Organization of the multiaminoacyl-tRNA synthetase complex and the cotranslational protein folding

Aminoacyl-tRNA synthetases (ARSs) play an essential role in the protein synthesis by catalyzing an attachment of their cognate amino acids to tRNAs. Unlike their prokaryotic counterparts, ARSs in higher eukaryotes form a multiaminoacyl-tRNA synthetase complex (MARS), consisting of the subset of ARS polypeptides and three auxiliary proteins. The intriguing feature of MARS complex is the presence of only nine out of twenty ARSs, specific for Arg, Asp, Gln, Glu, Ile, Leu, Lys, Met, and Pro, regardless of the organism, cell, or tissue types. Although existence of MARSs complex in higher eukaryotes has been already known for more than four decades, its functional significance remains elusive. We found that seven of the nine corresponding amino acids (Arg, Gln, Glu, Ile, Leu, Lys, and Met) together with Ala form a predictor of the protein α-helicity. Remarkably, all amino acids (besides Ala) in the predictor have the highest possible number of side-chain rotamers. Therefore, compositional bias of a typical α-helix can contribute to the helix''s stability by increasing the entropy of the folded state. It also appears that position-specific α-helical propensity, specifically periodic alternation of charged and hydrophobic residues in the helices, may well be provided by the structural organization of the complex. Considering characteristics of MARS complex from the perspective of the α-helicity, we hypothesize that specific composition and structure of the complex represents a functional mechanism for coordination of translation with the fast and correct folding of amphiphilic α-helices.     

Using multivariate adaptive regression splines to predict the distributions of New Zealand's freshwater diadromous fish

1. Relationships between probabilities of occurrence for fifteen diadromous fish species and environmental variables characterising their habitat in fluvial waters were explored using an extensive collection of distributional data from New Zealand rivers and streams. Environmental predictors were chosen for their likely functional relevance, and included variables describing conditions in the stream segment where sampling occurred, downstream factors affecting the ability of fish to move upriver from the sea, and upstream, catchment‐scale factors mostly affecting variation in river flows. 2. Analyses were performed using multivariate adaptive regression splines (MARS), a technique that uses piece‐wise linear segments to describe non‐linear relationships between species and environmental variables. All species were analysed using an option that allows simultaneous analysis of community data to identify the combination of environmental variables best able to predict the occurrence of the component species. Model discrimination was assessed for each species using the area under the receiver operating characteristic curve (ROC) statistic, calculated using a bootstrap procedure that estimates performance when predictions are made to independent data. 3. Environmental predictors having the strongest overall relationships with probabilities of occurrence included distance from the sea, stream size, summer temperature, and catchment‐scale drivers of variation in stream flow. Many species were also sensitive to variation in either the average and/or maximum downstream slope, and riparian shade was an important predictor for some species. 4. Analysis results were imported into a Geographic Information System where they were combined with extensive environmental data, allowing spatially explicit predictions of probabilities of occurrence by species to be made for New Zealand's entire river network. This information will provide a valuable context for future conservation management in New Zealand's rivers and streams.     

Assignment-free solution NMR method reveals CesT as an unswapped homodimer

The X-ray structure of the homodimeric chaperone CesT is the only structure among the type three secretion system (TTSS) chaperones that shows a domain swap. This swap has potential importance for the mechanism of effector translocation through a TTSS. Here we present two nuclear magnetic resonance strategies exploiting pre-existing structural models and residual dipolar couplings (RDCs), which reveal the unswapped 35.4-kDa dimer to be present in solution. Particularly efficient is the discrimination of a swapped and unswapped structural state performed simultaneously to automatic backbone assignment using only HN-RDCs and carbonyl backbone chemical shifts. This direct approach may prove to be generally useful to rapidly differentiate two structural models.     

