Matching Items (126)
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
In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.
ContributorsOran, Paul (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Ros, Alexandra (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
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
Surface plasmon resonance (SPR) has emerged as a popular technique for elucidating subtle signals from biological events in a label-free, high throughput environment. The efficacy of conventional SPR sensors, whose signals are mass-sensitive, diminishes rapidly with the size of the observed target molecules. The following work advances the current SPR sensor paradigm for the purpose of small molecule detection. The detection limits of two orthogonal components of SPR measurement are targeted: speed and sensitivity. In the context of this report, speed refers to the dynamic range of measured kinetic rate constants, while sensitivity refers to the target molecule mass limitation of conventional SPR measurement. A simple device for high-speed microfluidic delivery of liquid samples to a sensor surface is presented to address the temporal limitations of conventional SPR measurement. The time scale of buffer/sample switching is on the order of milliseconds, thereby minimizing the opportunity for sample plug dispersion. The high rates of mass transport to and from the central microfluidic sensing region allow for SPR-based kinetic analysis of binding events with dissociation rate constants (kd) up to 130 s-1. The required sample volume is only 1 μL, allowing for minimal sample consumption during high-speed kinetic binding measurement. Charge-based detection of small molecules is demonstrated by plasmonic-based electrochemical impedance microscopy (P-EIM). The dependence of surface plasmon resonance (SPR) on surface charge density is used to detect small molecules (60-120 Da) printed on a dextran-modified sensor surface. The SPR response to an applied ac potential is a function of the surface charge density. This optical signal is comprised of a dc and an ac component, and is measured with high spatial resolution. The amplitude and phase of local surface impedance is provided by the ac component. The phase signal of the small molecules is a function of their charge status, which is manipulated by the pH of a solution. This technique is used to detect and distinguish small molecules based on their charge status, thereby circumventing the mass limitation (~100 Da) of conventional SPR measurement.
ContributorsMacGriff, Christopher Assiff (Author) / Tao, Nongjian (Thesis advisor) / Wang, Shaopeng (Committee member) / LaBaer, Joshua (Committee member) / Chae, Junseok (Committee member) / Arizona State University (Publisher)
Created2013
Description
Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay (MSIA) which has been one of the primary methods of biomarker discovery techniques. MSIA analyzes protein molecules as potential biomarkers using time of flight mass spectrometry (TOF-MS). Peak detection in TOF-MS is important for biomarker analysis and many other MS related application. Though many peak detection algorithms exist, most of them are based on heuristics models. One of the ways of detecting signal peaks is by deploying stochastic models of the signal and noise observations. Likelihood ratio test (LRT) detector, based on the Neyman-Pearson (NP) lemma, is an uniformly most powerful test to decision making in the form of a hypothesis test. The primary goal of this dissertation is to develop signal and noise models for the electrospray ionization (ESI) TOF-MS data. A new method is proposed for developing the signal model by employing first principles calculations based on device physics and molecular properties. The noise model is developed by analyzing MS data from careful experiments in the ESI mass spectrometer. A non-flat baseline in MS data is common. The reasons behind the formation of this baseline has not been fully comprehended. A new signal model explaining the presence of baseline is proposed, though detailed experiments are needed to further substantiate the model assumptions. Signal detection schemes based on these signal and noise models are proposed. A maximum likelihood (ML) method is introduced for estimating the signal peak amplitudes. The performance of the detection methods and ML estimation are evaluated with Monte Carlo simulation which shows promising results. An application of these methods is proposed for fractional abundance calculation for biomarker analysis, which is mathematically robust and fundamentally different than the current algorithms. Biomarker panels for type 2 diabetes and cardiovascular disease are analyzed using existing MS analysis algorithms. Finally, a support vector machine based multi-classification algorithm is developed for evaluating the biomarkers' effectiveness in discriminating type 2 diabetes and cardiovascular diseases and is shown to perform better than a linear discriminant analysis based classifier.
ContributorsBuddi, Sai (Author) / Taylor, Thomas (Thesis advisor) / Cochran, Douglas (Thesis advisor) / Nelson, Randall (Committee member) / Duman, Tolga (Committee member) / Arizona State University (Publisher)
Created2012
Description
Biological soil crusts (BSCs), topsoil microbial assemblages typical of arid land ecosystems, provide essential ecosystem services such as soil fertilization and stabilization against erosion. Cyanobacteria and lichens, sometimes mosses, drive BSC as primary producers, but metabolic activity is restricted to periods of hydration associated with precipitation. Climate models for the SW United States predict changes in precipitation frequency as a major outcome of global warming, even if models differ on the sign and magnitude of the change. BSC organisms are clearly well adapted to withstand desiccation and prolonged drought, but it is unknown if and how an alteration of the precipitation frequency may impact community composition, diversity, and ecosystem functions. To test this, we set up a BSC microcosm experiment with variable precipitation frequency treatments using a local, cyanobacteria-dominated, early-succession BSC maintained under controlled conditions in a greenhouse. Precipitation pulse size was kept constant but 11 different drought intervals were imposed, ranging between 416 to 3 days, during a period of 416 days. At the end of the experiments, bacterial community composition was analyzed by pyrosequencing of the 16s rRNA genes in the community, and a battery of functional assays were used to evaluate carbon and nitrogen cycling potentials. While changes in community composition were neither marked nor consistent at the Phylum level, there was a significant trend of decreased diversity with increasing precipitation frequency, and we detected particular bacterial phylotypes that responded to the frequency of precipitation in a consistent manner (either positively or negatively). A significant trend of increased respiration with increasingly long drought period was detected, but BSC could recover quickly from this effect. Gross photosynthesis, nitrification and denitrification remained essentially impervious to treatment. These results are consistent with the notion that BSC community structure adjustments sufficed to provide significant functional resilience, and allow us to predict that future alterations in precipitation frequency are unlikely to result in severe impacts to BSC biology or ecological relevance.
