Analysis of heterologous interacting systems by sedimentation velocity: curve fitting algorithms for estimation of sedimentation coefficients, equilibrium and kinetic constants

Analytical ultracentrifugation (AUC) has played and will continue to play an important role in the investigation of protein-protein, protein-DNA and protein-ligand interactions. A major advantage of AUC over other methods is that it allows the analysis of systems free in solution in nearly any buffer without worry about spurious interactions with a supporting matrix. Large amounts of high-quality data can be acquired in relatively short times. Advances in software for the treatment of AUC data over the last decade have eliminated many of the tedious aspects of AUC data analysis, allowing relatively rapid analysis of complicated systems that were previously unapproachable. A software package called sedanal is described that can perform global fits to AUC sedimentation velocity data obtained for both interacting and non-interacting, macromolecular multi-species, multi-component systems, by combining data from multiple runs over a range of sample concentrations and component ratios. Interaction parameters include both forward and reverse rate constants, or equilibrium constants, for each reaction, as well as concentration dependence of both sedimentation and diffusion coefficients. sedanal fits to time-difference data to eliminate time-independent systematic errors inherent in AUC data. The sedanal software package is based on the use of finite-element numerical solutions of the Lamm equation.     

A conserved role for retinoid signaling in vertebrate pancreas development

Retinoic acid (RA) signaling plays critical roles in the regionalization of the central nervous system and mesoderm of all vertebrates that have been examined. However, to date, a role for RA in pancreas and liver development has only been demonstrated for the teleost zebrafish. Here, we demonstrate that RA signaling is required for development of the pancreas but not the liver in the amphibian Xenopus laevis and the avian quail. We disrupted RA signaling in Xenopus tadpoles, using both a pharmacological and a dominant-negative strategy. RA-deficient quail embryos were obtained from hens with a dietary deficiency in vitamin A. In both species we found that pancreas development was dependent on RA signaling. Furthermore, treatment of Xenopus tadpoles with exogenous RA led to an expansion of the pancreatic field. By contrast, liver development was not perturbed by manipulation of RA signaling. Taken together with our previous finding that RA signaling is necessary and sufficient for zebrafish pancreas development, these data support the hypothesis that a critical role for RA signaling in pancreas development is a conserved feature of the vertebrates.     

Hypersulfated low molecular weight heparin with reduced affinity for antithrombin acts as an anticoagulant by inhibiting intrinsic tenase and prothrombinase

In buffer systems, heparin and low molecular weight heparin (LMWH) directly inhibit the intrinsic factor X-activating complex (intrinsic tenase) but have no effect on the prothrombin-activating complex (prothrombinase). Although chemical modification of LMWH, to lower its affinity for antithrombin (LA-LMWH) has no effect on its ability to inhibit intrinsic tenase, N-desulfation of LMWH reduces its activity 12-fold. To further explore the role of sulfation, hypersulfated LA-LMWH was synthesized (sLA-LMWH). sLA-LMWH is not only a 32-fold more potent inhibitor of intrinsic tenase than LA-LMWH; it also acquires prothrombinase inhibitory activity. A direct correlation between the extent of sulfation of LA-LMWH and its inhibitory activity against intrinsic tenase and prothrombinase is observed. In plasma-based assays of tenase and prothrombinase, sLA-LMWH produces similar prolongation of clotting times in plasma depleted of antithrombin and/or heparin cofactor II as it does in control plasma. In contrast, heparin has no effect in antithrombin-depleted plasma. When the effect of sLA-LMWH on various components of tenase and prothrombinase was examined, its inhibitory activity was found to be cofactor-dependent (factors Va and VIIIa) and phospholipid-independent. These studies reveal that sLA-LMWH acts as a potent antithrombin-independent inhibitor of coagulation by attenuating intrinsic tenase and prothrombinase.     

