30 April 2020

1 May 2020

1 May 2020

6 May 2020

Ankylosing Spondylitis (AS) is a common, inflammatory rheumatic disease, which primarily affects the axial skeleton and is associated with sacroiliitis, uveitis and enthesitis. Unlike other autoimmune rheumatic diseases, such as rheumatoid arthritis or systemic lupus erythematosus, autoantibodies have not yet been reported to be a feature of AS. We therefore wished to determine if plasma from patients with AS contained autoantibodies and if so, characterize and quantify this response in comparison to patients with Rheumatoid Arthritis (RA) and healthy controls. Two high-density nucleic acid programmable protein arrays expressing a total of 3498 proteins were screened with plasma from 25 patients with AS, 17 with RA and 25 healthy controls. Autoantigens identified were subjected to Ingenuity Pathway Analysis in order to determine patterns of signalling cascades or tissue origin. 44% of patients with Ankylosing Spondylitis demonstrated a broad autoantibody response, as compared to 33% of patients with RA and only 8% of healthy controls. Individuals with AS demonstrated autoantibody responses to shared autoantigens, and 60% of autoantigens identified in the AS cohort were restricted to that group. The AS patients autoantibody responses were targeted towards connective, skeletal and muscular tissue, unlike those of RA patients or healthy controls. Thus, patients with AS show evidence of systemic humoral autoimmunity and multispecific autoantibody production. Nucleic Acid Programmable Protein Arrays constitute a powerful tool to study autoimmune diseases.

Colorectal cancer (CRC) arises as the consequence of progressive changes from normal epithelial cells through polyp to tumor, and thus is an useful model for studying metabolic shift. In the present study, we studied the metabolomic profiles using high analyte specific gas chromatography/mass spectrometry (GC/MS) and liquid chromatography tandem mass spectrometry (LC/MS/MS) to attain a systems-level view of the shift in metabolism in cells progressing along the path to CRC. Colonic tissues including tumor, polyps and adjacent matched normal mucosa from 26 patients with sporadic CRC from freshly isolated resections were used for this study. The metabolic profiles were obtained using GC/MS and LC/MS/MS. Our data suggest there was a distinct profile change of a wide range of metabolites from mucosa to tumor tissues. Various amino acids and lipids in the polyps and tumors were elevated, suggesting higher energy needs for increased cellular proliferation. In contrast, significant depletion of glucose and inositol in polyps revealed that glycolysis may be critical in early tumorigenesis. In addition, the accumulation of hypoxanthine and xanthine, and the decrease of uric acid concentration, suggest that the purine biosynthesis pathway could have been substituted by the salvage pathway in CRC. Further, there was a step-wise reduction of deoxycholic acid concentration from mucosa to tumors. It appears that to gain a growth advantage, cancer cells may adopt alternate metabolic pathways in tumorigenesis and this flexibility allows them to adapt and thrive in harsh environment.

In quantitative proteomics work, the differences in expression of many separate proteins are routinely examined to test for significant differences between treatments. This leads to the multiple hypothesis testing problem: when many separate tests are performed many will be significant by chance and be false positive results. Statistical methods such as the false discovery rate (FDR) method that deal with this problem have been disseminated for more than one decade. However a survey of proteomics journals shows that such tests are not widely implemented in one commonly used technique, quantitative proteomics using two-dimensional electrophoresis (2-DE). We outline a selection of multiple hypothesis testing methods, including some that are well known and some lesser known, and present a simple strategy for their use by the experimental scientist in quantitative proteomics work generally. The strategy focuses on the desirability of simultaneous use of several different methods, the choice and emphasis dependent on research priorities and the results in hand. This approach is demonstrated using case scenarios with experimental and simulated model data.

Oxidative stress has been implicated in aging and many human diseases, notably neurodegenerative disorders and various cancers. The reactive oxygen species that are generated by aerobic metabolism and environmental stressors can chemically modify proteins and alter their biological functions. Cells possess protein repair pathways to rescue oxidized proteins and restore their functions. If these repair processes fail, oxidized proteins may become cytotoxic. Cell homeostasis and viability are therefore dependent on the removal of oxidatively damaged proteins. Numerous studies have demonstrated that the proteasome plays a pivotal role in the selective recognition and degradation of oxidized proteins. Despite extensive research, oxidative stress-triggered regulation of proteasome complexes remains poorly defined. Better understanding of molecular mechanisms underlying proteasome function in response to oxidative stress will provide a basis for developing new strategies aimed at improving cell viability and recovery as well as attenuating oxidation-induced cytotoxicity associated with aging and disease. Here we highlight recent advances in the understanding of proteasome structure and function during oxidative stress and describe how cells cope with oxidative stress through proteasome-dependent degradation pathways.

Cover art by Julie Newdoll for MCP April issue.

After successful completion of the Human Genome Project (HGP), HUPO has recently officially launched a global Human Proteome Project (HPP) which is designed to map the entire human protein set. Given the presence of about 30% undisclosed proteins out of 20,300 protein gene products, a systematic global effort is necessary to achieve this goal with respect to protein abundance, distribution, subcellular localization, interaction with other biomolecules, and functions at specific time points. As a general experimental strategy, HPP groups employ the three working pillars for HPP: mass spectrometry, antibody capture, and bioinformatics tools and knowledge base. The HPP participants will take advantage of the output and cross-analyses from the ongoing HUPO initiatives and a chromosome-based protein mapping strategy, termed C-HPP with many national teams currently engaged. In addition, numerous biologically-driven projects will be stimulated and facilitated by the HPP. Timely planning with proper governance of HPP will deliver a protein parts list, reagents and tools for protein studies and analyses, and a stronger basis for personalized medicine. HUPO urges each national research funding agency and the scientific community at large to identify their preferred pathways to participate in aspects of this highly promising project in a HPP consortium of funders and investigators.

