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Information is the cornerstone of research, from experimental (meta)data and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems to transform this large information load into useful scientific findings.

To understand the vertical variations in carbon fluxes in biologically productive waters, four autonomous carbon flux explorers (CFEs), ship-lowered CTD-interfaced particle-sensitive transmissometer and scattering sensors, and surface-drogued sediment traps were deployed in a filament of offshore flowing, recently upwelled water, during the June 2017 California Current Ecosystem-Long Term Ecological Research process study. The Lagrangian CFEs operating at depths from 100-500 m yielded carbon flux and its partitioning with size from 30 μ m-1 cm at three intensive study locations within the filament and in waters outside the filament. Size analysis codes intended to enable long-term CFE operations independent of ships are described. Different particle classes (anchovy pellets, copepod pellets, and > 1000 μ m aggregates) dominated the 100-150 m fluxes during successive stages of the filament evolution as it progressed offshore. Fluxes were very high at all locations in the filament; below 150 m, flux was invariant or increased with depth at the two locations closer to the coast. Martin curve bfactors (± denotes 95 % confidence intervals) for total particulate carbon flux were + 0.37 ± 0.59, + 0.85 ± 0.31,-0.24 ± 0.68, and-0.45 ± 0.70 at the three successively occupied locations within the plume, and in transitional waters. Interestingly, the flux profiles for all particles < 400 μ m were a much closer fit to the canonical Martin profile (b-0.86); however, most (typically > 90 %) of the particle flux was carried by > 1000 μ m sized aggregates which increased with depth. Mechanisms to explain the factor of 3 flux increase between 150 and 500 m at the mid-plume location are investigated.

To understand the vertical variations in carbon fluxes in biologically productive waters, four autonomous carbon flux explorers (CFEs), ship-lowered CTD-interfaced particle-sensitive transmissometer and scattering sensors, and surface-drogued sediment traps were deployed in a filament of offshore flowing, recently upwelled water, during the June 2017 California Current Ecosystem-Long Term Ecological Research process study. The Lagrangian CFEs operating at depths from 100-500 m yielded carbon flux and its partitioning with size from 30 μ m-1 cm at three intensive study locations within the filament and in waters outside the filament. Size analysis codes intended to enable long-term CFE operations independent of ships are described. Different particle classes (anchovy pellets, copepod pellets, and > 1000 μ m aggregates) dominated the 100-150 m fluxes during successive stages of the filament evolution as it progressed offshore. Fluxes were very high at all locations in the filament; below 150 m, flux was invariant or increased with depth at the two locations closer to the coast. Martin curve bfactors (± denotes 95 % confidence intervals) for total particulate carbon flux were + 0.37 ± 0.59, + 0.85 ± 0.31,-0.24 ± 0.68, and-0.45 ± 0.70 at the three successively occupied locations within the plume, and in transitional waters. Interestingly, the flux profiles for all particles < 400 μ m were a much closer fit to the canonical Martin profile (b-0.86); however, most (typically > 90 %) of the particle flux was carried by > 1000 μ m sized aggregates which increased with depth. Mechanisms to explain the factor of 3 flux increase between 150 and 500 m at the mid-plume location are investigated.

The proposed deep space exploration to the moon and later to Mars will result in astronauts receiving significant chronic exposures to space radiation (SR). SR exposure results in multiple neurocognitive impairments. Recently, our cross-species (mouse/rat) studies reported impaired associative memory formation in both species following a chronic 6-month low dose exposure to a mixed field of neutrons (1 mGy/day for a total dose pf 18 cGy). In the present study, we report neutron exposure induced synaptic plasticity in the medial prefrontal cortex, accompanied by microglial activation and significant synaptic loss in the hippocampus. In a parallel study, neutron exposure was also found to alter fluorescence assisted single synaptosome LTP (FASS-LTP) in the hippocampus of rats, that may be related to a reduced ability to insert AMPAR into the post-synaptic membrane, which may arise from increased phosphorylation of the serine 845 residue of the GluA1 subunit. Thus, we demonstrate for the first time, that low dose chronic neutron irradiation impacts homeostatic synaptic plasticity in the hippocampal-cortical circuit in two rodent species, and that the ability to successfully encode associative recognition memory is a dynamic, multicircuit process, possibly involving compensatory changes in AMPAR density on the synaptic surface.

Fungi are ecologically outstanding decomposers of lignocellulose. Fungal lignocellulose degradation is prominent in saprotrophic Ascomycota and Basidiomycota of the subkingdom Dikarya. Despite ascomycetes dominating the Dikarya inventory of aquatic environments, genome and transcriptome data relating to enzymes involved in lignocellulose decay remain limited to terrestrial representatives of these phyla. We sequenced the genome of an exclusively aquatic ascomycete (the aquatic hyphomycete Clavariopsis aquatica), documented the presence of genes for the modification of lignocellulose and its constituents, and compared differential gene expression between C. aquatica cultivated on lignocellulosic and sugar-rich substrates. We identified potential peroxidases, laccases, and cytochrome P450 monooxygenases, several of which were differentially expressed when experimentally grown on different substrates. Additionally, we found indications for the regulation of pathways for cellulose and hemicellulose degradation. Our results suggest that C. aquatica is able to modify lignin to some extent, detoxify aromatic lignin constituents, or both. Such characteristics would be expected to facilitate the use of carbohydrate components of lignocellulose as carbon and energy sources.

Although the early coral reef-bleaching warning system (NOAA/USA) is established, there is no feasible treatment that can minimize temperature bleaching and/or disease impacts on corals in the field. Here, we present the first attempts to extrapolate the widespread and well-established use of bacterial consortia to protect or improve health in other organisms (e.g., humans and plants) to corals. Manipulation of the coral-associated microbiome was facilitated through addition of a consortium of native (isolated from Pocillopora damicornis and surrounding seawater) putatively beneficial microorganisms for corals (pBMCs), including five Pseudoalteromonas sp., a Halomonas taeanensis and a Cobetia marina-related species strains. The results from a controlled aquarium experiment in two temperature regimes (26 °C and 30 °C) and four treatments (pBMC; pBMC with pathogen challenge - Vibrio coralliilyticus, VC; pathogen challenge, VC; and control) revealed the ability of the pBMC consortium to partially mitigate coral bleaching. Significantly reduced coral-bleaching metrics were observed in pBMC-inoculated corals, in contrast to controls without pBMC addition, especially challenged corals, which displayed strong bleaching signs as indicated by significantly lower photopigment contents and Fv/Fm ratios. The structure of the coral microbiome community also differed between treatments and specific bioindicators were correlated with corals inoculated with pBMC (e.g., Cobetia sp.) or VC (e.g., Ruegeria sp.). Our results indicate that the microbiome in corals can be manipulated to lessen the effect of bleaching, thus helping to alleviate pathogen and temperature stresses, with the addition of BMCs representing a promising novel approach for minimizing coral mortality in the face of increasing environmental impacts.

Although the early coral reef-bleaching warning system (NOAA/USA) is established, there is no feasible treatment that can minimize temperature bleaching and/or disease impacts on corals in the field. Here, we present the first attempts to extrapolate the widespread and well-established use of bacterial consortia to protect or improve health in other organisms (e.g., humans and plants) to corals. Manipulation of the coral-associated microbiome was facilitated through addition of a consortium of native (isolated from Pocillopora damicornis and surrounding seawater) putatively beneficial microorganisms for corals (pBMCs), including five Pseudoalteromonas sp., a Halomonas taeanensis and a Cobetia marina-related species strains. The results from a controlled aquarium experiment in two temperature regimes (26 °C and 30 °C) and four treatments (pBMC; pBMC with pathogen challenge - Vibrio coralliilyticus, VC; pathogen challenge, VC; and control) revealed the ability of the pBMC consortium to partially mitigate coral bleaching. Significantly reduced coral-bleaching metrics were observed in pBMC-inoculated corals, in contrast to controls without pBMC addition, especially challenged corals, which displayed strong bleaching signs as indicated by significantly lower photopigment contents and Fv/Fm ratios. The structure of the coral microbiome community also differed between treatments and specific bioindicators were correlated with corals inoculated with pBMC (e.g., Cobetia sp.) or VC (e.g., Ruegeria sp.). Our results indicate that the microbiome in corals can be manipulated to lessen the effect of bleaching, thus helping to alleviate pathogen and temperature stresses, with the addition of BMCs representing a promising novel approach for minimizing coral mortality in the face of increasing environmental impacts.

The magnitude and controls of particulate carbon exported from surface waters and its remineralization at depth are poorly constrained. The Carbon Flux Explorer (CFE), a Lagrangian float-deployed imaging sediment trap, has been designed to optically measure the hourly variations of particle flux to kilometer depths for months to seasons while relaying data in near-real time to shore via satellite without attending ships. The main optical proxy for particle load recorded by the CFE, volume attenuance (VA; units of mATN cm2), while rigorously defined and highly precise, has not been robustly calibrated in terms of particulate organic carbon (POC), nitrogen (PN) and phosphorus (PP). In this study, a novel 3-D-printed particle sampler using cutting edge additive manufacturing was developed and integrated with the CFE. Two such modified floats (CFE-Cals) were deployed a total of 15 times for 18-24 h periods to gain calibration imagery and samples at depths near 150m in four contrasting productivity environments during the June 2017 California Current Ecosystem Long-Term Ecological Research (LTER) process study. Regression slopes for VA: POC and VA: PN (units mATN cm2: mmol; R2, n, p value in parentheses) were 1.01×104 (0.86, 12, < 0.001) and 1:01×105 (0.86, 15, < 0.001), respectively, and were not sensitive to particle size classes or the contrasting environments encountered. PP was not well correlated with VA, reflecting the high lability of P relative to C and N. The volume attenuance flux (VAF) to POC flux calibration is compared to previous estimates.

