The role of enzyme compartmentalization on the regulation of steroid synthesis.

Steroidogenic enzymes can be compartmentalized at different levels, some by virtue of being membrane bound in specific intra-cellular compartments. Although both 3ß-hydroxysteroid dehydrogenase/Δ(5)-Δ(4) isomerase (3ß-HSD) and 17α-hydroxylase/17,20-lyase cytochrome P450 (P450c17) are expressed in the endoplasmic reticulum (ER) membrane, these proteins may still be spatially separated within this membrane system. Side chain cleavage cytochrome P450 (P450scc) is anchored to the inner mitochondrial membrane and this organelle is the major source of pregnenolone (P5) feeding steroidogenesis. Furthermore, steroidogenic enzymes can also be partitioned in different cells. Although well recognized, the effect of enzyme compartmentalization on the rate of steroid production and the balance of different steroids is unclear. This study uses mathematical modeling to investigate the effect of enzyme compartmentalization on steroid synthesis in a human-ovine-bovine model of steroid synthesis. The study shows that the spatial separation of steroidogenic enzymes within the ER has a minimal effect on the rate of steroid synthesis. The compartmentalization of the enzymes into different organelles of a cell creates cellular steroid gradients and can affect the balance of the different steroid products. The partitioning of steroidogenic enzymes in different cells reduces the rate of steroid synthesis. The greater is the distance between the cells that contain different enzymes, the more the rate of steroid synthesis is reduced. Additionally, when 3ß-HSD is not in the same cell with P450scc (the P5 source) and P450c17, the ratio of the Δ(5)-pathway products' concentrations to the Δ(4)-pathway products' concentrations is increased. However, none of these levels of compartmentalization of steroidogenic enzymes alter the qualitative behaviors of steroid synthesis in response to variation in an enzyme activity or P5 supply.

Multilevel regulation of steroid synthesis and metabolism in the bovine placenta.

Steroid hormones play critical roles in almost all physiological processes in male and female reproduction. In a normal pregnancy, the concentrations of steroid hormones in maternal and foetal blood vary with gestation in response to changing needs. The placenta plays a central role in producing the appropriate steroids to support the pregnancy by coordinating its own steroidogenic activity with that of the corpus luteum and responding to foetal signals. Although much is known about the steroidogenic potential of the bovine placenta, far less is known about how the placenta integrates the synthesis of steroids with their subsequent metabolism and clearance to achieve appropriate local and peripheral concentrations of steroids in maternal and foetal blood at each stage of gestation. This review focuses on the current knowledge of the temporal and spatial regulation and compartmentalization of the biochemical pathways by which potent steroid hormones are synthesized and metabolized in the bovine placenta. The aim is to increase our understanding of how the balance of synthesis and metabolism determines placental steroid output as it changes with development and differentiation, and how this is regulated in response to the variations in the foetal signals and luteal secretory activity. The review highlights knowledge gaps and suggests that mathematical modelling can help understand the effect of different levels of regulation on the steroidogenic output of an organ, such as the bovine placenta.

Post-term birth is associated with greater risk of obesity in adolescent males.

OBJECTIVE: To test the hypothesise that post-term birth (>42 weeks gestation) adversely affects longitudinal growth and weight gain throughout childhood. STUDY DESIGN: A total of 525 children (including 17 boys and 20 girls born post-term) were followed from birth to age 16 years. Weight and height were recorded prospectively throughout childhood, and respective velocities from birth to end of puberty were calculated using a mathematical model. RESULTS: At birth, post-term girls were slimmer than term girls (ponderal index, 27.7 ± 2.6 kg/m(3) vs 26.3 ± 2.8 kg/m(3); P<.05). At age 16 years, post-term boys were 11.8 kg heavier than term subjects (body mass index [BMI], 25.4 ± 5.5 kg/m(2) vs 21.7 ± 3.1 kg/m(2); P<.01). The rate of obesity was 29% in post-term boys and 7% in term boys (P<.01), and the combined rate of overweight and obesity was 47% in post-term boys and 13% in term boys (P<.01). Weight velocity, but not height velocity, was higher in post-term boys at age 1.5-7 years (P<.05) and again at age 11.5-16 years (P<.05). BMI was higher in post-term boys at age 3 years, with the difference increasing thereafter. BMI and growth were similar in post-term and term girls. CONCLUSION: In this post-term birth cohort, boys, but not girls, demonstrated accelerated weight gain during childhood, leading to greater risk of obesity in adolescence.

Variation in 3ß-hydroxysteroid dehydrogenase activity and in pregnenolone supply rate can paradoxically alter androstenedione synthesis.

