pinecone/core-2020-05-10-deduplication huggingface dataset:
Quantitative detection of changes in the leaf-mesophyll tonoplast proteome in dependency of a cadmium exposure of barley (Hordeum vulgare L.) plants

Although the vacuole is the most important final store for toxic heavy metals like cadmium (Cd(2+)), our knowledge on how they are transported into the vacuole is still insufficient. It has been suggested that Cd(2+) can be transported as phytochelatin-Cd(2+) by an unknown ABC transporter or in exchange with protons by cation/proton exchanger (CAX) transporters. To unravel the contribution of vacuolar transporters to Cd(2+) detoxification, a quantitative proteomics approach was performed. Highly purified vacuoles were isolated from barley plants grown under minus, low (20 microM), and high (200 microM) Cd(2+ )conditions and protein levels of the obtained tonoplast samples were analyzed using isobaric tag for relative and absolute quantitation (iTRAQ). Although 56 vacuolar transporter proteins were identified, only a few were differentially expressed. Under low-Cd(2+) conditions, an inorganic pyrophosphatase and a gamma-tonoplast intrinsic protein (gamma-TIP) were up-regulated, indicating changes in energization and water fluxes. In addition, the protein ratio of a CAX1a and a natural resistance-associated macrophage protein (NRAMP), responsible for vacuolar Fe(2+) export was increased. CAX1a might play a role in vacuolar Cd(2+) transport. An increase in NRAMP activity leads to a higher cytosolic Fe(2+) concentration, which may prevent the exchange of Fe(2+) by toxic Cd(2+). Additionally, an ABC transporter homolog to AtMRP3 showed up-regulation. Under high Cd(2+) conditions, the plant response was more specific. Only a protein homologous to AtMRP3 that showed already a response under low Cd(2+) conditions, was up-regulated. Interestingly, AtMRP3 is able to partially rescue a Cd(2+)-sensitive yeast mutant. The identified transporters are good candidates for further investigation of their roles in Cd(2+) detoxification
A proteome map of the pituitary melanotrope cell activated by black-background adaptation of Xenopus laevis

Upon transfer of Xenopus laevis from a white to a black background, the melanotrope cells in the pituitary pars intermedia secrete alpha-melanocyte-stimulating hormone, which stimulates dispersion of melanin pigment in skin melanophores. This adaptive behavior is under the control of neurotransmitters and neuropeptides of hypothalamic origin. The alpha-melanocyte-stimulating hormone-producing cells and their hypothalamic control system provide an interesting model to study proteins required for biosynthetic and secretory processes involved in peptide hormone production and for brain-pituitary signaling. We present a 2-D PAGE-based proteome map of melanotrope cells from black-adapted animals, identifying 204 different proteins by MS analysis
Quorum sensing in sourdough Lactobacillus plantarum DC400: Induction of plantaricin A (PlnA) under co-cultivatio with other lactic acid bacteria and effect of PlnA on bacterial and Caco2-cells

This work aimed at showing the effect of pheromone plantaricin A (PlnA) by Lactobacillus plantarum DC400 towards other sourdough lactic acid bacteria and the potential of PlnA to protect the function of the human intestinal barrier. Growth and survival of sourdough lactic acid bacteria were differently affected by co-cultivation with L. plantarum DC400. Compared to mono-cultures, Lactobacillus sanfranciscensis DPPMA174 and Pediococcus pentosaceus 2XA3 showed growth inhibition and decreased viability when co-cultured with L. plantarum DC400. L. sanfranciscensis DPPMA174 induced the highest synthesis of PlnA. Survival of strain DPPMA174 only slightly varied by comparing the addition of PlnA to the culture medium and the co-cultivation with L. plantarum DC400. Compared to mono-culture, the proteome of L. sanfranciscensis DPPMA174 grown in co-culture with L. plantarum DC400 showed the variation of expression of 58 proteins (47 over expressed and 11 repressed). Thirty-four of them were also over expressed or repressed during growth of DPPMA174 with PlnA. Fifty-one of the above 58 proteins were identified. They had a central role in stress response, amino acid, energy and nucleotide metabolisms, membrane transport, regulation of transcription, and cell redox homeostasis. PlnA markedly increased the viability of human Caco-2/TC7 cells and the transepithelial electrical resistance
Integrated data management and validation platform for phosphorylated tandem mass spectrometry data

MS/MS is a widely used method for proteome-wide analysis of protein expression and PTMs. The thousands of MS/MS spectra produced from a single experiment pose a major challenge for downstream analysis. Standard programs, such as MASCOT, provide peptide assignments for many of the spectra, including identification of PTM sites, but these results are plagued by false-positive identifications. In phosphoproteomic experiments, only a single peptide assignment is typically available to support identification of each phosphorylation site, and hence minimizing false positives is critical. Thus, tedious manual validation is often required to increase confidence in the spectral assignments. We have developed phoMSVal, an open-source platform for managing MS/MS data and automatically validating identified phosphopeptides. We tested five classification algorithms with 17 extracted features to separate correct peptide assignments from incorrect ones using over 2600 manually curated spectra. The naïve Bayes algorithm was among the best classifiers with an AUC value of 97% and PPV of 97% for phosphotyrosine data. This classifier required only three features to achieve a 76% decrease in false positives as compared with MASCOT while retaining 97% of true positives. This algorithm was able to classify an independent phosphoserine/threonine data set with AUC value of 93% and PPV of 91%, demonstrating the applicability of this method for all types of phospho-MS/MS data. PhoMSVal is available at http://csbi.ltdk.helsinki.fi/phomsval.National Science Foundation (U.S.). Graduate Research Fellowship Progra
Comparative proteome analysis of metabolic proteins from seeds of durum wheat (cv. Svevo) subjected to heat stress.

In Central and Southern Italy, where durum wheat represents one of the most widely cultivated crops, grain filling occurs during Spring, a period characterised by sudden increases in temperature.
Wheat grain proteins are classified into albumins, globulins, and prolamins. The non-prolamin fractions include proteins with metabolic activity or structural function.
In order to investigate the consequences of heat stress on the accumulation of non-prolamin proteins in mature durum wheat kernels, the Italian cultivar Svevo was subjected to two thermal regimes
(heat stress vs. control) during grain filling. The 2D patterns of non-prolamin proteins were monitored to identify polypeptides affected by heat stress. This study shows that heat stress alters significantly the durum wheat seed proteome, although the fold changes range only between 1.2 and 2.2. This analysis revealed 132 differentially expressed polypeptides, 47 of which were identified by MALDI TOF and MALDI-TOF-TOF MS and included heat shock proteins, proteins involved in the glycolysis and carbohydrate metabolism, as well as stress related proteins. Many of the heat
induced polypeptides are considered to be allergenic for sensitive individuals.
The differences observed with previously reported data regarding bread wheat may be explained by the absence of the D genome in durum wheatL'articolo è disponibile sul sito dell'editore: 
www.interscience.wiley.comProject “Proteine e geni per la protezione delle piante dagli stress biotici e abiotici (PROTEO-STRESS), MIPAF, Italy - MIUR, "Fondo per il sostegno dei giovani e per
favorire la mobilità degli studenti" in the framework “Valorizzazione dei prodotti tipici
dell’agroalimentare e sicurezza alimentare attraverso nuovi sistemi di caratterizzazione e garanzia
di qualità” - COST Action FA0603 Plant Proteomics
Is a gene-centric human proteome project the best way for proteomics to serve biology?

