Virion Structure and In Vitro Genome Release Mechanism of Dicistrovirus Kashmir Bee Virus

Infections with Kashmir bee virus (KBV) are lethal for honeybees and have been associated with colony collapse disorder. KBV and closely related viruses contribute to the ongoing decline in the number of honeybee colonies in North America, Europe, Australia, and other parts of the world. Despite the economic and ecological impact of KBV, its structure and infection process remain unknown. Here, we present the structure of the virion of KBV determined to a resolution of 2.8 angstrom. We show that the exposure of KBV to acidic pH induces a reduction in interpentamer contacts within capsids and the reorganization of its RNA genome from a uniform distribution to regions of high and low density. Capsids of KBV crack into pieces at acidic pH, resulting in the formation of open particles lacking pentamers of capsid proteins. The large openings of capsids enable the rapid release of genomes and thus limit the probability of their degradation by RNases. The opening of capsids may be a shared mechanism for the genome release of viruses from the family Dicistroviridae. IMPORTANCE The western honeybee (Apis mellifera) is indispensable for maintaining agricultural productivity as well as the abundance and diversity of wild flowering plants. However, bees suffer from environmental pollution, parasites, and pathogens, including viruses. Outbreaks of virus infections cause the deaths of individual honeybees as well as collapses of whole colonies. Kashmir bee virus has been associated with colony collapse disorder in the United States, and no cure for the disease is currently available. Here, we report the structure of an infectious particle of Kashmir bee virus and show how its protein capsid opens to release the genome. Our structural characterization of the infection process determined that therapeutic compounds stabilizing contacts between pentamers of capsid proteins could prevent the genome release of the virus.We gratefully acknowledge the Cryoelectron Microscopy and Tomography core facility of CEITEC supported by MEYS CR (LM2018127) . This research was carried out under the project CEITEC 2020 (LQ1601) , with financial support from the MEYS of the Czech Republic under National Sustainability Program II. This work was supported by IT4I project (CZ.1.05/1.1.00/02.0070) , funded by the European Regional Development Fund and the national budget of the Czech Republic via the RDIOP, as well as the MEYS via the grant (LM2011033) . The research of G.A.M. was supported by the grants CONICET (PIP 20150288) , 247 Agencia Nacional de Promocion Cientifica y Tecnica, Argentina (PICT no. 2015-248 0665, PICT No. 20181545) , and Universidad Nacional de La Plata, Argentina. The research of D.M.A.G. was supported by a Grupos Consolidados grant from the University of the Basque Country, Spain (GIU18/172) . The research leading to these results received funding from the Grant Agency of the Czech Republic grant GX19-25982X to P.P

The electrochemical and statistical evaluation of isolation of mellitin and apamin from honey bee (Apis Mellifera) venom.

We present in this manuscript for the first time the electrochemical and statistical evaluation of FPLC isolation of mellitin and apamin from honey bee (Apis mellifera) venom. Venoms are extremely complex blends of diverse substances that target a myriad of receptors or ion channels. Therefore, toxins, isolated from venomous organisms can be a valuable tool with diverse biological applications. In this study we decided to optimize the purification of honey bee venom by using fast protein liquid chromatography, to obtain biologically active peptide - melittin (2846.46 Da). Due to a presence of other compounds with similar molecular weight (apamin 2027.34 Da), we optimized a differential pulse voltammetry method with adsorptive transfer technique (AdT DPV), utilizing Brdicka supporting electrolyte for measurements. Typical voltammograms - fingerprints for each substance were obtained and numerical projections of voltammograms were employed to propose an artificial neural network. Our suggested neural network can simply predict the content of each peptide in fraction with following performance: 100 % for training and 100 % for testing

Laboratorni chov cmelaku (Hymenoptera: Apoidea: Bombus spp.)

Available from STL Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi