A core metabolic enzyme mediates resistance to phosphine gas

Phosphine is a small redox-active gas that is used to protect global grain reserves, which are threatened by the emergence of phosphine resistance in pest insects. We find that polymorphisms responsible for genetic resistance cluster around the redox-active catalytic disulfide or the dimerization interface of dihydrolipoamide dehydrogenase (DLD) in insects (Rhyzopertha dominica and Tribolium castaneum) and nematodes (Caenorhabditis elegans). DLD is a core metabolic enzyme representing a new class of resistance factor for a redox-active metabolic toxin. It participates in four key steps of core metabolism, and metabolite profiles indicate that phosphine exposure in mutant and wild-type animals affects these steps differently. Mutation of DLD in C. elegans increases arsenite sensitivity. This specific vulnerability may be exploited to control phosphine-resistant insects and safeguard food security.

Experimental and numerical investigation of strain-rate-dependent behavior of kangaroo shoulder cartilage

This thesis introduces a new animal model, kangaroo, to biomechanical investigations of shoulder cartilage research. It examines the effect of cartilage structure and constituents on tissue behavior and its adaptation to mechanical loading. In doing so, the study explains the relationship of tissue's functional behaviors to its structure and constituents which has important implications for tissue engineering strategies catering joint specific cartilage tissue generation.

The effect of pasture utilization rate on stocks of soil organic carbon and total nitrogen in a semi-arid tropical grassland

The influence of grazing management on total soil organic carbon (SOC) and soil total nitrogen (TN) in tropical grasslands is an issue of considerable ecological and economic interest. Here we have used linear mixed models to investigate the effect of grazing management on stocks of SOC and TN in the top 0.5 m of the soil profile. The study site was a long-term pasture utilization experiment, 26 years after the experiment was established for sheep grazing on native Mitchell grass (Astrebla spp.) pasture in northern Australia. The pasture utilization rates were between 0% (exclosure) and 80%, assessed visually. We found that a significant amount of TN had been lost from the top 0.1 m of the soil profile as a result of grazing, with 80% pasture utilization resulting in a loss of 84 kg ha−1 over the 26-year period. There was no significant effect of pasture utilization rate on TN when greater soil depths were considered. There was no significant effect of pasture utilization rate on stocks of SOC and soil particulate organic carbon (POC), or the C:N ratio at any depth; however, visual trends in the data suggested some agreement with the literature, whereby increased grazing pressure appeared to: (i) decrease SOC and POC stocks; and, (ii) increase the C:N ratio. Overall, the statistical power of the study was limited, and future research would benefit from a more comprehensive sampling scheme. Previous studies at the site have found that a pasture utilization rate of 30% is sustainable for grazing production on Mitchell grass; however, given our results, we conclude that N inputs (possibly through management of native N2-fixing pasture legumes) should be made for long-term maintenance of soil health, and pasture productivity, within this ecosystem.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment. This fraction is result of undesirable genotype-by-environment interactions (GxE) and measured by the genetic correlation (rg) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of GxE over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels.

Regression Rate Studies in Hypergolic System

Regression ra tes of a hypergolic combination of fuel and oxidiser have been experimentally measured as a function of chamber pressure, mass flux and the percentage component of the hypergolic compound in natural rubber. The hypergolic compound used is difurfurylidene cyclohexanone (DFCH) which is hypergolic with the oxidiser red fuming nitric acid (RFNA) with ignition dela y of 60-70 ms. The data of weight loss versus time is obtained for burn times varying between 5 and 20 seconds. Two methods of correlating the data using mass flux of oxidiser and the total flux of hot gases have shown that index n of the regression law r=aGoxn or r=aGnxn-1 (x the axial distance) is about 0.5 or a little lower and not 0.8 even though the flow through the port is turbulent. It is argued that the reduction of index n is due to heterogeneous reaction between the liquid oxidiser and the hypergolic fuel component on the surface.

