Organizational Unit:
School of Biological Sciences

Permanent Link
https://hdl.handle.net/1853/70750
Research Organization Registry ID
Description
Previous Names
Parent Organization
Parent Organization
Organizational Unit
Includes Organization(s)
ArchiveSpace Name Record
https://finding-aids.library.gatech.edu/agents/corporate_entities/1131

Filters

2010 - 2019 158
158 1
158
158
Reset filters

Settings
End date: 2019 × Start date: 2010 × search.filters.applied.f.resourcesubtype: Dissertation ×

Publication Search Results

Now showing 1 - 10 of 158
Thumbnail Image
Item

Ecological Community Assembly in the Face of Anthropogenic Environmental Changes

2019-11-11 , Yang, Xian

Anthropogenic environmental changes, such as increased nitrogen (N) deposition, changes in precipitation regimes, and habitat loss and fragmentation, are known to affect Earth’s ecosystems. Understanding mechanisms regulating the assembly of ecological communities in the face of anthropogenic environmental changes is one of the primary goals of contemporary ecology. In this dissertation, I present four studies addressing questions on community assembly under anthropogenic environmental changes. First, I conducted an experiment in a semi-arid grassland to examine how anthropogenic environmental changes, in the form of resource addition, influence phylogenetic alpha- and beta-diversity of the communities. I found N and water addition influenced different aspects of grassland community structure. N addition altered plant community phylogenetic structure, driving communities towards phylogenetic overdispersion; water addition promoted phylogenetic convergence, driving communities to converge towards a more similar phylogenetic structure over time. Next, I used bacterivorous ciliated protists as model organisms to explore how the loss of a keystone local community affects metacommunity biodiversity and ecosystem functions. I found that local communities with distinct environmental conditions supported endemic species, and had greater impact on regional-scale diversity than other local communities, therefore qualifying them as keystone communities. These keystone communities also had significant impacts on ecosystem functions, including biomass production and particulate organic matter decomposition. Finally, I investigated the drivers of variation in the phyllosphere microbial community composition in a fragmented subtropical forest on the islands of the Thousand-Island Lake, China. I found that stochastic processes, rather than deterministic processes, played a prominent role in shaping phyllosphere bacterial and fungal communities in the context of habitat fragmentation. Taken together, these findings further our understanding of community assembly processes in the face of anthropogenic environmental changes.

View
Thumbnail Image
Item

Genetic epidemiology algorithms for tracking drug resistance variants and genomic clustering of plasmodium species

2019-09-03 , Ravishankar, Shashidhar

The goal of this thesis is to develop algorithms for the analysis of P. falciparum, P. brasilianum, and P. malariae. Malaria is endemic in many parts of the world, including regions of central Africa, South America, and South East Asia. There are five known species that cause malaria in humans: P. falciparum, P. vivax, P. malariae, P. ovale, and P. knowlesi. P. knowlesi is a zoonotic parasite restricted to mostly South East Asia.According to a World Health Organization (WHO) report from 2018, these five species were responsible for nearly 219 million infections, resulting in an estimated 435,000 deaths related to malaria in 2017. In this work, we highlight algorithms that can identify the similarity between Plasmodium species and detect drug-resistant P. falciparum parasites. The two specific aims in this work, describe two novel algorithms for genomic clustering and molecular surveillance from Next-generation Sequencing (NGS) data. First, we describe a consensus-based variant identification framework molecular surveillance of drug resistance in infectious disease. We highlight its utility by identifying mutations associated with drug resistance in malaria isolates. The scalability of the framework is highlighted by analyzing 8351 M. tuberculosis isolates for the genotypic prediction of drug resistance. In the second aim, we describe a k-mer based alignment-free algorithm for the estimation of similarity between isolates from raw NGS data. Using a weighted Jaccard distance, we describe an exact method for estimation of the distance between isolates from k-mer count data. The memory efficiency, scalability, and accuracy of the algorithm was demonstrated using in-silico datasets generated from genomes of 12 Plasmodium species, as well as real-world isolates from an outbreak of C. auris in Colombia. The improved accuracy and scalability offered by the methods described in this work can facilitate the use of NGS in public health.

