Structure and Activity of the Peptidyl-Prolyl Isomerase Domain from the Histone Chaperone Fpr4 toward Histone H3 Proline Isomerization

The FK506-binding protein (FKBP) family of peptidyl-prolyl isomerases (PPIases) is characterized by a common catalytic domain that binds to the inhibitors FK506 and rapamycin. As one of four FKBPs within the yeast Saccharomyces cerevisiae, Fpr4 has been described as a histone chaperone, and is in addition implicated in epigenetic function in part due to its mediation of cis-trans conversion of proline residues within histone tails. To better understand the molecular details of this activity, we have determined the solution structure of the Fpr4 C-terminal PPIase domain by using NMR spectroscopy. This canonical FKBP domain actively increases the rate of isomerization of three decapeptides derived from the N terminus of yeast histone H3, whereas maintaining intrinsic cis and trans populations. Observation of the uncatalyzed and Fpr4-catalyzed isomerization rates at equilibrium demonstrate Pro¹⁶ and Pro³⁰ of histone H3 as the major proline targets of Fpr4, with little activity shown against Pro³⁸. This alternate ranking of the three target prolines, as compared with affinity determination or the classical chymotrypsin-based fluorescent assay, reveals the mechanistic importance of substrate residues C-terminal to the peptidyl-prolyl bond.     

Multi‐model comparison highlights consistency in predicted effect of warming on a semi‐arid shrub

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi‐model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi‐model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.     

Managing for multiple species: greater sage-grouse and sagebrush songbirds

Human activity has altered 33–50% of Earth's surface, including temperate grasslands and sagebrush rangelands, resulting in a loss of biodiversity. By promoting habitat for sensitive or wide-ranging species, less exigent species may be protected in an umbrella effect. The greater sage-grouse (Centrocercus urophasianus; sage-grouse) has been proposed as an umbrella for other sagebrush-obligate species because it has an extensive range that overlaps with many other species, it is sensitive to anthropogenic activity, it requires resources over large landscapes, and its habitat needs are known. The efficacy of the umbrella concept, however, is often assumed and rarely tested. Therefore, we surveyed sage-grouse pellet occurrence and sagebrush-associated songbird abundance in northwest Colorado, USA, to determine the amount of habitat overlap between sage-grouse and 4 songbirds (Brewer's sparrow [Spizella breweri], sage thrasher [Oreoscoptes montanus], sagebrush sparrow [Artemisiospiza nevadensis]), and green-tailed towhee [Pipilo chlorurus]). During May and June 2013–2015, we conducted standard point count breeding surveys for songbirds and counted sage-grouse pellets within 300 10-m radius plots. We modeled songbird abundance and sage-grouse pellet occurrence with multi-scaled environmental features, such as sagebrush cover and bare ground. To evaluate sage-grouse as an umbrella for sagebrush-associated passerines, we determined the correlation between probability of sage-grouse pellet occurrence and model-predicted songbird densities per sampling plot. We then classified the sage-grouse probability of occurrence as high (probability >0.5) and low (probability ≤0.5) and mapped model-predicted surfaces for each species in our study area. We determined average songbird density in areas of high and low probability of sage-grouse occurrence. Sagebrush cover at intermediate scales was an important predictor for all species, and ground cover was important for all species except sage thrashers. Areas with a higher probability of sage-grouse occurrence also contained higher densities of Brewer's sparrows, green-tailed towhees, and sage thrashers, but predicted sagebrush sparrow densities were lower in these areas. In northwest Colorado, sage-grouse may be an effective umbrella for Brewer's sparrows, green-tailed towhees, and sage thrashers, but sage-grouse habitat does not appear to capture areas that support high sagebrush sparrow densities. A multi-species focus may be the best management and conservation strategy for several species of concern, especially those with conflicting habitat requirements. © The Wildlife Society, 2019     

Proteomics of Colwellia psychrerythraea at subzero temperatures – a life with limited movement,flexible membranes and vital DNA repair

The mechanisms that allow psychrophilic bacteria to remain metabolically active at subzero temperatures result from form and function of their proteins. We present first proteomic evidence of physiological changes of the marine psychrophile Colwellia psychrerythraea 34H (Cp34H) after exposure to subzero temperatures (?1, and ?10°C in ice) through 8 weeks. Protein abundance was compared between different treatments to understand the effects of temperature and time, independently and jointly, within cells transitioning to, and being maintained in ice. Parallel [3H]‐leucine and [3H]–thymidine incubations indicated active protein and DNA synthesis to ?10°C. Mass spectrometry‐based proteomics identified 1763 proteins across four experimental treatments. Proteins involved in osmolyte regulation and polymer secretion were found constitutively present across all treatments, suggesting that they are required for metabolic success below 0°C. Differentially abundant protein groups indicated a reallocation of resources from DNA binding to DNA repair and from motility to chemo‐taxis and sensing. Changes to iron and nitrogen metabolism, cellular membrane structures, and protein synthesis and folding were also revealed. By elucidating vital strategies during life in ice, this study provides novel insight into the extensive molecular adaptations that occur in cold‐adapted marine organisms to sustain cellular function in their habitat.     

