Response of Tribolium castaneum and Rhyzopertha dominica to various resources, near and far from grain storage

Tribolium castaneum (Herbst) and Rhyzopertha dominica (F.) are common cosmopolitan pests of stored grain and grain products. We evaluated the relative attraction of T.castaneum and R.dominica to wheat, sorghum and cotton seeds in the field, near grain storage facilities and well away from storages in southern and central Queensland using multiple trapping techniques. The results show that T.castaneum is more strongly attracted to linted cotton seed relative to wheat, whereas R.dominica did not respond to cotton seed at all and was attracted only to wheat. Significantly more adults of T.castaneum (10-15 times) were attracted to traps placed on the ground, near grain storage, than to equivalent traps that were suspended (1.5m above the ground) nearby. These results suggest that Tribolium beetles detect and respond to resources towards the end of their dispersal flight, after which they localize resources while walking. By contrast R.dominica was captured only in suspended traps, which suggests they fly directly onto resources as they localize them. The ability of both species to colonize and reproduce in isolated resource patches within the relatively short time of 1month is illustrated by the returns from the traps deployed in the field (at least 1km from the nearest stored grain) even though they caught only a few beetles. The results presented here provide novel insights about the resource location behaviours of both T.castaneum and R.dominica. In particular, the relationship of T.castaneum with non-cereal resources that are not conventionally associated with this species suggests an emphasis on these other resources in investigating the resource location behaviour of these beetles. This new perspective on the ecology of T. castaneum highlights the potential role of non-cereal resources (such as the lint on cotton seed) in the spread of grain pest infestations.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

Barley genotype expressing "stay-green"-like characteristics maintains starch quality of the grain during water stress condition

The identification of "stay-green" in sorghum and its positive correlation with yield increases has encouraged attempts to incorporate "stay-green"-like traits into the genomes of other commercially important cereal crops. However, knowledge on the effects of "stay-green" expression on grain quality under extreme physiological stress is limited. This study examines impacts of "stay-green"-like expression on starch biosynthesis in barley (Hordeum vulgare L.) grain under mild, severe, and acute water stress conditions induced at anthesis. The proportions of long amylopectin branches and amylose branches in the grain of Flagship (a cultivar without "stay-green"-like characteristics) were higher at low water stress, suggesting that water stress affects starch biosynthesis in grain, probably due to early termination of grain fill. The changes in long branches can affect starch properties, such as the rates of enzymatic degradation, and hence its nutritional value. By contrast, grain from the "stay-green"-like cultivar (ND24260) did not show variation in starch molecular structure under the different water stress levels. The results indicate that the cultivar with "stay-green"-like traits has a greater potential to maintain starch biosynthesis and quality in grain during drought conditions, making the "stay-green"-like traits potentially useful in ensuring food security. (C) 2013 Elsevier Ltd. All rights reserved.

Liquid phase oxidation of propionaldehyde: Kinetics of initiation step

A method of determining the rate of the initiation reaction in the liquid phase oxidation of propionaldehyde is described.

Eco-Taxonomic Insights into Actinomycete Symbionts of Termites for Discovery of Novel Bioactive Compounds

Termites play a major role in foraging and degradation of plant biomass as well as cultivating bioactive microorganisms for their defense. Current advances in “omics” sciences are revealing insights into function-related presence of these symbionts, and their related biosynthetic activities and genes identified in gut symbiotic bacteria might offer a significant potential for biotechnology and biodiscovery. Actinomycetes have been the major producers of bioactive compounds with an extraordinary range of biological activities. These metabolites have been in use as anticancer agents, immune suppressants, and most notably, as antibiotics. Insect-associated actinomycetes have also been reported to produce a range of antibiotics such as dentigerumycin and mycangimycin. Advances in genomics targeting a single species of the unculturable microbial members are currently aiding an improved understanding of the symbiotic interrelationships among the gut microorganisms as well as revealing the taxonomical identity and functions of the complex multilayered symbiotic actinofloral layers. If combined with target-directed approaches, these molecular advances can provide guidance towards the design of highly selective culturing methods to generate further information related to the physiology and growth requirements of these bioactive actinomycetes associated with the termite guts. This chapter provides an overview on the termite gut symbiotic actinoflora in the light of current advances in the “omics” science, with examples of their detection and selective isolation from the guts of the Sunshine Coast regional termite Coptotermes lacteus in Queensland, Australia

