Identification of inositol 1,4,5‐trisphosphate‐binding proteins by heparin‐agarose affinity purification and LTQ ORBITRAP MS in Oryza sativa

Inositol 1,4,5‐trisphosohate (IP₃) and its receptors play a pivotal role in calcium signal transduction in mammals. However, no homologs of mammalian IP₃ receptors have been found in plants. In this study, we isolated the microsomal fractions from rice cells in suspension culture and further obtained putative IP₃‐binding proteins by heparin‐agarose affinity purification. The IP₃‐binding activities of these protein fractions were determined by [³H] IP₃‐binding assay. SDS‐PAGE and MS analysis were then performed to characterize these proteins. We have identified 297 proteins from the eluates of heparin‐agarose column chromatography, which will provide insight into the IP₃ signaling pathways in plants. All MS data have been deposited in the ProteomeXchange with identifier PXD000763 ( http://proteomecentral.proteomexchange.org/dataset/PXD000763 ).     

Glucosyltransferase‐dependent and ‐independent effects of TcdB on the proteome of HEp‐2 cells

Toxin B (TcdB) of the nosocomial pathogen C. difficile has been reported to exhibit a glucosyltransferase‐dependent and ‐independent effect on treated HEp‐2 cells at toxin concentration above 0.3 nM. In order to investigate and further characterize both effects epithelial cells were treated with wild type TcdB and glucosyltransferase‐deficient TcdB_NXN and their proteomes were analyzed by LC‐MS. Triplex SILAC labeling was used for quantification. Identification of 5212 and quantification of 4712 protein groups was achieved. Out of these 257 were affected by TcdB treatment, 92 by TcdB_NXN treatment and 49 by both. TcdB mainly led to changes in proteins that are related to “GTPase mediated signaling” and the “cytoskeleton” while “chromatin” and “cell cycle” related proteins were altered by both, TcdB and TcdB_NXN. The obtained dataset of HEp‐2 cell proteome helps us to better understand glucosyltransferase‐dependent and ‐independent mechanisms of TcdB and TcdB_NXN, particularly those involved in pyknotic cell death. All proteomics data have been deposited in the ProteomeXchange with the dataset identifier PXD006658 ( https://proteomecentral.proteomexchange.org/dataset/PXD006658 ).     

In‐depth characterization of the tomato fruit pericarp proteome

Since the genome of Solanum lycopersicum L. was published in 2012, some studies have explored its proteome although with a limited depth. In this work, we present an extended characterization of the proteome of the tomato pericarp at its ripe red stage. Fractionation of tryptic peptides generated from pericarp proteins by off‐line high‐pH reverse‐phase phase chromatography in combination with LC‐MS/MS analysis on a Fisher Scientific Q Exactive and a Sciex Triple‐TOF 6600 resulted in the identification of 8588 proteins with a 1% FDR both at the peptide and protein levels. Proteins were mapped through GO and KEGG databases and a large number of the identified proteins were associated with cytoplasmic organelles and metabolic pathways categories. These results constitute one of the most extensive proteome datasets of tomato so far and provide an experimental confirmation of the existence of a high number of theoretically predicted proteins. All MS data are available in the ProteomeXchange repository with the dataset identifiers PXD004947 and PXD004932.     

The advantage of laser‐capture microdissection over whole tissue analysis in proteomic profiling studies

Laser‐capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label‐free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p‐value < 0.001). 2D analysis on co‐expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 ( http://proteomecentral.proteomexchange.org/dataset/PXD002381 ).     

Distinct serum proteome profiles associated with collagen‐induced arthritis and complete Freund's adjuvant‐induced inflammation in CD38−/− mice: The discriminative power of protein species or proteoforms

Collagen‐type‐II‐induced arthritis (CIA) is an autoimmune disease, which involves a complex host systemic response including inflammatory and autoimmune reactions. CIA is milder in CD38^?/? than in wild‐type (WT) mice. ProteoMiner‐equalized serum samples were subjected to 2D‐DiGE and MS‐MALDI‐TOF/TOF analyses to identify proteins that changed in their relative abundances in CD38^?/? versus WT mice either with arthritis (CIA⁺), with no arthritis (CIA^?), or with inflammation (complete Freund's adjuvant (CFA)‐treated mice). Multivariate analyses revealed that a multiprotein signature (n = 28) was able to discriminate CIA⁺ from CIA^? mice, and WT from CD38^?/? mice within each condition. Likewise, a distinct multiprotein signature (n = 16) was identified which differentiated CIA⁺ CD38^?/? mice from CIA⁺ WT mice, and lastly, a third multiprotein signature (n = 18) indicated that CD38^?/? and WT mice could be segregated in response to CFA treatment. Further analyses showed that the discriminative power to distinguish these groups was reached at protein species level and not at the protein level. Hence, the need to identify and quantify proteins at protein species level to better correlate proteome changes with disease processes. It is crucial for plasma proteomics at the low‐abundance protein species level to apply the ProteoMiner enrichment. All MS data have been deposited in the ProteomeXchange with identifiers PXD001788, PXD001799 and PXD002071 ( http://proteomecentral.proteomexchange.org/dataset/PXD001788 , http://proteomecentral.proteomexchange.org/dataset/PXD001799 and http://proteomecentral.proteomexchange.org/dataset/PXD002071 ).     

Comparative phosphoproteomic analysis of mammalian glomeruli reveals conserved podocin C‐terminal phosphorylation as a determinant of slit diaphragm complex architecture

Glomerular biology is dependent on tightly controlled signal transduction networks that control phosphorylation of signaling proteins such as cytoskeletal regulators or slit diaphragm proteins of kidney podocytes. Cross‐species comparison of phosphorylation events is a powerful mean to functionally prioritize and identify physiologically meaningful phosphorylation sites. Here, we present the result of phosphoproteomic analyses of cow and rat glomeruli to allow cross‐species comparisons. We discovered several phosphorylation sites with potentially high biological relevance, e.g. tyrosine phosphorylation of the cytoskeletal regulator synaptopodin and the slit diaphragm protein neph‐1 (Kirrel). Moreover, cross‐species comparisons revealed conserved phosphorylation of the slit diaphragm protein nephrin on an acidic cluster at the intracellular terminus and conserved podocin phosphorylation on the very carboxyl terminus of the protein. We studied a highly conserved podocin phosphorylation site in greater detail and show that phosphorylation regulates affinity of the interaction with nephrin and CD2AP. Taken together, these results suggest that species comparisons of phosphoproteomic data may reveal regulatory principles in glomerular biology. All MS data have been deposited in the ProteomeXchange with identifier PXD001005 ( http://proteomecentral.proteomexchange.org/dataset/PXD001005 ).     

Proteomic and phosphoproteomic analyses of yeast reveal the global cellular response to sphingolipid depletion

Sphingolipids are essential components of eukaryotic cells with important functions in membrane biology and cellular signaling. Their levels are tightly controlled and coordinated with the abundance of other membrane lipids. How sphingolipid homeostasis is achieved is not yet well understood. Studies performed primarily in yeast showed that the phosphorylation states of several enzymes and regulators of sphingolipid synthesis are important, although a global understanding for such regulation is lacking. Here, we used high‐resolution MS‐based proteomics and phosphoproteomics to analyze the cellular response to sphingolipid synthesis inhibition. Our dataset reveals that changes in protein phosphorylation, rather than protein abundance, dominate the response to blocking sphingolipid synthesis. We identified Ypk signaling as a pathway likely to be activated under these conditions, and we identified potential Ypk1 target proteins. Our data provide a rich resource for on‐going mechanistic studies of key elements of the cellular response to the depletion of sphingolipid levels and the maintenance of sphingolipid homeostasis. All MS data have been deposited in the ProteomeXchange with identifier PXD003854 ( http://proteomecentral.proteomexchange.org/dataset/PXD003854 ).     

Copper stress‐induced changes in leaf soluble proteome of Cu‐sensitive and tolerant Agrostis capillaris L. populations

Changes in leaf soluble proteome were explored in 3‐month‐old plants of metallicolous (M) and nonmetallicolous (NM) Agrostis capillaris L. populations exposed to increasing Cu concentrations (1–50 μM) to investigate molecular mechanisms underlying plant responses to Cu excess and tolerance of M plants. Plants were cultivated on perlite (CuSO₄ spiked‐nutrient solution). Soluble proteins, extracted by the trichloroacetic acid/acetone procedure, were separated with 2‐DE (linear 4–7 pH gradient). Analysis of CCB‐stained gels (PDQuest) reproducibly detected 214 spots, and 64 proteins differentially expressed were identified using LC‐MS/MS. In both populations, Cu excess impacted both light‐dependent (OEE, cytochrome b6‐f complex, and chlorophyll a‐b binding protein), and ‐independent (RuBisCO) photosynthesis reactions, more intensively in NM leaves (ferredoxin‐NADP reductase and metalloprotease FTSH2). In both populations, upregulation of isocitrate dehydrogenase and cysteine/methionine synthases respectively suggested increased isocitrate oxidation and enhanced need for S‐containing amino‐acids, likely for chelation and detoxification. In NM leaves, an increasing need for energetic compounds was indicated by the stimulation of ATPases, glycolysis, pentose phosphate pathway, and Calvin cycle enzymes; impacts on protein metabolism and oxidative stress increase were respectively suggested by the rise of chaperones and redox enzymes. Overexpression of a HSP70 may be pivotal for M Cu tolerance by protecting protein metabolism. All MS data have been deposited in the ProteomeXchange with the dataset identifier PXD001930 ( http//proteomecentral.proteomexchange.org/dataset/PXD001930 ).     

