Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

Plant composition modulates arthropod pest and predator abundance: Evidence for culling exotics and planting natives

We investigate the role of plant species in crops, pasture and native vegetation remnants in supporting agronomic pests and their predators. The study was conducted in three Australian States and across 290 sites sampled monthly for two years. Pastures played a key role in harbouring pest species consistent across States, while native vegetation hosted relatively more predators than other habitat types within each State. Furthermore, native plant species supported the lowest pest density and more predators than pests; in contrast, 75 of the exotic weed species surveyed hosted more pests than predators. Despite the role of pasture in harbouring pests, we found in NSW that pasture also supported the highest proportion of juvenile predators, while native vegetation remnants had the lowest. Our results indicate that non-crop habitat (native remnants or pasture) with few exotic weeds supports high predator and low pest arthropod densities, and that weeds are associated with high pest densities. By linking broad response variables such as ‘all pests’ with specific predictors such as ‘plant species’, our study will inform on-farm management actions of which weeds to control and which natives to plant or regenerate. This study shows the importance of knowing the function of habitats and plants species in supporting pests and predators in agricultural landscapes across multiple regions.

The effects of lupin (Lupinus angustifolius) addition to wheat bread on its nutritional, phytochemical and bioactive composition and protein quality

The grain legume Australian sweet lupin (Lupinus angustifolius; ASL) is gaining international interest as a functional food ingredient; however its addition to refined wheat bread has been shown to decrease bread volume and textural quality, the extent of which is influenced by ASL variety. The present study evaluated the effects of ASL incorporation (20% of total flour) of the six commercial varieties; Belara, Coromup, Gungurru, Jenabillup, Mandelup and Tanjil, on the level of nutritional, phytochemical and bioactive composition and protein quality of refined wheat flour bread. Protein, dietary fiber, phenolic and carotenoid content, antioxidant capacity and protein digestibility corrected amino acid score (PDCAAS) were higher (p < 0.05), whereas available carbohydrate level was lower (p < 0.05) in ASL–wheat breads than the wheat-only bread, regardless of the ASL variety used. In addition, the blood-glucose lowering bioactive peptide γ-conglutin was detected in all ASL–wheat breads but not in wheat-only bread. The ASL variety used significantly (p < 0.05) affected the dietary fiber, fat, available carbohydrates and polyphenolic level, the antioxidant capacity and the PDCAAS of the ASL–wheat breads. These findings demonstrate the potential nutritional and health benefits of adding ASL to refined wheat bread and highlight the importance of selecting specific ASL varieties to maximise its nutritional attributes.

The effects of lupin (Lupinus angustifolius) addition to wheat bread on its nutritional, phytochemical and bioactive composition and protein quality

The grain legume Australian sweet lupin (Lupinus angustifolius; ASL) is gaining international interest as a functional food ingredient; however its addition to refined wheat bread has been shown to decrease bread volume and textural quality, the extent of which is influenced by ASL variety. The present study evaluated the effects of ASL incorporation (20% of total flour) of the six commercial varieties; Belara, Coromup, Gungurru, Jenabillup, Mandelup and Tanjil, on the level of nutritional, phytochemical and bioactive composition and protein quality of refined wheat flour bread. Protein, dietary fiber, phenolic and carotenoid content, antioxidant capacity and protein digestibility corrected amino acid score (PDCAAS) were higher (p < 0.05), whereas available carbohydrate level was lower (p < 0.05) in ASL–wheat breads than the wheat-only bread, regardless of the ASL variety used. In addition, the blood-glucose lowering bioactive peptide γ-conglutin was detected in all ASL–wheat breads but not in wheat-only bread. The ASL variety used significantly (p < 0.05) affected the dietary fiber, fat, available carbohydrates and polyphenolic level, the antioxidant capacity and the PDCAAS of the ASL–wheat breads. These findings demonstrate the potential nutritional and health benefits of adding ASL to refined wheat bread and highlight the importance of selecting specific ASL varieties to maximise its nutritional attributes.

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.