Enzyme molecular choreography : studies on soluble inorganic pyrophosphatases

Inorganic pyrophosphatases (PPases, EC 3.6.1.1) hydrolyse pyrophosphate in a reaction that provides the thermodynamic 'push' for many reactions in the cell, including DNA and protein synthesis. Soluble PPases can be classified into two families that differ completely in both sequence and structure. While Family I PPases are found in all kingdoms, family II PPases occur only in certain prokaryotes. The enzyme from baker's yeast (Saccharomyces cerevisiae) is very well characterised both kinetically and structurally, but the exact mechanism has remained elusive. The enzyme uses divalent cations as cofactors; in vivo the metal is magnesium. Two metals are permanently bound to the enzyme, while two come with the substrate. The reaction cycle involves the activation of the nucleophilic oxygen and allows different pathways for product release. In this thesis I have solved the crystal structures of wild type yeast PPase and seven active site variants in the presence of the native cofactor magnesium. These structures explain the effects of the mutations and have allowed me to describe each intermediate along the catalytic pathway with a structure. Although establishing the ʻchoreographyʼ of the heavy atoms is an important step in understanding the mechanism, hydrogen atoms are crucial for the mechanism. The most unambiguous method to determine the positions of these hydrogen atoms is neutron crystallography. In order to determine the neutron structure of yeast PPase I perdeuterated the enzyme and grew large crystals of it. Since the crystals were not stable at ambient temperature, a cooling device was developed to allow neutron data collection. In order to investigate the structural changes during the reaction in real time by time-resolved crystallography a photolysable substrate precursor is needed. I synthesised a candidate molecule and characterised its photolysis kinetics, but unfortunately it is hydrolysed by both yeast and Thermotoga maritima PPases. The mechanism of Family II PPases is subtly different from Family I. The native metal cofactor is manganese instead of magnesium, but the metal activation is more complex because the metal ions that arrive with the substrate are magnesium different from those permanently bound to the enzyme. I determined the crystal structures of wild type Bacillus subtilis PPase with the inhibitor imidodiphosphate and an inactive H98Q variant with the substrate pyrophosphate. These structures revealed a new trimetal site that activates the nucleophile. I also determined that the metal ion sites were partially occupied by manganese and iron using anomalous X- ray scattering.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

Status, challenges and tools for identification and diagnosis of Peronosclerospora and Sclerophthora of regulatory concern for graminicolous crops

Graminicolous Downy Mildew (GDM) diseases caused by the genera Peronosclerospora (13 spp.) and Sclerophthora (6 spp. and 1 variety) are poorly studied but destructive diseases of major crops such as corn, sorghum, sugarcane and other graminoids. Eight of the 13 described Peronosclerospora spp. are able to infect corn. In particular, P. philippinensis (= P. sacchari), P. maydis, P. heteropogonis, and S. rayssiae var. zeae cause major losses in corn yields in tropical Asia. In 2012 a new species, P. australiensis, was described based on isolates previously identified as P. maydis in Australia; this species is now a pathogen of major concern. Despite the strong impact of GDM diseases, there are presently no reliable molecular methods available for their detection. GDM pathogens are among the most difficult Oomycetes to identify using molecular tools, as their taxonomy is very challenging, and little genetic sequence data are available for development of molecular tools to detect GDM pathogens to species level. For example, from over 15 genes used in identification, diagnostics or phylogeny of Phytophthora, only ITS1 and cox2 show promise for use with GDM pathogens. Multiplex/multigene conventional and qPCR assays are currently under evaluation for the detection of economically important GDM spp. Scientists from the USA, Germany, Canada, Australia, and the Philippines are collaborating on the development and testing of diagnostic tools for these pathogens of concern.

Dietary media for mass rearing of rusty grain beetle, Cryptolestes ferrugineus (Stephens) and flat grain beetle, Cryptolestes pusillus (Schonherr) (Coleoptera: Cucujidae)

We developed a suitable diet for mass rearing of Cryptolestes ferrugineus (Stephens) populations under laboratory conditions. Recently, this pest has developed strong level of resistance to phosphine in Australia, and therefore, a significant amount of research has been directed towards its management. In total, nineteen grain-based diets, containing rolled oats, various combinations of cracked grains and flours of wheat, sorghum, maize and barley were tested. Each diet contained a small proportion of wheat germ (4.5% w/w) and torula yeast (0.5% w/w). Experiments were conducted at fixed temperature and relative humidity regimes of 30 ± 2 °C and 70 ± 2%, respectively, and replicated three times. Adults (n = 40) of a laboratory strain of C. ferrugineus were introduced into each diet, removed after 14 days and total numbers of live adult progeny were recorded. The following diets resulted in highest live progeny production: barley flour (95%) (607.67 ± 11.21) = rolled oats (75%) + cracked sorghum (20%) (597.33 ± 33.79) ≥ wheat flour (47.5%) + barley flour (47.5%) (496.67 ± 52.93) > cracked sorghum (95%) (384.00 ± 60.66). The performance of these four diets was then tested with field-collected populations of C. ferrugineus and Cryptolestes pusillus (Schonherr). The diets based on rolled oats + cracked sorghum, wheat flour + barley flour, and barley flour alone consistently produced highest progeny numbers in field-collected populations of both species, with mean progeny numbers ranging from 359.9 to 478.5. The multiplication of C. pusillus was significantly higher than C. ferrugineus on all four diets. Our findings will help in mass rearing of healthy cultures of C. ferrugineus and C. pusillus that will greatly facilitate laboratory and field research and in particular, in developing management tactics for these species.