Proteomic analysis of mouse astrocytes and their secretome by a combination of FASP and StageTip‐based,high pH,reversed‐phase fractionation

Astrocytes are the most abundant cells in the CNS, but their function remains largely unknown. Characterization of the whole‐cell proteome and secretome in astrocytes would facilitate the study of their functions in various neurodegenerative diseases and astrocyte–neuron communication. To build a reference proteome, we established a C8‐D1A astrocyte proteome to a depth of 7265 unique protein groups using a novel strategy that combined two‐step digestion, filter‐aided sample preparation, StageTip‐based high pH fractionation, and high‐resolution MS. Nearly, 6000 unique protein groups were identified from conditioned media of astrocyte cultures, constituting the largest astrocyte secretome that has been reported. High‐confidence whole‐cell proteomes and secretomes are valuable resources in studying astrocyte function by label‐free quantitation and bioinformatics analysis. All MS data have been deposited in the ProteomeXchange with identifier PXD000501 ( http://proteomecentral.proteomexchange.org/dataset/PXD000501 ).     

Protein 2DE reference map of the anterior midgut of the blood‐sucking bug Rhodnius prolixus

Rhodnius prolixus is an important vector of Trypanosoma cruzi, the causative agent of Chagas’ disease, an illness that affects 20% of Latin America population. The obligatory course of the parasite in the vector digestive tract has made it an important target for investigation in order to control the parasite transmission and thus interrupt its biological cycle in the insect vector. Therefore, an insight into the vector midgut physiology is valuable for insect control as well as to provide potential novel targets for drugs and vaccines development and thus disease treatment. In this study, the first 2DE map of R. prolixus anterior midgut is described. Proteins were separated by 2DE and analyzed by nano‐LC MS/MS. The results yielded 489 proteins from 475 spots. These proteins were classified into 28 functional groups and their physiological roles in the insect midgut are discussed. All MS data have been deposited in the ProteomeXchange with identifiers PXD001488 and PXD001489 ( http://proteomecentral.proteomexchange.org/dataset/PXD001488 , http://proteomecentral.proteomexchange.org/dataset/PXD001489 ).     

Spectral Libraries for SWATH‐MS Assays for Drosophila melanogaster and Solanum lycopersicum

Quantitative proteomics methods have emerged as powerful tools for measuring protein expression changes at the proteome level. Using MS‐based approaches, it is now possible to routinely quantify thousands of proteins. However, prefractionation of the samples at the protein or peptide level is usually necessary to go deep into the proteome, increasing both MS analysis time and technical variability. Recently, a new MS acquisition method named SWATH is introduced with the potential to provide good coverage of the proteome as well as a good measurement precision without prior sample fractionation. In contrast to shotgun‐based MS however, a library containing experimental acquired spectra is necessary for the bioinformatics analysis of SWATH data. In this study, spectral libraries for two widely used models are built to study crop ripening or animal embryogenesis, Solanum lycopersicum (tomato) and Drosophila melanogaster, respectively. The spectral libraries comprise fragments for 5197 and 6040 proteins for S. lycopersicum and D. melanogaster, respectively, and allow reproducible quantification for thousands of peptides per MS analysis. The spectral libraries and all MS data are available in the MassIVE repository with the dataset identifiers MSV000081074 and MSV000081075 and the PRIDE repository with the dataset identifiers PXD006493 and PXD006495.     

In‐depth characterization of the secretome of mouse CNS cell lines by LC‐MS/MS without prefractionation

Microglia, astrocytes, and neurons, which have important functions in the central nervous system (CNS), communicate mutually to generate a signal through secreted proteins or small molecules, but many of which have not been identified. Because establishing a reference for the secreted proteins from CNS cells could be invaluable in examining cell‐to‐cell communication in the brain, we analyzed the secretome of three murine CNS cell lines without prefractionation by high‐resolution mass spectrometry. In this study, 2795 proteins were identified from conditioned media of the three cell lines, and 2125 proteins were annotated as secreted proteins by bioinformatics analysis. Further, approximately 500 secreted proteins were quantifiable as differentially expressed proteins by label‐free quantitation. As a result, our secretome references are useful datasets for the future study of neuronal diseases. All MS data have been deposited in the ProteomeXchange with identifier PXD001597 ( http://proteomecentral.proteomexchange.org/dataset/PXD001597 ).     

