Mass-spectrometric exploration of proteome structure and function

Proteomics to study macrophage response to viral infection

Viral infections are a major burden to human and animal health. Immune response against viruses consists of innate and adaptive immunity which are both critical for the eradication of the viral infection. The innate immune system is the first line of defense against viral infections. Proper innate immune response is required for the activation of adaptive, humoral and cell-mediated immunity. Macrophages are innate immune cells which have a central role in detecting viral infections including influenza A and human immunodeficiency viruses. Macrophages and other host cells respond to viral infection by modulating their protein expression levels, proteins' posttranslational modifications, as well as proteins' intracellular localization and secretion. Therefore the detailed characterization how viruses dynamically manipulate host proteome is needed for understanding the molecular mechanisms of viral infection. It is critical to identify cellular host factors which are exploited by different viruses, and which are less prone for mutations and could serve as potential targets for novel antiviral compounds. Here, we review how proteomics studies have enhanced our understanding of macrophage response to viral infection with special focus on Influenza A and Human immunodeficiency viruses, and virus infections of swine.

SIGNIFICANCE

Influenza A viruses (IAVs) and human immunodeficiency viruses (HIV) infect annually millions of people worldwide and they form a severe threat to human health. Both IAVs and HIV-1 can efficiently antagonize host response and develop drug-resistant variants. Most current antiviral drugs are directed against viral proteins, and there is a constant need to develop new next-generation drugs targeting host proteins that are essential for viral replication. Porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2) are economically important swine pathogens. Both PRRSV and PCV2 cause severe respiratory tract illnesses in swine. IAVs, HIV-1, and swine viruses infect macrophages activating antiviral response against these viruses. Macrophages also have a central role in the replication and spread of these viruses. However, macrophage response to these viruses is incompletely understood. Current proteomics methods can provide a global view of host-response to viral infection which is needed for in-depth understanding the molecular mechanisms of viral infection. Here we review the current proteomics studies on macrophage response to viral infection and provide insight into the global host proteome changes upon viral infection.

Proteome-wide Adaptations of Mouse Skeletal Muscles during a Full Month in Space

The safety of space flight is challenged by a severe loss of skeletal muscle mass, strength, and endurance that may compromise the health and performance of astronauts. The molecular mechanisms underpinning muscle atrophy and decreased performance have been studied mostly after short duration flights and are still not fully elucidated. By deciphering the muscle proteome changes elicited in mice after a full month aboard the BION-M1 biosatellite, we observed that the antigravity soleus incurred the greatest changes compared with locomotor muscles. Proteomics data notably suggested mitochondrial dysfunction, metabolic and fiber type switching toward glycolytic type II fibers, structural alterations, and calcium signaling-related defects to be the main causes for decreased muscle performance in flown mice. Alterations of the protein balance, mTOR pathway, myogenesis, and apoptosis were expected to contribute to muscle atrophy. Moreover, several signs reflecting alteration of telomere maintenance, oxidative stress, and insulin resistance were found as possible additional deleterious effects. Finally, 8 days of recovery post flight were not sufficient to restore completely flight-induced changes. Thus in-depth proteomics analysis unraveled the complex and multifactorial remodeling of skeletal muscle structure and function during long-term space flight, which should help define combined sets of countermeasures before, during, and after the flight.

Application of SWATH Proteomics to Mouse Biology

The quantitative measurement of the proteome has been shown to yield new insights into physiology and cell biology that cannot be determined from the genome and transcriptome because the quantitative relationship between transcriptome and proteome is complex. MS-based proteomics techniques, such as SWATH-MS, have recently advanced to the point at which they may be reliably applied by biologists who are not specialists in mass spectrometry. Here we provide standard protocols for preparation of tissue samples for input into the SWATH-MS analytical pipeline. These protocols are designed for high-throughput processing of tissues with ≥5 mg of sample available for analysis. Studies with extremely limited amounts of tissue should consider PCT-SWATH. An experienced single user should be able to process 48 samples per day for injection into the mass spectrometer, or up to 144 samples a week. The machine time necessary for running these samples with SWATH is approximately 1.5 hr per sample. Data acquisition protocols are also provided. © 2017 by John Wiley & Sons, Inc.

A community proposal to integrate proteomics activities in ELIXIR

Computational approaches have been major drivers behind the progress of proteomics in recent years. The aim of this white paper is to provide a framework for integrating computational proteomics into ELIXIR in the near future, and thus to broaden the portfolio of omics technologies supported by this European distributed infrastructure. This white paper is the direct result of a strategy meeting on ‘The Future of Proteomics in ELIXIR’ that took place in March 2017 in Tübingen (Germany), and involved representatives of eleven ELIXIR nodes.

