Maintenance and exchange of the aromatic amino acid pool in Escherichia coli

The pool of phenylalanine, tyrosine, and tryptophan is formed in Escherichia coli K-12 by a general aromatic transport system [Michaelis constant (K(m)) for each amino acid approximately 5 x 10(-7)m] and three further transport systems each specific for a single aromatic amino acid (K(m) for each amino acid approximately 2 x 10(-6)m, reference 3). When the external concentration of a particular aromatic amino acid is saturating for both classes of transport system, the free amino acid pool is supplied with external amino acid by both systems. Blocking the general transport system reduces the pool size by 80 to 90% but does not interfere with the supply of the amino acid to protein synthesis. If, however, the external concentration is too low to saturate specific transport, blocking general transport inhibits the incorporation of external amino acid into protein by about 75%. It is concluded that the amino acids transported by either class of transport system can be used for protein synthesis. Dilution of the external amino acid or deprivation of energy causes efflux of the aromatic pool. These results and rapid exchange observed between pool amino acid and external amino acids indicate that the aromatic pool circulates rapidly between the inside and the outside of the cell. Evidence is presented that this exchange is mediated by the aromatic transport systems. Mutation of aroP (a gene specifying general aromatic transport) inhibits exit and exchange of the small pool generated by specific transport. These findings are discussed and a simple physiological model of aromatic pool formation, and exchange, is proposed.     

Network modelling of gene regulation

Gene regulatory network (GRN) modelling has gained increasing attention in the past decade. Many computational modelling techniques have been proposed to facilitate the inference and analysis of GRN. However, there is often confusion about the aim of GRN modelling, and how a gene network model can be fully utilised as a tool for systems biology. The aim of the present article is to provide an overview of this rapidly expanding subject. In particular, we review some fundamental concepts of systems biology and discuss the role of network modelling in understanding complex biological systems. Several commonly used network modelling paradigms are surveyed with emphasis on their practical use in systems biology research.     

Mathematical models of predator/prey/plant interactions in a patch environment

Several tritrophic systems are characterized by local over-exploitation of the food source. Interactions between predatory mites, spider mites and their host plants are an example of such systems: either the spider mites over-exploit local patches of host plants or the spider mites are exterminated by predatory mites. It is often stated that modelling the overall population dynamics of such systems in a realistic way would soon lead to an unmanageable edifice. We advocate, however, the use of physiologically structured population models as a both general and formal mathematical framework. The advantage is that analytically tractable models may be obtained from the complex ‘master’ model by time-scale arguments or special choices of model ingredients. In this way a network of models can be derived, each concentrating on a particular aspect, all inadequate to cover the entire spectrum, but together (we hope) providing a coherent set of insights the relative importance of which can be assessed by computer experiments on the ‘master’ model. In this paper a rather realistic model of predator/prey interactions in an ensemble of host-plant patches is presented and, as an example of our approach, some special cases are derived from that model. Their analysis provided some first, useful insights. It is shown that prolonged duration of the prey-dispersal phase and prey dispersal from predator (-invaded prey) patches may result in a stable steady state, whereas a humped plant-production function may — under certain conditions — result in two stable steady states.     

DNA Transfection to Study Translational Control in Mammalian Cells

Mammalian cells respond to changes in their environment by rapid and reversible covalent modification of the translational machinery. In most cases, these modifications involve the phosphorylation and dephosphorylation of translation initiation factors (for review see Ref. 1). The modification of translation initiation factors may affect translational activity of either specific mRNAs or general cellular mRNAs. To study the effect of a particular factor or its modification on the translational capacity of an mRNA, there are a number of potential approaches that includein vitrotranslation reactions as well asin vivoexperiments. Generally, experiments initially report a covalent modification that correlates with altered translational capacity of either a specific or a general class of mRNAs. The modification and the particular amino acid residue involved are then identified. Then mutations are made at the modified residue to prevent modification (for example, a serine-to-alanine mutation to prevent phosphorylation) and the effect of the mutant factor on the translation of a target mRNA is tested. The most convenient method for monitoring the effect of a mutant translation factor on translation is the use of transient DNA transfection. However, in certain situations it is desirable to isolate stably transfected cell lines to study the effect of overexpression, underexpression, or expression of a particular mutant translation factor. This article reviews two methods that are routinely used to study translational control that involve either transient or stable DNA transfection.     

Superposition properties of independent ion channels

Membrane patches usually contain several ion channels of a given type. However, most of the stochastic modelling on which data analysis (in particular, estimation of kinetic constants) is currently based, relates to a single channel rather than to multiple channels. Attempts to circumvent this problem experimentally by recording under conditions where channel activity is low are restrictive and can introduce bias; moreover, possibly important information on how multichannel systems behave will be missed. We have extended existing theory to multichannel systems by applying results from point process theory to derive some distributional properties of the various types of sojourn time that occur when a given number of channels are open in a system containing a specified number of independent channels in equilibrium. Separate development of properties of a single channel and the superposition of several such independent channels simplifies the presentation of known results and extensions. To illustrate the general theory, particular attention is given to the types of sojourn time that occur in a two channel system; detailed expressions are presented for a selection of models, both Markov and non-Markov.     

Conundrums in mixed woody–herbaceous plant systems

Aims To identify approaches to improve our understanding of, and predictive capability for, mixed tree–grass systems. Elucidation of the interactions, dynamics and determinants, and identification of robust generalizations that can be broadly applied to tree–grass systems would benefit ecological theory, modelling and land management. Methods A series of workshops brought together scientific expertise to review theory, data availability, modelling approaches and key questions. Location Ecosystems characterized by mixtures of herbaceous and woody plant life‐forms, often termed ‘savannas’, range from open grasslands with few woody plants, to woodlands or forests with a grass layer. These ecosystems represent a substantial portion of the terrestrial biosphere, an important wildlife habitat, and a major resource for provision of livestock, fuel wood and other products. Results Although many concepts and principles developed for grassland and forest systems are relevant to these dual life‐form communities, the novel, complex, nonlinear behaviour of mixed tree–grass systems cannot be accounted for by simply studying or modelling woody and herbaceous components independently. A more robust understanding requires addressing three fundamental conundrums: (1) The ‘treeness’ conundrum. What controls the relative abundance of woody and herbaceous plants for a given set of conditions at given site? (2) The coexistence conundrum. How do the life‐forms interact with each other? Is a given woody–herbaceous ratio dynamically stable and persistent under a particular set of conditions? (3) The net primary productivity (NPP) conundrum. How does NPP of the woody vegetation, the herbaceous vegetation, and the total ecosystem (woody + herbaceous) change with changes in the tree–grass ratio? Tests of the theory and conceptual models of determinants of mixed woody–herbaceous systems have been largely site‐ or region‐specific and have seldom been broadly or quantitatively evaluated. Cross‐site syntheses based on data and modelling are required to address the conundrums and identify emerging patterns, yet, there are very few data sets for which either biomass or NPP have been quantified for both the woody and the herbaceous components of tree–grass systems. Furthermore, there are few cross‐site comparisons spanning the diverse array of woody–herbaceous mixtures. Hence, initial synthesis studies should focus on compiling and standardizing a global data base which could be (1) explored to ascertain if robust generalizations and consistent patterns exist; and (2) used to evaluate the performance of savanna simulation models over a range of woody–herbaceous mixtures. Savanna structure and productivity are the result of complex and dynamic interactions between climate, soils and disturbances, notably fire and herbivory. Such factors are difficult to isolate or experimentally manipulate in order to evaluate their impacts at spatial and temporal scales appropriate for assessing ecosystem dynamics. These factors can, however, be evaluated with simulation models. Existing savanna models vary markedly with respect to their conceptual approach, their data requirements and the extent to which they incorporate mechanistic processes. Model intercomparisons can elucidate those approaches most suitable for various research questions and management applications. Conclusion Theoretical and conceptual advances could be achieved by considering a broad continuum of grass–shrub–tree combinations using data meta‐analysis techniques and modelling.     

Activation of multiple oncogene pathways: a model for experimental carcinogenesis

Evidence from experimental animal tumor models suggests that in many instances, the identity and mechanism of activation of cellular oncogenes is a function of both carcinogen and tissue specificity. In addition, the activation of no single oncogene has yet been found to be either sufficient or necessary for tumorigenesis in any particular experimental system. A hypothesis to account for these and other molecular and biological observations of experimental tumorigenesis has been developed. The hypothesis is based on the premise that multiple tissue specific groups or pathways of oncogenes exist in each cell, and that activation of all the oncogenes in any of these alternative pathways leads to transformation. It is assumed that each oncogene (which may be a member of one or more pathways) has a spontaneous and a carcinogen specific probability of activation. The latter value will vary from carcinogen to carcinogen. By modelling the spontaneous and carcinogen specific probabilities of activation of each gene, the number and identity of genes in each pathway, and the number of pathways in a particular cell type, it is possible to calculate the relative potency of carcinogens, the percentage of tumors containing each activated oncogene, the dose-response relationship, and other parameters. Use of this hypothetical model gives results consistent with experimental observations on oncogene activation in carcinogen-induced animal tumors.     

Event-related functional magnetic resonance imaging: modelling, inference and optimization.

Event-related functional magnetic resonance imaging is a recent and popular technique for detecting haemodynamic responses to brief stimuli or events. However, the design of event-related experiments requires careful consideration of numerous issues of measurement, modelling and inference. Here we review these issues, with particular emphasis on the use of basis functions within a general linear modelling framework to model and make inferences about the haemodynamic response. With these models in mind, we then consider how the properties of functional magnetic resonance imaging data determine the optimal experimental design for a specific hypothesis, in terms of stimulus ordering and interstimulus interval. Finally, we illustrate various event-related models with examples from recent studies.     

