Root Rot Disease of Torreya grandis Caused by Fusarium fujikuroi in China.

Torreya grandis is an evergreen plant endemic of China and widely grown in Southern China. Its fruit is a precious nut in China, rich in vitamins and minerals, can be directly eaten, can also be used as medicinal plants with functions of lowering blood lipids and softening blood vessels (Wang 2022). From 2018 to 2020, typical root rot symptoms of Torreya grandis was found in plantations in Huangshan and surrounding areas of Huangshan, Anhui province, China. About 15 to 32% of root rot disease incidence was recorded at the plantation. Diseased plants were observed with symptoms such as yellow to brownish leaves without lesions and later drying, and rotten roots looked dark brown while the roots of heathy plants showed white, and eventually leading to the death of the diseased plant. The root rot symptomatic plants were collected in June of 2020. Tissues were cut to the length of 0.3 to 0.5 cm, then surface sterilized by 2% sodium hypochlorite for 2 min and 75% alcohol for 1 min, rinsed three times in sterile distilled water, and placed on potato dextrose agar (PDA) and incubated at 25℃ for 5 to 9 days. Eight isolates with similar morphology were isolated from single spores. On PDA, the isolates produced abundant aerial white mycelia with septation and turned violet to dark pink on the reverse side of the culture. Morphological characteristic was determined using a pure culture grown on synthetic low nutrient agar (SNA). Two types of conidia, microconidia and macroconidia, were observed on SNA. Macroconidia were long and slender, usually 3 to 5 septate, measuring 2.7 to 4.3 × 22.3 to 49.6 µm (n=30), and narrowed at the both ends. Microconidia were abundant, oval, clavate or ovate, zero to one septate and measured 1.6 to 3.9 × 4.4 to 13.0 µm (n=50). According to the culture and conidial characteristics, the isolates were tentatively identified as Fusarium species (Leslie and Summerell 2006). Four isolates were random selected for molecular identification. The general primers ITS1/ITS4 for internal transcribed spacer (ITS) (White et al. 1990), EF1/EF2 for translation elongation factor (TEF1) (O'Donnell et al. 1998), 5F2/7cR for the second largest subunit of RNA polymerase Ⅱ(RPB2) (O'Donnell et al., 2007), H3-1a/H3-1b for Histone H3 (Jacobs et al., 2010), F5/R8 for subunits 1 of DNA-directed RNA polymerase Ⅱ (RPB1) (O'Donnell et al. 2010) and MS3F/MS3R for mitochondrial small subunit (mtSSU) (Stenglein et al. 2010) were amplified, respectively. The products were sequenced and deposited in GenBank with accession numbers of MW350689, MW029444, ON077156, ON077158, ON077157, ON054432, respectively. Blast analysis showed 99.40 to 100% sequence homology with known F. fujikuroi isolates. A phylogenetic analysis based on the concatenated sequences clustered from the combined datasets (TEF1, RPB2, Histone H3, RPB1 and mtSSU) revealed the isolate most closely related to the F. fujikuroi (100% bootstrap). Fifteen 2-year-old healthy plants of Torreya grandis were selected for the pathogenicity test. A conidial suspension (1×106 conidia/ml) was prepared by collecting spores from 10-day-old cultures on PDA. The root of each plants inoculated with 200 ml of a 106 conidia/ml suspension, and the five control plants inoculated with sterilized water. The plants were incubated in green house with 25℃ (14 h light)/22℃ (10 h dark) at 85% humidity. Two weeks later, 100% of artificially inoculated plants showed the same symptoms similar to those observed in the plantation, like yellow leaves, dark brown and rotten roots, meanwhile, the roots of control plants displayed healthy. From symptomatic roots, the pathogen was reisolated which satisfying Koch's postulates. F. fujikuroi causes root rot of soybean and Reineckia carnea (Detranaltes et al. 2021, Sun et al. 2018).To the best of our knowledge, this is the first report of F. fujikuroi causing root rot of Torreya grandis in China.

