Early identification of common-source foodborne virus outbreaks in Europe.

The importance of foodborne viral infections is increasingly recognized. Food handlers can transmit infection during preparation or serving; fruit and vegetables may be contaminated by fecally contaminated water used for growing or washing. And the globalization of the food industry mean that a contaminated food item may not be limited to national distribution. International outbreaks do occur, but little data are available about the incidence of such events and the food items associated with the highest risks. We developed a combined research and surveillance program for enteric viruses involving 12 laboratories in 9 European countries. This project aims to gain insight into the epidemiology of enteric viruses in Europe and the role of food in transmission by harmonizing (i.e., assessing the comparability of data through studies of molecular detection techniques) and enhancing epidemiologic surveillance. We describe the setup and preliminary results of our system, which uses a Web-accessible central database to track viruses and provides the foundation for an early warning system of foodborne and other common-source outbreaks

A regionally informed abundance index for supporting integrative analyses across butterfly monitoring schemes

1. The rapid expansion of systematic monitoring schemes necessitates robust methods to reliably assess species' status and trends. Insect monitoring poses a challenge where there are strong seasonal patterns, requiring repeated counts to reliably assess abundance. Butterfly monitoring schemes (BMSs) operate in an increasing number of countries with broadly the same methodology, yet they differ in their observation frequency and in the methods used to compute annual abundance indices. 2. Using simulated and observed data, we performed an extensive comparison of two approaches used to derive abundance indices from count data collected via BMS, under a range of sampling frequencies. Linear interpolation is most commonly used to estimate abundance indices from seasonal count series. A second method, hereafter the regional generalized additive model (GAM), fits a GAM to repeated counts within sites across a climatic region. For the two methods, we estimated bias in abundance indices and the statistical power for detecting trends, given different proportions of missing counts. We also compared the accuracy of trend estimates using systematically degraded observed counts of the Gatekeeper Pyronia tithonus (Linnaeus 1767). 3. The regional GAM method generally outperforms the linear interpolation method. When the proportion of missing counts increased beyond 50%, indices derived via the linear interpolation method showed substantially higher estimation error as well as clear biases, in comparison to the regional GAM method. The regional GAM method also showed higher power to detect trends when the proportion of missing counts was substantial. 4. Synthesis and applications. Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within-year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales

The European Butterfly Indicator for grassland species: 1990-2013

This report presents the fifth version of the European Grassland Butterfly Indicator, one of the EU biodiversity indicators of the European Environment Agency

Identification of Loci Associated with Enhanced Virulence in Spodoptera litura Nucleopolyhedrovirus Isolates Using Deep Sequencing

Spodoptera litura is an emerging pest insect in cotton and arable crops in Central Asia. To explore the possibility of using baculoviruses as biological control agents instead of chemical pesticides, in a previous study we characterized a number of S. litura nucleopolyhedrovirus (SpltNPV) isolates from Pakistan. We found significant differences in speed of kill, an important property of a biological control agent. Here we set out to understand the genetic basis of these differences in speed of kill, by comparing the genome of the fast-killing SpltNPV-Pak-TAX1 isolate with that of the slow-killing SpltNPV-Pak-BNG isolate. These two isolates and the SpltNPV-G2 reference strain from China were deep sequenced with Illumina. As expected, the two Pakistani isolates were closely related with >99% sequence identity, whereas the Chinese isolate was more distantly related. We identified two loci that may be associated with the fast action of the SpltNPV-Pak-TAX1 isolate. First, an analysis of rates of synonymous and non-synonymous mutations identified neutral to positive selection on open reading frame (ORF) 122, encoding a viral fibroblast growth factor (vFGF) that is known to affect virulence in other baculoviruses. Second, the homologous repeat region hr17, a putative enhancer of transcription and origin of replication, is absent in SpltNPV-Pak-TAX1 suggesting it may also affect virulence. Additionally, we found there is little genetic variation within both Pakistani isolates, and we identified four genes under positive selection in both isolates that may have played a role in adaptation of SpltNPV to conditions in Central Asia. Our results contribute to the understanding of the enhanced activity of SpltNPV-Pak-TAX1, and may help to select better SpltNPV isolates for the control of S. litura in Pakistan and elsewhere.</p

Identification of Loci Associated with Enhanced Virulence in Spodoptera litura Nucleopolyhedrovirus Isolates Using Deep Sequencing

Spodoptera litura is an emerging pest insect in cotton and arable crops in Central Asia. To explore the possibility of using baculoviruses as biological control agents instead of chemical pesticides, in a previous study we characterized a number of S. litura nucleopolyhedrovirus (SpltNPV) isolates from Pakistan. We found significant differences in speed of kill, an important property of a biological control agent. Here we set out to understand the genetic basis of these differences in speed of kill, by comparing the genome of the fast-killing SpltNPV-Pak-TAX1 isolate with that of the slow-killing SpltNPV-Pak-BNG isolate. These two isolates and the SpltNPV-G2 reference strain from China were deep sequenced with Illumina. As expected, the two Pakistani isolates were closely related with >99% sequence identity, whereas the Chinese isolate was more distantly related. We identified two loci that may be associated with the fast action of the SpltNPV-Pak-TAX1 isolate. First, an analysis of rates of synonymous and non-synonymous mutations identified neutral to positive selection on open reading frame (ORF) 122, encoding a viral fibroblast growth factor (vFGF) that is known to affect virulence in other baculoviruses. Second, the homologous repeat region hr17, a putative enhancer of transcription and origin of replication, is absent in SpltNPV-Pak-TAX1 suggesting it may also affect virulence. Additionally, we found there is little genetic variation within both Pakistani isolates, and we identified four genes under positive selection in both isolates that may have played a role in adaptation of SpltNPV to conditions in Central Asia. Our results contribute to the understanding of the enhanced activity of SpltNPV-Pak-TAX1, and may help to select better SpltNPV isolates for the control of S. litura in Pakistan and elsewhere.</p