View
Thumbnail Image
Item

Public health informatics - Strategy and decision modeling

2019-08-21 , Tian, Haozheng

My research is composed of three studies focused on providing decision modeling and analytical tools with the objective of protecting public health. The first study introduces an agent-based simulation platform that serves as a decision support system for crowd management in public venues. I propose a new implementation of agent-based simulation with improvement on four aspects: path planning, collision avoidance, emotion modeling and optimization with simulation. The deliverables of this study also include a complete simulation platform for researcher’s use. The second study applies a data-driven informatics and machine learning approach to quantify the outcome of practice variance of medical care providers. The study investigates the safety and efficacy of a large-dose, needle-based epidural anesthesia technique for parturient women. Machine learning model is proposed as the classifier to predict the occurrence of hypotension. Further, machine learning approach is applied to predict the outcome of epidural anesthesia, uncovering the important factors of a successful practice. Quantification of the effect of practice variance and medicine usage is provided. The findings from this investigation facilitate delivery improvement and establish an improved clinical practice guideline for training and for dissemination of safe practice. The third study proposes the application of convolutional neural network (CNN) in the prediction of antigenicity of influenza viruses (A/H3N2) and vaccine recommendation. The study systematically explores the ways of representation of hemagglutinin (HA) besides using binary digit or character as widely applied in other researches. Heuristic optimization is applied to optimize the selection of AAindex as well as the structure of CNN. Contrasting to other state-of-the-art approaches, the model offers better coverage in vaccine recommendation and has superior performance in accurate prediction of antigenicity.

View
Thumbnail Image
Item

Integrative immunotranscriptomic analysis of long-lived plasma cells

2019-05-21 , Garimalla, Swetha N.

Long-lived plasma cells are a key component of serological memory encoded by the adaptive immune response. To date, prior studies of these cell types have largely assessed plasma cells as one homogenous population. The Lee Lab at Emory University provided strong evidence for the presence of subpopulations of plasma cells in the bone marrow and peripheral blood. In this work, I analyze six of these populations: pops 2, 3, and 5 in the peripheral blood and pops A, B, and D in the bone marrow sampled from live human donors. Whole-transcriptome analysis of these six flow-sorted plasma cell populations is compared within and across tissue within this study. Further, I present 4 possible models of development of these plasma cells based on the results. Finally, I performed a singlecell RNA sequencing analysis of the long-lived plasma cells (popD) and present evidence for the possibility of subpopulations of this cell type. This work describes many mechanisms of molecular development of long-lived plasma cells, some of which have been experimentally validated by Dr. Doan Nguyen as a result of these analyses, however, further experimental validation is required to validate all findings in this work.

View
Thumbnail Image
Item

Human genetic ancestry, health, and adaptation in Latin America

2019-11-05 , Norris, Emily Taylor

Genetic admixture is the process that occurs when populations that were previously reproductively isolated, and consequently genetically diverged, come back together and exchange genes. Recent studies of modern and ancient genomes have underscored the frequency with which admixture has occurred during human evolution. Indeed, human evolution has been characterized by numerous iterations of physical isolation and genetic divergence followed by population convergence and admixture. Genetic admixture has profound implications for human evolution as it results in the creation of evolutionarily novel genomes that contain combinations of genetic variants (haplotypes) never seen before on the same genomic background. This dissertation explores the implications of large-scale genetic admixture in Latin America for human health, evolution (natural selection), and population structure (assortative mating). Latin America provides an ideal setting to explore the implications of admixture given the formation of modern populations via admixture among distinct African, European, and Native American population groups. Human health and evolution are explored through the lens of admixture, with an emphasis on the demographic processes that serve to combine distinct ancestry components within genomes. Population structure is considered with respect to assortative mating, which serves to limit the extent of genetic admixture within populations, thereby maintaining genetic diversity among distinct population groups even when they are co-located. In order to understand the implications of admixture for the formation of the New World, comparative genomic analyses were used to characterize patterns of genetic ancestry and admixture for individuals from four modern Latin American populations: Colombia, Mexico, Peru, and Puerto Rico. Comparative genomic analyses with ancestral source populations allowed for the characterization of genetic ancestry and admixture profiles for these four Latin American populations at both genome-wide (global) and variant/gene (local) levels. These data on genetic ancestry were integrated with a variety of functional genomic data sources in an effort to more fully understand the biological implications of admixture. Global patterns of ancestry for each population were used to parameterize the expected values of local ancestry, for both specific genetic variants and at the level of individual genes, and comparisons of observed versus expected ancestry levels were used to look for anomalous deviations of local ancestry, i.e. ancestry enrichment. Ancestry-enriched genetic variants were implicated in a number of health-related phenotypes, including immune system and disease response pathways, and a number of these variants were shown to exert their phenotypic effects via ancestry-specific gene regulation. Ancestry enrichment at the gene level was used to provide evidence for rapid adaptation to local environments via admixture-enabled selection, which occurs when admixture introduces novel genetic variants (haplotypes) to newly formed populations at intermediate frequencies. Admixture-enabled selection was observed for the major histocompatibility complex (MHC) locus of the adaptive immune system across multiple Latin American populations, and both the adaptive and innate immune systems were shown to evolve via polygenic admixture-enabled selection. Patterns of gene level ancestry were also used to search for evidence of population structure caused by assortative mating, whereby mate choice is influenced by phenotypic similarity. This analysis allowed us to characterize the genetic basis of phenotypic cues that influence patterns of assortative mating, including a number of anthropometric and neurological traits as well as the MHC locus. Considered together, these results underscore the outsized role that admixture has played in shaping the biology of modern Latin American populations. Global patterns of genetic ancestry and admixture are distinct to each population, and local ancestry can differ widely even for closely related individuals within a population. Local ancestry impacts a wide variety of health-related traits, provides the raw material for rapid, adaptive evolution, and informs the phenotypic cues that are used for mate choice and help to maintain population structure.

View
Thumbnail Image
Item

Global dysregulation of gene expression and tumorigenesis: Data science for cancer

2019-09-03 , Clayton, Evan

Dysregulation of gene expression is a hallmark of cancer. Broadly speaking, my research is focused on the changes in gene expression that characterize the transition from normal to cancerous states, i.e. tumorigenesis. To study such changes, I performed integrated analysis of next generation sequencing data for matched normal and primary tumor samples from hundreds of patients across numerous different cancer types. By analyzing this sequencing data, I have been able to explore the global landscape of transcriptional reprogramming in cancer and discover how changes in the regulation of gene expression may be implicated in tumorigenesis. My thesis is focused on four specific areas of transcriptional reprogramming in cancer: (1) changes in the expression and activity of transposable elements (TEs), (2) changes in alternative splicing induced by TEs, (3) allele-specific expression of tumor suppressor genes (TSGs), and (4) gene expression changes that are implicated in cancer drug response. TEs are known to be uniformly overexpressed in cancer, suggesting a possible role for their activity in tumorigenesis. I discovered a class of long interspersed nuclear elements (the LINE-1 family) with elevated levels of expression and activity in three different cancer types, and I showed examples where cancer-specific LINE-1 insertions disrupt enhancers, leading to the down-regulation of TSGs. TEs are also implicated in the creation of novel splicing isoforms, and aberrant alternative splicing has been associated with tumorigenesis for a number of different cancers. Integrated analysis of genome sequence and transcriptome data revealed thousands of TE-generated alternative splice events genome-wide, including close to 5,000 events distributed among cancer associated genes. I explored the functional implications of specific cases of isoform switching, whereby TE-induced isoforms of cancer associated genes show elevated levels of relative expression in tumor samples. A closer look at TSG expression in matched normal and tumor samples indicated that functionally important changes in patterns of allele-specific expression in individuals heterozygous for loss-of-function TSG alleles is a significant factor in cancer onset/progression. These results identified a variety of molecular mechanisms that contribute to the observed changes in allele-specific expression patterns in cancer with allele-specific alternative splicing mediated by anti-sense RNA emerging as a predominant factor. Furthermore, analysis of the genomic variation for world-wide human populations demonstrates that loss-of-function TSG alleles are segregating at remarkedly high frequencies implying that a significant fraction of otherwise healthy individuals may be pre-disposed to developing cancer. For the final study of my thesis research, I applied the gene expression data from primary tumor samples to build predictive models of cancer drug response for two common chemotherapeutics: 5-Fluorouracil and Gemcitabine. My gene expression based models predict whether patients will respond to individual therapies with up to 86% accuracy. The genes that I found to be most informative for predicting drug response were enriched in well-known cancer signaling pathways highlighting their potential significance in prognosis of chemotherapy.

