One of the goals of neuroscience is to classify all of the neurons in the brain. Neuronal types can be defined using a combination of morphology, electrophysiology, and gene expression profiles. Gene expression profiles allow differentiation between cells that share similar characteristics. Leveraging the advantage of Berghia stephanieae (Gastropoda; Nudibranchia), which has around 28,000 neurons, I constructed high-throughput single-neuron transcriptomes for its whole brain. I produced a single-cell dissociation protocol and a custom data analysis pipeline for data of this nature. Around 129,000 cells were collected from 18 rhinophore ganglia and 20 circumesophageal ring ganglia (brain), consisting of the cerebropleural, pedal, and buccal ganglia. Messenger RNA libraries were constructed using the 10X Genomics’ Chromium platform. After library preparation, around 1,000 cells were recovered and sequenced. The HTStream package was utilized to trim off unwanted sequences from the raw reads and remove PCR duplicates and other contamination, then the salmon alevin package was employed to construct gene-by-cell matrices containing all the transcripts for each gene in each cell. The Seurat pipeline was used to extract this expression data from the matrices, normalize it, and perform dimensionality reduction. The cells were clustered based on similarities in their gene expression profiles. The cells formed eight clusters on a UMAP graph, each having distinct marker genes. Additionally, one cluster was composed of almost exclusively cells from the rhinophore ganglia, accounting for 30% of all rhinophore ganglion cells in the sample. Cells from the rhinophore ganglia are as heteregenous as cells from the rest of the brain, with cells forming six clusters. Cell populations that express the same neurotransmitter were identified for a wide range of both small-molecule neurotransmitters and neuropeptides. In a separate project, the locomotion of Berghia was recorded over 9 days with 2 lighting regimes: LD first and DD first. The results suggest that locomotion of Berghia is governed by circadian clock and that Berghia is nocturnal. Hunger state likely plays a role in modulating this circadian rhythm.

Indiana University-Purdue University Indianapolis (IUPUI) / The successful treatment and potential eradication of many complex diseases, such as cancer, begins with elucidating the convoluted mapping of molecular profiles to phenotypical manifestation. Our observed molecular profiles (e.g., genomics, transcriptomics, epigenomics) are often high-dimensional and are collected from patient samples falling into heterogeneous disease subtypes. Interpretable learning from such data calls for sparsity-driven models. This dissertation addresses the high dimensionality, sparsity, and heterogeneity issues when analyzing multiple-omics data, where each method is implemented with a concomitant R package. First, we examine challenges in submatrix identification, which aims to find subgroups of samples that behave similarly across a subset of features. We resolve issues such as two-way sparsity, non-orthogonality, and parameter tuning with an adaptive thresholding procedure on the singular vectors computed via orthogonal iteration. We validate the method with simulation analysis and apply it to an Alzheimer’s disease dataset. The second project focuses on modeling relationships between large, matched datasets. Exploring regressional structures between large data sets can provide insights such as the effect of long-range epigenetic influences on gene expression. We present a high-dimensional version of mixture multivariate regression to detect patient clusters, each with different correlation structures of matched-omics datasets. Results are validated via simulation and applied to matched-omics data sets. In the third project, we introduce a novel approach to modeling spatial transcriptomics (ST) data with a spatially penalized multinomial model of the expression counts. This method solves the low-rank structures of zero-inflated ST data with spatial smoothness constraints. We validate the model using manual cell structure annotations of human brain samples. We then applied this technique to additional ST datasets. / 2025-05-22

