Biological response of broiler chickens fed peas (Pisum sativum L.) expressing the bean (Phaseolus vulgaris L.) alpha-amylase inhibitor transgene

The nutritive value of transgenic peas expressing an a-amylase inhibitor (alpha-Ail) was evaluated with broiler chickens. The effects of feeding transgenic peas on the development of visceral organs associated with digestion and nutrient absorption were also examined. The chemical composition of the conventional and the transgenic peas used in this study were similar. In the two feeding trials, that were conducted normal and transgenic peas were incorporated into a maize-soybean diet at concentrations up to 500 g kg(-1). The diets were balanced to contain similar levels of apparent metabolisable energy (AME) and amino acids. In the first trial, the birds were fed the diets from 3 to 17days post-hatching and with levels of transgenic peas at 250 g kg(-1) or greater there was a significant reduction in body weight but an increase in feed intake resulting in deceased feed conversion efficiency. In the second trial, in which the birds were fed diets containing 300 g kg(-1) transgenic peas until 40 days of age, growth performance was significantly reduced. It was also demonstrated that the ileal starch digestibility coefficient (0.80 vs 0.42) was significantly reduced in the birds fed transgenic peas. Determination of AME and ileal digestibility of amino acids in 5-week-old broilers demonstrated a significant reduction in AME (12.12 vs 5.08 MJ kg(-1) DM) in the birds fed the transgenic peas. The AME value recorded for transgenic peas reflected the lower starch digestibility of this line. Real digestion of protein and amino acids was unaffected by treatment. Expression of a-Ail in peas did not appear to affect bird health or the utilisation of dietary protein. However, the significant reduction in ileal digestion of starch in transgenic peas does reduce the utility of this feedstuff in monogastric diets where efficient energy utilisation is required. (c) 2006 Society of Chemical Industry.

Effects of artificial foods on the blood chemistry of the Australian magpie

Bird feeding on residential property is a popular activity throughout Western countries. Advocates insist the practice is beneficial, while opponents maintain that it can result in a wide range of negative outcomes including malnutrition. The biological effects of 'backyard feeding' were studied in Australian magpies Gymnorhina tibicen during the non-breeding season in 1999 in the Greater Brisbane and the Lockyer Valley regions, south-east Queensland, Australia. Six magpie populations were selected and 70 birds were individually tagged for identification. The birds were provided with processed foods, 20-40 g per bird daily. To monitor the effects of the food, blood chemistry and body mass (BM) were used as indices. Significant effects were observed in BM and plasma cholesterol (PC), showing strong sensitivity to food provisioning. Significant effects on PC and uric acid were found only when birds were fed dog sausage. Results suggest that blood PC levels in magpies are readily influenced by, probably, the lipids present in food, and that the type of food can affect blood PC levels. These effects may occur widely among fed magpies if the influence that we demonstrated at plasma level can be generalized. Following the free-ranging study, six magpies were captured and subjected to a 6-day captive experiment to determine whether the selected foods had the potential to alter the birds' blood chemistry. It was found that all of the foods, when provided ad libitum, influence at least two of the three blood parameters (PC and non-esterified fatty acids). Due to its popularity, wildlife feeding will continue. To make wildlife-feeding activities truly sustainable, there is a need for further studies. This study clearly demonstrated that the physiology of wild magpies can be affected by 'backyard feeding'.

Lasers - An effective artificial source of radiation for the cultivation of anoxygenic photosynthetic bacteria

The laser diode (LD) is a unique light source that can efficiently produce all radiant energy within the narrow wavelength range used most effectively by a photosynthetic microorganism. We have investigated the use of a single type of LID for the cultivation of the well-studied anoxygenic photosynthetic bacterium, Rhodobacter capsulatus (Rb. capsulatus). An array of vertical-cavity surface-emitting lasers (VCSELs) was driven with a current of 25 mA, and delivered radiation at 860 nm with 0.4 nm linewidth. The emitted light was found to be a suitable source of radiant energy for the cultivation of Rb. capsulatus. The dependence of growth rate on incident irradiance was quantified. Despite the unusual nearly monochromatic light source used in these experiments, no significant changes in the pigment composition and in the distribution of bacteriochlorophyll between LHII and LHI-RC were detected in bacterial cells transferred from incandescent light to laser light. We were also able to show that to achieve a given growth rate in a light-limited culture, the VCSEL required only 30% of the electricity needed by an incandescent bulb, which is of great significance for the potential use of laser-devices in biotechnological applications and photobioreactor construction. (c) 2006 Wiley Periodicals, Inc.

Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Evolving genetic regulatory networks using an artificial genome

Boolean models of genetic regulatory networks (GRNs) have been shown to exhibit many of the characteristic dynamics of real GRNs, with gene expression patterns settling to point attractors or limit cycles, or displaying chaotic behaviour, depending upon the connectivity of the network and the relative proportions of excitatory and inhibitory interactions. This range of behaviours is only apparent, however, when the nodes of the GRN are updated synchronously, a biologically implausible state of affairs. In this paper we demonstrate that evolution can produce GRNs with interesting dynamics under an asynchronous update scheme. We use an Artificial Genome to generate networks which exhibit limit cycle dynamics when updated synchronously, but collapse to a point attractor when updated asynchronously. Using a hill climbing algorithm the networks are then evolved using a fitness function which rewards patterns of gene expression which revisit as many previously seen states as possible. The final networks exhibit “fuzzy limit cycle” dynamics when updated asynchronously.