Prophage Gene Rv2650c Enhances Intracellular Survival of Mycobacterium smegmatis.

BACKGROUND: Induced by the pathogen Mycobacterium tuberculosis, tuberculosis remains one of the most dangerous infectious diseases in the world. As a special virus, prophage is domesticated by its host and are major contributors to virulence factors for bacterial pathogenicity. The function of prophages and their genes in M. tuberculosis is still unknown. METHODS: Rv2650c is a prophage gene in M. tuberculosis genome. We constructed recombinant Mycobacterium smegmatis (M. smegmatis) to observe bacteria morphology and analyze the resistance to various adverse environments. Recombinant and control strains were used to infect macrophages, respectively. Furthermore, we performed ELISA experiments of infected macrophages. RESULTS: Rv2650c affected the spread of colonies of M. smegmatis and enhanced the resistance of M. smegmatis to macrophages and various stress agents such as acid, oxidative stress, and surfactant. ELISA experiments revealed that the Rv2650c can inhibit the expression of inflammatory factors TNF-α, IL-10, IL-1ß, and IL-6. CONCLUSION: This study demonstrates that the prophage gene Rv2650c can inhibit the spread of colonies and the expression of inflammatory factors and promote intracellular survival of M. smegmatis. These results build the foundation for the discovery of virulence factors of M. tuberculosis, and provide novel insights into the function of the prophage in Mycobacterium.

Diagnosis of Coronavirus Disease 2019 (COVID-19) With Structured Latent Multi-View Representation Learning.

Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of infected patients and heavy labor for doctors, computer-aided diagnosis with machine learning algorithm is urgently needed, and could largely reduce the efforts of clinicians and accelerate the diagnosis process. Chest computed tomography (CT) has been recognized as an informative tool for diagnosis of the disease. In this study, we propose to conduct the diagnosis of COVID-19 with a series of features extracted from CT images. To fully explore multiple features describing CT images from different views, a unified latent representation is learned which can completely encode information from different aspects of features and is endowed with promising class structure for separability. Specifically, the completeness is guaranteed with a group of backward neural networks (each for one type of features), while by using class labels the representation is enforced to be compact within COVID-19/community-acquired pneumonia (CAP) and also a large margin is guaranteed between different types of pneumonia. In this way, our model can well avoid overfitting compared to the case of directly projecting high-dimensional features into classes. Extensive experimental results show that the proposed method outperforms all comparison methods, and rather stable performances are observed when varying the number of training data.

Expression of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and Ki-67 in ductal carcinoma in situ (DCIS) and DCIS with microinvasion.

Ductal carcinoma in situ (DCIS) represents a heterogeneous disease in its histologic appearance and biological potential. Some women treated for DCIS subsequently develop invasive breast cancer. DCIS with microinvasion is considered as the interim stage in the progression from DCIS to invasive breast cancer. Analysis of the differences between DCIS and DCIS with microinvasion may aid in understanding the characteristic of DCIS with microinvasion and identifying biological factors determining progression of DCIS to invasive disease.Retrospective analysis of 219 cases between 2012 and 2018 was performed in our institution. The pathological results and axillary lymph nodes status were collected. Analysis of the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 in pure DCIS (164 cases), and DCIS with microinvasion (55 cases) using immunohistochemistry.DCIS with microinvasion had a higher nuclear grade (P < .001) and was more likely to have sentinel lymph node biopsy (SLNB) positivity (P = .039) than DCIS. Expression of ER, PR were significantly higher in DCIS compared with DCIS with microinvasion (P < .001, P < .001). While the expression of HER-2 in DCIS with microinvasion (56.4%) was significantly higher than in DCIS (36.6%, P = .01). Furthermore, DCIS with microinvasion was significantly more likely to have aggressive subtype (Triple-negative and HER2-enriched tumors, P = .005).Our results indicated that DCIS with microinvasion was different from pure DCIS in clinicopathologic characteristics and molecular alterations. It displayed a more aggressive biological nature than pure DCIS. It may be a distinct entity.