Genome sequencing and comparative genome analysis of Rhizoctonia solani AG-3.

Rhizoctonia solani AG-3 is a plant pathogenic fungus that belongs to the group of multinucleate Rhizoctonia. According to its internal transcribed spacer (ITS) cluster analysis and host range, it is divided into TB, PT, and TM subgroups. AG-3 TB mainly causes tobacco target spots, AG-3 PT mainly causes potato black scurf, and AG-3 TM mainly causes tomato leaf blight. In our previous study, we found that all 36 tobacco target spot strains isolated from Yunnan (Southwest China) were classified into AG-3 TB subgroup, while only two of the six tobacco target spot strains isolated from Liaoning (Northeast China) were classified into AG-3 TB subgroup, and the remaining four strains were classified into AG-3 TM subgroup, which had a unique taxonomic status, and there was no previous report on the whole genome information of AG-3 TM subgroup. In this study, the whole genomes of R. solani AG-3 strains 3T-1 (AG-3 TM isolated from Liaoning) and MJ-102 (AG-3 TB isolated from Yunnan) isolated from tobacco target spot in Liaoning and Yunnan were sequenced by IIumina and PacBio sequencing platforms. Comparative genomic analysis was performed with the previously reported AG-3 PT strain Rhs1AP, revealing their differences in genomes and virulence factors. The results indicated that the genome size of 3T-1 was 42,103,597 bp with 11,290 coding genes and 49.74% GC content, and the genome size of MJ-102 was 41,908,281 bp with 10,592 coding genes and 48.91% GC content. Through comparative genomic analysis with the previously reported strain Rhs1AP (AG-3 PT), it was found that the GC content between the genomes was similar, but the strains 3T-1 and MJ-102 contained more repetitive sequences. Similarly, there are similarities between their virulence factors, but there are also some differences. In addition, the results of collinearity analysis showed that 3T-1 and MJ-102 had lower similarity and longer evolutionary distance with Rhs1AP, but the genetic relationship between 3T-1 and MJ-102 was closer. This study can lay a foundation for studying the molecular pathogenesis and virulence factors of R. solani AG-3, and revealing its genomic composition will also help to develop more effective disease control strategies.

Effects of Chemical and Biological Fungicide Applications on Sexual Sporulation of Rhizoctonia solani AG-3 TB on Tobacco.

Rhizoctonia solani AG-3 TB primarily causes tobacco target spot disease by producing a large number of sexual spores. However, inducing sexual spore formation under in vitro conditions has been challenging, impeding further research on its control. In this study, field experiments were conducted to assess the effects of different concentrations of chemical and biological fungicides on the production of sexual spores of R. solani AG-3 TB on tobacco plants. The results demonstrated that four chemical fungicides (propiconazole-morpholine guanidine, bordeaux mixture, thiophanate-methyl, and mancozeb) significantly induced sexual spore formation. Among them, increasing the concentrations of the first three fungicides resulted in an increase in the number of sexual spores, while increasing the concentration of mancozeb led to a decrease in spore count. The pathogenic fungus produced more sexual spores during the night than during the day. Temperature, humidity, and light conditions influenced spore production. Additionally, the infection rate of sexual spores was directly proportional to their concentration and inoculation time, but their survival time did not exceed 6 h in vitro. Importantly, Streptomyces rectiolaceus A8 significantly suppressed sexual spore formation, achieving an 83.63% control efficacy in the field and producing antimicrobial substances against R. solani AG-3 TB. In conclusion, appropriate concentrations of chemical fungicides can induce sexual spore formation, while A8 can inhibit their production, showing potential value for controlling tobacco target spot disease.

Virome Analysis of Aconitum carmichaelii Reveals Infection by Eleven Viruses, including Two Potentially New Species.

