Mutations in the intersubunit bridge regions of 16S rRNA affect decoding and subunit–subunit interactions on the 70S ribosome

The small and large subunits of the ribosome are held together by a series of bridges, involving RNA–RNA, RNA–protein and protein–protein interactions. Some 12 bridges have been described for the Escherichia coli 70S ribosome. In this work, we have targeted for mutagenesis, some of the 16S rRNA residues involved in the formation of intersubunit bridges B3, B5, B6, B7b and B8. In addition to effects on subunit association, the mutant ribosomes also affect the fidelity of translation; bridges B5, B6 and B8 increase decoding errors during elongation, while disruption of bridges B3 and B7b alters the stringency of start codon selection. Moreover, mutations in the bridge B5, B6 and B8 regions of 16S rRNA also correct the growth and decoding defects associated with alterations in ribosomal protein S12. These results link bridges B5, B6 and B8 with the decoding process and are consistent with the recently described location of translation factor EF-Tu on the ribosome and the proposed involvement of h14 in activating Guanosine-5′-triphosphate (GTP) hydrolysis by aminoacyl-tRNA•EF-Tu•GTP. These observations are consistent with a model in which bridges B5, B6 and B8 contribute to the fidelity of translation by modulating GTP hydrolysis by aminoacyl-tRNA•EF-Tu•GTP ternary complexes during the elongation phase of protein synthesis

Review of the European Greenomyia Brunetti (Diptera, Mycetophilidae) with new descriptions of females

The females of the four continental Greenomyia Brunetti species in Europe are associated with the males, diagnosed and keyed, providing the first association and description of the females of Greenomyia baikalica Zaitzev, 1994 and Greenomyia stackelbergi Zaitzev, 1982. Colour photographs of their habitus and line drawings of their female terminalia are provided. Greenomyia mongolica Laštovka & Matile, 1974 is found to be a senior synonym of Greenomyia theresae Matile, 2002. syn. n. The diagnostic characters used to distinguish between Greenomyia and Neoclastobasis Ostroverkhova in keys did not hold up to a closer scrutiny and leave the status of Neoclastobasis as separate genus questionable

Comparison of ammonia emissions related to nitrogen use efficiency of livestock production in Europe

The increasing global demand for food and the environmental effects of reactive nitrogen losses in the food production chain, increase the need for efficient use of nitrogen (N). Of N harvested in agricultural plant products, 80% is used to feed livestock. Because the largest atmospheric loss of reactive nitrogen from livestock production systems is ammonia (NH3), the focus of this paper is on N lost as NH3 during the production of animal protein. The focus of this paper is to understand the key factors explaining differences in Nitrogen Use Efficiency (NUE) of animal production among various European countries. Therefore we developed a conceptual framework to describe the NUE defined as the amount of animal-protein N per N in feed and NH3–N losses in the production of milk, beef, pork, chicken meat and eggs in The Netherlands, Switzerland, United Kingdom, Germany, Austria and Denmark. The framework describes how manure management and animal-related parameters (feed, metabolism) relate to NH3 emissions and NUE. The results showed that the animal product with the lowest NUE had the largest NH3 emissions and vice versa, which agrees with the reciprocal relationship between NUE and NH3 within the conceptual framework. Across animal products for the countries considered, about 20% of the N in feed is lost as NH3. The significant smallest proportion (12%) of NH3–N per unit of Nfeed is from chicken production. The proportions for other products are 17%, 19%, 20% and 22% for milk, pork, eggs and beef respectively. These differences were not significantly different due to the differences among countries. For all countries, NUE was lowest for beef and highest for chicken. The production of 1 kg N in beef required about 5 kg N in feed, of which 1 kg N was lost as NH3–N. For the production of 1 kg N in chicken meat, 2 kg N in feed was required and 0.2 kg was lost as NH3. The production of 1 kg N in milk required 4 kg N in feed with 0.6 kg NH3–N loss, the same as pork and eggs, but those needed 3 and 3.5 kg N in feed per kg N in product respectively. Except for beef, the differences among these European countries were mainly caused by differences in manure management practices and their emission factors, rather than by animal-related factors including feed and digestibility influencing the excreted amount of ammoniacal N (TAN). For beef, both aspects caused important differences. Based on the results, we encourage the expression of N losses as per N in feed or per N in product, in addition to per animal place, when comparing production efficiency and NUE. We consider that disaggregating emission factors into a diet/animal effect and a manure management effect would improve the basis for comparing national NH3 emission inventories. © 2018 The Author

Source control options for reducing emission of priority pollutants from urban areas.

The overall aim of the ScorePP project is to develop comprehensive and appropriate source control strategies that authorities, cities, water utilities and the chemical industry can employ to reduce emissions of priority pollutants (PPs) from urban areas into the receiving water environment. Focus is on the 33 priority and priority hazardous substances and substance groups identified in the European Water Framework Directive. However, this list may be expanded to include emerging pollutants or reduced if appropriate model compounds can be identified. The initial work focuses on 67 substances, including substances identified in the proposed European environmental quality standard (EQS) directive as well as the defined example compounds and several organometallic derivatives. Information on inherent properties, environmental presence and fate, and legislative issues is made available in open database format, and a data management system combining chemical identification (CAS#), NACE economic activity classifications and NOSE-P emission source classifications has been developed as a basis for spatial characterisation of PP sources using GIS. Further work will focus on dynamic urban scale source-flux models, identifying emission patterns and optimising monitoring programmes in case studies and multi-criteria comparison of source control versus end-of-pipe mitigation options in relation to their economic, social and environmental impacts