From Genes to Flower Patterns and Evolution: Dynamic Models of Gene Regulatory Networks

Genes and proteins form complex dynamical systems or gene regulatory networks (GRN) that can reach several steady states (attractors). These may be associated with distinct cell types. In plants, the ABC combinatorial model establishes the necessary gene combinations for floral organ cell specification. We have developed dynamic gene regulatory network (GRN) models to understand how the combinatorial selection of gene activity is established during floral organ primordia specification as a result of the concerted action of ABC and non-ABC genes. Our analyses have shown that the floral organ specification GRN reaches six attractors with gene configurations observed in primordial cell types during early stages of flower development and four that correspond to regions of the inflorescence meristem. This suggests that it is the overall GRN dynamics rather than precise signals that underlie the ABC model. Furthermore, our analyses suggest that the steady states of the GRN are robust to random alterations of the logical functions that define the gene interactions. Here we have updated the GRN model and have systematically altered the outputs of all the logical functions and addressed in which cases the original attractors are recovered. We then reduced the original three-state GRN to a two-state (Boolean) GRN and performed the same systematic perturbation analysis. Interestingly, the Boolean GRN reaches the same number and type of attractors as reached by the three-state GRN, and it responds to perturbations in a qualitatively identical manner as the original GRN. These results suggest that a Boolean model is sufficient to capture the dynamical features of the floral network and provide additional support for the robustness of the floral GRN. These findings further support that the GRN model provides a dynamical explanation for the ABC model and that the floral GRN robustness could be behind the widespread conservation of the floral plan among eudicotyledoneous plants. Other aspects of evolution of flower organ arrangement and ABC gene expression patterns are discussed in the context of the approach proposed here. álvaro Chaos, Max Aldana and Elena Alvarez-Buylla contributed equally to this work.     

On open access and optimal landings tax

This paper develops two types of simple models on the dynamic interaction between the stock of fish and the effort expended by fishers: continuous-time/discrete-time models in which a landings tax is incorporated as a control variable available to the management authority. The continuous-time model can describe several ideal options of the optimal tax program; however, unfortunately, it is incapable of choosing the best option. Hence, using the alternative tractable discrete-time model and a computational method, the remaining task of determining a unique optimal tax program is accomplished. The fishery thus managed exhibits a regulated open access.     

Distributed moment histogram: A neurophysiology based method of agonist and antagonist trunk muscle activity prediction

A neurocortical-based technique of muscle recruitment is presented to solve the muscle indeterminacy problem for lumbar torso modeling. Cortical recordings from behaving primates have established motor cortex cells that respond to a wide range of task directions, but are tuned to a preferred direction. A characteristic activity pattern of these neurons seems to be associated with effort direction. It was hypothesized that a model which recruits muscles based on a similar distribution would predict antagonistic muscle activity with greater realism than a widely referenced optimization formulation. The predictions of the Distributed Moment Histogram (DMH) method were evaluated under common speed (<30^os⁻¹) sagittal plane lifting conditions using five subjects. The predicted forces showed high correspondence with agonist and antagonist myoelectric patterns. The mean coefficient of determination for the erector spinae was r²=0.91, and 0.41 for the latissimus. For the antagonistic muscles, the rectus abdominus was found to be electrically silent (<3% MVC) and no activity was predicted by the method. The external oblique muscle was observed to be minimally active (<16% MVC), and the DMH method predicted its mostly constant activity with a mean standard error of 1.6% MVC. The realistic antagonistic predictions supported the hypothesis and justify this cortical based technique as an alternative for muscle tension estimation in biomechanical torso modeling. A primary advantage of this method is its computational simplicity and direct physiologic analogy     

Dynamic control in metabolic engineering: Theories,tools, and applications

Metabolic engineering has allowed the production of a diverse number of valuable chemicals using microbial organisms. Many biological challenges for improving bio-production exist which limit performance and slow the commercialization of metabolically engineered systems. Dynamic metabolic engineering is a rapidly developing field that seeks to address these challenges through the design of genetically encoded metabolic control systems which allow cells to autonomously adjust their flux in response to their external and internal metabolic state. This review first discusses theoretical works which provide mechanistic insights and design choices for dynamic control systems including two-stage, continuous, and population behavior control strategies. Next, we summarize molecular mechanisms for various sensors and actuators which enable dynamic metabolic control in microbial systems. Finally, important applications of dynamic control to the production of several metabolite products are highlighted, including fatty acids, aromatics, and terpene compounds. Altogether, this review provides a comprehensive overview of the progress, advances, and prospects in the design of dynamic control systems for improved titer, rate, and yield metrics in metabolic engineering.     