Aconitum carmichaelii is a herbaceous herb indigenous to China that has been cultivated for traditional medicine for centuries. Virus-like symptoms of A. carmichaelii plants were observed on leaves in some A. carmichaelii plantations in Zhanyi and Wuding Counties, Yunnan Province, southwest China. High-throughput sequencing (HTS) was performed on 28 symptomatic plants, and the results revealed infection with 11 viruses, including 2 novel viruses and 9 previously described viruses: Aconitum amalgavirus 1 (AcoAV-1), aconite virus A (AcVA), cucumber mosaic virus (CMV), currant latent virus (CuLV), apple stem grooving virus (ASGV), chilli veinal mottle virus (ChiVMV), tomato spotted wilt orthotospovirus (TSWV), tobacco vein distorting virus (TVDV), and potato leafroll virus (PLRV). Two novel viruses tentatively named Aconitum potyvirus 1 and Aconitum betapartitivirus 1, were supported by sequence and phylogenetic analysis results of their genomes. We proposed the names Potyvirus aconiti and Betapartitivirus aconiti. RT-PCR assays of 142 plants revealed the predominance and widespread distribution of CMV, AcVA, and AcoPV-1 in plantations. The detection of isolates of CuLV, ASGV, ChiVMV, TSWV, TVDV, and PLRV infections for the first time in A. carmichaelii expands their known host ranges.

Horizontal and Vertical Transmission of a Mycovirus Closely Related to the Partitivirus RhsV717 That Confers Hypovirulence in Rhizoctonia solani.

Rhizoctonia solani virus717 (RhsV717) was isolated from the Rhizoctonia solani (R. solani) AG-2 strain Rhs717. This study isolated a virus designated as Rhizoctonia solani partitivirus BS-5 (RsPV-BS5) from the R. solani AG-3 strain BS-5, the causal agent of tobacco target spot disease. The virus was identified as a strain of RhsV717. Transmission electron microscopy (TEM) images showed that RsPV-BS5 had virus particles with a diameter of approximately 40 nm. Importantly, it can be horizontally transmitted through hyphal anastomosis and vertically transmitted via sexual basidiospores. Furthermore, this study demonstrated that RsPV-BS5 infection significantly impedes mycelial growth and induces hypovirulence in tobacco leaves. Thus, RsPV-BS5 presents a promising avenue for biocontrolling tobacco target spot disease. Transcriptome analysis unveiled differential expression of four genes related to cell wall-degrading enzymes between two isogenic strains, 06-2-15V and 06-2-15. These findings shed light on the molecular mechanism through which RsPV-BS5 reduces host pathogenicity.

Complete genome sequence of a novel fusarivirus from Rhizoctonia solani AG-3 PT strain 3P-2-2.

Here, we describe a novel mycovirus, tentatively designated as "Rhizoctonia solani fusarivirus 6" (RsFV6), which was discovered in Rhizoctonia solani AG-3 PT strain 3P-2-2. The virus has a single-stranded positive-sense RNA (+ssRNA) genome of 6141 nucleotides containing two open reading frames (ORFs) and a poly(A) tail. ORF1 encodes a large polypeptide of 1,862 amino acids (aa) with conserved RNA-dependent RNA polymerase (RdRp) and helicase (Hel) domains. ORF2 encodes a putative 167-aa protein of unknown function. BLASTp searches revealed that the ORF1-encoded polypeptide showed the highest sequence similarity (70.67% identity) to that of Rhizoctonia solani fusarivirus 3 (RsFV3), which was isolated from Rhizoctonia solani AG-2-2LP. Multiple sequence alignments and phylogenetic analysis based on RdRp and Hel sequences indicated that RsFV6 could be a novel member of the genus Alphafusarivirus family Fusariviridae.

Development and validation of an artificial intelligence-based system for predicting colorectal cancer invasion depth using multi-modal data.

OBJECTIVES: Accurate endoscopic optical prediction of the depth of cancer invasion is critical for guiding an optimal treatment approach of large sessile colorectal polyps but was hindered by insufficient endoscopists expertise and inter-observer variability. We aimed to construct a clinically applicable artificial intelligence (AI) system for the identification of presence of cancer invasion in large sessile colorectal polyps. METHODS: A deep learning-based colorectal cancer invasion calculation (CCIC) system was constructed. Multi-modal data including clinical information, white light (WL) and image-enhanced endoscopy (IEE) were included for training. The system was trained using 339 lesions and tested on 198 lesions across three hospitals. Man-machine contest, reader study and video validation were further conducted to evaluate the performance of CCIC. RESULTS: The overall accuracy of CCIC system using image and video validation was 90.4% and 89.7%, respectively. In comparison with 14 endoscopists, the accuracy of CCIC was comparable with expert endoscopists but superior to all the participating senior and junior endoscopists in both image and video validation set. With CCIC augmentation, the average accuracy of junior endoscopists improved significantly from 75.4% to 85.3% (P = 0.002). CONCLUSIONS: This deep learning-based CCIC system may play an important role in predicting the depth of cancer invasion in colorectal polyps, thus determining treatment strategies for these large sessile colorectal polyps.