Human population growth and global industrial development are driving potentially irreversible anthropogenic impacts on the natural world, including altering global climate and ocean conditions and exposing oceanic environments to a wide range of pollutants. While there are numerous studies highlighting the variable effects of climate change and pollution on marine organisms independently, there are very few studies focusing on the potential interactive effects of these stressors. The deep-sea is under increasing threat from these anthropogenic stressors, especially cold-water coral (CWC) communities which contribute to nutrient and carbon cycling, as well as providing biogenic habitats, feeding grounds, and nurseries for many fishes and invertebrates. The primary goals of this dissertation are to assess the vulnerability of CWCs to independent and interacting anthropogenic stressors in their environment; including natural hydrocarbon seepage, hydrocarbon and dispersant concentrations released during an accidental oil spill (i.e. Deepwater Horizon), and the interacting effects of climate change-related factors and hydrocarbon/dispersant exposure. To address these goals, multiple stressor experiments were implemented to assess the effects of current and future conditions [(a) temp: 8C and pH: 7.9; (b) temp: 8C and pH: 7.6; (c) temp: 12C and pH: 7.9; (d) temp: 12C and pH: 7.6] and oil spill exposure (oil, dispersant, oil + dispersant combined) on coral health using the CWC Lophelia pertusa. Phenotypic response was assessed through observations of diagnostic characteristics that were combined into an average health rating at four points during exposure and recovery. Regardless of environmental condition, average health significantly declined during 24-hour exposure to dispersant alone and increased temperature resulted in a delay in recovery (72 hours) from dispersant exposure. The overall gene expression patterns varied by coral colony, but the dispersant exposure elicited the strongest response. Gene ontology (GO) enrichment analysis revealed that L. pertusa likely experienced varying stages of the cellular stress response (CSR) during exposure to oil, dispersant, and a decrease in pH. The most severe responses were associated with the dispersant exposure including GO terms related to apoptosis, the immune system, wound healing, and stress-related responses. However, the oil exposure induced an upregulation of metabolic pathways and energy transfer but a downregulation of cell growth and development, indicating that the coral nubbins could have been reallocating resources and reducing growth to maintain cellular homeostasis. The decrease in seawater pH elicited a similar response to oil through the enrichment of terms associated with a reduction in the cell cycle and development. Interestingly, the increase in temperature did not elicit a CSR that was detectable in the gene expression data. To further investigate the influence of hydrocarbon exposure on CWCs, comparisons of gene expression profiles were conducted using Callogorgia delta colonies that live in close proximity to active hydrocarbon seepage (“seep”) areas with no current active seepage (“non-seep”) at two different sites in the Gulf of Mexico. There were fewer differentially expressed genes in the “seep” versus “non-seep” comparison (n=21) than the site comparison (n=118) but both analyses revealed GO terms indicating slight alterations in natural biological housekeeping processes, as opposed to a CSR. Our results indicate that distinct stages of the CSR are induced depending on the intensity of stress. This bolsters the idea that there is a stress response shared by all corals in response to a variety of stressors. These data provide evidence that CWCs can be more negatively impacted, both on the phenotypic and molecular levels, by exposure to chemical dispersants than to hydrocarbons alone. Gaining an understanding of how these communities respond, not only to independent stressors, but the combination of these stressors, provides vital information about how CWC communities will fair in current and future conditions. / Biology

Channel catfish (Ictalurus punctatus) have a broad distribution from Canada to Mexico, suggesting that different strains may have different thermal tolerances. In aquaculture, daily temperature maximums up to 36-40°C and fluctuations of 3-6°C occur, and may be exacerbated by future climate change. To quantify differences in thermal tolerance amongst geographically-distinct channel catfish strains and corresponding hybrid catfish (I. punctatus x [blue catfish] I. furcatus): acute critical thermal maximum (CTmax), and the effects of chronic thermal regimes on growth, survival and differential gene expression were examined. Southern channel catfish had higher CTmax than northern, and channel catfish had higher CTmax than hybrid catfish. Under chronic thermal stress, hybrid catfish had the greatest survival and most consistent growth. Further, northern channel catfish had the greatest magnitude and largest amount of upregulated gene transcripts in response to high temperatures, indicating greater thermal stress. Therefore, catfish thermal tolerance varies by geographic region and species.

No description available.