Growth analysis and biomass partitioning of Cyperus iria in response to rice planting density and nitrogen rate

Cyperus iria is a weed of rice with widespread occurrence throughout the world. Because of concerns about excessive and injudicious use of herbicides, cultural weed management approaches that are safe and economical are needed. Developing such approaches will require a better understanding of weed biology and ecology, as well as of weed response to increases in crop density and nutrition. Knowledge of the effects of nitrogen (N) fertilizer on crop-weed competitive interactions could also help in the development of integrated weed management strategies. The present study was conducted in a screenhouse to determine the effects of rice planting density (0, 5, 10, and 20 plants pot−1) and N rate (0, 50, 100, and 150 kg ha−1) on the growth of C. iria. Tiller number per plant decreased by 73–88%, leaf number by 85–94%, leaf area by 85–98%, leaf biomass by 92–99%, and inflorescence biomass by 96–99% when weed plants were grown at 20 rice plants pot−1 (i.e., 400 plants m−2) compared with weed plants grown alone. All of these parameters increased when N rates were increased. On average, weed biomass increased by 118–389% and rice biomass by 121–275% with application of 50–150 kg N ha−1, compared to control. Addition of N favored weed biomass production relative to rice biomass. Increased N rates reduced the root-to-shoot weight ratio of C. iria. Rice interference reduced weed growth and biomass and completely suppressed C. iria when no N was applied at high planting densities (i.e., 20 plants pot−1). The weed showed phenotypic plasticity in response to N application, and the addition of N increased the competitive ability of the weed over rice at densities of 5 and 10 rice plants pot−1 compared with 20 plants pot−1. The results of the present study suggest that high rice density (i.e., 400 plants m−2) can help suppress C. iria growth even at high N rates (150 kg ha−1).

Grazing impacts on the susceptibility of rangelands to wind erosion: The effects of stocking rate, stocking strategy and land condition

An estimated 110 Mt of dust is eroded by wind from the Australian land surface each year, most of which originates from the arid and semi-arid rangelands. Livestock production is thought to increase the susceptibility of the rangelands to wind erosion by reducing vegetation cover and modifying surface soil stability. However, research is yet to quantify the impacts of grazing land management on the erodibility of the Australian rangelands, or determine how these impacts vary among land types and over time. We present a simulation analysis that links a pasture growth and animal production model (GRASP) to the Australian Land Erodibility Model (AUSLEM) to evaluate the impacts of stocking rate, stocking strategy and land condition on the erodibility of four land types in western Queensland, Australia. Our results show that declining land condition, over stocking, and using inflexible stocking strategies have potential to increase land erodibility and amplify accelerated soil erosion. However, land erodibility responses to grazing are complex and influenced by land type sensitivities to different grazing strategies and local climate characteristics. Our simulations show that land types which are more resilient to livestock grazing tend to be least susceptible to accelerated wind erosion. Increases in land erodibility are found to occur most often during climatic transitions when vegetation cover is most sensitive to grazing pressure. However, grazing effects are limited during extreme wet and dry periods when the influence of climate on vegetation cover is strongest. Our research provides the opportunity to estimate the effects of different land management practices across a range of land types, and provides a better understanding of the mechanisms of accelerated erosion resulting from pastoral activities. The approach could help further assessment of land erodibility at a broader scale notably if combined with wind erosion models.

Cyanidin 3-glucoside improves diet-induced metabolic syndrome in rats

Increased consumption of dark-coloured fruits and vegetables may mitigate metabolic syndrome. This study has determined the changes in metabolic parameters, and in cardiovascular and liver structure and function, following chronic administration of either cyanidin 3-glucoside (CG) or Queen Garnet plum juice (QG) containing cyanidin glycosides to rats fed either a corn starch (C) or a high-carbohydrate, high-fat (H) diet. Eight to nine-week-old male Wistar rats were randomly divided into six groups for 16-week feeding with C, C with CG or QG, H or H with CG or QG. C or H were supplemented with CG or QG at a dose of ∼8 mg/kg/day cyanidin glycosides from week 8 to 16. H rats developed signs of metabolic syndrome including visceral adiposity, impaired glucose tolerance, hypertension, cardiovascular remodelling, increased collagen depots in left ventricle, non-alcoholic fatty liver disease, increased plasma liver enzymes and increased inflammatory cell infiltration in the heart and liver. Both CG and QG reversed these cardiovascular, liver and metabolic signs. However, no intact anthocyanins or common methylated/conjugated metabolites could be detected in the plasma samples and plasma hippuric acid concentrations were unchanged. Our results suggest CG is the most likely mediator of the responses to QG but that further investigation of the pharmacokinetics of oral CG in rats is required.

