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Effective microbial forensic analysis of materials used in a potential biological attack requires robust methods of morphological and genetic characterization of the attack materials in order to enable the attribution of the materials to potential sources and to exclude other potential sources. The genetic homogeneity and potential intersample variability of many of the category A to C bioterrorism agents offer a particular challenge to the generation of attributive signatures, potentially requiring whole-genome or proteomic approaches to be utilized. Currently, irradiation of mail is standard practice at several government facilities judged to be at particularly high risk. Thus, initial forensic signatures would need to be recovered from inactivated (nonviable) material. In the study described in this report, we determined the effects of high-dose gamma irradiation on forensic markers of bacterial biothreat agent surrogate organisms with a particular emphasis on the suitability of genomic DNA (gDNA) recovered from such sources as a template for whole-genome analysis. While irradiation of spores and vegetative cells affected the retention of Gram and spore stains and sheared gDNA into small fragments, we found that irradiated material could be utilized to generate accurate whole-genome sequence data on the Illumina and Roche 454 sequencing platforms.

Once effective coronavirus disease 2019 (COVID-19) vaccines are developed, they will be scarce. This presents the question of how to distribute them fairly across countries. Vaccine allocation among countries raises complex and controversial issues involving public opinion, diplomacy, economics, public health, and other considerations. Nevertheless, many national leaders, international organizations, and vaccine producers recognize that one central factor in this decision-making is ethics (1, 2). Yet little progress has been made toward delineating what constitutes fair international distribution of vaccine. Many have endorsed ?equitable distribution of COVID-19?vaccine? without describing a framework or recommendations (3, 4). Two substantive proposals for the international allocation of a COVID-19 vaccine have been advanced, but are seriously flawed. We offer a more ethically defensible and practical proposal for the fair distribution of COVID-19 vaccine: the Fair Priority Model.The Fair Priority Model is primarily addressed to three groups. One is the COVAX facility?led by Gavi, the World Health Organization (WHO), and the Coalition for Epidemic Preparedness Innovations (CEPI)?which intends to purchase vaccines for fair distribution across countries (5). A second group is vaccine producers. Thankfully, many producers have publicly committed to a ?broad and equitable? international distribution of vaccine (2). The last group is national governments, some of whom have also publicly committed to a fair distribution (1).These groups need a clear framework for reconciling competing values, one that they and others will rightly accept as ethical and not just as an assertion of power. The Fair Priority Model specifies what a fair distribution of vaccines entails, giving content to their commitments. Moreover, acceptance of this common ethical framework will reduce duplication and waste, easing efforts at a fair distribution. That, in turn, will enhance producers' confidence that vaccines will be fairly allocated to benefit people, thereby motivating an increase in vaccine supply for international distribution. ; Fil: Emanuel, Ezekiel J. University of Pennsylvania; Estados Unidos ; Fil: Persad, Govind. University of Denver.; Estados Unidos ; Fil: Kern, Adam. University of Princeton; Estados Unidos ; Fil: Buchanan, Allen. University of Arizona; Estados Unidos ; Fil: Fabre, Cécile. All Souls College; Reino Unido ; Fil: Halliday, Daniel. University of Melbourne; Australia ; Fil: Heath, Joseph. University of Toronto; Canadá ; Fil: Herzog, Lisa. University of Groningen; Países Bajos ; Fil: Leland, R. J. University of Manitoba; Canadá ; Fil: Lemango, Ephrem T. No especifíca; ; Fil: Luna, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Facultad Latinoamericana de Ciencias Sociales; Argentina ; Fil: McCoy, Matthew S. University of Pennsylvania; Estados Unidos ; Fil: Norheim, Ole F. University of Bergen; Noruega ; Fil: Ottersen, Trygve. Norwegian Institute Of Public Health; Noruega ; Fil: Schaefer, G. Owen. Yong Loo Lin School Of Medicine; Singapur ; Fil: Tan, Kok-Chor. University of Pennsylvania; Estados Unidos ; Fil: Wellman, Christopher Heath. Washington University in St. Louis; Estados Unidos ; Fil: Wolff, Jonathan. University of Oxford; Reino Unido ; Fil: Richardson, Henry S. Kennedy Institute Of Ethics; Estados Unidos

Background The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. Results The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. Conclusions By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available.