Thermodynamically Stable DNA Code Design using a Similarity Significance Model

DNA code design aims to generate a set of DNA sequences (codewords) with minimum likelihood of undesired hybridizations among sequences and their reverse-complement (RC) pairs (cross-hybridization). Inspired by the distinct hybridization affinities (or stabilities) of perfect double helix constructed by individual single-stranded DNA (ssDNA) and its RC pair, we propose a novel similarity significance (SS) model to measure the similarity between DNA sequences. Particularly, instead of directly measuring the similarity of two sequences by any metric/approach, the proposed SS works in a way to evaluate how more likely will the undesirable hybridizations occur over the desirable hybridizations in the presence of the two measured sequences and their RC pairs. With this SS model, we construct thermodynamically stable DNA codes subject to several combinatorial constraints using a sorting-based algorithm. The proposed scheme results in DNA codes with larger code sizes and wider free energy gaps (hence better cross-hybridization performance) compared to the existing methods.Comment: To appear in ISIT 202

Biodiversity assessment of marine benthic communities with COI metabarcoding: methods and applications

[eng] Ecosystem biomonitoring is crucial for proper management of natural communities during the Anthropocene era. With the advent of new sequencing technologies, DNA metabarcoding has been proposed as a game-changing tool for biomonitoring. In this Thesis we plead for the use of metabarcoding of a highly variable marker to infer not only the interspecies but also the intraspecies variability to assess both biogeographic, at the species level, and metaphylogeographic patterns, at the haplotype level. We focused on highly complex hard-substratum benthic littoral communities. The term "Metaphylogeography", coined in this Thesis, refers to the study of phylogeographic patterns of many species at the same time using metabarcoding data. However, as of the start of this Thesis, only a few studies had tested the metabarcoding method to directly characterize the whole eukaryotic community in highly diverse benthic ecosystems. This required to set up and calibrate methods for these communities as a prior step. We first evaluated both the sampling methods and the bioinformatic pipelines. We assessed the viability of detecting the environmental DNA released from the benthic community into the adjacent water layer using metabarcoding of COI with highly degenerated primers targeting the whole eukaryotic community. We sampled water from 0 to 20m from shallow rocky benthic communities and compared the DNA signal with the results obtained from metabarcoding directly the benthic communities by traditional quadrat sampling. We also designed a pipeline combining clustering and denoising methods to treat metabarcoding data of COI. We considered the entropy of each codon position of this coding fragment both to improve the detection of spurious sequences and to calibrate the best performing parameters of the software used. In addition, we created our own denoising program, DnoisE, to incorporate information on the codon position. This new code and parameter calibration were required as the commonly used bioinformatic pipelines had been designed and tested mostly for less variable ribosomal fragments and, particularly, in prokaryotes. Results showed that the DNA signal from the benthos decreased with the distance but was too weak for a correct assessment of benthic biodiversity. The proportion of eukaryotic DNA sequenced was also very low in water samples due to the amplification of prokaryotic DNA. We thus concluded that the benthos must be sampled directly to properly assess its biodiversity composition. The new bioinformatic developments allowed us to propose new methods for processing metabarcoding reads, combining clustering and denoising steps, and to set optimal values for the parameters used at each step. These contributions effectively expanded the field to the novel analysis of inter- and intraspecies genetic variability with metabarcoding data. Finally, we applied this methodology to 12 localities of the Western Iberian Coast along two well studied fronts, the Almeria-Oran Front (AOF) and the Ibiza Channel (IC). We analysed the species and haplotypes using the COI barcode. From a biogeographical perspective, the AOF had a strong effect in separating regions, while IC effect was less marked, but still half of the MOTUs were found in only one side of this divide. For the metaphylogeographic analysis, only 10% of the MOTUs could be used. However, they showed a good separation between populations of the three regions with a strong effect of the AOF break. The IC, on the other hand, seemed to be more a transitional zone than a fixed break. This Thesis laid the ground for the efficient use of metabarcoding in the biomonitoring of benthic reef habitats, allowing community composition, β-diversity, and biogeographic patterns to be analysed in a fast, repeatable, and cost-efficient way. We also developed the metaphylogeography approach as a new tool to assess population genetic structure at the community-wide level

Structure and temporal dynamics of marine biodiversity in the Terra Nova Bay area (Ross Sea, Antarctica) analysed through DNA barcoding and metabarcoding: A standardized and systematic approach for the construction of a \u201cDNA Barcode\u201d library.

