Knowledge discovery using multiple sources of biological data

The primary aim of this dissertation is to develop data mining tools for knowledge discovery in biomedical data when multiple (homogeneous or heterogeneous) sources of data are available. The central hypothesis is that, when information from multiple sources of data are used appropriately and effectively, knowledge discovery can be better achieved than what is possible from only a single source. ^ Recent advances in high-throughput technology have enabled biomedical researchers to generate large volumes of diverse types of data on a genome-wide scale. These data include DNA sequences, gene expression measurements, and much more; they provide the motivation for building analysis tools to elucidate the modular organization of the cell. The challenges include efficiently and accurately extracting information from the multiple data sources; representing the information effectively, developing analytical tools, and interpreting the results in the context of the domain. ^ The first part considers the application of feature-level integration to design classifiers that discriminate between soil types. The machine learning tools, SVM and KNN, were used to successfully distinguish between several soil samples. ^ The second part considers clustering using multiple heterogeneous data sources. The resulting Multi-Source Clustering (MSC) algorithm was shown to have a better performance than clustering methods that use only a single data source or a simple feature-level integration of heterogeneous data sources. ^ The third part proposes a new approach to effectively incorporate incomplete data into clustering analysis. Adapted from K-means algorithm, the Generalized Constrained Clustering (GCC) algorithm makes use of incomplete data in the form of constraints to perform exploratory analysis. Novel approaches for extracting constraints were proposed. For sufficiently large constraint sets, the GCC algorithm outperformed the MSC algorithm. ^ The last part considers the problem of providing a theme-specific environment for mining multi-source biomedical data. The database called PlasmoTFBM, focusing on gene regulation of Plasmodium falciparum, contains diverse information and has a simple interface to allow biologists to explore the data. It provided a framework for comparing different analytical tools for predicting regulatory elements and for designing useful data mining tools. ^ The conclusion is that the experiments reported in this dissertation strongly support the central hypothesis.^

Chemical characterization of soil organic matter in an oligotrophic, subtropical, freshwater wetland system: Sources, diagenesis and preservation

Freshwater wetland soils of the Everglades were studied in order to assess present environmental conditions and paleo-environmental changes using organic geochemistry techniques. Organic matter in dominant vegetation, peat and marl soils was characterized by geochemical means. Samples were selected along nutrient and hydrology gradients with the objective to determine the historical sources of organic matter as well as the extent of its preservation. Effective molecular proxies were developed to differentiate the relative input of organic matter from different biological sources to wetland soils. Thus historical vegetation shifts and hydroperiods were reconstructed using those proxies. The data show good correlations with historical water management practices starting at the turn of the century and during the mid 1900's. Overall, significant shortening of hydroperiods during this period was observed. The soil organic matter (SOM) preservation was assessed through elemental analysis and molecular characterizations of bulk 13C stable isotopes, solid state 13C NMR spectroscopy, UV-Vis spectroscopy, and tetramethyl ammonium hydroxide (TMAH) thermochemolysis-GC/MS. The relationship of the environmental conditions and degradation status of the soil organic matter (SOM) among the sites suggested that both high nutrient levels and long hydroperiod favor organic matter degradation in the soils. This is probably the result of an increase in the microbial activity in the soils which have higher nutrient levels, while longer hydroperiods may enhance physical/chemical degradation processes. The most significant transformations of biomass litter in this environment are controlled by very early physical/chemical processes and once the OM is incorporated into surface soils, the diagenetic change, even over extended periods of time is comparatively minimal, and SOM is relatively well preserved regardless of hydroperiod or nutrient levels. SOM accumulated in peat soils is more prone to continued degradation than the SOM in the marl soils. The latter is presumably stabilized early on through direct air exposure (oxidation) and thus, it is more refractory to further diagenetic transformations such as humification and aromatization reactions.

Across-scale patterning of plant-soil-water interactions surrounding tree islands in Southern Everglades landscapes

The freshwater Everglades is a complex system containing thousands of tree islands embedded within a marsh-grassland matrix. The tree island-marsh mosaic is shaped and maintained by hydrologic, edaphic and biological mechanisms that interact across multiple scales. Preserving tree islands requires a more integrated understanding of how scale-dependent phenomena interact in the larger freshwater system. The hierarchical patch dynamics paradigm provides a conceptual framework for exploring multi-scale interactions within complex systems. We used a three-tiered approach to examine the spatial variability and patterning of nutrients in relation to site parameters within and between two hydrologically defined Everglades landscapes: the freshwater Marl Prairie and the Ridge and Slough. Results were scale-dependent and complexly interrelated. Total carbon and nitrogen patterning were correlated with organic matter accumulation, driven by hydrologic conditions at the system scale. Total and bioavailable phosphorus were most strongly related to woody plant patterning within landscapes, and were found to be 3 to 11 times more concentrated in tree island soils compared to surrounding marshes. Below canopy resource islands in the slough were elongated in a downstream direction, indicating soil resource directional drift. Combined multi-scale results suggest that hydrology plays a significant role in landscape patterning and also the development and maintenance of tree islands. Once developed, tree islands appear to exert influence over the spatial distribution of nutrients, which can reciprocally affect other ecological processes.

