Prescreening of biological and biorational fungicides against common hemp pathogens using in vitro analyses

Upon reintroduction of hemp in 2014 and legalization in 2018, labeled pesticides have remained limited. Further, consumer demand has aimed the market toward organic or chemical-free production systems. In efforts to manage diseases and pests in fields and greenhouses, producers turn toward biological and biorational formulations. Efficacy of these fungicides against common aerial diseases of hemp is largely unpublished. Challenges of efficacy testing, however, further delay or discourage research. In this study, we evaluated screening methods against some common biological products. The aim was to test a screening model in order to examine products against fungal pathogens and to identify demonstrable differences under controlled conditions. Thus, in this study, we prescreen 11 biological and biorational fungicides against four common fungal leaf and flower pathogens using three bioassays. Confirmation that the major modes of action for these products have measurable activity against major pathogens of hemp serves as a first step toward more complex field studies.

A cultivar of brown mustard Alisa

Brown mustard is one of the valuable oil crops which allows increasing the production of edible vegetable oil. In the conditions of insufficient moisture in the Rostov region, new cultivars of brown mustard are being developed, which combine yield, early maturity with high product quality and are resistant to stress factors. A new cultivar of brown mustard Alisa was bred by the method of individual selection from the hybrid population G-2384 (G-2319 × 50041). According to the results of competitive trials for 2017–2019, the cultivar Alisa exceeded the standard cultivar Lux by seed yield by 0.31 t per ha, seed oil content – by 0.8%. The brown mustard cultivar Alisa is characterized by a lower plant height, increased tolerance to major pathogens, and greater resistance to lodging. Plants are well uniformed in height, blooming and maturity. The cultivar was registered in 2020 in the State Register of breeding achievements approved for production. It is recommended for cultivation for grain in all regions of the Russian Federation.

Mathematical modeling suggests cooperation of plant-infecting viruses

Viruses are major pathogens of agricultural crops. Viral infections often start after the virus enters the outer layer of a tissue or surface and many successful viruses, after local replication in the infected tissue, are able to spread systemically. Quantitative details of virus dynamics in plants, however, have been poorly understood, in part, because of the lack of experimental methods allowing to accurately measure the degree of infection in individual plant tissues. Recently, by using flow cytometry and two different flourescently-labeled strains of the Tobacco etch virus (TEV), Venus and BFP, kinetics of viral infection of individual cells in leaves of {\it Nicotiana tabacum} plants was followed over time \cite{Tromas.pg14}. A simple mathematical model, assuming that viral spread occurs from lower to upper leaves, was fitted to these data. While the the original model could accurately describe the kinetics of viral spread locally and systemically, we also found that many alternative versions of the model, for example, if viral spread starts at upper leaves and progresses to lower leaves or when virus dissemination is stopped due to an immune response, provided fits of the data with reasonable quality, and yet with different parameter estimates. These results strongly suggest that experimental measurements of the virus infection in individual leaves may not be sufficient to identify the pathways of viral dissemination between different leaves and reasons for viral control; we propose experiments that may allow discrimination between the alternatives. By analyzing the kinetics of coinfection of individual cells by Venus and BFP strains of TEV we found a strong deviation from the random infection model, suggesting cooperation between the two strains when infecting plant cells. Importantly, we showed that many mathematical models on the kinetics of coinfection of cells with two strains could not adequately describe the data, and the best fit model needed to assume i) different susceptibility of uninfected cells to infection by two viruses locally in the leaf vs. systemically from other leaves, and ii) decrease in the infection rate depending on the fraction of uninfected cells which could be due to a systemic immune response. Our results thus demonstrate the difficulty in reaching definite conclusions from extensive and yet limited experimental data and provide evidence of potential cooperation between different viral variants infecting individual cells in plants.

Comparative Analysis of Sugar Metabolites and Their Transporters in Sugarcane Following Sugarcane mosaic virus (SCMV) Infection

Sugarcane mosaic virus (SCMV) is one of the major pathogens of sugarcane. SCMV infection causes dynamic changes in plant cells, including decreased photosynthetic rate, respiration, and sugar metabolism. To understand the basics of pathogenicity mechanism, we performed transcriptome and proteomics analysis in two sugarcane genotypes (Badila: susceptible to SCMV and B-48: SCMV resistant). Using Saccharum spontaneum L. genome as a reference, we identified the differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) that participate in sugar metabolism, transport of their metabolites, and Carbohydrate Activating enZYmes (CAZymes). Sequencing data revealed 287 DEGs directly or indirectly involved in sugar metabolism, transport, and storage, while 323 DEGs are associated with CAZymes. Significant upregulation of glucose, sucrose, fructose, starch, and SWEET-related transcripts was observed in the Badila after infection of SCMV. B-48 showed resistance against SCMV with a limited number of sugar transcripts up-regulation at the post-infection stage. For CAZymes, only glycosyltransferase (GT)1 and glycosyl hydrolase (GH)17 were upregulated in B-48. Regulation of DEGs was analyzed at the proteomics level as well. Starch, fructose, glucose, GT1, and GH17 transcripts were expressed at the post-translational level. We verified our transcriptomic results with proteomics and qPCR data. Comprehensively, this study proved that Badila upregulated sugar metabolizing and transporting transcripts and proteins, which enhance virus multiplication and infectionl.