Many proteins fold into highly regular and repetitive three dimensional structures. The analysis of structural patterns and repeated elements is fundamental to understand protein function and evolution. We present recent improvements to the CE-Symm tool for systematically detecting and analyzing the internal symmetry and structural repeats in proteins. In addition to the accurate detection of internal symmetry, the tool is now capable of i) reporting the type of symmetry, ii) identifying the smallest repeating unit, iii) describing the arrangement of repeats with transformation operations and symmetry axes, and iv) comparing the similarity of all the internal repeats at the residue level. CE-Symm 2.0 helps the user investigate proteins with a robust and intuitive sequence-to-structure analysis, with many applications in protein classification, functional annotation and evolutionary studies. We describe the algorithmic extensions of the method and demonstrate its applications to the study of interesting cases of protein evolution.

The magnitude and controls of particulate carbon exported from surface waters and its remineralization at depth are poorly constrained. The Carbon Flux Explorer (CFE), a Lagrangian float-deployed imaging sediment trap, has been designed to optically measure the hourly variations of particle flux to kilometer depths for months to seasons while relaying data in near-real time to shore via satellite without attending ships. The main optical proxy for particle load recorded by the CFE, volume attenuance (VA; units of mATN cm2), while rigorously defined and highly precise, has not been robustly calibrated in terms of particulate organic carbon (POC), nitrogen (PN) and phosphorus (PP). In this study, a novel 3-D-printed particle sampler using cutting edge additive manufacturing was developed and integrated with the CFE. Two such modified floats (CFE-Cals) were deployed a total of 15 times for 18-24 h periods to gain calibration imagery and samples at depths near 150m in four contrasting productivity environments during the June 2017 California Current Ecosystem Long-Term Ecological Research (LTER) process study. Regression slopes for VA: POC and VA: PN (units mATN cm2: mmol; R2, n, p value in parentheses) were 1.01×104 (0.86, 12, < 0.001) and 1:01×105 (0.86, 15, < 0.001), respectively, and were not sensitive to particle size classes or the contrasting environments encountered. PP was not well correlated with VA, reflecting the high lability of P relative to C and N. The volume attenuance flux (VAF) to POC flux calibration is compared to previous estimates.

The transcription factor MXD3 is an atypical member of the MYC/MAX/MXD transcriptional network and has been previously shown to be an important regulator of cell proliferation. MXD3 has been shown to be overexpressed and to be required for medulloblastoma and acute lymphoblastic leukemia cell proliferation. In this study we leveraged datasets from The Cancer Genome Atlas to examine MXD3 across several cancers. We find that MXD3 transcripts are significantly overexpressed in ~72% of the available datasets. The gene itself is not frequently altered, while the promoter appears to be hypomethylated. We examine the possibility that aberrant regulation of the MXD3 message is the cause of abnormal MXD3 expression across cancers. Specifically, we looked at MXD3 alternative splicing in glioblastoma multiforme (GBM) and find notable functional differences between the splice variants. The 3'UTR confers differential message stability. Furthermore, the different coding sequences lead to different protein stabilities and localizations. Altogether, these data extend our knowledge of MXD3 in the context of human cancers while characterizing a previously unstudied splice variant of MXD3.

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

We present an overview of the toxicological profile of the fast-acting, lipophilic macrocyclic imine toxins, an emerging family of organic compounds associated with algal blooms, shellfish contamination and neurotoxicity. Worldwide, shellfish contamination incidents are expanding; therefore, the significance of these toxins for the shellfish food industry deserves further study. Emphasis is directed to the dinoflagellate species involved in their production, their chemical structures, and their specific mode of interaction with their principal natural molecular targets, the nicotinic acetylcholine receptors, or with the soluble acetylcholine-binding protein, used as a surrogate receptor model. The dinoflagellates Karenia selliformis and Alexandrium ostenfeldii / A. peruvianum have been implicated in the biosynthesis of gymnodimines and spirolides, while Vulcanodinium rugosum is the producer of pinnatoxins and portimine. The cyclic imine toxins are characterized by a macrocyclic skeleton comprising 14-27 carbon atoms, flanked by two conserved moieties, the cyclic imine and the spiroketal ring system. These phycotoxins generally display high affinity and broad specificity for the muscle type and neuronal nicotinic acetylcholine receptors, a feature consistent with their binding site at the receptor subunit interfaces, composed of residues highly conserved among all nAChRs, and explaining the diverse toxicity among animal species. This is an article for the special issue XVth International Symposium on Cholinergic Mechanisms.

