Literature DB >> 16596704

Modeling a whole organ using proteomics: the avian bursa of Fabricius.

Fiona M McCarthy1, Amanda M Cooksey, Nan Wang, Susan M Bridges, G Todd Pharr, Shane C Burgess.   

Abstract

While advances in proteomics have improved proteome coverage and enhanced biological modeling, modeling function in multicellular organisms requires understanding how cells interact. Here we used the chicken bursa of Fabricius, a common experimental system for B cell function, to model organ function from proteomics data. The bursa has two major functional cell types: B cells and the supporting stromal cells. We used differential detergent fractionation-multidimensional protein identification technology (DDF-MudPIT) to identify 5198 proteins from all cellular compartments. Of these, 1753 were B cell specific, 1972 were stroma specific and 1473 were shared between the two. By modeling programmed cell death (PCD), cell differentiation and proliferation, and transcriptional activation, we have improved functional annotation of chicken proteins and placed chicken-specific death receptors into the PCD process using phylogenetics. We have identified 114 transcription factors (TFs); 42 of the bursal B cell TFs have not been reported before in any B cells. We have also improved the structural annotation of a newly sequenced genome by confirming the in vivo expression of 4006 "predicted", and 6623 ab initio, ORFs. Finally, we have developed a novel method for facilitating structural annotation, "expressed peptide sequence tags" (ePSTs) and demonstrate its utility by identifying 521 potential novel proteins from the chicken "unassigned chromosome".

Entities:  

Mesh:

Year:  2006        PMID: 16596704     DOI: 10.1002/pmic.200500648

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  16 in total

1.  Proteomics-based systems biology modeling of bovine germinal vesicle stage oocyte and cumulus cell interaction.

Authors:  Divyaswetha Peddinti; Erdogan Memili; Shane C Burgess
Journal:  PLoS One       Date:  2010-06-21       Impact factor: 3.240

2.  Global liver proteomics of rats exposed for 5 days to phenobarbital identifies changes associated with cancer and with CYP metabolism.

Authors:  Mary B Dail; L Allen Shack; Janice E Chambers; Shane C Burgess
Journal:  Toxicol Sci       Date:  2008-09-16       Impact factor: 4.849

3.  AgBase: supporting functional modeling in agricultural organisms.

Authors:  Fiona M McCarthy; Cathy R Gresham; Teresia J Buza; Philippe Chouvarine; Lakshmi R Pillai; Ranjit Kumar; Seval Ozkan; Hui Wang; Prashanti Manda; Tony Arick; Susan M Bridges; Shane C Burgess
Journal:  Nucleic Acids Res       Date:  2010-11-12       Impact factor: 16.971

4.  The proteogenomic mapping tool.

Authors:  William S Sanders; Nan Wang; Susan M Bridges; Brandon M Malone; Yoginder S Dandass; Fiona M McCarthy; Bindu Nanduri; Mark L Lawrence; Shane C Burgess
Journal:  BMC Bioinformatics       Date:  2011-04-22       Impact factor: 3.307

5.  AgBase: a unified resource for functional analysis in agriculture.

Authors:  Fiona M McCarthy; Susan M Bridges; Nan Wang; G Bryce Magee; W Paul Williams; Dawn S Luthe; Shane C Burgess
Journal:  Nucleic Acids Res       Date:  2006-11-29       Impact factor: 16.971

6.  AgBase: a functional genomics resource for agriculture.

Authors:  Fiona M McCarthy; Nan Wang; G Bryce Magee; Bindu Nanduri; Mark L Lawrence; Evelyn B Camon; Daniel G Barrell; David P Hill; Mary E Dolan; W Paul Williams; Dawn S Luthe; Susan M Bridges; Shane C Burgess
Journal:  BMC Genomics       Date:  2006-09-08       Impact factor: 3.969

7.  Optimized sample preparation for two-dimensional gel electrophoresis of soluble proteins from chicken bursa of Fabricius.

Authors:  Yongping Wu; Jiyong Zhou; Xin Zhang; Xiaojuan Zheng; Xuetao Jiang; Lixue Shi; Wei Yin; Junhua Wang
Journal:  Proteome Sci       Date:  2009-10-08       Impact factor: 2.480

8.  Overcoming function annotation errors in the Gram-positive pathogen Streptococcus suis by a proteomics-driven approach.

Authors:  Manuel J Rodríguez-Ortega; Inmaculada Luque; Carmen Tarradas; José A Bárcena
Journal:  BMC Genomics       Date:  2008-12-05       Impact factor: 3.969

9.  Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.

Authors:  James C Wright; Deana Sugden; Sue Francis-McIntyre; Isabel Riba-Garcia; Simon J Gaskell; Igor V Grigoriev; Scott E Baker; Robert J Beynon; Simon J Hubbard
Journal:  BMC Genomics       Date:  2009-02-04       Impact factor: 3.969

10.  Comprehensive proteomic analysis of bovine spermatozoa of varying fertility rates and identification of biomarkers associated with fertility.

Authors:  Divyaswetha Peddinti; Bindu Nanduri; Abdullah Kaya; Jean M Feugang; Shane C Burgess; Erdogan Memili
Journal:  BMC Syst Biol       Date:  2008-02-22
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