Analysis of Gene Regulatory Networks in the Mammalian Circadian Rhythm

Circadian rhythm is fundamental in regulating a wide range of cellular, metabolic, physiological, and behavioral activities in mammals. Although a small number of key circadian genes have been identified through extensive molecular and genetic studies in the past, the existence of other key circadian genes and how they drive the genomewide circadian oscillation of gene expression in different tissues still remains unknown. Here we try to address these questions by integrating all available circadian microarray data in mammals. We identified 41 common circadian genes that showed circadian oscillation in a wide range of mouse tissues with a remarkable consistency of circadian phases across tissues. Comparisons across mouse, rat, rhesus macaque, and human showed that the circadian phases of known key circadian genes were delayed for 4–5 hours in rat compared to mouse and 8–12 hours in macaque and human compared to mouse. A systematic gene regulatory network for the mouse circadian rhythm was constructed after incorporating promoter analysis and transcription factor knockout or mutant microarray data. We observed the significant association of cis-regulatory elements: EBOX, DBOX, RRE, and HSE with the different phases of circadian oscillating genes. The analysis of the network structure revealed the paths through which light, food, and heat can entrain the circadian clock and identified that NR3C1 and FKBP/HSP90 complexes are central to the control of circadian genes through diverse environmental signals. Our study improves our understanding of the structure, design principle, and evolution of gene regulatory networks involved in the mammalian circadian rhythm

A stochastic local search algorithm with adaptive acceptance for high-school timetabling

Automating high school timetabling is a challenging task. This problem is a well known hard computational problem which has been of interest to practitioners as well as researchers. High schools need to timetable their regular activities once per year, or even more frequently. The exact solvers might fail to find a solution for a given instance of the problem. A selection hyper-heuristic can be defined as an easy-to-implement, easy-to-maintain and effective 'heuristic to choose heuristics' to solve such computationally hard problems. This paper describes the approach of the team hyper-heuristic search strategies and timetabling (HySST) to high school timetabling which competed in all three rounds of the third international timetabling competition. HySST generated the best new solutions for three given instances in Round 1 and gained the second place in Rounds 2 and 3. It achieved this by using a fairly standard stochastic search method but significantly enhanced by a selection hyper-heuristic with an adaptive acceptance mechanism. © 2014 Springer Science+Business Media New York

Quantum Criticality in Heavy Fermion Metals

Quantum criticality describes the collective fluctuations of matter undergoing a second-order phase transition at zero temperature. Heavy fermion metals have in recent years emerged as prototypical systems to study quantum critical points. There have been considerable efforts, both experimental and theoretical, which use these magnetic systems to address problems that are central to the broad understanding of strongly correlated quantum matter. Here, we summarize some of the basic issues, including i) the extent to which the quantum criticality in heavy fermion metals goes beyond the standard theory of order-parameter fluctuations, ii) the nature of the Kondo effect in the quantum critical regime, iii) the non-Fermi liquid phenomena that accompany quantum criticality, and iv) the interplay between quantum criticality and unconventional superconductivity.Comment: (v2) 39 pages, 8 figures; shortened per the editorial mandate; to appear in Nature Physics. (v1) 43 pages, 8 figures; Non-technical review article, intended for general readers; the discussion part contains more specialized topic

Prader-Willi syndrome: A primer for clinicians

The advent of sensitive genetic testing modalities for the diagnosis of Prader-Willi syndrome has helped to define not only the phenotypic features of the syndrome associated with the various genotypes but also to anticipate clinical and psychological problems that occur at each stage during the life span. With advances in hormone replacement therapy, particularly growth hormone children born in circumstances where therapy is available are expected to have an improved quality of life as compared to those born prior to growth hormone

On How Network Architecture Determines the Dominant Patterns of Spontaneous Neural Activity

In the absence of sensory stimulation, neocortical circuits display complex patterns of neural activity. These patterns are thought to reflect relevant properties of the network, including anatomical features like its modularity. It is also assumed that the synaptic connections of the network constrain the repertoire of emergent, spontaneous patterns. Although the link between network architecture and network activity has been extensively investigated in the last few years from different perspectives, our understanding of the relationship between the network connectivity and the structure of its spontaneous activity is still incomplete. Using a general mathematical model of neural dynamics we have studied the link between spontaneous activity and the underlying network architecture. In particular, here we show mathematically how the synaptic connections between neurons determine the repertoire of spatial patterns displayed in the spontaneous activity. To test our theoretical result, we have also used the model to simulate spontaneous activity of a neural network, whose architecture is inspired by the patchy organization of horizontal connections between cortical columns in the neocortex of primates and other mammals. The dominant spatial patterns of the spontaneous activity, calculated as its principal components, coincide remarkably well with those patterns predicted from the network connectivity using our theory. The equivalence between the concept of dominant pattern and the concept of attractor of the network dynamics is also demonstrated. This in turn suggests new ways of investigating encoding and storage capabilities of neural networks

Selective C-Rel Activation via Malt1 Controls Anti-Fungal TH-17 Immunity by Dectin-1 and Dectin-2

