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Now showing 1 - 10 of 1170
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    Chordate-specific gene regulatory network of neuron development in Ciona.
    (Georgia Institute of Technology, 2023-12-12) Kim, Kwantae
    In this research, I investigated the complex gene regulatory networks underlying neurogenesis, taking advantage of the unique neurons of the Ciona model system. I revealed that Fgf signaling is crucial for the neurogenesis of Bipolar Tail Neurons (BTNs) by controlling the expression of Neurogenin, the fate-determining transcription factor in these neurons. Then I also characterized multiple effector genes functioning in the development of BTNs. Additionally, I determined the vital role of the Pax3/7 transcription factor in the neural plate border to induce the neural tube closure. Finally, I demonstrated how the Pax3/7 also orchestrates an intricate gene regulatory network upstream of multiple transcription factors and functional effectors during the neurogenesis of Descending Decussating Neurons (ddNs). I found that the majority of this network’s regulatory branches are shared with other neurons in Ciona or even other organisms including vertebrates. Moreover, I revealed the role of key putative effector genes during the neurogenesis of ddNs. These findings will provide profound insights into developmental mechanisms in the central nervous system of chordates.
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    Evolution in real time: insights from micro- to macroscopic multicellular organisms
    (Georgia Institute of Technology, 2023-12-06) Pineau, Rozenn
    Multicellularity has evolved independently at least 50 times and fundamentally transformed life on Earth, yet basic questions remain about how this transition initially occurs and shapes ecological dynamics. Understanding this transition and its underlying mechanisms is essential to better understand the evolution of life on Earth. The first part of this work examines the emergence of a common yet understudied multicellular organism morphology, cuboidal packing. Spherical fission yeast (Schizosaccharomyces pombe) mutants were experimentally evolved via daily settling selection favoring larger size. Within 20 days, multicellular clusters evolved cuboidal cellular packing, a topology found across the tree of life. These clusters displayed traits of multicellular individuals: reproduction via cluster fracture, heritability in size, and response to group selection. Our genetic analysis reveals mutations in the ACE2 gene underlying this transition to multicellularity. This is an example of a deep convergent evolution, as this gene has also been implicated in the transition to multicellularity in Saccharomyces cerevisiae, a yeast species that diverged from S. pombe 300 millions of years ago. Next, we explore the ecological implications of the transition to multicellularity and show how the formation of groups itself is an opportunity for niche expansion and divergence. Using long-term experimental evolution of snowflake yeast (S. cerevisiae), we show that the fundamental trade-off between growth and survival facilitated the evolution of two distinct coexisting phenotypes: one Small phenotype specialized in growth, and one Large phenotype specialized in survival. Coexistence is maintained by negative frequency dependent selection, and sequencing reveals that the dominant lineages present after 715 daily transfers have coexisted throughout the duration of the experiment. This work demonstrates how a simple and yet fundamental trade-off between growth and survival can immediately drive adaptive diversification and maintain increased ecological diversity. Overall, this work provides experimental and theoretical insights into eco-evolutionary niche construction and long-term population dynamics following multicellularity's origins. Finally, the last part of this dissertation sheds light on mutation dynamics in complex and ancient multicellular organisms. We explore the evolutionary history of an ancient and still-living clonal forest, the Pando aspen clone. Harnessing the genetic signal generated by the accumulation of somatic mutations in the different tissues of the Pando clone, we detect spatial genetic structure, and estimate Pando's minimum age around 2,000 years. Together, this thesis uses experimental evolution in unicellular microbes and natural experiments in clonal macrobes, contributing fundamental knowledge to our understanding of multicellular evolution, from the initial emergence of multicellular groups to the formation of complex, ancient organisms.
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    Raw data for article: "Moth resonant mechanics are tuned to wingbeat frequency and energetic demands"
    (Georgia Institute of Technology, 2023-12) Wold, Ethan ; Aiello, Brett ; Harris, Manon ; bin Sikandar, Usama ; Lynch, James ; Gravish, Nick ; Sponberg, Simon
    Raw data accompanying the article "Moth resonance mechanics are tuned to wingbeat frequency and energetic demands".
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    Quorum Sensing Cooperation and Conflict in Pseudomonas aeruginosa
    (Georgia Institute of Technology, 2023-11-17) O'connor, Kathleen Audrey
    Bacteria are single celled organisms capable of making great changes to their environment. They accomplish this by working together – using social behaviors to collectively affect the world they live in. Bacterial cells are capable of both cooperation and conflict, flip sides of social behaviors that either benefit or harm the overall population. Social behaviors can only be maintained when the trait benefits both producing cells and closely-related neighbors, and are not overly costly to fitness. The social evolution in microbes field was born from looking at intra-species Pseudomonas aeruginosa social behaviors in liquid media, studying theory established by evolutionary biologists and economists and applying it to real organisms. Social studies in bacteria have now expanded to inter-species and even inter-kingdom social interactions. The field has also begun studying the importance of spatial structure for social traits, and it has been suggested that proximity is essential for social interactions in microbes. In this thesis, I focus on the social behavior quorum sensing (QS) in P. aeruginosa. I first investigate the variation in phenotypic and genotypic QS traits in P. aeruginosa across different environments, and then I study the impact of spatial structure and proximity on QS-regulated cooperation and spite.
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    Evolution, Virulence, and Resistance in Chronic Pseudomonas aeruginosa Infection
    (Georgia Institute of Technology, 2023-11-08) Vanderwoude, Jeongran
    Pseudomonas aeruginosa is a versatile opportunistic pathogen known to cause a spectrum of human disease, including chronic wound and cystic fibrosis (CF) lung infections. Due to its intrinsic resistance to antibiotics, arsenal of virulence factors, and immune-evading adaptations, chronic P. aeruginosa infection is challenging to treat. Population heterogeneity may be a contributing factor to treatment failure, as diverse microbial populations harbor more resistance mechanisms and rare variants that evade detection. The rapid rise in antimicrobial resistance (AMR) rates in clinical P. aeruginosa strains has intensified the challenges associated with treating these infections, necessitating improved understanding of how these dynamic populations evolve and novel approaches beyond conventional antibiotics, such as anti-virulence drugs. This thesis explores the evolution of virulence and AMR in order to illuminate the evolutionary landscape of chronic P. aeruginosa infection. The first study delves into P. aeruginosa virulence evolution and evolutionary adaptations in an understudied system, chronic wounds. In a two-part serial passage and sepsis experiment in murine chronic wounds, virulence evolved divergently in each of three lines of evolution. Morphological diversity of these evolved populations was constrained, highlighting potential differences between chronic wound and CF lung environments. Virulence genes commonly mutated in CF lung infection were also mutated in these evolved populations, with evidence of parallel evolution, revealing shared genetic adaptations across diverse infection settings. The second study explores the relationship between genomic diversification and AMR diversity in P. aeruginosa populations extracted from individuals with CF to understand the molecular and evolutionary basis of AMR diversity. Genomic diversity was neither a reliable predictor of nor a requisite for phenotypic AMR diversity, as populations with widely varying genetic backgrounds and levels of genomic diversity exhibited comparable levels of AMR diversity. Hypermutator strains in these populations often displayed increased sensitivity to antimicrobials, even in cases where strains had been subject to treatment by the same antibiotic within the patient. There was poor evidence for either collateral sensitivity or trade-offs between AMR and fitness in these populations, suggesting AMR diversity may be driven by other evolutionary forces. Taken together, these findings elucidate the evolutionary pathways exploited by P. aeruginosa during chronic infection, highlighting key similarities and differences across two important infection systems.
