22 research outputs found

    Rhamnogalacturonan-I as a nematode chemoattractant from Lotus corniculatus L. super-growing root culture

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    IntroductionThe soil houses a tremendous amount of micro-organisms, many of which are plant parasites and pathogens by feeding off plant roots for sustenance. Such root pathogens and parasites often rely on plant-secreted signaling molecules in the rhizosphere as host guidance cues. Here we describe the isolation and characterization of a chemoattractant of plant-parasitic root-knot nematodes (Meloidogyne incognita, RKN).MethodsThe Super-growing Root (SR) culture, consisting of excised roots from the legume species Lotus corniculatus L., was found to strongly attract infective RKN juveniles and actively secrete chemoattractants into the liquid culture media. The chemo-attractant in the culture media supernatant was purified using hydrophobicity and anion exchange chromatography, and found to be enriched in carbohydrates.ResultsMonosaccharide analyses suggest the chemo-attractant contains a wide array of sugars, but is enriched in arabinose, galactose and galacturonic acid. This purified chemoattractant was shown to contain pectin, specifically anti-rhamnogalacturonan-I and anti-arabinogalactan protein epitopes but not anti-homogalacturonan epitopes. More importantly, the arabinose and galactose sidechain groups were found to be essential for RKN-attracting activities. This chemo-attractant appears to be specific to M. incognita, as it wasn’t effective in attracting other Meloidogyne species nor Caenorhabditis elegans.DiscussionThis is the first report to identify the nematode attractant purified from root exudate of L corniculatus L. Our findings re-enforce pectic carbohydrates as important chemicals mediating micro-organism chemotaxis in the soil, and also highlight the unexpected utilities of the SR culture system in root pathogen research

    Quantitative analysis of seven plant hormones in Lotus japonicus using standard addition method.

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    Plant hormones have been identified to be versatile signaling molecules essential for plant growth, development, and stress response. Their content levels vary depending on the species, and they also change in response to any external stimuli. Thus, simultaneous quantification of multiple plant hormones is required to understand plant physiology. Sensitive and quantitative analysis using liquid chromatography-linked mass spectrometry (LC-MS/MS) has been used in detecting plant hormones; however, quantification without stable isotopes is yet to be established. In this study, we quantified seven representative plant hormones of Lotus japonicus, which is a model legume for standard addition method. Accurate masses for monoisotopic ions of seven phytohormones were determined for high-resolution mass spectrometry (HR-MS). Selected ion monitoring (SIM) mode based on accurate masses was used in detecting phytohormones in the roots, stems, and leaves. Evaluation of matrix effects showed ion suppression ranging from 10.2% to 87.3%. Both stable isotope dilution and standard addition methods were able to detect plant hormones in the roots, stems, and leaves, with no significant differences in using both approaches and thus a standard addition method can be used to quantify phytohormones in L. japonicus. The method will be effective, especially when stable isotopes are not available to correct for matrix effects

    Development of a digital phenotyping system using 3D model reconstruction for zoysiagrass

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    Abstract Digital phenotyping, particularly the use of plant 3D models, is a promising method for high‐throughput plant evaluation. Although many recent studies on the topic have been published, further research is needed to apply it to breeding research and other related fields. In this study, using a 3D model phenotyping system we developed, we reconstructed and analyzed 20 accessions of zoysiagrass (Zoysia spp.), including three species and their hybrid, over a period of 1 year. Artificial neural network with three hidden layers was able to effectively remove nonplant parts while retaining plant parts that were incorrectly removed using the cropping method, offering a robust and flexible approach for post‐processing of 3D models. The system also demonstrated its ability to accurately evaluate a range of traits, including height, area, and color using red green blue (RGB)‐based vegetation indices. The results showed a high correlation between the estimated volume obtained from voxel 3D model and dry weight, enabling its use as a non‐destructive method for measuring plant volume. In addition, we found that the green red normalized difference index from RGB‐based indices was similar to the commonly used normalized difference vegetation index in controlled illumination conditions. These results demonstrate the potential for three‐dimensional model phenotyping to facilitate plant breeding, particularly in the field of turfgrass and feed crops

    Aberrant gene methylation in the peritoneal fluid is a risk factor predicting peritoneal recurrence in gastric cancer

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    AIM: To investigate whether gene methylation in the peritoneal fluid (PF) predicts peritoneal recurrence in gastric cancer patients
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