Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies – Spearman and Kendall correlations – and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric—Euclidean distance—delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.

After ejaculation, mammalian spermatozoa must undergo a process known as capacitation in order to successfully fertilize the oocyte. Several post-translational modifications occur during capacitation, including sialylation, which despite being limited to a few proteins, seems to be essential for proper sperm-oocyte interaction. Regardless of its importance, to date, no single study has ever identified nor quantified which glycoproteins bearing terminal sialic acid (Sia) are altered during capacitation. Here we characterize sialylation during mouse sperm capacitation. Using tandem MS coupled with liquid chromatography (LC–MS/MS), we found 142 nonreductant peptides, with 9 of them showing potential modifications on their sialylated oligosaccharides during capacitation. As such, N-linked sialoglycopeptides from C4b-binding protein, endothelial lipase (EL), serine proteases 39 and 52, testis-expressed protein 101 and zonadhesin were reduced following capacitation. In contrast, mitochondrial aconitate hydratase (aconitase; ACO2), a TCA cycle enzyme, was the only protein to show an increase in Sia content during capacitation. Interestingly, although the loss of Sia within EL (N62) was accompanied by a reduction in its phospholipase A₁ activity, a decrease in the activity of ACO2 (i.e. stereospecific isomerization of citrate to isocitrate) occurred when sialylation increased (N612). The latter was confirmed by N612D recombinant protein tagged with both His and GFP. The replacement of Sia for the negatively charged Aspartic acid in the N612D mutant caused complete loss of aconitase activity compared with the WT. Computer modeling show that N612 sits atop the catalytic site of ACO2. The introduction of Sia causes a large conformational change in the alpha helix, essentially, distorting the active site, leading to complete loss of function. These findings suggest that the switch from oxidative phosphorylation, over to glycolysis that occurs during capacitation may come about through sialylation of ACO2.

Renal Cell Carcinoma (RCC) is one of the most commonly diagnosed cancers worldwide with research efforts dramatically improving understanding of the biology of the disease. To investigate the role of the immune system in treatment-naïve clear cell Renal Cell Carcinoma (ccRCC), we interrogated the immune infiltrate in patient-matched ccRCC tumor samples, benign normal adjacent tissue (NAT) and peripheral blood mononuclear cells (PBMCs isolated from whole blood, focusing our attention on the myeloid cell infiltrate. Using flow cytometric, MS, and ExCYT analysis, we discovered unique myeloid populations in PBMCs across patient samples. Furthermore, normal adjacent tissues and ccRCC tissues contained numerous myeloid populations with a unique signature for both tissues. Enrichment of the immune cell (CD45⁺) fraction and subsequent gene expression analysis revealed a number of myeloid-related genes that were differentially expressed. These data provide evidence, for the first time, of an immunosuppressive and pro-tumorigenic role of myeloid cells in early, clinically localized ccRCC. The identification of a number of immune proteins for therapeutic targeting provides a rationale for investigation into the potential efficacy of earlier intervention with single-agent or combination immunotherapy for ccRCC.

The EGFR tyrosine kinase inhibitor gefitinib is commonly used for lung cancer patients. However, some patients eventually become resistant to gefitinib and develop progressive disease. Here, we indicate that ecto-ATP synthase, which ectopically translocated from mitochondrial inner membrane to plasma membrane, is considered as a potential therapeutic target for drug-resistant cells. Quantitative multi-omics profiling reveals that ecto-ATP synthase inhibitor mediates CK2-dependent phosphorylation of DNA topoisomerase IIα (topo IIα) at serine 1106 and subsequently increases the expression of long noncoding RNA, GAS5. Additionally, we also determine that downstream of GAS5, p53 pathway, is activated by ecto-ATP synthase inhibitor for regulation of programed cell death. Interestingly, GAS5-proteins interactomic profiling elucidates that GAS5 associates with topo IIα and subsequently enhancing the phosphorylation level of topo IIα. Taken together, our findings suggest that ecto-ATP synthase blockade is an effective therapeutic strategy via regulation of CK2/phospho-topo IIα/GAS5 network in gefitinib-resistant lung cancer cells.

Small admixtures in water, e.g. of metal ions, often act as cell growth regulators. Here we report that enrichment of deuterium content in water, normally found at 8 mm concentration, two-three folds increases cell proliferation and lowers the oxidative stress level as well. Acting as an anti-oxidant, deuterium-enriched water prevents the toxic effect of such oxidative agents as hydrogen peroxide and auranofin. This action is opposite to that of deuterium depletion that is known to suppress cell growth and induce oxidative stress in mitochondria. We thus hypothesize that deuterium may be a natural cell growth regulator that controls mitochondrial oxidation-reduction balance. Because growth acceleration is reduced approximately by half by addition to water a minute amount (0.15%) of ¹⁸O isotope, at least part of the deuterium effect on cell growth can be explained by the isotopic resonance phenomenon. A slight (2-fold) enrichment of deuterium in water accelerates human cell growth. Quantitative MS based proteomics determined changes in protein abundances and redox states and found that deuterium-enriched water acts mainly through decreasing ROS production in mitochondria. This action is opposite to that of deuterium depletion that suppresses cell growth by inducing oxidative stress. Thus deuterium may be a natural cell growth regulator that controls mitochondrial oxidation-reduction balance. The role of isotopic resonance in this effect was validated by further experiments on bacteria.

Coronavirus disease 2019 (COVID-19) is a highly contagious infection and threating the human lives in the world. The elevation of cytokines in blood is crucial to induce cytokine storm and immunosuppression in the transition of severity in COVID-19 patients. However, the comprehensive changes of serum proteins in COVID-19 patients throughout the SARS-CoV-2 infection is unknown. In this work, we developed a high-density antibody microarray and performed an in-depth proteomics analysis of serum samples collected from early COVID-19 (n = 15) and influenza (n = 13) patients. We identified a large set of differentially expressed proteins (n = 132) that participate in a landscape of inflammation and immune signaling related to the SARS-CoV-2 infection. Furthermore, the significant correlations of neutrophil and lymphocyte with the CCL2 and CXCL10 mediated cytokine signaling pathways was identified. These information are valuable for the understanding of COVID-19 pathogenesis, identification of biomarkers and development of the optimal anti-inflammation therapy.