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    Computational Analysis of Gene Expression in the Teleost Forebrain and the Cellular Basis of a Social Behavior
    (Georgia Institute of Technology, 2023-08-18) Gruenhagen, George Wolfgang
    Teleosts (ray-finned fish) are the largest vertebrate clade, comprising roughly half of all extant vertebrate species, and can perform complex behaviors requiring advanced cognition. A species of teleost fish, Mchenga conophoros (MC), performs a social behavior called bower-building, whereby males repetitively manipulate sand to form a structure called a bower, over which they court females and chase away competing males. Comparative genomic analysis has revealed that this social behavior performed by MC is associated with a region of high genomic divergence on linkage group 11. While the genetic basis of this behavior has been investigated, the brain regions and cell populations involved are unknown. Furthermore, the homology of brain regions in the teleost to the mammalian brain is unclear due to the unique folding of the teleost brain during development. This work aims to 1) identify the cellular basis of bower-building in MC and 2) uncover the relationships between cell-types and anatomical regions in the teleost brain to other vertebrates - amphibians, reptiles, birds and mammals. To address the first aim, we performed single nuclei RNA-sequencing (snRNA-seq) on 19 males actively performing bower-building and 19 control males that were not performing bower-building. This resulted in a total of 33,674 nuclei. I linked genes associated with the evolution of bower-building behavior to a subpopulation of quiescent stem-like cells. We found evidence that behavior-associated neural activity may result in a departure from quiescence and a differential supply of new neurons to a specific region in the teleost brain, the ventral subdivision of the dorsal lateral pallium (Dl-v). To determine the relationship of teleostean brain regions, such as the Dl-v, to other vertebrates, we performed spatial transcriptomics, which profiles gene expression within tissue architecture, unlike snRNA-seq. Together, with these complementary technologies, we created a spatially resolved atlas of gene expression in the MC forebrain and compared expression profiles of thousands of genes across vertebrates. I identified ancestral features of non-neuronal and neuronal populations in MC, including hippocampal and surprisingly neocortical populations. The presence of neocortical-like structures in non-mammals is widely debated. Here I find evidence of neocortical transcriptional signatures in the teleost granule zone of the dorsal lateral pallium (Dl-g). Additionally, I found conserved molecular features of the hippocampus in the teleost Dl-v. In summary, we identified forebrain populations involved in bower-building behavior and ascertained their evolutionary relationships to other vertebrates.
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    Experiments to optimize the ribose-seq protocol
    (Georgia Institute of Technology, 2023-07-31) Bahl, Smriti
    Ribonucleoside monophosphates (rNMPs), the units of RNA, are the most abundant non-standard nucleotides found in genomic DNA. They can be incorporated by DNA polymerases during DNA replication and repair, by hydroxyl radicals during oxidative stress or during incomplete maturation of Okazaki fragments. rNMPs have profound consequences on genome stability, DNA structure, function, and various cellular processes. To better understand these effects, the Storici lab developed the ribose-seq protocol which is a systematic technique for capturing and analyzing rNMPs in genomic DNA. The aim of this study is to optimize the ribose-seq protocol by enhancing the efficiency and accuracy of rNMP detection while minimizing the required amount of starting DNA, thereby enabling easier acquisition also for possible clinical applications. We systematically investigated three key steps of the protocol: (1) adaptor ligation, (2) self-ligation using Arabidopsis thaliana tRNA ligase (AtRNL), and (3) degradation of linear single-stranded DNA (ssDNA) using exonuclease. Through rigorous experimentation and analysis, we observed that modifying the adaptor ligation conditions resulted in approximately a 30% increase in ligation efficiency of the adaptor to the fragmented DNA. The use of AtRNL with an extended incubation period at lower temperature enabled improved circularization of DNA containing the rNMPs, resulting in more abundant ribose-seq library product. Furthermore, novel exonucleases were evaluated as potential replacements for T5 exonuclease in order to effectively eliminate the remaining linear ssDNA following AtRNL self-ligation and protect the circular ssDNA structures containing rNMPs from exonuclease-mediated degradation. To validate the findings of this project, ribose-seq libraries were constructed using Saccharomyces cerevisiae DNA, demonstrating the potential to reduce the starting DNA amount by up to 50%. These findings present a significant advancement in the ribose-seq methodology, enabling researchers to investigate ribonucleotide-mediated genomic processes with enhanced sensitivity and reduced resource requirements.
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    Intensive Locomotor-Related Skill Training and TDCS Neuromodulation to Improve Walking and Balance Function in Persons with Chronic Spinal Cord Injury
    (Georgia Institute of Technology, 2023-07-25) Evans, Nicholas H.