This article provides an introduction to Fourier transform-based mass spectrometry (FTMS). The key performance characteristics of FTMS, mass accuracy and resolution, are presented in the view of how they impact the interpretation of measurements in proteomic applications. The theory and principles of operation of two types of mass analyzer, Fourier transform ion cyclotron resonance and Orbitrap, are described. Major benefits as well as limitations of FTMS technology are discussed in the context of practical sample analysis, and illustrated with examples included as figures in this text and in the accompanying slide set. Comparisons highlighting the performance differences between the two mass analyzers are made where deemed useful in assisting the user with choosing the most appropriate technology for his/her application. Recent developments of these high-performing mass spectrometers are mentioned to provide a future outlook.

Electrospray ionization is today the most widely used ionization technique in chemical and bio-chemical analysis. Interfaced with a mass spectrometer it allows to investigate the molecular composition of liquid samples. With electrospray a large variety of chemical substances can be ionized. There is no limitation in mass which enables even the investigation of large non-covalent protein complexes. Its high ionization efficiency profoundly changed bio-molecular sciences because proteins can be identified and quantified on trace amounts in a high throughput fashion. This review article focusses mainly on the exploration of the underlying ionization mechanism. Some ionization characteristics are discussed which are related to this mechanism. Typical spectra of peptides, proteins and non-covalent complexes are shown and the quantitative character of spectra is highlighted. Finally the possibilities and limitations in measuring the association constant of bivalent non-covalent complexes are described.

The development of the HUPO-PSI's (Proteomics Standards Initiative) standard data formats and MIAPE (Minimum Information About a Proteomics Experiment) guidelines should improve proteomics data sharing within the scientific community. Proteomics journals have encouraged the use of these standards and guidelines to improve the quality of experimental reporting and ease the evaluation and publication of manuscripts. However, there is an evident lack of bioinformatics tools specifically designed to create and edit standard file formats and reports, or embed them within proteomics workflows. In this article, we describe a new web-based software suite (The ProteoRed MIAPE web toolkit) that performs several complementary roles related to proteomic data standards. Firstly, it can verify the reports fulfill the minimum information requirements of the corresponding MIAPE modules, highlighting inconsistencies or missing information. Secondly, the toolkit can convert several XML-based data standards directly into human readable MIAPE reports stored within the ProteoRed MIAPE repository. Finally, it can also perform the reverse operation, allowing users to export from MIAPE reports into XML files for computational processing, data sharing or public database submission. The toolkit is thus the first application capable of automatically linking the PSI's MIAPE modules with the corresponding XML data exchange standards, enabling bidirectional conversions. This toolkit is freely available at http://www.proteored.org/MIAPE/.

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.

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Protein tyrosine kinases (PTKs) play key roles in cellular signal transduction, cell cycle regulation, cell division, and cell differentiation. Dysregulation of PTK-activated pathways, often by receptor overexpression, gene amplification, or genetic mutation, is a causal factor underlying numerous cancers. In this study, we have developed a parallel reaction monitoring (PRM)-based assay for quantitative profiling of 83 PTKs. The assay detects 308 proteotypic peptides from 54 receptor tyrosine kinases and 29 nonreceptor tyrosine kinases in a single run. Quantitative comparisons were based on the labeled reference peptide method. We implemented the assay in four cell models: 1) a comparison of proliferating versus epidermal growth factor (EGF)-stimulated A431 cells, 2) a comparison of SW480Null (mutant APC) and SW480APC (APC restored) colon tumor cell lines, and 3) a comparison of 10 colorectal cancer cell lines with different genomic abnormalities, and 4) lung cancer cell lines with either susceptibility (11-18) or acquired resistance (11-18R) to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib. We observed distinct PTK expression changes that were induced by stimuli, genomic features or drug resistance, which were consistent with previous reports. However, most of the measured expression differences were novel observations. For example, acquired resistance to erlotinib in the 11-18 cell model was associated not only with previously reported upregulation of MET, but also with upregulation of FLK2 and downregulation of LYN and PTK7. Immunoblot analyses and shotgun proteomics data were highly consistent with PRM data. Multiplexed PRM assays provide a targeted, systems-level profiling approach to evaluate cancer-related proteotypes and adaptations. Data are available through Proteome eXchange Accession PXD002706.

This article has been withdrawn by the authors. We discovered an error after this manuscript was published as a Paper in Press. Specifically, we learned that the structures of glycans presented for the PD-L1 peptide were drawn and labeled incorrectly. We wish to withdraw this article and submit a corrected version for review.

The histidine kinase Hik33 plays important roles in mediating cyanobacterial response to divergent types of abiotic stresses including cold, salt, high light (HL), and osmotic stresses. However, how these functions are regulated by Hik33 remains to be addressed. Using a hik33-deficient strain (hik33) of Synechocystis sp. PCC 6803 (Synechocystis) and quantitative proteomics, we found that Hik33 depletion induces differential protein expression highly similar to that induced by divergent types of stresses. This typically includes downregulation of proteins in photosynthesis and carbon assimilation that are necessary for cell propagation, and upregulation of heat shock proteins, chaperons, and proteases that are important for cell survival. This observation indicates that depletion of Hik33 alone mimics divergent types of abiotic stresses, and that Hik33 could be important for preventing abnormal stress response in the normal condition. Moreover, we found the majority of proteins of plasmid origin were significantly upregulated in hik33, though their biological significance remains to be addressed. Together, the systematically characterized Hik33-regulated cyanobacterial proteome, which is largely involved in stress responses, builds the molecular basis for Hik33 as a general regulator of stress responses.