ContributorsMyers, Natalie Kristine (Author) / Garcia-Pichel, Ferran (Thesis advisor) / Hall, Sharon (Committee member) / Turner, Benjamin (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
Improving cyanobacterial hydrogen production through bioprospecting of natural microbial communities
Description
Some cyanobacteria can generate hydrogen (H2) under certain physiological conditions and are considered potential agents for biohydrogen production. However, they also present low amounts of H2 production, a reaction reversal towards H2 consumption, and O2 sensitivity. Most attempts to improve H2 production have involved genetic or metabolic engineering approaches. I used a bio-prospecting approach instead to find novel strains that are naturally more apt for biohydrogen production. A set of 36, phylogenetically diverse strains isolated from terrestrial, freshwater and marine environments were probed for their potential to produce H2 from excess reductant. Two distinct patterns in H2 production were detected. Strains displaying Pattern 1, as previously known from Synechocystis sp. PCC 6803, produced H2 only temporarily, reverting to H2 consumption within a short time and after reaching only moderately high H2 concentrations. By contrast, Pattern 2 cyanobacteria, in the genera Lyngbya and Microcoleus, displayed high production rates, did not reverse the direction of the reaction and reached much higher steady-state H2 concentrations. L. aestuarii BL J, an isolate from marine intertidal mats, had the fastest production rates and reached the highest steady-state concentrations, 15-fold higher than that observed in Synechocystis sp. PCC 6803. Because all Pattern 2 strains originated in intertidal microbial mats that become anoxic in dark, it was hypothesized that their strong hydrogenogenic capacity may have evolved to aid in fermentation of the photosynthate. When forced to ferment, these cyanobacteria display similarly desirable characteristics of physiological H2 production. Again, L. aestuarii BL J had the fastest specific rates and attained the highest H2 concentrations during fermentation, which proceeded via a mixed-acid pathway to yield acetate, ethanol, lactate, H2, CO2 and pyruvate. The genome of L. aestuarii BL J was sequenced and bioinformatically compared to other cyanobacterial genomes to ascertain any potential genetic or structural basis for powerful H2 production. The association hcp exclusively in Pattern 2 strains suggests its possible role in increased H2 production. This study demonstrates the value of bioprospecting approaches to biotechnology, pointing to the strain L. aestuarii BL J as a source of useful genetic information or as a potential platform for biohydrogen production.
ContributorsKothari, Ankita (Author) / Garcia-Pichel, Ferran (Thesis advisor) / Vermaas, Willem F J (Committee member) / Rittmann, Bruce (Committee member) / Torres, Cesar (Committee member) / Arizona State University (Publisher)
Created2013
Description
Future robotic and human missions to the Moon and Mars will need in situ capabilities to characterize the mineralogy of rocks and soils within a microtextural context. Such spatially-correlated information is considered crucial for correct petrogenetic interpretations and will be key observations for assessing the potential for past habitability on Mars. These data will also enable the selection of the highest value samples for further analysis and potential caching for return to Earth. The Multispectral Microscopic Imager (MMI), similar to a geologist's hand lens, advances the capabilities of current microimagers by providing multispectral, microscale reflectance images of geological samples, where each image pixel is comprised of a 21-band spectrum ranging from 463 to 1735 nm. To better understand the capabilities of the MMI in future surface missions to the Moon and Mars, geological samples comprising a range of Mars-relevant analog environments as well as 18 lunar rocks and four soils, from the Apollo collection were analyzed with the MMI. Results indicate that the MMI images resolve the fine-scale microtextural features of samples, and provide important information to help constrain mineral composition. Spectral end-member mapping revealed the distribution of Fe-bearing minerals (silicates and oxides), along with the presence of hydrated minerals. In the case of the lunar samples, the MMI observations also revealed the presence of opaques, glasses, and in some cases, the effects of space weathering in samples. MMI-based petrogenetic interpretations compare favorably with laboratory observations (including VNIR spectroscopy, XRD, and thin section petrography) and previously published analyses in the literature (for the lunar samples). The MMI was also deployed as part of the 2010 ILSO-ISRU field test on the slopes of Mauna Kea, Hawaii and inside the GeoLab as part of the 2011 Desert RATS field test at the Black Point Lava Flow in northern Arizona to better assess the performance of the MMI under realistic field conditions (including daylight illumination) and mission constraints to support human exploration. The MMI successfully imaged rocks and soils in outcrops and samples under field conditions and mission operation scenarios, revealing the value of the MMI to support future rover and astronaut exploration of planetary surfaces.
ContributorsNúñez Sánchez, Jorge Iván (Author) / Farmer, Jack D. (Thesis advisor) / Christensen, Philip R. (Committee member) / Garcia-Pichel, Ferran (Committee member) / Robinson, Mark S. (Committee member) / Sellar, R. Glenn (Committee member) / Williams, Lynda B. (Committee member) / Arizona State University (Publisher)
Created2012