Evaluation of proteomic search engines for the analysis of histone modifications.
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ABSTRACT:
SUBMITTER: Yuan ZF
PROVIDER: S-EPMC4184451 | biostudies-literature | 2014 Oct
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe evaluation of information retrieval techniques has traditionally relied on human judges to determine which documents are relevant to a query and which are not. This protocol is used in the Text Retrieval Evaluation Conference (TREC), organized annually for the past 15 years, to support the unbiased evaluation of novel information retrieval approaches. The TREC Genomics Track has recently been introduced to measure the performance of information retrieval for biomedical applications.ResultsWe describe two protocols for evaluating biomedical information retrieval techniques without human relevance judgments. We call these protocols No Title Evaluation (NT Evaluation). The first protocol measures performance for focused searches, where only one relevant document exists for each query. The second protocol measures performance for queries expected to have potentially many relevant documents per query (high-recall searches). Both protocols take advantage of the clear separation of titles and abstracts found in Medline. We compare the performance obtained with these evaluation protocols to results obtained by reusing the relevance judgments produced in the 2004 and 2005 TREC Genomics Track and observe significant correlations between performance rankings generated by our approach and TREC. Spearman's correlation coefficients in the range of 0.79-0.92 are observed comparing bpref measured with NT Evaluation or with TREC evaluations. For comparison, coefficients in the range 0.86-0.94 can be observed when evaluating the same set of methods with data from two independent TREC Genomics Track evaluations. We discuss the advantages of NT Evaluation over the TRels and the data fusion evaluation protocols introduced recently.ConclusionOur results suggest that the NT Evaluation protocols described here could be used to optimize some search engine parameters before human evaluation. Further research is needed to determine if NT Evaluation or variants of these protocols can fully substitute for human evaluations.
| S-EPMC2292696 | biostudies-literature
Project description:To identify confident spectra from histone peptides containing PTMs, we present a method in which one kind of modification is searched each time. We then combine the identifications of multiple search engines to obtain confident results. We find that two search engines, pFind and Mascot, identify most of the confident results. This study will be beneficial those who are interested in histone proteomics analysis.
2014-09-01 | PXD001118 | Pride
Project description:A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.
| S-EPMC3769318 | biostudies-literature
Project description:Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at the individual level (diversity of topics related to the researcher) and at the social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.
| S-EPMC3374816 | biostudies-other
Project description:Heat shock protein 90 (HSP90) inhibition is an attractive strategy for cancer treatment. Several HSP90 inhibitors have shown promising effects in clinical oncology trials. However, little is known about HSP90 inhibition-mediated bladder cancer therapy. Here, we report a quantitative proteomic study that evaluates alterations in protein expression and histone post-translational modifications (PTMs) in bladder carcinoma in response to HSP90 inhibition. We show that 5 HSP90 inhibitors (AUY922, ganetespib, SNX2112, AT13387, and CUDC305) potently inhibited the proliferation of bladder cancer 5637 cells in a dose- and time-dependent manner. Our proteomic study quantified 518 twofold up-regulated and 811 twofold down-regulated proteins common to both AUY922 and ganetespib treatment. Bioinformatic analyses revealed that those differentially expressed proteins were involved in multiple cellular processes and enzyme-regulated signaling pathways, including chromatin modifications and cell death-associated pathways. Furthermore, quantitative proteome studies identified 14 types of PTMs with 93 marks on the core histones, including 34 novel histone marks of butyrylation, citrullination, 2-hydroxyisobutyrylation, methylation, O-GlcNAcylation, propionylation, and succinylation in AUY922- and ganetespib-treated 5637 cells. Together, this study outlines the association between proteomic changes and histone PTMs in response to HSP90 inhibitor treatment in bladder carcinoma cells, and thus intensifies the understanding of HSP90 inhibition-mediated bladder cancer therapeutics.
| S-EPMC5427839 | biostudies-literature
Project description:Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the postprocessing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server and a downloadable application that makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline also provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download.
