dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins

Huang, Kai-Yao; Su, Min-Gang; Kao, Hui-Ju; Hsieh, Yun-Chung; Jhong, Jhih-Hua; Cheng, Kuang-Hao; Huang, Hsien-Da; Lee, Tzong-Yi

doi:10.1093/nar/gkv1240

Cited by 161 publications

(123 citation statements)

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“…These organelle proteomes are also enriched in low complexity domain-containing proteins. A similar analysis was performed with proteins that have experimentally validated N-glyosylation sites (N-GlyocsylDB) deposited in dbPTM (46). As expected, N-glyocsylated proteins were found enriched in the golgi, endoplasmic reticulum, lysosomes and membrane fractions as defined by UniProtKB (51).…”

Section: Introductionmentioning

confidence: 99%

ADPriboDB: The database of ADP-ribosylated proteins

et al. 2016

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ADP-ribosylation refers to the addition of one or more ADP-ribose units onto proteins post-translationally. This protein modification is often added by ADP-ribosyltransferases, commonly known as PARPs, but it can also be added by other enzymes, including sirtuins or bacterial toxins. While past literature has utilized a variety of methods to identify ADP-ribosylated proteins, recent proteomics studies bring the power of mass spectrometry to determine sites of the modification. To appreciate the diverse roles of ADP-ribosylation across the proteome, we have created ADPriboDB – a database of ADP-ribosylated proteins (http://ADPriboDB.leunglab.org). Each entry of ADPriboDB is annotated manually by at least two independent curators from the literature between January 1975 and July 2015. The current database includes over 12 400 protein entries from 459 publications, identifying 2389 unique proteins. Here, we describe the structure and the current state of ADPriboDB as well as the criteria for entry inclusion. Using this aggregate data, we identified a statistically significant enrichment of ADP-ribosylated proteins in non-membranous RNA granules. To our knowledge, ADPriboDB is the first publicly available database encapsulating ADP-ribosylated proteins identified from the past 40 years, with a hope to facilitate the research of both basic scientists and clinicians to better understand ADP-ribosylation at the molecular level.

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Section: Introductionmentioning

confidence: 99%

ADPriboDB: The database of ADP-ribosylated proteins

et al. 2016

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“…2014) (Du et al 2011), PhosphoSitePlus (Apr. 2014) (Hornbeck et al 2012), dbPTM (May 2013) (Huang et al 2016), PhosphoELM (May 2013) (Dinkel et al 2011), ProteomeScout (Mar. 2014) (Matlock et al 2015), and D2P2 (Dec. 2014) (Oates et al 2013).…”

Section: Annotationsmentioning

confidence: 99%

Identification of protein features encoded by alternative exons using Exon Ontology

et al. 2017

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Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing variation in physiological-or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named "Exon Ontology," based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encoded protein features instead of gene level functional annotations. Exon Ontology describes the protein features encoded by a selected list of exons and looks for potential Exon Ontology term enrichment. By applying this strategy to exons that are differentially spliced between epithelial and mesenchymal cells and after extensive experimental validation, we demonstrate that Exon Ontology provides support to discover specific protein features regulated by alternative splicing. We also show that Exon Ontology helps to unravel biological processes that depend on suites of coregulated alternative exons, as we uncovered a role of epithelial cell-enriched splicing factors in the AKT signaling pathway and of mesenchymal cell-enriched splicing factors in driving splicing events impacting on autophagy. Freely available on the web, Exon Ontology is the first computational resource that allows getting a quick insight into the protein features encoded by alternative exons and investigating whether coregulated exons contain the same biological information. [Supplemental material is available for this article.]Alternative splicing is a major step in the gene expression process leading to the production of different transcripts with different exon content (or alternative splicing variants) from one single gene. This mechanism is the rule, as 95% of human genes produce at least two splicing variants (Nilsen and Graveley 2010;de Klerk and 't Hoen 2015;Lee and Rio 2015). Alternative splicing decisions rely on splicing factors binding on pre-mRNA molecules more or less close to splicing sites and regulating their recognition by the spliceosome (Lee and Rio 2015). Other mechanisms, including usage of alternative promoters and alternative polyadenylation sites, also increase the diversity of transcripts and drive both quantitative and qualitative effects (Tian and Manley 2013;de Klerk and 't Hoen 2015). Indeed, alternative promoters and alternative polyadenylation sites can impact mRNA 5 ′ -and 3 ′ -untranslated regions, which can have consequences on transcript stability or translation (Tian and Manley 2013;de Klerk and 't Hoen 2015). In addition, alternative splicing can lead to the biogenesis of nonproductive mRNAs degraded by the nonsense-mediated mRNA decay pathway (Hamid and Makeyev 2014). These mechanisms can also change the gene coding sequence. Alternative promoters and alternative polyadenylation sites can change protein N-and C-terminal domains, respec...

