Dataset Information

OsPAL2-1 Mediates Allelopathic Interactions Between Rice and Specific Microorganisms in the Rhizosphere Ecosystem.

ABSTRACT: The use of plant allelopathy to control weeds in the field has been generally recognized as a win-win strategy because it is an environmentally friendly and resource-saving method. The mechanism of this natural weed-control method relies on allelochemicals, the rhizosphere microbiome, and their bio-interaction, and exploring the link between allelochemicals and specific microbes helps accelerate the application of allelopathic characteristics in farming. In this study, we used allelopathic rice PI312777 (PI), its genetically modified OsPAL2-1 repression (PR) or overexpression (PO) lines, and non-allelopathic rice Lemont (Le) as donor plants to reveal the bio-interaction between rice allelochemicals and rhizosphere specific microorganisms. The results showed a higher content of phenolic acid exudation from the roots of PI than those of Le, which resulted in a significantly increased population of Myxococcus in the rhizosphere soil. Transgenic PO lines exhibited increasing exudation of phenolic acid, which led to the population of Myxococcus xanthus in the rhizosphere soil of PO to be significantly increased, while PR showed the opposite result in comparison with wild type PI. Exogenous application of phenolic acid induced the growth of M. xanthus, and the expressions of chemotaxis-related genes were up-regulated in M. xanthus. In addition, quercetin was identified in the culture medium; according to the bioassay determination, a quercetin concentration of 0.53 mM inhibited the root length by 60.59%. Our study indicates that OsPAL2-1 is among the efficient genes that regulate rice allelopathy by controlling the synthesis of phenolic acid allelochemicals, and phenolic acid (ferulic acid, FA) induces the chemotactic aggregation of M. xanthus, which promoted the proliferation and aggregation of this microbe. The potential allelochemical, quercetin was generated from the FA-induced M. xanthus cultured medium.

SUBMITTER: Li Y

PROVIDER: S-EPMC7391800 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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<i>OsPAL2-1</i> Mediates Allelopathic Interactions Between Rice and Specific Microorganisms in the Rhizosphere Ecosystem.

Li Yingzhe Y Jian Xin X Li Yue Y Zeng Xiaomei X Xu Lining L Khan Muhammad Umar MU Lin Wenxiong W

Frontiers in microbiology 20200723

The use of plant allelopathy to control weeds in the field has been generally recognized as a win-win strategy because it is an environmentally friendly and resource-saving method. The mechanism of this natural weed-control method relies on allelochemicals, the rhizosphere microbiome, and their bio-interaction, and exploring the link between allelochemicals and specific microbes helps accelerate the application of allelopathic characteristics in farming. In this study, we used allelopathic rice ...[more]

PMID: 32793125

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Project description:BackgroundIdentification of the allelopathy-interrelated metabolites from the allelopathic rice rhizosphere is crucial to understand the allelopathic mechanism of rice, which in turn can promote its applications to farming. In this study, the metabolites from the rhizosphere soil of five different rice lines, including allelopathic rice accession PI312777 (PI) and non-allelopathic rice accession Lemont (Le) as well as their genetic derivatives (e.g., phenylalanine ammonia-lyase (PAL) gene overexpression transgenic lines of PI and Le, namely, PO and LO respectively, and PAL RNA interference line of PI, namely, PR) were identified and comparatively analyzed to explore the positive compounds that are involved in the process of rice allelopathy.ResultsThe results showed that 21 non-polar compounds and 21 polar compounds differed in content in the rhizosphere soil of PI and Le, which include several volatile fatty acids and long-chain fatty acids. The relative contents of fatty acids also differed between PAL overexpressing or RNA interference (RNAi)-silenced line and their wild-type respectively. Acetic acid content also differed among groups, i.e., it is higher in the high allelopathic potential rice. Further analysis showed that different metabolites from the ADS8 resin-extracted phase were more abundant than that those from the ADS21 resin-extracted phase, suggesting that the allelochemicals in root exudates of allelopathic rice are mainly non-polar substances. KEGG annotation of these differential metabolites revealed that these compounds were related to nutrient metabolism, secondary metabolite synthesis, signaling substance synthesis, and toxin degradation.ConclusionsRice allelochemicals deposited in the ADS8 resin-extracted phase were more abundant than those in the ADS21 resin-extracted phase. Allelochemicals in root exudates of allelopathic rice are mainly non-polar substances, and long-chain fatty acids are considered as allelopathy interrelated metabolites.

