Large‐scale identification of genetic design strategies using local search

In the past decade, computational methods have been shown to be well suited to unraveling the complex web of metabolic reactions in biological systems. Methods based on flux–balance analysis (FBA) and bi‐level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. Bi‐level FBA is, however, limited in applicability because the required computational time and resources scale poorly as the size of the metabolic system and the number of genetic manipulations increase. To overcome these limitations, we have developed Genetic Design through Local Search (GDLS), a scalable, heuristic, algorithmic method that employs an approach based on local search with multiple search paths, which results in effective, low‐complexity search of the space of genetic manipulations. Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.     

Intergenerational effects of birth weight on glucose tolerance and reproductive performance

Women who were themselves small-for-gestational age (SGA) are at a greater risk of adulthood diseases such as non-insulin-dependent diabetes mellitus (NIDDM), and twice at risk of having an SGA baby themselves. The aim of this study was to examine the intergenerational pig. Low (L) and normal (N) birth weight female piglets were followed throughout their first pregnancy (generation 1 (G1)). After they had given birth, the growth and development of the lightest (l) and heaviest (n) female piglet from each litter were monitored until approximately 5 months of age (generation 2 (G2)). A glucose tolerance test (GTT) was conducted on G1 pig at 6 months of age and again during late pregnancy; a GTT was also conducted on G2 pigs at 4 months of age. G1 L offspring exhibited impaired glucose metabolism in later life compared to their G1 N sibling but in the next generation a similar scenario was only observed between l and n offspring born to G1 L mothers. Despite G1 L mothers showing greater glucose intolerance in late pregnancy and a decreased litter size, average piglet birth weight was reduced and there was also a large variation in litter weight; this suggests that they were, to some extent, prioritising their nutrient intake towards themselves rather than promoting their reproductive performance. There were numerous relationships between body shape at birth and glucose curve characteristics in later life, which can, to some extent, be used to predict neonatal outcome. In conclusion, intergenerational effects are partly seen in the pig. It is likely that some of the intergenerational influences may be masked due to the pig being a litter-bearing species.     

Efficient nonlinear predictive control of a biochemical reactor using neural models

This paper describes the application of artificial neural networks to modelling and control of a continuous fermentor. A computationally efficient nonlinear model predictive control (MPC) algorithm with nonlinear prediction and linearisation (MPC-NPL) which needs solving on-line a quadratic programming problem is developed. It is demonstrated that the algorithm results in closed-loop control performance similar to that obtained in nonlinear MPC, which hinges on full on-line non-convex optimisation. The computational complexity of the MPC-NPL algorithm is shown, control accuracy and robustness are also demonstrated in the case of noisy measurements and disturbances affecting the process.     

A review on data mining and continuous optimization applications in computational biology and medicine

An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene‐expression patterns; it nowadays requests mathematics to deeply understand its foundations. This article surveys data mining and machine learning methods for an analysis of complex systems in computational biology. It mathematically deepens recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic context within the framework of matrix and interval arithmetics. Given the data from DNA microarray experiments and environmental measurements, we extract nonlinear ordinary differential equations which contain parameters that are to be determined. This is done by a generalized Chebychev approximation and generalized semi‐infinite optimization. Then, time‐discretized dynamical systems are studied. By a combinatorial algorithm which constructs and follows polyhedra sequences, the region of parametric stability is detected. In addition, we analyze the topological landscape of gene‐environment networks in terms of structural stability. As a second strategy, we will review recent model selection and kernel learning methods for binary classification which can be used to classify microarray data for cancerous cells or for discrimination of other kind of diseases. This review is practically motivated and theoretically elaborated; it is devoted to a contribution to better health care, progress in medicine, a better education, and more healthy living conditions. Birth Defects Research (Part C) 87:165–181, 2009. © 2009 Wiley‐Liss, Inc.     

Offspring born to ewes fed high salt during pregnancy have altered responses to oral salt loads

Prenatal growth is sensitive to the direct and indirect effects of maternal dietary intake; manipulation can lead to behavioural and physiological changes of the offspring later in life. Here, we report on three aspects of how a high-salt diet during pregnancy (conception to parturition) may affect the offspring's response to high oral salt loads: (i) dietary preferences for salt; (ii) response to salt and water balance and aldosterone and arginine vasopressin (AVP) concentrations after an oral salt challenge; (iii) concentrations of insulin and leptin after an oral salt challenge. We used two groups of lambs born to ewes fed either a high-salt (13% NaCl) diet during pregnancy (S lambs; n = 12) or control animals born to ewes fed a conventional (0.5% NaCl) diet during pregnancy (C lambs; n = 12). Lambs were subjected to short- (5 min) and long-term (24 h) preference tests for a high-salt (13% NaCl) or control diet, and the response to an oral challenge with either water or 25% NaCl solution were also carried out. Weaned lambs born to ewes fed high salt during pregnancy did not differ in their preference for dietary salt, but they did differ in their physiological responses to an oral salt challenge. Results indicate that these differences reflect an alteration in the regulation of water and salt balance as the metabolic hormones, insulin and leptin, were not affected. During the first 2 h after a single salt dose, S lambs had a 25% lower water intake compared to the C lambs. S lambs had, on average, a 13% lower AVP concentration than the C lambs (P = 0.014). The plasma concentration of aldosterone was higher in the S lambs than in the C lambs (P = 0.013). Results suggest that lambs born to ewes that ingest high amounts of salt during pregnancy are programmed to have an altered thirst threshold, and blunted response in aldosterone to oral salt loads.     

The importance of catch-up growth after early malnutrition for the programming of obesity in male rat

Objective: To investigate whether catch‐up growth after maternal malnutrition would favor the development of obesity in adulthood. Research Methods and Procedures: Pregnant rats were submitted to protein or calorie restriction during the course of gestation. During lactation, pups were protein‐restricted, normally fed, or overfed [reduced litter size, control (C) diet]. At weaning, rats were transferred to chow or to a hypercaloric diet (HCD) known to induce obesity. Body weight, food intake, blood parameters, glucose tolerance, adipocyte cellularity, and adipose factors contributing to cardiovascular disease development were measured. Results: Protein and calorie restriction during gestation led to growth retardation at birth. If malnutrition was prolonged throughout lactation, adult body weight was permanently reduced. However, growth‐retarded offspring overfed during the suckling period underwent a rapid catch‐up growth and became heavier than the normally fed Cs. Offspring of calorie‐restricted rats gained more weight than those of dams fed protein‐restricted diet. Feeding an HCD postnatally amplified the effect of calorie restriction, and offspring that underwent catch‐up growth became more obese than Cs. The HCD was associated with hyperphagia, hyperglycemia, hyperinsulinemia, glucose intolerance, insulin resistance, and adipocyte hypertrophy. The magnitude of effects varied depending on the type and the timing of early malnutrition. The expression of genes encoding factors implicated in cardiovascular disease was also modulated differently by early malnutrition and adult obesity. Discussion: Catch‐up growth immediately after early malnutrition should be a key point for the programming of obesity.     

Lactational programming? mother's milk energy predicts infant behavior and temperament in rhesus macaques (Macaca mulatta)

There are many aspects of “mothering” that may provide information to the mammalian infant about environmental conditions during critical periods of development. One essential element of mothering involves the quantity and quality of milk that mothers provide for their infants, but little is known about the consequences of variation in milk production. Mother's milk may affect infant behavior by contributing to brain development and to the development of behavioral dispositions. Here we present the first evidence for any mammal that natural variation in available milk energy (AME) from the mother is associated with later variation in infant behavior and temperament in rhesus macaques (Macaca mulatta, N=59). In the early postnatal period, heavier mothers with more reproductive experience produced greater AME, which is the product of milk energy density (kcal/g) and milk yield (g). Moreover, infants whose mothers produced greater AME in the early postnatal period showed higher activity levels and greater confidence in a stressful setting later in infancy. Our results suggest that the milk energy available soon after birth may be a nutritional cue that calibrates the infant's behavior to environmental or maternal conditions. These data provide new insight into potential mechanisms for the development of behavior and temperament and illuminate new directions for investigating maternal effects, nutritional programming, and developmental plasticity. Am. J. Primatol. 72:522–529, 2010. © 2010 Wiley‐Liss, Inc.     

On the construction of bounds in prospective studies with missing ordinal outcomes: application to the good behavior game trial

This article is concerned with drawing inference about aspects of the population distribution of ordinal outcome data measured on a cohort of individuals on two occasions, where some subjects are missing their second measurement. We present two complementary approaches for constructing bounds under assumptions on the missing data mechanism considered plausible by scientific experts. We develop our methodology within the context of a randomized trial of the "Good Behavior Game," an intervention designed to reduce aggressive misbehavior among children.     

Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization

The advent of genome-scale models of metabolism has laid the foundation for the development of computational procedures for suggesting genetic manipulations that lead to overproduction. In this work, the computational OptKnock framework is introduced for suggesting gene deletion strategies leading to the overproduction of chemicals or biochemicals in E. coli. This is accomplished by ensuring that a drain towards growth resources (i.e., carbon, redox potential, and energy) must be accompanied, due to stoichiometry, by the production of a desired product. Computational results for gene deletions for succinate, lactate, and 1,3-propanediol (PDO) production are in good agreement with mutant strains published in the literature. While some of the suggested deletion strategies are straightforward and involve eliminating competing reaction pathways, many others suggest complex and nonintuitive mechanisms of compensating for the removed functionalities. Finally, the OptKnock procedure, by coupling biomass formation with chemical production, hints at a growth selection/adaptation system for indirectly evolving overproducing mutants.     

Multicriteria optimization of biochemical systems by linear programming: application to production of ethanol by Saccharomyces cerevisiae

In this study we present a method for simultaneous optimization of several metabolic responses of biochemical pathways. The method, based on the use of the power law formalism to obtain a linear system in logarithmic coordinates, is applied to ethanol production by Saccharomyces cerevisiae. Starting from an experimentally based kinetic model, we translated it to its power law equivalent. With this new model representation, we then applied the multiobjective optimization method. Our intent was to maximize ethanol production and minimize each of the internal metabolite concentrations. To ensure cell viability, all optimizations were carried out under imposed constraints. The different solutions obtained, which correspond to alternative patterns of enzyme overexpression, were implemented in the original model. We discovered few discrepancies between the S-system-optimized steady state and the corresponding optimized state in the original kinetic model, thus demonstrating the suitability of the S-system representation as the basis for the optimization procedure. In all optimized solutions, the ATP level reached its maximum and any increase in its activity positively affected the optimization process. This work illustrates that in any optimization study no single criteria is of general application being the multiobjective and constrained task the proper way to address it. It is concluded that the proposed multiobjective method can serve to carry out, in a single study, the general pattern of behavior of a given metabolic system with regard to its control and optimization.