Crowdsourcing a Collective Sense of Place

Place can be generally defined as a location that has been assigned meaning through human experience, and as such it is of multidisciplinary scientific interest. Up to this point place has been studied primarily within the context of social sciences as a theoretical construct. The availability of large amounts of user-generated content, e.g. in the form of social media feeds or Wikipedia contributions, allows us for the first time to computationally analyze and quantify the shared meaning of place. By aggregating references to human activities within urban spaces we can observe the emergence of unique themes that characterize different locations, thus identifying places through their discernible sociocultural signatures. In this paper we present results from a novel quantitative approach to derive such sociocultural signatures from Twitter contributions and also from corresponding Wikipedia entries. By contrasting the two we show how particular thematic characteristics of places (referred to herein as platial themes) are emerging from such crowd-contributed content, allowing us to observe the meaning that the general public, either individually or collectively, is assigning to specific locations. Our approach leverages probabilistic topic modelling, semantic association, and spatial clustering to find locations are conveying a collective sense of place. Deriving and quantifying such meaning allows us to observe how people transform a location to a place and shape its characteristics.     

Mathematical Modelling of Anaerobic Reactors Treating Domestic Wastewater: Rational Criteria for Model Use

Anaerobic digestion modelling is an established method for assessing anaerobic wastewater treatment for design, systems analysis, operational analysis, and control. Anaerobic treatment of domestic wastewater is a relatively new, but rapidly maturing technology, especially in developing countries, where the combination of low cost, and moderate-good performance are particularly attractive. The key emerging technology is high-rate anaerobic treatment, particularly UASB reactors. Systems modelling can potentially offer a number of advantages to this field, and the key motivations for modelling have been identified as operational analysis, technology development, and model-based design. Design is particularly important, as it determines capital cost, a key motivation for implementers. Published modelling studies for anaerobic domestic sewage treatment are limited in number, but well directed at specific issues. Most have a low structural complexity, with first order kinetics, as compared to the more commonly used Monod kinetics. This review addresses the use of anaerobic models in general, application of models to domestic sewage systems, and evaluates future requirements for models that need to address the key motivations of operational analysis, technology development, and model-based design. For operational analysis and technology development, a complex model such as the ADM1 is recommended, with further extensions as required to address factors such as sulphate reduction. For design, the critical issSues are hydraulics and particles (i.e., biomass and solid substrate) modelling. Therefore, the kinetic structure should be relatively simple (at least two-step), but the hydraulic and particulate model should be relatively complex.     

Physiological desensitization of carbohydrate permeases and adenylate cyclase to regulation by the phosphoenolpyruvate:sugar phosphotransferase system in Escherichia coli and Salmonella typhimurium. Involvement of adenosine cyclic 3',5'-phosphate and inducer

Adenylate cyclase and a number of carbohydrate transport systems are subject to regulation by the phosphoenolpyruvate:sugar phosphotransferase system. These sensitive carbohydrate transport systems are desensitized to regulation by the phosphotransferase system, and adenylate cyclase is deactivated when cells are grown in medium containing cyclic AMP. These effects are specific for cyclic AMP and are potentiated by the genetic loss of cyclic AMP phosphodiesterase. Inclusion in the growth medium of an inducer of a sensitive transport system also promotes desensitization of that particular transport system. Inducer-promoted desensitization is specific for the particular target transport system, while cyclic AMP-promoted desensitization is general and affects several systems. Desensitization of the permeases to regulation, and inactivation of adenylate cyclase, are slow processes which are blocked by chloramphenicol and are therefore presumably dependent on protein synthesis. Several sugar substrates of the phosphotransferase system are capable of regulating the sensitive carbohydrate transport systems. The evidence suggests that desensitization to this regulation does not result from a direct effect on the functioning of Enzyme I, a small heat-stable protein of the phosphotransferase system, HPr, or an Enzyme II of the phosphotransferase system, but specifically uncouples the permease systems from regulation.     

Community‐level vs species‐specific approaches to model selection

A topic of particular current interest is community‐level approaches to species distribution modelling (SDM), i.e. approaches that simultaneously analyse distributional data for multiple species. Previous studies have looked at the advantages of community‐level approaches for parameter estimation, but not for model selection – the process of choosing which model (and in particular, which subset of environmental variables) to fit to data. We compared the predictive performance of models using the same modelling method (generalised linear models) but choosing the subset of variables to include in the model either simultaneously across all species (community‐level model selection) or separately for each species (species‐specific model selection). Our results across two large presence/absence tree community datasets were inconclusive as to whether there was an overall difference in predictive performance between models fitted via species‐specific vs community‐level model selection. However, we found some evidence that a community approach was best suited to modelling rare species, and its performance decayed with increasing prevalence. That is, when data were sparse there was more opportunity for gains from “borrowing strength” across species via a community‐level approach. Interestingly, we also found that the community‐level approach tended to work better when the model selection problem was more difficult, and more reliably detected “noise” variables that should be excluded from the model.