Conservation in a cup of water: estimating biodiversity and population abundance from environmental DNA

Three mantras often guide species and ecosystem management: (i) for preventing invasions by harmful species, ‘early detection and rapid response’; (ii) for conserving imperilled native species, ‘protection of biodiversity hotspots’; and (iii) for assessing biosecurity risk, ‘an ounce of prevention equals a pound of cure.’ However, these and other management goals are elusive when traditional sampling tools (e.g. netting, traps, electrofishing, visual surveys) have poor detection limits, are too slow or are not feasible. One visionary solution is to use an organism’s DNA in the environment (eDNA), rather than the organism itself, as the target of detection. In this issue of Molecular Ecology, Thomsen et al. (2012) provide new evidence demonstrating the feasibility of this approach, showing that eDNA is an accurate indicator of the presence of an impressively diverse set of six aquatic or amphibious taxa including invertebrates, amphibians, a fish and a mammal in a wide range of freshwater habitats. They are also the first to demonstrate that the abundance of eDNA, as measured by qPCR, correlates positively with population abundance estimated with traditional tools. Finally, Thomsen et al. (2012) demonstrate that next‐generation sequencing of eDNA can quantify species richness. Overall, Thomsen et al. (2012) provide a revolutionary roadmap for using eDNA for detection of species, estimates of relative abundance and quantification of biodiversity.     

Admixture in Mexico City: implications for admixture mapping of Type 2 diabetes genetic risk factors

Admixture mapping is a recently developed method for identifying genetic risk factors involved in complex traits or diseases showing prevalence differences between major continental groups. Type 2 diabetes (T2D) is at least twice as prevalent in Native American populations as in populations of European ancestry, so admixture mapping is well suited to study the genetic basis of this complex disease. We have characterized the admixture proportions in a sample of 286 unrelated T2D patients and 275 controls from Mexico City and we discuss the implications of the results for admixture mapping studies. Admixture proportions were estimated using 69 autosomal ancestry-informative markers (AIMs). Maternal and paternal contributions were estimated from geographically informative mtDNA and Y-specific polymorphisms. The average proportions of Native American, European and, West African admixture were estimated as 65, 30, and 5%, respectively. The contributions of Native American ancestors to maternal and paternal lineages were estimated as 90 and 40%, respectively. In a logistic model with higher educational status as dependent variable, the odds ratio for higher educational status associated with an increase from 0 to 1 in European admixture proportions was 9.4 (95%, credible interval 3.8–22.6). This association of socioeconomic status with individual admixture proportion shows that genetic stratification in this population is paralleled, and possibly maintained, by socioeconomic stratification. The effective number of generations back to unadmixed ancestors was 6.7 (95% CI 5.7–8.0), from which we can estimate that genome-wide admixture mapping will require typing about 1,400 evenly distributed AIMs to localize genes underlying disease risk between populations of European and Native American ancestry. Sample sizes of about 2,000 cases will be required to detect any locus that contributes an ancestry risk ratio of at least 1.5.     

The Urfold: Structural similarity just above the superfold level?

We suspect that there is a level of granularity of protein structure intermediate between the classical levels of “architecture” and “topology,” as reflected in such phenomena as extensive three‐dimensional structural similarity above the level of (super)folds. Here, we examine this notion of architectural identity despite topological variability, starting with a concept that we call the “Urfold.” We believe that this model could offer a new conceptual approach for protein structural analysis and classification: indeed, the Urfold concept may help reconcile various phenomena that have been frequently recognized or debated for years, such as the precise meaning of “significant” structural overlap and the degree of continuity of fold space. More broadly, the role of structural similarity in sequence?structure?function evolution has been studied via many models over the years; by addressing a conceptual gap that we believe exists between the architecture and topology levels of structural classification schemes, the Urfold eventually may help synthesize these models into a generalized, consistent framework. Here, we begin by qualitatively introducing the concept.