C-type lectins dectin-1 and dectin-2 on dendritic cells elicit protective immunity against fungal infections through induction of TH1 and TH-17 cellular responses. Fungal recognition by dectin-1 on human dendritic cells engages the CARD9-Bcl10-Malt1 module to activate NF-κB. Here we demonstrate that Malt1 recruitment is pivotal to TH-17 immunity by selective activation of NF-κB subunit c-Rel, which induces expression of TH-17-polarizing cytokines IL-1β and IL-23p19. Malt1 inhibition abrogates c-Rel activation and TH-17 immunity to Candida species. We found that Malt1-mediated activation of c-Rel is similarly essential to induction of TH-17-polarizing cytokines by dectin-2. Whereas dectin-1 activates all NF-κB subunits, dectin-2 selectively activates c-Rel, signifying a specialized TH-17-enhancing function for dectin-2 in anti-fungal immunity by human dendritic cells. Thus, dectin-1 and dectin-2 control adaptive TH-17 immunity to fungi via Malt1-dependent activation of c-Rel

Defining the Plasticity of Transcription Factor Binding Sites by Deconstructing DNA Consensus Sequences: The PhoP-Binding Sites among Gamma/Enterobacteria

Transcriptional regulators recognize specific DNA sequences. Because these sequences are embedded in the background of genomic DNA, it is hard to identify the key cis-regulatory elements that determine disparate patterns of gene expression. The detection of the intra- and inter-species differences among these sequences is crucial for understanding the molecular basis of both differential gene expression and evolution. Here, we address this problem by investigating the target promoters controlled by the DNA-binding PhoP protein, which governs virulence and Mg2+ homeostasis in several bacterial species. PhoP is particularly interesting; it is highly conserved in different gamma/enterobacteria, regulating not only ancestral genes but also governing the expression of dozens of horizontally acquired genes that differ from species to species. Our approach consists of decomposing the DNA binding site sequences for a given regulator into families of motifs (i.e., termed submotifs) using a machine learning method inspired by the “Divide & Conquer” strategy. By partitioning a motif into sub-patterns, computational advantages for classification were produced, resulting in the discovery of new members of a regulon, and alleviating the problem of distinguishing functional sites in chromatin immunoprecipitation and DNA microarray genome-wide analysis. Moreover, we found that certain partitions were useful in revealing biological properties of binding site sequences, including modular gains and losses of PhoP binding sites through evolutionary turnover events, as well as conservation in distant species. The high conservation of PhoP submotifs within gamma/enterobacteria, as well as the regulatory protein that recognizes them, suggests that the major cause of divergence between related species is not due to the binding sites, as was previously suggested for other regulators. Instead, the divergence may be attributed to the fast evolution of orthologous target genes and/or the promoter architectures resulting from the interaction of those binding sites with the RNA polymerase

Estimating the Fitness Cost of Escape from HLA Presentation in HIV-1 Protease and Reverse Transcriptase

Human immunodeficiency virus (HIV-1) is, like most pathogens, under selective pressure to escape the immune system of its host. In particular, HIV-1 can avoid recognition by cytotoxic T lymphocytes (CTLs) by altering the binding affinity of viral peptides to human leukocyte antigen (HLA) molecules, the role of which is to present those peptides to the immune system. It is generally assumed that HLA escape mutations carry a replicative fitness cost, but these costs have not been quantified. In this study, we assess the replicative cost of mutations which are likely to escape presentation by HLA molecules in the region of HIV-1 protease and reverse transcriptase. Specifically, we combine computational approaches for prediction of in vitro replicative fitness and peptide binding affinity to HLA molecules. We find that mutations which impair binding to HLA-A molecules tend to have lower in vitro replicative fitness than mutations which do not impair binding to HLA-A molecules, suggesting that HLA-A escape mutations carry higher fitness costs than non-escape mutations. We argue that the association between fitness and HLA-A binding impairment is probably due to an intrinsic cost of escape from HLA-A molecules, and these costs are particularly strong for HLA-A alleles associated with efficient virus control. Counter-intuitively, we do not observe a significant effect in the case of HLA-B, but, as discussed, this does not argue against the relevance of HLA-B in virus control. Overall, this article points to the intriguing possibility that HLA-A molecules preferentially target more conserved regions of HIV-1, emphasizing the importance of HLA-A genes in the evolution of HIV-1 and RNA viruses in general

Toward a Comprehensive Approach to the Collection and Analysis of Pica Substances, with Emphasis on Geophagic Materials

Pica, the craving and subsequent consumption of non-food substances such as earth, charcoal, and raw starch, has been an enigma for more than 2000 years. Currently, there are little available data for testing major hypotheses about pica because of methodological limitations and lack of attention to the problem.In this paper we critically review procedures and guidelines for interviews and sample collection that are appropriate for a wide variety of pica substances. In addition, we outline methodologies for the physical, mineralogical, and chemical characterization of these substances, with particular focus on geophagic soils and clays. Many of these methods are standard procedures in anthropological, soil, or nutritional sciences, but have rarely or never been applied to the study of pica.Physical properties of geophagic materials including color, particle size distribution, consistency and dispersion/flocculation (coagulation) should be assessed by appropriate methods. Quantitative mineralogical analyses by X-ray diffraction should be made on bulk material as well as on separated clay fractions, and the various clay minerals should be characterized by a variety of supplementary tests. Concentrations of minerals should be determined using X-ray fluorescence for non-food substances and inductively coupled plasma-atomic emission spectroscopy for food-like substances. pH, salt content, cation exchange capacity, organic carbon content and labile forms of iron oxide should also be determined. Finally, analyses relating to biological interactions are recommended, including determination of the bioavailability of nutrients and other bioactive components from pica substances, as well as their detoxification capacities and parasitological profiles.This is the first review of appropriate methodologies for the study of human pica. The comprehensive and multi-disciplinary approach to the collection and analysis of pica substances detailed here is a necessary preliminary step to understanding the nutritional enigma of non-food consumption