Cross-linking MS (XL-MS) has been recognized as an effective source of information about protein structures and interactions. In contrast to regular peptide identification, XL-MS has to deal with a quadratic search space, where peptides from every protein could potentially be cross-linked to any other protein. To cope with this search space, most tools apply different heuristics for search space reduction. We introduce a new open-source XL-MS database search algorithm, OpenPepXL, which offers increased sensitivity compared with other tools. OpenPepXL searches the full search space of an XL-MS experiment without using heuristics to reduce it. Because of efficient data structures and built-in parallelization OpenPepXL achieves excellent runtimes and can also be deployed on large compute clusters and cloud services while maintaining a slim memory footprint. We compared OpenPepXL to several other commonly used tools for identification of noncleavable labeled and label-free cross-linkers on a diverse set of XL-MS experiments. In our first comparison, we used a data set from a fraction of a cell lysate with a protein database of 128 targets and 128 decoys. At 5% FDR, OpenPepXL finds from 7% to over 50% more unique residue pairs (URPs) than other tools. On data sets with available high-resolution structures for cross-link validation OpenPepXL reports from 7% to over 40% more structurally validated URPs than other tools. Additionally, we used a synthetic peptide data set that allows objective validation of cross-links without relying on structural information and found that OpenPepXL reports at least 12% more validated URPs than other tools. It has been built as part of the OpenMS suite of tools and supports Windows, macOS, and Linux operating systems. OpenPepXL also supports the MzIdentML 1.2 format for XL-MS identification results. It is freely available under a three-clause BSD license at https://openms.org/openpepxl.

Trypsin is the protease of choice in bottom-up proteomics. However, its application can be limited by the amino acid composition of target proteins and the pH of the digestion solution. In this study we characterize ProAlanase, a protease from the fungus Aspergillus niger that cleaves primarily on the C-terminal side of proline and alanine residues. ProAlanase achieves high proteolytic activity and specificity when digestion is carried out at acidic pH (1.5) for relatively short (2 h) time periods. To elucidate the potential of ProAlanase in proteomics applications, we conducted a series of investigations comprising comparative multi-enzymatic profiling of a human cell line proteome, histone PTM analysis, ancient bone protein identification, phosphosite mapping and de novo sequencing of a proline-rich protein and disulfide bond mapping in mAb. The results demonstrate that ProAlanase is highly suitable for proteomics analysis of the arginine- and lysine-rich histones, enabling high sequence coverage of multiple histone family members. It also facilitates an efficient digestion of bone collagen thanks to the cleavage at the C terminus of hydroxyproline which is highly prevalent in collagen. This allows to identify complementary proteins in ProAlanase- and trypsin-digested ancient bone samples, as well as to increase sequence coverage of noncollagenous proteins. Moreover, digestion with ProAlanase improves protein sequence coverage and phosphosite localization for the proline-rich protein Notch3 intracellular domain (N3ICD). Furthermore, we achieve a nearly complete coverage of N3ICD protein by de novo sequencing using the combination of ProAlanase and tryptic peptides. Finally, we demonstrate that ProAlanase is efficient in disulfide bond mapping, showing high coverage of disulfide-containing regions in a nonreduced mAb.

Over the past decade, modern methods of MS (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. Although MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem MS (LC-MS²) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be laborious and time-consuming, especially if the experimental LC-MS² data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC–MS measurements. Peptide masses are then extracted from MS¹ data and systematically tested against an in silico library of all possible peptide mass data compiled in-house. The library has been computed from the UniProt Knowledgebase covering Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from correlation coefficients between experimental and strain-specific in silico peptide mass profiles and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient – less than 2 mins per sample - and has been successfully tested by a test set of 39 LC-MS¹ peak lists obtained from 19 different microbial pathogens. The proposed method is rapid, simple and automatable and we foresee wide application potential for future microbiological applications.

Extracellular vesicles (EVs) secreted by the epididymal epithelium transfer to spermatozoa key proteins that are essential in promoting motility and subsequent fertilization success. Using the domestic cat model, the objectives were to (1) characterize and compare protein content of EVs between segments of the epididymis, and (2) compare EV protein compositions between normo- and teratospermic individuals (producing >60% of abnormal spermatozoa). Epididymal EVs from adult cats were isolated and assessed via liquid chromatography tandem MS. Both male types shared 3008 proteins in total, with 98 and 20 EV proteins unique to normospermic and teratospermic males, respectively. Expression levels of several proteins changed between epididymal segments in both male types. Several proteins in both groups were related to sperm motility (e.g. hexokinase 1, adenylate kinase isoenzyme) and zona pellucida or oolemma binding (e.g. disintegrin and metalloproteinase domain proteins, zona binding proteins 1 and 2). Interestingly, seven cauda-derived EV proteins trended downward in teratospermic compared with normospermic males, which may relate to poor sperm quality. Collective results revealed, for the first time, EV proteins related to sequential sperm maturation with differences observed between normospermic and teratospermic individuals.

