Ranking the risk of animal-to-human spillover for newly discovered viruses

The death toll and economic loss resulting from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic are stark reminders that we are vulnerable to zoonotic viral threats. Strategies are needed to identify and characterize animal viruses that pose the greatest risk of spillover and spread in humans and inform public health interventions. Using expert opinion and scientific evidence, we identified host, viral, and environmental risk factors contributing to zoonotic virus spillover and spread in humans. We then developed a risk ranking framework and interactive web tool, SpillOver, that estimates a risk score for wildlife-origin viruses, creating a comparative risk assessment of viruses with uncharacterized zoonotic spillover potential alongside those already known to be zoonotic. Using data from testing 509,721 samples from 74,635 animals as part of a virus discovery project and public records of virus detections around the world, we ranked the spillover potential of 887 wildlife viruses. Validating the risk assessment, the top 12 were known zoonotic viruses, including SARS-CoV-2. Several newly detected wildlife viruses ranked higher than known zoonotic viruses. Using a scientifically informed process, we capitalized on the recent wealth of virus discovery data to systematically identify and prioritize targets for investigation. The publicly accessible SpillOver platform can be used by policy makers and health scientists to inform research and public health interventions for prevention and rapid control of disease outbreaks. SpillOver is a living, interactive database that can be refined over time to continue to improve the quality and public availability of information on viral threats to human health

Transcriptome analysis of Bupleurum chinense focusing on genes involved in the biosynthesis of saikosaponins

<p>Abstract</p> <p>Background</p> <p><it>Bupleurum chinense </it>DC. is a widely used traditional Chinese medicinal plant. Saikosaponins are the major bioactive constituents of <it>B. chinense</it>, but relatively little is known about saikosaponin biosynthesis. The 454 pyrosequencing technology provides a promising opportunity for finding novel genes that participate in plant metabolism. Consequently, this technology may help to identify the candidate genes involved in the saikosaponin biosynthetic pathway.</p> <p>Results</p> <p>One-quarter of the 454 pyrosequencing runs produced a total of 195, 088 high-quality reads, with an average read length of 356 bases (NCBI SRA accession SRA039388). A <it>de novo </it>assembly generated 24, 037 unique sequences (22, 748 contigs and 1, 289 singletons), 12, 649 (52.6%) of which were annotated against three public protein databases using a basic local alignment search tool (E-value ≤1e-10). All unique sequences were compared with NCBI expressed sequence tags (ESTs) (237) and encoding sequences (44) from the <it>Bupleurum </it>genus, and with a Sanger-sequenced EST dataset (3, 111). The 23, 173 (96.4%) unique sequences obtained in the present study represent novel <it>Bupleurum </it>genes. The ESTs of genes related to saikosaponin biosynthesis were found to encode known enzymes that catalyze the formation of the saikosaponin backbone; 246 cytochrome P450 (<it>P450</it>s) and 102 glycosyltransferases (<it>GT</it>s) unique sequences were also found in the 454 dataset. Full length cDNAs of 7 <it>P450</it>s and 7 uridine diphosphate <it>GT</it>s (<it>UGT</it>s) were verified by reverse transcriptase polymerase chain reaction or by cloning using 5' and/or 3' rapid amplification of cDNA ends. Two <it>P450</it>s and three <it>UGT</it>s were identified as the most likely candidates involved in saikosaponin biosynthesis. This finding was based on the coordinate up-regulation of their expression with <it>β-AS </it>in methyl jasmonate-treated adventitious roots and on their similar expression patterns with <it>β-AS </it>in various <it>B. chinense </it>tissues.</p> <p>Conclusions</p> <p>A collection of high-quality ESTs for <it>B. chinense </it>obtained by 454 pyrosequencing is provided here for the first time. These data should aid further research on the functional genomics of <it>B. chinense </it>and other <it>Bupleurum </it>species. The candidate genes for enzymes involved in saikosaponin biosynthesis, especially the <it>P450</it>s and <it>UGT</it>s, that were revealed provide a substantial foundation for follow-up research on the metabolism and regulation of the saikosaponins.</p

Cross-cutting principles for planetary health education

Since the 2015 launch of the Rockefeller Foundation Lancet Commission on planetary health,1 an enormous groundswell of interest in planetary health education has emerged across many disciplines, institutions, and geographical regions. Advancing these global efforts in planetary health education will equip the next generation of scholars to address crucial questions in this emerging field and support the development of a community of practice. To provide a foundation for the growing interest and efforts in this field, the Planetary Health Alliance has facilitated the first attempt to create a set of principles for planetary health education that intersect education at all levels, across all scales, and in all regions of the world—ie, a set of cross-cutting principles

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security