SummaryWe developed a new software tool, BioJava-ModFinder, for identifying protein modifications observed in 3D structures archived in the Protein Data Bank (PDB). Information on more than 400 types of protein modifications were collected and curated from annotations in PDB, RESID, and PSI-MOD. We divided these modifications into three categories: modified residues, attachment modifications, and cross-links. We have developed a systematic method to identify these modifications in 3D protein structures. We have integrated this package with the RCSB PDB web application and added protein modification annotations to the sequence diagram and structure display. By scanning all 3D structures in the PDB using BioJava-ModFinder, we identified more than 30 000 structures with protein modifications, which can be searched, browsed, and visualized on the RCSB PDB website.Availability and implementationBioJava-ModFinder is available as open source (LGPL license) at ( https://github.com/biojava/biojava/tree/master/biojava-modfinder ). The RCSB PDB can be accessed at http://www.rcsb.org .Contactpwrose@ucsd.edu.

Meiosis produces haploid gametes through a succession of chromosomal events, including pairing, synapsis, and recombination. Mechanisms that orchestrate these events remain poorly understood. We found that the SUMO (small ubiquitin-like modifier)-modification and ubiquitin-proteasome systems regulate the major events of meiotic prophase in mouse. Interdependent localization of SUMO, ubiquitin, and proteasomes along chromosome axes was mediated largely by RNF212 and HEI10, two E3 ligases that are also essential for crossover recombination. RNF212-dependent SUMO conjugation effected a checkpointlike process that stalls recombination by rendering the turnover of a subset of recombination factors dependent on HEI10-mediated ubiquitylation. We propose that SUMO conjugation establishes a precondition for designating crossover sites via selective protein stabilization. Thus, meiotic chromosome axes are hubs for regulated proteolysis via SUMO-dependent control of the ubiquitin-proteasome system.

BackgroundThe success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology.ResultsHere, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/).ConclusionsTranslating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10-7) and thalamus (d=-0.148; P=4.27 × 10-3) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10-5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10-7) and thalamus (d=-0.148; P=4.27 × 10-3) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10-5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.

Open access, open data, open source and other open scholarship practices are growing in popularity and necessity. However, widespread adoption of these practices has not yet been achieved. One reason is that researchers are uncertain about how sharing their work will affect their careers. We review literature demonstrating that open research is associated with increases in citations, media attention, potential collaborators, job opportunities and funding opportunities. These findings are evidence that open research practices bring significant benefits to researchers relative to more traditional closed practices.

Atypical protein kinase C (aPKC) enzymes signal on protein scaffolds, yet how they are maintained in an active conformation on scaffolds is unclear. A myristoylated peptide based on the autoinhibitory pseudosubstrate fragment of the atypical PKCζ, zeta inhibitory peptide (ZIP), has been extensively used to inhibit aPKC activity; however, we have previously shown that ZIP does not inhibit the catalytic activity of aPKC isozymes in cells (Wu-Zhang, A. X., Schramm, C. L., Nabavi, S., Malinow, R., and Newton, A. C. (2012) J. Biol. Chem. 287, 12879-12885). Here we sought to identify a bona fide target of ZIP and, in so doing, unveiled a novel mechanism by which aPKCs are maintained in an active conformation on a protein scaffold. Specifically, we used protein-protein interaction network analysis, structural modeling, and protein-protein docking to predict that ZIP binds an acidic surface on the Phox and Bem1 (PB1) domain of p62, an interaction validated by peptide array analysis. Using a genetically encoded reporter for PKC activity fused to the p62 scaffold, we show that ZIP inhibits the activity of wild-type aPKC, but not a construct lacking the pseudosubstrate. These data support a model in which the pseudosubstrate of aPKCs is tethered to the acidic surface on p62, locking aPKC in an open, signaling-competent conformation. ZIP competes for binding to the acidic surface, resulting in displacement of the pseudosubstrate of aPKC and re-engagement in the substrate-binding cavity. This study not only identifies a cellular target for ZIP, but also unveils a novel mechanism by which scaffolded aPKC is maintained in an active conformation.

Pinnatoxins are macrocyclic imine phycotoxins associated with algal blooms and shellfish toxicity. Functional analysis of pinnatoxin A and pinnatoxin G by binding and voltage-clamp electrophysiology on membrane-embedded neuronal α7, α4β2, α3β2, and muscle-type α12βγδ nicotinic acetylcholine receptors (nAChRs) reveals high-affinity binding and potent antagonism for the α7 and α12βγδ subtypes. The toxins also bind to the nAChR surrogate, acetylcholine-binding protein (AChBP), with low Kd values reflecting slow dissociation. Crystal structures of pinnatoxin-AChBP complexes (1.9-2.2 Å resolution) show the multiple anchoring points of the hydrophobic portion, the cyclic imine, and the substituted bis-spiroketal and cyclohexene ring systems of the pinnatoxins that dictate tight binding between the opposing loops C and F at the receptor subunit interface, as observed for the 13-desmethyl-spirolide C and gymnodimine A congeners. Uniquely, however, the bulky bridged EF-ketal ring specific to the pinnatoxins extends radially from the interfacial-binding pocket to interact with the sequence-variable loop F and govern nAChR subtype selectivity and central neurotoxicity.