These discussions led to a list of priority areas in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR’s existing platforms, and how it could lead to a new ELIXIR use case in proteomics. We also highlight connections to the related field of metabolomics, where similar activities are ongoing. This white paper could thus serve as a starting point for the integration of computational proteomics into ELIXIR. Over the next few months we will be working closely with all stakeholders involved, and in particular with other representatives of the proteomics community, to further refine this paper.

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.

Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics

BACKGROUND

Triple-negative breast cancer (TNBC) accounts for 15-20% of all breast cancers and usually requires the administration of adjuvant chemotherapy after surgery but even with this treatment many patients still suffer from a relapse. The main objective of this study was to identify proteomics-based biomarkers that predict the response to standard adjuvant chemotherapy, so that patients at are not going to benefit from it can be offered therapeutic alternatives.

METHODS

We analyzed the proteome of a retrospective series of formalin-fixed, paraffin-embedded TNBC tissue applying high-throughput label-free quantitative proteomics. We identified several protein signatures with predictive value, which were validated with quantitative targeted proteomics in an independent cohort of patients and further evaluated in publicly available transcriptomics data.

RESULTS

Using univariate Cox analysis, a panel of 18 proteins was significantly associated with distant metastasis-free survival of patients (p<0.01). A reduced 5-protein profile with prognostic value was identified and its prediction performance was assessed in an independent targeted proteomics experiment and a publicly available transcriptomics dataset. Predictor P5 including peptides from proteins RAC2, RAB6A, BIEA and IPYR was the best performance protein combination in predicting relapse after adjuvant chemotherapy in TNBC patients.

CONCLUSIONS

This study identified a protein combination signature that complements histopathological prognostic factors in TNBC treated with adjuvant chemotherapy. The protein signature can be used in paraffin-embedded samples, and after a prospective validation in independent series, it could be used as predictive clinical test in order to recommend participation in clinical trials or a more exhaustive follow-up.

Fam60a defines a variant Sin3a-Hdac complex in embryonic stem cells required for self-renewal

Sin3a is the central scaffold protein of the prototypical Hdac1/2 chromatin repressor complex, crucially required during early embryonic development for the growth of pluripotent cells of the inner cell mass. Here, we compare the composition of the Sin3a-Hdac complex between pluripotent embryonic stem (ES) and differentiated cells by establishing a method that couples two independent endogenous immunoprecipitations with quantitative mass spectrometry. We define the precise composition of the Sin3a complex in multiple cell types and identify the Fam60a subunit as a key defining feature of a variant Sin3a complex present in ES cells, which also contains Ogt and Tet1. Fam60a binds on H3K4me3-positive promoters in ES cells, together with Ogt, Tet1 and Sin3a, and is essential to maintain the complex on chromatin. Finally, we show that depletion of Fam60a phenocopies the loss of Sin3a, leading to reduced proliferation, an extended G1-phase and the deregulation of lineage genes. Taken together, Fam60a is an essential core subunit of a variant Sin3a complex in ES cells that is required to promote rapid proliferation and prevent unscheduled differentiation.

Towards personalized tumor markers

The cancer biomarker discovery pipeline is progressing slowly. The difficulties of finding novel and effective biomarkers for diagnosis and management of cancer patients are well-known. We speculate that it is unlikely to discover new serological biomarkers characterized by high sensitivity and specificity. This projection is supported by recent findings that cancers are genetically highly heterogeneous. Here, we propose a new way of improving the landscape of cancer biomarker research. There are currently hundreds, if not thousands, of described biomarkers which perform at high specificity (> 90%), but at relatively low sensitivity (< 30%). We call these “rare tumor markers.” Borrowing from the principles of precision medicine, we advocate that among these low sensitivity markers, some may be useful to specific patients. We suggest screening new patients for hundreds to thousands of cancer biomarkers to identify a few that are informative, and then use them clinically. This is similar to what we currently do with genomics to identify personalized therapies. We further suggest that this approach may explain as to why some biomarkers are elevated in only a small group of patients. It is likely that these differences in expression are linked to specific genomic alterations, which could then be found with genomic sequencing.

Methods, Tools and Current Perspectives in Proteogenomics

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications.

