C. elegans germline-deficient mutants respond to pathogen infection using shared and distinct mechanisms.

Reproduction extracts a cost in resources that organisms are then unable to utilize to deal with a multitude of environmental stressors. In the nematode C. elegans, development of the germline shortens the lifespan of the animal and increases its susceptibility to microbial pathogens. Prior studies have demonstrated germline-deficient nematodes to have increased resistance to gram negative bacteria. We show that germline-deficient strains display increased resistance across a broad range of pathogens including gram positive and gram negative bacteria, and the fungal pathogen Cryptococcus neoformans. Furthermore, we show that the FOXO transcription factor DAF-16, which regulates longevity and immunity in C. elegans, appears to be crucial for maintaining longevity in both wild-type and germline-deficient backgrounds. Our studies indicate that germline-deficient mutants glp-1 and glp-4 respond to pathogen infection using common and different mechanisms that involve the activation of DAF-16.

MicroRNA antagonism of the picornaviral life cycle: alternative mechanisms of interference.

In addition to modulating the function and stability of cellular mRNAs, microRNAs can profoundly affect the life cycles of viruses bearing sequence complementary targets, a finding recently exploited to ameliorate toxicities of vaccines and oncolytic viruses. To elucidate the mechanisms underlying microRNA-mediated antiviral activity, we modified the 3' untranslated region (3'UTR) of Coxsackievirus A21 to incorporate targets with varying degrees of homology to endogenous microRNAs. We show that microRNAs can interrupt the picornavirus life-cycle at multiple levels, including catalytic degradation of the viral RNA genome, suppression of cap-independent mRNA translation, and interference with genome encapsidation. In addition, we have examined the extent to which endogenous microRNAs can suppress viral replication in vivo and how viruses can overcome this inhibition by microRNA saturation in mouse cancer models.

Neural mechanisms of context effects on face recognition: automatic binding and context shift decrements.

Although people do not normally try to remember associations between faces and physical contexts, these associations are established automatically, as indicated by the difficulty of recognizing familiar faces in different contexts ("butcher-on-the-bus" phenomenon). The present fMRI study investigated the automatic binding of faces and scenes. In the face-face (F-F) condition, faces were presented alone during both encoding and retrieval, whereas in the face/scene-face (FS-F) condition, they were presented overlaid on scenes during encoding but alone during retrieval (context change). Although participants were instructed to focus only on the faces during both encoding and retrieval, recognition performance was worse in the FS-F than in the F-F condition ("context shift decrement" [CSD]), confirming automatic face-scene binding during encoding. This binding was mediated by the hippocampus as indicated by greater subsequent memory effects (remembered > forgotten) in this region for the FS-F than the F-F condition. Scene memory was mediated by right parahippocampal cortex, which was reactivated during successful retrieval when the faces were associated with a scene during encoding (FS-F condition). Analyses using the CSD as a regressor yielded a clear hemispheric asymmetry in medial temporal lobe activity during encoding: Left hippocampal and parahippocampal activity was associated with a smaller CSD, indicating more flexible memory representations immune to context changes, whereas right hippocampal/rhinal activity was associated with a larger CSD, indicating less flexible representations sensitive to context change. Taken together, the results clarify the neural mechanisms of context effects on face recognition.

Mechanisms of specificity in neuronal activity-regulated gene transcription.

The brain is a highly adaptable organ that is capable of converting sensory information into changes in neuronal function. This plasticity allows behavior to be accommodated to the environment, providing an important evolutionary advantage. Neurons convert environmental stimuli into long-lasting changes in their physiology in part through the synaptic activity-regulated transcription of new gene products. Since the neurotransmitter-dependent regulation of Fos transcription was first discovered nearly 25 years ago, a wealth of studies have enriched our understanding of the molecular pathways that mediate activity-regulated changes in gene transcription. These findings show that a broad range of signaling pathways and transcriptional regulators can be engaged by neuronal activity to sculpt complex programs of stimulus-regulated gene transcription. However, the shear scope of the transcriptional pathways engaged by neuronal activity raises the question of how specificity in the nature of the transcriptional response is achieved in order to encode physiologically relevant responses to divergent stimuli. Here we summarize the general paradigms by which neuronal activity regulates transcription while focusing on the molecular mechanisms that confer differential stimulus-, cell-type-, and developmental-specificity upon activity-regulated programs of neuronal gene transcription. In addition, we preview some of the new technologies that will advance our future understanding of the mechanisms and consequences of activity-regulated gene transcription in the brain.