Predators and mutualists influence the exclusion of aphid species from natural communities

We investigated why two species of aphids (Aphis jacobaeae and Brachycaudus cardui) were very rare in a study site despite their abundance in the surrounding area. The study site contained many common species of aphid and we tested the hypothesis that the community of aphid predators in the field excluded the missing species. Colonies of the two aphid species were artificially initiated in the experimental site and allocated to one of four treatments: control; ground predator exclusion; total predator exclusion, and provision of mutualist ants. Two measures of colony performance were analysed: longevity and cumulative aphid density. Colonies decline naturally in late summer but control colonies disappeared very quickly while colonies protected from all predators survived the longest. The performance of colonies protected from just ground predators was intermediate. We failed to persuade ants to tend A. jacobaeae. Colonies of B. cardui attended by ants performed better than controls and those with ground predators excluded, but not as well as those with all predators excluded. We conclude that the absence of the two species of aphid in the study site is influenced by the resident predator community, and by the availability of mutualists. Received: 27 April 1998 / Accepted: 30 November 1998     

Adaptive bolus-chasing computed tomography angiography in the cases of symmetric and asymmetric arterial flows in peripheral arteries

Synchronization of the contrast bolus peak and CT imaging aperture is a crucial issue for computed tomography angiography (CTA). It affects the CTA image quality and the amount of contrast dose. A whole-body CTA procedure means to scan from the abdominal aorta to pedal arteries. In this context, the synchronization is much more difficult with the asymmetric arterial flow in lower extremities than in the case of symmetric arterial flow. In this paper, we propose an adaptive optimal controller to chase the contrast bolus peak while it propagates in the aorta and lower extremities with symmetric flow. In the case of asymmetric flow after the contrast bolus splitting into two lower limbs, we propose a dynamic programming approach to cover the lower limbs optimally. Simulation and experimental results show that the proposed methods outperform the current constant-speed method substantially.     

Dynamic consolidated bioprocessing for direct production of xylonate and shikimate from xylan by Escherichia coli

Numerous value-added chemicals can be produced using xylan as a feedstock. However, the product yields are limited by low xylan utilization efficiency, as well as by carbon flux competition between biomass production and biosynthesis. Herein, a dynamic consolidated bioprocessing strategy was developed, which coupled xylan utilization and yield optimization modules. Specifically, we achieved the efficient conversion of xylan to valuable chemicals in a fully consolidated manner by optimizing the expression level of xylanases and xylose transporter in the xylan utilization module. Moreover, a cell density-dependent, and Cre-triggered dynamic system that enabled the dynamic decoupling of biosynthesis and biomass production was constructed in the yield optimization module. The final shake flask-scale titers of xylonate, produced through an exogenous pathway, and shikimate, produced through an endogenous pathway, reached 16.85 and 3.2 g L⁻¹, respectively. This study not only provides an efficient microbial platform for the utilization of xylan, but also opens up the possibility for the large-scale production of high value-added chemicals from renewable feedstocks.     

Contrasting roles of dynamics in protein allostery: NMR and structural studies of CheY and the third PDZ domain from PSD-95

Allosteric regulation is a ubiquitous phenomenon exploited in biological processes to control cells in a myriad of ways. It is also of emerging interest in the design of functional proteins and therapeutics. Even though allostery was proposed over 50 years ago and has been studied intensively from a structural perspective, many key details of allosteric mechanisms remain mysterious. Over the last decade significant attention has been paid to the “dynamic component” of allostery, as opposed to the analysis of rigid structures. Nuclear magnetic resonance spectroscopy and its ability to detect conformationally dynamic processes at atomic resolution have played an important role in expanding our understanding of allosteric mechanisms and opening up new questions. This article focuses on work that highlights how protein dynamics can factor into allosteric processes in distinct ways. Two cases are contrasted. The first considers the “traditionally allosteric” protein CheY, which undergoes a conformational change as a key element of its allostery. The second considers the more rarely observed “dynamic allostery” in a PDZ domain, in which allosteric behavior arises from changes in internal structural dynamics. Interestingly, the dynamic processes in these two contrasting examples occur on different timescales. In the case of the PDZ domain, subsequent experimental and computational work is reviewed to reveal a more complete picture of this interesting case of allostery.     

Global Kinetic Explorer: A new computer program for dynamic simulation and fitting of kinetic data

We describe a new dynamic kinetic simulation program that allows multiple data sets to be fit simultaneously to a single model based on numerical integration of the rate equations describing the reaction mechanism. Unlike other programs that allow fitting based on numerical integration of rate equations, in the dynamic simulation rate constants, output factors, and starting concentrations of reactants can be scrolled while observing the change in the shape of the simulated reaction curves. Fast dynamic simulation facilitates the exploration of initial parameters that serve as the starting point for nonlinear regression in fitting data and facilitates exploration of the relationships between individual constants and observable reactions. The exploration of parameter space by dynamic simulation provides a powerful tool for learning kinetics and for evaluating the extent to which parameters are constrained by the data. This feature is critical to avoid overly complex models that are not supported by the data.