Mass spectrometry-based proteomic exploration of the human immune system: focus on the inflammasome, global protein secretion, and T cells

INTRODUCTION

The immune system is our defense system against microbial infections and tissue injury, and understanding how it works in detail is essential for developing drugs for different diseases. Mass spectrometry-based proteomics can provide in-depth information on the molecular mechanisms involved in immune responses. Areas covered: Summarized are the key immunology findings obtained with MS-based proteomics in the past five years, with a focus on inflammasome activation, global protein secretion, mucosal immunology, immunopeptidome and T cells. Special focus is on extracellular vesicle-mediated protein secretion and its role in immune responses. Expert commentary: Proteomics is an essential part of modern omics-scale immunology research. To date, MS-based proteomics has been used in immunology to study protein expression levels, their subcellular localization, secretion, post-translational modifications, and interactions in immune cells upon activation by different stimuli. These studies have made major contributions to understanding the molecular mechanisms involved in innate and adaptive immune responses. New developments in proteomics offer constantly novel possibilities for exploring the immune system. Examples of these techniques include mass cytometry and different MS-based imaging approaches which can be widely used in immunology.

Neprosin, a Selective Prolyl Endoprotease for Bottom-up Proteomics and Histone Mapping

Trypsin dominates bottom-up proteomics, but there are reasons to consider alternative enzymes. Improving sequence coverage, exposing proteomic "dark matter," and clustering post-translational modifications in different ways and with higher-order drive the pursuit of reagents complementary to trypsin. Additionally, enzymes that are easy to use and generate larger peptides that capitalize upon newer fragmentation technologies should have a place in proteomics. We expressed and characterized recombinant neprosin, a novel prolyl endoprotease of the DUF239 family, which preferentially cleaves C-terminal to proline residues under highly acidic conditions. Cleavage also occurs C-terminal to alanine with some frequency, but with an intriguingly high "skipping rate." Digestion proceeds to a stable end point, resulting in an average peptide mass of 2521 units and a higher dependence upon electron-transfer dissociation for peptide-spectrum matches. In contrast to most proline-cleaving enzymes, neprosin effectively degrades proteins of any size. For 1251 HeLa cell proteins identified in common using trypsin, Lys-C, and neprosin, almost 50% of the neprosin sequence contribution is unique. The high average peptide mass coupled with cleavage at residues not usually modified provide new opportunities for profiling clusters of post-translational modifications. We show that neprosin is a useful reagent for reading epigenetic marks on histones. It generates peptide 1-38 of histone H3 and peptide 1-32 of histone H4 in a single digest, permitting the analysis of co-occurring post-translational modifications in these important N-terminal tails.

Drug Resistance Mechanisms in Colorectal Cancer Dissected with Cell Type-Specific Dynamic Logic Models

Genomic features are used as biomarkers of sensitivity to kinase inhibitors used widely to treat human cancer, but effective patient stratification based on these principles remains limited in impact. Insofar as kinase inhibitors interfere with signaling dynamics, and, in turn, signaling dynamics affects inhibitor responses, we investigated associations in this study between cell-specific dynamic signaling pathways and drug sensitivity. Specifically, we measured 14 phosphoproteins under 43 different perturbed conditions (combinations of 5 stimuli and 7 inhibitors) in 14 colorectal cancer cell lines, building cell line-specific dynamic logic models of underlying signaling networks. Model parameters representing pathway dynamics were used as features to predict sensitivity to a panel of 27 drugs. Specific parameters of signaling dynamics correlated strongly with drug sensitivity for 14 of the drugs, 9 of which had no genomic biomarker. Following one of these associations, we validated a drug combination predicted to overcome resistance to MEK inhibitors by coblockade of GSK3, which was not found based on associations with genomic data. These results suggest that to better understand the cancer resistance and move toward personalized medicine, it is essential to consider signaling network dynamics that cannot be inferred from static genotypes. Cancer Res; 77(12); 3364-75. ©2017 AACR.

Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob).

SIGNIFICANCE

The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments.

Tissue-Specific Signaling Networks Rewired by Major Somatic Mutations in Human Cancer Revealed by Proteome-Wide Discovery

