Catalysis by hen egg-white lysozyme proceeds via a covalent intermediate

Hen egg-white lysozyme (HEWL) was the first enzyme to have its three-dimensional structure determined by X-ray diffraction techniques(1). A catalytic mechanism, featuring a long-lived oxo-carbenium-ion intermediate, was proposed on the basis of model-building studies(2). The `Phillips' mechanism is widely held as the paradigm for the catalytic mechanism of beta -glycosidases that cleave glycosidic linkages with net retention of configuration of the anomeric centre. Studies with other retaining beta -glycosidases, however, provide strong evidence pointing to a common mechanism for these enzymes that involves a covalent glycosyl-enzyme intermediate, as previously postulated(3). Here we show, in three different cases using electrospray ionization mass spectrometry, a catalytically competent covalent glycosyl-enzyme intermediate during the catalytic cycle of HEWL. We also show the three-dimensional structure of this intermediate as determined by Xray diffraction. We formulate a general catalytic mechanism for all retaining beta -glycosidases that includes substrate distortion, formation of a covalent intermediate, and the electrophilic migration of C1 along the reaction coordinate

Composite structural motifs of binding sites for delineating biological functions of proteins

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs which represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.Comment: 34 pages, 7 figure

Studies on the production of branched-chain alcohols in engineered Ralstonia eutropha

Wild-type Ralstonia eutropha H16 produces polyhydroxybutyrate (PHB) as an intracellular carbon storage material during nutrient stress in the presence of excess carbon. In this study, the excess carbon was redirected in engineered strains from PHB storage to the production of isobutanol and 3-methyl-1-butanol (branched-chain higher alcohols). These branched-chain higher alcohols can directly substitute for fossil-based fuels and be employed within the current infrastructure. Various mutant strains of R. eutropha with isobutyraldehyde dehydrogenase activity, in combination with the overexpression of plasmid-borne, native branched-chain amino acid biosynthesis pathway genes and the overexpression of heterologous ketoisovalerate decarboxylase gene, were employed for the biosynthesis of isobutanol and 3-methyl-1-butanol. Production of these branched-chain alcohols was initiated during nitrogen or phosphorus limitation in the engineered R. eutropha. One mutant strain not only produced over 180 mg/L branched-chain alcohols in flask culture, but also was significantly more tolerant of isobutanol toxicity than wild-type R. eutropha. After the elimination of genes encoding three potential carbon sinks (ilvE, bkdAB, and aceE), the production titer improved to 270 mg/L isobutanol and 40 mg/L 3-methyl-1-butanol. Semicontinuous flask cultivation was utilized to minimize the toxicity caused by isobutanol while supplying cells with sufficient nutrients. Under this semicontinuous flask cultivation, the R. eutropha mutant grew and produced more than 14 g/L branched-chain alcohols over the duration of 50 days. These results demonstrate that R. eutropha carbon flux can be redirected from PHB to branched-chain alcohols and that engineered R. eutropha can be cultivated over prolonged periods of time for product biosynthesis.United States. Dept. of EnergyUnited States. Advanced Research Projects Agency-Energ

Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets

<p>Abstract</p> <p>Background</p> <p>The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phenotypes. The immense potential offered by these data derives from the fact that genotypic variation is the sole source of perturbation and can therefore be used to reconcile changes in gene expression programs with the parental genotypes. To date, several methodologies have been developed for modeling eQTL data. These methods generally leverage genotypic data to resolve causal relationships among gene pairs implicated as associates in the expression data. In particular, leading studies have augmented Bayesian networks with genotypic data, providing a powerful framework for learning and modeling causal relationships. While these initial efforts have provided promising results, one major drawback associated with these methods is that they are generally limited to resolving causal orderings for transcripts most proximal to the genomic loci. In this manuscript, we present a probabilistic method capable of learning the causal relationships between transcripts at all levels in the network. We use the information provided by our method as a prior for Bayesian network structure learning, resulting in enhanced performance for gene network reconstruction.</p> <p>Results</p> <p>Using established protocols to synthesize eQTL networks and corresponding data, we show that our method achieves improved performance over existing leading methods. For the goal of gene network reconstruction, our method achieves improvements in recall ranging from 20% to 90% across a broad range of precision levels and for datasets of varying sample sizes. Additionally, we show that the learned networks can be utilized for expression quantitative trait loci mapping, resulting in upwards of 10-fold increases in recall over traditional univariate mapping.</p> <p>Conclusions</p> <p>Using the information from our method as a prior for Bayesian network structure learning yields large improvements in accuracy for the tasks of gene network reconstruction and expression quantitative trait loci mapping. In particular, our method is effective for establishing causal relationships between transcripts located both proximally and distally from genomic loci.</p

Practitioner perspectives on informing decisions in One Health sectors with predictive models

The continued emergence of challenges in human, animal, and environmental health (One Health sectors) requires public servants to make management and policy decisions about system-level ecological and sociological processes that are complex, poorly understood, and change over time. Relying on intuition, evidence, and experience for robust decision-making is challenging without a formal assimilation of these elements (a model), especially when the decision needs to consider potential impacts if an action is or is not taken. Models can provide assistance to this challenge, but effective development and use of model-based evidence in decision-making (‘model-to-decision workflow’) can be challenging. To address this gap, we examined conditions that maximize the value of model-based evidence in decision-making in One Health sectors by conducting 41 semi-structured interviews of researchers, science advisors, operational managers, and policy decision-makers with direct experience in model-to-decision workflows (‘Practitioners’) in One Health sectors. Broadly, our interview guide was structured to understand practitioner perspectives about the utility of models in health policy or management decision-making, challenges and risks with using models in this capacity, experience with using models, factors that affect trust in model-based evidence, and perspectives about conditions that lead to the most effective model-to-decision workflow. We used inductive qualitative analysis of the interview data with iterative coding to identify key themes for maximizing the value of model-based evidence in One Health applications. Our analysis describes practitioner perspectives for improved collaboration among modelers and decision-makers in public service, and priorities for increasing accessibility and value of model-based evidence in One Health decision-making. Two emergent priorities include establishing different standards for development of model-based evidence before or after decisions are made, or in real-time versus preparedness phases of emergency response, and investment in knowledge brokers with modeling expertise working in teams with decision-makers.fals