MotivationCircular permutation is an important type of protein rearrangement. Natural circular permutations have implications for protein function, stability and evolution. Artificial circular permutations have also been used for protein studies. However, such relationships are difficult to detect for many sequence and structure comparison algorithms and require special consideration.ResultsWe developed a new algorithm, called Combinatorial Extension for Circular Permutations (CE-CP), which allows the structural comparison of circularly permuted proteins. CE-CP was designed to be user friendly and is integrated into the RCSB Protein Data Bank. It was tested on two collections of circularly permuted proteins. Pairwise alignments can be visualized both in a desktop application or on the web using Jmol and exported to other programs in a variety of formats.Availability and implementationThe CE-CP algorithm can be accessed through the RCSB website at http://www.rcsb.org/pdb/workbench/workbench.do. Source code is available under the LGPL 2.1 as part of BioJava 3 (http://biojava.org; http://github.com/biojava/biojava).Contactsbliven@ucsd.edu or info@rcsb.org.

The RCSB Protein Data Bank (RCSB PDB, http://www.rcsb.org) provides access to 3D structures of biological macromolecules and is one of the leading resources in biology and biomedicine worldwide. Our efforts over the past 2 years focused on enabling a deeper understanding of structural biology and providing new structural views of biology that support both basic and applied research and education. Herein, we describe recently introduced data annotations including integration with external biological resources, such as gene and drug databases, new visualization tools and improved support for the mobile web. We also describe access to data files, web services and open access software components to enable software developers to more effectively mine the PDB archive and related annotations. Our efforts are aimed at expanding the role of 3D structure in understanding biology and medicine.

Unravelling the contributions of local anthropogenic and seasonal environmental factors in suppressing the coral immune system is important for prioritizing management actions at reefs exposed to high levels of human activities. Here, we monitor health of the model coral Acropora millepora adjacent to a high-use and an unused reef-based tourist platform, plus a nearby control site without a platform, over 7 months spanning a typical austral summer. Comparisons of temporal patterns in a range of biochemical and genetic immune parameters (Toll-like receptor signalling pathway, lectin-complement system, prophenoloxidase-activating system and green fluorescent protein-like proteins) among healthy, injured and diseased corals revealed that corals exhibit a diverse array of immune responses to environmental and anthropogenic stressors. In healthy corals at the control site, expression of genes involved in the Toll-like receptor signalling pathway (MAPK p38, MEKK1, cFos and ATF4/5) and complement system (C3 and Bf) was modulated by seasonal environmental factors in summer months. Corals at reef platform sites experienced additional stressors over the summer, as evidenced by increased expression of various immune genes, including MAPK p38 and MEKK1. Despite increased expression of immune genes, signs of white syndromes were detected in 31% of study corals near tourist platforms in the warmest summer month. Evidence that colonies developing disease showed reduced expression of genes involved in the complement pathway prior to disease onset suggests that their immune systems may have been compromised. Responses to disease and physical damage primarily involved the melanization cascade and GFP-like proteins, and appeared to be sufficient for recovery when summer heat stress subsided. Overall, seasonal and anthropogenic factors may have interacted synergistically to overwhelm the immune systems of corals near reef platforms, leading to increased disease prevalence in summer at these sites.

SummaryThe Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) resource provides tools for query, analysis and visualization of the 3D structures in the PDB archive. As the mobile Web is starting to surpass desktop and laptop usage, scientists and educators are beginning to integrate mobile devices into their research and teaching. In response, we have developed the RCSB PDB Mobile app for the iOS and Android mobile platforms to enable fast and convenient access to RCSB PDB data and services. Using the app, users from the general public to expert researchers can quickly search and visualize biomolecules, and add personal annotations via the RCSB PDB's integrated MyPDB service.Availability and implementationRCSB PDB Mobile is freely available from the Apple App Store and Google Play (http://www.rcsb.org).

SummaryThe Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) resource provides tools for query, analysis and visualization of the 3D structures in the PDB archive. As the mobile Web is starting to surpass desktop and laptop usage, scientists and educators are beginning to integrate mobile devices into their research and teaching. In response, we have developed the RCSB PDB Mobile app for the iOS and Android mobile platforms to enable fast and convenient access to RCSB PDB data and services. Using the app, users from the general public to expert researchers can quickly search and visualize biomolecules, and add personal annotations via the RCSB PDB's integrated MyPDB service.Availability and implementationRCSB PDB Mobile is freely available from the Apple App Store and Google Play (http://www.rcsb.org).

Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes.

The RCSB Protein Data Bank (RCSB PDB, http://www.rcsb.org) provides access to 3D structures of biological macromolecules and is one of the leading resources in biology and biomedicine worldwide. Our efforts over the past 2 years focused on enabling a deeper understanding of structural biology and providing new structural views of biology that support both basic and applied research and education. Herein, we describe recently introduced data annotations including integration with external biological resources, such as gene and drug databases, new visualization tools and improved support for the mobile web. We also describe access to data files, web services and open access software components to enable software developers to more effectively mine the PDB archive and related annotations. Our efforts are aimed at expanding the role of 3D structure in understanding biology and medicine.