Massive somatic mutations discovered by large cancer genome sequencing projects provide unprecedented opportunities in the development of precision oncology. However, deep understanding of functional consequences of somatic mutations and identifying actionable mutations and the related drug responses currently remain formidable challenges. Dysfunction of protein posttranslational modification plays critical roles in tumorigenesis and drug responses. In this study, we proposed a novel computational oncoproteomics approach, named kinome-wide network module for cancer pharmacogenomics (KNMPx), for identifying actionable mutations that rewired signaling networks and further characterized tumorigenesis and anticancer drug responses. Specifically, we integrated 746,631 missense mutations in 4,997 tumor samples across 16 major cancer types/subtypes from The Cancer Genome Atlas into over 170,000 carefully curated nonredundant phosphorylation sites covering 18,610 proteins. We found 47 mutated proteins (e.g., ERBB2, TP53, and CTNNB1) that had enriched missense mutations at their phosphorylation sites in pan-cancer analysis. In addition, tissue-specific kinase-substrate interaction modules altered by somatic mutations identified by KNMPx were significantly associated with patient survival. We further reported a kinome-wide landscape of pharmacogenomic interactions by incorporating somatic mutation-rewired signaling networks in 1,001 cancer cell lines via KNMPx. Interestingly, we found that cell lines could highly reproduce oncogenic phosphorylation site mutations identified in primary tumors, supporting the confidence in their associations with sensitivity/resistance of inhibitors targeting EGF, MAPK, PI3K, mTOR, and Wnt signaling pathways. In summary, our KNMPx approach is powerful for identifying oncogenic alterations via rewiring phosphorylation-related signaling networks and drug sensitivity/resistance in the era of precision oncology. Cancer Res; 77(11); 2810-21. ©2017 AACR.

Ultrastable Artificial Binding Pairs as a Supramolecular Latching System: A Next Generation Chemical Tool for Proteomics

In this Commentary, we discuss cucurbit[7]uril-based ultrastable artificial binding pairs as a supramolecular latching system and how we envision this becoming important tools in proteomics. The limitations of current proteomic techniques are described with an emphasis on the lack of tools to answer questions about the complex and dynamic nature of the proteome. Our thoughts as to how artificial ultrastable binding pairs may be able to address these questions are given especially when they are combined with existing methods.

Advances in mass spectrometry based strategies to study receptor tyrosine kinases

Receptor tyrosine kinases (RTKs) are key transmembrane environmental sensors that are capable of transmitting extracellular information into phenotypic responses, including cell proliferation, survival and metabolism. Advances in mass spectrometry (MS)-based phosphoproteomics have been instrumental in providing the foundations of much of our current understanding of RTK signalling networks and activation dynamics. Furthermore, new insights relating to the deregulation of RTKs in disease, for instance receptor co-activation and kinome reprogramming, have largely been identified using phosphoproteomic-based strategies. This review outlines the current approaches employed in phosphoproteomic workflows, including phosphopeptide enrichment and MS data-acquisition methods. Here, recent advances in the application of MS-based phosphoproteomics to bridge critical gaps in our knowledge of RTK signalling are focused on. The current limitations of the technology are discussed and emerging areas such as computational modelling, high-throughput phospho-proteomic workflows and next-generation single-cell approaches to further our understanding in new areas of RTK biology are highlighted.

Technologies for Proteome-Wide Discovery of Extracellular Host-Pathogen Interactions

Pathogens have evolved unique mechanisms to breach the cell surface barrier and manipulate the host immune response to establish a productive infection. Proteins exposed to the extracellular environment, both cell surface-expressed receptors and secreted proteins, are essential targets for initial invasion and play key roles in pathogen recognition and subsequent immunoregulatory processes. The identification of the host and pathogen extracellular molecules and their interaction networks is fundamental to understanding tissue tropism and pathogenesis and to inform the development of therapeutic strategies. Nevertheless, the characterization of the proteins that function in the host-pathogen interface has been challenging, largely due to the technical challenges associated with detection of extracellular protein interactions. This review discusses available technologies for the high throughput study of extracellular protein interactions between pathogens and their hosts, with a focus on mammalian viruses and bacteria. Emerging work illustrates a rich landscape for extracellular host-pathogen interaction and points towards the evolution of multifunctional pathogen-encoded proteins. Further development and application of technologies for genome-wide identification of extracellular protein interactions will be important in deciphering functional host-pathogen interaction networks, laying the foundation for development of novel therapeutics.