Aims and structure of the thesis: The firs objective of this thesis consisted in the quantification of the reference library completeness for the Cytochrome c oxidase subunit I (COI) barcode of metazoan species occurring in the Ross Sea MPA and in identifying which taxonomic groups in the last decades were investigated by using \u201cDNA barcode\u201d techniques performed in the Southern Ocean. In order to do that, all the available sequence data on major public repositories were gathered and analyzed. A collection of COI sequences amplified from specimen of the Italian National Antarctic Museum (MNA) was produced and aggregated to the latter to assemble the first global Ross Sea reference library of metazoan COI barcoding sequences. The potentialities of \u201cDNA metabarcoding\u201d techniques applied to the analysis of Antarctic biological communities were also evaluated in Terra Nova Bay (TNB) by focusing on the development of macrozoobenthic pioneering communities colonizing artificial structures over a period of three years and on nanoplankton temporal short-term dynamics in two consecutive years. These studies were conducted using innovative sampling methodologies and experiments and differed not only for the investigated community, but also for the sampling frequency, timing and study purposes. Due to the peculiarities of the three analyses, these will be detailed in three separate chapters. Each chapter is composed by its specific \u201cIntroduction\u201d to the concepts discussed in that study, followed by a section on \u201cMaterials and Methods\u201d and a joint section with the \u201cResults and Discussion\u201d. Considering that the different chapters, notwithstanding the fact that they pertain to the same, general topic of research, greatly differs in the overall design, as mentioned earlier, no general Discussion for the entire thesis was produced. Instead, an Introduction, discussing the most general topics covered by the entire thesis, is presented at first (i.e. the \u201cThesis Introduction\u201d), whereas the thesis\u2019 Conclusions, considering all the outcomes reported in the different chapters, will be presented at the end of the whole thesis (\u201cThesis Conclusions\u201d)

Total Constraint Management for Improving Construction Work Flow in Liquefied Natural Gas Industry

Australia has benefited and will continue to benefit significantly from Liquefied Natural Gas (LNG) investments underway. Managing these LNG projects is challenging as they become increasingly complex and technologically demanding. The primary goal of this thesis is to develop a Total Constraint Management (TCM) method to improve construction work flow during LNG construction. Five controlled experiments were conducted and results show that successful implementation of TCM can significantly improve construction productivity and reduce schedule overruns

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

New synchronous machine rotor design for easy insertion of excitation coils based on surrogate optimisation

The thesis reviews the development of traditional synchronous machine design and point out one problem with the manufacture of wound rotor synchronous machines. Install and repair process of the rotor windings can be considered labor-costly and time-consuming in synchronous machine design. The conclusion indicates a new winding method would be helpful for not only the new machines but also for rewound machines. A new rotor design for the easy insertion and repair of the rotor windings is then introduced. This new asymmetrical rotor shows good potentials for reducing the maintenance and repair costs of synchronous machines, making it suitable for manufacturers within the mass production markets such as gen-sets, steam turbines, wind power generators. Simulation results from 2-D finite element analysis and experimental results from testing a 27.5 kVA prototype machine have verified the performance of the new rotor. The results show that the asymmetrical machine’s electromagnetic performance is worse than traditional design and need to be optimised. The shape of the rotor is then optimised based on novel surrogate method in order to achieve the lowest power loss under the maximum power output. This method combines surrogate optimistaion with finite element method. It significantly reduces the time cost of the optimization process and can be applied with very complicated geometry design of the rotor. The performance of the new rotor is examined in 2-D finite element software and validated by experiments. After optimisation, the efficiency of the new rotor can reach the same level of the traditional rotor in electromagnetic performance in addition to its easy insertion and repair feature

Simulations and Modelling for Biological Invasions

Biological invasions are characterized by the movement of organisms from their native geographic region to new, distinct regions in which they may have significant impacts. Biological invasions pose one of the most serious threats to global biodiversity, and hence significant resources are invested in predicting, preventing, and managing them. Biological systems and processes are typically large, complex, and inherently difficult to study naturally because of their immense scale and complexity. Hence, computational modelling and simulation approaches can be taken to study them. In this dissertation, I applied computer simulations to address two important problems in invasion biology. First, in invasion biology, the impact of genetic diversity of introduced populations on their establishment success is unknown. We took an individual-based modelling approach to explore this, leveraging an ecosystem simulation called EcoSim to simulate biological invasions. We conducted reciprocal transplants of prey individuals across two simulated environments, over a gradient of genetic diversity. Our simulation results demonstrated that a harsh environment with low and spatially-varying resource abundance mediated a relationship between genetic diversity and short-term establishment success of introduced populations rather than the degree of difference between native and introduced ranges. We also found that reducing Allee effects by maintaining compactness, a measure of spatial density, was key to the establishment success of prey individuals in EcoSim, which were sexually reproducing. Further, we found evidence of a more complex relationship between genetic diversity and long-term establishment success, assuming multiple introductions were occurring. Low-diversity populations seemed to benefit more strongly from multiple introductions than high-diversity populations. Our results also corroborated the evolutionary imbalance hypothesis: the environment that yielded greater diversity produced better invaders and itself was less invasible. Finally, our study corroborated a mechanical explanation for the evolutionary imbalance hypothesis – the populations evolved in a more intense competitive environment produced better invaders. Secondly, an important advancement in invasion biology is the use of genetic barcoding or metabarcoding, in conjunction with next-generation sequencing, as a potential means of early detection of aquatic introduced species. Barcoding and metabarcoding invariably requires some amount of computational DNA sequence processing. Unfortunately, optimal processing parameters are not known in advance and the consequences of suboptimal parameter selection are poorly understood. We aimed to determine the optimal parameterization of a common sequence processing pipeline for both early detection of aquatic nonindigenous species and conducting species richness assessments. We then aimed to determine the performance of optimized pipelines in a simulated inoculation of sequences into community samples. We found that early detection requires relatively lenient processing parameters. Further, optimality depended on the research goal – what was optimal for early detection was suboptimal for estimating species richness and vice-versa. Finally, with optimal parameter selection, fewer than 11 target sequences were required in order to detect 90% of nonindigenous species

