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The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra) study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology. [ABSTRACT FROM AUTHOR]

Stochasticity inherent to biochemical reactions (intrinsic noise) and variability in cellular states (extrinsic noise) degrade information transmitted through signaling networks. We analyzed the ability of temporal signal modulation--that is, dynamics--to reduce noise-induced information loss. In the extracellular signal-regulated kinase (ERK), calcium (Ca2+), and nuclear factor kappa-B (NF-κB) pathways, response dynamics resulted in significantly greater information transmission capacities compared to nondynamic responses. Theoretical analysis demonstrated that signaling dynamics has a key role in overcoming extrinsic noise. Experimental measurements of information transmission in the ERK network under varying signal-to-noise levels confirmed our predictions and showed that signaling dynamics mitigate, and can potentially eliminate, extrinsic noise-induced information loss. By curbing the information-degrading effects of cell-to-cell variability, dynamic responses substantially increase the accuracy of biochemical signaling networks. [ABSTRACT FROM AUTHOR]

One promise of synthetic biology is the creation of genetic circuitry that enables the execution of logical programming in living cells. Such 'wet programming' is positioned to transform a wide and diverse swathe of biotechnology ranging from therapeutics and diagnostics to water treatment strategies. Although progress in the development of a library of genetic modules continues apace, a major challenge for their integration into larger circuits is the generation of sufficiently fast and precise communication between modules. An attractive approach is to integrate engineered circuits with host processes that facilitate robust cellular signalling. In this context, recent studies have demonstrated that bacterial protein degradation can trigger a precise response to stress by overloading a limited supply of intracellular proteases. Here we use protease competition to engineer rapid and tunable coupling of genetic circuits across multiple spatial and temporal scales. We characterize coupling delay times that are more than an order of magnitude faster than standard transcription-factor-based coupling methods (less than 1 min compared with ∼20-40 min) and demonstrate tunability through manipulation of the linker between the protein and its degradation tag. We use this mechanism as a platform to couple genetic clocks at the intracellular and colony level, then synchronize the multi-colony dynamics to reduce variability in both clocks. We show how the coupled clock network can be used to encode independent environmental inputs into a single time series output, thus enabling frequency multiplexing (information transmitted on a common channel by distinct frequencies) in a genetic circuit context. Our results establish a general framework for the rapid and tunable coupling of genetic circuits through the use of native 'queueing' processes such as competitive protein degradation. [ABSTRACT FROM AUTHOR]

Many cellular stress-responsive signaling systems exhibit highly dynamic behavior with oscillatory features mediated by delayed negative feedback loops. What remains unclear is whether oscillatory behavior is the basis for a signaling code based on frequency modulation (FM) or whether the negative feedback control modules have evolved to fulfill other functional requirements. Here, we use experimentally calibrated computational models to interrogate the negative feedback loops that regulate the dynamic activity of the transcription factor NF-B. Linear stability analysis of the model shows that oscillatory frequency is a hard-wired feature of the primary negative feedback loop and not a function of the stimulus, thus arguing against an FM signaling code. Instead, our modeling studies suggest that the two feedback loops may be tuned to provide for rapid activation and inactivation capabilities for transient input signals of a wide range of durations; by minimizing late phase oscillations response durations may be fine-tuned in a graded rather than quantized manner. Further, in the presence of molecular noise the dual delayed negative feedback system minimizes stochastic excursions of the output to produce a robust NF-B response. [ABSTRACT FROM AUTHOR]

A mechanistic understanding of gene regulatory network dynamics requires quantitative single-cell data of multiple network components in response to well-defined perturbations. Recent advances in the development of fluorescent biomarkers for proteins, detection of RNA and interactions, microfluidic technology, and high-resolution imaging have set the stage for a host of new studies that elucidate the important roles of stochasticity and cell–cell variability in response to external perturbations. In this review, we briefly describe methods for high-resolution visualization and the control of gene expression, along with application of these novel methods to recent studies involving gene networks. [ABSTRACT FROM AUTHOR]

Cell membranes are dynamic structures found in all living organisms. There have been numerous constructs that model phospholipid membranes. However, unlike natural membranes, these biomimetic systems cannot sustain growth owing to an inability to replenish phospholipid-synthesizing catalysts. Here we report on the design and synthesis of artificial membranes embedded with synthetic, self-reproducing catalysts capable of perpetuating phospholipid bilayer formation. Replacing the complex biochemical pathways used in nature with an autocatalyst that also drives lipid synthesis leads to the continual formation of triazole phospholipids and membrane-bound oligotriazole catalysts from simpler starting materials. In addition to continual phospholipid synthesis and vesicle growth, the synthetic membranes are capable of remodeling their physical composition in response to changes in the environment by preferentially incorporating specific precursors. These results demonstrate that complex membranes capable of indefinite self-synthesis can emerge when supplied with simpler chemical building blocks. [ABSTRACT FROM AUTHOR]

Summary Background The cyanobacterial circadian clock system has been extensively studied, and the structures, interactions, and biochemical activities of the central oscillator proteins (KaiA, KaiB, and KaiC) have been well elucidated. Despite this rich repository of information, little is known about the distribution of these proteins within the cell. Results Here we report that KaiA and KaiC localize as discrete foci near a single pole of cells in a clock-dependent fashion, with enhanced polar localization observed at night. KaiA localization is dependent on KaiC; consistent with this notion, KaiA and KaiC colocalize with each other, as well as with CikA, a key input and output factor previously reported to display unipolar localization. The molecular mechanism that localizes KaiC to the poles is conserved in Escherichia coli , another Gram-negative rod-shaped bacterium, suggesting that KaiC localization is not dependent on other clock- or cyanobacterial-specific factors. Moreover, expression of CikA mutant variants that distribute diffusely results in the striking delocalization of KaiC. Conclusions This work shows that the cyanobacterial circadian system undergoes a circadian orchestration of subcellular organization. We propose that the observed spatiotemporal localization pattern represents a novel layer of regulation that contributes to the robustness of the clock by facilitating protein complex formation and synchronizing the clock with environmental stimuli. [ABSTRACT FROM AUTHOR]

Biological clocks are self-sustained oscillators that adjust their phase to the daily environmental cycles in a process known as entrainment. Molecular dissection and mathematical modeling of biological oscillators have progressed quite far, but quantitative insights on the entrainment of clocks are relatively sparse. We simultaneously tracked the phases of hundreds of synthetic genetic oscillators relative to a common external stimulus to map the entrainment regions predicted by a detailed model of the clock. Synthetic oscillators were frequency-locked in wide intervals of the external period and showed higher-order resonance. Computational simulations indicated that natural oscillators may contain a positive-feedback loop to robustly adapt to environmental cycles. [ABSTRACT FROM AUTHOR]