Automated protein resonance assignments of magic angle spinning solid-state NMR spectra of β1 immunoglobulin binding domain of protein G (GB1)

Magic-angle spinning solid-state NMR (MAS SSNMR) represents a fast developing experimental technique with great potential to provide structural and dynamics information for proteins not amenable to other methods. However, few automated analysis tools are currently available for MAS SSNMR. We present a methodology for automating protein resonance assignments of MAS SSNMR spectral data and its application to experimental peak lists of the β1 immunoglobulin binding domain of protein G (GB1) derived from a uniformly 13C- and 15N-labeled sample. This application to the 56 amino acid GB1 produced an overall 84.1% assignment of the N, CO, CA, and CB resonances with no errors using peak lists from NCACX 3D, CANcoCA 3D, and CANCOCX 4D experiments. This proof of concept demonstrates the tractability of this problem

Global Diversity of the Stylasteridae (Cnidaria: Hydrozoa: Athecatae)

The history and rate of discovery of the 247 valid Recent stylasterid species are discussed and graphed, with emphasis on five historical pulses of species descriptions. A table listing all genera, their species numbers, and their bathymetric ranges are presented. The number of species in 19 oceanographic regions is mapped, the southwestern temperate Pacific (region including New Zealand) having the most species; species are cosmopolitan from the Arctic Circle to the Antarctic at depths from 0 to 2789 m. The current phylogenetic classification of the genera is briefly discussed. An illustrated glossary of 53 morphological characters is presented. Biological and ecological information pertaining to reproduction, development, commensals, and distribution is discussed. Aspects of stylasterid mineralogy and taxa of commercial value are discussed, concluding with suggestions for future work

Sexual Size Dimorphism and Body Condition in the Australasian Gannet

Funding: The research was financially supported by the Holsworth Wildlife Research Endowment. Acknowledgments We thank the Victorian Marine Science Consortium, Sea All Dolphin Swim, Parks Victoria, and the Point Danger Management Committee for logistical support. We are grateful for the assistance of the many field volunteers involved in the study.Peer reviewedPublisher PD

Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR

ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [13C,15N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches

Robust structure-based resonance assignment for functional protein studies by NMR

High-throughput functional protein NMR studies, like protein interactions or dynamics, require an automated approach for the assignment of the protein backbone. With the availability of a growing number of protein 3D structures, a new class of automated approaches, called structure-based assignment, has been developed quite recently. Structure-based approaches use primarily NMR input data that are not based on J-coupling and for which connections between residues are not limited by through bonds magnetization transfer efficiency. We present here a robust structure-based assignment approach using mainly HN–HN NOEs networks, as well as 1H–15N residual dipolar couplings and chemical shifts. The NOEnet complete search algorithm is robust against assignment errors, even for sparse input data. Instead of a unique and partly erroneous assignment solution, an optimal assignment ensemble with an accuracy equal or near to 100% is given by NOEnet. We show that even low precision assignment ensembles give enough information for functional studies, like modeling of protein-complexes. Finally, the combination of NOEnet with a low number of ambiguous J-coupling sequential connectivities yields a high precision assignment ensemble. NOEnet will be available under: http://www.icsn.cnrs-gif.fr/download/nmr

Probabilistic Interaction Network of Evidence Algorithm and its Application to Complete Labeling of Peak Lists from Protein NMR Spectroscopy

The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination

Fully automated high-quality NMR structure determination of small 2H-enriched proteins

Determination of high-quality small protein structures by nuclear magnetic resonance (NMR) methods generally requires acquisition and analysis of an extensive set of structural constraints. The process generally demands extensive backbone and sidechain resonance assignments, and weeks or even months of data collection and interpretation. Here we demonstrate rapid and high-quality protein NMR structure generation using CS-Rosetta with a perdeuterated protein sample made at a significantly reduced cost using new bacterial culture condensation methods. Our strategy provides the basis for a high-throughput approach for routine, rapid, high-quality structure determination of small proteins. As an example, we demonstrate the determination of a high-quality 3D structure of a small 8 kDa protein, E. coli cold shock protein A (CspA), using <4 days of data collection and fully automated data analysis methods together with CS-Rosetta. The resulting CspA structure is highly converged and in excellent agreement with the published crystal structure, with a backbone RMSD value of 0.5 Å, an all atom RMSD value of 1.2 Å to the crystal structure for well-defined regions, and RMSD value of 1.1 Å to crystal structure for core, non-solvent exposed sidechain atoms. Cross validation of the structure with 15N- and 13C-edited NOESY data obtained with a perdeuterated 15N, 13C-enriched 13CH3 methyl protonated CspA sample confirms that essentially all of these independently-interpreted NOE-based constraints are already satisfied in each of the 10 CS-Rosetta structures. By these criteria, the CS-Rosetta structure generated by fully automated analysis of data for a perdeuterated sample provides an accurate structure of CspA. This represents a general approach for rapid, automated structure determination of small proteins by NMR

