Analysis of circadian pattern reveals tissue-specific alternative transcription in leptin signaling pathway

*Background*
It has been previously reported that most mammalian genes display a circadian oscillation in their baseline expression. Consequently, the phase and amplitude of each component of a signal transduction cascade has downstream consequences. 

*Results*
We report our analysis of alternative transcripts in the leptin signaling pathway which is responsible for the systemic regulation of macronutrient storage and energy balance. We focused on the circadian expression pattern of a critical component of the leptin signaling system, suppressor of cytokine signaling 3 (SOCS3). On an Affymetrix GeneChip 430A2 microarray, this gene is represented by three probe sets targeting different regions within the 3’ end of the last exon. We demonstrate that in murine brown adipose tissue two downstream 3’ probe sets experience circadian baseline oscillation in counter-phase to the upstream probe set. Such differences in expression patterns are a telltale sign of alternative splicing within the last exon of SOCS3. In contrast, all three probe sets oscillated in a common phase in murine liver and white adipose tissue. This suggests that the regulation of SOCS3 expression in brown fat is tissue specific. Another component of the signaling pathway, Janus kinase (JAK), is directly regulated by SOCS and has alternative transcript probe sets oscillating in counter-phase in a white adipose tissue specific manner.
 
*Conclusion*
We hypothesize that differential oscillation of alternative transcripts may provide a mechanism to maintain steady levels of expression in spite of circadian baseline variation

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

An isoform of Arabidopsis myosin XI interacts with small GTPases in its C-terminal tail region

Myosin XI, a class of myosins expressed in plants is believed to be responsible for cytoplasmic streaming and the translocation of organelles and vesicles. To gain further insight into the translocation of organelles and vesicles by myosin XI, an isoform of Arabidopsis myosin XI, MYA2, was chosen and its role in peroxisome targeting was examined. Using the yeast two-hybrid screening method, two small GTPases, AtRabD1 and AtRabC2a, were identified as factors that interact with the C-terminal tail region of MYA2. Both recombinant AtRabs tagged with His bound to the recombinant C-terminal tail region of MYA2 tagged with GST in a GTP-dependent manner. Furthermore, AtRabC2a was localized on peroxisomes, when its CFP-tagged form was expressed transiently in protoplasts prepared from Arabidopsis leaf tissue. It is suggested that MYA2 targets the peroxisome through an interaction with AtRabC2a

Invariant Distribution of Promoter Activities in Escherichia coli

Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources

Real-time monitoring in three-dimensional hepatocytes reveals that insulin acts as a synchronizer for liver clock

Resetting the peripheral clock and understanding the integration between the circadian rhythm and metabolic pathways are fundamental questions. To test whether insulin acts as a synchronizer for the hepatic clock by cell-autonomous mechanisms, the phase-resetting capabilities of insulin were investigated in cultured hepatic cells. We provide evidence that three-dimensional (3D) cell culture conditions that preserve the differentiated state of primary hepatocytes sustained the robustness of the molecular clock, while this robustness rapidly dampened under classical monolayer cell culture conditions. Herein, we established a 3D cell culture system coupled with a real-time luciferase reporter, and demonstrated that insulin directly regulates the phase entrainment of hepatocyte circadian oscillators. We found that insulin-deficient diabetic rats had a pronounced phase advance in their hepatic clock. Subsequently, a single administration of insulin induced phase-dependent bi-directional phase shifts in diabetic rat livers. Our results clearly demonstrate that insulin is a liver clock synchronizer

Mathematical Identification of Critical Reactions in the Interlocked Feedback Model

Dynamic simulations are necessary for understanding the mechanism of how biochemical networks generate robust properties to environmental stresses or genetic changes. Sensitivity analysis allows the linking of robustness to network structure. However, it yields only local properties regarding a particular choice of plausible parameter values, because it is hard to know the exact parameter values in vivo. Global and firm results are needed that do not depend on particular parameter values. We propose mathematical analysis for robustness (MAR) that consists of the novel evolutionary search that explores all possible solution vectors of kinetic parameters satisfying the target dynamics and robustness analysis. New criteria, parameter spectrum width and the variability of solution vectors for parameters, are introduced to determine whether the search is exhaustive. In robustness analysis, in addition to single parameter sensitivity analysis, robustness to multiple parameter perturbation is defined. Combining the sensitivity analysis and the robustness analysis to multiple parameter perturbation enables identifying critical reactions. Use of MAR clearly identified the critical reactions responsible for determining the circadian cycle in the Drosophila interlocked circadian clock model. In highly robust models, while the parameter vectors are greatly varied, the critical reactions with a high sensitivity are uniquely determined. Interestingly, not only the per-tim loop but also the dclk-cyc loop strongly affect the period of PER, although the dclk-cyc loop hardly changes its amplitude and it is not potentially influential. In conclusion, MAR is a powerful method to explore wide parameter space without human-biases and to link a robust property to network architectures without knowing the exact parameter values. MAR identifies the reactions critically responsible for determining the period and amplitude in the interlocked feedback model and suggests that the circadian clock intensively evolves or designs the kinetic parameters so that it creates a highly robust cycle

Potential conservation of circadian clock proteins in the phylum Nematoda as revealed by bioinformatic searches

Although several circadian rhythms have been described in C. elegans, its molecular clock remains elusive. In this work we employed a novel bioinformatic approach, applying probabilistic methodologies, to search for circadian clock proteins of several of the best studied circadian model organisms of different taxa (Mus musculus, Drosophila melanogaster, Neurospora crassa, Arabidopsis thaliana and Synechoccocus elongatus) in the proteomes of C. elegans and other members of the phylum Nematoda. With this approach we found that the Nematoda contain proteins most related to the core and accessory proteins of the insect and mammalian clocks, which provide new insights into the nematode clock and the evolution of the circadian system.Fil: Romanowski, Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; ArgentinaFil: Garavaglia, Matías Javier. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Ing.genética y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Goya, María Eugenia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ghiringhelli, Pablo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Ing.genética y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Golombek, Diego Andres. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Regulation of Clock-Controlled Genes in Mammals

The complexity of tissue- and day time-specific regulation of thousands of clock-controlled genes (CCGs) suggests that many regulatory mechanisms contribute to the transcriptional output of the circadian clock. We aim to predict these mechanisms using a large scale promoter analysis of CCGs

Time-Course Analysis of Cyanobacterium Transcriptome: Detecting Oscillatory Genes

The microarray technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining these data one can identify the dynamics of the gene expression time series. The detection of genes that are periodically expressed is an important step that allows us to study the regulatory mechanisms associated with the circadian cycle. The problem of finding periodicity in biological time series poses many challenges. Such challenge occurs due to the fact that the observed time series usually exhibit non-idealities, such as noise, short length, outliers and unevenly sampled time points. Consequently, the method for finding periodicity should preferably be robust against such anomalies in the data. In this paper, we propose a general and robust procedure for identifying genes with a periodic signature at a given significance level. This identification method is based on autoregressive models and the information theory. By using simulated data we show that the suggested method is capable of identifying rhythmic profiles even in the presence of noise and when the number of data points is small. By recourse of our analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis