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ITRAQ-based quantitative proteome analysis reveals metabolic changes between a cleistogamous wheat mutant and its wild-type wheat counterpart.

ABSTRACT: Background:Wheat is one of the most important staple crops worldwide. Fusarium head blight (FHB) severely affects wheat yield and quality. A novel bread wheat mutant, ZK001, characterized as cleistogamic was isolated from a non-cleistogamous variety Yumai 18 (YM18) through static magnetic field mutagenesis. Cleistogamy is a promising strategy for controlling FHB. However, little is known about the mechanism of cleistogamy in wheat. Methods:We performed a FHB resistance test to identify the FHB infection rate of ZK001. We also measured the agronomic traits of ZK001 and the starch and total soluble sugar contents of lodicules in YM18 and ZK001. Finally, we performed comparative studies at the proteome level between YM18 and ZK001 based on the proteomic technique of isobaric tags for relative and absolute quantification. Results:The infection rate of ZK001 was lower than that of its wild-type and Aikang 58. The abnormal lodicules of ZK001 lost the ability to push the lemma and palea apart during the flowering stage. Proteome analysis showed that the main differentially abundant proteins (DAPs) were related to carbohydrate metabolism, protein transport, and calcium ion binding. These DAPs may work together to regulate cellular homeostasis, osmotic pressure and the development of lodicules. This hypothesis is supported by the analysis of starch, soluble sugar content in the lodicules as well as the results of Quantitative reverse transcription polymerase chain reaction. Conclusions:Proteomic analysis has provided comprehensive information that should be useful for further research on the lodicule development mechanism in wheat. The ZK001 mutant is optimal for studying flower development in wheat and could be very important for FHB resistant projects via conventional crossing.

SUBMITTER: Tang C

PROVIDER: S-EPMC6585907 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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iTRAQ-based quantitative proteome analysis reveals metabolic changes between a cleistogamous wheat mutant and its wild-type wheat counterpart.

Tang Caiguo C Zhang Huilan H Zhang Pingping P Ma Yuhan Y Cao Minghui M Hu Hao H Shah Faheem Afzal FA Zhao Weiwei W Li Minghao M Wu Lifang L

PeerJ 20190617

<h4>Background</h4>Wheat is one of the most important staple crops worldwide. <i>Fusarium</i> head blight (FHB) severely affects wheat yield and quality. A novel bread wheat mutant, <i>ZK001</i>, characterized as cleistogamic was isolated from a non-cleistogamous variety Yumai 18 (YM18) through static magnetic field mutagenesis. Cleistogamy is a promising strategy for controlling FHB. However, little is known about the mechanism of cleistogamy in wheat.<h4>Methods</h4>We performed a FHB resistan ...[more]

PMID: 31245178

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Project description:BackgroundWheat (Triticum aestivum L.) is an economically important grain crop. Two-dimensional gel-based approaches are limited by the low identification rate of proteins and lack of accurate protein quantitation. The recently developed isobaric tag for relative and absolute quantitation (iTRAQ) method allows sensitive and accurate protein quantification. Here, we performed the first iTRAQ-based quantitative proteome and phosphorylated proteins analyses during wheat grain development.ResultsThe proteome profiles and phosphoprotein characterization of the metabolic proteins during grain development of the elite Chinese bread wheat cultivar Yanyou 361 were studied using the iTRAQ-based quantitative proteome approach, TiO2 microcolumns, and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Among 1,146 non-redundant proteins identified, 421 showed at least 2-fold differences in abundance, and they were identified as differentially expressed proteins (DEPs), including 256 upregulated and 165 downregulated proteins. Of the 421 DEPs, six protein expression patterns were identified, most of which were up, down, and up-down expression patterns. The 421 DEPs were classified into nine functional categories mainly involved in different metabolic processes and located in the membrane and cytoplasm. Hierarchical clustering analysis indicated that the DEPs involved in starch biosynthesis, storage proteins, and defense/stress-related proteins significantly accumulated at the late grain development stages, while those related to protein synthesis/assembly/degradation and photosynthesis showed an opposite expression model during grain development. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis of 12 representative genes encoding different metabolic proteins showed certain transcriptional and translational expression differences during grain development. Phosphorylated proteins analyses demonstrated that 23 DEPs such as AGPase, sucrose synthase, Hsp90, and serpins were phosphorylated in the developing grains and were mainly involved in starch biosynthesis and stress/defense.ConclusionsOur results revealed a complex quantitative proteome and phosphorylation profile during wheat grain development. Numerous DEPs are involved in grain starch and protein syntheses as well as adverse defense, which set an important basis for wheat yield and quality. Particularly, some key DEPs involved in starch biosynthesis and stress/defense were phosphorylated, suggesting their roles in wheat grain development.

