CsiLAC4 modulates boron flow in Arabidopsis and Citrus via high-boron-dependent lignification of cell walls.

The mechanisms underlying plant tolerance to boron (B) excess are far from fully understood. Here we characterized the role of the miR397-CsiLAC4/CsiLAC17 (from Citrus sinensis) module in regulation of B flow. Live-cell imaging techniques were used in localization studies. A tobacco transient expression system tested modulations of CsiLAC4 and CsiLAC17 by miR397. Transgenic Arabidopsis were generated to analyze the biological functions of CsiLAC4 and CsiLAC17. CsiLAC4's role in xylem lignification was determined by mRNA hybridization and cytochemistry. In situ B distribution was analyzed by laser ablation inductively coupled plasma mass spectrometry. CsiLAC4 and CsiLAC17 are predominantly localized in the apoplast of tobacco epidermal cells. Overexpression of CsiLAC4 in Arabidopsis improves the plants' tolerance to boric acid excess by triggering high-B-dependent lignification of the vascular system's cell wall and reducing free B content in roots and shoots. In Citrus, CsiLAC4 is expressed explicitly in the xylem parenchyma and is modulated by B-responsive miR397. Upregulation of CsiLAC4 in Citrus results in lignification of the xylem cell walls, restricting B flow from xylem vessels to the phloem. CsiLAC4 contributes to plant tolerance to boric acid excess via high-B-dependent lignification of cell walls, which set up a 'physical barrier' preventing B flow.

MicroRNA Sequencing Revealed Citrus Adaptation to Long-Term Boron Toxicity through Modulation of Root Development by miR319 and miR171.

Boron (B) toxicity in Citrus is a common physiological disorder leading to reductions in both productivity and quality. Studies on how Citrus roots evade B toxicity may provide new insight into plant tolerance to B toxicity. Here, using Illumina sequencing, differentially expressed microRNAs (miRNAs) were identified in B toxicity-treated Citrus sinensis (tolerant) and C. grandis (intolerant) roots. The results showed that 37 miRNAs in C. grandis and 11 miRNAs in C. sinensis were differentially expressed when exposed to B toxicity. Among them, miR319, miR171, and miR396g-5p were confirmed via 5'-RACE and qRT-PCR to target a myeloblastosis (MYB) transcription factor gene, a SCARECROW-like protein gene, and a cation transporting ATPase gene, respectively. Maintenance of SCARECROW expression in B treated Citrus roots might fulfill stem cell maintenance, quiescent center, and endodermis specification, thus allowing regular root elongation under B-toxic stress. Down-regulation of MYB due to up-regulation of miR319 in B toxicity-treated C. grandis roots might decrease the number of root tips, thereby dramatically changing root system architecture. Our findings suggested that miR319 and miR171 play a pivotal role in Citrus adaptation to long-term B toxicity by targeting MYB and SCARECROW, respectively, both of which are responsible for root growth and development.

An automatic identification system for citrus greening disease (Huanglongbing) using a YOLO convolutional neural network.

Huanglongbing (HLB), or citrus greening disease, has complex and variable symptoms, making its diagnosis almost entirely reliant on subjective experience, which results in a low diagnosis efficiency. To overcome this problem, we constructed and validated a deep learning (DL)-based method for detecting citrus HLB using YOLOv5l from digital images. Three models (Yolov5l-HLB1, Yolov5l-HLB2, and Yolov5l-HLB3) were developed using images of healthy and symptomatic citrus leaves acquired under a range of imaging conditions. The micro F1-scores of the Yolov5l-HLB2 model (85.19%) recognising five HLB symptoms (blotchy mottling, "red-nose" fruits, zinc-deficiency, vein yellowing, and uniform yellowing) in the images were higher than those of the other two models. The generalisation performance of Yolov5l-HLB2 was tested using test set images acquired under two photographic conditions (conditions B and C) that were different from that of the model training set condition (condition A). The results suggested that this model performed well at recognising the five HLB symptom images acquired under both conditions B and C, and yielded a micro F1-score of 84.64% and 85.84%, respectively. In addition, the detection performance of the Yolov5l-HLB2 model was better for experienced users than for inexperienced users. The PCR-positive rate of Candidatus Liberibacter asiaticus (CLas) detection (the causative pathogen for HLB) in the samples with five HLB symptoms as classified using the Yolov5l-HLB2 model was also compared with manual classification by experts. This indicated that the model can be employed as a preliminary screening tool before the collection of field samples for subsequent PCR testing. We also developed the 'HLBdetector' app using the Yolov5l-HLB2 model, which allows farmers to complete HLB detection in seconds with only a mobile phone terminal and without expert guidance. Overall, we successfully constructed a reliable automatic HLB identification model and developed the user-friendly 'HLBdetector' app, facilitating the prevention and timely control of HLB transmission in citrus orchards.

Expression of rice gall dwarf virus outer coat protein gene (S8) in insect cells.

To obtain the P8 protein of Rice gall dwarf virus (RGDV) with biological activity, its outer coat protein gene S8 was expressed in Spodoptera frugiperda (Sf9) insect cells using the baculovirus expression system. The S8 gene was subcloned into the pFastBac™1 vector, to produce the recombinant baculovirus transfer vector pFB-S8. After transformation, pFB-S8 was introduced into the competent cells (E. coli DH10Bac) containing a shuttle vector, Bacmid, generating the recombinant bacmid rbpFB-S8. After being infected by recombinant baculovirus rvpFB-S8 at different multiplicities of infection, Sf9 cells were collected at different times and analyzed by SDS-PAGE, Western blotting and immunofluorescence microscopy. The expression level of the P8 protein was highest between 48-72 h after transfection of Sf9 cells. Immunofluorescence microscopy showed that P8 protein of RGDV formed punctate structures in the cytoplasm of Sf9 cells.