Literature DB >> 16219920

Combining experimental and predicted datasets for determination of the subcellular location of proteins in Arabidopsis.

Joshua L Heazlewood1, Julian Tonti-Filippini, Robert E Verboom, A Harvey Millar.   

Abstract

Substantial experimental datasets defining the subcellular location of Arabidopsis (Arabidopsis thaliana) proteins have been reported in the literature in the form of organelle proteomes built from mass spectrometry data (approximately 2,500 proteins). Subcellular location for specific proteins has also been published based on imaging of chimeric fluorescent fusion proteins in intact cells (approximately 900 proteins). Further, the more diverse history of biochemical determination of subcellular location is stored in the entries of the Swiss-Prot database for the products of many Arabidopsis genes (approximately 1,800 proteins). Combined with the range of bioinformatic targeting prediction tools and comparative genomic analysis, these experimental datasets provide a powerful basis for defining the final location of proteins within the wide variety of subcellular structures present inside Arabidopsis cells. We have analyzed these published experimental and prediction data to answer a range of substantial questions facing researchers about the veracity of these approaches to determining protein location and their interrelatedness. We have merged these data to form the subcellular location database for Arabidopsis proteins (SUBA), providing an integrated understanding of protein location, encompassing the plastid, mitochondrion, peroxisome, nucleus, plasma membrane, endoplasmic reticulum, vacuole, Golgi, cytoskeleton structures, and cytosol (www.suba.bcs.uwa.edu.au). This includes data on more than 4,400 nonredundant Arabidopsis protein sequences. We also provide researchers with an online resource that may be used to query protein sets or protein families and determine whether predicted or experimental location data exist; to analyze the nature of contamination between published proteome sets; and/or for building theoretical subcellular proteomes in Arabidopsis using the latest experimental data.

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Year:  2005        PMID: 16219920      PMCID: PMC1255979          DOI: 10.1104/pp.105.065532

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  73 in total

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2.  Proteomic identification of divalent metal cation binding proteins in plant mitochondria.

Authors:  V L Herald; J L Heazlewood; D A Day; A H Millar
Journal:  FEBS Lett       Date:  2003-02-27       Impact factor: 4.124

3.  Experimental analysis of the Arabidopsis mitochondrial proteome highlights signaling and regulatory components, provides assessment of targeting prediction programs, and indicates plant-specific mitochondrial proteins.

Authors:  Joshua L Heazlewood; Julian S Tonti-Filippini; Alexander M Gout; David A Day; James Whelan; A Harvey Millar
Journal:  Plant Cell       Date:  2003-12-11       Impact factor: 11.277

4.  Free-flow electrophoresis for fractionation of Arabidopsis thaliana membranes.

Authors:  N Bardy; A Carrasco; J P Galaud; R Pont-Lezica; H Canut
Journal:  Electrophoresis       Date:  1998-06       Impact factor: 3.535

5.  Random GFP::cDNA fusions enable visualization of subcellular structures in cells of Arabidopsis at a high frequency.

Authors:  S R Cutler; D W Ehrhardt; J S Griffitts; C R Somerville
Journal:  Proc Natl Acad Sci U S A       Date:  2000-03-28       Impact factor: 11.205

6.  The focusing positions of polypeptides in immobilized pH gradients can be predicted from their amino acid sequences.

Authors:  B Bjellqvist; G J Hughes; C Pasquali; N Paquet; F Ravier; J C Sanchez; S Frutiger; D Hochstrasser
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7.  A proteomic analysis of organelles from Arabidopsis thaliana.

Authors:  T A Prime; D J Sherrier; P Mahon; L C Packman; P Dupree
Journal:  Electrophoresis       Date:  2000-10       Impact factor: 3.535

8.  Proteomic analysis of the Arabidopsis thaliana cell wall.

Authors:  Stephen Chivasa; Bongani K Ndimba; William J Simon; Duncan Robertson; Xiao-Lan Yu; J Paul Knox; Paul Bolwell; Antoni R Slabas
Journal:  Electrophoresis       Date:  2002-06       Impact factor: 3.535

