An efficient genetic manipulation protocol for dark septate endophyte Falciphora oryzae.

OBJECTIVE: To investigate the protoplast preparation and transformation system of endophytic fungus Falciphora oryzae. RESULTS: F. oryzae strain obtained higher protoplast yield and effective transformation when treated with enzyme digestion solution containing 0.9 M KCl solution and 10 mg mL-1 glucanase at 30 °C with shaking at 80 rpm for 2-3 h. When the protoplasts were plated on a regenerations-agar medium containing 1 M sucrose, the re-growth rate of protoplasts was the highest. We successfully acquired green fluorescent protein-expressing transformants by transforming the pKD6-GFP vector into protoplasts. Further, the GFP expression in fungal hyphae possessed good stability and intensity during symbiosis in rice roots. CONCLUSIONS: This study provided a protoplast transformation system of F. oryzae, creating opportunities for future genetic research in other endophytic fungi.

A New Species in Pseudophialophora From Wild Rice and Beneficial Potential.

Wild rice (Oryza granulata) is a natural resource pool containing abundant unknown endophytic fungi species. There are few reports on the endophytic fungi in wild rice. Here, one isolate recovered from wild rice roots was identified as a new species Pseudophialophora oryzae sp. nov based on the molecular phylogeny and morphological characteristics. Fluorescent protein-expressing P. oryzae was used to monitor the fungal colonization pattern. Hyphae invaded the epidermis to the inner cortex but not into the root stele. The inoculation of P. oryzae promoted the rice growth, with the growth parameters of chlorophyll content, shoot height, root length, fresh shoot weight, fresh root weight and dry weight increasing by 24.10, 35.32, 19.35, 90.00, 33.3, and 79.17%, respectively. P. oryzae induced up-regulation of nitrate transporter OsPTR9 and potassium transporter OsHAK16 by 7.28 ± 0.84 and 2.57 ± 0.80 folds, promoting nitrogen and potassium elements absorption. In addition, P. oryzae also conferred a systemic resistance against rice blast, showing a 72.65 and 75.63% control rate in sterile plates and potting conditions. This systemic resistance was mediated by the strongly up-regulated expression of resistance-related genes NAC, OsSAUR2, OsWRKY71, EL5, and PR1α. Since P. oryzae can promote rice growth, biomass and induce systemic disease resistance, it can be further developed as a new biogenic agent for agricultural production, providing a new approach for biocontrol of rice blast.

The Endophytic Fungus Piriformospora Indica-Assisted Alleviation of Cadmium in Tobacco.

Increasing evidence suggests that the endophytic fungus Piriformospora indica helps plants overcome various abiotic stresses, especially heavy metals. However, the mechanism of heavy metal tolerance has not yet been elucidated. Here, the role of P. indica in alleviating cadmium (Cd) toxicities in tobacco was investigated. It was found that P. indica improved Cd tolerance to tobacco, increasing Cd accumulation in roots but decreasing Cd accumulation in leaves. The colonization of P. indica altered the subcellular repartition of Cd, increasing the Cd proportion in cell walls while reducing the Cd proportion in membrane/organelle and soluble fractions. During Cd stress, P. indica significantly enhanced the peroxidase (POD) activity and glutathione (GSH) content in tobacco. The spatial distribution of GSH was further visualized by Raman spectroscopy, showing that GSH was distributed in the cortex of P. indica-inoculated roots while in the epidermis of the control roots. A LC-MS/MS-based label-free quantitative technique evaluated the differential proteomics of P. indica treatment vs. control plants under Cd stress. The expressions of peroxidase, glutathione synthase, and photosynthesis-related proteins were significantly upregulated. This study provided extensive evidence for how P. indica enhances Cd tolerance in tobacco at physiological, cytological, and protein levels.

Application of Hyperspectral Imaging for Maturity and Soluble Solids Content Determination of Strawberry With Deep Learning Approaches.

Maturity degree and quality evaluation are important for strawberry harvest, trade, and consumption. Deep learning has been an efficient artificial intelligence tool for food and agro-products. Hyperspectral imaging coupled with deep learning was applied to determine the maturity degree and soluble solids content (SSC) of strawberries with four maturity degrees. Hyperspectral image of each strawberry was obtained and preprocessed, and the spectra were extracted from the images. One-dimension residual neural network (1D ResNet) and three-dimension (3D) ResNet were built using 1D spectra and 3D hyperspectral image as inputs for maturity degree evaluation. Good performances were obtained for maturity identification, with the classification accuracy over 84% for both 1D ResNet and 3D ResNet. The corresponding saliency maps showed that the pigments related wavelengths and image regions contributed more to the maturity identification. For SSC determination, 1D ResNet model was also built, with the determination of coefficient (R 2) over 0.55 of the training, validation, and testing sets. The saliency maps of 1D ResNet for the SSC determination were also explored. The overall results showed that deep learning could be used to identify strawberry maturity degree and determine SSC. More efforts were needed to explore the use of 3D deep learning methods for the SSC determination. The close results of 1D ResNet and 3D ResNet for classification indicated that more samples might be used to improve the performances of 3D ResNet. The results in this study would help to develop 1D and 3D deep learning models for fruit quality inspection and other researches using hyperspectral imaging, providing efficient analysis approaches of fruit quality inspection using hyperspectral imaging.