Norovirus GII.Pe Genotype: Tracking a Foodborne Outbreak on a Cruise Ship Through Molecular Epidemiology,Brazil, 2014

Norovirus (NoV) is recognized as the most common cause of foodborne outbreaks. In 2014, an outbreak of acute gastroenteritis occurred on a cruise ship in Brazil, and NoV became the suspected etiology. Here we present the molecular identification of the NoV strains and the use of sequence analysis to determine modes of virus transmission. Food (cream cheese, tuna salad, grilled fish, orange mousse, and vegetables soup) and clinical samples were analyzed by ELISA, conventional RT-PCR, qRT-PCR, and sequencing. Genogroup GII NoV was identified by ELISA and conventional RT-PCR in fecal samples from 5 of 12 patients tested (41.7%), and in the orange mousse food sample by conventional RT-PCR and qRT-PCR. Two fecal GII NoV samples and the orange mousse GII NoV sample were successfully genotyped as GII.Pe (ORF 1), revealed 98.0–98.8% identities among them, and shared phylogenetically distinct cluster. Establishing the source of a NoV outbreak can be a challenging task. In this report, the molecular analysis of the partial RdRp NoV gene provided a powerful tool for genotyping (GII.Pe) and tracking of outbreak-related samples. In addition, the same fast and simple extraction methods applied to clinical samples could be successfully used for complex food matrices, and have the potential to be introduced in routine laboratories for screening foods for presence of NoV.     

Meeting emission targets under uncertainty—the case of Finnish non-emission-trading sector

The European Union (EU) has set a target to reduce its greenhouse gas (GHG) emissions at least 10 % below the 2005 levels by 2020 in the non-Emission Trading Sector (non-ETS). As part of this, each Member State has a binding national emission limitation target for the non-ETS sector. Finland’s target, examined as a case study in this paper, is to reduce emissions at least 16 % below 2005 levels by 2020. The objective of this study is to find cost optimal mitigation portfolios that meet Finland’s reduction target and to analyze the risks of not attaining the emission target or exceeding the assumed costs. The question was addressed with a stochastic optimization model, Stochastic Optimization of non-ETS Emissions (SONETS) selecting separate mitigation measures that meet the target on expectation. The results show that optimal portfolios include relatively high uncertainty both in costs and achieved reductions. The prices of crude oil and diesel, and the abatement cost of reducing hydrofluorocarbon (HFC) emissions seem to account for the majority of uncertainty regarding total costs. The baseline predictions for various non-ETS subsectors (such as transport and agriculture) were found to have the greatest contribution to the uncertainty of attaining emission target. The results also show that some abatement actions are chosen in nearly all efficient portfolios, while other actions are seldom chosen. For example replacing oil burners in the end of technical life time or recovery of methane (CH₄) from waste are often chosen whereas ban of landfilling of organic waste is chosen extremely seldom. It also seems that the results are somewhat sensitive to the inclusion or exclusion of the interdependencies of mitigation measures.     

Power matters in closing the phenotyping gap

Much of our understanding of physiology and metabolism is derived from investigating mouse mutants and transgenic mice, and open-access platforms for standardized mouse phenotyping such as the German Mouse Clinic (GMC) are currently viewed as one powerful tool for identifying novel gene-function relationships. Phenotyping or phenotypic screening involves the comparison of wild-type control mice with their mutant or transgenic littermates. In our study, we explored the extent to which standardized phenotyping will succeed in detecting biologically relevant phenotypic differences in mice generated and provided by different collaborators. We analyzed quantitative metabolic data (body mass, energy intake, and energy metabolized) collected at the GMC under the current workflow, and used them for statistical power considerations. Our results demonstrate that there is substantial variability in these parameters among lines of wild-type C57BL/6 (B6) mice from different sources. Given this variable background noise in mice that serve as controls, subtle phenotypes in mutant or transgenic littermates may be overlooked. Furthermore, a phenotype observed in one cohort of a mutant line may not be reproducible (to the same extent) in mice coming from a different environment or supplier. In the light of these constraints, we encourage researchers to incorporate information on intrastrain variability into future study planning, or to perform advanced hierarchical analyses. Both will ultimately improve the detectability of novel phenotypes by phenotypic screening. Carola W. Meyer and Ralf Elvert contributed equally to this work.     