International audienceWith the recent developments in proteomic technologies, a complete human proteome project (HPP) appears feasible for the first time. However, there is still debate as to how it should be designed and what it should encompass. In "proteomics speak", the debate revolves around the central question as to whether a gene-centric or a protein-centric proteomics approach is the most appropriate way forward. In this paper, we try to shed light on what these definitions mean, how large-scale proteomics such as a HPP can insert into the larger omics chorus, and what we can reasonably expect from a HPP in the way it has been proposed so far
Improvements and simplifications in in-gel fluorescent detection of proteins using ruthenium II tris-(bathophenanthroline disulfonate): the poor man's fluorescent detection method.

International audienceFluorescent detection of proteins is a popular method of detection allying sensitivity, linearity and compatibility with mass spectrometry. Among the numerous methods described in the literature, staining with ruthenium II tris(bathophenanthroline disulfonate) is particularly cost-effective, but slightly cumbersome owing to difficulties in the preparation of the complex and complexity of staining protocols. We describe here the modifications on both aspects that allow to perform a higher contrast staining and offer a more robust method of complex preparation, thereby maximizing the advantages of the method
Dose‐dependent proteomic analysis of glioblastoma cancer stem cells upon treatment with γ‐secretase inhibitor

Notch signaling has been demonstrated to have a central role in glioblastoma (GBM) cancer stem cells (CSCs) and we have demonstrated recently that Notch pathway blockade by γ‐secretase inhibitor (GSI) depletes GBM CSCs and prevents tumor propagation both in vitro and in vivo. In order to understand the proteome alterations involved in this transformation, a dose‐dependent quantitative mass spectrometry (MS)‐based proteomic study has been performed based on the global proteome profiling and a target verification phase where both Immunoassay and a multiple reaction monitoring (MRM) assay are employed. The selection of putative protein candidates for confirmation poses a challenge due to the large number of identifications from the discovery phase. A multilevel filtering strategy together with literature mining is adopted to transmit the most confident candidates along the pipeline. Our results indicate that treating GBM CSCs with GSI induces a phenotype transformation towards non‐tumorigenic cells with decreased proliferation and increased differentiation, as well as elevated apoptosis. Suppressed glucose metabolism and attenuated NFR2‐mediated oxidative stress response are also suggested from our data, possibly due to their crosstalk with Notch Signaling. Overall, this quantitative proteomic‐based dose‐dependent work complements our current understanding of the altered signaling events occurring upon the treatment of GSI in GBM CSCs
A novel procedure for protein extraction from formalin-fixed paraffin-embedded tissues

[Abstract] Most of the archived pathological specimens in hospitals are kept as formalin-fixed paraffin-embedded tissues (FFPE) for long-term preservation. Up to now, these samples are only used for immunohistochemistry in a clinical routine as it is difficult to recover intact protein from these FFPE tissues. Here, we report a novel, short time-consuming and cost-effective method to extract full-length, non-degraded proteins from FFPE tissues. This procedure is combined with an effective and non-toxic deparaffinisation process and an extraction method based on antigen-retrieval, high concentration of SDS and high temperature. We have obtained enough intact protein to be detected by Western blotting analysis. This technique will allow utilising these stored FFPE tissues in several applications for protein analysis helping to advance the translational studies in cancer and other diseases.Xunta de Galicia; PS09/24Xunta de Galicia; 10CSA916023P
Contribution of proteomics to understanding the role of\ud
tumor-derived exosomes in cancer progression: State of\ud
the art and new perspectives

