Matching Items (130)
Description
The oceans play an essential role in global biogeochemical cycles and in regulating climate. The biological carbon pump, the photosynthetic fixation of carbon dioxide by phytoplankton and subsequent sequestration of organic carbon into deep water, combined with the physical carbon pump, make the oceans the only long-term net sink for anthropogenic carbon dioxide. A full understanding of the workings of the biological carbon pump requires a knowledge of the role of different taxonomic groups of phytoplankton (protists and cyanobacteria) to organic carbon export. However, this has been difficult due to the degraded nature of particles sinking into particle traps, the main tools employed by oceanographers to collect sinking particulate matter in the ocean. In this study DNA-based molecular methods, including denaturing gradient gel electrophoresis, cloning and sequencing, and taxon-specific quantitative PCR, allowed for the first time for the identification of which protists and cyanobacteria contributed to the material collected by the traps in relation to their presence in the euphotic zone. I conducted this study at two time-series stations in the subtropical North Atlantic Ocean, one north of the Canary Islands, and one located south of Bermuda. The Bermuda study allowed me to investigate seasonal and interannual changes in the contribution of the plankton community to particle flux. I could also show that small unarmored taxa, including representatives of prasinophytes and cyanobacteria, constituted a significant fraction of sequences recovered from sediment trap material. Prasinophyte sequences alone could account for up to 13% of the clone library sequences of trap material during bloom periods. These observations contradict a long-standing paradigm in biological oceanography that only large taxa with mineral shells are capable of sinking while smaller, unarmored cells are recycled in the euphotic zone through the microbial loop. Climate change and a subsequent warming of the surface ocean may lead to a shift in the protist community toward smaller cell size in the future, but in light of these findings these changes may not necessarily lead to a reduction in the strength of the biological carbon pump.
ContributorsAmacher, Jessica (Author) / Neuer, Susanne (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Lomas, Michael (Committee member) / Wojciechowski, Martin (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2011
Description
Functional magnetic resonance imaging (fMRI) has been widely used to measure the retinotopic organization of early visual cortex in the human brain. Previous studies have identified multiple visual field maps (VFMs) based on statistical analysis of fMRI signals, but the resulting geometry has not been fully characterized with mathematical models. This thesis explores using concepts from computational conformal geometry to create a custom software framework for examining and generating quantitative mathematical models for characterizing the geometry of early visual areas in the human brain. The software framework includes a graphical user interface built on top of a selected core conformal flattening algorithm and various software tools compiled specifically for processing and examining retinotopic data. Three conformal flattening algorithms were implemented and evaluated for speed and how well they preserve the conformal metric. All three algorithms performed well in preserving the conformal metric but the speed and stability of the algorithms varied. The software framework performed correctly on actual retinotopic data collected using the standard travelling-wave experiment. Preliminary analysis of the Beltrami coefficient for the early data set shows that selected regions of V1 that contain reasonably smooth eccentricity and polar angle gradients do show significant local conformality, warranting further investigation of this approach for analysis of early and higher visual cortex.
ContributorsTa, Duyan (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Wonka, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
Pathogenic Gram-negative bacteria employ a variety of molecular mechanisms to combat host defenses. Two-component regulatory systems (TCR systems) are the most ubiquitous signal transduction systems which regulate many genes required for virulence and survival of bacteria. In this study, I analyzed different TCR systems in two clinically-relevant Gram-negative bacteria, i.e., oral pathogen Porphyromonas gingivalis and enterobacterial Escherichia coli. P. gingivalis is a major causative agent of periodontal disease as well as systemic illnesses, like cardiovascular disease. A microarray study found that the putative PorY-PorX TCR system controls the secretion and maturation of virulence factors, as well as loci involved in the PorSS secretion system, which secretes proteinases, i.e., gingipains, responsible for periodontal disease. Proteomic analysis (SILAC) was used to improve the microarray data, reverse-transcription PCR to verify the proteomic data, and primer extension assay to determine the promoter regions of specific PorX regulated loci. I was able to characterize multiple genetic loci regulated by this TCR system, many of which play an essential role in hemagglutination and host-cell adhesion, and likely contribute to virulence in this bacterium. Enteric Gram-negative bacteria must withstand many host defenses such as digestive enzymes, low pH, and antimicrobial peptides (AMPs). The CpxR-CpxA TCR system of E. coli has been extensively characterized and shown to be required for protection against AMPs. Most recently, this TCR system has been shown to up-regulate the rfe-rff operon which encodes genes involved in the production of enterobacterial common antigen (ECA), and confers protection against a variety of AMPs. In this study, I utilized primer extension and DNase I footprinting to determine how CpxR regulates the ECA operon. My findings suggest that CpxR modulates transcription by directly binding to the rfe promoter. Multiple genetic and biochemical approaches were used to demonstrate that specific TCR systems contribute to regulation of virulence factors and resistance to host defenses in P. gingivalis and E. coli, respectively. Understanding these genetic circuits provides insight into strategies for pathogenesis and resistance to host defenses in Gram negative bacterial pathogens. Finally, these data provide compelling potential molecular targets for therapeutics to treat P. gingivalis and E. coli infections.