Extensive Peptide Fractionation and y1 Ion-Based Interference Detection Method for Enabling Accurate Quantification by Isobaric Labeling and Mass Spectrometry

Isobaric labeling quantification by mass spectrometry (MS) has emerged as a powerful technology for multiplexed large-scale protein profiling, but measurement accuracy in complex mixtures is confounded by the interference from coisolated ions, resulting in ratio compression. Here we report that the ratio compression can be essentially resolved by the combination of pre-MS peptide fractionation, MS2-based interference detection, and post-MS computational interference correction. To recapitulate the complexity of biological samples, we pooled tandem mass tag (TMT)-labeled Escherichia coli peptides at 1:3:10 ratios and added in ∼20-fold more rat peptides as background, followed by the analysis of two-dimensional liquid chromatography (LC)-MS/MS. Systematic investigation shows that quantitative interference was impacted by LC fractionation depth, MS isolation window, and peptide loading amount. Exhaustive fractionation (320 × 4 h) can nearly eliminate the interference and achieve results comparable to the MS3-based method. Importantly, the interference in MS2 scans can be estimated by the intensity of contaminated y₁ product ions, and we thus developed an algorithm to correct reporter ion ratios of tryptic peptides. Our data indicate that intermediate fractionation (40 × 2 h) and y₁ ion-based correction allow accurate and deep TMT profiling of more than 10 000 proteins, which represents a straightforward and affordable strategy in isobaric labeling proteomics.

In Vivo and in Vitro Proteome Analysis of Human Immunodeficiency Virus (HIV)-1-infected, Human CD4+ T Cells

Host-directed therapies against HIV-1 are thought to be critical for long term containment of the HIV-1 pandemic but remain elusive. Because HIV-1 infects and manipulates important effectors of both the innate and adaptive immune system, identifying modulations of the host cell systems in humans during HIV-1 infection may be crucial for the development of immune based therapies. Here, we quantified the changes of the proteome in human CD4⁺ T cells upon HIV-1 infection, both in vitro and in vivo A SWATH-MS approach was used to measure the proteome of human primary CD4⁺ T cells infected with HIV-1 in vitro as well as CD4⁺ T cells from HIV-1-infected patients with paired samples on and off antiretroviral treatment. In the in vitro experiment, the proteome of CD4⁺ T cells was quantified over a time course following HIV-1 infection. 1,725 host cell proteins and 4 HIV-1 proteins were quantified, with 145 proteins changing significantly during the time course. Changes in the proteome peaked 24 h after infection, concomitantly with significant HIV-1 protein production. In the in vivo branch of the study, CD4⁺ T cells from viremic patients and those with no detectable viral load after treatment were sorted, and the proteomes were quantified. We consistently detected 895 proteins, 172 of which were considered to be significantly different between the viremic patients and patients undergoing successful treatment. The proteome of the in vitro-infected CD4⁺ T cells was modulated on multiple functional levels, including TLR-4 signaling and the type 1 interferon signaling pathway. Perturbations in the type 1 interferon signaling pathway were recapitulated in CD4⁺ T cells from patients. The study shows that proteome maps generated by SWATH-MS indicate a range of functionally significant changes in the proteome of HIV-infected human CD4⁺ T cells. Exploring these perturbations in more detail may help identify new targets for immune based interventions.

Proteomics Tracing the Footsteps of Infectious Disease

Every year, a major cause of human disease and death worldwide is infection with the various pathogens-viruses, bacteria, fungi, and protozoa-that are intrinsic to our ecosystem. In efforts to control the prevalence of infectious disease and develop improved therapies, the scientific community has focused on building a molecular picture of pathogen infection and spread. These studies have been aimed at defining the cellular mechanisms that allow pathogen entry into hosts cells, their replication and transmission, as well as the core mechanisms of host defense against pathogens. The past two decades have demonstrated the valuable implementation of proteomic methods in all these areas of infectious disease research. Here, we provide a perspective on the contributions of mass spectrometry and other proteomics approaches to understanding the molecular details of pathogen infection. Specifically, we highlight methods used for defining the composition of viral and bacterial pathogens and the dynamic interaction with their hosts in space and time. We discuss the promise of MS-based proteomics in supporting the development of diagnostics and therapies, and the growing need for multiomics strategies for gaining a systems view of pathogen infection.

Deep-proteome mapping of WM-266-4 human metastatic melanoma cells: From oncogenic addiction to druggable targets