Morphological and molecular characterization of Rhizoctonia solani AG-3 associated with tobacco target leaf spot in China.

Tobacco target leaf spot is a leaf disease that seriously affects both the quantity and quality of commercial tobacco crops and has caused huge economic losses in many countries and also pandemics in China since 2006. The anastomosis group-3 (AG-3) pathogen is divided into different subgroups namely AG-3 PT (potato type), AG-3TB (tobacco type), and AG-3 TM (tomato type), based on their host and the combined data from the ribosomal DNA internal transcribed spacer (rDNA-ITS), rDNA intergenic spacer 1 (rDNA-IGS1) regions, and translation elongation factor 1-α (tef-1α) gene. In this study, we collected tobacco leaves showing target spot symptom from four fields in China. We obtained 49 isolates from southwest China (Yunnan Provinces) and six isolates from northeast China (Liaoning Province). Phylogenetic tree based on rDNA-ITS region indicated that 51 isolates (49 isolates from Yunnan and two isolates from Liaoning) and 4 isolates from Liaoning belonged to AG-3 TB and AG-3 TM, respectively.

Real-time automated diagnosis of colorectal cancer invasion depth using a deep learning model with multimodal data (with video).

BACKGROUND AND AIMS: The optical diagnosis of colorectal cancer (CRC) invasion depth with white light (WL) and image-enhanced endoscopy (IEE) remains challenging. We aimed to construct and validate a 2-modal deep learning-based system, incorporated with both WL and IEE images (named Endo-CRC) in estimating the invasion depth of CRC. METHODS: Samples were retrospectively obtained from 3 hospitals in China. We combined WL and IEE images into image pairs. Altogether, 337,278 image pairs from 268 noninvasive and superficial CRC and 181,934 image pairs from 82 deep CRC were used for training. A total of 296,644 and 4528 image pairs were used for internal and external tests and for comparison with endoscopists. Thirty-five videos were used for evaluating the real-time performance of the Endo-CRC system. Two deep learning models, solely using either WL (model W) or IEE images (model I), were constructed to compare with Endo-CRC. RESULTS: The accuracies of Endo-CRC in internal image tests with and without advanced CRC were 91.61% and 93.78%, respectively, and 88.65% in the external test, which did not include advanced CRC. In an endoscopist-machine competition, Endo-CRC achieved an expert comparable accuracy of 88.11% and the highest sensitivity compared with all endoscopists. In a video test, Endo-CRC achieved an accuracy of 100.00%. Compared with model W and model I, Endo-CRC had a higher accuracy (per image pair: 91.61% vs 88.27% compared with model I and 91.61% vs 81.32% compared with model W). CONCLUSIONS: The Endo-CRC system has great potential for assisting in CRC invasion depth diagnosis and may be well applied in clinical practice.

MiR-34a inhibits migration and invasion by regulating the SIRT1/p53 pathway in human SW480 cells.

MicroRNA-34a (miR-34a) is a direct transcriptional target of p53, and is downregulated in several different types of cancer. However, the underlying mechanism of the miR-34a effects in colorectal cancer is not well understood. In this study, we explored the role of miR-34a in cell invasion, migration, and apoptosis. Transient overexpression of miR-34a in SW480 cells caused a severe decrease in cell migration and invasion (both, p<0.05) compared to the control groups. Combining miR-34a transfection with 5-fluorouracil (5-FU) treatment further enhanced the inhibition in SW480 cell migration and invasion (both, p<0.05) compared to 5-FU treatment alone. These cellular changes were associated with upregulation of acetylated­p53 (ac-p53) and p21 and downregulation of sirtuin 1 (SIRT1). These data demonstrate that miR-34a regulates the expression of a number of critical proteins involved in apoptosis, proliferation and the response to chemotherapy. In summary, miR-34a increases the sensitivity of colon cancer cells to 5-FU treatment through specific regulation of the SIRT1/p53 pathway.