View
Thumbnail Image
Item

Densely packed yeast: A tool to study evolution of group dynamics and to enhance biomanufacturing

2019-08-19 , Gulli, Jordan

Yeast can thrive in dense assemblages of its own, or our making, resulting in patterns of behavior that differ markedly from that of single planktonic cells. We first studied unicellular yeast that create their own assemblage upon selection for rapid settling in liquid medium. In these experiments, large clonal clusters, composed of hundreds to thousands of cells, began to form even larger macroscopic aggregates composed of hundreds of potentially unrelated clusters. The matrix of these aggregates includes extracellular proteins, and is likely produced via apoptosis. We found that such aggregates increase survival in environments that favor fast settling, but are evolutionarily unstable because they do not discriminate between aggregate-producers and non-producers. Next, we examined unicellular yeast maintained at high density via immobilization in a Ca2+-alginate matrix. Immobilization uncouples reproduction from metabolism, resulting in metabolically active but growth-arrested cells. Because immobilized yeast allocates little substrate to biomass, we investigated its potential to enhance ethanol production under biorefinery-like conditions. We found that over a 7-week course of fed-batch culture immobilized yeast is able to produce more ethanol from the same amount of substrate than planktonic yeast. We further tested the resilience of different immobilization matrices to support long-term, fed-batch cultures, and determined that Protanal alginate has the lowest rates of cell escape and the highest ethanol yields. Lastly, we tested whether immobilization, by inducing replication arrest, could stabilize the genomes of dikaryons created by protoplast fusion of different yeast species: Saccharomyces cerevisiae and Pichia stipitis. In the absence of selection, planktonic dikaryons quickly revert to their parental genotypes via nuclear segregation during replication. We discovered that genome content of growth-arrested immobilized dikaryons is stable in 19-day, fed-batch cultures, and that stable dikaryons retain the metabolic capacity of different the fused species to ferment 6-carbon and 5-carbon sugars. Taken together, our results demonstrate the utility of densely-packed yeasts to address issues related to the evolution of group dynamics as well as to enhance efficiency and longevity in biomanufacturing.

View
Thumbnail Image
Item

Exploring the ecological and evolutionary consequences of clonal and aggregative development during the transition to multicellularity

2019-09-03 , Pentz, Jennifer T.

Multicellular organisms form groups in one of two basic ways: cells can ‘stay together’ due to incomplete separation following cellular division (clonal development), or cells can ‘come together’ via aggregation (aggregative development). Multicellularity has evolved multiple times via both routes, but all ‘complex multicellularity’ (e.g., plants, animals, fungi) has only evolved in lineages that develop clonally. Evolutionary theory predicts that clonal development may be superior to aggregation because groups formed this way have little among-cell genetic conflict, thereby aligning the fitness interests of lower-level units (cells), increasing the potential for groups to undergo an ‘evolutionary transition in individuality’ (ETI). ETIs are characterized by a hierarchical shift in the level at which heritable variation in fitness is expressed (e.g., from cells to the multicellular group). In this dissertation, I compare clonal and aggregative development in a simple yeast (Saccharomyces cerevisiae) model system. First, I performed a selection experiment using wild-isolated aggregative yeast (termed flocs) with daily selection for rapid sedimentation in liquid medium. Clonally-developing yeast (termed ‘snowflake yeast’) arose and displaced flocs, and invading snowflake yeast showed higher fitness than their floc counterparts. Next, I engineered snowflake and floc yeast from a common unicellular ancestor, so these two strains only differ in their mode of cluster development. In monoculture, floc yeast were superior to snowflake yeast, growing faster and forming larger clusters that settling more rapidly. Yet, in direct competition, snowflake yeast exploit flocs, becoming disproportionately represented within fast-settling groups. Modeling suggests that ‘choosy’ flocs that exclude snowflake yeast would have the highest fitness, but such a strain would not be able to invade from rare. Finally, I performed a long-term evolution experiment to compare the dynamics of multicellular adaptation in floc and snowflake yeast by selecting for increasingly large cluster size, a multicellular trait. Our environment introduces two important life history traits that affect fitness, growth (cell level) and settling (cluster level), and evolved floc and snowflake yeast exhibited fitness gains in these two opposing traits, respectively. Furthermore, snowflake yeast were enriched with mutations that decrease fitness at the single-cell level, but may be beneficial at the cluster-level. Over evolutionary time, this could result in cells becoming interdependent parts of a new multicellular individual. Taken together, these results show that non-clonal cellular binding may be beneficial in environments favoring rapid multicellular group formation, but this paves the way for persistent evolutionary conflict. Conversely, simple clonal multicellular life cycles increase the efficacy of cluster-level adaptation relative to cell-level, which can potentiate an ETI and establish the emergent multicellular cluster as the new level of biological organization. These results highlight the critical role early multicellular life cycles play in driving – or constraining – this major evolutionary transition.

View
Thumbnail Image
Item

Building a systematic analytic pipeline – big data innovation in healthcare

2019-08-27 , Wang, Yuanbo

Electronic Health Records (EHR) containing large amount of patient data present both opportunities and challenges to industry, policy makers, and researchers. Data-driven healthcare utilizing big data in EHR has the potential to revolutionize care delivery while reducing costs. However, for researchers, policymakers, and practitioners to take full advantage of the benefits that electronic records can provide, several challenges must be addressed: 1) Extraction and coding methods for EHR data must be strategically designed to address issues of data quantity, quality, and patient confidentiality; 2) Standardization of clinical terminologies is essential in facilitating interoperability among EHR systems and allows for multi-site comparative effectiveness studies; 3) Effective methods for mining longitudinal health data common in the EHR are critical for revealing disease progression, treatment patterns, and patient similarities, all of which play important role in clinical decision support and treatment improvement; 4) Advanced machine learning techniques are necessary for early detection and prognosis of disease and identifying critical factors that impact patient outcome and; 5) Practical intervention strategies must be developed to address healthcare disparity in rural and remote areas with lack of resources and access. This thesis focuses on these five issues by developing a systematic analytic pipeline for big data in healthcare. Specifically, innovative strategies are developed for information extraction, clinical terminology mapping, time-series mining and clustering, feature selection and discriminatory modeling. Finally, practical implementation methods for telehealth services are designed to reduce healthcare disparity in underserved rural Appalachian counties in Georgia.

View
Thumbnail Image
Item

Molecular analyses of avian sex chromosomes and sex chromosome-like autosomes

2019-07-26 , Sun, Dan

Sex chromosomes have originated multiple times throughout eukaryotes. In species with the XY sex-determination system, dosage compensation (a process that balances expression of sex-linked genes between sexes) is often efficient, and its epigenetic basis has been well studied. However, the extent of epigenetic differentiation between sexes in female-heterogametic systems (ZW), which generally lack complete compensation, is poorly understood. Here, I examined the genome-wide DNA methylation landscapes between males and females in mammalian and avian species. In contrast to the X chromosome in mammals, birds display highly similar methylation patterns between sexes on the Z chromosome. Despite this, in chicken and potentially other species in the Galloanserae lineage, two extremely localized regions with pronounced methylation differentiation were observed, including a previously identified locus (referred to as ‘male hypermethylated [MHM1]’) and a novel locus (referred to as ‘MHM2’). The two MHM loci bear remarkably similar molecular features and potential function in reducing male-to-female expression ratios of their neighboring genes. Therefore, DNA methylation is employed to solve dose problems for genes potentially essential to females, at least twice in the evolutionary history of the Galloanserae lineage. In the white-throated sparrow, a pair of autosomes that are distinguished by chromosomal inversions resemble sex chromosomes. In this species, two plumage morphs that mate almost exclusively with each other display striking behavioral differences: within the same sex, birds of the white-striped morph (ZAL2/ZAL2m) display more territorial aggression and less nestling provision than birds of the tan-striped morph (ZAL2/ZAL2). A detailed genomic comparison between a tan bird and a rare ZAL2m homozygote revealed subtle nucleotide differences between ZAL2 and ZAL2m as well as weak degeneration of the non-recombining ZAL2m chromosome. Nevertheless, a large proportion of genes exhibit allelic differential expression in the brain. Intriguingly, similar to the evolutionary path taken by sex chromosomes across many taxa, dosage compensation evolved as a mechanism to re-balance expression between morphs in this nascent autosomal system. Last, I examined the DNA methylation landscape of the white-throated sparrow. Differences in DNA methylation between chicks and adults are pervasive across the genome, with hypermethylation in adults consistent with the overexpression of DNA methyltransferases. Functional enrichment analysis revealed that the observed changes in methylation are likely involved in development. In contrast to the widespread age effects, morph influences are most prominent on the ZAL2/ZAL2m chromosomes. Notably, allelic differences in DNA methylation and allelic differences in gene expression are significantly linked. Taken together, these findings offer new insights into the epigenetic regulation of gene expression in avian sex chromosomes and sex chromosome-like autosomes.

View