscopy (NMR) approach, which permitted dynamic quantification of an entire “heterotypic” network – simultaneously monitoring three distinct molecule classes (metabolites, proteins, RNA) and all elementary reaction types (bimolecular interactions, catalysis, unimolecular changes). Focusing on an 8-reaction co-transcriptional RNA folding network, in a single sample we recorded over 35 time-points with over 170 observables each, and accurately determined 5 core reaction constants in multiplex. This reconstruction revealed unexpected cross-talk between the different reactions. We further observed dynamic phase-separation in a system of five distinct RNA binding domains in the course of the RNA transcription reaction. Our Systems NMR approach provides a deeper understanding of biological network dynamics by combining the dynamic resolution of biochemical assays and the multiplexing ability of “omics”.

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

While mass spectrometry (MS)-based quantification of small molecules has been successfully used for decades, targeted MS has only recently been used by the proteomics community to investigate clinical questions such as biomarker verification and validation. Targeted MS holds the promise of a paradigm shift in the quantitative determination of proteins. Nevertheless, targeted quantitative proteomics requires improvisation in making sample processing, instruments, and data analysis more accessible. In the backdrop of the genomic era reaching its zenith, certain questions arise: is the proteomic era about to come? If we are at the beginning of a new future for protein quantification, are we prepared to incorporate targeted proteomics at the benchside for basic research and at the bedside for the good of patients? Here, an overview of the knowledge required to perform targeted proteomics as well as its applications is provided. A special emphasis is placed on upcoming areas such as peptidomics, proteoform research, and mass spectrometry imaging, where the utilization of targeted proteomics is expected to bring forth new avenues. The limitations associated with the acceptance of this technique for mainstream usage are also highlighted. Also see the video abstract here https://youtu.be/mieB47B8gZw.

Discovering cellular protein-protein interactions: Technological strategies and opportunities

The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption often leads to diseases. Hence, many technologies have been developed to study protein-protein interactions (PPIs) in a cellular context. The expansion of the PPI technology toolbox however complicates the selection of optimal approaches for diverse biological questions. This review gives an overview of the binary and co-complex technologies, with the former evaluating the interaction of two co-expressed genetically tagged proteins, and the latter only needing the expression of a single tagged protein or no tagged proteins at all. Mass spectrometry is crucial for some binary and all co-complex technologies. After the detailed description of the different technologies, the review compares their unique specifications, advantages, disadvantages, and applicability, while highlighting opportunities for further advancements.

Co-occurring KRAS mutation/LKB1 loss in non-small cell lung cancer cells results in enhanced metabolic activity susceptible to caloric restriction: an in vitro integrated multilevel approach

Background

Non–small-cell lung cancer (NSCLC) is a heterogeneous disease, with multiple different oncogenic mutations. Approximately 25–30% of NSCLC patients present KRAS mutations, which confer poor prognosis and high risk of tumor recurrence. About half of NSCLCs with activating KRAS lesions also have deletions or inactivating mutations in the serine/threonine kinase 11 (LKB1) gene. Loss of LKB1 on a KRAS-mutant background may represent a significant source of heterogeneity contributing to poor response to therapy.

Methods

Here, we employed an integrated multilevel proteomics, metabolomics and functional in-vitro approach in NSCLC H1299 isogenic cells to define their metabolic state associated with the presence of different genetic background. Protein levels were obtained by label free and single reaction monitoring (SRM)-based proteomics. The metabolic state was studied coupling targeted and untargeted mass spectrometry (MS) strategy. In vitro metabolic dependencies were evaluated using 2-deoxy glucose (2-DG) treatment or glucose/glutamine nutrient limitation.

Results

Here we demonstrate that co-occurring KRAS mutation/LKB1 loss in NSCLC cells allowed efficient exploitation of glycolysis and oxidative phosphorylation, when compared to cells with each single oncologic genotype. The enhanced metabolic activity rendered the viability of cells with both genetic lesions susceptible towards nutrient limitation.

Conclusions

Co-occurrence of KRAS mutation and LKB1 loss in NSCLC cells induced an enhanced metabolic activity mirrored by a growth rate vulnerability under limited nutrient conditions relative to cells with the single oncogenetic lesions. Our results hint at the possibility that energy stress induced by calorie restriction regimens may sensitize NSCLCs with these co-occurring lesions to cytotoxic chemotherapy.