In large-scale proteomic experiments, multiple peptide precursors are often cofragmented simultaneously in the same mixture tandem mass (MS/MS) spectrum. These spectra tend to elude current computational tools because of the ubiquitous assumption that each spectrum is generated from only one peptide. Therefore, tools that consider multiple peptide matches to each MS/MS spectrum can potentially improve the relatively low spectrum identification rate often observed in proteomics experiments. More importantly, data independent acquisition protocols promoting the cofragmentation of multiple precursors are emerging as alternative methods that can greatly improve the throughput of peptide identifications but their success also depends on the availability of algorithms to identify multiple peptides from each MS/MS spectrum. Here we address a fundamental question in the identification of mixture MS/MS spectra: determining the statistical significance of multiple peptides matched to a given MS/MS spectrum. We propose the MixGF generating function model to rigorously compute the statistical significance of peptide identifications for mixture spectra and show that this approach improves the sensitivity of current mixture spectra database search tools by a ≈30-390%. Analysis of multiple data sets with MixGF reveals that in complex biological samples the number of identified mixture spectra can be as high as 20% of all the identified spectra and the number of unique peptides identified only in mixture spectra can be up to 35.4% of those identified in single-peptide spectra.

Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.

Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) develops tools and resources that provide a structural view of biology for research and education. The RCSB PDB web site (http://www.rcsb.org) uses the curated 3D macromolecular data contained in the PDB archive to offer unique methods to access, report and visualize data. Recent activities have focused on improving methods for simple and complex searches of PDB data, creating specialized access to chemical component data and providing domain-based structural alignments. New educational resources are offered at the PDB-101 educational view of the main web site such as Author Profiles that display a researcher's PDB entries in a timeline. To promote different kinds of access to the RCSB PDB, Web Services have been expanded, and an RCSB PDB Mobile application for the iPhone/iPad has been released. These improvements enable new opportunities for analyzing and understanding structure data.

UnlabelledBioJava is an open-source project for processing of biological data in the Java programming language. We have recently released a new version (3.0.5), which is a major update to the code base that greatly extends its functionality.ResultsBioJava now consists of several independent modules that provide state-of-the-art tools for protein structure comparison, pairwise and multiple sequence alignments, working with DNA and protein sequences, analysis of amino acid properties, detection of protein modifications and prediction of disordered regions in proteins as well as parsers for common file formats using a biologically meaningful data model.AvailabilityBioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.6 or higher. All inquiries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists.

UnlabelledBioJava is an open-source project for processing of biological data in the Java programming language. We have recently released a new version (3.0.5), which is a major update to the code base that greatly extends its functionality.ResultsBioJava now consists of several independent modules that provide state-of-the-art tools for protein structure comparison, pairwise and multiple sequence alignments, working with DNA and protein sequences, analysis of amino acid properties, detection of protein modifications and prediction of disordered regions in proteins as well as parsers for common file formats using a biologically meaningful data model.AvailabilityBioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.6 or higher. All inquiries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists.

The RCSB Protein Data Bank (RCSB PDB, www.pdb.org) is a key online resource for structural biology and related scientific disciplines. The website is used on average by 165,000 unique visitors per month, and more than 2000 other websites link to it. The amount and complexity of PDB data as well as the expectations on its usage are growing rapidly. Therefore, ensuring the reliability and robustness of the RCSB PDB query and distribution systems are crucially important and increasingly challenging. This article describes quality assurance for the RCSB PDB website at several distinct levels, including: (i) hardware redundancy and failover, (ii) testing protocols for weekly database updates, (iii) testing and release procedures for major software updates and (iv) miscellaneous monitoring and troubleshooting tools and practices. As such it provides suggestions for how other websites might be operated.

IEDB-3D is the 3D structural component of the Immune Epitope Database (IEDB) available via the 'Browse by 3D Structure' page at http://www.iedb.org. IEDB-3D catalogs B- and T-cell epitopes and Major Histocompatibility Complex (MHC) ligands for which 3D structures of complexes with antibodies, T-cell receptors or MHC molecules are available in the Protein Data Bank (PDB). Journal articles that are primary citations of PDB structures and that define immune epitopes are curated within IEDB as any other reference along with accompanying functional assays and immunologically relevant information. For each curated structure, IEDB-3D provides calculated data on intermolecular contacts and interface areas and includes an application, EpitopeViewer, to visualize the structures. IEDB-3D is fully embedded within IEDB, thus allowing structural data, both curated and calculated, and all accompanying information to be queried using multiple search interfaces. These include queries for epitopes recognized in different pathogens, eliciting different functional immune responses, and recognized by different components of the immune system. The query results can be downloaded in Microsoft Excel format, or the entire database, together with structural data both curated and calculated, can be downloaded in either XML or MySQL formats.