Endometrial carcinoma (EC) is the most common gynecologic malignancy in the United States, with limited effective targeted therapies. Endometrial tumors exhibit frequent alterations in protein kinases, yet only a small fraction of the kinome has been therapeutically explored. To identify kinase therapeutic avenues for EC, we profiled the kinome of endometrial tumors and normal endometrial tissues using Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS). Our proteomics analysis identified a network of kinases overexpressed in tumors, including Serine/Arginine-Rich Splicing Factor Kinase 1 (SRPK1). Immunohistochemical (IHC) analysis of endometrial tumors confirmed MIB-MS findings and showed SRPK1 protein levels were highly expressed in endometrioid and uterine serous cancer (USC) histological subtypes. Moreover, querying large-scale genomics studies of EC tumors revealed high expression of SRPK1 correlated with poor survival. Loss-of-function studies targeting SRPK1 in an established USC cell line demonstrated SRPK1 was integral for RNA splicing, as well as cell cycle progression and survival under nutrient deficient conditions. Profiling of USC cells identified a compensatory response to SRPK1 inhibition that involved EGFR and the up-regulation of IGF1R and downstream AKT signaling. Co-targeting SRPK1 and EGFR or IGF1R synergistically enhanced growth inhibition in serous and endometrioid cell lines, representing a promising combination therapy for EC.

Specific E3 ligases target tumor suppressors for degradation. Inhibition of such E3 ligases may be an important approach to cancer treatment. RNF146 is a RING domain and PARylation-dependent E3 ligase that functions as an activator of the β-catenin/Wnt and YAP/Hippo pathways by targeting the degradation of several tumor suppressors. Tankyrases 1 and 2 (TNKS1/2) are the only known poly-ADP-ribosyltransferases that require RNF146 to degrade their substrates. However, systematic identification of RNF146 substrates have not yet been performed. To uncover substrates of RNF146 that are targeted for degradation, we generated RNF146 knockout cells and TNKS1/2-double knockout cells and performed proteome profiling with label-free quantification as well as transcriptome analysis. We identified 160 potential substrates of RNF146, which included many known substrates of RNF146 and TNKS1/2 and 122 potential TNKS-independent substrates of RNF146. In addition, we validated OTU domain-containing protein 5 and Protein mono-ADP-ribosyltransferase PARP10 as TNKS1/2-independent substrates of RNF146 and SARDH as a novel substrate of TNKS1/2 and RNF146. Our study is the first proteome-wide analysis of potential RNF146 substrates. Together, these findings not only demonstrate that proteome profiling can be a useful general approach for the systemic identification of substrates of E3 ligases but also reveal new substrates of RNF146, which provides a resource for further functional studies.

Mallory-Denk-bodies (MDBs) are hepatic protein aggregates associated with inflammation both clinically and in MDB-inducing models. Similar protein aggregation in neurodegenerative diseases also triggers inflammation and NF-B activation. However, the precise mechanism that links protein aggregation to NF-B-activation and inflammatory response remains unclear. Herein we find that treating primary hepatocytes with MDB-inducing agents (N-methylprotoporphyrin (NMPP), protoporphyrin IX (PPIX), or Zinc-protoporphyrin IX (ZnPP)) elicited an IBα-loss with consequent NF-B activation. Four known mechanisms of IBα-loss i.e. the canonical ubiquitin-dependent proteasomal degradation (UPD), autophagic-lysosomal degradation, calpain degradation and translational inhibition, were all probed and excluded. Immunofluorescence analyses of ZnPP-treated cells coupled with 8 M urea/CHAPS-extraction revealed that this IBα-loss was due to its sequestration along with IBβ into insoluble aggregates, thereby releasing NF-B. Through affinity pulldown, proximity biotinylation by antibody recognition, and other proteomic analyses, we verified that NF-B subunit p65, which stably interacts with IBα under normal conditions, no longer binds to it upon ZnPP-treatment. Additionally, we identified 10 proteins that interact with IBα under baseline conditions, aggregate upon ZnPP-treatment, and maintain the interaction with IBα after ZnPP-treatment, either by cosequestering into insoluble aggregates or through a different mechanism. Of these 10 proteins, the nucleoporins Nup153 and Nup358/RanBP2 were identified through RNA-interference, as mediators of IBα-nuclear import. The concurrent aggregation of IBα, NUP153, and RanBP2 upon ZnPP-treatment, synergistically precluded the nuclear entry of IBα and its consequent binding and termination of NF-B activation. This novel mechanism may account for the protein aggregate-induced inflammation observed in liver diseases, thus identifying novel targets for therapeutic intervention. Because of inherent commonalities this MDB cell model is a bona fide protoporphyric model, making these findings equally relevant to the liver inflammation associated with clinical protoporphyria.

At neuronal synapses, activation of group I metabotropic glutamate receptors (mGluR1/5) triggers a form of long-term depression (mGluR-LTD) that relies on new protein synthesis and the internalization of AMPA-type glutamate receptors. Dysregulation of these processes has been implicated in the development of mental disorders such as autism spectrum disorders and therefore merit a better understanding on a molecular level. Here, to study mGluR-induced signaling pathways, we integrated quantitative phosphoproteomics with the analyses of newly synthesized proteins via bio-orthogonal amino acids (azidohomoalanine) in a pulsed labeling strategy in cultured hippocampal neurons stimulated with DHPG, a specific agonist for group I mGluRs. We identified several kinases with important roles in DHPG-induced mGluR activation, which we confirmed using small molecule kinase inhibitors. Furthermore, changes in the AMPA receptor endocytosis pathway in both protein synthesis and protein phosphorylation were identified, whereby Intersectin-1 was validated as a novel player in this pathway. This study revealed several new insights into the molecular pathways downstream of group I mGluR activation in hippocampal neurons, and provides a rich resource for further analyses.

Stroke remains a leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures in the hyper-acute phase of ischemic stroke is still a primary interest for translational research on stroke diagnosis, prognosis, and treatment. Data integration from high-throughput -omics techniques has become crucial to unraveling key interactions among different molecular elements in complex biological contexts, such as ischemic stroke. Thus, we used advanced data integration methods for a multi-level joint analysis of transcriptomics and proteomics data sets obtained from mouse brains at 2 h after cerebral ischemia. By modeling net-like correlation structures, we identified an integrated network of genes and proteins that are differentially expressed at a very early stage after stroke. We validated 10 of these deregulated elements in acute stroke, and changes in their expression pattern over time after cerebral ischemia were described. Of these, CLDN20, GADD45G, RGS2, BAG5, and CTNND2 were next evaluated as blood biomarkers of cerebral ischemia in mice and human blood samples, which were obtained from stroke patients and patients presenting stroke-mimicking conditions. Our findings indicate that CTNND2 levels in blood might potentially be useful for distinguishing ischemic strokes from stroke-mimicking conditions in the hyper-acute phase of the disease. Furthermore, circulating GADD45G content within the first 6 h after stroke could also play a key role in predicting poor outcomes in stroke patients. For the first time, we have used an integrative biostatistical approach to elucidate key molecules in the initial stages of stroke pathophysiology and highlight new notable molecules that might be further considered as blood biomarkers of ischemic stroke.

Gêne constant, difficulté à respirer : avez-vous une impression de glaires coincées dans la gorge actuellement ? Cette impression peut être due à plusieurs facteurs parfois bénignes mais aussi graves. Fort heureusement, il existe quelques astuces naturelles qui vous permettront d’avoir un soulagement en attendant de consulter un médecin ORL. Mais avant, l’impression de glaires coincées dans la gorge est […]

L’article Comment se débarrasser des glaires coincées dans la gorge ? est apparu en premier sur Ortho Doc France.

Contrairement à ce qu’on pourrait croire, bien plus de femmes se préoccupent de leurs poids et y font attention. Pour ces femmes, comprendre ce qu’est un indice de masse corporelle (IMC) normal peut permettre de maintenir une bonne santé et savoir quand faire appel à un médecin pour leurs poids. C’est quoi l’IMC ou indice de masse […]

L’article Quel est l’IMC normal pour une femme ? est apparu en premier sur Ortho Doc France.

Middle East and North Africa

Research on the Middle East and North Africa region focuses on changes to politics and society, economics, and security issues.

This is a turbulent period for the region following the Arab Spring, with conflict in Syria continuing to impact its neighbours, governance in Libya under scrutiny, and increasing pressures on the Gulf monarchies, especially around human rights.   

Key research areas include the Gulf States and the Gulf Cooperation Council (GCC), the future of the state, mapping the region’s war economies, the Yemen conflict, Iraq’s reconstruction, and the influence of Saudi Arabia and Iran.

Withdrawn by Author.

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.

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.

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.

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification.

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. Mass spectrometry (MS)-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This manuscript provides a systematic review of the intact glycopeptide identification process using mass spectrometry data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

Glycopeptides in peptide or digested protein samples pose a number of analytical and bioinformatics challenges beyond those posed by unmodified peptides or peptides with smaller posttranslational modifications. Exact structural elucidation of glycans is generally beyond the capability of a single mass spectrometry experiment, so a reasonable level of identification for tandem mass spectrometry, taken by several glycopeptide software tools, is that of peptide sequence and glycan composition, meaning the number of monosaccharides of each distinct mass, for example HexNAc(2)Hex(5) rather than man5. Even at this level, however, glycopeptide analysis poses challenges:  finding glycopeptide spectra when they are a tiny fraction of the total spectra; assigning spectra with unanticipated glycans, not in the initial glycan database; and finding, scoring, and labeling diagnostic peaks in tandem mass spectra.  Here we discuss recent improvements to Byonic, a glycoproteomics search program, that address these three issues. Byonic now supports filtering spectra by m/z peaks, so that the user can limit attention to spectra with diagnostic peaks, for example, at least two out of three of 204.087 for HexNAc, 274.092 for NeuAc (with water loss), and 366.139 for HexNAc-Hex, all within a set mass tolerance, for example, ± 0.01 Daltons. Also new is glycan "wildcard" search, which allows an unspecified mass within a user-set mass range to be applied to N- or O-linked glycans and enables assignment of spectra with unanticipated glycans. Finally the next release of Byonic supports user-specified peak annotations from user-defined posttranslational modifications. We demonstrate the utility of these new software features by finding previously unrecognized glycopeptides in publicly available data, including glycosylated neuropeptides from rat brain.

This review covers recent developments in glycosaminoglycan (GAG) analysis via mass spectrometry (MS). GAGs participate in a variety of biological functions, including cellular communication, wound healing, and anticoagulation, and are important targets for structural characterization. GAGs exhibit a diverse range of structural features due to the variety of O- and N-sulfation modifications and uronic acid C-5 epimerization that can occur, making their analysis a challenging target. Mass spectrometry approaches to the structure assignment of GAGs have been widely investigated, and new methodologies remain the subject of development. Advances in sample preparation, tandem MS techniques (MS/MS), on-line separations and automated analysis software have advanced the field of GAG analysis. These recent developments have led to remarkable improvements in the precision and time efficiency for the structural characterization of GAGs.

O-GlcNAcylation, the addition of a single N-acetylglucosamine residue to serine and threonine residues of cytoplasmic, nuclear, or mitochondrial proteins, is a widespread regulatory post-translational modification. It is involved in response to nutritional status and stress and its dysregulation is associated with diseases ranging from Alzheimer’s to diabetes.  While the modification was first detected over thirty-five years ago, research into the function of O-GlcNAcylation has accelerated dramatically in the last ten years due to the development of new enrichment and mass spectrometry techniques that facilitate its analysis.  This article summarizes methods for O-GlcNAc enrichment, key mass spectrometry instrumentation advancements, particularly those that allow modification site localization, and software tools that allow analysis of data from O-GlcNAc modified peptides.

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry (MS)-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography (HILIC) and its derivatives, porous graphitic carbon (PGC), reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as MS instrumentation and software improve, so this review aims to help equip researchers with necessary information to choose appropriate enrichment strategies that best complement these efforts.

CD4+ T cell responses are crucial for inducing and maintaining effective anti-cancer immunity, and the identification of human leukocyte antigen class II (HLA-II) cancer-specific epitopes is key to the development of potent cancer immunotherapies. In many tumor types, and especially in glioblastoma (GBM), HLA-II complexes are hardly ever naturally expressed. Hence, little is known about immunogenic HLA-II epitopes in GBM. With stable expression of the class II major histocompatibility complex transactivator (CIITA) coupled to a detailed and sensitive mass spectrometry based immunopeptidomics analysis, we here uncovered a remarkable breadth of the HLA-ligandome in HROG02, HROG17 and RA GBM cell lines. The effect of CIITA expression on the induction of the HLA-II presentation machinery was striking in each of the three cell lines, and it was significantly higher compared to interferon gamma (IFN) treatment. In total, we identified 16,123 unique HLA-I peptides and 32,690 unique HLA-II peptides. In order to genuinely define the identified peptides as true HLA ligands, we carefully characterized their association with the different HLA allotypes. In addition, we identified 138 and 279 HLA-I and HLA-II ligands, respectively, most of which are novel in GBM, derived from known GBM-associated tumor-antigens that have been used as source proteins for a variety of GBM vaccines. Our data further indicate that CIITA-expressing GBM cells acquired an antigen presenting cell-like phenotype as we found that they directly present external proteins as HLA-II ligands. Not only that CIITA-expressing GBM cells are attractive models for antigen discovery endeavors, but also such engineered cells have great therapeutic potential through massive presentation of a diverse antigenic repertoire.

Regulation of gene expression is essential for the functioning of all eukaryotic organisms. Understanding gene expression regulation requires determining which proteins interact with regulatory elements in chromatin. Mass spectrometry-based analysis of chromatin has emerged as a powerful tool to identify proteins associated with gene regulation, as it allows studying protein function and protein complex formation in their in vivo chromatin-bound context. Total chromatin isolated from cells can be directly analysed using mass spectrometry or further fractionated into transcriptionally active and inactive chromatin prior to MS-based analysis. Newly formed chromatin that is assembled during DNA replication can also be specifically isolated and analysed. Furthermore, capturing specific chromatin domains facilitates the identification of previously unknown transcription factors interacting with these domains. Finally, in recent years, advances have been made towards identifying proteins that interact with a single genomic locus of interest. In this review, we highlight the power of chromatin proteomics approaches and how these provide complementary alternatives compared to conventional affinity purification methods. Furthermore, we discuss the biochemical challenges that should be addressed to consolidate and expand the role of chromatin proteomics as a key technology in the context of gene expression regulation and epigenetics research in health and disease.

The choice for adjuvant chemotherapy in stage II colorectal cancer (CRC) is controversial as many patients are cured by surgery alone and it is difficult to identify patients with high-risk of recurrence of the disease. There is a need for better stratification of this group of patients. Mass spectrometry imaging could identify patients at risk. We report here the N-glycosylation signatures of the different cell populations in a group of stage II CRC tissue samples. The cancer cells, compared to normal epithelial cells, have increased levels of sialylation and high-mannose glycans, as well as decreased levels of fucosylation and highly branched N-glycans. When looking at the interface between cancer and its microenvironment, it seems that the cancer N-glycosylation signature spreads into the surrounding stroma at the invasive front of the tumor. This finding was more outspoken in patients with a worse outcome within this sample group.

Paramphistomosis, caused by the rumen fluke, Calicophoron daubneyi, is a parasitic infection of ruminant livestock which has seen a rapid rise in prevalence throughout Western Europe in recent years. Following ingestion of metacercariae (parasite cysts) by the mammalian host, newly-excysted juveniles (NEJs) emerge and invade the duodenal submucosa which causes significant pathology in heavy infections. The immature larvae then migrate upwards, along the gastrointestinal tract, and enter the rumen where they mature and begin to produce eggs. Despite their emergence, and sporadic outbreaks of acute disease, we know little about the molecular mechanisms used by C. daubneyi to establish infection, acquire nutrients and to avoid the host immune response. Here, transcriptome analysis of four intra-mammalian life-cycle stages, integrated with secretome analysis of the NEJ and adult parasites (responsible for acute and chronic disease respectively), revealed how the expression and secretion of selected families of virulence factors and immunomodulators are regulated in accordance with fluke development and migration. Our data show that whilst a family of cathepsins B with varying S2 sub-site residues (indicating distinct substrate specificities) are differentially secreted by NEJs and adult flukes, cathepsins L and F are secreted in low abundance by NEJs only. We found that C. daubneyi has an expanded family of aspartic peptidases, which is up-regulated in adult worms, although they are underrepresented in the secretome. The most abundant proteins in adult fluke secretions were helminth defence molecules (HDMs) that likely establish an immune environment permissive to fluke survival and/or neutralise pathogen-associated molecular patterns (PAMPs) such as bacterial lipopolysaccharide in the microbiome-rich rumen. The distinct collection of molecules secreted by C. daubneyi allowed the development of the first coproantigen-based ELISA for paramphistomosis which, importantly, did not recognise antigens from other helminths commonly found as co-infections with rumen fluke.

The increasing consumption of high-fat foods combined with a lack of exercise is a major contributor to the burden of obesity in humans. Aerobic exercise such as running is known to provide metabolic benefits, but how the over-consumption of a high fat diet (HFD) and exercise interact is not well characterized at the molecular level. Here, we examined the plasma proteome in mice for the effects of aerobic exercise as both a treatment and as a preventative regime for animals on either HFD or a healthy control diet. This analysis detected large changes in the plasma proteome induced by the HFD, such as increased abundance of SERPINA7, ALDOB, and down-regulation of SERPINA1E, CFD (adipsin). Some of these changes were significantly reverted using exercise as a preventative measure, but not as a treatment regime. To determine if either the intensity, or duration, of exercise influenced the outcome, we compared high-intensity interval training (HIIT) and endurance running. Endurance running slightly out-performed HIIT exercise, but overall, both provided similar reversion in abundance of plasma proteins modulated by the high-fat diet including SERPINA7, APOE, SERPINA1E, and CFD. Finally, we compared the changes induced by over-consumption of HFD to previous data from mice fed an isocaloric high saturated fat (SFA) or polyunsaturated fat (PUFA) diet. This identified several common changes including increased APOC2 and APOE, but also highlighted changes specific for either over-consumption of HFD (ALDOB, SERPINA7, CFD), SFA-based diets (SERPINA1E), or PUFA-based diets (Haptoglobin - Hp). Together, these data highlight the importance of early intervention with exercise to revert HFD-induced phenotypes and suggest some of the molecular mechanisms leading to the changes in the plasma proteome generated by high fat diet consumption. Web-based interactive visualizations are provided for this dataset (larancelab.com/hfd-exercise), which give insight into diet and exercise phenotypic interactions on the plasma proteome.

Biological functions emerge from complex and dynamic networks of protein-protein interactions. Because these protein-protein interaction networks, or interactomes, represent pairwise connections within a hierarchically organized system, it is often useful to identify higher-order associations embedded within them, such as multi-member protein complexes. Graph-based clustering techniques are widely used to accomplish this goal, and dozens of field-specific and general clustering algorithms exist. However, interactomes can be prone to errors, especially when inferred from high-throughput biochemical assays. Therefore, robustness to network-level noise is an important criterion for any clustering algorithm that aims to generate robust, reproducible clusters. Here, we tested the robustness of a range of graph-based clustering algorithms in the presence of noise, including algorithms common across domains and those specific to protein networks. Strikingly, we found that all of the clustering algorithms tested here markedly amplified noise within the underlying protein interaction network. Randomly rewiring only 1% of network edges yielded more than a 50% change in clustering results, indicating that clustering markedly amplified network-level noise. Moreover, we found the impact of network noise on individual clusters was not uniform: some clusters were consistently robust to injected noise while others were not. To assist in assessing this, we developed the clust.perturb R package and Shiny web application to measure the reproducibility of clusters by randomly perturbing the network. We show that clust.perturb results are predictive of real-world cluster stability: poorly reproducible clusters as identified by clust.perturb are significantly less likely to be reclustered across experiments. We conclude that graph-based clustering amplifies noise in protein interaction networks, but quantifying the robustness of a cluster to network noise can separate stable protein complexes from spurious associations.

Protease activity has been associated with pathological processes that can lead to cancer development and progression. However, understanding the pathological unbalance in proteolysis is challenging since changes can occur simultaneously at protease, their inhibitor and substrate levels. Here, we present a pipeline that combines peptidomics, proteomics and peptidase predictions for studying proteolytic events in the saliva of seventy-nine patients and their association with oral squamous cell carcinoma (OSCC) prognosis. Our findings revealed differences in the saliva peptidome of patients with (pN+) or without (pN0) lymph node metastasis and delivered a panel of ten endogenous peptides correlated with poor prognostic factors plus five molecules able to classify pN0 and pN+ patients (ROC-AUC>0.85). In addition, endo- and exopeptidases putatively implicated in the processing of differential peptides were investigated using cancer tissue gene expression data from publicly repositories reinforcing their association with poorer survival rates and prognosis in oral cancer. The dynamics of the OSCC-related proteolysis was further explored via the proteomic profiling of saliva. This revealed that peptidase/endopeptidase inhibitors exhibited reduced levels in the saliva of pN+ patients, as confirmed by SRM-MS, whilst minor changes were detected in the level of saliva proteases. Taken together, our results indicated that proteolytic activity is accentuated in the saliva of OSCC patients with lymph node metastasis and, at least in part, this is modulated by reduced levels of salivary peptidase inhibitors. Therefore, this integrated pipeline provided better comprehension and discovery of molecular features with implications in the oral cancer metastasis prognosis.

Modulation of the host cell is integral to the survival and replication of microbial pathogens. Several intracellular bacterial pathogens deliver bacterial proteins, termed ‘effector proteins’ into the host cell during infection by sophisticated protein translocation systems, which manipulate cellular processes and functions. The functional contribution of individual effectors is poorly characterised, particularly in intracellular bacterial pathogens with large effector protein repertoires. Technical caveats have limited the capacity to study these proteins during a native infection, with many effector proteins having only been demonstrated to be translocated during over-expression of tagged versions. Here we developed a novel strategy to examine effector proteins in the context of infection. We coupled a broad, unbiased proteomics-based screen with organelle purification to study the host-pathogen interactions occurring between the host cell mitochondrion and the Gram-negative, Q fever pathogen Coxiella burnetii. We identify 4 novel mitochondrially-targeted C. burnetii effector proteins, renamed Mitochondrial Coxiella effector protein (Mce) B to E. Examination of the subcellular localisation of ectopically expressed proteins confirmed their mitochondrial localisation, demonstrating the robustness of our approach. Subsequent biochemical analysis and affinity enrichment proteomics of one of these effector proteins, MceC, revealed the protein localises to the inner membrane and can interact with components of the mitochondrial quality control machinery. Our study adapts high-sensitivity proteomics to study intracellular host-pathogen interactions, providing a robust strategy to examine the sub-cellular localisation of effector proteins during native infection. This approach could be applied to a range of pathogens and host cell compartments to provide a rich map of effector dynamics throughout infection.

Thyroglobulin (Tg) is a secreted iodoglycoprotein serving as the precursor for T3 and T4 hormones. Many characterized Tg gene mutations produce secretion-defective variants resulting in congenital hypothyroidism (CH). Tg processing and secretion is controlled by extensive interactions with chaperone, trafficking, and degradation factors comprising the secretory proteostasis network. While dependencies on individual proteostasis network components are known, the integration of proteostasis pathways mediating Tg protein quality control and the molecular basis of mutant Tg misprocessing remain poorly understood. We employ a multiplexed quantitative affinity purification–mass spectrometry approach to define the Tg proteostasis interactome and changes between WT and several CH-variants. Mutant Tg processing is associated with common imbalances in proteostasis engagement including increased chaperoning, oxidative folding, and engagement by targeting factors for ER-associated degradation (ERAD). Furthermore, we reveal mutation-specific changes in engagement with N-glycosylation components, suggesting distinct requirements for one Tg variant on dual engagement of both oligosaccharyltransferase complex isoforms for degradation. Modulating dysregulated proteostasis components and pathways may serve as a therapeutic strategy to restore Tg secretion and thyroid hormone biosynthesis.

