New insights into the maize disease lesion mimics-conferred defense response revealed by integrated transcriptomics and metabolomics analysis
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ABSTRACT:
ORGANISM(S): Zea mays
PROVIDER: GSE148220 | GEO | 2021/05/12
REPOSITORIES: GEO
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Project description:New insights into the maize disease lesion mimics-conferred defense response revealed by integrated transcriptomics and metabolomics analysis
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Project description:Disease lesion mimic (Les/les) mutants display disease-like spontaneous lesions in the absence of pathogen infection, implying the constitutive activation of defense responses. However, the genetic and biochemical bases underlying the activated defense responses in those mutants remain largely unknown. Here, we performed integrated transcriptomics and metabolomics analysis on three typical maize Les mutants Les4, Les10, and Les17 with large, medium, and small lesion size, respectively, thereby dissecting the activated defense responses at the transcriptional and metabolomic level. A total of 1,714, 4,887, and 1,625 differentially expressed genes (DEGs) were identified in Les4, Les10, and Les17, respectively. Among them, 570, 3,299, and 447 specific differentially expressed genes (SGs) were identified, implying a specific function of each LES gene. In addition, 480 common differentially expressed genes (CGs) and 42 common differentially accumulated metabolites (CMs) were identified in all Les mutants, suggesting the robust activation of shared signaling pathways. Intriguingly, substantial analysis of the CGs indicated that genes involved in the programmed cell death, defense responses, and phenylpropanoid and terpenoid biosynthesis were most commonly activated. Genes involved in photosynthetic biosynthesis, however, were generally repressed. Consistently, the dominant CMs identified were phenylpropanoids and flavonoids. In particular, lignin, the phenylpropanoid-based polymer, was significantly increased in all three mutants. These data collectively imply that transcriptional activation of defense-related gene expression; increase of phenylpropanoid, lignin, flavonoid, and terpenoid biosynthesis; and inhibition of photosynthesis are generalnatures associated with the lesion formation and constitutively activated defense responses in those mutants. Further studies on the identified SGs and CGs will shed new light on the function of each LES gene as well as the regulatory network of defense responses in maize.
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Project description:To gain comprehensive and accurate system biological information, we developed a multiomics analytical method that integrated metabolomics and proteomics, named Windows Scanning Multiomics (WSM).
2023-12-18 | PXD046533 | Pride
Project description:The goal of this study is to characterize the human immune responses to the live attenuated Herpes zoster vaccine Zostavax, to understand the molecular and cellular mechanisms that lead to antibody production and T cell induction, and to understand the difference between young and elderly healthy adults. The overall data collection included antigen specific assays, flow cytometric profiling of innate and adaptive cell populations, measurement of serum cytokines, and transcriptomic and metabolomics signatures. Zostavax induced robust antigen-specific antibody responses, and significant T cell responses. A number of gene pathways were upregulated after vaccination. Using our previously developed blood transcription modules, we also identified transcriptomic correlates to antibody response. Furthermore, this study revealed strong association between PBMC transcriptomics and plasma metabolomics. Integrative analysis of orthogonal datasets from metabolomics, transcriptomic and immune profiling facilitated a temporal reconstruction of Zostavax induced biological networks culminating in antibody responses , and the delineation of novel molecular correlates of vaccine immunity.
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Project description:Tibetan sheep microbiome and metabolomics
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Project description:This study aims at identifying a dual transcriptomics and metabolomics blood signature following administration of CpG-ODN (cytosine-phosphate-guanine oligodeoxynucleotides), a reference immune-stimulatory molecule. A clinical study was conducted with chicks and transcriptomics and metabolomics analyses were performed on whole-blood and plasma samples respectively. Statistical analyses resulting in lists of differentially expressed genes and metabolites with different abundance were identified in chicks treated with CpG-ODN. The results showed that CpG-ODN activates the innate immune systems within hours following administration and its effect lasts over time, as metabolomic and transcriptomic profiles are still varying at 6 days after administration.