Wetland food resources for spring-migrating ducks in the Upper Mississippi River and Great Lakes Region

Wetlands in the Upper Mississippi River and Great Lakes Region (UMRGLR) must annually sustain populations of migrating waterfowl from the mid-continent of North America. We used multi-stage sampling to estimate plant and invertebrate food biomasses (kg/ha) for ducks in 3 wetland habitat types at 6 stop-over locations in the UMRGLR during 2006 and 2007. Total biomass was greatest in palustrine emergent (PEM; = 208 kg/ha, SE = 23, median = 120), followed by palustrine forested (PF; = 87 kg/ha, SE = 7; median = 43), and lacustrine–riverine (LR; = 52 kg/ha, SE = 7; median = 27) wetlands. Ducks that foraged in forested and LR wetlands encountered the least food abundance during spring in the UMRGLR. Our estimates of food abundance were the lowest reported among other landscape scale surveys from mid-continent North America. About 1 in every 5 PEM wetlands and over half of our PF and LR wetlands that we sampled contained <50 kg/ha of food, suggesting many had little or no forage value to ducks during spring. Biomass of plant foods generally exceeded invertebrate biomass in all habitat types, although invertebrate biomass estimates exceeded plant biomass in 8 of 29 sites when considered by wetland type and year. Total food biomass estimates varied widely ( = 6–425 kg/ha) between years and among habitats; thus, using global arithmetic means to estimate food abundance for conservation planning obscures fine scale temporal and spatial variation that may be necessary for management on local and sub-regional levels. Distributions of food biomass estimates were right-skewed, causing us to question whether arithmetic means realistically represent levels of food abundance that all ducks encounter during spring migration. Alternative measures of central tendency (e.g., median) may be more biologically realistic, particularly if spring-migrating ducks are not distributed in an ideal-free manner with respect to food abundance. Future research should determine how ducks distribute themselves in relation to variation in food abundance in space and time during spring migration to strengthen the biological approach to conservation planning in non-breeding Joint Venture areas of the North American Waterfowl Management Plan. © 2011 The Wildlife Society.     

Proteomic analysis of a pleistocene mammoth femur reveals more than one hundred ancient bone proteins

We used high-sensitivity, high-resolution tandem mass spectrometry to shotgun sequence ancient protein remains extracted from a 43?000 year old woolly mammoth ( Mammuthus primigenius ) bone preserved in the Siberian permafrost. For the first time, 126 unique protein accessions, mostly low-abundance extracellular matrix and plasma proteins, were confidently identified by solid molecular evidence. Among the best characterized was the carrier protein serum albumin, presenting two single amino acid substitutions compared to extant African ( Loxodonta africana ) and Indian ( Elephas maximus ) elephants. Strong evidence was observed of amino acid modifications due to post-mortem hydrolytic and oxidative damage. A consistent subset of this permafrost bone proteome was also identified in more recent Columbian mammoth ( Mammuthus columbi ) samples from temperate latitudes, extending the potential of the approach described beyond subpolar environments. Mass spectrometry-based ancient protein sequencing offers new perspectives for future molecular phylogenetic inference and physiological studies on samples not amenable to ancient DNA investigation. This approach therefore represents a further step into the ongoing integration of different high-throughput technologies for identification of ancient biomolecules, unleashing the field of paleoproteomics.     

A unified multitask architecture for predicting local protein properties

A variety of functionally important protein properties, such as secondary structure, transmembrane topology and solvent accessibility, can be encoded as a labeling of amino acids. Indeed, the prediction of such properties from the primary amino acid sequence is one of the core projects of computational biology. Accordingly, a panoply of approaches have been developed for predicting such properties; however, most such approaches focus on solving a single task at a time. Motivated by recent, successful work in natural language processing, we propose to use multitask learning to train a single, joint model that exploits the dependencies among these various labeling tasks. We describe a deep neural network architecture that, given a protein sequence, outputs a host of predicted local properties, including secondary structure, solvent accessibility, transmembrane topology, signal peptides and DNA-binding residues. The network is trained jointly on all these tasks in a supervised fashion, augmented with a novel form of semi-supervised learning in which the model is trained to distinguish between local patterns from natural and synthetic protein sequences. The task-independent architecture of the network obviates the need for task-specific feature engineering. We demonstrate that, for all of the tasks that we considered, our approach leads to statistically significant improvements in performance, relative to a single task neural network approach, and that the resulting model achieves state-of-the-art performance.