    Spinal cord injury (SCI) results in immediate and persistent impairments in sensory and motor function below the neurological level of injury. Improved walking function is a priority among persons with SCI (PwSCI). Rehabilitation strategies aimed at recovery of walking function are primarily directed toward activation of spinal neural networks despite evidence demonstrating that human bipedal locomotion involves both spinal and supraspinal contributions. Additionally, the cost and long-term accessibility of existing locomotor training approaches limits participation in ongoing training once individuals are discharged from the clinical setting. Consequently, training interventions aimed at enhancing corticospinal drive to motoneurons of the lower limb muscles and that can be feasibly carried out in the home or community setting, either with or without supervision, may be advantageous. These interventions may have value both for promoting long-term recovery of walking function beyond initial rehabilitation, and/or for preserving gains in walking function acquired during rehabilitation. Considering the need to explore alternative interventions that can be feasibly implemented beyond initial rehabilitation and the need to develop interventions that expand the range of neural targets subserving bipedal walking, this thesis explores the following questions: (1) Do persons with motor-incomplete SCI (PwMISCI) demonstrate improvements in lower limb motor function and walking performance following an intensive, high-velocity locomotor-related motor skill training (MST) intervention?; (2) Does enhancing corticospinal drive through the addition of non-invasive brain stimulation (i.e., transcranial direct current stimulation [tDCS]), delivered to the motor cortex and cerebellum, augment the effects of lower limb motor training in this population?; (3) Are there specific characteristics of walking performance that are most influenced by high-velocity locomotor-related motor skill training among PwMISCI? Twenty-six individuals with chronic (≥11months), motor-incomplete SCI were enrolled in a multi-day intervention study with parallel group design, wherein participants were randomized to either a motor skill training plus sham tDCS condition (MST+tDCSsham) or a motor skill training plus active tDCS condition (MST+tDCS). Measures of walking function and gait quality were collected over five consecutive days and between-groups differences in the effects of training were compared. Three consecutive days of MST was associated with significant improvements in walking speed, walking distance, and spatiotemporal gait characteristics (i.e., cadence, stride length), stronger limb trailing limb angle (TLA), and intralimb coordination of the weaker leg. Measures of balance function and perceived fear of falling were also improved; however, concurrent application of tDCS with MST was not associated with greater improvement in outcomes compared to motor training alone. Additionally, among those walking outcomes that were positively influenced by MST intervention, between-day (offline) effects contributed to a greater proportion of total change in outcomes compared to within-day (online) effects. Given the diminished capacity of PwMISCI to produce high step frequencies along with a relatively intact ability to modulate step length, we anticipated that participants in the study would present with diminished step length-frequency coordination (i.e., higher Walk Ratio [step length/step frequency ratio] values) compared to previous reports in non-injured adults. Furthermore, we anticipated that MST emphasizing high-velocity lower limb movements would be associated with improvements in step length-frequency coordination mediated in large part by improvements in the capacity to increase step frequency. Additionally, given that baseline walking speed may influence outcomes, we divided the study sample into slow versus fast walkers to account for differences that may be attributable to differences in walking speed. Among the full study sample, we observed higher Walk Ratio values among PwMISCI than previous reports in other neurological populations; however, values among fast walkers were comparable to non-injured adults. Slow walkers demonstrated greater variability in the Walk Ratio with higher values associated with slower walking speed. Following MST, increases in walking speed among slow walkers coincided with a decrease in the Walk Ratio, mediated primarily through an effect on step frequency suggesting a mechanism by which high velocity MST may improve walking function among PwMISCI with greater mobility deficits. According to the findings, we conclude that a brief intensive, high-velocity MST designed to overcome limitations of existing locomotor training approaches was effective at improving measures of overground walking function and balance in PwMISCI, that concurrent application of tDCS failed to augment the effects of MST, that between-day (offline) change in outcomes contributed to observed improvements to a greater extent than within-day (online) change, and that the high-velocity nature of MST may have contributed to improvements in walking speed among more impaired individuals through a greater effect on step frequency compared to step length.