From Offshore to Onshore: Multiple Origins of Shallow-Water Corals from Deep-Sea Ancestors

Shallow-water tropical reefs and the deep sea represent the two most diverse marine environments. Understanding the origin and diversification of this biodiversity is a major quest in ecology and evolution. The most prominent and well-supported explanation, articulated since the first explorations of the deep sea, holds that benthic marine fauna originated in shallow, onshore environments, and diversified into deeper waters. In contrast, evidence that groups of marine organisms originated in the deep sea is limited, and the possibility that deep-water taxa have contributed to the formation of shallow-water communities remains untested with phylogenetic methods. Here we show that stylasterid corals (Cnidaria: Hydrozoa: Stylasteridae)—the second most diverse group of hard corals—originated and diversified extensively in the deep sea, and subsequently invaded shallow waters. Our phylogenetic results show that deep-water stylasterid corals have invaded the shallow-water tropics three times, with one additional invasion of the shallow-water temperate zone. Our results also show that anti-predatory innovations arose in the deep sea, but were not involved in the shallow-water invasions. These findings are the first robust evidence that an important group of tropical shallow-water marine animals evolved from deep-water ancestors

Effect of eplerenone on parathyroid hormone levels in patients with primary hyperparathyroidism: a randomized, double-blind, placebo-controlled trial

<p>Abstract</p> <p>Background</p> <p>Increasing evidence suggests the bidirectional interplay between parathyroid hormone and aldosterone as an important mechanism behind the increased risk of cardiovascular damage and bone disease observed in primary hyperparathyroidism. Our primary object is to assess the efficacy of the mineralocorticoid receptor-blocker eplerenone to reduce parathyroid hormone secretion in patients with parathyroid hormone excess.</p> <p>Methods/design</p> <p>Overall, 110 adult male and female patients with primary hyperparathyroidism will be randomly assigned to eplerenone (25 mg once daily for 4 weeks and 4 weeks with 50 mg once daily after dose titration] or placebo, over eight weeks. Each participant will undergo detailed clinical assessment, including anthropometric evaluation, 24-h ambulatory arterial blood pressure monitoring, echocardiography, kidney function and detailed laboratory determination of biomarkers of bone metabolism and cardiovascular disease.</p> <p>The study comprises the following exploratory endpoints: mean change from baseline to week eight in (1) parathyroid hormone(1–84) as the primary endpoint and (2) 24-h systolic and diastolic ambulatory blood pressure levels, NT-pro-BNP, biomarkers of bone metabolism, 24-h urinary protein/albumin excretion and echocardiographic parameters reflecting systolic and diastolic function as well as cardiac dimensions, as secondary endpoints.</p> <p>Discussion</p> <p>In view of the reciprocal interaction between aldosterone and parathyroid hormone and the potentially ensuing target organ damage, the EPATH trial is designed to determine whether eplerenone, compared to placebo, will effectively impact on parathyroid hormone secretion and improve cardiovascular, renal and bone health in patients with primary hyperparathyroidism.</p> <p>Trial registration</p> <p>ISRCTN33941607</p

Charting Evolution’s Trajectory: Using Molluscan Eye Diversity to Understand Parallel and Convergent Evolution

For over 100 years, molluscan eyes have been used as an example of convergent evolution and, more recently, as a textbook example of stepwise evolution of a complex lens eye via natural selection. Yet, little is known about the underlying mechanisms that create the eye and generate different morphologies. Assessing molluscan eye diversity and understanding how this diversity came about will be important to developing meaningful interpretations of evolutionary processes. This paper provides an introduction to the myriad of eye types found in molluscs, focusing on some of the more unusual structures. We discuss how molluscan eyes can be applied to the study of evolution by examining patterns of convergent and parallel evolution and provide several examples, including the putative convergence of the camera-type eyes of cephalopods and vertebrates