Cutaneous melanoma is a malignant tumor of skin melanocytes that are pigment-producing cells located in the basal layer (stratum basale) of epidermis. Accumulation of genetic mutations within their oncogenes or tumor-suppressor genes compels melanocytes to aberrant proliferation and spread to distant organs of the body, thereby resulting in severe and/or lethal malignancy. Metastatic melanoma's heavy mutational load, molecular heterogeneity and resistance to therapy necessitate the development of novel biomarkers and drug-based protocols that target key proteins involved in perpetuation of the disease. To this direction, we have herein employed a nano liquid chromatography-tandem mass spectrometry (nLC-MS/MS) proteomics technology to profile the deep-proteome landscape of WM-266-4 human metastatic melanoma cells. Our advanced melanoma-specific catalogue proved to contain 6,681 unique proteins, which likely constitute the hitherto largest single cell-line-derived proteomic collection of the disease. Through engagement of UNIPROT, DAVID, KEGG, PANTHER, INTACT, CYTOSCAPE, dbEMT and GAD bioinformatics resources, WM-266-4 melanoma proteins were categorized according to their sub-cellular compartmentalization, function and tumorigenicity, and successfully reassembled in molecular networks and interactomes. The obtained data dictate the presence of plastically inter-converted sub-populations of non-cancer and cancer stem cells, and also indicate the oncoproteomic resemblance of melanoma to glioma and lung cancer. Intriguingly, WM-266-4 cells seem to be subjected to both epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial (MET) programs, with 1433G and ADT3 proteins being identified in the EMT/MET molecular interface. Oncogenic addiction of WM-266-4 cells to autocrine/paracrine signaling of IL17-, DLL3-, FGF(2/13)- and OSTP-dependent sub-routines suggests their critical contribution to the metastatic melanoma chemotherapeutic refractoriness. Interestingly, the 1433G family member that is shared between the BRAF- and EMT/MET-specific interactomes likely emerges as a novel and promising druggable target for the malignancy. Derailed proliferation and metastatic capacity of WM-266-4 cells could also derive from their metabolic addiction to pathways associated with glutamate/ammonia, propanoate and sulfur homeostasis, whose successful targeting may prove beneficial for advanced melanoma-affected patients.

Applying proteomics to tick vaccine development: where are we?

INTRODUCTION

Ticks are second to mosquitoes as a vector of human diseases and are the first vector of animal diseases with a great impact on livestock farming. Tick vaccines represent a sustainable and effective alternative to chemical acaricides for the control of tick infestations and transmitted pathogens. The application of proteomics to tick vaccine development is a fairly recent area, which has resulted in the characterization of some tick-host-pathogen interactions and the identification of candidate protective antigens. Areas covered: In this article, we review the application and possibilities of various proteomic approaches for the discovery of tick and pathogen derived protective antigens, and the design of effective vaccines for the control of tick infestations and pathogen infection and transmission. Expert commentary: In the near future, the application of reverse proteomics, immunoproteomics, structural proteomics, and interactomics among other proteomics approaches will likely contribute to improve vaccine design to control multiple tick species with the ultimate goal of controlling tick-borne diseases.

Loss-less Nano-fractionator for High Sensitivity, High Coverage Proteomics

Recent advances in mass spectrometry (MS)-based proteomics now allow very deep coverage of cellular proteomes. To achieve near-comprehensive identification and quantification, the combination of a first HPLC-based peptide fractionation orthogonal to the on-line LC-MS/MS step has proven to be particularly powerful. This first dimension is typically performed with milliliter/min flow and relatively large column inner diameters, which allow efficient pre-fractionation but typically require peptide amounts in the milligram range. Here, we describe a novel approach termed "spider fractionator" in which the post-column flow of a nanobore chromatography system enters an eight-port flow-selector rotor valve. The valve switches the flow into different flow channels at constant time intervals, such as every 90 s. Each flow channel collects the fractions into autosampler vials of the LC-MS/MS system. Employing a freely configurable collection mechanism, samples are concatenated in a loss-less manner into 2-96 fractions, with efficient peak separation. The combination of eight fractions with 100 min gradients yields very deep coverage at reasonable measurement time, and other parameters can be chosen for even more rapid or for extremely deep measurements. We demonstrate excellent sensitivity by decreasing sample amounts from 100 μg into the sub-microgram range, without losses attributable to the spider fractionator and while quantifying close to 10,000 proteins. Finally, we apply the system to the rapid automated and in-depth characterization of 12 different human cell lines to a median depth of 11,472 different proteins, which revealed differences recapitulating their developmental origin and differentiation status. The fractionation technology described here is flexible, easy to use, and facilitates comprehensive proteome characterization with minimal sample requirements.

Open-pNovo: De Novo Peptide Sequencing with Thousands of Protein Modifications

De novo peptide sequencing has improved remarkably, but sequencing full-length peptides with unexpected modifications is still a challenging problem. Here we present an open de novo sequencing tool, Open-pNovo, for de novo sequencing of peptides with arbitrary types of modifications. Although the search space increases by ∼300 times, Open-pNovo is close to or even ∼10-times faster than the other three proposed algorithms. Furthermore, considering top-1 candidates on three MS/MS data sets, Open-pNovo can recall over 90% of the results obtained by any one traditional algorithm and report 5-87% more peptides, including 14-250% more modified peptides. On a high-quality simulated data set, ∼85% peptides with arbitrary modifications can be recalled by Open-pNovo, while hardly any results can be recalled by others. In summary, Open-pNovo is an excellent tool for open de novo sequencing and has great potential for discovering unexpected modifications in the real biological applications.