ContributorsLeonetti, Cori (Author) / Shi, Yixin (Thesis advisor) / Stout, Valerie (Committee member) / Nickerson, Cheryl (Committee member) / Sandrin, Todd (Committee member) / Arizona State University (Publisher)
Created2013
Description
In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set of 3D morphological differences in the corpus callosum between two groups of subjects. The CCs are segmented from whole brain T1-weighted MRI and modeled as 3D tetrahedral meshes. The callosal surface is divided into superior and inferior patches on which we compute a volumetric harmonic field by solving the Laplace's equation with Dirichlet boundary conditions. We adopt a refined tetrahedral mesh to compute the Laplacian operator, so our computation can achieve sub-voxel accuracy. Thickness is estimated by tracing the streamlines in the harmonic field. We combine areal changes found using surface tensor-based morphometry and thickness information into a vector at each vertex to be used as a metric for the statistical analysis. Group differences are assessed on this combined measure through Hotelling's T2 test. The method is applied to statistically compare three groups consisting of: congenitally blind (CB), late blind (LB; onset > 8 years old) and sighted (SC) subjects. Our results reveal significant differences in several regions of the CC between both blind groups and the sighted groups; and to a lesser extent between the LB and CB groups. These results demonstrate the crucial role of visual deprivation during the developmental period in reshaping the structural architecture of the CC.
ContributorsXu, Liang (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
The study of bacterial resistance to antimicrobial peptides (AMPs) is a significant area of interest as these peptides have the potential to be developed into alternative drug therapies to combat microbial pathogens. AMPs represent a class of host-mediated factors that function to prevent microbial infection of their host and serve as a first line of defense. To date, over 1,000 AMPs of various natures have been predicted or experimentally characterized. Their potent bactericidal activities and broad-based target repertoire make them a promising next-generation pharmaceutical therapy to combat bacterial pathogens. It is important to understand the molecular mechanisms, both genetic and physiological, that bacteria employ to circumvent the bactericidal activities of AMPs. These understandings will allow researchers to overcome challenges posed with the development of new drug therapies; as well as identify, at a fundamental level, how bacteria are able to adapt and survive within varied host environments. Here, results are presented from the first reported large scale, systematic screen in which the Keio collection of ~4,000 Escherichia coli deletion mutants were challenged against physiologically significant AMPs to identify genes required for resistance. Less than 3% of the total number of genes on the E. coli chromosome was determined to contribute to bacterial resistance to at least one AMP analyzed in the screen. Further, the screen implicated a single cellular component (enterobacterial common antigen, ECA) and a single transporter system (twin-arginine transporter, Tat) as being required for resistance to each AMP class. Using antimicrobial resistance as a tool to identify novel genetic mechanisms, subsequent analyses were able to identify a two-component system, CpxR/CpxA, as a global regulator in bacterial resistance to AMPs. Multiple previously characterized CpxR/A members, as well as members found in this study, were identified in the screen. Notably, CpxR/A was found to transcriptionally regulate the gene cluster responsible for the biosynthesis of the ECA. Thus, a novel genetic mechanism was uncovered that directly correlates with a physiologically significant cellular component that appears to globally contribute to bacterial resistance to AMPs.