9.  Genome-wide insertional mutagenesis of Arabidopsis thaliana.

Authors:  José M Alonso; Anna N Stepanova; Thomas J Leisse; Christopher J Kim; Huaming Chen; Paul Shinn; Denise K Stevenson; Justin Zimmerman; Pascual Barajas; Rosa Cheuk; Carmelita Gadrinab; Collen Heller; Albert Jeske; Eric Koesema; Cristina C Meyers; Holly Parker; Lance Prednis; Yasser Ansari; Nathan Choy; Hashim Deen; Michael Geralt; Nisha Hazari; Emily Hom; Meagan Karnes; Celene Mulholland; Ral Ndubaku; Ian Schmidt; Plinio Guzman; Laura Aguilar-Henonin; Markus Schmid; Detlef Weigel; David E Carter; Trudy Marchand; Eddy Risseeuw; Debra Brogden; Albana Zeko; William L Crosby; Charles C Berry; Joseph R Ecker
Journal:  Science       Date:  2003-08-01       Impact factor: 47.728

10.  ARAMEMNON, a novel database for Arabidopsis integral membrane proteins.

Authors:  Rainer Schwacke; Anja Schneider; Eric van der Graaff; Karsten Fischer; Elisabetta Catoni; Marcelo Desimone; Wolf B Frommer; Ulf-Ingo Flügge; Reinhard Kunze
Journal:  Plant Physiol       Date:  2003-01       Impact factor: 8.340

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  61 in total

1.  Mitochondrial biogenesis and function in Arabidopsis.

Authors:  A Harvey Millar; Ian D Small; David A Day; James Whelan
Journal:  Arabidopsis Book       Date:  2008-07-09

2.  Web-based Arabidopsis functional and structural genomics resources.

Authors:  Yan Lu; Robert L Last
Journal:  Arabidopsis Book       Date:  2008-10-28

3.  Combining machine learning and homology-based approaches to accurately predict subcellular localization in Arabidopsis.

Authors:  Rakesh Kaundal; Reena Saini; Patrick X Zhao
Journal:  Plant Physiol       Date:  2010-07-20       Impact factor: 8.340

4.  A predicted interactome for Arabidopsis.

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Journal:  Plant Physiol       Date:  2007-08-03       Impact factor: 8.340

5.  Nuclear, chloroplast, and mitochondrial transcript abundance along a maize leaf developmental gradient.

Authors:  A Bruce Cahoon; Elizabeth M Takacs; Richard M Sharpe; David B Stern
Journal:  Plant Mol Biol       Date:  2007-10-12       Impact factor: 4.076

Review 6.  The continuing conundrum of the LEA proteins.

Authors:  Alan Tunnacliffe; Michael J Wise
Journal:  Naturwissenschaften       Date:  2007-05-04

7.  Conservation of dual-targeted proteins in Arabidopsis and rice points to a similar pattern of gene-family evolution.

Authors:  Carolina V Morgante; Ricardo A O Rodrigues; Phellippe A S Marbach; Camila M Borgonovi; Daniel S Moura; Marcio C Silva-Filho
Journal:  Mol Genet Genomics       Date:  2009-02-13       Impact factor: 3.291

8.  Arabidopsis nuclear-encoded plastid transit peptides contain multiple sequence subgroups with distinctive chloroplast-targeting sequence motifs.

Authors:  Dong Wook Lee; Jong Kyoung Kim; Sumin Lee; Seungjin Choi; Sanguk Kim; Inhwan Hwang
Journal:  Plant Cell       Date:  2008-06-13       Impact factor: 11.277

9.  Divalent metal ions in plant mitochondria and their role in interactions with proteins and oxidative stress-induced damage to respiratory function.

Authors:  Yew-Foon Tan; Nicholas O'Toole; Nicolas L Taylor; A Harvey Millar
Journal:  Plant Physiol       Date:  2009-12-14       Impact factor: 8.340

10.  Arginase-negative mutants of Arabidopsis exhibit increased nitric oxide signaling in root development.

Authors:  Teresita Flores; Christopher D Todd; Alejandro Tovar-Mendez; Preetinder K Dhanoa; Natalia Correa-Aragunde; Mary Elizabeth Hoyos; Disa M Brownfield; Robert T Mullen; Lorenzo Lamattina; Joe C Polacco
Journal:  Plant Physiol       Date:  2008-06-20       Impact factor: 8.340

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