A longitudinal population-based study of predictors of mortality from bloodstream infections in Calgary, Alberta, Canada

Aim: To study the predictors of mortality from nine major pathogens causing approximately 70% of cases over a 7-year period. Materials & methods: A population-based surveillance cohort of all adult and pediatric patients in the Calgary Zone with an initial episode of bloodstream infections (BSI). Results: The 1-year mortality was 29.2% among 9524 patients (5164 males [54%]). Incidence rates for BSI increased annually to 119.7/100,000 persons by 2016. Distinct survival curves were found for each specific pathogen. Age, comorbidity burden and infecting organism were significantly associated with increased hazard of death. No relationship occurred between the time to positivity for blood cultures and overall mortality. Conclusion: BSI has a high mortality, but overall survival depends on underlying host health and the type of pathogen acquired.

A Review of UK-Registered and Candidate Vaccines for Bovine Respiratory Disease

Vaccination is widely regarded as a cornerstone in animal or herd health and infectious disease management. Nineteen vaccines against the major pathogens implicated in bovine respiratory disease are registered for use in the UK by the Veterinary Medicines Directorate (VMD). However, despite annual prophylactic vaccination, bovine respiratory disease is still conservatively estimated to cost the UK economy approximately £80 million per annum. This review examines the vaccine types available, discusses the surrounding literature and scientific rationale of the limitations and assesses the potential of novel vaccine technologies.

Emergence of a novel recombinant of CV-A5 in HFMD epidemics in Xiangyang, China

Background Hand, foot and mouth disease (HFMD) is caused by a variety of enterovirus serotypes and the etiological spectrum worldwide has changed since a large scale of outbreaks occurred in 1997. Methods A large number of clinical specimens of HFMD patients were collected in Xiangyang and genotyping was performed by qRT-PCR, conventional PCR amplification and sequencing. Among the 146 CV-A5 detected cases, the complete genome sequences of representative strains were determined for genotyping and for recombination analysis. Results It was found that CV-A5 was one of the six major serotypes that caused the epidemic from October 2016 to December 2017. Phylogenetic analyses based on the VP1 sequences showed that these CV-A5 belonged to the genotype D which dominantly circulated in China. Recombination occurred between the CV-A5 and CV-A2 strains with a breakpoint in the 2A region at the nucleotide 3791. Conclusions The result may explain the emergence of CV-A5 as one of the major pathogens of HFMD. A multivalent vaccine against HFMD is urgently needed to control the disease and to prevent emerging and spreading of new recombinants.

DETIRE: A Hybrid Deep Learning Model for identifying Viral Sequences from Metagenomes

A metagenome contains all DNA sequences from an environmental sample, including viruses, bacteria, fungi, actinomycetes and so on. Since viruses are of huge abundance and have caused vast mortality and morbidity to human society in history as a kind of major pathogens, detecting viruses from metagenomes plays a crucial role in analysing the viral component of samples and is the very first step for clinical diagnosis. However, detecting viral fragments directly from the metagenomes is still a tough issue because of the existence of huge number of short sequences. In this paper, a hybrid Deep lEarning model for idenTifying vIral sequences fRom mEtagenomes (DETIRE), is proposed to solve the problem. Firstly, the graph-based nucleotide sequence embedding strategy is utilized to enrich the expression of DNA sequences by training an embedding matrix. Then the spatial and sequential features are extracted by trained CNN and BiLSTM networks respectively to improve the feature expression of short sequences. Finally, the two set of features are weighted combined for the final decision. Trained by 220,000 sequences of 500bp subsampled from the Virus and Host RefSeq genomes, DETIRE identifies more short viral sequences (<1,000bp) than three latest methods, DeepVirFinder, PPR-Meta and CHEER. DETIRE is freely available at https://github.com/crazyinter/DETIRE.

Arms and ammunitions: effectors at the interface of rice and it’s pathogens and pests

The plant immune system has evolved to resist attack by pathogens and pests. However, successful phytopathogens deliver effector proteins into plant cells where they hijack the host cellular machinery to suppress the plant immune responses and promote infection. This manipulation of the host cellular pathways is done by the pathogen using various enzymatic activities, protein- DNA or protein- protein interactions. Rice is one the major economically important crops and its yield is affected by several pathogens and pests. In this review, we summarize the various effectors at the plant- pathogen/ pest interface for the major pathogens and pests of rice, specifically, on the mode of action and target genes of the effector proteins. We then compare this across the major rice pathogens and pests in a bid to understand probable conserved pathways which are under attack from pathogens and pests in rice. This analysis highlights conserved patterns of effector action, as well as unique host pathways targeted by the pathogens and pests.