Identification of mammalian mitochondrial proteins that interact with IAPs via N-terminal IAP binding motifs

Direct IAP binding protein with low pI/second mitochondrial activator of caspases, HtrA2/Omi and GstPT/eRF3 are mammalian proteins that bind via N-terminal inhibitor of apoptosis protein (IAP) binding motifs (IBMs) to the baculoviral IAP repeat (BIR) domains of IAPs. These interactions can prevent IAPs from inhibiting caspases, or displace active caspases, thereby promoting cell death. We have identified several additional potential IAP antagonists, including glutamate dehydrogenase (GdH), Nipsnap 3 and 4, CLPX, leucine-rich pentatricopeptide repeat motif-containing protein and 3-hydroxyisobutyrate dehydrogenase. All are mitochondrial proteins from which N-terminal import sequences are removed generating N-terminal IBMs. Whereas most of these proteins have alanine at the N-terminal position, as observed for previously described antagonists, GdH has an N-terminal serine residue that is essential for X-linked IAP (XIAP) interaction. These newly described IAP binding proteins interact with XIAP mainly via BIR2, with binding eliminated or significantly reduced by a single point mutation (D214S) within this domain. Through this interaction, many are able to antagonise XIAP inhibition of caspase 3 in vitro.     

Exploration of structure-antifouling relationships of capsaicin-like compounds that inhibit zebra mussel (Dreissena polymorpha) macrofouling

Macrofouling of aquatic man-made structures by zebra mussels (Dreissena polymorpha) poses significant economic burdens on commercial freshwater shipping and facilities utilising raw water. The negative environmental impact of some current antifouling technologies has limited their use and prompted investigation of non-organometallic and non-oxidising antifoulants as possible environment-friendly alternatives. The plant-derived natural product capsaicin and 18 other compounds with one or more capsaicin-like structural features were tested for their potential to inhibit zebra mussel byssal attachment at a single high concentration of 30 microM. Of these, three compounds displaying the highest levels of attachment inhibition where selected for further concentration-response testing. This testing revealed that capsaicin (8-methyl-N-vanillyl-trans-6-nonenamide), N-vanillylnonanamide, and N-benzoylmonoethanolamine benzoate all inhibited byssal attachment with potency values (EC(50)) in the micromolar range. None of these compounds were lethal to adult specimens of the water flea, Daphnia magna, at concentrations that inhibited mussel byssal attachment.     

Range maps and species richness patterns: errors of commission and estimates of uncertainty

Range maps are often combined into “range overlap maps” to estimate spatial variation in species richness. Range maps are, in most cases, designed to represent a species’ maximum geographical extent and not patterns of occupancy within the range. As a consequence, range maps overestimate occupancy by presenting false occupancy (errors of commission) within the interior of the range. To assess the implications of errors of commission when developing and applying range overlap maps, we used neutral landscapes to simulate range maps and patterns of occupancy within ranges. We explored several scenarios based on combinations of six parameters defining biogeographical and cartographic factors typically encountered by investigators. Our results suggest that, in general, uncertainty is lowest when map resolutions are moderately fine, the majority of species have geographically restricted ranges, species occur throughout their range, patterns of occupancy within the range are not correlated among species, and geographically local and widespread species tend to occupy different regions. Several of these outcomes are associated with broad geographical extents, the scale at which range overlap maps are typically applied. Thus, under most circumstances, reasonably accurate and precise representation of species richness patterns can be achieved. However, these representations can be improved by enhancing occupancy data for widespread species – a primary source of uncertainty – and selecting a map resolution that captures relevant biological and environmental heterogeneity. Hence, by determining where a study is situated within the scenarios examined in our simulations, uncertainty and its sources and implications can be ascertained. With this knowledge, research goals, methods, and data sources can be reassessed and refined and, in the end, conclusions and recommendations can be qualified. Alternatively, unique regional, taxonomic, or cartographic factors could be included in future simulations to provide direct assessments of uncertainty.     