Prenatal cannibalism in an insect

Host selection and infection strategies of parasitoids often correlate with high parental investment and low numbers of progeny. In this study, we investigate how additional internal mechanisms might shape brood size and fitness of the offspring. Emblemasoma auditrix is a parasitoid fly in which about 38 larvae hatch simultaneously in utero. After host location, a single larva is deposited into the host, where it rapidly develops and pupates after about 5 days. The search for hosts can take several weeks, and during that time, the larvae arrest their development and remain in the first larval instar. Nevertheless, the larvae increase in weight within the uterus, and this growth correlates to a decrease in the number of larvae, although no larvae are deposited. Thus, our data indicate a first case of prenatal cannibalism in an invertebrate with larvae feeding on each other within the uterus of the adult.     

Experience,but not distance,influences the recruitment precision in the stingless bee <Emphasis Type="Italic">Scaptotrigona mexicana</Emphasis>

Recruitment precision, i.e. the proportion of recruits that reach an advertised food source, is a crucial adaptation of social bees to their environment. Studies with honeybees showed that recruitment precision is not a fixed feature, but it may be enhanced by factors like experience and distance. However, little is known regarding the recruitment precision of stingless bees. Hence, in this study, we examined the effects of experience and spatial distance on the precision of the food communication system of the stingless bee Scaptotrigona mexicana. We conducted the experiments by training bees to a three-dimensional artificial patch at several distances from the colony. We recorded the choices of individual recruited foragers, either being newcomers (foragers without experience with the advertised food source) or experienced (foragers that had previously visited the feeder). We found that the average precision of newcomers (95.6 ± 2.61%) was significantly higher than that of experienced bees (80.2 ± 1.12%). While this might seem counter-intuitive on first sight, this “loss” of precision can be explained by the tendency of experienced recruits to explore nearby areas to find new rewarding food sources after they had initially learned the exact location of the food source. Increasing the distance from the colony had no significant effect on the precision of the foraging bees. Thus, our data show that experience, but not the distance of the food source, affected the patch precision of S. mexicana foragers.     

Impact analysis of drought, water excess and salinity on grass production in The Netherlands using historical and future climate data

The coupled SWAP-WOFOST model was used to study the effects of increasing salinity of groundwater, drought and water excess on grass production in The Netherlands. WOFOST simulates crop growth and SWAP simulates transport of water, solutes and heat in the vadose zone. The model was tested using several datasets from field experiments. We applied the models at regional scale where we quantified the impact of various groundwater salinity levels on grass growth and production using historical weather data (1971-2000). The salt concentrations in the subsoil were derived from the National Hydrological Instrument. The results show that salinity effects on grass production are limited. In wet years the excess rainfall will infiltrate the soil and reduce salt water seepage. In a next step we used future weather data for the year 2050, derived from 3 Global Circulation Models. From each model we used data from two CO₂ emission scenarios. As expected higher temperatures increased drought stress, however, the production reduction as a result of salt water in the root zone is limited. Salt stress mainly occurred when irrigation was applied with saline water. The increased CO₂ concentration in combination with the limited drought stress resulted in increasing simulated actual and potential yields. Overall conclusion for grassland in The Netherlands: drought stress is stronger than stress caused by water excess which on its turn is stronger than salinity stress. Future water demand for irrigation may increase by 11-19% and result in water scarcity if water supply is insufficient.     

Carbon footprint of food - approaches from national input-output statistics and a LCA of a food portion

The aim of the study, on which this paper is based, was to provide guidance to consumers to make environmentally responsible choices in their food consumption, to assist food supply chain stakeholders to identify the key areas for environmental improvements, and to provide policy makers with a tool for monitoring the potential impacts on climate change resulting from developments within the food sector. At the macro level, the EIO-LCA model was developed specifically for the Finnish food chain; at the micro level, LCAs were performed on 30 lunch portions. The contribution of the Finnish food chain to climate change was 14%, which comprised 40% CO₂ emissions, 25% CH₄ emissions, and 34% N₂O emissions. The share of impacts from domestic agricultural processes was the highest, at 69%. The impact of a single lunch portion ranged between 0.65 and 3.80 kg of equivalent CO₂. According to the EIO-LCA model, the average impact was 7.7 kg CO₂ eq/person daily. The consumer phase accounted for between 8 and 47% of the climate change impacts for homemade portions. In ready-to-eat portions industry and retail phases were emphasized, representing 25-38% of climate change impacts. We present an approach to steer the Finnish food sector onto an environmentally sustainable path; practical tools for consumers and farmers will especially need to be developed further.