pinecone/core-2020-05-10-deduplication huggingface dataset:
Visualisation of proteomics data using R and Bioconductor

Data visualization plays a key role in high-throughput biology. It is an essential tool for data exploration allowing to shed light on data structure and patterns of interest. Visualization is also of paramount importance as a form of communicating data to a broad audience. Here, we provided a short overview of the application of the R software to the visualization of proteomics data. We present a summary of R's plotting systems and how they are used to visualize and understand raw and processed MS-based proteomics data.LG was supported by the
European Union 7th Framework Program (PRIME-XS project,
grant agreement number 262067) and a BBSRC Strategic Longer
and Larger grant (Award BB/L002817/1). LMB was supported
by a BBSRC Tools and Resources Development Fund (Award
BB/K00137X/1). TN was supported by a ERASMUS Placement
scholarship.This is the final published version of the article. It was originally published in Proteomics (PROTEOMICS Special Issue: Proteomics Data Visualisation Volume 15, Issue 8, pages 1375–1389, April 2015. DOI: 10.1002/pmic.201400392). The final version is available at http://onlinelibrary.wiley.com/doi/10.1002/pmic.201400392/abstract
Version 4.0 of PaxDb: Protein abundance data, integrated across model organisms, tissues, and cell-lines

Protein quantification at proteome-wide scale is an important aim, enabling insights into fundamental cellular biology and serving to constrain experiments and theoretical models. While proteome-wide quantification is not yet fully routine, many datasets approaching proteome-wide coverage are becoming available through biophysical and MS techniques. Data of this type can be accessed via a variety of sources, including publication supplements and online data repositories. However, access to the data is still fragmentary, and comparisons across experiments and organisms are not straightforward. Here, we describe recent updates to our database resource "PaxDb" (Protein Abundances Across Organisms). PaxDb focuses on protein abundance information at proteome-wide scope, irrespective of the underlying measurement technique. Quantification data is reprocessed, unified, and quality-scored, and then integrated to build a meta-resource. PaxDb also allows evolutionary comparisons through precomputed gene orthology relations. Recently, we have expanded the scope of the database to include cell-line samples, and more systematically scan the literature for suitable datasets. We report that a significant fraction of published experiments cannot readily be accessed and/or parsed for quantitative information, requiring additional steps and efforts. The current update brings PaxDb to 414 datasets in 53 organisms, with (semi-) quantitative abundance information covering more than 300,000 proteins
Identification of novel biomarker candidates for immunohistochemical diagnosis to distinguish low-grade chondrosarcoma from enchondroma

Chondrosarcoma is the third most common primary bone cancer, requiring surgical resection. However, differentiation of low-grade chondrosarcoma (grade 1) from enchondroma that is benign and only requires regular follow-up is one of the most frequent diagnostic dilemmas facing orthopedic oncologists in clinical management. Although multiple techniques are applied to make the distinction, immunohistochemistry is an important ancillary technique, especially when a histopathological stain of specimen must be obtained in order to guarantee an accurate confirmation. Currently, no adequate immunohistochemical diagnostic protein biomarkers are available to distinguish low-grade chondrosarcoma from enchondroma. To discover novel protein biomarker candidates, an LC-MS/MS approach was applied to directly compare formalin-fixed, paraffin-embedded low-grade chondrosarcoma with enchondroma tissue samples. The proteomics analysis revealed 17 protein biomarker candidates. A principle was developed to prioritize the candidates using category and ranking. An algorithm, prioritization index of biomarker candidates for immunohistochemistry on tissue specimens, was developed to rank the candidates inside each category. Using the proteomics data and bioinformatics results, the prioritization index of biomarker candidates for immunohistochemistry on tissue revealed periostin as a top candidate. Immunohistochemical staining of periostin in 23 low-grade chondrosarcoma and 31 enchondroma tissue specimens disclosed 87% specificity and 70% sensitivity
Quantitative proteomics analysis of the Arg/N-end rule pathway of targeted degradation in Arabidopsis roots