This article has been withdrawn by the authors. This article did not comply with the editorial guidelines of MCP. Specifically, single peptide based protein identifications of 9-19% were included in the analysis and discussed in the results and conclusions. We wish to withdraw this article and resubmit a clarified, corrected manuscript for review.

Ion mobility can add a dimension to LC-MS based shotgun proteomics which has the potential to boost proteome coverage, quantification accuracy and dynamic range.  Required for this is suitable software that extracts the information contained in the four-dimensional (4D) data space spanned by m/z, retention time, ion mobility and signal intensity. Here we describe the ion mobility enhanced MaxQuant software, which utilizes the added data dimension. It offers an end to end computational workflow for the identification and quantification of peptides and proteins in LC-IMS-MS/MS shotgun proteomics data. We apply it to trapped ion mobility spectrometry (TIMS) coupled to a quadrupole time-of-flight (QTOF) analyzer. A highly parallelizable 4D feature detection algorithm extracts peaks which are assembled to isotope patterns. Masses are recalibrated with a non-linear m/z, retention time, ion mobility and signal intensity dependent model, based on peptides from the sample. A new matching between runs (MBR) algorithm that utilizes collisional cross section (CCS) values of MS1 features in the matching process significantly gains specificity from the extra dimension. Prerequisite for using CCS values in MBR is a relative alignment of the ion mobility values between the runs. The missing value problem in protein quantification over many samples is greatly reduced by CCS aware MBR.MS1 level label-free quantification is also implemented which proves to be highly precise and accurate on a benchmark dataset with known ground truth. MaxQuant for LC-IMS-MS/MS is part of the basic MaxQuant release and can be downloaded from http://maxquant.org.

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t-test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all datasets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several datasets including E.coli proteome spike-in data, using both label-free and TMT-labelled quantification. In comparison to previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared to other statistical methods in both label-free and labelled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.

In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein (e.g., precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined. We propose a statistical approach that automatically detects spectral features with such inconsistent patterns. The detected features can be separately investigated, and if necessary removed from the dataset. We evaluated the proposed approach on a series of benchmark controlled mixtures and biological investigations with DDA, DIA and SRM data acquisitions. The results demonstrated that it can facilitate and complement manual curation of the data. Moreover, it can improve the estimation accuracy, sensitivity and specificity of detecting differentially abundant proteins, and reproducibility of conclusions across different data processing tools. The approach is implemented as an option in the open-source R-based software MSstats.

Drug resistance is a major obstacle to curative cancer therapies, and increased understanding of the molecular events contributing to resistance would enable better prediction of therapy response, as well as contribute to new targets for combination therapy. Here we have analyzed the early molecular response to epidermal growth factor receptor (EGFR) inhibition using RNA sequencing data covering 13 486 genes and mass spectrometry data covering 10 138 proteins. This analysis revealed a massive response to EGFR inhibition already within the first 24 hours, including significant regulation of hundreds of genes known to control downstream signaling, such as transcription factors, kinases, phosphatases and ubiquitin E3-ligases. Importantly, this response included upregulation of key genes in multiple oncogenic signaling pathways that promote proliferation and survival, such as ERBB3, FGFR2, JAK3 and BCL6, indicating an early adaptive response to EGFR inhibition. Using a library of more than 500 approved and experimental compounds in a combination therapy screen, we could show that several kinase inhibitors with targets including JAK3 and FGFR2 increased the response to EGFR inhibitors. Further, we investigated the functional impact of BCL6 upregulation in response to EGFR inhibition using siRNA-based silencing of BCL6. Proteomics profiling revealed that BCL6 inhibited transcription of multiple target genes including p53, resulting in reduced apoptosis which implicates BCL6 upregulation as a new EGFR inhibitor treatment escape mechanism. Finally, we demonstrate that combined treatment targeting both EGFR and BCL6 act synergistically in killing lung cancer cells. In conclusion, or data indicates that multiple different adaptive mechanisms may act in concert to blunt the cellular impact of EGFR inhibition, and we suggest BCL6 as a potential target for EGFR inhibitor-based combination therapy.

Stimulating brown adipose tissue (BAT) activity represents a promising therapy for overcoming metabolic diseases. mTORC2 is important for regulating BAT metabolism, but its downstream targets have not been fully characterized. In this study, we apply proteomics and phosphoproteomics to investigate the downstream effectors of mTORC2 in brown adipocytes. We compare wild-type controls to isogenic cells with an induced knockout of the mTORC2 subunit RICTOR (Rictor-iKO) by stimulating each with insulin for a 30-minute time course. In Rictor-iKO cells, we identify decreases to the abundance of glycolytic and de novo lipogenesis enzymes, and increases to mitochondrial proteins as well as a set of proteins known to increase upon interferon stimulation. We also observe significant differences to basal phosphorylation due to chronic RICTOR loss including decreased phosphorylation of the lipid droplet protein perilipin-1 in Rictor-iKO cells, suggesting that RICTOR could be involved with regulating basal lipolysis or droplet dynamics. Finally, we observe mild dampening of acute insulin signaling response in Rictor-iKO cells, and a subset of AKT substrates exhibiting statistically significant dependence on RICTOR.

Glioblastoma (GBM) is one of the most aggressive human cancers with a median survival of less than two years. A distinguishing pathological feature of GBM is a high degree of inter- and intratumoral heterogeneity. Intertumoral heterogeneity of GBM has been extensively investigated on genomic, methylomic, transcriptomic, proteomic and metabolomics levels, however only a few studies describe intratumoral heterogeneity due to the lack of methods allowing to analyze GBM samples with high spatial resolution. Here, we applied TOF-SIMS (Time-of-flight secondary ion mass spectrometry) for the analysis of single cells and clinical samples such as paraffin and frozen tumor sections obtained from 57 patients. We developed a technique that allows us to simultaneously detect the distribution of proteins and metabolites in glioma tissue with 800 nm spatial resolution. Our results demonstrate that according to TOF-SIMS data glioma samples can be subdivided into clinically relevant groups and distinguished from the normal brain tissue. In addition, TOF-SIMS was able to elucidate differences between morphologically distinct regions of GBM within the same tumor. By staining GBM sections with gold-conjugated antibodies against Caveolin-1 we could visualize border between zones of necrotic and cellular tumor and subdivide glioma samples into groups characterized by different survival of the patients. Finally, we demonstrated that GBM contains cells that are characterized by high levels of Caveolin-1 protein and cholesterol. This population may partly represent a glioma stem cells. Collectively, our results show that the technique described here allows to analyze glioma tissues with a spatial resolution beyond reach of most of other omics approaches and the obtained data may be used to predict clinical behavior of the tumor.

The onset of obesity-linked type 2 diabetes (T2D) is marked by an eventual failure in pancreatic β-cell function and mass that is no longer able to compensate for the inherent insulin resistance and increased metabolic load intrinsic to obesity. However, in a commonly used model of T2D, the db/db mouse, β-cells have an inbuilt adaptive flexibility enabling them to effectively adjust insulin production rates relative to the metabolic demand. Pancreatic β-cells from these animals have markedly reduced intracellular insulin stores, yet high rates of (pro)insulin secretion, together with a substantial increase in proinsulin biosynthesis highlighted by expanded rough endoplasmic reticulum and Golgi apparatus. However, when the metabolic overload and/or hyperglycemia is normalized, β-cells from db/db mice quickly restore their insulin stores and normalize secretory function. This demonstrates the β-cell’s adaptive flexibility and indicates that therapeutic approaches applied to encourage β-cell rest are capable of restoring endogenous β-cell function. However, mechanisms that regulate β-cell adaptive flexibility are essentially unknown. To gain deeper mechanistic insight into the molecular events underlying β-cell adaptive flexibility in db/db β-cells, we conducted a combined proteomic and post-translational modification specific proteomic (PTMomics) approach on islets from db/db mice and wild-type controls (WT) with or without prior exposure to normal glucose levels. We identified differential modifications of proteins involved in redox homeostasis, protein refolding, K48-linked deubiquitination, mRNA/protein export, focal adhesion, ERK1/2 signaling, and renin-angiotensin-aldosterone signaling, as well as sialyltransferase activity, associated with β-cell adaptive flexibility. These proteins are all related to proinsulin biosynthesis and processing, maturation of insulin secretory granules, and vesicular trafficking—core pathways involved in the adaptation of insulin production to meet metabolic demand. Collectively, this study outlines a novel and comprehensive global PTMome signaling map that highlights important molecular mechanisms related to the adaptive flexibility of β-cell function, providing improved insight into disease pathogenesis of T2D.

The human leucocyte antigen (HLA)-B*27:05 allele and the endoplasmic reticulum-resident aminopeptidases are strongly associated with ankylosing spondylitis (AS), a chronic inflammatory spondyloarthropathy. This study examined the effect of endoplasmic reticulum aminopeptidase 2 (ERAP2) in the generation of the natural HLA-B*27:05 ligandome in live cells. Complexes of HLA-B*27:05-bound peptide pools were isolated from human ERAP2-edited cell clones and the peptides were identified using high throughput mass spectrometry analyses. The relative abundance of thousand ligands was established by quantitative tandem mass spectrometry and bioinformatics analysis. The residue frequencies at different peptide position, identified in presence or absence of ERAP2, determined structural features of ligands and their interactions with specific pockets of antigen binding site of HLA-B*27:05 molecule. Sequence alignment of ligands identified with species of bacteria associated with HLA-B*27-dependent reactive arthritis was performed. In the absence of ERAP2, peptides with N-terminal basic residues, and minority canonical P2 residues are enriched in the natural ligandome. Further, alterations of residue frequencies and hydrophobicity profile at P3, P7, and P positions were detected. In addition, several ERAP2-dependent cellular peptides were highly similar to protein sequences of arthritogenic bacteria, including one human HLA-B*27:05 ligand fully conserved in a protein from Campylobacter jejuni. These findings highlight the pathogenic role of this aminopeptidase in the triggering of AS autoimmune disease.

Post-translational modifications play a critical and diverse role in regulating cellular activities. Despite their fundamentally important role in cellular function, there has been no report to date of an effective generalized approach to the targeting, extraction and characterization of the critical c-terminal regions of natively prenylated proteins. Various chemical modification and metabolic labelling strategies in cell culture have been reported. However, their applicability is limited to cell culture systems and does not allow for analysis of tissue samples. The chemical characteristics (hydrophobicity, low abundance, highly basic charge) of many of the c-terminal regions of prenylated proteins have impaired the use of standard proteomic workflows. In this context, we sought a direct approach to the problem in order to examine these proteins in tissue without the use of labelling.  Here we demonstrate that prenylated proteins can be captured on chromatographic resins functionalized with mixed disulfide functions. Protease treatment of resin-bound proteins using chymotryptic digestion revealed peptides from many known prenylated proteins. Exposure of the protease-treated resin to reducing agents and hydro organic mixtures released c-terminal peptides with intact prenyl groups along with other enzymatic modifications expected in this protein family. Database and search parameters were selected to allow for c-terminal modifications unique to these molecules such as CAAX box processing and c-terminal methylation. In summary, we present a direct approach to enrich and obtain information at a molecular level of detail about prenylation of proteins from tissue and cell extracts using high performance LCMS without the need for metabolic labeling and derivatization.