Exosomes are nanometer-sized vesicles (40–100 nm diameter) of endocytic origin released\ud
from different cell types under both normal and pathological conditions. They function as cell\ud
free messengers, playing a relevant role in the cell–cell communication that is strongly related\ud
to the nature of the molecules (proteins, mRNAs, miRNAs, and lipids) that they transport.\ud
Tumor cells actively shed exosomes into their surrounding microenvironment and growing\ud
evidence indicates that these vesicles have pleiotropic functions in the regulation of tumor\ud
progression, promoting immune escape, tumor invasion, neovascularization, and metastasis.\ud
During the last few years remarkable efforts have been made to obtain an accurate definition\ud
of the protein content of tumor-derived exosomes (TDEs) by applying MS-based proteomic\ud
technologies. To date, TDEs proteomic studies have been mainly utilized to catalog TDEs\ud
proteins with the purpose of identifying disease biomarkers. The future challenge for improving\ud
our understanding and characterization of TDEs will be the implementation of new systemsdriven\ud
and proteomic integrative strategies. The aim of this article is to provide an overview of\ud
the most characterized exosomes-mediated mechanisms that contribute to the pathogenesis of\ud
cancer and to review recent proteomics data that support the protumorigenic role of TDEs
The initiative on Model Organism Proteomes (iMOP) Session September 6, 2011, Geneva, Switzerland

iMOP – the Initiative on Model Organism Proteomes – was accepted as a new HUPO initiative at the Ninth HUPO meeting in Sydney in 2010. A goal of iMOP is to integrate research groups working on a great diversity of species into a model organism community. At the Tenth HUPO meeting in Geneva this variety was reflected in the iMOP session on Tuesday September 6, 2011. The presentations covered the quantitative proteome database PaxDb, proteomics projects studying farm animals,  Arabidopsis thaliana , as well as host–pathogen interactions
Resilience in the proteomics data ecosystem: how the field cares for its data

The public dissemination of data is an integral part of the life sciences. In the field of proteomics too, data sharing has taken off over the last few years, with the first downstream uses of these data quickly gaining prominence. At the same time, the recent unfortunate demise of two repositories, NCBI Peptidome and ProteomeCommons Tranche, has shown the frailty of such data gathering efforts. Heroic efforts by the PRIDE and Peptidome teams to rescue the Peptidome data have now ensured their continued availability to the field, and alternatives have already been put in place for Tranche. But with public data increasingly at the hub of the life sciences, it is a good time to look at the proteomics data ecosystem in some more detail
Surface proteomic analysis of differentiated versus stem-like osteosarcoma human cells

Cancer stem cell characterization represents a breakthrough in cancer research. Despite evidence\ud
showing the existence and the role of cancer stem cells in osteosarcoma (OS) onset and\ud
progression, little is known about their specific surface phenotype. To address this issue, we\ud
carried out a cytometric analysis with an antibody-array comprising 245 membrane proteins\ud
comparing the stem and differentiated OS cells. As experimentalmodel, we chose the stem-like\ud
cell line 3aminobenzamide-OS and its parental, differentiated, cell line MG63. We identified\ud
50 differentially expressed, 23 homogeneously expressed, and 172 not expressed proteins in\ud
the two cell line models, thus defining a surface protein signature specific for each of them.\ud
Furthermore, we selected ERK1/2 (p44/42 mitogen-activated protein kinases) as a potential\ud
pathway correlated with processes that characterize tumorigenic potential and stemness of\ud
3aminobenzamide-OS cells
Machine learning applications in proteomics research: How the past can boost the future

Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that
allow computers to learn solving a (complex) problem from existing data. This ability can be
used to generate a solution to a particularly intractable problem, given that enough data is
available to train and subsequently evaluate an algorithm on. Since mass spectrometry based
proteomics has no shortage of complex problems, and since publicly available data is becoming
available in ever growing amounts, machine learning is fast becoming a very popular tool in the
field. We here therefore present an overview of the different applications of machine learning in
proteomics that together cover nearly the entire wet- and dry-lab workflow, and that address key
bottlenecks in experiment planning and design, as well as in data processing and analysis.status: publishe
iTRAQ as a method for optimization: enhancing peptide recovery after gel fractionation

At the dawn of a new era in label-free quantitation on high-resolution MS instruments, classical methods such as iTRAQ continue to provide very useful insights in comparative proteomics. The potential to multiplex samples makes this reporter-based labeling technique highly suited for method optimization as demonstrated here by a set of standard series. Instead of studying ratios of annotated proteins, we propose an alternative method, based on the analysis of the average reporter ratios of all the spectra from a sample or a large distinct subset herein. This strategy circumvents the bias, associated with the annotation and iTRAQ quantitation, leading to increased adequacy in measuring yield differences between workflows. As gel electrophoresis prior to MS analysis is highly beneficial, for example, as a fractionation step, the approach was applied to evaluate the influence of several parameters of the established in-gel digestion protocol. We quantified the negative effect of SYPRO Ruby staining and the positive effect of gel fixation prior to digestion on peptide yield. Finally, we emphasize the benefits of adding CaCl2 and ACN to a tryptic in-gel digest, resulting in an up to tenfold enhanced peptide recovery and fewer trypsin missed cleavages
INPPO actions and recognition as a driving force for progress in plant proteomics: Change of guard, INPPO update, and upcoming activities

The International Plant Proteomics Organization (INPPO) is a non-profit organization whose members are scientists involved or interested in plant proteomics. Since the publication of the first INPPO highlights in 2012, continued progress on many of the organization’s mandates/goals has been achieved. Two major events are emphasized in this second INPPO highlights. First, the change of guard at the top, passing of the baton from Dominique Job, INPPO founding President to Ganesh Kumar Agrawal as the incoming President. Ganesh K. Agrawal, along with Dominique Job and Randeep Rakwal initiated the INPPO. Second, the most recent INPPO achievements and future targets, mainly the organization of first the INPPO World Congress in 2014, tentatively planned for Hamburg (Germany), are mentioned.Web of Scienc
A standardized framing for reporting protein identifications in mzIdentML 1.2

Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software
Proteogenomics in Microbiology: Taking the Right Turn at the Junction of Genomics and Proteomics

High-accuracy and high-throughput proteomic methods have completely changed the way we can identify and characterize proteins. MS-based proteomics can now provide a unique supplement to genomic data and add a new level of information to the interpretation of genomic sequences. Proteomics-driven genome annotation has become especially relevant in microbiology where genomes are sequenced on a daily basis and limitations of an in silico driven annotation process are well recognized. In this review paper, we outline different strategies on how one can design a proteogenomic experiment, for example on genome-sequenced (synonymous proteogenomics) versus unsequenced organisms (ortho-proteogenomics) or with the aid of other "omic" data such as RNA-seq. We touch upon many challenges that are encountered during a typical proteogenomic study, mostly concerning bioinformatics methods and downstream data analysis, but also related to creation and use of sequence databases. A large list of proteogenomic case studies of different microorganisms is provided to illustrate the mapping of MS/MS-derived peptide spectra to genomic DNA sequences. These investigations have led to accurate determination of translational initiation sites, pointed out eventual read-throughs or programmed frameshifts, detected signal peptide processing or other protein maturation events, removed questionable annotation assignments, and provided evidence for predicted hypothetical proteins
A sarabande of tropical fruit proteomics: Avocado, banana, and mango

The present review highlights the progress made in plant proteomics via the introduction of combinatorial peptide ligand libraries (CPLL) for detecting low-abundance species. Thanks to a novel approach to the CPLL methodology, namely, that of performing the capture both under native and denaturing conditions, identifying plant species in the order of thousands, rather than hundreds, is now possible. We report here data on a trio of tropical fruits, namely, banana, avocado, and mango. The first two are classified as “recalcitrant” tissues since minute amounts of proteins (in the order of 1%) are embedded on a very large matrix of plant-specific material (e.g., polysaccharides and other plant polymers). Yet, even under these adverse conditions we could report, in a single sweep, from 1000 to 3000 unique gene products. In the case of mango the investigation has been extended to the peel too, since this skin is popularly used to flavor dishes in Far East cuisine. Even in this tough peel 330 proteins could be identified, whereas in soft peels, such as in lemons, one thousand unique species could be detected