The tarnished plant bug, Lygus lineolaris, is an economically important polyphagous pest with a broad host range. With occurrence of insecticide resistance, strategies to limit its ability to reproduce, which would curb population growth, are becoming increasingly more valuable. Strategies toward this goal include the application of insect growth regulators (IGRs) and utilization of resistant cotton lines. This thesis summarizes experiments that elucidate the physiological underpinnings of the mode of action of novaluron, an IGR, and a cotton chromosome substitution (CS) line on the reproductive physiology of L. lineolaris. Investigations reported herein indicate that novaluron inhibits oviposition by inhibiting ovarian development and decreasing the expression of a gene (LlCHS-1) encoding chitin synthase. Transcriptomic analysis of ovarian tissue of L. lineolaris fed on a resistant CS line compared to a control line revealed the downregulation of genes involved in chitin synthesis and upregulation of genes involved in chitin degradation.

Cancer is a dangerous disease caused by mutations in the host's genome that makes the cells proliferateuncontrollably and disrupts bodily functions. The immune system tries to prevent this, but tumours have methods ofdisrupting the immune system's ability to combat the cancer. These immunosuppression events can for examplehappen when the immune system interacts with the tumour to recognise it or try and destroy it. The tumours can bychanging their displayed proteins on the cell surface avoid detection or by excreting proteins, they can neutralisedangerous immune cells. This happens within the tumour microenvironment (TME), the immediate surrounding of atumour where there is a plethora of different cells both aiding and suppressing the tumour. Some of these cells arenot cancer cells but can still aid the tumour due to how the tumour has influenced them. For example, throughangiogenesis, where new blood vessels are formed which feeds the tumour. The interactions in the TME can be used as a target for immunotherapy, a field of treatments which improves theimmune system's own ability at defending against cancer. Immunotherapy can for example help the immune systemby guiding immune cells towards the tumour. It is therefore essential to understand the complex system ofinteractions within the TME to be able to create new methods of immunotherapy and thus treat cancers moreefficiently. Concurrently new methods of mapping what happens in a tissue have been developed in recent years,namely spatial transcriptomics (ST). It allows for the retrieval of transcriptomic information of cells throughsequencing while still retaining spatial information. However, the ST methods which capture the wholetranscriptome of the cells and reveal the cell-to-cell interactions are not of single-cell resolution yet. They capturemultiple cells in each spot, creating a mix of cells in the sequencing. This mix of cells can be detangled, and theproportions of each cell type revealed through the process of deconvolution. Deconvolution works by mapping thesingle cell expression profile of different cell types onto the ST data and figuring out what proportions of expressioneach cell type produces the expression of the mix. This reveals the cellular composition of the microenvironment.But since the interactions in the TME depend on the cells current expression we need to deconvolute according tophenotype and not just cell type. In this project we were able to create a tool which automatically finds phenotypes in the single-cell data and usesthose phenotypes to deconvolute ST data. Phenotypes are found using dimensionality reduction methods todifferentiate cells according to their contribution to the variability in the data. The resulting deconvoluted data wasthen used as the foundation for describing the growth of a cancer as a system of phenotype proportions in the tumourmicroenvironment. From this system a mathematical model was created which predicts the growth and couldprovide insight into how the phenotypes interact. The tool created worked as intended and the model explains thegrowth of a tumour in the TME with not just cancer cells phenotypes but other cell phenotypes as well. However, nonew interaction could be discovered by the final model and no phenotype found could provide us with new insightsto the structure of the TME. But our analysis was able to identify structures we expect to see in a tumour, eventhough they might not be so obvious, so an improved version of our tools might be able to find even more detailsand perhaps new, more subtle interactions.