Quantitative phosphoproteomic analysis of the PI3K‐regulated signaling network

The PI3K pathway is commonly activated in cancer. Only a few studies have attempted to explore the spectrum of phosphorylation signaling downstream of the PI3K cascade. Such insight, however, is imperative to understand the mechanisms responsible for oncogenic phenotypes. By applying MS‐based phosphoproteomics, we mapped 2509 phosphorylation sites on 1096 proteins, and quantified their responses to activation or inhibition of PIK3CA using isogenic knock‐in derivatives and a series of targeted inhibitors. We uncovered phosphorylation changes in a wide variety of proteins involved in cell growth and proliferation, many of which have not been previously associated with PI3K signaling. A significant update of the posttranslational modification database PHOSIDA ( http://www.phosida.com ) allows efficient use of the data. All MS data have been deposited in the ProteomeXchange with identifier PXD003899 ( http://proteomecentral.proteomexchange.org/dataset/PXD003899 ).     

Proteomic analysis of N‐glycosylation of human seminal plasma

Seminal plasma is a mixture of secretions from several male accessory glands. The seminal plasma contains many secreted proteins which are important for sperm function and male fertility. In this study, we employed N‐linked glycosylated peptide enrichment, combined with LC–MS/MS analysis, and establish the first large scale N‐linked glycoproteome of human seminal plasma. Combined with the results of five biological replicates, a total of 720 N‐glycosylated sites on 372 proteins were identified. Analysis of variations among five individuals revealed similar compositions of N‐glycosylated proteins in seminal plasma. The N‐linked glycoproteome could help us understanding the biological functions of human seminal plasma. The data set could also be a resource for further screening of biomarkers for male diseases including cancer and infertility at the level of N‐glycosylation. For example, N‐glycosylated prostate‐specific antigen is known to be an efficient biomarker that can distinguish benign prostate hyperplasia from prostate cancer. All MS data have been deposited in the ProteomeXchange with identifier PXD000959 ( http://proteomecentral.proteomexchange.org/dataset/PXD000959 ).     

Proteomic profiles of human lung adeno and squamous cell carcinoma using super‐SILAC and label‐free quantification approaches

Nonsmall cell lung cancer (NSCLC) accounts for 85% of lung cancers, and is subdivided into two major histological subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). There is an unmet need to further subdivide NSCLC according to distinctive molecular features that may be associated with responsiveness to therapies. Four primary tumor‐derived xenograft proteomes (two‐each ADC and SCC) were quantitatively compared by using a super‐SILAC labeling approach together with ultrahigh‐resolution MS. Proteins highly differentially expressed in the two subtypes were identified, including 30 that were validated in an independent cohort of 12 NSCLC primary tumor‐derived xenograft tumors whose proteomes were quantified by an alternative, label‐free shotgun MS methodology. The 30‐protein signature contains metabolism enzymes including phosphoglycerate dehydrogenase, which is more highly expressed in SCC, as well as a comprehensive set of cytokeratins and other components of the epithelial barrier, which is therefore distinctly different between ADC and SCC. These results demonstrate the utility of the super‐SILAC method for the characterization of primary tissues, and compatibility with datasets derived from different MS‐based platforms. The validation of proteome signatures of NSCLC subtypes supports the further development and application of MS‐based quantitative proteomics as a basis for precision classifications and treatments of tumors. All MS data have been deposited in the ProteomeXchange with identifier PXD000438 ( http://proteomecentral.proteomexchange.org/dataset/PXD000438 ).     

Proteome and carbon flux analysis of Pseudomonas aeruginosa clinical isolates from different infection sites

Pseudomonas aeruginosa is known as opportunistic pathogen frequently isolated from different infection sites. To investigate the expression rates of P. aeruginosa proteins commonly expressed by different clinical isolates, absolute protein quantities were determined employing a gel‐free and data‐independent LC‐IMS^E approach. Moreover, the metabolic diversity of these isolates was investigated by ¹³C‐metabolic flux analyses. 812 proteins were reproducibly identified and absolutely quantified for the reference strain P. aeruginosa PAO1, 363 of which were also identified and relatively quantified in all isolates. Whilst the majority of these proteins were expressed in constant amounts, expression rates of 42 proteins were highly variable between the isolates. Notably, the outer membrane protein OprH and the response regulator PhoP were strongly expressed in burned wounds isolates compared to lung/urinary tract isolates. Moreover, proteins involved in iron/amino acids uptake were found to be highly abundant in urinary tract isolates. The fluxome data revealed a conserved glycolysis, and a niche‐specific divergence in fluxes through the glyoxylate shunt and the TCA cycle among the isolates. The integrated proteome/fluxome analysis did not indicate straightforward correlation between the protein amount and flux, but rather points to additional layers of regulation that mediate metabolic adaption of P. aeruginosa to different host environments. All MS data have been deposited in the ProteomeXchange with identifier PXD002373 ( http://proteomecentral.proteomexchange.org/dataset/PXD002373 ).