A data management system for structural genomics

Background  

Structural genomics (SG) projects aim to determine thousands of protein structures by the development of high-throughput techniques for all steps of the experimental structure determination pipeline. Crucial to the success of such endeavours is the careful tracking and archiving of experimental and external data on protein targets.     

Genetic tailoring of N-linked oligosaccharides: the role of glucose residues in glycoprotein processing of Saccharomyces cerevisiae in vivo

In higher eukaryotes a quality control system monitoring the folding state of glycoproteins is located in the ER and is composed of the proteins calnexin, calreticulin, glucosidase II, and UDP-glucose: glycoprotein glucosyltransferase. It is believed that the innermost glucose residue of the N- linked oligosaccharide of a glycoprotein serves as a tag in this control system and therefore performs an important function in the protein folding pathway. To address this function, we constructed Saccharomyces cerevisiae strains which contain nonglucosylated (G0), monoglucosylated (G1), or diglucosylated (G2) glycoproteins in the ER and used these strains to study the role of glucose residues in the ER processing of glycoproteins. These alterations of the oligosaccharide structure did not result in a growth phenotype, but the induction of the unfolded protein response upon treatment with DTT was much higher in G0 and G2 strains as compared to wild-type and G1 strains. Our results provide in vivo evidence that the G1 oligosaccharide is an active oligosaccharide structure in the ER glycoprotein processing pathway of S.cerevisiae. Furthermore, by analyzing N- linked oligosaccharides of the constructed strains we can directly show that no general glycoprotein glucosyltransferase exists in S. cerevisiae.      

Validated predictive modelling of the environmental resistome

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.     

Estimating Orangutan Densities Using the Standing Crop and Marked Nest Count Methods: Lessons Learned for Conservation

Reliable estimates of great ape abundance are needed to assess distribution, monitor population status, evaluate conservation tactics, and identify priority populations for conservation. Rather than using direct counts, surveyors often count ape nests. The standing crop nest count (SCNC) method converts the standing stock of nests into animal densities using a set of parameters, including nest decay rate. Nest decay rates vary greatly over space and time, and it takes months to calculate a site-specific value. The marked nest count (MNC) method circumvents this issue and only counts new nests produced during a defined period. We compared orangutan densities calculated by the two methods using data from studies in Sumatra and Kalimantan, Indonesia. We show how animal densities calculated using nest counts should be cautiously interpreted when used to make decisions about management or budget allocation. Even with site-specific decay rates, short studies using the SCNC method may not accurately reflect the current population unless conducted at a scale sufficient to include wide-ranging orangutan movement. Density estimates from short studies using the MNC method were affected by small sample sizes and by orangutan movement. To produce reliable results, the MNC method may require a similar amount of effort as the SCNC method. We suggest a reduced reliance on the traditional line transect surveys in favor of feasible alternative methods when absolute abundance numbers are not necessary or when site-specific nest decay rates are not known. Given funding constraints, aerial surveys, reconnaissance walks, and interview techniques may be more cost-effective means of accomplishing some survey goals.     

Predicting patch occupancy in fragmented landscapes at the rangewide scale for an endangered species: an example of an American warbler

AIM: Our objective was to identify the distribution of the endangered golden-cheeked warbler (Setophaga chrysoparia) in fragmented oak-juniper woodlands by applying a geoadditive semiparametric occupancy model to better assist decision-makers in identifying suitable habitat across the species breeding range on which conservation or mitigation activities can be focused and thus prioritize management and conservation planning. LOCATION: Texas, USA. METHODS: We used repeated double-observer detection/non-detection surveys of randomly selected (n = 287) patches of potential habitat to evaluate warbler patch-scale presence across the species breeding range. We used a geoadditive semiparametric occupancy model with remotely sensed habitat metrics (patch size and landscape composition) to predict patch-scale occupancy of golden-cheeked warblers in the fragmented oak-juniper woodlands of central Texas, USA. RESULTS: Our spatially explicit model indicated that golden-cheeked warbler patch occupancy declined from south to north within the breeding range concomitant with reductions in the availability of large habitat patches. We found that 59% of woodland patches, primarily in the northern and central portions of the warbler's range, were predicted to have occupancy probabilities ≤0.10 with only 3% of patches predicted to have occupancy probabilities >0.90. Our model exhibited high prediction accuracy (area under curve = 0.91) when validated using independently collected warbler occurrence data. MAIN CONCLUSIONS: We have identified a distinct spatial occurrence gradient for golden-cheeked warblers as well as a relationship between two measurable landscape characteristics. Because habitat-occupancy relationships were key drivers of our model, our results can be used to identify potential areas where conservation actions supporting habitat mitigation can occur and identify areas where conservation of future potential habitat is possible. Additionally, our results can be used to focus resources on maintenance and creation of patches that are more likely to harbour viable local warbler populations.     

Induction of iNOS restricts functional activity of both eNOS and nNOS in pig cerebral artery

The aim of the study was to investigate the effect of iNOS expression on eNOS and nNOS functional activity in porcine cerebral arteries. iNOS was induced in pig basilar arteries using lipopolysaccharide (LPS). Arteries expressing iNOS generated NO and relaxed when challenged with L-arginine (30 microM), an effect that was reduced by treatment with dexamethasone (coincubated with LPS) and prevented by the iNOS inhibitor 1400 W (administered 10 min prior to precontraction). eNOS was activated by A23187 and was found to be impaired in arteries that had iNOS induced (A23187 1 microM relaxation: control 110+/-8%, LPS-treated 50+/-16% ; p<0.05, N=5-6). This was due mainly to reduced formation of NO by A23187 (NO concentration in response to A23187 1 microM: control 25+/-6 nM, LPS-treated 0.8+/-1.2 nM; p<0.001, N=5-6), in addition to a small reduction in the vasodilator response to the NO-donors NOC-22 and SIN-1. Cerebral vasodilation produced by stimulation of intramural nitrergic nerves was impaired in arteries that had iNOS induced, and this was reversed by 1400 W (control 23+/-4% relaxation, LPS-treated 11+/-1% relaxation, LPS plus 1400 W 10 microM treated 25+/-2% relaxation; p<0.01 for control versus LPS, N=6). It is concluded that the induction of iNOS in cerebral arteries reduces NO-mediated vasodilation initiated by eNOS and by nNOS, primarily by modulation of NO formation.