Stable expression of silencing-suppressor protein enhances the performance and longevity of an engineered metabolic pathway

Transgenic engineering of plants is important in both basic and applied research. However, the expression of a transgene can dwindle over time as the plant's small (s)RNA-guided silencing pathways shut it down. The silencing pathways have evolved as antiviral defence mechanisms, and viruses have co-evolved viral silencing-suppressor proteins (VSPs) to block them. Therefore, VSPs have been routinely used alongside desired transgene constructs to enhance their expression in transient assays. However, constitutive, stable expression of a VSP in a plant usually causes pronounced developmental abnormalities, as their actions interfere with endogenous microRNA-regulated processes, and has largely precluded the use of VSPs as an aid to stable transgene expression. In an attempt to avoid the deleterious effects but obtain the enhancing effect, a number of different VSPs were expressed exclusively in the seeds of Arabidopsis thaliana alongside a three-step transgenic pathway for the synthesis of arachidonic acid (AA), an ω-6 long chain polyunsaturated fatty acid. Results from independent transgenic events, maintained for four generations, showed that the VSP-AA-transformed plants were developmentally normal, apart from minor phenotypes at the cotyledon stage, and could produce 40% more AA than plants transformed with the AA transgene cassette alone. Intriguingly, a geminivirus VSP, V2, was constitutively expressed without causing developmental defects, as it acts on the siRNA amplification step that is not part of the miRNA pathway, and gave strong transgene enhancement. These results demonstrate that VSP expression can be used to protect and enhance stable transgene performance and has significant biotechnological application.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Carbon dioxide emissions in the short run: The rate and sources of economic growth matter

This paper investigates the short-run effects of economic growth on carbon dioxide emissions from the combustion of fossil fuels and the manufacture of cement for 189 countries over the period 1961-2010. Contrary to what has previously been reported, we conclude that there is no strong evidence that the emissions-income elasticity is larger during individual years of economic expansion as compared to recession. Significant evidence of asymmetry emerges when effects over longer periods are considered. We find that economic growth tends to increase emissions not only in the same year, but also in subsequent years. Delayed effects - especially noticeable in the road transport sector - mean that emissions tend to grow more quickly after booms and more slowly after recessions. Emissions are more sensitive to fluctuations in industrial value added than agricultural value added, with services being an intermediate case. On the expenditure side, growth in consumption and growth in investment have similar implications for national emissions. External shocks have a relatively large emissions impact, and the short-run emissions-income elasticity does not appear to decline as incomes increase. Economic growth and emissions have been more tightly linked in fossil-fuel rich countries.

Fine root dry matter relative to mango (Mangifera indica) tree scion size grafted on size-controlling rootstocks, is negatively related to scion growth rate

Knowledge of root dry matter (DM) allocation, in relation to differing vigour conferred by rootstock cultivars, is required to understand the structural relationships between rootstock and scion. We investigated the mass of roots (four size classes up to 23 mm diameter) by coring proximal to five polyembryonic mango rootstock cultivars known to differ in their effects on the vigour and productivity of scion cultivar ‘Kensington Pride’, in a field trial of 13-year-old trees. Significant differences in fine (<0.64 and 0.64–1.88 mm diameter) and small (1.88–7.50 mm) root DM contents were observed between rootstock cultivars. There was a complex relationship between the amount of feeder (fine and small size classes) roots and scion size (trunk cross sectional area, TCSA), with intermediate size trees on rootstock MYP having the most feeder roots, while the smallest trees, on the rootstock Vellaikulamban had the least of these roots. Across rootstock cultivars, tree vigour (TCSA growth rate) was negatively and significantly related to the ratio of fine root DM/scion TCSA, suggesting this may be a useful indicator of the vigour that different rootstocks confer on the scion. In contrast non-ratio root DM and scion TCSA results had no significant relationships. The significant rootstock effects on orchard root growth and tree size could not be predicted from earlier differences in nursery seedling vigour, nor did seedling vigour predict root DM allocation.