Cell-selective proteomics for biological discovery

Cells alter the proteome to respond to environmental and developmental cues. Global analysis of proteomic responses is of limited value in heterogeneous environments, where there is no 'average' cell. Advances in sequencing, protein labeling, mass spectrometry, and data analysis have fueled recent progress in the investigation of specific subpopulations of cells in complex systems. Here we highlight recently developed chemical tools that enable cell-selective proteomic analysis of complex biological systems, from bacterial pathogens to whole animals.

System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects

Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

Enriching the Circadian Proteome

Circadian clocks regulate most aspects of physiology and metabolism. Genome-wide approaches have uncovered widespread circadian rhythms in the transcriptome, cistrome, and epigenome of mice, and now two proteomics studies in this issue (Robles et al., 2016; Wang et al., 2016) reveal extensive circadian regulation of the nuclear and phosphoproteome.

Variations of Histone Modification Patterns: Contributions of Inter-plant Variability and Technical Factors

Inter-individual variability of conspecific plants is governed by differences in their genetically determined growth and development traits, environmental conditions, and adaptive responses under epigenetic control involving histone post-translational modifications. The apparent variability in histone modifications among plants might be increased by technical variation introduced in sample processing during epigenetic analyses. Thus, to detect true variations in epigenetic histone patterns associated with given factors, the basal variability among samples that is not associated with them must be estimated. To improve knowledge of relative contribution of biological and technical variation, mass spectrometry was used to examine histone modification patterns (acetylation and methylation) among Arabidopsis thaliana plants of ecotypes Columbia 0 (Col-0) and Wassilewskija (Ws) homogenized by two techniques (grinding in a cryomill or with a mortar and pestle). We found little difference in histone modification profiles between the ecotypes. However, in comparison of the biological and technical components of variability, we found consistently higher inter-individual variability in histone mark levels among Ws plants than among Col-0 plants (grown from seeds collected either from single plants or sets of plants). Thus, more replicates of Ws would be needed for rigorous analysis of epigenetic marks. Regarding technical variability, the cryomill introduced detectably more heterogeneity in the data than the mortar and pestle treatment, but mass spectrometric analyses had minor apparent effects. Our study shows that it is essential to consider inter-sample variance and estimate suitable numbers of biological replicates for statistical analysis for each studied organism when investigating changes in epigenetic histone profiles.

Target and identify: triazene linker helps identify azidation sites of labelled proteins via click and cleave strategy

A method for identifying probe modification of proteinsviatandem mass spectrometry was developed.

High-Throughput Parallel Proteomic Sample Preparation Using 96-Well Polyvinylidene Fluoride (PVDF) Membranes and C18 Purification Plates

Meaningful proteomic-based biomarker discovery projects using primary human-derived specimens require the analysis of hundreds of samples in order to address the issue of interpersonal variability. Thus, robust high-throughput methods for the digestion of plasma samples are a prerequisite for such large clinical proteomic studies with hundreds of samples. Commonly used sample preparation methods are often difficult to parallelize and/or automate. Herein we describe a method for parallel 96-well plate-based sample preparation. Protein digestion is performed in 96-well polyvinylidene fluoride (PVDF) membrane plates and the subsequent purification in 96-well reversed phase C18 purification plates, enabling the usage of multichannel pipettes in all steps. The protocol can be applied using neat or depleted plasma/serum samples, but has also proven effective with other sample types.

Deep Phosphoproteomic Measurements Pinpointing Drug Induced Protective Mechanisms in Neuronal Cells

Alzheimer's disease (AD) is a progressive and irreversible neurological disorder that impairs the living quality of old population and even life spans. New compounds have shown potential inneuroprotective effects in AD, such as GFKP-19, a 2-pyrrolidone derivative which has been proved to enhance the memory of dysmnesia mouse. The molecular mechanisms remain to be established for these drug candidates. Large-scale phosphoproteomic approach has been evolved rapidly in the last several years, which holds the potential to provide a useful toolkit to understand cellular signaling underlying drug effects. To establish and test such a method, we accurately analyzed the deep quantitative phosphoproteome of the neuro-2a cells treated with and without GFKP-19 using triple SILAC labeling. A total of 14,761 Class I phosphosites were quantified between controls, damaged, and protected conditions using the high resolution mass spectrometry, with a decent inter-mass spectrometer reproducibility for even subtle regulatory events. Our data suggests that GFKP-19 can reverse Aβ₂₅₋₃₅ induced phosphorylation change in neuro-2a cells, and might protect the neuron system in two ways: firstly, it may decrease oxidative damage and inflammation induced by NO via down regulating the phosphorylation of nitric oxide synthase NOS1 at S847; Secondly, it may decrease tau protein phosphorylation through down-regulating the phosphorylation level of MAPK14 at T180. All mass spectrometry data are available via ProteomeXchange with identifier PXD005312.

Digestomics: an emerging strategy for comprehensive analysis of protein catabolism

When cells mobilize nutrients from protein, they generate a fingerprint of peptide fragments that reflects the net action of proteases and the identities of the affected proteins. Analyzing these mixtures falls into a grey area between proteomics and metabolomics that is poorly served by existing technology. Herein, we describe an emerging digestomics strategy that bridges this gap and allows mixtures of proteolytic fragments to be quantitatively mapped with an amino acid level of resolution. We describe recent successes using this technique, including a case where digestomics provided the link between hemoglobin digestion by the malaria parasite and the world-wide distribution of chloroquine resistance. We highlight other areas of microbiology and cancer research that are well-suited to this emerging technology.

Proteomics reveals the effects of sustained weight loss on the human plasma proteome

Sustained weight loss is a preferred intervention in a wide range of metabolic conditions, but the effects on an individual's health state remain ill‐defined. Here, we investigate the plasma proteomes of a cohort of 43 obese individuals that had undergone 8 weeks of 12% body weight loss followed by a year of weight maintenance. Using mass spectrometry‐based plasma proteome profiling, we measured 1,294 plasma proteomes. Longitudinal monitoring of the cohort revealed individual‐specific protein levels with wide‐ranging effects of losing weight on the plasma proteome reflected in 93 significantly affected proteins. The adipocyte‐secreted SERPINF1 and apolipoprotein APOF1 were most significantly regulated with fold changes of −16% and +37%, respectively (P < 10⁻¹³), and the entire apolipoprotein family showed characteristic differential regulation. Clinical laboratory parameters are reflected in the plasma proteome, and eight plasma proteins correlated better with insulin resistance than the known marker adiponectin. Nearly all study participants benefited from weight loss regarding a ten‐protein inflammation panel defined from the proteomics data. We conclude that plasma proteome profiling broadly evaluates and monitors intervention in metabolic diseases.

Evaluation of inflammation-related signaling events covering phosphorylation and nuclear translocation of proteins based on mass spectrometry data

Peripheral blood mononuclear cells are important players in immune regulation relying on a complex network of signaling pathways. In this study, we evaluated the power of label-free quantitative shotgun proteomics regarding the comprehensive characterization of signaling pathways in such primary cells by studying regulation of protein abundance, post-translational modifications and nuclear translocation events. The effects of inflammatory stimulation and the treatment of stimulated cells with dexamethasone were investigated. Therefore, a previously published dataset accessible via ProteomeXchange consisting of 6901 identified protein groups was re-evaluated. These data enabled us to comprehensively map the c-JUN, ERK5 and NF-κB signaling cascade in a semi-quantitative fashion. Without the application of any enrichment, 3775 highly confident phosphopeptides derived from 1249 proteins including 66 kinases were identified. Efficient subcellular fractionation and subsequent comparative analysis identified previously unrecognized inflammation-associated nuclear translocation events of proteins such as histone-modifying proteins, zinc finger proteins as well as transcription factors. Profound effects of inflammatory stimulation and dexamethasone treatment on histone H3 and ZFP161 localization represent novel findings and were verified by immunofluorescence. In conclusion, we demonstrate that multiple regulatory events resulting from the activity of signaling pathways can be determined out of untargeted shotgun proteomics data.

SIGNIFICANCE

Relevant functional events such as phosphorylation and nuclear translocation of proteins were extracted from high-resolution mass spectrometry data and provided additional biological information contained in shotgun proteomics data.

Turning Over Paradigms in Protein Decay

Protein degradation is as important as synthesis in regulating protein expression, but protein degradation kinetics are relatively less understood. In a recent paper in Cell, McShane et al. (2016) use a novel methodology to demonstrate that many proteins decay non-exponentially, with biological implications for proteins in heteromeric complexes and in aneuploidy.