Electrostatic considerations affecting the calculated HOMO-LUMO gap in protein molecules.

A detailed study of energy differences between the highest occupied and lowest unoccupied molecular orbitals (HOMO-LUMO gaps) in protein systems and water clusters is presented. Recent work questioning the applicability of Kohn-Sham density-functional theory to proteins and large water clusters (E. Rudberg, J. Phys.: Condens. Mat. 2012, 24, 072202) has demonstrated vanishing HOMO-LUMO gaps for these systems, which is generally attributed to the treatment of exchange in the functional used. The present work shows that the vanishing gap is, in fact, an electrostatic artefact of the method used to prepare the system. Practical solutions for ensuring the gap is maintained when the system size is increased are demonstrated. This work has important implications for the use of large-scale density-functional theory in biomolecular systems, particularly in the simulation of photoemission, optical absorption and electronic transport, all of which depend critically on differences between energies of molecular orbitals.Comment: 13 pages, 4 figure

A Precision Measurement of Nuclear Muon Capture on 3He

The muon capture rate in the reaction mu- 3He -> nu + 3H has been measured at PSI using a modular high pressure ionization chamber. The rate corresponding to statistical hyperfine population of the mu-3He atom is (1496.0 +- 4.0) s^-1. This result confirms the PCAC prediction for the pseudoscalar form factors of the 3He-3H system and the nucleon.Comment: 13 pages, 6 PostScript figure

Loss of VGLUT3 Produces Circadian-Dependent Hyperdopaminergia and Ameliorates Motor Dysfunction and l-Dopa-Mediated Dyskinesias in a Model of Parkinson\u27s Disease.

UNLABELLED: The striatum is essential for many aspects of mammalian behavior, including motivation and movement, and is dysfunctional in motor disorders such as Parkinson\u27s disease. The vesicular glutamate transporter 3 (VGLUT3) is expressed by striatal cholinergic interneurons (CINs) and is thus well positioned to regulate dopamine (DA) signaling and locomotor activity, a canonical measure of basal ganglia output. We now report that VGLUT3 knock-out (KO) mice show circadian-dependent hyperlocomotor activity that is restricted to the waking cycle and is due to an increase in striatal DA synthesis, packaging, and release. Using a conditional VGLUT3 KO mouse, we show that deletion of the transporter from CINs, surprisingly, does not alter evoked DA release in the dorsal striatum or baseline locomotor activity. The mice do, however, display changes in rearing behavior and sensorimotor gating. Elevation of DA release in the global KO raised the possibility that motor deficits in a Parkinson\u27s disease model would be reduced. Remarkably, after a partial 6-hydroxydopamine (6-OHDA)-mediated DA depletion (∼70% in dorsal striatum), KO mice, in contrast to WT mice, showed normal motor behavior across the entire circadian cycle. l-3,4-dihydroxyphenylalanine-mediated dyskinesias were also significantly attenuated. These findings thus point to new mechanisms to regulate basal ganglia function and potentially treat Parkinson\u27s disease and related disorders. SIGNIFICANCE STATEMENT: Dopaminergic signaling is critical for both motor and cognitive functions in the mammalian nervous system. Impairments, such as those found in Parkinson\u27s disease patients, can lead to severe motor deficits. Vesicular glutamate transporter 3 (VGLUT3) loads glutamate into secretory vesicles for neurotransmission and is expressed by discrete neuron populations throughout the nervous system. Here, we report that the absence of VGLUT3 in mice leads to an upregulation of the midbrain dopamine system. Remarkably, in a Parkinson\u27s disease model, the mice show normal motor behavior. They also show fewer abnormal motor behaviors (dyskinesias) in response to l-3,4-dihydroxyphenylalanine, the principal treatment for Parkinson\u27s disease. The work thus suggests new avenues for the development of novel treatment strategies for Parkinson\u27s disease and potentially other basal-ganglia-related disorders

Assembling evidence for identifying reservoirs of infection

Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems

A unified framework for multi-locus association analysis of both common and rare variants

<p>Abstract</p> <p>Background</p> <p>Common, complex diseases are hypothesized to result from a combination of common and rare genetic variants. We developed a unified framework for the joint association testing of both types of variants. Within the framework, we developed a union-intersection test suitable for genome-wide analysis of single nucleotide polymorphisms (SNPs), candidate gene data, as well as medical sequencing data. The union-intersection test is a composite test of association of genotype frequencies and differential correlation among markers.</p> <p>Results</p> <p>We demonstrated by computer simulation that the false positive error rate was controlled at the expected level. We also demonstrated scenarios in which the multi-locus test was more powerful than traditional single marker analysis. To illustrate use of the union-intersection test with real data, we analyzed a publically available data set of 319,813 autosomal SNPs genotyped for 938 cases of Parkinson disease and 863 neurologically normal controls for which no genome-wide significant results were found by traditional single marker analysis. We also analyzed an independent follow-up sample of 183 cases and 248 controls for replication.</p> <p>Conclusions</p> <p>We identified a single risk haplotype with a directionally consistent effect in both samples in the gene <it>GAK</it>, which is involved in clathrin-mediated membrane trafficking. We also found suggestive evidence that directionally inconsistent marginal effects from single marker analysis appeared to result from risk being driven by different haplotypes in the two samples for the genes <it>SYN3 </it>and <it>NGLY1</it>, which are involved in neurotransmitter release and proteasomal degradation, respectively. These results illustrate the utility of our unified framework for genome-wide association analysis of common, complex diseases.</p