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“…For example, the activity of an enzyme can be controlled at numerous levels including the rate of transcription, alternative splicing, mRNA stability, translation control, post-translational modification which may be covalent (e.g. phosphorylation (Ruprecht and Lemeer 2014), acetylation (Choudhary et al 2009), OGlcNAcylation (Zachara and Hart 2004; Hahne et al 2012) among many others (Huang KY et al 2016; Hornbeck 2015)) or non covalent “allosteric” interactions, as is commonly observed in central metabolism such as feedback inhibition of phosphofructokinase-1 (PFK-1) by ATP and citrate, up regulation of PFK-1 by fructose-2,6-bisphosphate, feed-forward activation of pyruvate kinase by fructose-1,6-phosphate (Christofk et al 2008) and reciprocal activation of pyruvate carboxylase and inhibition of pyruvate dehydrogenase by acetyl CoA (Jitrapakdee et al 2008). Indeed, the catalytic activities of a large fraction of enzymes in metabolic networks are modulated by interactions with metabolites.…”

Section: Introductionmentioning

confidence: 99%

Preclinical models for interrogating drug action in human cancers using Stable Isotope Resolved Metabolomics (SIRM)

2016

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Aims In this review we compare the advantages and disadvantages of different model biological systems for determining the metabolic functions of cells in complex environments, how they may change in different disease states, and respond to therapeutic interventions. Background All preclinical drug-testing models have advantages and drawbacks. We compare and contrast established cell, organoid and animal models with ex vivo organ or tissue culture and in vivo human experiments in the context of metabolic readout of drug efficacy. As metabolism reports directly on the biochemical state of cells and tissues, it can be very sensitive to drugs and/or other environmental changes. This is especially so when metabolic activities are probed by stable isotope tracing methods, which can also provide detailed mechanistic information on drug action. We have developed and been applying Stable Isotope-Resolved Metabolomics (SIRM) to examine metabolic reprogramming of human lung cancer cells in monoculture, in mouse xenograft/explant models, and in lung cancer patients in situ (Lane et al. 2011; T. W. Fan et al. 2011; T. W-M. Fan et al. 2012; T. W. Fan et al. 2012; Xie et al. 2014b; Ren et al. 2014a; Sellers et al. 2015b). We are able to determine the influence of the tumor microenvironment using these models. We have now extended the range of models to fresh human tissue slices, similar to those originally described by O. Warburg (Warburg 1923), which retain the native tissue architecture and heterogeneity with a paired benign versus cancer design under defined cell culture conditions. This platform offers an unprecedented human tissue model for preclinical studies on metabolic reprogramming of human cancer cells in their tissue context, and response to drug treatment (Xie et al. 2014a). As the microenvironment of the target human tissue is retained and individual patient's response to drugs is obtained, this platform promises to transcend current limitations of drug selection for clinical trials or treatments. Conclusions and Future Work Development of ex vivo human tissue and animal models with humanized organs including bone marrow and liver show considerable promise for analyzing drug responses that are more relevant to humans. Similarly using stable isotope tracer methods with these improved models in advanced stages of the drug development pipeline, in conjunction with tissue biopsy is expected significantly to reduce the high failure rate of experimental drugs in Phase II and III clinical trials.

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dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins

Cited by 161 publications

References 70 publications

ADPriboDB: The database of ADP-ribosylated proteins

ADPriboDB: The database of ADP-ribosylated proteins

Identification of protein features encoded by alternative exons using Exon Ontology

Preclinical models for interrogating drug action in human cancers using Stable Isotope Resolved Metabolomics (SIRM)

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