Gonadal soma-derived factor (gsdf) has been demonstrated to be essential for testicular differentiation in medaka (Oryzias latipes). To understand the protein dynamics of Gsdf in spermatogenesis regulation, we used a His-tag "pull-down" assay coupled with shotgun LC-MS/MS to identify a group of potential interacting partners for Gsdf, which included cytoplasmic dynein light chain 2, eukaryotic polypeptide elongation factor 1 alpha (eEF1α), and actin filaments in mature medaka testis. As for the interaction with TGFβ-dynein being critical for spermatogonial division in Drosophila melanogaster, the physical interactions of Gsdf-dynein and Gsdf-eEF1α were identified through a yeast 2-hybrid (Y2H) screening of an adult testis cDNA library using Gsdf as bait, which were verified by a paired Y2H assay. Co-immunoprecipitation of Gsdf and eEF1α was defined in adult testes as supporting the requirement of a Gsdf and eEF1α interaction in testis development. Proteomics analysis (data are available via ProteomeXchange with identifier PXD022153) and ultrastrutural observations showed that Gsdf deficiency activated eEF1α-mediated protein synthesis and ribosomal biogenesis, which in turn led to the differentiation of undifferentiated germ cells. Thus, our results provide a framework and new insight into the coordination of a Gsdf (TGFβ and eEF1α complex in the basic processes of germ cell proliferation, transcriptional and translational control of sexual RNA which may be fundamentally conserved across phyla during sexual differentiation.

The goal of clinical proteomics is to identify, quantify, and characterize proteins in body fluids or tissue to assist diagnosis, prognosis, and treatment of patients. In this way, it is similar to more mature omics technologies, such as genomics, that are increasingly applied in biomedicine. We argue that, similar to those fields, proteomics also faces ethical issues related to the kinds of information that is inherently obtained through sample measurement, although their acquisition was not the primary purpose. Specifically, we demonstrate the potential to identify individuals both by their characteristic, individual-specific protein levels and by variant peptides reporting on coding single nucleotide polymorphisms. Furthermore, it is in the nature of blood plasma proteomics profiling that it broadly reports on the health status of an individual – beyond the disease under investigation. Finally, we show that private and potentially sensitive information, such as ethnicity and pregnancy status, can increasingly be derived from proteomics data. Although this is potentially valuable not only to the individual, but also for biomedical research, it raises ethical questions similar to the incidental findings obtained through other omics technologies. We here introduce the necessity of - and argue for the desirability for - ethical and human rights-related issues to be discussed within the proteomics community. Those thoughts are more fully developed in our accompanying manuscript. Appreciation and discussion of ethical aspects of proteomic research will allow for deeper, better-informed, more diverse, and, most importantly, wiser guidelines for clinical proteomics.

Urinary proteomics studies have primarily focused on identifying markers of chronic kidney disease (CKD) progression. Here, we aimed to determine urinary markers of CKD renal parenchymal injury through proteomics analysis in animal kidney tissues and cells and in the urine of patients with CKD. Label-free quantitative proteomics analysis based on liquid chromatography-tandem mass spectrometry was performed on urine samples obtained from 6 normal controls and 9, 11, and 10 patients with CKD stages 1, 3, and 5, respectively, and on kidney tissue samples from a rat CKD model by 5/6 nephrectomy. Tandem mass tag-based quantitative proteomics analysis was performed for primary cultured glomerular endothelial cells (GECs) and proximal tubular epithelial cells (PTECs) before and after inducing 24-h hypoxia injury. Upon hierarchical clustering, out of 858 differentially expressed proteins (DEPs) in the urine of CKD patients, the levels of 416 decreased and 403 increased sequentially according to the disease stage, respectively. Among 2965 DEPs across 5/6 nephrectomized and sham-operated rat kidney tissues, 86 DEPs showed same expression patterns in the urine and kidney tissue. After cross-validation with two external animal proteome datasets, 38 DEPs were organized; only 10 DEPs, including serotransferrin, gelsolin, poly ADP-ribose polymerase 1, neuroblast differentiation-associated protein AHNAK, microtubule-associated protein 4, galectin-1, protein S, thymosin beta-4, myristoylated alanine-rich C-kinase substrate, and vimentin were finalized by screening human GECs and PTECs data. Among these ten potential candidates for universal CKD marker, validation analyses for protein S and galectin-1 were conducted. Galectin-1 was observed to have a significant inverse correlation with renal function as well as higher expression in glomerulus with chronic injury than protein S. This constitutes the first multi-sample proteomics study for identifying key renal-expressed proteins associated with CKD progression. The discovered proteins represent potential markers of chronic renal cell and tissue damage and candidate contributors to CKD pathophysiology.

Sporozoites are a motile form of malaria-causing Plasmodium falciparum parasites that migrate from the site of transmission in the dermis through the bloodstream to invade hepatocytes. Sporozoites interact with many cells within the host, but the molecular identity of these interactions and their role in the pathology of malaria is poorly understood. Parasite proteins that are secreted and embedded within membranes are known to be important for these interactions, but our understanding of how they interact with each other to form functional complexes is largely unknown. Here, we compile a library of recombinant proteins representing the repertoire of cell surface and secreted proteins from the P. falciparum sporozoite and use an assay designed to detect extracellular interactions to systematically identify complexes. We identify three protein complexes including an interaction between two components of the p24 complex that is involved in the trafficking of glycosylphosphatidylinositol (GPI)-anchored proteins through the secretory pathway. Plasmodium parasites lacking either gene are strongly inhibited in the establishment of liver stage infections. These findings reveal an important role for the p24 complex in malaria pathogenesis and show that the library of recombinant proteins represents a valuable resource to investigate P. falciparum sporozoite biology.