Project description:Chlamydia muridarum, an obligate intracellular pathogen, was used to establish a murine model of female upper genital tract infection by Chlamydia trachomatis. TC0668 in C. muridarum is a hypothetical chromosomal virulence protein that is involved in upper genital tract pathogenesis. The infection of mice with the C. muridarum TC0668-mutant (G216*) strain results in less pathological damage in the upper genital tract. In this study, an isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics analysis was performed to identify differentially expressed proteins between TC0668 wild-type (TC0668wt) and TC0668 mutant (TC0668mut) strains at 6, 12, 18, and 24 h post-infection (p.i.). Of the 550 proteins differentially expressed at 18 h p.i., 222 and 328 were up-regulated and down-regulated, respectively, inTC0668mut-infected cells. The expression of seven up-regulated proteins (encoded by SRPRB, JAK1, PMM1, HLA-DQB1, THBS1, ITPR1, and BCAP31) and three down-regulated proteins (encoded by MAPKAPK2, TRAFD1, and IFI16) from the iTRAQ analysis were validated using quantitative real-time (qRT)-PCR. The qRT-PCR results were consistent with those of iTRAQ. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the differentially expressed proteins primarily participated in inflammatory responses, fibrosis, metabolic processes, and complement coagulation cascades, and were mainly enriched in the phosphatidylinositol 3'-kinase (PI3K)/Akt, nuclear factor kappa-B (NF-κB), and other signaling pathways. Using western-blotting and immunofluorescence detection, significant differences in activation of the PI3K/Akt and NF-κB signaling pathways were observed between the TC0668wt- and TC0668mut-infected cells. Differentially expressed proteins linked with inflammation and fibrosis were used in a protein-protein interaction network analysis. The results suggest that TC0668 may play a pivotal role in C. muridarum-induced genital pathology by inducing inflammatory responses and fibrosis, which may involve the activation of the PI3K/Akt and NF-κB signaling pathways.

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Project description:BackgroundHuman saliva is a protein-rich, easily accessible source of potential biomarkers for the diagnosis of oral and systemic diseases. However, little is known about the changes in salivary proteome associated with aging of patients with dental caries. Here, we applied isobaric tags for relative and absolute quantitation (iTRAQ) in combination with multiple reaction monitoring mass spectrometry (MRM-MS) to characterize the salivary proteome profiles of subjects of different ages, presenting with and without caries, with the aim of identifying age-related biomarkers for dental caries.MethodsUnstimulated whole saliva samples were collected from 40 caries-free and caries-susceptible young adults and elderly individuals. Salivary proteins were extracted, reduced, alkylated, digested with trypsin and then analyzed using iTRAQ-coupled LC-MS/MS, followed by GO annotation, biological pathway analysis, hierarchical clustering analysis, and protein-protein interaction analysis. Candidate verification was then conducted using MRM-MS.ResultsAmong 658 salivary proteins identified using tandem mass spectrometry, 435 proteins exhibited altered expression patterns in different age groups with and without caries. Of these proteins, 96 displayed age-specific changes among caries-susceptible adults and elderly individuals, and were mainly associated with salivary secretion pathway, while 110 age-specific proteins were identified among healthy individuals. It was found that the age factor caused significant variations and played an important role in both healthy and cariogenic salivary proteomes. Subsequently, a total of 136 target proteins with complex protein-protein interactions, including 14 age-specific proteins associated with caries, were further successfully validated using MRM analysis. Moreover, non-age-specific proteins (histatin-1 and BPI fold-containing family B member 1) were verified to be important candidate biomarkers for common dental caries.ConclusionsOur proteomic analysis performed using the discovery-through-verification pipeline revealed distinct variations caused by age factor in both healthy and cariogenic salivary proteomes, highlighting the significance of age in the great potential of saliva for caries diagnosis and biomarker discovery.

Project description:It is generally recognized that proteins constitute the key cellular component in shaping microbial phenotypes. Due to limited cellular resources and space, optimal allocation of proteins is crucial for microbes to facilitate maximum proliferation rates while allowing a flexible response to environmental changes. To account for the growth condition-dependent proteome in the constraint-based metabolic modeling of Escherichia coli, we consolidated a coarse-grained protein allocation approach with the explicit consideration of enzymatic constraints on reaction fluxes. Besides representing physiologically relevant wild-type phenotypes and flux distributions, the resulting protein allocation model (PAM) advances the predictability of the metabolic responses to genetic perturbations. A main driver of mutant phenotypes was ascribed to inherited regulation patterns in protein distribution among metabolic enzymes. Moreover, the PAM correctly reflected metabolic responses to an augmented protein burden imposed by the heterologous expression of green fluorescent protein. In summary, we were able to model the effects of important and frequently applied metabolic engineering approaches on microbial metabolism. Therefore, we want to promote the integration of protein allocation constraints into classical constraint-based models to foster their predictive capabilities and application for strain analysis and engineering purposes.IMPORTANCE Predictive metabolic models are important, e.g., for generating biological knowledge and designing microbes with superior performance for target compound production. Yet today's whole-cell models either show insufficient predictive capabilities or are computationally too expensive to be applied to metabolic engineering purposes. By linking the inherent genotype-phenotype relationship to a complete representation of the proteome, the PAM advances the accuracy of simulated phenotypes and intracellular flux distributions of E. coli Being equally computationally lightweight as classical stoichiometric models and allowing for the application of established in silico tools, the PAM and related simulation approaches will foster the use of a model-driven metabolic research. Applications range from the investigation of mechanisms of microbial evolution to the determination of optimal strain design strategies in metabolic engineering, thus supporting basic scientists and engineers alike.

Dataset Information

ITRAQ-based quantitative proteome analysis reveals metabolic changes between a cleistogamous wheat mutant and its wild-type wheat counterpart.

Publications

iTRAQ-based quantitative proteome analysis reveals metabolic changes between a cleistogamous wheat mutant and its wild-type wheat counterpart.

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