Electronic supplementary material

The online version of this article (10.1186/s13046-018-0954-5) contains supplementary material, which is available to authorized users.

Layers of regulation of cell-cycle gene expression in the budding yeast Saccharomyces cerevisiae

In the budding yeast Saccharomyces cerevisiae, transcription factors (TFs) regulate the periodic expression of many genes during the cell cycle, including gene products required for progression through cell-cycle events. Experimental evidence coupled with quantitative models suggests that a network of interconnected TFs is capable of regulating periodic genes over the cell cycle. Importantly, these dynamical models were built on transcriptomics data and assumed that TF protein levels and activity are directly correlated with mRNA abundance. To ask whether TF transcripts match protein expression levels as cells progress through the cell cycle, we applied a multiplexed targeted mass spectrometry approach (parallel reaction monitoring) to synchronized populations of cells. We found that protein expression of many TFs and cell-cycle regulators closely followed their respective mRNA transcript dynamics in cycling wild-type cells. Discordant mRNA/protein expression dynamics was also observed for a subset of cell-cycle TFs and for proteins targeted for degradation by E3 ubiquitin ligase complexes such as SCF (Skp1/Cul1/F-box) and APC/C (anaphase-promoting complex/cyclosome). We further profiled mutant cells lacking B-type cyclin/CDK activity ( clb1-6) where oscillations in ubiquitin ligase activity, cyclin/CDKs, and cell-cycle progression are halted. We found that a number of proteins were no longer periodically degraded in clb1-6 mutants compared with wild type, highlighting the importance of posttranscriptional regulation. Finally, the TF complexes responsible for activating G1/S transcription (SBF and MBF) were more constitutively expressed at the protein level than at periodic mRNA expression levels in both wild-type and mutant cells. This comprehensive investigation of cell-cycle regulators reveals that multiple layers of regulation (transcription, protein stability, and proteasome targeting) affect protein expression dynamics during the cell cycle.

Proteomics and Lipidomics in Inflammatory Bowel Disease Research: From Mechanistic Insights to Biomarker Identification

Inflammatory bowel disease (IBD) represents a group of progressive disorders characterized by recurrent chronic inflammation of the gut. Ulcerative colitis and Crohn's disease are the major manifestations of IBD. While our understanding of IBD has progressed in recent years, its etiology is far from being fully understood, resulting in suboptimal treatment options. Complementing other biological endpoints, bioanalytical "omics" methods that quantify many biomolecules simultaneously have great potential in the dissection of the complex pathogenesis of IBD. In this review, we focus on the rapidly evolving proteomics and lipidomics technologies and their broad applicability to IBD studies; these range from investigations of immune-regulatory mechanisms and biomarker discovery to studies dissecting host⁻microbiome interactions and the role of intestinal epithelial cells. Future studies can leverage recent advances, including improved analytical methodologies, additional relevant sample types, and integrative multi-omics analyses. Proteomics and lipidomics could effectively accelerate the development of novel targeted treatments and the discovery of complementary biomarkers, enabling continuous monitoring of the treatment response of individual patients; this may allow further refinement of treatment and, ultimately, facilitate a personalized medicine approach to IBD.

Pseudotargeted MS Method for the Sensitive Analysis of Protein Phosphorylation in Protein Complexes

In this study, we presented an enrichment-free approach for the sensitive analysis of protein phosphorylation in minute amounts of samples, such as purified protein complexes. This method takes advantage of the high sensitivity of parallel reaction monitoring (PRM). Specifically, low confident phosphopeptides identified from the data-dependent acquisition (DDA) data set were used to build a pseudotargeted list for PRM analysis to allow the identification of additional phosphopeptides with high confidence. The development of this targeted approach is very easy as the same sample and the same LC-system were used for the discovery and the targeted analysis phases. No sample fractionation or enrichment was required for the discovery phase which allowed this method to analyze minute amount of sample. We applied this pseudotargeted MS method to quantitatively examine phosphopeptides in affinity purified endogenous Shc1 protein complexes at four temporal stages of EGF signaling and identified 82 phospho-sites. To our knowledge, this is the highest number of phospho-sites identified from the protein complexes. This pseudotargeted MS method is highly sensitive in the identification of low abundance phosphopeptides and could be a powerful tool to study phosphorylation-regulated assembly of protein complex.

