Literature DB >> 25369122

Use of ENCODE resources to characterize novel proteoforms and missing proteins in the human proteome.

Carol L Nilsson1, Ekaterina Mostovenko, Cheryl F Lichti, Kelly Ruggles, David Fenyö, Kate R Rosenbloom, William S Hancock, Young-Ki Paik, Gilbert S Omenn, Joshua LaBaer, Roger A Kroes, Matthias Uhlén, Sophia Hober, Ákos Végvári, Per E Andrén, Erik P Sulman, Frederick F Lang, Manuel Fuentes, Elisabet Carlsohn, Mark R Emmett, Joseph R Moskal, Frode S Berven, Thomas E Fehniger, György Marko-Varga.   

Abstract

We describe the utility of integrated strategies that employ both translation of ENCODE data and major proteomic technology pillars to improve the identification of the "missing proteins", novel proteoforms, and PTMs. On one hand, databases in combination with bioinformatic tools are efficiently utilized to establish microarray-based transcript analysis and supply rapid protein identifications in clinical samples. On the other hand, sequence libraries are the foundation of targeted protein identification and quantification using mass spectrometric and immunoaffinity techniques. The results from combining proteoENCODEdb searches with experimental mass spectral data indicate that some alternative splicing forms detected at the transcript level are in fact translated to proteins. Our results provide a step toward the directives of the C-HPP initiative and related biomedical research.

Entities:  

Keywords:  Chromosome-centric Human Protein Project; ENCODE; glioma stem cell; microassays; missing proteins; protein sequence mass spectrometry

Mesh:

Substances:

Year:  2014        PMID: 25369122     DOI: 10.1021/pr500564q

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  6 in total

Review 1.  Proteins and Proteoforms: New Separation Challenges.

Authors:  Fred E Regnier; JinHee Kim
Journal:  Anal Chem       Date:  2017-12-18       Impact factor: 6.986

2.  Large Scale Identification of Variant Proteins in Glioma Stem Cells.

Authors:  Ekaterina Mostovenko; Ákos Végvári; Melinda Rezeli; Cheryl F Lichti; David Fenyö; Qianghu Wang; Frederick F Lang; Erik P Sulman; K Barbara Sahlin; György Marko-Varga; Carol L Nilsson
Journal:  ACS Chem Neurosci       Date:  2017-12-21       Impact factor: 4.418

3.  Semi-automated biobank sample processing with a 384 high density sample tube robot used in cancer and cardiovascular studies.

Authors:  Johan Malm; Henrik Lindberg; David Erlinge; Roger Appelqvist; Maria Yakovleva; Charlotte Welinder; Erik Steinfelder; Thomas E Fehniger; György Marko-Varga
Journal:  Clin Transl Med       Date:  2015-08-14

4.  PARP1 expression and its correlation with survival is tumour molecular subtype dependent in glioblastoma.

Authors:  Balázs Murnyák; Mahan C Kouhsari; Rotem Hershkovitch; Bernadette Kálmán; György Marko-Varga; Álmos Klekner; Tibor Hortobágyi
Journal:  Oncotarget       Date:  2017-07-11

Review 5.  Transcriptomics resources of human tissues and organs.

Authors:  Mathias Uhlén; Björn M Hallström; Cecilia Lindskog; Adil Mardinoglu; Fredrik Pontén; Jens Nielsen
Journal:  Mol Syst Biol       Date:  2016-04-04       Impact factor: 11.429

Review 6.  Towards the Molecular Foundations of Glutamatergic-targeted Antidepressants.

Authors:  Roger A Kroes; Carol L Nilsson
Journal:  Curr Neuropharmacol       Date:  2017       Impact factor: 7.363

  6 in total

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