Systems Biology of the qa Gene Cluster in Neurospora crassa

An ensemble of genetic networks that describe how the model fungal system, Neurospora crassa, utilizes quinic acid (QA) as a sole carbon source has been identified previously. A genetic network for QA metabolism involves the genes, qa-1F and qa-1S, that encode a transcriptional activator and repressor, respectively and structural genes, qa-2, qa-3, qa-4, qa-x, and qa-y. By a series of 4 separate and independent, model-guided, microarray experiments a total of 50 genes are identified as QA-responsive and hypothesized to be under QA-1F control and/or the control of a second QA-responsive transcription factor (NCU03643) both in the fungal binuclear Zn(II)2Cys6 cluster family. QA-1F regulation is not sufficient to explain the quantitative variation in expression profiles of the 50 QA-responsive genes. QA-responsive genes include genes with products in 8 mutually connected metabolic pathways with 7 of them one step removed from the tricarboxylic (TCA) Cycle and with 7 of them one step removed from glycolysis: (1) starch and sucrose metabolism; (2) glycolysis/glucanogenesis; (3) TCA Cycle; (4) butanoate metabolism; (5) pyruvate metabolism; (6) aromatic amino acid and QA metabolism; (7) valine, leucine, and isoleucine degradation; and (8) transport of sugars and amino acids. Gene products both in aromatic amino acid and QA metabolism and transport show an immediate response to shift to QA, while genes with products in the remaining 7 metabolic modules generally show a delayed response to shift to QA. The additional QA-responsive cutinase transcription factor-1β (NCU03643) is found to have a delayed response to shift to QA. The series of microarray experiments are used to expand the previously identified genetic network describing the qa gene cluster to include all 50 QA-responsive genes including the second transcription factor (NCU03643). These studies illustrate new methodologies from systems biology to guide model-driven discoveries about a core metabolic network involving carbon and amino acid metabolism in N. crassa

Genotype determination for polymorphisms in linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies with single nucleotide polymorphisms (SNPs) show great promise to identify genetic determinants of complex human traits. In current analyses, genotype calling and imputation of missing genotypes are usually considered as two separated tasks. The genotypes of SNPs are first determined one at a time from allele signal intensities. Then the missing genotypes, i.e., no-calls caused by not perfectly separated signal clouds, are imputed based on the linkage disequilibrium (LD) between multiple SNPs. Although many statistical methods have been developed to improve either genotype calling or imputation of missing genotypes, treating the two steps independently can lead to loss of genetic information.</p> <p>Results</p> <p>We propose a novel genotype calling framework. In this framework, we consider the signal intensities and underlying LD structure of SNPs simultaneously by estimating both cluster parameters and haplotype frequencies. As a result, our new method outperforms some existing algorithms in terms of both call rates and genotyping accuracy. Our studies also suggest that jointly analyzing multiple SNPs in LD provides more accurate estimation of haplotypes than haplotype reconstruction methods that only use called genotypes.</p> <p>Conclusion</p> <p>Our study demonstrates that jointly analyzing signal intensities and LD structure of multiple SNPs is a better way to determine genotypes and estimate LD parameters.</p

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Transglutaminase 2 Undergoes a Large Conformational Change upon Activation

Human transglutaminase 2 (TG2), a member of a large family of enzymes that catalyze protein crosslinking, plays an important role in the extracellular matrix biology of many tissues and is implicated in the gluten-induced pathogenesis of celiac sprue. Although vertebrate transglutaminases have been studied extensively, thus far all structurally characterized members of this family have been crystallized in conformations with inaccessible active sites. We have trapped human TG2 in complex with an inhibitor that mimics inflammatory gluten peptide substrates and have solved, at 2-Å resolution, its x-ray crystal structure. The inhibitor stabilizes TG2 in an extended conformation that is dramatically different from earlier transglutaminase structures. The active site is exposed, revealing that catalysis takes place in a tunnel, bridged by two tryptophan residues that separate acyl-donor from acyl-acceptor and stabilize the tetrahedral reaction intermediates. Site-directed mutagenesis was used to investigate the acyl-acceptor side of the tunnel, yielding mutants with a marked increase in preference for hydrolysis over transamidation. By providing the ability to visualize this activated conformer, our results create a foundation for understanding the catalytic as well as the non-catalytic roles of TG2 in biology, and for dissecting the process by which the autoantibody response to TG2 is induced in celiac sprue patients