Structural characteristics affecting functions of two actin regulating proteins

Structural biology is a branch of science that concentrates on the relationship between the structure and function of biological macromolecules. The prevalence of a large number of three dimensional structures offers effective tools for bio-scientists to understand the living world. Actin is the most abundant cellular protein and one of its main functions is to produce movement in living cells. Actin forms filaments that are dynamic and which are regulated by a number of different proteins. A class of these regulatory proteins contains actin depolymerizing factor homology (ADF-H) domains. These directly interact with actin through their ADF-H domains. Although ADF-H domains possess very similar three dimensional structures to one another, they vary in their functional properties. One example of this is the ability to bind to actin monomers or filaments. During the work for this thesis two structures of ADF-H domains were solved by nuclear magnetic resonance spectroscopy (NMR). The elucidated structures help us understand the binding specificities of the ADF-H family members.

Networks of stored grain diseases and pests: Strategies for sampling and mitigation

Pathogens and pests of stored grains move through complex dynamic networks linking fields, farms, and bulk storage facilities. Human transport and other forms of dispersal link the components of this network. A network model for pathogen and pest movement through stored grain systems is a first step toward new sampling and mitigation strategies that utilize information about the network structure. An understanding of network structure can be applied to identifying the key network components for pathogen or pest movement through the system. For example, it may be useful to identify a network node, such as a local grain storage facility, through which grain from a large number of fields will be accumulated and move through the network. This node may be particularly important for sampling and mitigation. In some cases more detailed information about network structure can identify key nodes that link two large sections of the network, such that management at the key nodes will greatly reduce the risk of spread between the two sections. In addition to the spread of particular species of pathogens and pests, we also evaluate the spread of problematic subpopulations, such as subpopulations with pesticide resistance. We present an analysis of stored grain pathogen and pest networks for Australia and the United States.

Aspects and Applications of Pulse Sequence Design for Solution-State Nuclear Magnetic Resonance Spectroscopy

NMR spectroscopy enables the study of biomolecules from peptides and carbohydrates to proteins at atomic resolution. The technique uniquely allows for structure determination of molecules in solution-state. It also gives insights into dynamics and intermolecular interactions important for determining biological function. Detailed molecular information is entangled in the nuclear spin states. The information can be extracted by pulse sequences designed to measure the desired molecular parameters. Advancement of pulse sequence methodology therefore plays a key role in the development of biomolecular NMR spectroscopy. A range of novel pulse sequences for solution-state NMR spectroscopy are presented in this thesis. The pulse sequences are described in relation to the molecular information they provide. The pulse sequence experiments represent several advances in NMR spectroscopy with particular emphasis on applications for proteins. Some of the novel methods are focusing on methyl-containing amino acids which are pivotal for structure determination. Methyl-specific assignment schemes are introduced for increasing the size range of 13C,15N labeled proteins amenable to structure determination without resolving to more elaborate labeling schemes. Furthermore, cost-effective means are presented for monitoring amide and methyl correlations simultaneously. Residual dipolar couplings can be applied for structure refinement as well as for studying dynamics. Accurate methods for measuring residual dipolar couplings in small proteins are devised along with special techniques applicable when proteins require high pH or high temperature solvent conditions. Finally, a new technique is demonstrated to diminish strong-coupling induced artifacts in HMBC, a routine experiment for establishing long-range correlations in unlabeled molecules. The presented experiments facilitate structural studies of biomolecules by NMR spectroscopy.

Harvest weed seed control: is there a role in northern region farming systems?

Harvest weed seed control (HWSC) is a new approach which targets weed seed removal and/or destruction during the crop harvest operation. The success of HWSC is dependant upon weed seed retention at harvest. To identify and define the potential value of HWSC in northern farming systems, we conducted a field survey. In total 1400 transects across 70 paddocks assessed weed distribution, density and seed production at harvest time in wheat, chickpea and sorghum crops. Seventy weed species were identified, of which many had large seed numbers retained at crop harvest. The most prevalent included common sowthistle, flaxleaf fleabane, awnless barnyard grass, wild oat, and African turnip weed. Our field survey has shown there is a role for HWSC in the northern farming system. Therefore the efficacy of specific HWSC systems on problematic weeds should be evaluated in the northern region.

Crop design for specific adaptation in variable dryland production environments

Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.