Adaptive regression splines in the Cox model

We develop a method for constructing adaptive regression spline models for the exploration of survival data. The method combines Cox's (1972, Journal of the Royal Statistical Society, Series B 34, 187-200) regression model with a weighted least-squares version of the multivariate adaptive regressi on spline (MARS) technique of Friedman (1991, Annals of Statistics 19, 1-141) to adaptively select the knots and covariates. The new technique can automatically fit models with terms that represent nonlinear effects and interactions among covariates. Applications based on simulated data and data from a clinical trial for myeloma are presented. Results from the myeloma application identified several important prognostic variables, including a possible nonmonotone relationship with survival in one laboratory variable. Results are compared to those from the adaptive hazard regression (HARE) method of Kooperberg, Stone, and Truong (1995, Journal of the American Statistical Association 90, 78-94).     

Coevolution of Specificity Determinants in Eukaryotic Glutamyl- and Glutaminyl-tRNA Synthetases

The glutaminyl-tRNA synthetase (GlnRS) enzyme, which pairs glutamine with tRNA^Gln for protein synthesis, evolved by gene duplication in early eukaryotes from a nondiscriminating glutamyl-tRNA synthetase (GluRS) that aminoacylates both tRNA^Gln and tRNA^Glu with glutamate. This ancient GluRS also separately differentiated to exclude tRNA^Gln as a substrate, and the resulting discriminating GluRS and GlnRS further acquired additional protein domains assisting function in cis (the GlnRS N-terminal Yqey domain) or in trans (the Arc1p protein associating with GluRS). These added domains are absent in contemporary bacterial GlnRS and GluRS. Here, using Saccharomyces cerevisiae enzymes as models, we find that the eukaryote-specific protein domains substantially influence amino acid binding, tRNA binding and aminoacylation efficiency, but they play no role in either specific nucleotide readout or discrimination against noncognate tRNA. Eukaryotic tRNA^Gln and tRNA^Glu recognition determinants are found in equivalent positions and are mutually exclusive to a significant degree, with key nucleotides located adjacent to portions of the protein structure that differentiated during the evolution of archaeal nondiscriminating GluRS to GlnRS. These findings provide important corroboration for the evolutionary model and suggest that the added eukaryotic domains arose in response to distinctive selective pressures associated with the greater complexity of the eukaryotic translational apparatus. We also find that the affinity of GluRS for glutamate is significantly increased when Arc1p is not associated with the enzyme. This is consistent with the lower concentration of intracellular glutamate and the dissociation of the Arc1p:GluRS complex upon the diauxic shift to respiratory conditions.     

Use of guilds for modelling avian responses to vegetation in the Intermountain West (USA)

Aim Individually focused conservation management of many species is expensive and logistically impractical. Mesofilter conservation methods may facilitate the simultaneous management of multiple species. We used data on distributions of two sets of avian guilds, based on dependence on riparian vegetation and on nest location, to relate occurrence rates to environmental variables. Variables were selected by expert opinion and are likely to be affected by changes in climate and land use. Location Data were collected from 2001–06 in four adjacent mountain ranges in the central Great Basin (Lander, Nye and Eureka counties, Nevada, USA): the Shoshone Mountains and the Toiyabe, Toquima and Monitor ranges. Methods Data on occurrence of birds, vegetation composition and vegetation structure were obtained in the field. Geographical coordinates and the normalized difference vegetation index were derived from a digital elevation model and a satellite image. To construct a general model for guilds as a whole, while allowing flexibility for variation in the functional responses of individual species, we applied multivariate adaptive regression splines. Results The predictive capacity of expert knowledge of relationships between birds and vegetation was inconsistent. Latitude, longitude and elevation may constrain the response of some guilds to changes in vegetation structure and composition. Guild‐based models were useful for modelling species with sparse distributions, which are difficult to model individually. In essence, this method supplements models for the individual species with patterns for the guild to which they belong. Main conclusions Guilds of birds appeared to have predictable associations with selected attributes of vegetation structure and composition. The criteria by which species are grouped into guilds may affect the success of predictions and management interventions. Our derived models offer the potential to predict effects on the avifauna of management or climate‐driven change in vegetation.