Computational Methods for Detecting Large-Scale Chromosome Rearrangements in SNP Data

Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.

Service Composition on a Mobile Phone

With the recent increase in interest in service-oriented architectures (SOA) and Web services, developing applications with the Web services paradigm has become feasible. Web services are self-describing, platform-independent computational elements. New applications can be assembled from a set of previously created Web services, which are composed together to make a service that uses its components to perform a certain task. This is the idea of service composition. To bring service composition to a mobile phone, I have created Interactive Service Composer for mobile phones. With Interactive Service Composer, the user is able to build service compositions on his mobile phone, consisting of Web services or services that are available from the mobile phone itself. The service compositions are reusable and can be saved in the phone's memory. Previously saved compositions can also be used in new compositions. While developing applications for mobile phones has been possible for some time, the usability of the solutions is not the same as when developing for desktop computers. When developing for mobile phones, the developer has to more carefully consider the decisions he is going to make with the program he is developing. With the lack of processing power and memory, the applications cannot function as well as on desktop PCs. On the other hand, this does not remove the appeal of developing applications for mobile devices.

Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range

Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific. © 2015 Macmillan Publishers Limited.

Small-scale capture, transport and tank adaptation of live, medium-sized Scombrids using "Tuna Tubes"

The transport of live fish is a crucial step to establish fish culture in captivity, and is especially challenging for species that have not been commonly cultured before, therefore transport and handling methods need to be optimized and tailored. This study describes the use of tuna tubes for small-scale transport of medium-sized pelagic fish from the Scombridae family. Tuna tubes are an array of vertical tubes that hold the fish, while fresh seawater is pumped up the tubes and through the fish mouth and gills, providing oxygen and removing wastes. In this study, 19 fish were captured using rod and line and 42% of the captured fish were transported alive in the custom-designed tuna tubes to an on-shore holding tank: five mackerel tuna (Euthynnus affinis) and three leaping bonito (Cybiosarda elegans). Out of these, just three (15.8% of total fish) acclimatized to the tank's condition. Based on these results, we discuss an improved design of the tuna tubes that has the potential to increase survival rates and enable a simple and low cost method of transporting of live pelagic fish.

Composition by Rabbi Dob Pique Sung at consecration of synagogue

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Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action: Food composition

Reviews and synthesizes evidence to produce evidence-based recommendations on policy actions to improve food composition for NSW Health

Achieving medium-high density in low scale development: The Queensland experience in innovative ‘fine-grained’ urbanism

Worldwide population growth and economic agglomeration is driving increasing urban density within larger metropolitan conurbations. Population growth and housing diversity and affordability issues in Queensland have seen an increasing demand for more diverse and higher density development. Under Queensland’s flexible planning regulatory provisions, a level of ‘medium’ to ‘high density’ is being achieved by a focus on fine-grained urban design, low scale development, lot diversity, and delivery of single dwelling products. This for Queensland (and Australia) has been an unprecedented innovation in urban and dwelling design. Dwellings are being delivered on lots with zero regulatory minimum sizes providing for a range of new products including ‘apartments on the ground’. This paper reviews recent and nascent demonstrations of EDQ’s fine-grained urbanism principles, identifiable with historical ‘vernacular suburbanism’. The paper introduces and defines a concept of a ‘natural density’ linking human scale built form with walkability. The paper challenges the notion that (sub)urban development, outside major city centres, needs to be of a higher scale to achieve density and diversity aspirations. ‘Natural density’ provides a means of achieving the increasing demand for more diverse and higher density development.

A simple method for large-scale preparation of chick embryo tRNA

A simple method for preparing bulk quantities of tRNA from chick embryo has been developed. In this method chick embryos were homogenized in a buffer of pH 4.5, followed by deproteinization with phenol. The aqueous layer was allowed to separate under gravity. The resulting aqueous layer, after two more phenol treatments, was directly passed through a DEAE-cellulose column and the tRNA eluted therefrom with 1 Image NaCl. The tRNA prepared by this method was as active as the one prepared at neutral pH.