Fungi under Modified Atmosphere—The Effects of CO2 Stress on Cell Membranes and Description of New Yeast Stenotrophomyces fumitolerans gen. nov., sp. nov.

High levels of carbon dioxide are known to inhibit the growth of microorganisms. A total of twenty strains of filamentous fungi and yeasts were isolated from habitats with enriched carbon dioxide concentration. Most strains were derived from modified atmosphere packed (MAP) food products or mofettes and were cultivated under an atmosphere of 20% CO₂ and 80% O₂. The influence of CO₂ on fungal cell membrane fatty acid profiles was examined in this study. Major changes were the increase in linolenic acid (C18:3 cis 9, 12, 15) and, additionally in most strains, linoleic acid (C18:2 cis 9, 12) with a maximum of 24.8%, at the expense of oleic (C18:1 cis 9), palmitic (C16:0), palmitoleic (C16:1 cis 9) and stearic acid (C18:0). The degree of fatty acid unsaturation increased for all of the strains in the study, which consequently led to lower melting temperatures of the cell membranes after incubation with elevated levels of CO₂, indicating fluidization of the membrane and a potential membrane malfunction. Growth was reduced in 18 out of 20 strains in laboratory experiments and a change in pigmentation was observed in several strains. Two of the isolated strains, strain WT5 and strain WR1, were found to represent a hitherto undescribed yeast for which the new genus and species Stenotrophomyces fumitolerans (MB# 849906) is proposed

HuR biological function involves RRM3-mediated dimerization and RNA binding by all three RRMs

HuR/ELAVL1 is an RNA-binding protein involved in differentiation and stress response that acts primarily by stabilizing messenger RNA (mRNA) targets. HuR comprises three RNA recognition motifs (RRMs) where the structure and RNA binding of RRM3 and of full-length HuR remain poorly understood. Here, we report crystal structures of RRM3 free and bound to cognate RNAs. Our structural, NMR and biochemical data show that RRM3 mediates canonical RNA interactions and reveal molecular details of a dimerization interface localized on the -helical face of RRM3. NMR and SAXS analyses indicate that the three RRMs in full-length HuR are flexibly connected in the absence of RNA, while they adopt a more compact arrangement when bound to RNA. Based on these data and crystal structures of tandem RRM1,2- RNA and our RRM3-RNA complexes, we present a structural model of RNA recognition involving all three RRM domains of full-length HuR. Mutational analysis demonstrates that RRM3 dimerization and RNA binding is required for functional activity of fulllength HuR in vitro and to regulate target mRNAs levels in human cells, thus providing a fine-tuning for HuR activity in vivo.Peer reviewe

Structural basis of RNA recognition and dimerization by the STAR proteins T-STAR and Sam68

Sam68 and T-STAR are members of the STAR family of proteins that directly link signal transduction with post-transcriptional gene regulation. Sam68 controls the alternative splicing of many oncogenic proteins. T-STAR is a tissue-specific paralogue that regulates the alternative splicing of neuronal pre-mRNAs. STAR proteins differ from most splicing factors, in that they contain a single RNA-binding domain. Their specificity of RNA recognition is thought to arise from their property to homodimerize, but how dimerization influences their function remains unknown. Here, we establish at atomic resolution how T-STAR and Sam68 bind to RNA, revealing an unexpected mode of dimerization different from other members of the STAR family. We further demonstrate that this unique dimerization interface is crucial for their biological activity in splicing regulation, and suggest that the increased RNA affinity through dimer formation is a crucial parameter enabling these proteins to select their functional targets within the transcriptome

ARTEFACTS: How do we want to deal with the future of our one and only planet?

The European Commission’s Science and Knowledge Service, the Joint Research Centre (JRC), decided to try working hand-in-hand with leading European science centres and museums. Behind this decision was the idea that the JRC could better support EU Institutions in engaging with the European public. The fact that European Union policies are firmly based on scientific evidence is a strong message which the JRC is uniquely able to illustrate. Such a collaboration would not only provide a platform to explain the benefits of EU policies to our daily lives but also provide an opportunity for European citizens to engage by taking a more active part in the EU policy making process for the future. A PILOT PROGRAMME To test the idea, the JRC launched an experimental programme to work with science museums: a perfect partner for three compelling reasons. Firstly, they attract a large and growing number of visitors. Leading science museums in Europe have typically 500 000 visitors per year. Furthermore, they are based in large European cities and attract local visitors as well as tourists from across Europe and beyond. The second reason for working with museums is that they have mastered the art of how to communicate key elements of sophisticated arguments across to the public and making complex topics of public interest readily accessible. That is a high-value added skill and a crucial part of the valorisation of public-funded research, never to be underestimated. Finally museums are, at present, undergoing something of a renaissance. Museums today are vibrant environments offering new techniques and technologies to both inform and entertain, and attract visitors of all demographics.JRC.H.2-Knowledge Management Methodologies, Communities and Disseminatio

Pesticide authorization in the EU-environment unprotected?

