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New insights into the maize disease lesion mimics-conferred defense response revealed by integrated transcriptomics and metabolomics analysis

ABSTRACT: New insights into the maize disease lesion mimics-conferred defense response revealed by integrated transcriptomics and metabolomics analysis

PROVIDER: PRJNA623523 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11497400_1.fastq.gz	Fastqsanger.gz
	SRR11497400_2.fastq.gz	Fastqsanger.gz
	SRR11497401_1.fastq.gz	Fastqsanger.gz
	SRR11497401_2.fastq.gz	Fastqsanger.gz
	SRR11497402_1.fastq.gz	Fastqsanger.gz

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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.

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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New insights into the maize disease lesion mimics-conferred defense response revealed by integrated transcriptomics and metabolomics analysis

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