| S-EPMC3707089 | biostudies-literature
Project description:ObjectiveCountries have major differences in the acceptance of face mask use for the prevention of COVID-19. This work aims at studying the information online in different countries in terms of information quality and content.DesignContent analysis.MethodWe analysed 450 webpages returned by searching the string 'are face masks dangerous' in Italy, the UK and the USA using three search engines (Bing, Duckduckgo and Google) in August 2020. The type of website and the stance about masks were assessed by two raters for each language and inter-rater agreement reported as Cohen's kappa. The text of the webpages was collected from the web using WebBootCaT and analysed using a corpus analysis software to identify issues mentioned.ResultsMost pages were news outlets, and few (2%-6%) from public health agencies. Webpages with a negative stance on masks were more frequent in Italian (28%) than English (19%). Google returned the highest number of mask-positive pages and Duckduckgo the lowest. Google also returned the lowest number of pages mentioning conspiracy theories and Duckduckgo the highest. Webpages in Italian scored lower than those in English in transparency (reporting authors, their credentials and backing the information with references). When issues about the use of face masks were analysed, mask effectiveness was the most discussed followed by hypercapnia (accumulation of carbon dioxide), contraindication in respiratory disease and hypoxia, with issues related to their contraindications in mental health conditions and disability mentioned by very few pages.ConclusionsThis study suggests that: (1) public health agencies should increase their web presence in providing correct information on face masks; (2) search engines should improve the information quality criteria in their ranking; (3) the public should be more informed on issues related to the use of masks and disabilities, mental health and stigma arising for those people who cannot wear masks.
| S-EPMC8275368 | biostudies-literature
Project description:Post-translational modifications of proteins are a major determinant of biological function. Phosphorylation of proteins involved in signal transduction contributes to the induction and maintenance of several examples of cellular and synaptic plasticity. In this study we have identified phosphoproteins regulated by Pavlovian conditioning in lysates of Hermissenda nervous systems using two-dimensional electrophoresis (2DE) in conjunction with (32)P labeling, fluorescence based phosphoprotein in-gel staining, and mass spectrometry. Modification of protein phosphorylation regulated by conditioning was first assessed by densitometric analysis of (32)P labeled proteins resolved by 2DE from lysates of conditioned and pseudorandom control nervous systems. An independent assessment of phosphorylation regulated by conditioning was obtained from an examination of 2D gels stained with Pro-Q Diamond phosphoprotein dye. Mass spectrometric analysis of protein digests from phosphoprotein stained analytical gels or Coomassie Blue stained preparative gels provided for the identification of phosphoproteins that exhibited statistically significant increased phosphorylation in conditioned groups as compared to pseudorandom controls. A previously identified cytoskeletal related protein, Csp24 (24 kDa conditioned stimulus pathway phosphoprotein), involved in intermediate-term memory exhibited significantly increased phosphorylation detected 24 h post-conditioning. Our results show that proteins involved in diverse cellular functions such as transcriptional regulation, cell signaling, cytoskeletal regulation, metabolic activity, and protein degradation contribute to long-term post-translational modifications associated with Pavlovian conditioning.
| S-EPMC2815081 | biostudies-literature
Project description:Although isothiocyanates (ITC), which are found in cruciferous vegetables, have been shown to inhibit carcinogenesis in animal models and induce apoptosis and cell cycle arrest in tumor cells, the biochemical mechanisms of cell growth inhibition by these compounds are not fully understood. Studies have reported that ITC binding to intracellular proteins may be an important event for initiating apoptosis. Specific protein target(s) and molecular mechanisms for ITC have been investigated in human lung cancer A549 cells using proteomic tools. Cells were treated with various amounts (1-100 μmol/L) of radiolabeled phenethyl-ITC (PEITC) and sulforaphane (SFN) and the extracted proteins resolved using 2-dimensional gel electrophoresis. The results of mass spectrometric analyses suggested that tubulin may be an in vivo binding target for ITC. The binding of ITC to tubulin was associated with growth arrest. The proliferation of A549 cells was significantly reduced by ITC, with benzyl-ITC (BITC) having a greater relative activity than PEITC or SFN. Mitotic arrest and apoptosis as well as disruption of microtubule polymerization were induced in the order: BITC > PEITC > SFN. An analysis of tubulins isolated from BITC-treated A549 cells showed that Cys(347), a conserved cysteine in all α-tubulin isoforms, was covalently modified by BITC. Taken together, these results suggest that tubulin is a binding target of ITC and that this interaction can lead to growth inhibition and apoptosis.
| S-EPMC3374673 | biostudies-literature
Project description:Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.
| S-EPMC3128686 | biostudies-literature