Data independent acquisition (DIA) is now an emerging method in bottom-up proteomics and capable of achieving deep proteome coverage and accurate label-free quantification. However, for post-translational modifications (PTM), such as glycosylation, DIA methodology is still in the early stage of development. The full characterization of glycoproteins requires site specific glycan identification as well as subsequent quantification of glycan structures at each site. The tremendous complexity of glycosylation represents a significant analytical challenge in glycoproteomics. This review focuses on the development and perspectives of DIA methodology for N- and O- glycoproteomics and posits that DIA-based glycoproteomics could be a method of choice to address some of the challenging aspects of glycoproteomics. First, the current challenges in glycoproteomics and the basic principles of DIA is briefly introduced. DIA based glycoproteomics is then summarized and described into four aspects based on the actual samples. Lastly, we discussed the important challenges and future perspectives in the field. We believe that DIA can significantly facilitate glycoproteomic studies and contribute to the development of future advanced tools and approaches in the field of glycoproteomics.

The F-box protein MORE AXILLARY GROWTH 2 (MAX2) is a central component in the signaling cascade of strigolactones (SLs) as well as of the smoke derived karrikins (KARs) and the so far unknown endogenous KAI2 ligand (KL). The two groups of molecules are involved in overlapping and unique developmental processes, and signal-specific outcomes are attributed to perception by the paralogous α/β-hydrolases DWARF14 (D14) for SL and KARRIKIN INSENSITIVE 2/ HYPOSENSITIVE TO LIGHT (KAI2/HTL) for KAR/KL. Additionally, depending on which receptor is activated, specific members of the SUPPRESSOR OF MAX2 1 (SMAX1) – LIKE (SMXL) family control KAR/KL and SL responses. As proteins that function in the same signal transduction pathway often occur in large protein complexes, we aimed at discovering new players of the MAX2, D14 and KAI2 protein network by tandem affinity purification using Arabidopsis cell cultures. When using MAX2 as a bait, various proteins were co-purified among which general components of the Skp1-Cullin-F-box complex and members of the CONSTITUTIVE PHOTOMORPHOGENIC 9 signalosome. Here, we report the identification of a novel interactor of MAX2, a type 5 serine/threonine protein phosphatase, designated PHYTOCHROME-ASSOCIATED PROTEIN PHOSPHATASE 5 (PAPP5). Quantitative affinity purification pointed at PAPP5 as being more present in KAI2 rather than D14 protein complexes. In agreement, mutant analysis suggests that PAPP5 modulates KAR/KL-dependent seed germination in suboptimal conditions and seedling development. Additionally, a phosphopeptide enrichment experiment revealed that PAPP5 might dephosphorylate MAX2 in vivo independently of the synthetic strigolactone analog, rac-GR24. Together, by analyzing the protein complexes to which MAX2, D14 and KAI2 belong, we revealed a new MAX2 interactor, PAPP5, that might act through dephosphorylation of MAX2 to control mainly KAR/KL- related phenotypes and, hence, provide another link with the light pathway.

Cells continually degrade and replace damaged proteins. However, the high energetic demand of protein turnover generates reactive oxygen species (ROS) that compromise the long-term health of the proteome. Thus, the relationship between aging, protein turnover and energetic demand remains unclear. Here, we used a proteomic approach to measure rates of protein turnover within primary fibroblasts isolated from a number of species with diverse lifespans including the longest-lived mammal, the bowhead whale. We show that organismal lifespan is negatively correlated with turnover rates of highly abundant proteins. In comparison to mice, cells from long-lived naked mole rats have slower rates of protein turnover, lower levels of ATP production and reduced ROS levels. Despite having slower rates of protein turnover, naked mole rat cells tolerate protein misfolding stress more effectively than mouse cells. We suggest that in lieu of rapid constitutive turnover, long-lived species may have evolved more energetically efficient mechanisms for selective detection and clearance of damaged proteins.

Alpha-1-acid glycoprotein (AGP) is an acute phase glycoprotein in blood, which is primarily synthetized in the liver and whose biological role is not completely understood. It consists of 45% carbohydrates that are present in the form of five N-linked complex glycans. AGP N-glycosylation was shown to be changed in many different diseases and some changes appear to be disease-specific, thus it has a great diagnostic and prognostic potential. However, AGP glycosylation was mainly analyzed in small cohorts and without detailed site-specific glycan information. Here, we developed a cost-effective method for a high-throughput and site-specific N-glycosylation LC-MS analysis of AGP which can be applied on large cohorts, aid in search for novel disease biomarkers and enable better understanding of AGP’s role and function in health and disease. The method does not require isolation of AGP with antibodies and affinity chromatography, but AGP is enriched by acid precipitation from 5 μl of bloodplasma in a 96 well format. After trypsinization, AGP glycopeptides are purified using a hydrophilic interaction chromatography based solid-phase extraction and analyzed by RP-LC-ESI-MS. We used our method to show for the first time that AGP N-glycan profile is stable in healthy individuals (14 individuals in 3 time points), which is a requirement for evaluation of its diagnostic potential. Furthermore, we tested our method on a population including individuals with registered hyperglycemia in critical illness (59 cases and 49 controls), which represents a significantly increased risk of developing type 2 diabetes. Individuals at higher risk of diabetes presented increased N-glycan branching on AGP’s second glycosylation site and lower sialylation of N-glycans on AGP’s third and AGP1’s fourth glycosylation site. Although this should be confirmed on a larger prospective cohort, it indicates that site-specific AGP N-glycan profile could help distinguish individuals who are at risk of type 2 diabetes.