Project description:BackgroundAllelopathy in rice (Oryza sativa) is a chemically induced response that is elevated by the exogenous application of chemical compounds and barnyard grass root exudates. An in-depth understanding of the response mechanisms of rice to chemical induction is necessary for the identification of target genes for increasing the allelopathic potential of rice. However, no previous studies have evaluated the transcriptomic changes associated with allelopathy in rice in response to barnyard grass exudates treatment. Thus, the aim of the present study was to reveal differentially expressed genes (DEGs) in allelopathic and non-allelopathic rice seedlings treated with barnyard grass exudates to identify target allelopathy genes.ResultsThe inhibitory effect of the culture solutions on the allelopathic rice accession PI312777 (PI) and the non-allelopathic rice accession Lemont (LE) significantly increased (P < 0.05) after treatment with barnyard grass root exudates. The RNA sequencing results revealed that 14,891 genes in PI(+B) vs. LE(+B), 12,505 genes in PI(+B) vs. PI(-B), and 5857 genes in LE(+B) vs. LE(-B) were differentially expressed following root exudates treatment. These DEGs were classified into three categories and 32 functional groups, i.e., 12 groups in the biological process category, 12 groups in the cellular component category, and eight groups in the molecular function category. There were 5857 and 2846 upregulated genes and 135 and 50 upregulated Gene Ontology terms (P < 0.05) in the biological process category in PI(+B) vs. PI(-B) and LE(+B) vs. LE(-B), respectively. These results indicated that the allelopathic accession PI is more sensitive than the non-allelopathic accession LE to exogenous root exudates treatment. Genes related to rice allelochemical-related biosynthesis pathways, particularly the shikimic acid and acetic acid pathways, were significantly differentially expressed in both rice accessions. These findings suggested that phenolic acids, fatty acids, and flavonoids, which constitute the downstream metabolites of the shikimic acid and acetic acid pathways, are significantly expressed in response to root exudates of barnyard grass.ConclusionsThe allelopathic potential of both rice accessions could be significantly enhanced by barnyard grass root exudates application. Furthermore, genes related to the biosynthesis pathways of reported rice allelochemicals were significantly differentially expressed in both accessions. Phenylalanine ammonia lyase was determined to be a potential target for the regulation of chemical induction.

Project description:BackgroundAllelopathic rice releases allelochemicals through its root systems, thereby exerting a negative effect on paddy weeds. This research aimed to evaluate the relationship between fine-root traits and the rice allelopathic potential at the seedling stage.MethodsTwo allelopathic rice cultivars, 'PI312777' and 'Taichung Native1,' and one non-allelopathic rice cultivar, 'Lemont,' were grown to the 3-6 leaf stage in a hydroponic system. Their fine roots were collected for morphological trait (root length, root surface area, root volume, and root tips number) in smaller diameter cutoffs and proliferative trait (root biomass) analysis. Their root-exudates were used for quantitative analysis of phenolic acids contents and an evaluation of allelopathic potential. Correlation analysis was also used to assess whether any linear relationships existed.ResultsOur results showed that allelopathic rice cultivars had significantly higher fine-root length having diameters <0.2 mm, more root tips number, and greater root biomass, coupled with higher allelopathic potential and phenolic acid contents of their root exudates, comparing with non-allelopathic rice cultivar. These fine-root traits were significantly-positively correlated to allelopathic inhibition and total phenolic contents in rice root-exudates. However, there were not significant correlations among the rice allelopathic potential and total phenolic acid contents of rice root-exudates with the root length, root surface area, and root volume of fine root in diameter >0.2 mm.DiscussionOur results implied that fine-root traits appears to be important in understanding rice allelopathy at the seedling stage. The high allelopathic potential of rice cultivars might be attributed to their higher length of fine roots <0.2 mm in diameter and more number of root tips of fine root, which could accumulate and release more allelochemicals to solutions, thereby resulting in high inhibition on target plants. The mechanisms regulating this process need to be further studied.

Project description:BackgroundEnterohemorrhagic Escherichia coli (EHEC) are zoonotic agents associated with outbreaks worldwide. Growth of EHEC strains in ground beef could be inhibited by background microbiota that is present initially at levels greater than that of the pathogen E. coli. However, how the microbiota outcompetes the pathogenic bacteria is unknown. Our objective was to identify metabolic pathways of EHEC that were altered by natural microbiota in order to improve our understanding of the mechanisms controlling the growth and survival of EHECs in ground beef.ResultsBased on 16S metagenomics analysis, we identified the microbial community structure in our beef samples which was an essential preliminary for subtractively analyzing the gene expression of the EHEC strains. Then, we applied strand-specific RNA-seq to investigate the effects of this microbiota on the global gene expression of EHEC O2621765 and O157EDL933 strains by comparison with their behavior in beef meat without microbiota. In strain O2621765, the expression of genes connected with nitrate metabolism and nitrite detoxification, DNA repair, iron and nickel acquisition and carbohydrate metabolism, and numerous genes involved in amino acid metabolism were down-regulated. Further, the observed repression of ftsL and murF, involved respectively in building the cytokinetic ring apparatus and in synthesizing the cytoplasmic precursor of cell wall peptidoglycan, might help to explain the microbiota's inhibitory effect on EHECs. For strain O157EDL933, the induced expression of the genes implicated in detoxification and the general stress response and the repressed expression of the peR gene, a gene negatively associated with the virulence phenotype, might be linked to the survival and virulence of O157:H7 in ground beef with microbiota.ConclusionIn the present study, we show how RNA-Seq coupled with a 16S metagenomics analysis can be used to identify the effects of a complex microbial community on relevant functions of an individual microbe within it. These findings add to our understanding of the behavior of EHECs in ground beef. By measuring transcriptional responses of EHEC, we could identify putative targets which may be useful to develop new strategies to limit their shedding in ground meat thus reducing the risk of human illnesses.

Dataset Information

OsPAL2-1 Mediates Allelopathic Interactions Between Rice and Specific Microorganisms in the Rhizosphere Ecosystem.

Publications

<i>OsPAL2-1</i> Mediates Allelopathic Interactions Between Rice and Specific Microorganisms in the Rhizosphere Ecosystem.

Similar Datasets

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