Differential mechanisms of morphine antinociceptive tolerance revealed in (beta)arrestin-2 knock-out mice.

Morphine induces antinociception by activating mu opioid receptors (muORs) in spinal and supraspinal regions of the CNS. (Beta)arrestin-2 (beta)arr2), a G-protein-coupled receptor-regulating protein, regulates the muOR in vivo. We have shown previously that mice lacking (beta)arr2 experience enhanced morphine-induced analgesia and do not become tolerant to morphine as determined in the hot-plate test, a paradigm that primarily assesses supraspinal pain responsiveness. To determine the general applicability of the (beta)arr2-muOR interaction in other neuronal systems, we have, in the present study, tested (beta)arr2 knock-out ((beta)arr2-KO) mice using the warm water tail-immersion paradigm, which primarily assesses spinal reflexes to painful thermal stimuli. In this test, the (beta)arr2-KO mice have greater basal nociceptive thresholds and markedly enhanced sensitivity to morphine. Interestingly, however, after a delayed onset, they do ultimately develop morphine tolerance, although to a lesser degree than the wild-type (WT) controls. In the (beta)arr2-KO but not WT mice, morphine tolerance can be completely reversed with a low dose of the classical protein kinase C (PKC) inhibitor chelerythrine. These findings provide in vivo evidence that the muOR is differentially regulated in diverse regions of the CNS. Furthermore, although (beta)arr2 appears to be the most prominent and proximal determinant of muOR desensitization and morphine tolerance, in the absence of this mechanism, the contributions of a PKC-dependent regulatory system become readily apparent.

Biological and ecological mechanisms supporting marine self-governance: The Seri Callo de Hacha Fishery in Mexico

My goal was to describe how biological and ecological factors give shape to fishing practices that can contribute to the successful self-governance of a small-scale fishing system in the Gulf of California, Mexico. The analysis was based on a comparison of the main ecological and biological indicators that fishers claim to use to govern their day-to-day decision making about fishing and data collected in situ. I found that certain indicators allow fishers to learn about differences and characteristics of the resource system and its units. Fishers use such information to guide their day-to-day fishing decisions. More importantly, these decisions appear unable to shape the reproductive viability of the fishery because no indicators were correlated to the reproductive cycle of the target species. As a result, the fishing practices constitute a number of mechanisms that might provide short-term buffering capacity against perturbations or stress factors that otherwise would threaten the overall sustainability and self-governance of the system. The particular biological circumstances that shape the harvesting practices might also act as a precursor of self-governance because they provide fishers with enough incentives to meet the costs of organizing the necessary rule structure that underlies a successful self-governance system.

Development of the morpholino gene knockdown technique in Fundulus heteroclitus: a tool for studying molecular mechanisms in an established environmental model.

A significant challenge in environmental toxicology is that many genetic and genomic tools available in laboratory models are not developed for commonly used environmental models. The Atlantic killifish (Fundulus heteroclitus) is one of the most studied teleost environmental models, yet few genetic or genomic tools have been developed for use in this species. The advancement of genetic and evolutionary toxicology will require that many of the tools developed in laboratory models be transferred into species more applicable to environmental toxicology. Antisense morpholino oligonucleotide (MO) gene knockdown technology has been widely utilized to study development in zebrafish and has been proven to be a powerful tool in toxicological investigations through direct manipulation of molecular pathways. To expand the utility of killifish as an environmental model, MO gene knockdown technology was adapted for use in Fundulus. Morpholino microinjection methods were altered to overcome the significant differences between these two species. Morpholino efficacy and functional duration were evaluated with molecular and phenotypic methods. A cytochrome P450-1A (CYP1A) MO was used to confirm effectiveness of the methodology. For CYP1A MO-injected embryos, a 70% reduction in CYP1A activity, a 86% reduction in total CYP1A protein, a significant increase in beta-naphthoflavone-induced teratogenicity, and estimates of functional duration (50% reduction in activity 10 dpf, and 86% reduction in total protein 12 dpf) conclusively demonstrated that MO technologies can be used effectively in killifish and will likely be just as informative as they have been in zebrafish.