The 3ß-hydroxysteroid dehydrogenase/Δ(5)-Δ(4) isomerase (3ß-HSD) and 17α-hydroxylase/17,20-lyase cytochrome P450 (P450c17) enzymes are important in determining the balance of the synthesis of different steroids such as progesterone (P4), glucocorticoids, androgens, and estrogens. How this is achieved is not a simple matter because each of the two enzymes utilizes more than one substrate and some substrates are shared in common between the two enzymes. The two synthetic pathways, Δ(4) and Δ(5), are interlinked such that it is difficult to predict how the synthesis of each steroid changes when any of the enzyme activities is varied. In addition, the P450c17 enzyme exhibits different substrate specificities among species, particularly with respect to the 17,20-lyase activity. The mathematical model developed in this study simulates the network of reactions catalyzed by 3ß-HSD and P450c17 that characterizes steroid synthesis in human, non-human primate, ovine, and bovine species. In these species, P450c17 has negligible 17,20-lyase activity with the Δ(4)-steroid 17α-hydroxy-progesterone (17OH-P4); therefore androstenedione (A4) is synthesized efficiently only from dehydroepiandrosterone (DHEA) through the Δ(5) pathway. The model helps to understand the interplay between fluxes through the Δ(4) and Δ(5) pathways in this network, and how this determines the response of steroid synthesis to the variation in 3ß-HSD activity or in the supply of the precursor substrate, pregnenolone (P5). The model simulations show that A4 synthesis can change paradoxically when 3ß-HSD activity is varied. A decrease in 3ß-HSD activity to a certain point can increase A4 synthesis by favouring metabolism through the Δ(5) pathway, though further decrease in 3ß-HSD activity beyond that point eventually limits A4 synthesis. The model also showed that due to the competitive inhibition of the enzymes' activities by substrates and products, increasing the rate of P5 supply above a certain point can suppress the synthesis of A4, DHEA, and 17OH-P4, and consequently drive more P5 towards P4 synthesis.

Bacterial biofilms associated with food particles in the human large bowel.

Bacteria within the gastro-intestinal tract affect host function via production of short-chain fatty acids and synthesis of vitamins. Additionally, the commensal enteric bacteria modulate the immune system and provide protection from potentially pathogenic bacteria. Only recently heterogeneous bacterial biofilms were found to be associated with food particles within the intestinal tract. There are a number of studies investigating the formation and function of pathogenic and single-species biofilms, though few studies have investigated the dynamics of multispecies biofilms, especially with regard to food/microbial/host interactions. The scope of this review is to discuss the current knowledge of bacterial biofilms associated with food particles in the human large bowel, examine the established mathematical models depicting bacterial attachment, and elucidate key areas for further research.

Using existing data to predict and quantify the risks of GM forage to a population of a non-target invertebrate species: a New Zealand case study.

Determining the effects of genetically modified (GM) crops on non-target organisms is essential as many non-target species provide important ecological functions. However, it is simply not possible to collect field data on more than a few potential non-target species present in the receiving environment of a GM crop. While risk assessment must be rigorous, new approaches are necessary to improve the efficiency of the process. Utilisation of published information and existing data on the phenology and population dynamics of test species in the field can be combined with limited amounts of experimental biosafety data to predict possible outcomes on species persistence. This paper presents an example of an approach where data from laboratory experiments and field studies on phenology are combined using predictive modelling. Using the New Zealand native weevil species Nicaeana cervina as a case study, we could predict that oviposition rates of the weevil feeding on a GM ryegrass could be reduced by up to 30% without threat to populations of the weevil in pastoral ecosystems. In addition, an experimentally established correlation between feeding level and oviposition led to the prediction that a consistent reduction in feeding of 50% or higher indicated a significant risk to the species and could potentially lead to local extinctions. This approach to biosafety risk assessment, maximising the use of pre-existing field and laboratory data on non-target species, can make an important contribution to informed decision-making by regulatory authorities and developers of new technologies.

A mathematical model of fatigue in skeletal muscle force contraction.

The ability for muscle to repeatedly generate force is limited by fatigue. The cellular mechanisms behind muscle fatigue are complex and potentially include breakdown at many points along the excitation-contraction pathway. In this paper we construct a mathematical model of the skeletal muscle excitation-contraction pathway based on the cellular biochemical events that link excitation to contraction. The model includes descriptions of membrane voltage, calcium cycling and crossbridge dynamics and was parameterised and validated using the response characteristics of mouse skeletal muscle to a range of electrical stimuli. This model was used to uncover the complexities of skeletal muscle fatigue. We also parameterised our model to describe force kinetics in fast and slow twitch fibre types, which have a number of biochemical and biophysical differences. How these differences interact to generate different force/fatigue responses in fast- and slow- twitch fibres is not well understood and we used our modelling approach to bring new insights to this relationship.

Anatomically based lower limb nerve model for electrical stimulation.

