An evolutionarily conserved phosphoserine-arginine salt bridge in the interface between ribosomal proteins uS4 and uS5 regulates translational accuracy in Saccharomyces cerevisiae

Protein-protein and protein-rRNA interactions at the interface between ribosomal proteins uS4 and uS5 are thought to maintain the accuracy of protein synthesis by increasing selection of cognate aminoacyl-tRNAs. Selection involves a major conformational change-domain closure-that stabilizes aminoacyl-tRNA in the ribosomal acceptor (A) site. This has been thought a constitutive function of the ribosome ensuring consistent accuracy. Recently, the Saccharomyces cerevisiae Ctk1 cyclin-dependent kinase was demonstrated to ensure translational accuracy and Ser238 of uS5 proposed as its target. Surprisingly, Ser238 is outside the uS4-uS5 interface and no obvious mechanism has been proposed to explain its role. We show that the true target of Ctk1 regulation is another uS5 residue, Ser176, which lies in the interface opposite to Arg57 of uS4. Based on site specific mutagenesis, we propose that phospho-Ser176 forms a salt bridge with Arg57, which should increase selectivity by strengthening the interface. Genetic data show that Ctk1 regulates accuracy indirectly; the data suggest that the kinase Ypk2 directly phosphorylates Ser176. A second kinase pathway involving TORC1 and Pkc1 can inhibit this effect. The level of accuracy appears to depend on competitive action of these two pathways to regulate the level of Ser176 phosphorylation.

Long-term increases in soil carbon due to ecosystem fertilization by atmospheric nitrogen deposition demonstrated by regional-scale modelling and observations

Fertilization of nitrogen (N)-limited ecosystems by anthropogenic atmospheric nitrogen deposition (Ndep) may promote CO2 removal from the atmosphere, thereby buffering human effects on global radiative forcing. We used the biogeochemical ecosystem model N14CP, which considers interactions among C (carbon), N and P (phosphorus), driven by a new reconstruction of historical Ndep, to assess the responses of soil organic carbon (SOC) stocks in British semi-natural landscapes to anthropogenic change. We calculate that increased net primary production due to Ndep has enhanced detrital inputs of C to soils, causing an average increase of 1.2 kgCm-2 (c. 10%) in soil SOC over the period 1750-2010. The simulation results are consistent with observed changes in topsoil SOC concentration in the late 20th Century, derived from sample-resample measurements at nearly 2000 field sites. More than half (57%) of the additional topsoil SOC is predicted to have a short turnover time (c. 20 years), and will therefore be sensitive to future changes in Ndep. The results are the first to validate model predictions of Ndep effects against observations of SOC at a regional field scale. They demonstrate the importance of long-term macronutrient interactions and the transitory nature of soil responses in the terrestrial C cycle.

Concentrations and geographic distribution of selected organic pollutants in Scottish surface soils

Concentrations of selected persistent organic pollutants (POPs) representing three chemical classes (polycyclic aromatic hydrocarbons (PAH), polybrominated diphenyl ethers (PBDE) and polychlorinated biphenyls (PCB) and the organic pollutant diethylhexyl phthalate (DEHP), were determined in surface soil samples (0-5 cm) collected at 20 km grid intersects throughout Scotland over a three-year period. Detectable amounts of all chemical classes and most individual congeners were present in all samples. There were no consistent effects of soil or vegetation type, soil carbon content, pH, altitude or distance from centres of population on concentrations which exhibited extreme variation, even in adjacent samples. It is concluded that soil POPs and DEHP concentrations and associated rates of animal and human exposure were highly variable, influenced by multiple, interacting factors, and not clearly related to local sources but possibly related to wet atmospheric deposition and the organic carbon content of the soil.

Modelling nitrate losses from agricultural activities on a national scale

The Nitrogen Risk Assessment Model for Scotland (NIRAMS) has been developed as a screening tool for prediction of streamwater N concentrations draining from agricultural land in Scotland. The objective of the model is to be able to predict N concentrations for ungauged catchments, to fill gaps in monitoring data and provide guidance in relation to policy development. The model uses national land use, soils and meteorology data sets and has been developed within an ArcView GIS user interface. The model includes modules to calculate N inputs to the land, residual N remaining at the end of the growing season, weekly time-series of leached N and transport of N at the catchment scale. The N leaching and transport are. controlled by hydrological modules, including a national water balance model and a catchment scale transport model. Preliminary testing of NIRAMS has been carried out on eight Scottish catchments, diverse in terms of geographic location as well as land use. The model is capable of predicting the correct mean level of stream N concentrations, as well as the basic characteristics of seasonal variation. As such the model can be of value for providing estimates of N concentrations in ungauged areas.

Modelling the influence of irrigation abstractions on Scotland's water resources

Legislation to control abstraction of water in Scotland is limited and for purposes such as irrigation there are no restrictions in place over most of the country. This situation is set to change with implementation of the European Water Framework Directive. As a first step towards the development of appropriate policy for irrigation control there is a need to assess the current scale of irrigation practices in Scotland. This paper presents a modelling approach that has been used to quantify spatially the volume of water abstractions across the country for irrigation of potato crops under typical climatic conditions. A water balance model was developed to calculate soil moisture deficits and identify the potential need for irrigation. The results were then combined with spatial data on potato cropping and integrated to the sub-catchment scale to identify the river systems most at risk from over-abstraction. The results highlight that the areas that have greatest need for irrigation of potatoes are all concentrated in the central east-coast area of Scotland. The difference between irrigation demand in wet and dry years is very significant, although spatial patterns of the distribution are similar.