Genetic and genomic research has greatly advanced our understanding of heart disease. Yet, comprehensive, in-depth, quantitative maps of protein expression in hearts of living humans are still lacking. Using samples obtained during valve replacement surgery in patients with mitral valve prolapse (MVP), we set out to define inter-chamber differences, the intersect of proteomic data with genetic or genomic datasets, and the impact of left atrial dilation on the proteome of patients with no history of atrial fibrillation (AF).  We collected biopsies from right atria (RA), left atria (LA) and left ventricle (LV) of seven male patients with mitral valve regurgitation with dilated LA but no history of AF. Biopsy samples were analyzed by high-resolution mass spectrometry (MS), where peptides were pre-fractionated by reverse phase high-pressure liquid chromatography prior to MS measurement on a Q-Exactive-HF Orbitrap instrument. We identified 7,314 proteins based on 130,728 peptides. Results were confirmed in an independent set of biopsies collected from three additional individuals. Comparative analysis against data from post-mortem samples showed enhanced quantitative power and confidence level in samples collected from living hearts. Our analysis, combined with data from genome wide association studies suggested candidate gene associations to MVP, identified higher abundance in ventricle for proteins associated with cardiomyopathies and revealed the dilated LA proteome, demonstrating differential representation of molecules previously associated with AF, in non-AF hearts. This is the largest dataset of cardiac protein expression from human samples collected in vivo. It provides a comprehensive resource that allows insight into molecular fingerprints of MVP and facilitates novel inferences between genomic data and disease mechanisms. We propose that over-representation of proteins in ventricle is consequent not to redundancy but to functional need, and conclude that changes in abundance of proteins known to associate with AF are not sufficient for arrhythmogenesis.

Accumulation and propagation of hyperphosphorylated tau (p-tau) is a common neuropathological hallmark associated with neurodegeneration of Alzheimer's disease (AD), frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17), and related tauopathies. Extracellular vesicles, specifically exosomes, have recently been demonstrated to participate in mediating tau propagation in brain. Exosomes produced by human induced pluripotent stem cell (iPSC)-derived neurons expressing mutant Tau (mTau), containing the P301L and V337M Tau mutations of FTDP-17, possess the ability to propagate p-tau pathology after injection into mouse brain.  To gain an understanding of the mTau exosome cargo involved in tau pathogenesis, these pathogenic exosomes were analyzed by proteomics and bioinformatics. The data showed that mTau expression dysregulates the exosome proteome to result in (1) proteins uniquely present only in mTau, and not control exosomes, (2) the absence of proteins in mTau exosomes, uniquely present in control exosomes, and (3) shared proteins which were significantly up-regulated or down-regulated in mTau compared to control exosomes. Notably, mTau exosomes (not control exosomes) contain ANP32A (also known as I1PP2A), an endogenous inhibitor of the PP2A phosphatase which regulates the phosphorylation state of p-tau.  Several of the mTau exosome-specific proteins have been shown to participate in AD mechanisms involving lysosomes, inflammation, secretases, and related processes.  Furthermore, the mTau exosomes lacked a substantial portion of proteins present in control exosomes involved in pathways of localization, vesicle transport, and protein binding functions. The shared proteins present in both mTau and control exosomes represented exosome functions of vesicle-mediated transport, exocytosis, and secretion processes. These data illustrate mTau as a dynamic regulator of the biogenesis of exosomes to result in acquisition, deletion, and up- or down-regulation of protein cargo to result in pathogenic mTau exosomes capable of in vivo propagation of p-tau neuropathology in mouse brain. 

The degradation of intra- and extracellular proteins is essential in all cell types and mediated by two systems, the ubiquitin-proteasome system (UPS) and the autophagy-lysosome pathway. This study investigates the changes in autophagosomal and lysosomal proteomes upon inhibition of proteasomes by bortezomib (BTZ) or MG132. We find an increased abundance of more than 50 proteins in lysosomes of cells in which the proteasome is inhibited. Among those are dihydrofolate reductase (DHFR), ß-Catenin and 3-hydroxy-3-methylglutaryl-coenzym-A (HMGCoA)-reductase. Since these proteins are known to be degraded by the proteasome they seem to be compensatorily delivered to the autophagosomal pathway when the proteasome is inactivated. Surprisingly, most of the proteins which show increased amounts in the lysosomes of BTZ or MG132 treated cells are proteasomal subunits. Thus an inactivated, non-functional proteasome is delivered to the autophagic pathway. Native gel electrophoresis shows that the proteasome reaches the lysosome intact and not disassembled. Adaptor proteins, which target proteasomes to autophagy, have been described in Arabidopsis, Saccharomyces and upon starvation in mammalians. However, in cell lines deficient of these proteins or their mammalian orthologues, respectively, the transfer of proteasomes to the lysosome is not impaired. Obviously, these proteins do not play a role as autophagy adaptor proteins in mammalian cells. We can also show that chaperone-mediated autophagy (CMA) does not participate in the proteasome delivery to the lysosomes. In autophagy-related (ATG)-5 and ATG7 deficient cells the delivery of inactivated proteasomes to the autophagic pathway was only partially blocked, indicating the existence of at least two different pathways by which inactivated proteasomes can be delivered to the lysosome in mammalian cells.

Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.