Multiplex PCR for Assessment of Tetracycline Resistance (tet) Genes in Antibiotic-Resistant Soil Bacteria and the Ecological Implications

Antibiotics are becoming increasingly prevalent in bacterial communities due to clinical and agricultural misuse and overuse in their environment. As exposure increases, so does the incidence of microbial resistance. Such is the case with bacterial resistance to tetracyclines, a phenotype often acquired through the horizontal gene transfer of tet genes between bacteria. The objective of this project was to analyze the bacterial diversity of tet resistance genes in soil from Miami-Dade County. Bacterial isolates were Gram-stained and the Kirby-Bauer antibiotic disk diffusion test was performed to determine each bacterium’s degree of resistance. The 16S rRNA gene from antibiotic-resistant isolates was amplified by PCR and sequenced to identify the isolates. All isolates’ tet genes were amplified by multiplex PCR, sequenced, and compared. Among eight isolates, three distinct species were positively identified based on their 16S rRNA sequences and four distinct tet genes were identified, though all tested susceptible to tetracycline via the Kirby-Bauer test. This project clarifies some aspects of the ecology of antibiotic resistance genes, their natural ecological function and the potential for the expansion of intrinsic multi-antibiotic resistance into new ecosystems and/or hosts.

Enhanced Growth of Tetracycline-susceptible Soil Bacteria Treated with Iron and Oxytetracycline

Antibiotic resistance has become an important area of research because of the excessive use of antibiotics in clinical and agricultural settings that are driving the evolution of antibiotic resistant bacteria. However, drug tolerance is a naturally occurring phenomenon in soil communities, and is often linked to those soils that are exposed to heavy metals as well as antibiotics. Resistance to antibiotics maybe coupled with resistance to heavy metals in soil bacteria through efflux pumps that can be regulated by iron. Although considered s a heavy metal, iron is an essential component of life that regulates gene expression through the Ferric Uptake Regulator (Fur) protein. This master regulator protein is known to control siderophore production, and other biological pathways. As a suspected controller of biofilm formation, the role of Fur in environmental antibiotic resistance may be greater than is currently realized. In this study, we sought to explore a potential Fur-regulated drug tolerance pathway by understanding the response of soil bacteria when stressed with oxytetracycline and iron. Bacteria were collected from two locations in Miami Dade County. Isolates were first tested using Kirby-Bauer Disk Diffusion tests for antibiotic resistance/susceptibility and identified by 16S rDNA sequencing. A 96-well growth assay was developed to measure planktonic cell growth with 3 mM FeCl3, Oxytetracycline HCl, and the combination treatments. A Microtiter Dish Biofilm Formation Assay was employed and Fur diversity was evaluated. Tetracycline-susceptible bacterial isolates developed drug resistance with iron supplementation, but iron did not enhance biofilm formation. Development of a Fur-dependent drug resistance may be selected for, but further study is required to evaluate Fur evolution in the studied isolates. Gene expression analysis is also needed to further understand the ecological role of Fur and antibiotic resistance.

Analysis of organomercurials in environmental and biological samples by capillary column gas chromatography with atomic fluorescence detection

The general method for determining organomercurials in environmental and biological samples is gas chromatography with electron capture detection (GC-ECD). However, tedious sample work up protocols and poor chromatographic response show the need for the development of new methods. Here, Atomic Fluorescence-based methods are described, free from these deficiencies. The organomercurials in soil, sediment and tissue samples are first released from the matrices with acidic KBr and cupric ions and extracted into dichloromethane. The initial extracts are subjected to thiosulfate clean up and the organomercury species are isolated as their chloride derivatives by cupric chloride and subsequent extraction into a small volume of dichloromethane. In water samples the organomercurials are pre-concentrated using a sulfhydryl cotton fiber adsorbent, followed by elution with acidic KBr and CuSO 4 and extraction into dichloromethane. Analysis of the organomercurials is accomplished by capillary column chromatography with atomic fluorescence detection.