According to the Arg/N-end rule pathway, proteins with basic N-termini are targeted for degradation by the Arabidopsis thaliana E3 ligase, PROTEOLYSIS6 (PRT6). Proteins can also become PRT6 substrates following post-translational arginylation by arginyltransferases ATE1 and 2. Here, we undertook a quantitative proteomics study of Arg/N-end rule mutants, ate1/2 and prt6, to investigate the impact of this pathway on the root proteome. Tandem mass tag labelling identified a small number of proteins with increased abundance in the mutants, some of which represent downstream targets of transcription factors known to be N-end rule substrates. Isolation of N-terminal peptides using terminal amine isotope labelling of samples (TAILS) combined with triple dimethyl labelling identified 1465 unique N-termini. Stabilising residues were over-represented among the free neo-N-termini, but destabilising residues were not markedly enriched in N-end rule mutants. The majority of free neo-N-termini were revealed following cleavage of organellar targeting signals, thus compartmentation may account in part for the presence of destabilising residues in the wild-type N-terminome. Our data suggest that PRT6 does not have a marked impact on the global proteome of Arabidopsis roots and is likely involved in the controlled degradation of relatively few regulatory proteins. All MS data have been deposited in the ProteomeXchange with identifier PXD001719 ()
Pitfalls in histone propionylation during bottom-up mass spectrometry analysis

Despite their important role in regulating gene expression, posttranslational histone modifications remain technically challenging to analyze. For identification by bottom-up MS, propionylation is required prior to and following trypsin digestion. Hereby, more hydrophobic peptides are generated enabling RP HPLC separation. When histone dynamics are studied in a quantitative manner, specificity, and efficiency of this chemical derivatization are crucial. Therefore we examined eight different protocols, including two different propionylation reagents. This revealed amidation (up to 70%) and methylation (up to 9%) of carboxyl groups as a side reaction. Moreover, incomplete (up to 85%) as well as a specific propionylation (up to 63%) can occur, depending on the protocol. These results highlight the possible pitfalls and implications for data analysis when doing bottom-up MS on histones
Metaproteomics and metabolomics analyses of chronically petroleum-polluted sites reveal the importance of general anaerobic processes uncoupled with degradation

Crude oil is one of the most important natural assets for humankind, yet it is a major environmental pollutant, notably in marine environments. One of the largest crude oil polluted areas in the word is the semi-enclosed Mediterranean Sea, in which the metabolic potential of indigenous microbial populations towards the large-scale chronic pollution is yet to be defined, particularly in anaerobic and micro-aerophilic sites. Here, we provide an insight into the microbial metabolism in sediments from three chronically polluted marine sites along the coastline of Italy: the Priolo oil terminal/refinery site (near Siracuse, Sicily), harbour of Messina (Sicily) and shipwreck of MT Haven (near Genoa). Using shotgun metaproteomics and community metabolomics approaches, the presence of 651 microbial proteins and 4776 metabolite mass features have been detected in these three environments, revealing a high metabolic heterogeneity between the investigated sites. The proteomes displayed the prevalence of anaerobic metabolisms that were not directly related with petroleum biodegradation, indicating that in the absence of oxygen, biodegradation is significantly suppressed. This suppression was also suggested by examining the metabolome patterns. The proteome analysis further highlighted the metabolic coupling between methylotrophs and sulphate reducers in oxygen-depleted petroleum-polluted sediments
N-terminal modifications of cellular proteins: the enzymes involved, their substrate specificities and biological effects

The vast majority of eukaryotic proteins are N-terminally modified by one or more processing enzymes. Enzymes acting on the very first amino acid of a polypeptide include different peptidases, transferases, and ligases. Methionine aminopeptidases excise the initiator methionine leaving the nascent polypeptide with a newly exposed amino acid that may be further modified. N-terminal acetyl-, methyl-, myristoyl-, and palmitoyltransferases may attach an acetyl, methyl, myristoyl, or palmitoyl group, respectively, to the α-amino group of the target protein N-terminus. With the action of ubiquitin ligases, one or several ubiquitin molecules are transferred, and hence, constitute the N-terminal modification. Modifications at protein N-termini represent an important contribution to proteomic diversity and complexity, and are essential for protein regulation and cellular signaling. Consequently, dysregulation of the N-terminal modifying enzymes is implicated in human diseases. We here review the different protein N-terminal modifications occurring co- or post-translationally with emphasis on the responsible enzymes and their substrate specificities
Proteomic analysis of lipid body from the alkenone-producing marine haptophyte alga Tisochrysis lutea