The complete genome sequence and genetic analysis of ΦCA82 a novel uncultured microphage from the turkey gastrointestinal system

The genomic DNA sequence of a novel enteric uncultured microphage, ΦCA82 from a turkey gastrointestinal system was determined utilizing metagenomics techniques. The entire circular, single-stranded nucleotide sequence of the genome was 5,514 nucleotides. The ΦCA82 genome is quite different from other microviruses as indicated by comparisons of nucleotide similarity, predicted protein similarity, and functional classifications. Only three genes showed significant similarity to microviral proteins as determined by local alignments using BLAST analysis. ORF1 encoded a predicted phage F capsid protein that was phylogenetically most similar to the Microviridae ΦMH2K member's major coat protein. The ΦCA82 genome also encoded a predicted minor capsid protein (ORF2) and putative replication initiation protein (ORF3) most similar to the microviral bacteriophage SpV4. The distant evolutionary relationship of ΦCA82 suggests that the divergence of this novel turkey microvirus from other microviruses may reflect unique evolutionary pressures encountered within the turkey gastrointestinal system

Natural infection by the protozoan Leptomonas wallacei impacts the morphology, physiology, reproduction, and lifespan of the insect Oncopeltus fasciatus

Trypanosomatids are protozoan parasites that infect thousands of globally dispersed hosts, potentially affecting their physiology. Several species of trypanosomatids are commonly found in phytophagous insects. Leptomonas wallacei is a gut-restricted insect trypanosomatid only retrieved from Oncopeltus fasciatus. The insects get infected by coprophagy and transovum transmission of L. wallacei cysts. The main goal of the present study was to investigate the effects of a natural infection by L. wallacei on the hemipteran insect O. fasciatus, by comparing infected and uninfected individuals in a controlled environment. The L. wallacei-infected individuals showed reduced lifespan and morphological alterations. Also, we demonstrated a higher infection burden in females than in males. The infection caused by L. wallacei reduced host reproductive fitness by negatively impacting egg load, oviposition, and eclosion, and promoting an increase in egg reabsorption. Moreover, we associated the egg reabsorption observed in infected females, with a decrease in the intersex gene expression. Finally, we suggest alterations in population dynamics induced by L. wallacei infection using a mathematical model. Collectively, our findings demonstrated that L. wallacei infection negatively affected the physiology of O. fasciatus, which suggests that L. wallacei potentially has a vast ecological impact on host population growth

Axonal Regeneration and Neuronal Function Are Preserved in Motor Neurons Lacking ß-Actin In Vivo

The proper localization of ß-actin mRNA and protein is essential for growth cone guidance and axon elongation in cultured neurons. In addition, decreased levels of ß-actin mRNA and protein have been identified in the growth cones of motor neurons cultured from a mouse model of Spinal Muscular Atrophy (SMA), suggesting that ß-actin loss-of-function at growth cones or pre-synaptic nerve terminals could contribute to the pathogenesis of this disease. However, the role of ß-actin in motor neurons in vivo and its potential relevance to disease has yet to be examined. We therefore generated motor neuron specific ß-actin knock-out mice (Actb-MNsKO) to investigate the function of ß-actin in motor neurons in vivo. Surprisingly, ß-actin was not required for motor neuron viability or neuromuscular junction maintenance. Skeletal muscle from Actb-MNsKO mice showed no histological indication of denervation and did not significantly differ from controls in several measurements of physiologic function. Finally, motor axon regeneration was unimpaired in Actb-MNsKO mice, suggesting that ß-actin is not required for motor neuron function or regeneration in vivo

Open questions in utility theory

Throughout this paper, our main idea is to explore different classical questions arising in Utility Theory, with a particular attention to those that lean on numerical representations of preference orderings. We intend to present a survey of open questions in that discipline, also showing the state-of-art of the corresponding literature.This work is partially supported by the research projects ECO2015-65031-R, MTM2015-63608-P (MINECO/ AEI-FEDER, UE), and TIN2016-77356-P (MINECO/ AEI-FEDER, UE)

Expression QTLs Mapping and Analysis: A Bayesian Perspective.

The aim of expression Quantitative Trait Locus (eQTL) mapping is the identification of DNA sequence variants that explain variation in gene expression. Given the recent yield of trait-associated genetic variants identified by large-scale genome-wide association analyses (GWAS), eQTL mapping has become a useful tool to understand the functional context where these variants operate and eventually narrow down functional gene targets for disease. Despite its extensive application to complex (polygenic) traits and disease, the majority of eQTL studies still rely on univariate data modeling strategies, i.e., testing for association of all transcript-marker pairs. However these "one at-a-time" strategies are (1) unable to control the number of false-positives when an intricate Linkage Disequilibrium structure is present and (2) are often underpowered to detect the full spectrum of trans-acting regulatory effects. Here we present our viewpoint on the most recent advances on eQTL mapping approaches, with a focus on Bayesian methodology. We review the advantages of the Bayesian approach over frequentist methods and provide an empirical example of polygenic eQTL mapping to illustrate the different properties of frequentist and Bayesian methods. Finally, we discuss how multivariate eQTL mapping approaches have distinctive features with respect to detection of polygenic effects, accuracy, and interpretability of the results