BACKGROUND: Functional Electrical Stimulation (FES) is a technique that aims to rehabilitate or restore functionality of skeletal muscles using external electrical stimulation. Despite the success achieved within the field of FES, there are still a number of questions that remain unanswered. One way of providing input to the answers is through the use of computational models. METHODS: This paper describes the development of an anatomically based computer model of the motor neurons in the lower limb of the human leg and shows how it can be used to simulate electrical signal propagation from the beginning of the sciatic nerve to a skeletal muscle. One-dimensional cubic Hermite finite elements were used to represent the major portions of the lower limb nerves. These elements were fit to data that had been digitised using images from the Visible Man project. Nerves smaller than approximately 1 mm could not be seen in the images, and thus a tree-branching algorithm was used to connect the ends of the fitted nerve model to the respective skeletal muscle. To simulate electrical propagation, a previously published mammalian nerve model was implemented and solved on the anatomically based nerve mesh using a finite difference method. The grid points for the finite difference method were derived from the fitted finite element mesh. By adjusting the tree-branching algorithm, it is possible to represent different levels of motor-unit recruitment. RESULTS: To illustrate the process of a propagating nerve stimulus to a muscle in detail, the above method was applied to the nerve tree that connects to the human semitendinosus muscle. A conduction velocity of 89.8 m/s was obtained for a 15 mum diameter nerve fibre. This signal was successfully propagated down the motor neurons to a selected group of motor units in the muscle. CONCLUSION: An anatomically and physiologically based model of the posterior motor neurons in the human lower limb was developed. This model can be used to examine the effect of external stimulation on nerve and muscle activity, as may occur, for example, in the field of FES.

Anomalous ion diffusion within skeletal muscle transverse tubule networks.

BACKGROUND: Skeletal muscle fibres contain transverse tubular (t-tubule) networks that allow electrical signals to rapidly propagate into the fibre. These electrical signals are generated by the transport of ions across the t-tubule membranes and this can result in significant changes in ion concentrations within the t-tubules during muscle excitation. During periods of repeated high-frequency activation of skeletal muscle the t-tubule K+ concentration is believed to increase significantly and diffusive K+ transport from the t-tubules into the interstitial space provides a mechanism for alleviating muscle membrane depolarization. However, the tortuous nature of the highly branched space-filling t-tubule network impedes the diffusion of material through the network. The effective diffusion coefficient for ions in the t-tubules has been measured to be approximately five times lower than in free solution, which is significantly different from existing theoretical values of the effective diffusion coefficient that range from 2-3 times lower than in free solution. To resolve this discrepancy, in this paper we study the process of diffusion within electron microscope scanned sections of the skeletal muscle t-tubule network using mathematical modelling and computer simulation techniques. Our model includes t-tubule geometry, tautness, hydrodynamic and non-planar network factors. RESULTS: Using our model we found that the t-tubule network geometry reduced the K+ diffusion coefficient to 19-27% of its value in free solution, which is consistent with the experimentally observed value of 21% and is significantly smaller than existing theoretical values that range from 32-50%. We also found that diffusion in the t-tubules is anomalous for skeletal muscle fibres with a diameter of less than approximately 10-20 microm as a result of obstructed diffusion. We also observed that the [K+] within the interior of the t-tubule network during high-frequency activation is greater for fibres with a larger diameter. Smaller skeletal muscle fibres are therefore more resistant to membrane depolarization. Because the t-tubule network is anisotropic and inhomogeneous, we also found that the [K+] distribution generated within the network was irregular for fibres of small diameter. CONCLUSION: Our model explains the measured effective diffusion coefficient for ions in skeletal muscle t-tubules.

Modeling suggests frequency estimates are not informative for predicting the long-term effect of horizontal gene transfer in bacteria.

Horizontal gene transfer (HGT) is an important mechanism by which bacteria recombine and acquire novel genes and functions. Risk scenarios where novel plant transgenes transfer horizontally into bacteria have been addressed in numerical theoretical assessments and experimental studies. A key outcome of these studies has been that the frequencies of such inter-domain transfer are very low, if occurring at all, suggesting that such transfers would not occur at a level that is biologically significant. The relationship between transfer frequencies and the subsequent selection or genetic drift of transgene carrying bacteria often remains unresolved in these studies and assessments. Here we present a stochastic model to better understand the initial establishment and population dynamics of rare bacterial transformants carrying horizontally acquired (trans)genes. The following key parameters are considered: initial transformant numbers, strength of selection, bacterial population size and bacterial generations (time). We find that the initial number of transformants is important for the subsequent persistence of transformants only in the range of 1 to approximately 50 independent HGT events. Our simulations show that transformant populations under a wide range of HGT rates and selection coefficients undergo stochastic developments where they persist at low frequencies for up to several years (at frequencies that are below detection using available field sampling methodology), after which they eventually may go to fixation. Stochastic variability may thus play a crucial but disregarded role in the design of field monitoring strategies e.g. in biosafety assessments. We also estimate the time required for transformants to reach 0.0002% prevalence in a bacterial population, a threshold that allows experimental detection of transgene carrying bacteria through sampling of the larger bacterial populations.