Data independent acquisition (DIA) is an attractive alternative to standard shotgun proteomics methods for quantitative experiments. However, most DIA methods require collecting exhaustive, sample-specific spectrum libraries with data dependent acquisition (DDA) to detect and quantify peptides. In addition to working with non-human samples, studies of splice junctions, sequence variants, or simply working with small sample yields can make developing DDA-based spectrum libraries impractical. Here we illustrate how to acquire, queue, and validate DIA data without spectrum libraries, and provide a workflow to efficiently generate DIA-only chromatogram libraries using gas-phase fractionation (GPF). We present best-practice methods for collecting DIA data using Orbitrap-based instruments, and develop an understanding for why DIA using an Orbitrap mass spectrometer should be approached differently than when using time-of-flight instruments. Finally, we discuss several methods for analyzing DIA data without libraries.

Molecular mechanisms underlying sperm motility have not been fully explained, particularly in chickens. The objective was to identify seminal plasma proteins associated with chicken sperm motility by comparing the seminal plasma proteomic profile of roosters with low sperm motility (LSM, n = 4) and high sperm motility (HSM, n = 4). Using a label-free MS-based method, a total of 522 seminal plasma proteins were identified, including 386 (~74%) previously reported and 136 novel ones. A total of 70 differentially abundant proteins were defined, including 48 more-abundant, 15 less-abundant, and seven proteins unique to the LSM group (specific proteins). Key secretory proteins like less-abundant ADGRG2 and more-abundant SPINK2 in the LSM suggested that the corresponding secretory tissues played a crucial role in maintaining sperm motility. Majority (80%) of the more-abundant and five specific proteins were annotated to the cytoplasmic domain which might be a result of higher plasma membrane damage and acrosome dysfunction in LSM. Additionally, more-abundant mitochondrial proteins were detected in LSM seminal plasma associated with lower spermatozoa mitochondrial membrane potential (m) and ATP concentrations. Further studies showed that the spermatozoa might be suffering from oxidative stress, as the amount of spermatozoa reactive oxygen species (ROS) were largely enhanced, seminal malondialdehyde (MDA) concentrations were increased, and the seminal plasma total antioxidant capacity (T-AOC) were decreased. Our study provides an additional catalog of chicken seminal plasma proteome and supports the idea that seminal plasma could be as an indicator of spermatozoa physiology. More-abundant of acrosome, mitochondria and sperm cytoskeleton proteins in the seminal plasma could be a marker of sperm dysfunction and loss of motility. The degeneration of spermatozoa caused the reduced seminal T-AOC and enhanced oxidative stress might be potential determinants of low sperm motility. These results could extend our understanding of sperm motility and sperm physiology regulation.

Assembly factors play a critical role in the biogenesis of mitochondrial respiratory chain complexes I-IV where they assist in the membrane insertion of subunits, attachment of co-factors, and stabilization of assembly intermediates. The major fraction of complexes I, III and IV are present together in large molecular structures known as respiratory chain supercomplexes. A number of assembly factors have been proposed as required for supercomplex assembly, including the hypoxia inducible gene 1 domain family member HIGD2A. Using gene-edited human cell lines and extensive steady state, translation and affinity enrichment proteomics techniques we show that loss of HIGD2A leads to defects in the de novo biogenesis of mtDNA-encoded COX3, subsequent accumulation of complex IV intermediates and turnover of COX3 partner proteins. Deletion of HIGD2A also leads to defective complex IV activity. The impact of HIGD2A loss on complex IV was not altered by growth under hypoxic conditions, consistent with its role being in basal complex IV assembly. While in the absence of HIGD2A we show that mitochondria do contain an altered supercomplex assembly, we demonstrate it to harbor a crippled complex IV lacking COX3. Our results redefine HIGD2A as a classical assembly factor required for building the COX3 module of complex IV.

Label-Free Quantitative mass spectrometry based workflows for differential expression (DE) analysis of proteins impose important challenges on the data analysis due to peptide-specific effects and context dependent missingness of peptide intensities. Peptide-based workflows, like MSqRob, test for DE directly from peptide intensities and outperform summarization methods which first aggregate MS1 peptide intensities to protein intensities before DE analysis. However, these methods are computationally expensive, often hard to understand for the non-specialised end-user, and do not provide protein summaries, which are important for visualisation or downstream processing. In this work, we therefore evaluate state-of-the-art summarization strategies using a benchmark spike-in dataset and discuss why and when these fail compared to the state-of-the-art peptide based model, MSqRob. Based on this evaluation, we propose a novel summarization strategy, MSqRobSum, which estimates MSqRob’s model parameters in a two-stage procedure circumventing the drawbacks of peptide-based workflows. MSqRobSum maintains MSqRob’s superior performance, while providing useful protein expression summaries for plotting and downstream analysis. Summarising peptide to protein intensities considerably reduces the computational complexity, the memory footprint and the model complexity, and makes it easier to disseminate DE inferred on protein summaries. Moreover, MSqRobSum provides a highly modular analysis framework, which provides researchers with full flexibility to develop data analysis workflows tailored towards their specific applications.

The vessel wall is continuously exposed to hemodynamic forces generated by blood flow. Endothelial mechanosensors perceive and translate mechanical signals via cellular signaling pathways into biological processes that control endothelial development, phenotype and function. To assess the hemodynamic effects on the endothelium on a system-wide level, we applied a quantitative mass spectrometry approach combined with cell surface chemical footprinting. SILAC-labeled endothelial cells were subjected to flow-induced shear stress for 0, 24 or 48 hours, followed by chemical labeling of surface proteins using a non-membrane permeable biotin label, and analysis of the whole proteome and the cell surface proteome by LC-MS/MS analysis. These studies revealed that of the >5000 quantified proteins 104 were altered, which were highly enriched for extracellular matrix proteins and proteins involved in cell-matrix adhesion. Cell surface proteomics indicated that LAMA4 was proteolytically processed upon flow-exposure, which corresponded to the decreased LAMA4 mass observed on immunoblot. Immunofluorescence microscopy studies highlighted that the endothelial basement membrane was drastically remodeled upon flow exposure. We observed a network-like pattern of LAMA4 and LAMA5, which corresponded to the localization of laminin-adhesion molecules ITGA6 and ITGB4. Furthermore, the adaptation to flow-exposure did not affect the inflammatory response to tumor necrosis factor α, indicating that inflammation and flow trigger fundamentally distinct endothelial signaling pathways with limited reciprocity and synergy. Taken together, this study uncovers the blood flow-induced remodeling of the basement membrane and stresses the importance of the subendothelial basement membrane in vascular homeostasis.

Protein cross-linking and the analysis of cross-linked peptides by mass spectrometry is currently receiving much attention. Not only is this approach applied to isolated complexes to provide information about spatial arrangements of proteins but it is also increasingly applied to entire cells and their organelles. As in quantitative proteomics, the application of isotopic labelling further makes it possible to monitor quantitative changes in the protein-protein interactions between different states of a system. Here, we cross-linked mitochondria from Saccharomyces cerevisiae grown on either glycerol- or glucose-containing medium to monitor protein-protein interactions under non-fermentative and fermentative conditions. We investigated qualitatively the protein-protein interactions of the 400 most abundant proteins applying stringent data-filtering criteria, i.e. a minimum of two cross-linked peptide spectrum matches and a cut-off in the spectrum scoring of the used search engine. The cross-linker BS3 proved to be equally suited for connecting proteins in all compartments of mitochondria when compared with its water-insoluble but membrane-permeable derivative DSS. We also applied quantitative cross-linking to mitochondria of both the growth conditions using stable-isotope labelled BS3. Significant differences of cross-linked proteins under glycerol and glucose conditions were detected, however, mainly due to the different copy numbers of these proteins in mitochondria under both the conditions. Results obtained from the glycerol condition indicate that the internal NADH:ubiquinone oxidoreductase Ndi1 is part of an electron transport chain supercomplex. We have also detected several hitherto uncharacterized proteins and identified their interaction partners. Among those, Min8 was found to be associated with cytochrome c oxidase. BN-PAGE analyses of min8 mitochondria suggest that Min8 promotes the incorporation of Cox12 into cytochrome c oxidase.

Protein subcellular localization is an essential and highly regulated determinant of protein function. Major advances in mass spectrometry and imaging have allowed the development of powerful spatial proteomics approaches for determining protein localization at the whole cell scale. Here, a brief overview of current methods is presented, followed by a detailed discussion of organellar mapping through proteomic profiling. This relatively simple yet flexible approach is rapidly gaining popularity, due to its ability to capture the localizations of thousands of proteins in a single experiment. It can be used to generate high-resolution cell maps, and as a tool for monitoring protein localization dynamics. This review highlights the strengths and limitations of the approach, and provides guidance to designing and interpreting profiling experiments. 

Protein-protein interactions are often mediated by short linear motifs (SLiMs) that are located in intrinsically disordered regions (IDRs) of proteins. Interactions mediated by SLiMs are notoriously difficult to study, and many functionally relevant interactions likely remain to be uncovered. Recently, pull-downs with synthetic peptides in combination with quantitative mass spectrometry emerged as a powerful screening approach to study protein-protein interactions mediated by SLiMs. Specifically, arrays of synthetic peptides immobilized on cellulose membranes provide a scalable means to identify the interaction partners of many peptides in parallel. In this minireview we briefly highlight the relevance of SLiMs for protein-protein interactions, outline existing screening technologies, discuss unique advantages of peptide-based interaction screens and provide practical suggestions for setting up such peptide-based screens.

The cyclic GMP-AMP synthase (cGAS) protein is a pattern-recognition receptor of the mammalian innate immune system that is recognized as a main cytosolic sensor of pathogenic or damaged DNA. cGAS DNA binding initiates catalytic production of the second messenger, cyclic GMP-AMP, which activates the STING-TBK1-IRF3 signaling axis to induce cytokine expression. Post-translational modification (PTM) has started to be recognized as a critical component of cGAS regulation, yet the extent of these modifications remains unclear. Here, we report the identification and functional analysis of cGAS phosphorylations and acetylations in several cell types under basal and immune-stimulated conditions. cGAS was enriched by immunoaffinity purification from human primary fibroblasts prior to and after infection with herpes simplex virus type 1 (HSV-1), as well as from immune-stimulated STING-HEK293T cells. Six phosphorylations and eight acetylations were detected, of which eight PTMs were not previously documented. PTMs were validated by parallel reaction monitoring (PRM) mass spectrometry in fibroblasts, HEK293T cells, and THP-1 macrophage-like cells. Primary sequence and structural analysis of cGAS highlighted a subset of PTM sites with elevated surface accessibility and high evolutionary sequence conservation. To assess the functional relevance of each PTM, we generated a series of single-point cGAS mutations. Stable cell lines were constructed to express cGAS with amino acid substitutions that prevented phosphorylation (Ser-to-Ala) and acetylation (Lys-to-Arg) or that mimicked the modification state (Ser-to-Asp and Lys-to-Gln). cGAS-dependent apoptotic and immune signaling activities were then assessed for each mutation. Our results show that acetyl-mimic mutations at Lys384 and Lys414 inhibit the ability of cGAS to induce apoptosis. In contrast, the Lys198 acetyl-mimic mutation increased cGAS-dependent interferon signaling when compared to the unmodified charge-mimic. Moreover, targeted PRM quantification showed that Lys198 acetylation is decreased upon infections with two herpesviruses—HSV-1 and human cytomegalovirus (HCMV), highlighting this residue as a regulatory point during virus infection.