The RCSB Protein Data Bank (RCSB PDB) web site (http://www.pdb.org) has been redesigned to increase usability and to cater to a larger and more diverse user base. This article describes key enhancements and new features that fall into the following categories: (i) query and analysis tools for chemical structure searching, query refinement, tabulation and export of query results; (ii) web site customization and new structure alerts; (iii) pair-wise and representative protein structure alignments; (iv) visualization of large assemblies; (v) integration of structural data with the open access literature and binding affinity data; and (vi) web services and web widgets to facilitate integration of PDB data and tools with other resources. These improvements enable a range of new possibilities to analyze and understand structure data. The next generation of the RCSB PDB web site, as described here, provides a rich resource for research and education.

IEDB-3D is the 3D structural component of the Immune Epitope Database (IEDB) available via the 'Browse by 3D Structure' page at http://www.iedb.org. IEDB-3D catalogs B- and T-cell epitopes and Major Histocompatibility Complex (MHC) ligands for which 3D structures of complexes with antibodies, T-cell receptors or MHC molecules are available in the Protein Data Bank (PDB). Journal articles that are primary citations of PDB structures and that define immune epitopes are curated within IEDB as any other reference along with accompanying functional assays and immunologically relevant information. For each curated structure, IEDB-3D provides calculated data on intermolecular contacts and interface areas and includes an application, EpitopeViewer, to visualize the structures. IEDB-3D is fully embedded within IEDB, thus allowing structural data, both curated and calculated, and all accompanying information to be queried using multiple search interfaces. These include queries for epitopes recognized in different pathogens, eliciting different functional immune responses, and recognized by different components of the immune system. The query results can be downloaded in Microsoft Excel format, or the entire database, together with structural data both curated and calculated, can be downloaded in either XML or MySQL formats.

SummaryWith the continuous growth of the RCSB Protein Data Bank (PDB), providing an up-to-date systematic structure comparison of all protein structures poses an ever growing challenge. Here, we present a comparison tool for calculating both 1D protein sequence and 3D protein structure alignments. This tool supports various applications at the RCSB PDB website. First, a structure alignment web service calculates pairwise alignments. Second, a stand-alone application runs alignments locally and visualizes the results. Third, pre-calculated 3D structure comparisons for the whole PDB are provided and updated on a weekly basis. These three applications allow users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user.Availability and implementationA web user interface is available at http://www.rcsb.org/pdb/workbench/workbench.do. The source code is available under the LGPL license from http://www.biojava.org. A source bundle, prepared for local execution, is available from http://source.rcsb.orgContactandreas@sdsc.edu; pbourne@ucsd.edu.

SummaryWith the continuous growth of the RCSB Protein Data Bank (PDB), providing an up-to-date systematic structure comparison of all protein structures poses an ever growing challenge. Here, we present a comparison tool for calculating both 1D protein sequence and 3D protein structure alignments. This tool supports various applications at the RCSB PDB website. First, a structure alignment web service calculates pairwise alignments. Second, a stand-alone application runs alignments locally and visualizes the results. Third, pre-calculated 3D structure comparisons for the whole PDB are provided and updated on a weekly basis. These three applications allow users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user.Availability and implementationA web user interface is available at http://www.rcsb.org/pdb/workbench/workbench.do. The source code is available under the LGPL license from http://www.biojava.org. A source bundle, prepared for local execution, is available from http://source.rcsb.orgContactandreas@sdsc.edu; pbourne@ucsd.edu.

BackgroundThe root of the tree of life has been a holy grail ever since Darwin first used the tree as a metaphor for evolution. New methods seek to narrow down the location of the root by excluding it from branches of the tree of life. This is done by finding traits that must be derived, and excluding the root from the taxa those traits cover. However the two most comprehensive attempts at this strategy, performed by Cavalier-Smith and Lake et al., have excluded each other's rootings.ResultsThe indel polarizations of Lake et al. rely on high quality alignments between paralogs that diverged before the last universal common ancestor (LUCA). Therefore, sequence alignment artifacts may skew their conclusions. We have reviewed their data using protein structure information where available. Several of the conclusions are quite different when viewed in the light of structure which is conserved over longer evolutionary time scales than sequence. We argue there is no polarization that excludes the root from all Gram-negatives, and that polarizations robustly exclude the root from the Archaea.ConclusionWe conclude that there is no contradiction between the polarization datasets. The combination of these datasets excludes the root from every possible position except near the Chloroflexi.

BackgroundThe root of the tree of life has been a holy grail ever since Darwin first used the tree as a metaphor for evolution. New methods seek to narrow down the location of the root by excluding it from branches of the tree of life. This is done by finding traits that must be derived, and excluding the root from the taxa those traits cover. However the two most comprehensive attempts at this strategy, performed by Cavalier-Smith and Lake et al., have excluded each other's rootings.ResultsThe indel polarizations of Lake et al. rely on high quality alignments between paralogs that diverged before the last universal common ancestor (LUCA). Therefore, sequence alignment artifacts may skew their conclusions. We have reviewed their data using protein structure information where available. Several of the conclusions are quite different when viewed in the light of structure which is conserved over longer evolutionary time scales than sequence. We argue there is no polarization that excludes the root from all Gram-negatives, and that polarizations robustly exclude the root from the Archaea.ConclusionWe conclude that there is no contradiction between the polarization datasets. The combination of these datasets excludes the root from every possible position except near the Chloroflexi.