2019-10-17 | GSE138956 | GEO
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Project description:Unintended effects of genetically modified (GM) crops may pose safety issues. Omics techniques provide researchers with useful tools to assess such unintended effects. Proteomics and metabolomics analyses were performed for three GM maize varieties, 2A-7, CC-2, and 2A-7×CC-2 stacked transgenic maize, and the corresponding non-GM parent Zheng58.Proteomics revealed 120, 271 and 135 maize differentially expressed proteins (DEPs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most DEPs participated in metabolic pathways and the biosynthesis of secondary metabolite. Metabolomics revealed 179, 135 and 131 differentially accumulated metabolites (DAMs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Based on KEGG enrichment analysis, most DAMs are involved in the biosynthesis of secondary metabolite and metabolic pathways. According to integrated proteomics and metabolomics analysis, the introduction of exogenous EPSPS did not affect the expression levels of six other enzymes or the abundance of seven metabolites involved in the shikimic acid pathway in CC-2 and 2A-7×CC-2 seeds. Six co-DEPs annotated by integrated proteomics and metabolomics pathway analysis were further analyzed by qRT-PCR.This study successfully employed integrated proteomic and metabolomic technology to assess unintended changes in maize varieties. The results suggest that GM and gene stacking do not cause significantly unintended effects.
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Project description:Fusarium ear rot (FER) caused by Fusarium verticillioides is one of the main fungal diseases in maize worldwide. To develop a pathogen-tailored FER resistant maize line for local implementation, insights into the virulence variability of a residing F. verticillioides population are crucial for developing customized maize varieties, but remain unexplored. Moreover, little information is currently available on the involvement of the archetypal defense pathways in the F. verticillioides-maize interaction using local isolates and germplasm, respectively. Therefore, this study aims to fill these knowledge gaps. We used a collection of 12 F. verticillioides isolates randomly gathered from diseased maize fields in the Vietnamese central highlands. To assess the plant's defense responses against the pathogens, two of the most important maize hybrid genotypes grown in this agro-ecological zone, lines CP888 and Bt/GT NK7328, were used. Based on two assays, a germination and an in-planta assay, we found that line CP888 was more susceptible to the F. verticillioides isolates when compared to line Bt/GT NK7328. Using the most aggressive isolate, we monitored disease severity and gene expression profiles related to biosynthesis pathways of salicylic acid (SA), jasmonic acid (JA), abscisic acid (ABA), benzoxazinoids (BXs), and pathogenesis-related proteins (PRs). As a result, a stronger induction of SA, JA, ABA, BXs, and PRs synthesizing genes might be linked to the higher resistance of line Bt/GT NK7328 compared to the susceptible line CP888. All these findings could supply valuable knowledge in the selection of suitable FER resistant lines against the local F. verticllioides population and in the development of new FER resistant germplasms.
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Project description:The interplay between pathogens and hosts has been studied for decades using targeted approaches such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods such as transcriptomics and proteomics have been used to study host-pathogen interactions. Recently, metabolomics was established as a new method to study changes in the biochemical composition of host tissues. We report a metabolomics study of Salmonella enterica serovar Typhimurium infection. We used Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Direct Infusion to reveal that dozens of host metabolic pathways are affected by Salmonella in a murine infection model. In particular, multiple host hormone pathways are disrupted. Our results identify unappreciated effects of infection on host metabolism and shed light on mechanisms used by Salmonella to cause disease, and by the host to counter infection. Female C57BL/6 mice were infected with Salmonella enterica serovar Typhimurium SL1344 cells by oral gavage. Feces and livers were collected and metabolites extracted using acetonitrile. For experiments with feces, samples were collected from 4 mice before and after infection. For liver experiments, 11 uninfected and 11 infected mice were used. Samples were combined into 3 groups of 3-4 mice each, resulting in the analysis of 3 group samples of uninfected and 3 of infected mice. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140 [PMID 19081807]). To identify differences in metabolite composition between uninfected and infected samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from uninfected and infected mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.
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