The promise of targeted proteomics for quantitative network biology

Proteomics is a powerful tool for obtaining information on a large number of proteins with regard to their expression levels, interactions with other molecules, and posttranslational modifications. Whereas nontargeted, discovery proteomics uncovers differences in the proteomic landscape under different conditions, targeted proteomics has been developed to overcome the limitations of this approach with regard to quantitation. In addition to technical advances in instruments and informatics tools, the advent of the synthetic proteome composed of synthetic peptides or recombinant proteins has advanced the adoption of targeted proteomics across a wide range of research fields. Targeted proteomics can now be applied to measurement of the dynamics of any proteins of interest under a variety of conditions as well as to estimation of the absolute abundance or stoichiometry of proteins in a given network. Multiplexed targeted proteomics assays of high reproducibility and accuracy can provide insight at the quantitative level into entire networks that govern biological phenomena or diseases. Such assays will establish a new paradigm for data-driven science.

Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition

Quantitative proteomics is key for basic research, but needs improvements to satisfy an increasing demand for large sample series in diagnostics, academia and industry. A switch from nanoflowrate to microflowrate chromatography can improve throughput and reduce costs. However, concerns about undersampling and coverage have so far hampered its broad application. We used a QTOF mass spectrometer of the penultimate generation (TripleTOF5600), converted a nanoLC system into a microflow platform, and adapted a SWATH regime for large sample series by implementing retention time- and batch correction strategies. From 3 µg to 5 µg of unfractionated tryptic digests that are obtained from proteomics-typical amounts of starting material, microLC-SWATH-MS quantifies up to 4000 human or 1750 yeast proteins in an hour or less. In the acquisition of 750 yeast proteomes, retention times varied between 2% and 5%, and quantified the typical peptide with 5–8% signal variation in replicates, and below 20% in samples acquired over a five-months period. Providing precise quantities without being dependent on the latest hardware, our study demonstrates that the combination of microflow chromatography and data-independent acquisition strategies has the potential to overcome current bottlenecks in academia and industry, enabling the cost-effective generation of precise quantitative proteomes in large scale.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

Highly Multiplexed Single-Cell Protein Analysis

Single-cell proteomic analysis is crucial to advance our understanding of normal physiology and disease pathogenesis. The comprehensive protein profiling in individual cells of a heterogeneous sample can provide new insights into many important biological issues, such as the regulation of inter- and intracellular signaling pathways or the varied cellular compositions of normal and diseased tissues. With highly multiplexed molecular imaging of many different protein biomarkers in patient biopsies, diseases can be accurately diagnosed to guide the selection of the ideal treatment. In this Minireview, we will describe the recent technological advances of single-cell proteomic assays, discuss their advantages and limitations, highlight their applications in biology and precision medicine, and present the current challenges and potential solutions.

Targeted degradomics in protein terminomics and protease substrate discovery

Targeted degradomics integrates positional information into mass spectrometry (MS)-based targeted proteomics workflows and thereby enables analysis of proteolytic cleavage events with unprecedented specificity and sensitivity. Rapid progress in the establishment of protease-substrate relations provides extensive degradomics target lists that now can be tested with help of selected and parallel reaction monitoring (S/PRM) in complex biological systems, where proteases act in physiological environments. In this minireview, we describe the general principles of targeted degradomics, outline the generic experimental workflow of the methodology and highlight recent and future applications in protease research.

Systems toxicology meta-analysis of in vitro assessment studies: biological impact of a candidate modified-risk tobacco product aerosol compared with cigarette smoke on human organotypic cultures of the aerodigestive tract

