published_or_final_version / Biochemistry / Doctoral / Doctor of Philosophy

This study concerns the relationship between social and technological change. It asks whether the introduction of a new technology, computer mediated communication, enables scientists to engage in an altogether new and potentially more effective research activity, the online hunt for microbes. It shows that such technology, in the form of the Microbial Strain Data Network (MSDN), boosts significantly the overall speed, flexibility and extent of possible communication between microbe hunters and microbe suppliers. As a result, the global hunt for microbes in existing research and service oriented culture collections can transcend historiC geographic and institutional barriers that diminish its timeliness and comprehensiveness and, as a result, its potential utility. Therefore, the study hypothesises, microbe hunters will use extensively the MSDN's electronic mail and, especially, its online microbial strain databases. However, contrary to expectations, the mere availability of the MSDN is evidently insufficient to assure its widespread use. The MSDN was, in fact, little used during an extensive six month evaluation period in 1990191. Moreover, despite lowering its prices and increasing its strain database offerings, as well as improving its ease of use, the MSDN remains liltle used today. The study concludes that the MSDN's non-use reflects its general incompatibility with the context in which it was applied. The prevailing sociotechnological structure of microbiology diminishes significantly the accessibility, comparability, and reliability of shared strain data. In doing so, it reduces the potential benefits of CMC technology generally, and the MSDN in particular, in facilitating the online hunt for microbes. Success in the online hunt for microbes therefore requires changing the socio-technological context in which the hunt occurs. The discussion recommends possible changes to the socio-technological structure of microbiology to improve the online hunt's viability. It also points to the need for further research about the viability of the online hunt for microbes, as well as about the effective application of computer mediated communication technology to science generally.

No description available.

<p> Shaking palsy, or tremors are one of the four cardinal symptoms of Parkinson&rsquo;s Disease (PD). Tremors are a quantifiable symptom that should be detected to understand the severity of tremors in a patient suffering from PD. The proposed project has developed a prototype that measures tremor acceleration for twenty-four hours and saves the average acceleration per hour values in a text file of a computer. The tremor acceleration data saved from a patient&rsquo;s tremors is then sent to a healthcare provider for daily monitoring of the patient. </p><p> The tremor acceleration is measured using the accelerometer. The data from the accelerometer is processed by the Arduino board. The programming in the Arduino board is performed using C programming. The automatic emailer in the computer is programmed using Python programming language. On testing the prototype, the system demonstrated the capability to monitor tremors and transmit the data to the desired email address.</p>

Recent developments in DNA sequencing technology allow the study of microbial ecology at unmatched detail. To fully embrace this revolution, an important avenue of research is the development of bioinformatic tools that enable scientists to leverage and manipulate the exceedingly large amounts of data produced. In this thesis, several bioinformatic tools were developed in order to process and analyze metagenomic sequence data. Subsequently, the tools were applied to the study of microbial biogeography and microbial systems biology. A targeted metagenomics pipeline automating quality filtering, joining and taxonomic annotation was developed to assess the diversity of bacteria, archaea and eukaryotes permitting the study of biogeographic patterns in great detail. Next, a second software package which provides annotation based on environmental ontology terms was coded aiming to exploit the cornucopia of information available in public databases. It was applied to resource tracking, paleontology, and biogeography. Indeed, both these tools have already found broad applications in extending our understanding of microbial diversity in inland waters and have contributed to the development of conceptual frameworks for microbial biogeography in lotic systems. The programs were used for analyzing samples from several environments such as alkaline soda lakes and ancient sediment cores. These studies corroborated the view that the dispersal limitations of microbes are more or less non-existant as environmental properties dictating their distribution and that dormant microbes allow the reconstruction of the origin and history of the sampled community. Furthermore, a shotgun metagenomics analysis pipeline for the characterization of total DNA extraction from the environment was put in place. The pipeline included all essential steps from raw sequence processing to functional annotation and reconstruction of prokaryotic genomes. By applying this tool, we were able to reconstruct the biochemical processes in a selection of systems representative of the tens of millions of lakes and ponds of the boreal landscape. This revealed the genomic content of abundant and so far undescribed prokaryotes harboring important functions in these ecosystems. We could show the presence of organisms with the capacity for photoferrotrophy and anaerobic methanotrophy encoded in their genomes, traits not previously detected in these systems. In another study, we showed that microbes respond to alkaline conditions by adjusting their energy acquisition and carbon fixation strategies. To conclude, we demonstrated that the "reverse ecology" approach in which the role of microbes in elemental cycles is assessed by genomic tools is very powerful as we can identify novel pathways and obtain the partitioning of metabolic processes in natural environments.

<p>Population differentiation is both one of the central processes underlying the diversity that we observe in the natural world, and a mechanism that can be used to differentiate between evolutionary forces both at the level of the polymorphism, and at the level of the entire genome. Here, I use simulated evolution to analyze the statistical power to detect signals of selection in artificially selected laboratory populations, and use genomic data from wild populations of the clam shrimp Eulimnadia texana to identify genomic signals of selection in wild populations. Several loci in the wild populations appear to be under selection, and I analyze the types of genes that appear to contribute to differentiation of these populations. Additionally, I describe an analysis of genome assembly techniques that allowed for the creation of a highly contiguous genome assembly in the clam shrimp. I find that a pipeline that uses custom software to combine the results of several different genome assemblers is capable of producing genomes using long-read genomic sequencing data that are orders of magnitude more contiguous that pre-long-read methods. Simulations of experimental evolution indicated that extremely high levels of replication were necessary in order to achieve high power to detect signals of selection in experimental evolution. To this end, I describe a set of replicate experimentally evolved populations of E. texana that can be used to identify regions under selection with much higher power than could be accomplished with earlier experimental evolution schemes.