Computational Analysis of T Cell Receptor Repertoire and Structure

The human adaptive immune system has evolved to provide a sophisticated response to a vast body of pathogenic microbes and toxic substances. The primary mediators of this response are T and B lymphocytes. Antigenic peptides presented at the surface of infected cells by major histocompatibility complex (MHC) molecules are recognised by T cell receptors (TCRs) with exceptional specificity. This specificity arises from the enormous diversity in TCR sequence and structure generated through an imprecise process of somatic gene recombination that takes place during T cell development. Quantification of the TCR repertoire through the analysis of data produced by high-throughput RNA sequencing allows for a characterisation of the immune response to disease over time and between patients, and the development of methods for diagnosis and therapeutic design. The latest version of the software package Decombinator extracts and quantifies the TCR repertoire with improved accuracy and compatibility with complementary experimental protocols and external computational tools. The software has been extended for analysis of fragmented short-read data from single cells, comparing favourably with two alternative tools. The development of cell-based therapeutics and vaccines is incomplete without an understanding of molecular level interactions. The breadth of TCR diversity and cross-reactivity presents a barrier for comprehensive structural resolution of the repertoire by traditional means. Computational modelling of TCR structures and TCR-pMHC complexes provides an efficient alternative. Four generalpurpose protein-protein docking platforms were compared in their ability to accurately model TCR-pMHC complexes. Each platform was evaluated against an expanded benchmark of docking test cases and in the context of varying additional information about the binding interface. Continual innovation in structural modelling techniques sets the stage for novel automated tools for TCR design. A prototype platform has been developed, integrating structural modelling and an optimisation routine, to engineer desirable features into TCR and TCR-pMHC complex models

Development and Assessment of an Environmental DNA (eDNA) Assay for the Rio Grande Siren and Review of eDNA Metabarcoding Applications

Environmental DNA (eDNA) assays have become a major aspect of amphibian surveys in the past decade. These methods are highly sensitive, making them well-suited for monitoring rare and cryptic species. Current efforts to study the Rio Grande Siren in south Texas have been hampered due to the cryptic nature of these aquatic salamanders. Arid conditions further add to the difficulty in studying this species, as many water bodies they inhabit are ephemeral, sometimes constraining sampling efforts to a short window after heavy rain. Additionally, sirens are known to cease activity and reside underground when ponds begin to dry or as water temperatures increase. Conventional sampling efforts require extensive trap-hours to be effective, which is not always possible within the required sampling window. This study presents the development of a novel eDNA assay technique for this elusive species and compare eDNA results with simultaneous trapping at multiple sites to assess the relative effectiveness of the procedure. This methodology gives promise for future work assessing the distribution and status of the Rio Grande Siren and has potential for use on other south Texas amphibians. An expansive literature review on the subject of eDNA metabarcoding is also presented, along with a plan for implementation of this method in south Texas for community amphibian studies

Bioengineered conduits for directing digitized molecular-based information

Molecular recognition is a prevalent quality in natural biological environments: molecules- small as well as macro- enable dynamic response by instilling functionality and communicating information about the system. The accession and interpretation of this rich molecular information leads to context about the system. Moreover, molecular complexity, both in terms of chemical structure and diversity, permits information to be represented with high capacity. Thus, an opportunity exists to assign molecules as chemical portrayals of natural, non-natural, and even non-biological data. Further, their associated upstream, downstream, and regulatory pathways could be commandeered for the purpose of data processing and transmission. This thesis emphasizes molecules that serve as units of information, the processing of which elucidates context. The project first strategizes a biocompatible assembly process that integrates biological componentry in an organized configuration for molecular transfer (e.g. from a cell to a receptor). Next, we have explored the use of DNA for its potential to store data in richer, digital forms. Binary data is embedded within a gene for storage inside a cell carrier and is selectively conveyed. Successively, a catalytic relay is developed to transduce similar data from sequence-based DNA storage to a delineated chemical cue that programs cellular phenotype. Finally, these cell populations are used as mobile information processing units that independently seek and collectively categorize the information, which is fed back as fluorescently ‘binned’ output. Every development demonstrates a transduction process of molecular data that involves input acquisition, refinement, and output interpretation. Overall, by equipping biomimetic networks with molecular-driven performance, their interactions serve as conduits of information flow