Systems biology combines comprehensive molecular analyses with quantitative modeling to understand the characteristics of a biological system as a whole. Leveraging a similar approach, systems toxicology aims to decipher complex biological responses following exposures. This work reports a systems toxicology meta-analysis in the context of in vitro assessment of a candidate modified-risk tobacco product (MRTP) using three human organotypic cultures of the aerodigestive tract (buccal, bronchial, and nasal epithelia). Complementing a series of functional measures, a causal network enrichment analysis of transcriptomic data was used to compare quantitatively the biological impact of aerosol from the Tobacco Heating System (THS) 2.2, a candidate MRTP, with 3R4F cigarette smoke (CS) at similar nicotine concentrations. Lower toxicity was observed in all cultures following exposure to THS2.2 aerosol compared with 3R4F CS. Because of their morphological differences, a smaller exposure impact was observed in the buccal (stratified epithelium) compared with the bronchial and nasal (pseudostratified epithelium). However, the causal network enrichment approach supported a similar mechanistic impact of CS across the three cultures, including the impact on xenobiotic, oxidative stress, and inflammatory responses. At comparable nicotine concentrations, THS2.2 aerosol elicited reduced and more transient effects on these processes. To demonstrate the benefits of additional data modalities, we employed a newly established targeted mass-spectrometry marker panel to further confirm the reduced cellular stress responses elicited by THS2.2 aerosol compared with 3R4F CS in the nasal culture. Overall, this work demonstrates the applicability and robustness of the systems toxicology approach for in vitro inhalation toxicity assessment.

Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS

Consistent detection and quantification of protein post-translational modifications (PTMs) across sample cohorts is a prerequisite for functional analysis of biological processes. Data-independent acquisition (DIA) is a bottom-up mass spectrometry approach that provides complete information on precursor and fragment ions. However, owing to the convoluted structure of DIA data sets, confident, systematic identification and quantification of peptidoforms has remained challenging. Here, we present inference of peptidoforms (IPF), a fully automated algorithm that uses spectral libraries to query, validate and quantify peptidoforms in DIA data sets. The method was developed on data acquired by the DIA method SWATH-MS and benchmarked using a synthetic phosphopeptide reference data set and phosphopeptide-enriched samples. IPF reduced false site-localization by more than sevenfold compared with previous approaches, while recovering 85.4% of the true signals. Using IPF, we quantified peptidoforms in DIA data acquired from >200 samples of blood plasma of a human twin cohort and assessed the contribution of heritable, environmental and longitudinal effects on their PTMs.

Scout-MRM: Multiplexed Targeted Mass Spectrometry-Based Assay without Retention Time Scheduling Exemplified by Dickeya dadantii Proteomic Analysis during Plant Infection

Targeted mass spectrometry of a surrogate peptide panel is a powerful method to study the dynamics of protein networks, but chromatographic time scheduling remains a major limitation for dissemination and implementation of robust and large multiplexed assays. We unveil a Multiple Reaction Monitoring method (Scout-MRM) where the use of spiked scout peptides triggers complex transition lists, regardless of the retention time of targeted surrogate peptides. The interest of Scout-MRM method regarding the retention time independency, multiplexing capability, reproducibility, and putative interest in facilitating method transfer was illustrated by a 782-peptide-plex relative assay targeting 445 proteins of the phytopathogen Dickeya dadantii during plant infection.

A large-scale targeted proteomics assay resource based on an in vitro human proteome

Targeted proteomics approaches are of value for deep and accurate quantification of protein abundance. Extending such methods to quantify large numbers of proteins requires the construction of predefined targeted assays. We developed a targeted proteomics platform-in vitro proteome-assisted multiple reaction monitoring (MRM) for protein absolute quantification (iMPAQT)-by using >18,000 human recombinant proteins, thus enabling protein absolute quantification on a genome-wide scale. Our platform comprises experimentally confirmed MRM assays of mass tag (mTRAQ)-labeled peptides to allow for rapid and straightforward measurement of the absolute abundance of predefined sets of proteins by mass spectrometry. We applied iMPAQT to delineate the quantitative metabolic landscape of normal and transformed human fibroblasts. Oncogenic transformation gave rise to relatively small but global changes in metabolic pathways resulting in aerobic glycolysis (Warburg effect) and increased rates of macromolecule synthesis. iMPAQT should facilitate quantitative biology studies based on protein abundance measurements.

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high-accuracy MS in combination with high-resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism-focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high-resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques. Graphical Abstract ᅟ.

Advances in targeted proteomics and applications to biomedical research

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074-1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed.