In mammals, circadian rhythms are driven by a cell-autonomous core-clock mechanism consisting of over a dozen core-clock genes forming transcription-translation feedback loops. The core-clock mechanism also drives the rhythmic expression of downstream genes called clock-controlled genes, which are thought to be important for driving rhythmic biochemical and physiological processes. Mathematical models predict that for a gene to be rhythmically expressed, synthesis, degradation, or a combination of the two must be rhythmic. The purpose of this project was to investigate the contribution of synthesis and degradation of RNA to rhythmic gene expression. To systematically understand the contribution of synthesis, degradation, and other RNA dynamics to rhythmic gene expression, I used metabolic labeling and a novel computational pipeline to analyze transcriptomic data in synchronized NIH3T3 cells. I identified 685 rhythmically expressed RNAs with a period of 24-hour in my dataset, of those 389 were rhythmically synthesized and 24 were rhythmically degraded. Low amplitude degradation rhythms were detected more broadly in the 685 rhythmically expressed RNAs, but these were not statistically significant. Although synthesis was the primary driver of rhythmic 24-hour RNA expression, core-clock gene RNAs were regulated by both synthesis and degradation, presumably to sustain high amplitude of rhythmic expression. I also identified rhythmic RNA expression with a period of 12 and 8 hours; interestingly, degradation primarily drove rhythmic expression of these RNAs. Overall this dissertation revealed RNA dynamics that drive rhythmic gene expression. This will provide insights into how diverse circadian clock mechanisms ultimately drive tissue-specific rhythmic gene expression. / Doctor of Philosophy / Almost all organisms on Earth have an internal timekeeping system, called a circadian clock, that enables them to anticipate and respond to the day/night cycle. The circadian clock regulates diverse body processes such as the sleep/wake cycle, eating and digestion, body temperature, and blood pressure. Disruptions to the circadian clock are detrimental to health and wellbeing. Many organisms, including humans, have a core circadian clock mechanism that drives rhythmic gene expression in thousands of genes that are thought to be ultimately responsible for rhythmic biological and physiological processes. My project investigates how the core clock mechanism drives rhythmic gene expression. I found that rhythmic synthesis of RNA was a primary driver of rhythmic gene expression, but the genes involved in the core circadian clock mechanism itself was regulated by multiple rhythmic processes. Understanding rhythmic gene expression control points is integral for understanding how circadian gene expression can be changed or interrupted.

No description available.

Enteropathogenic bacteria, such as Shigella and Salmonella, are associated with diarrheal diseases, which remain a significant cause of infant mortality worldwide. The secretion of protein effectors by the type III secretion apparatus (T3SA) is used by these pathogens to invade human cells and modulate host cell functions. First, we used RNA-Seq to analyze the differential transcriptome of Shigella flexneri when the T3SA is active or inactive. This allowed us to identify two uncharacterized genes that were temporarily named gem1 and gem3 and whose expression was regulated by MxiE and IpgC as other late substrates of the T3SA. Finally, we pursued the characterization of gem1 and gem3 at the protein level and renamed them icaT and icaR, respectively, when we found their protein products were secreted by the T3SA. Furthermore, we find homologs of icaT and icaR with a conserved MxiE box in several E. coli phylogroups. We also demonstrated that these homologous genes could be reactivated when both MxiE and IpgC were introduced in these strains. This discovery paved a new perspective on the evolution of pathogenesis into the E. coli lineage as both commensal and pathogenic strains harbored these genes. Treating infections caused by Enterobacteriaceae is becoming more challenging due to growing antibiotic resistance and no vaccines are widely available. Accordingly, the World Health Organization (WHO) recognized that we entered the "post-antibiotic era," where new antibiotics or antivirulence drugs are urgently needed, including for Shigella. The T3SA is an attractive target for antivirulence drugs, which may become alternative to classical antibiotics. Through screening 3,000 compounds, we found two novel inhibitors of the T3SA. Our data suggested that one of these candidate inhibitors, a dipyridyl-containing compound, reduces the virulence of Shigella at the transcriptional level. Indeed, the virulence inhibition occurs via the repression of the transcriptional activator VirB by the small chromosomal RNA RyhB, which is upregulated by this compound through an unknown mechanism involving the pyridyl groups. The repression of VirB induced by this molecule reduce the expression of several genes encoding parts of the T3SA. In comparison, the second compound is a quinone that seems to affect the assembly of the T3SA.