Lipid body (LB) is recognized as the cellular carbon and energy storage organelle in many organisms. LBs have been observed in the marine haptophyte alga Tisochrysis lutea that produces special lipids such as long-chain (C37-C40) ketones (alkenones) with 2–4 trans-type double bonds. In this study, we succeeded in developing a modified method to isolate LB from T. lutea. Purity of isolated LBs was confirmed by the absence of chlorophyll auto-fluorescence and no contamination of the most abundant cellular protein ribulose-1,5-bisphosphate carboxylase/oxygenase. As alkenones predominated in the LB by GC-MS analysis, the LB can be more appropriately named as “alkenone body (AB).” Extracted AB-containing proteins were analyzed by the combination of 1DE (SDS-PAGE) and MS/MS for confident protein identification and annotated using BLAST tools at National Center for Biotechnology Information. Totally 514 proteins were identified at the maximum. The homology search identified three major proteins, V-ATPase, a hypothetical protein EMIHUDRAFT_465517 found in other alkenone-producing haptophytes, and a lipid raft-associated SPFH domain-containing protein. Our data suggest that AB of T. lutera is surrounded by a lipid membrane originating from either the ER or the ER-derived four layer-envelopes chloroplast and function as the storage site of alkenones and alkenes
Skin mucus proteome map of European sea bass (Dicentrarchus labrax)

Author's accepted version (postprint).This is the peer reviewed version of the following article: Cordero, H., Brinchmann, M.F., Cuesta, A., Meseguer, J. & Esteban, M.A. (2015). Skin mucus proteome map of European sea bass (Dicentrarchus labrax). Proteomics, 15(23-24), 4007-4020, which has been published in final form at http://dx.doi.org/10.1002/pmic.201500120. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving (http://olabout.wiley.com/WileyCDA/Section/id-820227.html).Available from 14/10/2016
iTRAQ proteomics analysis reveals that PI3K is highly associated with bupivacaine-induced neurotoxicity pathways

Bupivacaine, a commonly used local anesthetic, has potential neurotoxicity through diverse signaling pathways. However, the key mechanism of bupivacaine-induced neurotoxicity remains unclear. Cultured human SH-SY5Y neuroblastoma cells were treated (bupivacaine) or untreated (control) with bupivacaine for 24 h. Compared to the control group, bupivacaine significantly increased cyto-inhibition, cellular reactive oxygen species, DNA damage, mitochondrial injury, apoptosis (increased TUNEL-positive cells, cleaved caspase 3, and Bcl-2/Bax), and activated autophagy (enhanced LC3II/LC3I ratio). To explore changes in protein expression and intercommunication among the pathways involved in bupivacaine-induced neurotoxicity, an 8-plex iTRAQ proteomic technique and bioinformatics analysis were performed. Compared to the control group, 241 differentially expressed proteins were identified, of which, 145 were up-regulated and 96 were down-regulated. Bioinformatics analysis of the cross-talk between the significant proteins with altered expression in bupivacaine-induced neurotoxicity indicated that phosphatidyl-3-kinase (PI3K) was the most frequently targeted protein in each of the interactions. We further confirmed these results by determining the downstream targets of the identified signaling pathways (PI3K, Akt, FoxO1, Erk, and JNK). In conclusion, our study demonstrated that PI3K may play a central role in contacting and regulating the signaling pathways that contribute to bupivacaine-induced neurotoxicity.postprin
Multiclassifier combinatorial proteomics of organelle shadows at the example of mitochondria in chromatin data

