Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses

<p>Abstract</p> <p>Background</p> <p>Multidimensional protein identification technology (MudPIT)-based shot-gun proteomics has been proven to be an effective platform for functional proteomics. In particular, the various sample preparation methods and bioinformatics too...

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Main Authors: Zhang Yixiang, Liu Sanmin, Dai Susie Y, Yuan Joshua S
Format: Article
Language:English
Published: BMC 2012-09-01
Series:BMC Bioinformatics
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spelling doaj-f7c27400180343508e9416914538ce502020-11-25T02:15:33ZengBMCBMC Bioinformatics1471-21052012-09-0113Suppl 15S810.1186/1471-2105-13-S15-S8Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responsesZhang YixiangLiu SanminDai Susie YYuan Joshua S<p>Abstract</p> <p>Background</p> <p>Multidimensional protein identification technology (MudPIT)-based shot-gun proteomics has been proven to be an effective platform for functional proteomics. In particular, the various sample preparation methods and bioinformatics tools can be integrated to improve the proteomics platform for applications like target organelle proteomics. We have recently integrated a rapid sample preparation method and bioinformatics classification system for comparative analysis of plant responses to two plant hormones, zeatin and brassinosteroid (BR). These hormones belong to two distinct classes of plant growth regulators, yet both can promote cell elongation and growth. An understanding of the differences and the cross-talk between the two types of hormone responses will allow us to better understand the molecular mechanisms and to identify new candidate genes for plant engineering.</p> <p>Results</p> <p>As compared to traditional organelle proteomics, the organelle-enrichment method both simplifies the sample preparation and increases the number of proteins identified in the targeted organelle as well as the entire sample. Both zeatin and BR induce dramatic changes in signaling and metabolism. Their shared-regulated protein components indicate that both hormones may down-regulate some key components in auxin responses. However, they have shown distinct induction and suppression of metabolic pathways in mitochondria and chloroplast. For zeatin, the metabolic pathways in sucrose and starch biosynthesis and utilization were significantly changed, yet the lipid biosynthesis remained unchanged. For BR, lipid biosynthesis and β-oxidation were both down-regulated, yet the changes in sucrose and starch metabolism were minor.</p> <p>Conclusions</p> <p>We present a rapid sample preparation method and bioinformatics classification for effective proteomics analysis of plant hormone responses. The study highlighted the largely differing response to zeatin and brassinosteroid by the metabolic pathways in chloroplast and mitochondria.</p>
collection DOAJ
language English
format Article
sources DOAJ
author Zhang Yixiang
Liu Sanmin
Dai Susie Y
Yuan Joshua S
spellingShingle Zhang Yixiang
Liu Sanmin
Dai Susie Y
Yuan Joshua S
Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses
BMC Bioinformatics
author_facet Zhang Yixiang
Liu Sanmin
Dai Susie Y
Yuan Joshua S
author_sort Zhang Yixiang
title Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses
title_short Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses
title_full Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses
title_fullStr Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses
title_full_unstemmed Integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses
title_sort integration of shot-gun proteomics and bioinformatics analysis to explore plant hormone responses
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2012-09-01
description <p>Abstract</p> <p>Background</p> <p>Multidimensional protein identification technology (MudPIT)-based shot-gun proteomics has been proven to be an effective platform for functional proteomics. In particular, the various sample preparation methods and bioinformatics tools can be integrated to improve the proteomics platform for applications like target organelle proteomics. We have recently integrated a rapid sample preparation method and bioinformatics classification system for comparative analysis of plant responses to two plant hormones, zeatin and brassinosteroid (BR). These hormones belong to two distinct classes of plant growth regulators, yet both can promote cell elongation and growth. An understanding of the differences and the cross-talk between the two types of hormone responses will allow us to better understand the molecular mechanisms and to identify new candidate genes for plant engineering.</p> <p>Results</p> <p>As compared to traditional organelle proteomics, the organelle-enrichment method both simplifies the sample preparation and increases the number of proteins identified in the targeted organelle as well as the entire sample. Both zeatin and BR induce dramatic changes in signaling and metabolism. Their shared-regulated protein components indicate that both hormones may down-regulate some key components in auxin responses. However, they have shown distinct induction and suppression of metabolic pathways in mitochondria and chloroplast. For zeatin, the metabolic pathways in sucrose and starch biosynthesis and utilization were significantly changed, yet the lipid biosynthesis remained unchanged. For BR, lipid biosynthesis and β-oxidation were both down-regulated, yet the changes in sucrose and starch metabolism were minor.</p> <p>Conclusions</p> <p>We present a rapid sample preparation method and bioinformatics classification for effective proteomics analysis of plant hormone responses. The study highlighted the largely differing response to zeatin and brassinosteroid by the metabolic pathways in chloroplast and mitochondria.</p>
work_keys_str_mv AT zhangyixiang integrationofshotgunproteomicsandbioinformaticsanalysistoexploreplanthormoneresponses
AT liusanmin integrationofshotgunproteomicsandbioinformaticsanalysistoexploreplanthormoneresponses
AT daisusiey integrationofshotgunproteomicsandbioinformaticsanalysistoexploreplanthormoneresponses
AT yuanjoshuas integrationofshotgunproteomicsandbioinformaticsanalysistoexploreplanthormoneresponses
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