Several biomolecular pathways governing the control of cellular processes have been discovered over the last several years. Additionally, advances resulting from combining these pathways into networks have produced new insights into the complex behaviors observed in cell function assays. Unfortunately, identification of important subnetworks, or “motifs”, in these networks has been slower in development. This study focused on identifying important network motifs and their rate of occurrence in two different biomolecular networks. The two networks evaluated for this study represented both ends of the spectrum of interaction knowledge by comparing a well defined network (apoptosis) with and poorly studied network that was early in development (autism). This study identified several motifs that could be important in governing and controlling cellular processes in healthy and diseased cells. Additionally, this study revealed an inverse relationship when comparing the occurrence rate of these motifs in apoptosis and autism.

Virulent Trypanosoma cruzi, and the non-pathogenic Trypanosoma conorhini and Trypanosoma rangeli are protozoan parasites with divergent lifestyles. T. cruzi and T. rangeli are endemic to Latin America, whereas T. conorhini is tropicopolitan. Reduviid bug vectors spread these parasites to mammalian hosts, within which T. rangeli and T. conorhini replicate extracellularly, while T. cruzi has intracellular stages. Firstly, this work compares the genomes of these parasites to understand their differing phenotypes. Secondly, genome architecture of T. cruzi is examined to address the effect of a complex hybridization history, polycistronic transcription, and genome plasticity on this organism, and study its highly repetitive nature and cryptic genome organization. Whole genome sequencing, assembly and comparison, as well as chromosome-scale genome mapping were employed. This study presents the first comprehensive whole-genome maps of Trypanosoma, and the first T. conorhini strain ever sequenced. Original contributions vii to knowledge include the ~21-25 Mbp assembled genomes of the less virulent T. cruzi G, T. rangeli AM80, and T. conorhini 025E, containing ~10,000 to 13,000 genes, and the ~36 Mbp genome assembly of highly virulent T. cruzi CL with ~24,000 genes. The T. cruzi strains exhibited ~74% identity to proteins of T. rangeli or T. conorhini. T. rangeli and T. conorhini displayed greater complex carbohydrate metabolic capabilities, and contained fewer retrotransposons and multigene family copies, e.g. mucins, DGF-1, and MASP, compared to T. cruzi. Although all four genomes appear highly syntenic, T. rangeli and T. conorhini exhibited greater karyotype conservation. T. cruzi genome architecture studies revealed 66 maps varying from 0.13 to 2.4 Mbp. At least 2.6% of the genome comprises highly repetitive repeat regions, and 7.4% exhibits repetitive regions barren of labels. The 66 putative chromosomes identified are likely diploid. However, 20 of these maps contained regions of up to 1.25 Mbp of homology to at least one other map, suggestive of widespread segmental duplication or an ancient hybridization event that resulted in a genome with significant redundancy. Assembled genomes of these parasites closely reflect their phylogenetic relationships and give a greater context for understanding their divergent lifestyles. Genome mapping provides insight on the genomic evolution of these parasites.

Nematoda is a very diverse animal phylum. Within Nematoda, species display a multitude of life styles, different reproductive strategies and parasitism has arisen independently several times. Furthermore, morphological conservation and a high rate of homoplasy have impeded the resolution of nematode systematics. To address these issues, single gene (usually the nuclear ribosomal small subunit gene) and mitochondrial gene phylogenies have been used, but the information contained within the sequence of these genes is not enough to resolve the topological relationships between clades that emerged during rapid cladogenesis. Next generation sequencing data have been shown to produce high quality genomic and transcriptomic assemblies at low cost, as a result more and more nematode species are being sequenced. Sequences were gathered or generated for 53 nematode species from ESTs, gene predictions from full genome assemblies and transcripts from RNA-Seq experiments. These sequences were screened for orthologous gene clusters, which were concatenated into a supermatrix with thousands of aminoacid sites. The analysis of the supermatrix with maximum likelihood and Bayesian inference methods sheds light into the early splitting clades of the phylogenetic tree of nematodes and the derived clades III, IV and V. Furthermore, the phylogenetic relationships within the parastitic family Onchocercidae were resolved, unveiling the evolutionary history of these important taxa. Finally, data produced in this work will be useful for subsequent evolutionary studies of the phylum Nematoda.

<p> Metastatic, castrate-resistant prostate cancer (mCRPC) is one of the most prevalent cancers and is the third leading cause of cancer death among men. Several treatment options have been developed to combat mCRPC, however none have produced any tangible benefits to patients' overall survivability. As part of a crowd-sourced algorithm development competition, participants were asked to develop new prognostic models for mCRPC patients treated with docetaxel. Such results could potentially assist in clinical decision making for future mCRPC patients. </p><p> In this thesis, we present a new ensemble prognostic model to perform risk prediction for mCRPC patients treated with docetaxel. We rely on traditional survival analysis model like the Cox Proportional Hazard model, as well as more recently developed boosting model that incorporates smooth approximation of the concordance index for direct optimization. Our model performs better than the the current state-of-the-art mCRPC prognostic models for the concordance index performance measure and is competitive with these models on the integrated time-dependent area under the receiver operating characteristic curve.</p>