Dataset Information

Maize seedling root cells LC-MS/MS

ABSTRACT: Soil waterlogging is one of the major abiotic stresses affecting maize growth and yields. To understand the molecular mechanisms underlying waterlogging tolerance in maize, the iTRAQ LC-MS/MS technique was employed to map the proteome of seedling root cells of the A3237 (tolerant inbred) and A3239 (sensitive inbred) lines under control and waterlogged conditions. Among the 3373 identified proteins, 293 were differentially abundant proteins (DAPs), of which 207 originated in A3237 and 158 in A3239. These DAPs were categorized into 11 groups that are closely related to plant defence responses, including metabolism, energy, disease/defense and transport. In the tolerant line A3237, NADP-malic enzyme, glutamate decarboxylase, coproporphyrinogen III oxidase, glutathione S-transferase TAU 25, glutathione dehydrogenase and xyloglucan endotransglycosylase 6 were specifically accumulated to manage energy, maintain pH levels and minimize oxidative damage in waterlogged root cells.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Zea Mays (maize)

TISSUE(S): Plant Cell, Root

DISEASE(S): Disease Free

SUBMITTER: Feng Yu

LAB HEAD: Fazhan Qiu

PROVIDER: PXD001125 | Pride | 2014-11-18

REPOSITORIES: Pride

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Publications

Comparative proteomic analysis revealing the complex network associated with waterlogging stress in maize (Zea mays L.) seedling root cells.

Yu Feng F Han Xuesong X Geng Cunjuan C Zhao Yanxin Y Zhang Zuxin Z Qiu Fazhan F

Proteomics 20141203 1

Soil waterlogging is one of the major abiotic stresses affecting maize grain yields. To understand the molecular mechanisms underlying waterlogging tolerance in maize, the iTRAQ LC-MS/MS technique was employed to map the proteomes of seedling root cells of the A3237 (tolerant inbred) and A3239 (sensitive inbred) lines under control and waterlogging conditions. Among the 3318 proteins identified, 211 were differentially abundant proteins (DAPs), of which 81 were specific to A3237 and 57 were spec ...[more]

PMID: 25316036

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Project description:Background: Results obtained from our previous study using a label-free quantitation (LF) proteomic approach in which dynamic range compression was used to profile lower abundance proteins, demonstrated few proteins that were differentially abundant within the synovial fluid (SF) when comparing Autologous Chondrocyte Implantation (ACI) responders and non-responders at baseline (1). This study builds upon our previous findings by assessing higher abundance proteins within these SFs; providing a more global proteome analysis from which we can understand more fully the biology underlying ACI success or failure. Methods: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomics was used to assess SFs from ACI responders (mean Lysholm improvement of 33; n=14) and non-responders (mean Lysholm decrease of 14; n=13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins were investigated using pathway analyses and the iTRAQ proteomic dataset was combined with our published proteomic dataset of dynamically compressed SFs, from which an interactome network model of systemic protein interactions was generated. Results: iTRAQ proteomics has confirmed our previous finding that there is a marked proteome shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥2.0 fold change between Stages I and II in responders and non-responders, respectively) and has highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, that were not found in the LF study; 16 of which were altered at baseline. Two protein abundance changes (Complement C1S subcomponent and Matrix metalloproteinase 3 (MMP3), have been biochemically validated. Combination of the iTRAQ and LF proteomic datasets has generated in-depth SF proteome information that has been used to generate interactome networks representing ACI success or failure, from which functional pathways that are dysregulated in ACI non-responders have been identified. Conclusions: Several candidate biomarkers for baseline prediction of ACI outcome have been identified. A holistic overview of the SF proteome in responders and non-responders to ACI has been profiled providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders.

Project description:Constituting the final growth phase during the lifecycle of maize (Zea Mays L.), leaf senescence plays an important biological role in grain yield in crops. We undertook proteomic and physiological analyses in inbred line Yu816 in order to unravel the underlying mechanisms of leaf senescence induced by preventing pollination. A total of 6,941 proteins were identified by Isobaric tags for Relative and Absolute Quantitation (iTRAQ) analysis. Proteomic analyses between pollinated (POL) and non-pollinated (NONPOL) plants indicated that 973 different proteins accumulated in NONPOL plants. The accumulated proteins were classified into various groups, including response to stimuli, cellular processes, cell death and metabolic processes using functional analysis. Furthermore, in accordance with the changes in these different accumulated proteins, analysis of changes in leaf total soluble sugars and starch content showed that the prevention of pollination can disturb endogenousplant hormone and sugar metabolism and lead to ROS bursts, protein degradation and photosystem breakdown, eventually resulting in leaf senescence. This represents the first attempt at global proteome profiling in response to induced leaf senescence by preventing pollination in maize, and provides a better understanding of the molecular mechanisms involved in induced leaf senescence.Constituting the final growth phase during the lifecycle of maize (Zea Mays L.), leaf senescence plays an important biological role in grain yield in crops. We undertook proteomic and physiological analyses in inbred line Yu816 in order to unravel the underlying mechanisms of leaf senescence induced by preventing pollination. A total of 6,941 proteins were identified by Isobaric tags for Relative and Absolute Quantitation (iTRAQ) analysis. Proteomic analyses between pollinated (POL) and non-pollinated (NONPOL) plants indicated that 973 different proteins accumulated in NONPOL plants. The accumulated proteins were classified into various groups, including response to stimuli, cellular processes, cell death and metabolic processes using functional analysis. Furthermore, in accordance with the changes in these different accumulated proteins, analysis of changes in leaf total soluble sugars and starch content showed that the prevention of pollination can disturb endogenousplant hormone and sugar metabolism and lead to ROS bursts, protein degradation and photosystem breakdown, eventually resulting in leaf senescence. This represents the first attempt at global proteome profiling in response to induced leaf senescence by preventing pollination in maize, and provides a better understanding of the molecular mechanisms involved in induced leaf senescence.

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Dataset Information

Maize seedling root cells LC-MS/MS

Publications

Comparative proteomic analysis revealing the complex network associated with waterlogging stress in maize (Zea mays L.) seedling root cells.

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