Subcellular localization is an important aspect of protein function, but the protein composition of many intracellular compartments is poorly characterized. For example, many nuclear bodies are challenging to isolate biochemically and thus remain inaccessible to proteomics. Here, we explore covariation in proteomics data as an alternative route to subcellular proteomes. Rather than targeting a structure of interest biochemically, we target it by machine learning. This becomes possible by taking data obtained for one organelle and searching it for traces of another organelle. As an extreme example and proof-of-concept we predict mitochondrial proteins based on their covariation in published interphase chromatin data. We detect about 1/3 of the known mitochondrial proteins in our chromatin data, presumably most as contaminants. However, these proteins are not present at random. We show covariation of mitochondrial proteins in chromatin proteomics data. We then exploit this covariation by multiclassifier combinatorial proteomics to define a list of mitochondrial proteins. This list agrees well with different databases on mitochondrial composition. This benchmark test raises the possibility that, in principle, covariation proteomics may also be applicable to structures for which no biochemical isolation procedures are available
An interaction proteomics survey of transcription factor binding at recurrent TERT promoter mutations

Contains fulltext :
                  150779.pdf (publisher's version ) (Open Access)Aberrant telomerase reactivation in differentiated cells represents a major event in oncogenic transformation. Recurrent somatic mutations in the human telomerase reverse transcriptase (TERT) promoter region, predominantly localized to two nucleotide positions, are highly prevalent in many cancer types. Both mutations create novel consensus E26 transformation-specific (ETS) motifs and are associated with increased TERT expression. Here, we perform an unbiased proteome-wide survey of transcription factor binding at TERT promoter mutations in melanoma. We observe ELF1 binding at both mutations in vitro and we show that increased recruitment of GABP is enabled by the spatial architecture of native and novel ETS motifs in the TERT promoter region. We characterize the dynamics of competitive binding between ELF1 and GABP and provide evidence for ELF1 exclusion by transcriptionally active GABP. This study thus provides an important description of proteome-wide, mutation-specific binding at the recurrent, oncogenic TERT promoter mutations
A year (2014-2015) of plants in Proteomics journal. Progress in wet and dry methodologies, moving from protein catalogs, and the view of classic plant biochemists

International audienceThe present review is an update of the previous one published in Proteomics 2015 Reviews special issue (1) covering the 2014-July 2015 period. It has been written on the bases of the publications that appeared in Proteomics journal during that period and the most relevant ones that have been published in other high-impact journals. Methodological advances and the contribution of the field to the knowledge of plant biology processes and its translation to agroforestry and environmental sectors will be discussed. This review has been organized in four blocks, with a starting general introduction (literature survey) followed by sections focusing on the methodology (in vitro, in vivo, wet and dry), proteomics integration with other approaches (systems biology and proteogenomics), biological information, and knowledge (cell communication, receptors and signaling), ending with a brief mention of some other biological and translational topics to which proteomics has made some contribution
Group 1 metabotropic glutamate receptors 1 and 5 form a protein complex in mouse hippocampus and cortex

The group 1 metabotropic glutamate receptors 1 and 5 (mGluR1/5) have been implicated in mechanisms of synaptic plasticity and may serve as potential therapeutic targets in autism spectrum disorders. The interactome of group 1 mGluRs has remained largely unresolved. Using a knockout-controlled interaction proteomics strategy we examined the mGluR5 protein complex in two brain regions, hippocampus and cortex, and identified mGluR1 as its major interactor in addition to the well described Homer proteins. We confirmed the presence of mGluR1/5 complex by (i) reverse immunoprecipitation using an mGluR1 antibody to pulldown mGluR5 from hippocampal tissue, (ii) coexpression in HEK293 cells followed by coimmunoprecipitation to reveal the direct interaction of mGluR1 and 5, and (iii) superresolution microscopy imaging of hippocampal primary neurons to show colocalization of the mGluR1/5 in the synapse
Classification of MALDI-MS imaging data of tissue microarrays using canonical correlation analysis based variable selection