ContributorsWeatherspoon-Griffin, Natasha (Author) / Shi, Yixin (Thesis advisor) / Clark-Curtiss, Josephine (Committee member) / Misra, Rajeev (Committee member) / Nickerson, Cheryl (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2013
Description
Microbial electrochemical cells (MXCs) are promising platforms for bioenergy production from renewable resources. In these systems, specialized anode-respiring bacteria (ARB) deliver electrons from oxidation of organic substrates to the anode of an MXC. While much progress has been made in understanding the microbiology, physiology, and electrochemistry of well-studied model ARB such as Geobacter and Shewanella, tremendous potential exists for MXCs as microbiological platforms for exploring novel ARB. This dissertation introduces approaches for selective enrichment and characterization of phototrophic, halophilic, and alkaliphilic ARB. An enrichment scheme based on manipulation of poised anode potential, light, and nutrient availability led to current generation that responded negatively to light. Analysis of phototrophically enriched communities suggested essential roles for green sulfur bacteria and halophilic ARB in electricity generation. Reconstruction of light-responsive current generation could be successfully achieved using cocultures of anode-respiring Geobacter and phototrophic Chlorobium isolated from the MXC enrichments. Experiments lacking exogenously supplied organic electron donors indicated that Geobacter could produce a measurable current from stored photosynthate in the dark. Community analysis of phototrophic enrichments also identified members of the novel genus Geoalkalibacter as potential ARB. Electrochemical characterization of two haloalkaliphilic, non-phototrophic Geoalkalibacter spp. showed that these bacteria were in fact capable of producing high current densities (4-8 A/m2) and using higher organic substrates under saline or alkaline conditions. The success of these selective enrichment approaches and community analyses in identifying and understanding novel ARB capabilities invites further use of MXCs as robust platforms for fundamental microbiological investigations.
ContributorsBadalamenti, Jonathan P (Author) / Krajmalnik-Brown, Rosa (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Rittmann, Bruce E. (Committee member) / Torres, César I (Committee member) / Vermaas, Willem (Committee member) / Arizona State University (Publisher)
Created2013
Description
Human activity has increased loading of reactive nitrogen (N) in the environment, with important and often deleterious impacts on biodiversity, climate, and human health. Since the fate of N in the ecosystem is mainly controlled by microorganisms, understanding the factors that shape microbial communities becomes relevant and urgent. In arid land soils, these microbial communities and factors are not well understood. I aimed to study the role of N cycling microbes, such as the ammonia-oxidizing bacteria (AOB), the recently discovered ammonia-oxidizing archaea (AOA), and various fungal groups, in soils of arid lands. I also tested if niche differentiation among microbial populations is a driver of differential biogeochemical outcomes. I found that N cycling microbial communities in arid lands are structured by environmental factors to a stronger degree than what is generally observed in mesic systems. For example, in biological soil crusts, temperature selected for AOA in warmer deserts and for AOB in colder deserts. Land-use change also affects niche differentiation, with fungi being the major agents of N2O production in natural arid lands, whereas emissions could be attributed to bacteria in mesic urban lawns. By contrast, NO3- production in the native desert and managed soils was mainly controlled by autotrophic microbes (i.e., AOB and AOA) rather than by heterotrophic fungi. I could also determine that AOA surprisingly responded positively to inorganic N availability in both short (one month) and long-term (seven years) experimental manipulations in an arid land soil, while environmental N enrichment in other ecosystem types is known to favor AOB over AOA. This work improves our predictions of ecosystem response to anthropogenic N increase and shows that paradigms derived from mesic systems are not always applicable to arid lands. My dissertation also highlights the unique ecology of ammonia oxidizers and draws attention to the importance of N cycling in desert soils.
ContributorsMarusenko, Yevgeniy (Author) / Hall, Sharon J (Thesis advisor) / Garcia-Pichel, Ferran (Thesis advisor) / Mclain, Jean E (Committee member) / Schwartz, Egbert (Committee member) / Arizona State University (Publisher)
Created2013
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Laboratory automation systems have seen a lot of technological advances in recent times. As a result, the software that is written for them are becoming increasingly sophisticated. Existing software architectures and standards are targeted to a wider domain of software development and need to be customized in order to use them for developing software for laboratory automation systems. This thesis proposes an architecture that is based on existing software architectural paradigms and is specifically tailored to developing software for a laboratory automation system. The architecture is based on fairly autonomous software components that can be distributed across multiple computers. The components in the architecture make use of asynchronous communication methodologies that are facilitated by passing messages between one another. The architecture can be used to develop software that is distributed, responsive and thread-safe. The thesis also proposes a framework that has been developed to implement the ideas proposed by the architecture. The framework is used to develop software that is scalable, distributed, responsive and thread-safe. The framework currently has components to control very commonly used laboratory automation devices such as mechanical stages, cameras, and also to do common laboratory automation functionalities such as imaging.
ContributorsKuppuswamy, Venkataramanan (Author) / Meldrum, Deirdre (Thesis advisor) / Collofello, James (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Johnson, Roger (Committee member) / Arizona State University (Publisher)
Created2012