Most land plant species live in symbiosis with arbuscular mycorrhizal fungi. These fungi differentiate essential functional structures called arbuscules in root cortical cells from which mineral nutrients are released to the plant. We investigated the role of microRNA393 (miR393), an miRNA that targets several auxin receptors, in arbuscular mycorrhizal root colonization. Expression of the precursors of the miR393 was down-regulated during mycorrhization in three different plant species: Solanum lycopersicum, Medicago truncatula, and Oryza sativa. Treatment of S. lycopersicum, M. truncatula, and O. sativa roots with concentrations of synthetic auxin analogs that did not affect root development stimulated mycorrhization, particularly arbuscule formation. DR5-GUS, a reporter for auxin response, was preferentially expressed in root cells containing arbuscules. Finally, overexpression of miR393 in root tissues resulted in down-regulation of auxin receptor genes (transport inhibitor response1 and auxin-related F box) and underdeveloped arbuscules in all three plant species. These results support the conclusion that miR393 is a negative regulator of arbuscule formation by hampering auxin perception in arbuscule-containing cells.

Coronavirus disease 2019 (COVID-19) represents a major pandemic threat that has spread to more than 212 countries with more than 432,902 recorded deaths and 7,898,442 confirmed cases worldwide so far (on June 14, 2020). It is crucial to investigate the spatial drivers to prevent and control the epidemic of COVID-19. This is the first comprehensive study of COVID-19 in Iran; and it carries out spatial modeling, risk mapping, change detection, and outbreak trend analysis of the disease spread. Four main steps were taken: comparison of Iranian coronavirus data with the global trends, prediction of mortality trends using regression modeling, spatial modeling, risk mapping, and change detection using the random forest (RF) machine learning technique (MLT), and validation of the modeled risk map. The results show that from February 19 to June 14, 2020, the average growth rates (GR) of COVID-19 deaths and the total number of COVID-19 cases in Iran were 1.08 and 1.10, respectively. Based on the World Health Organisation (WHO) data, Iran's fatality rate (deaths/0.1M pop) is 10.53. Other countries' fatality rates were, for comparison, Belgium - 83.32, UK - 61.39, Spain - 58.04, Italy - 56.73, Sweden - 48.28, France - 45.04, USA - 35.52, Canada - 21.49, Brazil - 20.10, Peru - 19.70, Chile - 16.20, Mexico- 12.80, and Germany - 10.58. The fatality rate for China is 0.32 (deaths/0.1M pop). Over time, the heatmap of the infected areas identified two critical time intervals for the COVID-19 outbreak in Iran. The provinces were classified in terms of disease and death rates into a large primary group and three provinces that had critical outbreaks were separate from the others. The heatmap of countries of the world shows that China and Italy were distinguished from other countries in terms of nine viral infection-related parameters. The regression models for death cases showed an increasing trend but with some evidence of turning. A polynomial relationship was identified between the coronavirus infection rate and the province population density. Also, a third-degree polynomial regression model for deaths showed an increasing trend recently, indicating that subsequent measures taken to cope with the outbreak have been insufficient and ineffective. The general trend of deaths in Iran is similar to the world's, but Iran's shows lower volatility. Change detection of COVID-19 risk maps with a random forest model for the period from March 11 to March 18 showed an increasing trend of COVID-19 in Iran's provinces. It is worth noting that using the LASSO MLT to evaluate variables' importance, indicated that the most important variables were the distance from bus stations, bakeries, hospitals, mosques, ATMs (automated teller machines), banks, and the minimum temperature of the coldest month. We believe that this study's risk maps are the primary, fundamental step to take for managing and controlling COVID-19 in Iran and its provinces.

Summary: Fungi, nematodes and oomycetes belong to the most prominent eukaryotic plant pathogenic organisms. Unicellular organisms from other eukaryotic lineages, commonly addressed as protists, also infect plants. This review provides an introduction to plant pathogenic protists, including algae infecting oomycetes, and their current state of research.

Vegetables can be treated with biofertilizers as an alternative to chemical fertilizers because of their low toxicity. We investigated the effects of foliar spraying of Azotobacter under different levels of nitrogen (100, 150 and 200 mg/L in nutrient solution) on the growth, nutritional value, nitrate accumulation and antioxidant enzyme activities of hydroponically grown lettuce. The experiment was laid out in a completely randomized design with four replicates in a factorial combination. Plants treated with Azotobacter and 200 mg/L nitrogen had greater leaf area and photosynthetic pigments than plants treated with 200 mg/L nitrogen without spraying with Azotobacter. Increasing nitrogen levels increased leaf number, fresh and dry weights, leaf area and nitrate accumulation in lettuce plants. Peroxidase (POD) activity increased by 95.4% at a nitrogen level of 200 mg/L compared to a nitrogen level of 100 mg/L. Ascorbate peroxidase (APX) activity and leaf phosphorous (P) and potassium (K) concentrations were the highest in plants treated with a nitrogen source of 100 mg/L without foliar application of Azotobacter. As nitrogen levels increased in all treatments, nitrate reductase (NR) activity decreased and reached a minimum at the 200 mg/L nitrogen level. In general, foliar application of Azotobacter sp. can be used to promote plant growth and reduce nitrate accumulation in lettuce.