BackgroundReliable prediction of antibody, or B-cell, epitopes remains challenging yet highly desirable for the design of vaccines and immunodiagnostics. A correlation between antigenicity, solvent accessibility, and flexibility in proteins was demonstrated. Subsequently, Thornton and colleagues proposed a method for identifying continuous epitopes in the protein regions protruding from the protein's globular surface. The aim of this work was to implement that method as a web-tool and evaluate its performance on discontinuous epitopes known from the structures of antibody-protein complexes.ResultsHere we present ElliPro, a web-tool that implements Thornton's method and, together with a residue clustering algorithm, the MODELLER program and the Jmol viewer, allows the prediction and visualization of antibody epitopes in a given protein sequence or structure. ElliPro has been tested on a benchmark dataset of discontinuous epitopes inferred from 3D structures of antibody-protein complexes. In comparison with six other structure-based methods that can be used for epitope prediction, ElliPro performed the best and gave an AUC value of 0.732, when the most significant prediction was considered for each protein. Since the rank of the best prediction was at most in the top three for more than 70% of proteins and never exceeded five, ElliPro is considered a useful research tool for identifying antibody epitopes in protein antigens. ElliPro is available at http://tools.immuneepitope.org/tools/ElliPro.ConclusionThe results from ElliPro suggest that further research on antibody epitopes considering more features that discriminate epitopes from non-epitopes may further improve predictions. As ElliPro is based on the geometrical properties of protein structure and does not require training, it might be more generally applied for predicting different types of protein-protein interactions.

BackgroundReliable prediction of antibody, or B-cell, epitopes remains challenging yet highly desirable for the design of vaccines and immunodiagnostics. A correlation between antigenicity, solvent accessibility, and flexibility in proteins was demonstrated. Subsequently, Thornton and colleagues proposed a method for identifying continuous epitopes in the protein regions protruding from the protein's globular surface. The aim of this work was to implement that method as a web-tool and evaluate its performance on discontinuous epitopes known from the structures of antibody-protein complexes.ResultsHere we present ElliPro, a web-tool that implements Thornton's method and, together with a residue clustering algorithm, the MODELLER program and the Jmol viewer, allows the prediction and visualization of antibody epitopes in a given protein sequence or structure. ElliPro has been tested on a benchmark dataset of discontinuous epitopes inferred from 3D structures of antibody-protein complexes. In comparison with six other structure-based methods that can be used for epitope prediction, ElliPro performed the best and gave an AUC value of 0.732, when the most significant prediction was considered for each protein. Since the rank of the best prediction was at most in the top three for more than 70% of proteins and never exceeded five, ElliPro is considered a useful research tool for identifying antibody epitopes in protein antigens. ElliPro is available at http://tools.immuneepitope.org/tools/ElliPro.ConclusionThe results from ElliPro suggest that further research on antibody epitopes considering more features that discriminate epitopes from non-epitopes may further improve predictions. As ElliPro is based on the geometrical properties of protein structure and does not require training, it might be more generally applied for predicting different types of protein-protein interactions.

BackgroundOne of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because profiles are built from sequence alignments, the sequences included in the alignment and the method used to align them will be important to the sensitivity of the resulting profile. The inclusion of highly diverse sequences will presumably produce a more powerful profile, but distantly related sequences can be difficult to align accurately using only sequence information. Therefore, it would be expected that the use of protein structure alignments to improve the selection and alignment of diverse sequence homologs might yield improved profiles. However, the actual utility of such an approach has remained unclear.ResultsWe explored several iterative protocols for the generation of profile hidden Markov models. These protocols were tailored to allow the inclusion of protein structure alignments in the process, and were used for large-scale creation and benchmarking of structure alignment-enhanced models. We found that models using structure alignments did not provide an overall improvement over sequence-only models for superfamily-level structure predictions. However, the results also revealed that the structure alignment-enhanced models were complimentary to the sequence-only models, particularly at the edge of the "twilight zone". When the two sets of models were combined, they provided improved results over sequence-only models alone. In addition, we found that the beneficial effects of the structure alignment-enhanced models could not be realized if the structure-based alignments were replaced with sequence-based alignments. Our experiments with different iterative protocols for sequence-only models also suggested that simple protocol modifications were unable to yield equivalent improvements to those provided by the structure alignment-enhanced models. Finally, we found that models using structure alignments provided fold-level structure assignments that were superior to those produced by sequence-only models.ConclusionWhen attempting to predict the structure of remote homologs, we advocate a combined approach in which both traditional models and models incorporating structure alignments are used.