First published: 9 May 2016Applying MALDI-MS imaging to tissue microarrays (TMAs) provides access to proteomics data from large cohorts of patients in a cost- and time-efficient way, and opens the potential for applying this technology in clinical diagnosis. The complexity of these TMA data—high-dimensional low sample size—provides challenges for the statistical analysis, as classical methods typically require a nonsingular covariance matrix that cannot be satisfied if the dimension is greater than the sample size. We use TMAs to collect data from endometrial primary carcinomas from 43 patients. Each patient has a lymph node metastasis (LNM) status of positive or negative, which we predict on the basis of the MALDI-MS imaging TMA data. We propose a variable selection approach based on canonical correlation analysis that explicitly uses the LNM information. We apply LDA to the selected variables only. Our method misclassifies 2.3–20.9% of patients by leave-one-out cross-validation and strongly outperforms LDA after reduction of the original data with principle component analysis.Lyron Winderbaum, Inge Koch, Parul Mittal and Peter Hoffman
The use of MALDI-MSI in the investigation of psychiatric and neurodegenerative disorders: a review

First published: 17 May 2016Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a mass spectrometry technique used for the analysis of macromolecules on an intact tissue of interest, thereby allowing the assessment of molecular signatures in health and disease in the anatomical context. MALDI-MSI is increasingly used to investigate neurodegenerative and psychiatric disorders at the molecular level, including Alzheimer's disease (AD), Parkinson's disease (PD), and schizophrenia (SCZ). These illnesses are characterized by complex neuropathological processes, and conventional proteomic techniques investigating brain tissue homogenates have inherent limitations in determining the precise anatomical or cellular location of proteomic findings. In this article, we review MALDI-MSI studies on neurodegenerative and psychiatric disorders, and explore whether the technique could accelerate the translation of proteomic information into improved understanding and ultimately better therapeutic applications.Klaus Oliver Schubert, Florian Weiland, Bernhard T. Baune and Peter Hoffman
MALDI mass spectrometry imaging of N-glycans on tibial cartilage and subchondral bone proteins in knee osteoarthritis

Accepted manuscript online: 15 March 2016Magnetic Resonance Imaging (MRI) is a non-invasive technique routinely used to investigate pathological changes in knee osteoarthritis (OA) patients. MRI uniquely reveals zones of the most severe change in the subchondral bone (SCB) in OA, called bone marrow lesions (BMLs). BMLs have diagnostic and prognostic significance in OA, but MRI does not provide a molecular understanding of BMLs. Multiple N-glycan structures have been observed to play a pivotal role in the OA disease process. We applied matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) of N-glycans to formalin-fixed paraffin-embedded (FFPE) SCB tissue sections from patients with knee OA, and liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) was conducted on consecutive sections to structurally characterize and correlate with the N-glycans seen by MALDI-MSI. The application of this novel MALDI-MSI protocol has enabled the first steps to spatially investigate the N-glycome in the SCB of knee OA patients.Matthew T. Briggs, Julia S. Kuliwaba, Dzenita Muratovic, Arun V. Everest, Dass, Nicolle H. Packer, David M. Findlay, Peter Hoffman
Analysis of the Drosophila melanogaster proteome dynamics during the embryo early development by a combination of label‐free proteomics approaches

During embryogenesis, organisms undergo considerable cellular remodelling requiring the combined action of thousands of proteins. In the case of the well studied model Drosophila melanogaster, transcriptomic studies, most notably from the modENCODE project, have described in detail changes in gene expression at the mRNA level across development. Although such data are clearly very useful for understand how the genome is regulated during embryogenesis, it is important to understand how changes in gene expression are reflected at the level of the proteome. In this study, we describe a combination of two quantitative label‐free approaches, SWATH and Data Dependent Acquisition, to monitor changes in protein expression across a timecourse of Drosophila melanogaster embryonic development. We demonstrate that both approaches provide robust and reproducible methods for the analysis of proteome changes. In a preliminary analysis of Drosophila embryogenesis, we identified several pathways, including the heat‐shock response, nuclear protein import and energy production, that are regulated during embryo development. In some cases changes in protein expression mirrored transcript levels across development, whereas other proteins showed signatures of post‐ transcriptional regulation. Taken together, our pilot study provides a solid platform for a more detailed exploration of the embryonic proteome.Funding: B.F, D.K and L.G are funded by BBSRC (Ref: BB/L002817/1). MR and JV acknowledge funding by the Wellcome Trust (RG 093735/Z/10/Z) the ERC (Starting grant 260809), M.R. is a Wellcome Trust Research Career Development and Wellcome-Beit Prize fellow.  This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/pmic.20150048