Analysis of Drosophila melanogaster proteome dynamics during embryonic development by a combination of label-free proteomics approaches

During embryogenesis, organisms undergo considerable cellular remodelling requiring the combined action of thousands of proteins. In case of the well-studied model Drosophila melanogaster, transcriptomic studies, most notably from the modENCODE project, have described in detail changes in gene expression at the mRNA level across development. Although such data are clearly very useful to understand how the genome is regulated during embryogenesis, it is important to understand how changes in gene expression are reflected at the level of the proteome. In this study, we describe a combination of two quantitative label-free approaches, SWATH and data-dependent acquisition, to monitor changes in protein expression across a timecourse of D. melanogaster embryonic development. We demonstrate that both approaches provide robust and reproducible methods for the analysis of proteome changes. In a preliminary analysis of Drosophila embryogenesis, we identified several pathways, including the heat-shock response, nuclear protein import and energy production that are regulated during embryo development. In some cases changes in protein expression mirrored transcript levels across development, whereas other proteins showed signatures of post-transcriptional regulation. Taken together, our pilot study provides a solid platform for a more detailed exploration of the embryonic proteome.

Multiplexed Epitope-Based Tissue Imaging for Discovery and Healthcare Applications

The study of organs and tissues on a molecular level is necessary as we seek an understanding of health and disease. Over the last few years, powerful highly multiplexed epitope-based imaging approaches that rely on the serial imaging of tissues with fluorescently labeled antibodies and the simultaneous analysis using metal-labeled antibodies have emerged. These techniques enable analysis of dozens of epitopes in thousands of cells in a single experiment providing a systems level view of normal and disease processes at the single-cell level with spatial resolution in tissues. In this Review, I discuss, first, the highly multiplexed epitope-based imaging approaches and the generated data. Second, I describe challenges that must be overcome to implement these imaging methods from bench to bedside, including issues with tissue processing and analyses of the large amounts of data generated. Third, I discuss how these methods can be integrated with readouts of genome, transcriptome, metabolome, and live cell information, and fourth, the novel applications possible in tissue biology, drug development, and biomarker discovery. I anticipate that highly multiplexed epitope-based imaging approaches will broadly complement existing imaging methods and will become a cornerstone of tissue biology and biomedical research and of precision medical applications.

Plug-and-play analysis of the human phosphoproteome by targeted high-resolution mass spectrometry

Systematic approaches to studying cellular signaling require phosphoproteomic techniques that reproducibly measure the same phosphopeptides across multiple replicates, conditions, and time points. Here we present a method to mine information from large-scale, heterogeneous phosphoproteomics data sets to rapidly generate robust targeted mass spectrometry (MS) assays. We demonstrate the performance of our method by interrogating the IGF-1/AKT signaling pathway, showing that even rarely observed phosphorylation events can be consistently detected and precisely quantified.

Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes

Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.

Applications of targeted proteomics in systems biology and translational medicine

Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM-MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.

Signal Transduction Reaction Monitoring Deciphers Site-Specific PI3K-mTOR/MAPK Pathway Dynamics in Oncogene-Induced Senescence

We report a straightforward strategy to comprehensively monitor signal transduction pathway dynamics in mammalian systems. Combining targeted quantitative proteomics with highly selective phosphopeptide enrichment, we monitor, with great sensitivity, phosphorylation dynamics of the PI3K-mTOR and MAPK signaling networks. Our approach consists of a single enrichment step followed by a single targeted proteomics experiment, circumventing the need for labeling and immune purification while enabling analysis of selected phosphorylation nodes throughout signaling pathways. The need for such a comprehensive pathway analysis is illustrated by highlighting previously uncharacterized phosphorylation changes in oncogene-induced senescence, associated with diverse biological phenotypes and pharmacological intervention of the PI3K-mTOR pathway.

Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications

In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late.

Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

Proteomics beyond large-scale protein expression analysis

Proteomics is commonly referred to as the application of high-throughput approaches to protein expression analysis. Typical results of proteomics studies are inventories of the protein content of a sample or lists of differentially expressed proteins across multiple conditions. Recently, however, an explosion of novel proteomics workflows has significantly expanded proteomics beyond the analysis of protein expression. Targeted proteomics methods, for example, enable the analysis of the fine dynamics of protein systems, such as a specific pathway or a network of interacting proteins, and the determination of protein complex stoichiometries. Structural proteomics tools allow extraction of restraints for structural modeling and identification of structurally altered proteins on a proteome-wide scale. Other variations of the proteomic workflow can be applied to the large-scale analysis of protein activity, location, degradation and turnover. These exciting developments provide new tools for multi-level 'omics' analysis and for the modeling of biological networks in the context of systems biology studies.