Successful artificial insemination (AI) in the koala using neat and extended semen collected by electroejaculation (EE)

Presently AI in the koala has been based on the insemination of fresh undiluted semen collected with an artificial vagina (1). While this approach has been extremely successful, further refinement and implementation of AI for use with cryopreserved semen will require protocols that incorporate diluted semen collected by EE. Recent studies have shown that koala semen is likely to have an "ovulation factor" such that over-dilution may result in ovulation failure (2). The current study determined whether AI of EEed neat and/or diluted semen was capable of inducing a luteal phase and/or resulted in the production of pouch young. All koalas were inseminated in the breeding season between day 2 and 5 of oestrus and subsequently monitored for evidence of parturition (day 35) and return of oestrus. Successful induction of a luteal phase was based on evidence of an elevated progesterone concentration 28 days after insemination (2). All semen samples were collected by EE and seminal characteristics recorded (3). The diluent used for semen extension was Tris-citrate glucose (TCG) which contained antibiotics but no egg yolk (4). AI was conducted on conscious koalas using a "Cook koala insemination catheter" and a glass rod used to mimic penile thrusting (1). Three insemination treatments were used; (A) 1mL of undiluted semen (n = 9); (B) 2mL of 1:1 diluted semen (n = 9); and (C) 1 mL of 1:1 diluted semen (n = 9). The results of the AI trial are shown in Table 1. This study has shown that it is possible to use both neat and diluted semen (1:1; 1 or 2 mL) to successfully produce koala offspring at conception rates similar to those achieved following natural mating. Interestingly, dilution of semen had no apparent detrimental effect on induction of a luteal phase following AI.

A novel silicon membrane-based biosensing platform using distributive sensing strategy and artificial neural networks for feature analysis

A novel biosensing system based on a micromachined rectangular silicon membrane is proposed and investigated in this paper. A distributive sensing scheme is designed to monitor the dynamics of the sensing structure. An artificial neural network is used to process the measured data and to identify cell presence and density. Without specifying any particular bio-application, the investigation is mainly concentrated on the performance testing of this kind of biosensor as a general biosensing platform. The biosensing experiments on the microfabricated membranes involve seeding different cell densities onto the sensing surface of membrane, and measuring the corresponding dynamics information of each tested silicon membrane in the form of a series of frequency response functions (FRFs). All of those experiments are carried out in cell culture medium to simulate a practical working environment. The EA.hy 926 endothelial cell lines are chosen in this paper for the bio-experiments. The EA.hy 926 endothelial cell lines represent a particular class of biological particles that have irregular shapes, non-uniform density and uncertain growth behaviour, which are difficult to monitor using the traditional biosensors. The final predicted results reveal that the methodology of a neural-network based algorithm to perform the feature identification of cells from distributive sensory measurement has great potential in biosensing applications.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

The formulation of artificial reference standards for use within the ELISPOT assay

Whether to assess the functionality of equipment or as a determinate for the accuracy of assays, reference standards are essential for the purposes of standardisation and validation. The ELISPOT assay, developed over thirty years ago, has emerged as a leading immunological assay in the development of novel vaccines for the assessment of efficacy. However, with its widespread use, there is a growing demand for a greater level of standardisation across different laboratories. One of the major difficulties in achieving this goal has been the lack of definitive reference standards. This is partly due to the ex vivo nature of the assay, which relies on cells being placed directly into the wells. Thus, the aim of this thesis was to produce an artificial reference standard using liposomes, for use within the assay. Liposomes are spherical bilayer vesicles with an enclosed aqueous compartment and therefore are models for biological membranes. Initial work examined pre-design considerations in order to produce an optimal formulation that would closely mimic the action of the cells ordinarily placed on the assay. Recognition of the structural differences between liposomes and cells led to the formulation of liposomes with increased density. This was achieved by using a synthesised cholesterol analogue. By incorporating this cholesterol analogue in liposomes, increased sedimentation rates were observed within the first few hours. The optimal liposome formulation from these studies was composed of 2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), cholesterol (Chol) and brominated cholesterol (Brchol) at a 16:4:12 µMol ratio, based on a significantly higher (p<0.01) sedimentation (as determined by a percentage transmission of 59 ± 5.9 % compared to the control formulation at 29 ± 12 % after four hours). By considering a range of liposome formulations ‘proof of principle’ for using liposomes as ELISPOT reference standards was shown; recombinant IFN? cytokine was successfully entrapped within vesicles of different lipid compositions, which were able to promote spot formation within the ELISPOT assay. Using optimised liposome formulations composed of phosphatidylcholine with or without cholesterol (16 µMol total lipid) further development was undertaken to produce an optimised, scalable protocol for the production of liposomes as reference standards. A linear increase in spot number by the manipulation of cytokine concentration and/or lipid concentrations was not possible, potentially due to the saturation that occurred within the base of wells. Investigations into storage of the formulations demonstrated the feasibility of freezing and lyophilisation with disaccharide cryoprotectants, but also highlighted the need for further protocol optimisation to achieve a robust reference standard upon storage. Finally, the transfer of small-scale production to a medium lab-scale batch (40 mL) demonstrated this was feasible within the laboratory using the optimised protocol.