Abstract Pesticides constitute an integral part of highintensity European agriculture. Prior to their authorization, a highly elaborated environmental risk assessment is mandatory according to EU pesticide legislation, i.e., Regulation (EC) No. 1107/2009. However, no field data-based evaluation of the risk assessment outcome, i.e., the regulatory acceptable concentrations (RACs), and therefore of the overall protectiveness of EU pesticide regulations exists. We conducted here a comprehensive meta-analysis using peer-reviewed literature on agricultural insecticide concentrations in EU surface waters and evaluated associated risks using the RACs derived from official European pesticide registration documents. As a result, 44.7 % of the 1566 cases of measured insecticide concentrations (MICs) in EU surface waters exceeded their respective RACs. It follows that current EU pesticide regulations do not protect the aquatic environment and that insecticides threaten aquatic biodiversity. RAC exceedances were significantly higher for insecticides authorized using conservative tier-I RACs and for more recently developed insecticide classes, i.e., pyrethroids. In addition, we identified higher risks, e.g., for smaller surface waters that are specifically considered in the regulatory risk assessment schemes. We illustrate the shortcomings of the EU regulatory risk assessment using two case studies that contextualize the respective risk assessment outcomes to field exposure. Overall, our metaanalysis challenges the field relevance and protectiveness of the regulatory environmental risk assessment conducted for pesticide authorization in the EU and indicates that critical revisions of related pesticide regulations and effective mitigation measures are urgently needed to substantially reduce the environmental risks arising from agricultural insecticide use

Modeling Regulatory Threshold Levels for Pesticides in Surface Waters from Effect Databases

Regulatory threshold levels (RTL) represent robust benchmarks for assessing risks of pesticides, e.g., in surface waters. However, comprehensive scientific risk evaluations comparing RTL to measured environmental concentrations (MEC) of pesticides in surface waters were yet restricted to a low number of pesticides, as RTL are only available after extensive review of regulatory documents. Thus, the aim of the present study was to model RTL equivalents (RTLe) for aquatic organisms from publicly accessible ecotoxicological effect databases. We developed a model that applies validity criteria in accordance with official US EPA review guidelines and validated the model against a set of manually retrieved RTL (n = 49). Model application yielded 1283 RTLe (n = 676 for pesticides, plus 607 additional RTLe for other use types). In a case study, the usability of RTLe was demonstrated for a set of 27 insecticides by comparing RTLe and RTL exceedance rates for 3001 MEC from US surface waters. The provided dataset enables thorough risk assessments of surface water exposure data for a comprehensive number of substances. Especially regions without established pesticide regulations may benefit from this dataset by using it as a baseline information for pesticide risk assessment and for the identification of priority substances or potential high-risk regions

Regulatory FOCUS Surface Water Models Fail to Predict Insecticide Concentrations in the Field

The FOrum for the Co-ordination of pesticide fate models and their USe (FOCUS) exposure models are used to predict the frequency and magnitude of pesticide surface water concentrations within the European regulatory risk assessment. The predictions are based on realistic worst-case assumptions that result in predicted environmental concentrations (PEC). Here, we compared for the first time a larger data set of 122 measured field concentrations (MFC) of agricultural insecticides extracted from 22 field studies to respective PECs by using FOCUS steps 1–4. While FOCUS step 1 and 2 PECs generally overpredicted the MFCs, 23% of step 3 and 31% of step 4 standard PECs were exceeded by surface water MFCs, which questions the protectiveness of the FOCUS exposure assessment. Using realistic input parameters, step 3 simulations underpredicted MFCs in surface water and sediment by 43% and 78%, respectively, which indicate that a higher degree of realism even reduces the protectiveness of model results. The ratios between PEC and MFC in surface water were significantly lower for pyrethroids than for organophosphorus or organochlorine insecticides, which suggests that the FOCUS predictions are less protective for hydrophobic insecticides. In conclusion, the FOCUS modeling approach is not protective for insecticide concentrations in the field