The presentation of post-translationally modified (PTM) peptides by cell surface HLA molecules has the potential to increase the diversity of targets for surveilling T cells. Whilst immunopeptidomics studies routinely identify thousands of HLA-bound peptides from cell lines and tissue samples, in-depth analyses of the proportion and nature of peptides bearing one or more PTMs remains challenging. Here we have analyzed HLA-bound peptides from a variety of allotypes and assessed the distribution of mass spectrometry-detected PTMs, finding deamidation of asparagine or glutamine to be highly prevalent. Given that asparagine deamidation may arise either spontaneously or through enzymatic reaction, we assessed allele-specific and global motifs flanking the modified residues. Notably, we found that the N-linked glycosylation motif NX(S/T) was highly abundant across asparagine-deamidated HLA-bound peptides. This finding, demonstrated previously for a handful of deamidated T cell epitopes, implicates a more global role for the retrograde transport of nascently N-glycosylated polypeptides from the ER and their subsequent degradation within the cytosol to form HLA-ligand precursors. Chemical inhibition of Peptide:N-Glycanase (PNGase), the endoglycosidase responsible for the removal of glycans from misfolded and retrotranslocated glycoproteins, greatly reduced presentation of this subset of deamidated HLA-bound peptides. Importantly, there was no impact of PNGase inhibition on peptides not containing a consensus NX(S/T) motif. This indicates that a large proportion of HLA-I bound asparagine deamidated peptides are generated from formerly glycosylated proteins that have undergone deglycosylation via the ER-associated protein degradation (ERAD) pathway. The information herein will help train deamidation prediction models for HLA-peptide repertoires and aid in the design of novel T cell therapeutic targets derived from glycoprotein antigens.

Campylobacter jejuni is a major cause of food-borne gastroenteritis. Proteomics by label-based two-dimensional liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) identified proteins associated with growth in 0.1% sodium deoxycholate (DOC, a component of gut bile salts), and system-wide validation was performed by data-independent acquisition (DIA-SWATH-MS). LC-MS/MS quantified 1326 proteins (~82% of the predicted C. jejuni proteome), of which 1104 were validated in additional biological replicates by DIA-SWATH-MS. DOC resulted in a profound proteome shift with 512 proteins showing significantly altered abundance. Induced proteins were associated with flagellar motility and antibiotic resistance; and these correlated with increased DOC motility and resistance to polymyxin B and ciprofloxacin. DOC also increased human Caco-2 cell adherence and invasion. Abundances of proteins involved in nutrient transport were altered by DOC and aligned with intracellular changes to their respective carbon sources. DOC increased intracellular levels of sulfur-containing amino acids (cysteine and methionine) and the dipeptide cystine (Cys-Cys), which also correlated with reduced resistance to oxidative stress. A DOC induced transport protein was Cj0025c, which has sequence similarity to bacterial Cys-Cys transporters. Deletion of cj0025c (cj0025c) resulted in proteome changes consistent with sulfur starvation, as well as attenuated invasion, reduced motility, atypical morphology, increased antimicrobial susceptibility and poor biofilm formation. Targeted metabolomics showed cj0025c was capable of utilizing known C. jejuni amino and organic acid substrates commensurate with wild-type. Medium Cys-Cys levels however, were maintained in cj0025c relative to wild-type. A toxic Cys-Cys mimic (selenocystine) inhibited wild-type growth, but not cj0025c. Provision of an alternate sulfur source (2 mM thiosulfate) restored cj0025c motility. Our data confirm that Cj0025c is a Cys-Cys transporter that we have named TcyP consistent with the nomenclature of homologous proteins in other species.

Perlecan is a critical proteoglycan found in the extracellular matrix (ECM) of cartilage. In healthy cartilage, perlecan regulates cartilage biomechanics and we previously demonstrated perlecan deficiency leads to reduced cellular and ECM stiffness in vivo. This change in mechanics may lead to the early onset osteoarthritis seen in disorders resulting from perlecan knockdown such as Schwartz-Jampel syndrome (SJS). To identify how perlecan knockdown affects the material properties of developing cartilage, we used imaging and liquid chromatography–tandem mass spectrometry (LC-MS/MS) to study the ECM in a murine model of SJS, Hspg2C1532Y-Neo. Perlecan knockdown led to defective pericellular matrix formation, whereas the abundance of bulk ECM proteins, including many collagens, increased. Post-translational modifications and ultrastructure of collagens were not significantly different; however, LC-MS/MS analysis showed more protein was secreted by Hspg2C1532Y-Neo cartilage in vitro, suggesting that the incorporation of newly synthesized ECM was impaired. In addition, glycosaminoglycan deposition was atypical, which may explain the previously observed decrease in mechanics. Overall, these findings provide insight into the influence of perlecan on functional cartilage assembly and the progression of osteoarthritis in SJS.

1 April 2020

Considerations of justice and social equity are as important for the circular economy transition as they are in the contexts of low-carbon transitions and digitalization of the economy. This paper sets out the just transition approach, and its relevance in climate change and energy transition debates.

1 February 2008 , Number 5

1 February 2008 , Number 3

1 June 2008 , Number 6

Dmitri Medvedev’s appearance at the G8 Summit in Hokkaido will be his first step on the wide international stage that Vladimir Putin occupied with such a swagger. Expectations of change will be high, but they are likely to be unrealistic at such an early stage in Medvedev’s presidency. Putin’s foreign policy legacy is a heavy one and he has made it clear that Medvedev will be no soft touch, but will his approach ultimately be more productive?

1 July 2008 , Number 3

Ahead of the French holiday rush for relaxation in warm waters, President Nicolas Sarkozy has flung himself into the Mediterranean policy pool. Not content with existing arrangements, plans and processes for dealing with those on the other shore, the President has built his very own scheme, now adopted by the European Union. But the tides have not been altogether kind.