Dataset Information

Plasma membrane proteomics

ABSTRACT: Aluminum (Al) toxicity in acid soil is a worldwide agricultural problem that inhibits crop growth and productivity. However, the signal pathways associated with Al tolerance in plants still remain largely unclear. In this study, tandem mass tag (TMT)-based quantitative proteomic methods was used to identify the expression changes of plasma membrane (PM) proteins in Tamba black soybean (TBS) root tips under Al stress. The results showed that a total of 907 PM proteins were identified, and 90 differentially expressed proteins (DEPs) were disclosed between Al-treated and untreated plants, with 46 up-regulated and 44 down-regulated (fold change > 1.3 or < 0.77, P < 0.05). Functional enrichment based on GO, KEGG and protein domain revealed that the DEPs were associated with membrane trafficking and transporters, modifying cell wall composition, defense response and signal transduction.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Glycine Max

TISSUE(S): Root

SUBMITTER: yunmin wei

LAB HEAD: Yongxiong Yu

PROVIDER: PXD017160 | Pride | 2020-06-25

REPOSITORIES: Pride

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Plasma membrane proteomic analysis by TMT-PRM provides insight into mechanisms of aluminum resistance in tamba black soybean roots tips.

Wei Yunmin Y Jiang Caode C Han Rongrong R Xie Yonghong Y Liu Lusheng L Yu Yongxiong Y

PeerJ 20200610

Aluminum (Al) toxicity in acid soil is a worldwide agricultural problem that inhibits crop growth and productivity. However, the signal pathways associated with Al tolerance in plants remain largely unclear. In this study, tandem mass tag (TMT)-based quantitative proteomic methods were used to identify the differentially expressed plasma membrane (PM) proteins in Tamba black soybean (TBS) root tips under Al stress. Data are available via ProteomeXchange with identifier PXD017160. In addition, pa ...[more]

PMID: 32566407

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Project description:Purpose: In this study, we have undertaken the whole proteomic analysis and got a better understanding of biological processes involved in the development and progression of ccRCC. We hope promising biomarkers can be uncovered to facilitate early diagnosis, predict the prognosis and progression, more importantly, to be applied as potential therapeutic targets. Experimental design: Fresh frozen tissue samples were surgically resected from patients with local or locally advanced ccRCC. Trypsin digested proteins were analyzed using TMT-based LC-MS/MS proteomic approach, followed by bioinformatic analysis. A potential prognostic marker FMNL1, annotated with actin cytoskeleton assembly and cell migration, was chosen to be validated in TCGA_KIRC datasets(n=597), further validation sets(n=20) and expanded validation sets(n=97). Results: A total of 657 differentially expressed proteins were identified and quantified between ccRCC and adjacent normal tissues (p-value<0.05, FC>2 or<1/2), of which 186 proteins were up-regulated and 471 proteins were down-regulated. Bioinformatic analysis showed enriched metabolic biological processes and pathways including oxidative phosphorylation, valine, leucine and isoleucine degeneration, propanoate metabolism, fatty-acid degeneration, TCA cycle, glycolysis/gluconeogenesis, etc. Univariate and multivariate analysis defined FMNL1 as an independent negative prognostic marker in the TCGA datasets. High expression of FMNL1 correlated significantly with tumor stage, T stage, lymph node metastasis(P<0.05), and distant metastasis(P<0.05) both in the TCGA-KIRC datasets and expanded validation sets. And KM survival curve illustrated that patients with high FMNL1 protein level had shorter OS time in the expanded validation sets (p=0.0273) Conclusion and clinical relevance: The proteomic results uncovered sophisticated metabolic reprogramming of ccRCC and indicated that the upregulation of rate-limiting enzymes in glycolysis and mitochondrial impairment may be the cause of metabolic reprogramming in ccRCC. Moreover, FMNL1 has been identified as a diagnostic and prognostic marker, and may be implicated in the progression of ccRCC.

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Dataset Information

Plasma membrane proteomics

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Plasma membrane proteomic analysis by TMT-PRM provides insight into mechanisms of aluminum resistance in tamba black soybean roots tips.

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