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    A holistic approach to improving ovarian cancer care
    (Georgia Institute of Technology, 2023-07-17) Ban, Dongjo
    Ovarian cancer (OC), often referred to as the "silent killer" due to its elusive early-stage symptoms and frequent late diagnoses, remains a significant public health challenge. The primary objective of this research is to navigate the intricate landscape of OC at the genomic and metabolomic levels using high-throughput technologies. This exploration strives to uncover potential strategies for early detection and treatment improvement, thereby addressing this persistent health concern. In the initial phase of the study, the genomic complexity of OC is unraveled through an analysis of the tumor mutation burden (TMB) and patterns of copy-number alterations (CNAs). The investigation reveals a higher TMB in localized tumors and cancer-related genes compared to non-cancer genes. We observed that impaired DNA-repair mechanisms play a pivotal role in elevating TMB levels. A notable finding is the differential selective pressure patterns, represented by dN/dS ratio estimates, between early- and late-stage OC. Further, the impact of CNAs on OC patients was analyzed, showing a prevalence of amplification events over deletion ones and a higher number of affected genes in the early-stage group. Although CNAs were not found to be higher in cancer-associated genes, the study identifies a preference for amplification in oncogenes and deletion in tumor suppressor genes upon investigating driver regions. The latter phase of the research emphasizes the role of metabolomics in detecting early-stage OC. Machine learning (ML) approaches were employed to examine high-throughput serum metabolomic profiles from OC patients and non-cancerous individuals from various geographical locations. The resulting classifiers exhibited promising predictive potential, thus emphasizing the utility of metabolomics for early OC detection. Particularly, the emergence of lipid or lipid-like molecules as potential markers underscores their significance in OC detection. Collectively, these findings accentuate the potential of an integrated approach in developing personalized cancer management strategies, taking into account the unique variations observed in patients. This paves the way for clinically identifying high-risk individuals for more frequent monitoring and tailoring appropriate treatment options for optimal patient outcomes. Given the growing volume of data and the continuous advancements in technology, such comprehensive approaches can augment survival rates and ameliorate the quality of life for OC patients.
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    Responses of African Mammals and Ecosystems to Environmental Change Across Space and Time
    (Georgia Institute of Technology, 2023-07-07) Lauer, Daniel Avery
    Africa is home to some of the most biodiverse mammalian assemblages on Earth, but their diversity is threatened by human activities and rapid climate change. If we are to conserve Africa’s mammals, we must understand how they and their surrounding ecosystems respond to changing environmental conditions across space and time. I explored these responses in this dissertation, as I investigated the mechanisms through which species, communities, and ecosystems persist or become imperiled in the face of environmental change. In Chapter 1, I examined how past biodiversity losses in herbivorous megafauna may have impacted the fundamental relationships between megafaunal functional traits and environmental conditions. I adapted traditional methods in the field of ecometrics to evaluate if trait-environment relationships were disrupted over the past 7.5 Ma (million years). I found that while biodiversity losses have occurred since 5 Ma, only those after 2 Ma coincided with such a disruption. Before 2 Ma, biodiversity losses resulted from megafaunal adaptations to expanding grasslands. After 2 Ma, conversely, losses occurred as landscapes became arid and mismatches arose between megafaunal traits and environmental conditions. Consequently, past environmental change-induced biodiversity losses may have varied in their impacts on megafauna. For Chapter 2, I moved forward to modern times and disentangled the theory that heterogeneous environments constrain species’ geographic range sizes. Specifically, I compared the influences of habitat heterogeneity (variation in habitat types across space) versus topographic heterogeneity (variation in physical elevations) on mammalian ranges. Using statistical models, I found that only the former constrains species ranges, while the latter has no influence whatsoever. Such a distinction adds nuance to prior ecological theory, and it suggests that we must conserve range-limited mammals in regions of high habitat heterogeneity. I remained in modern times for Chapter 3 but shifted my focus to the ecosystems in which mammals live. I investigated the under-explored idea that ecosystems exhibit a tradeoff between their ability to withstand disturbance events (resistance) and their capacity to recover from them (stability). Statistical models revealed that such a tradeoff exists across African protected areas, as the characteristics of more resistant ecosystems oppose those of more stable ecosystems. This tradeoff may therefore be a widespread phenomenon, and consequently, a balance between the two must be struck if ecosystems are to endure future disturbances. Finally, I looked to the future in Chapter 4, as I combined insights from the fields of ecometrics and landscape connectivity to inform future mammalian conservation efforts. Using ecometrics, I determined that trait-environment relationships will weaken in >90% of herbivorous megafaunal communities across Africa. Such communities may require changes in their species compositions if they are to maintain their ability to function. I therefore built landscape connectivity models to assess where landscapes may facilitate or impede future movements of species between communities. Based on model outcomes, I provided recommendations for where conservation efforts should protect species either in situ or by facilitating their movements. Overall, my dissertation introduces new perspectives and re-evaluates conventional wisdom to advance our understanding of mammalian responses to changing environments.