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

RIVPACS models produce a community-level measure of biological condition known as O/E, which is derived from a comparison of the observed (O) biota with those expected (E) to occur in the absence of anthropogenic stress. We used benthic macroinvertebrate and environmental data collected at 925 stream monitoring stations, from 1993 to 2001, to develop, validate, and apply a RIVPACS model to assess the biological condition of wadeable streams in Wyoming. From this dataset, 296 samples were identified as reference, 157 of which were used to calibrate the model, 46 to validate it, and 93 to examine temporal variability in reference site O/E-values. We used cluster analyses to group the model development reference sites into biologically similar classes of streams and multiple discriminant function analysis to determine which environmental variables best discriminated among reference groups. A suite of 14 categorical and continuous environmental variables best discriminated among 15 reference groups and explained a large proportion of the natural variability in biota within the reference dataset. Eleven of the predictor variables were derived from GIS. As expected, mean O/E-values for reference sites used in model development and validation were near unity and statistically similar. Temporal variability in O/E-values for reference sites was low. Test site values ranged from 0 to 1.45 (mean = 0.73). The model was accurate in both space and time and precise enough (S.D. of O/E-values for calibration data = 0.17) to detect modest alteration in biota associated with anthropogenic stressors. Our model was comparable in performance to other RIVPACS models developed in the United States and can produce effective assessments of biological condition over a broad, ecologically diverse region. We also provide convincing evidence that RIVPACS models can be developed primarily with GIS-based predictor variables. This framework not only simplifies the extraction of predictor variable information while potentially reducing expenditures of time and money in the collection of predictor variable information, but opens the door for development and/or application of RIVPACS models in regions where there is a paucity of local-scale, abiotic information.     

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.     

Individualistic species limitations of climate‐induced range expansions generated by meso‐scale dispersal barriers

Aim Evidence indicates that species are responding to climate change through distributional range shifts that track suitable climatic conditions. We aim to elucidate the role of meso‐scale dispersal barriers in climate‐tracking responses. Location South coast of England (the English Channel). Methods Historical distributional data of four intertidal invertebrate species were logistically regressed against sea surface temperature (SST) to determine a climate envelope. This envelope was used to estimate the expected climate‐tracking response since 1990 along the coast, which was compared with observed range expansions. A hydrodynamic modelling approach was used to identify dispersal barriers and explore disparities between expected and observed climate tracking. Results Range shifts detected by field survey over the past 20 years were less than those predicted by the changes that have occurred in SST. Hydrodynamic model simulations indicated that physical barriers produced by complex tidal currents have variably restricted dispersal of pelagic larvae amongst the four species. Main conclusions We provide the first evidence that meso‐scale hydrodynamic barriers have limited climate‐induced range shifts and demonstrate that life history traits affect the ability of species to overcome such barriers. This suggests that current forecasts may be flawed, both by overestimating range shifts and by underestimating climatic tolerances of species. This has implications for our understanding of climate change impacts on global biodiversity.     

The use of phylogeny to interpret cross-cultural patterns in plant use and guide medicinal plant discovery: an example from Pterocarpus (Leguminosae)

Background

The study of traditional knowledge of medicinal plants has led to discoveries that have helped combat diseases and improve healthcare. However, the development of quantitative measures that can assist our quest for new medicinal plants has not greatly advanced in recent years. Phylogenetic tools have entered many scientific fields in the last two decades to provide explanatory power, but have been overlooked in ethnomedicinal studies. Several studies show that medicinal properties are not randomly distributed in plant phylogenies, suggesting that phylogeny shapes ethnobotanical use. Nevertheless, empirical studies that explicitly combine ethnobotanical and phylogenetic information are scarce.

Methodology/Principal Findings

In this study, we borrowed tools from community ecology phylogenetics to quantify significance of phylogenetic signal in medicinal properties in plants and identify nodes on phylogenies with high bioscreening potential. To do this, we produced an ethnomedicinal review from extensive literature research and a multi-locus phylogenetic hypothesis for the pantropical genus Pterocarpus (Leguminosae: Papilionoideae). We demonstrate that species used to treat a certain conditions, such as malaria, are significantly phylogenetically clumped and we highlight nodes in the phylogeny that are significantly overabundant in species used to treat certain conditions. These cross-cultural patterns in ethnomedicinal usage in Pterocarpus are interpreted in the light of phylogenetic relationships.

Conclusions/Significance

This study provides techniques that enable the application of phylogenies in bioscreening, but also sheds light on the processes that shape cross-cultural ethnomedicinal patterns. This community phylogenetic approach demonstrates that similar ethnobotanical uses can arise in parallel in different areas where related plants are available. With a vast amount of ethnomedicinal and phylogenetic information available, we predict that this field, after further refinement of the techniques, will expand into similar research areas, such as pest management or the search for bioactive plant-based compounds.