Denitrification and inference of nitrogen sources in the karstic Floridan Aquifer

Aquifer denitrification is among the most poorly constrained fluxes in global and regional nitrogen budgets. The few direct measurements of denitrification in groundwaters provide limited information about its spatial and temporal variability, particularly at the scale of whole aquifers. Uncertainty in estimates of denitrification may also lead to underestimates of its effect on isotopic signatures of inorganic N, and thereby confound the inference of N source from these data. In this study, our objectives are to quantify the magnitude and variability of denitrification in the Upper Floridan Aquifer (UFA) and evaluate its effect on N isotopic signatures at the regional scale. Using dual noble gas tracers (Ne, Ar) to generate physical predictions of N2 gas concentrations for 112 observations from 61 UFA springs, we show that excess (i.e. denitrification-derived) N2 is highly variable in space and inversely correlated with dissolved oxygen (O2). Negative relationships between O2 and δ15N NO3 across a larger dataset of 113 springs, well-constrained isotopic fractionation coefficients, and strong 15N:18O covariation further support inferences of denitrification in this uniquely organic-matter-poor system. Despite relatively low average rates, denitrification accounted for 32 % of estimated aquifer N inputs across all sampled UFA springs. Back-calculations of source δ15N NO3 based on denitrification progression suggest that isotopically-enriched nitrate (NO3-) in many springs of the UFA reflects groundwater denitrification rather than urban- or animal-derived inputs. © Author(s) 2012.

Nuclear import of Cdk/cyclin complexes: identification of distinct mechanisms for import of Cdk2/cyclin E and Cdc2/cyclin B1.

Reversible phosphorylation of nuclear proteins is required for both DNA replication and entry into mitosis. Consequently, most cyclin-dependent kinase (Cdk)/cyclin complexes are localized to the nucleus when active. Although our understanding of nuclear transport processes has been greatly enhanced by the recent identification of nuclear targeting sequences and soluble nuclear import factors with which they interact, the mechanisms used to target Cdk/cyclin complexes to the nucleus remain obscure; this is in part because these proteins lack obvious nuclear localization sequences. To elucidate the molecular mechanisms responsible for Cdk/cyclin transport, we examined nuclear import of fluorescent Cdk2/cyclin E and Cdc2/cyclin B1 complexes in digitonin-permeabilized mammalian cells and also examined potential physical interactions between these Cdks, cyclins, and soluble import factors. We found that the nuclear import machinery recognizes these Cdk/cyclin complexes through direct interactions with the cyclin component. Surprisingly, cyclins E and B1 are imported into nuclei via distinct mechanisms. Cyclin E behaves like a classical basic nuclear localization sequence-containing protein, binding to the alpha adaptor subunit of the importin-alpha/beta heterodimer. In contrast, cyclin B1 is imported via a direct interaction with a site in the NH2 terminus of importin-beta that is distinct from that used to bind importin-alpha.

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

The Adjuvant Activity and Mechanisms of Action for Mastoparan 7 Peptide After Intranasal Immunization in Mice

No

Morphological characteristics of urban water bodies: mechanisms of change and implications for ecosystem function.

The size, shape, and connectivity of water bodies (lakes, ponds, and wetlands) can have important effects on ecological communities and ecosystem processes, but how these characteristics are influenced by land use and land cover change over broad spatial scales is not known. Intensive alteration of water bodies during urban development, including construction, burial, drainage, and reshaping, may select for certain morphometric characteristics and influence the types of water bodies present in cities. We used a database of over one million water bodies in 100 cities across the conterminous United States to compare the size distributions, connectivity (as intersection with surface flow lines), and shape (as measured by shoreline development factor) of water bodies in different land cover classes. Water bodies in all urban land covers were dominated by lakes and ponds, while reservoirs and wetlands comprised only a small fraction of the sample. In urban land covers, as compared to surrounding undeveloped land, water body size distributions converged on moderate sizes, shapes toward less tortuous shorelines, and the number and area of water bodies that intersected surface flow lines (i.e., streams and rivers) decreased. Potential mechanisms responsible for changing the characteristics of urban water bodies include: preferential removal, physical reshaping or addition of water bodies, and selection of locations for development. The relative contributions of each mechanism likely change as cities grow. The larger size and reduced surface connectivity of urban water bodies may affect the role of internal dynamics and sensitivity to catchment processes. More broadly, these results illustrate the complex nature of urban watersheds and highlight the need to develop a conceptual framework for urban water bodies.

Computational inference of neural information flow networks.

Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks.