No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Complex biological systems are composed of many regulatory components, which can be measured with the advent of genomics technology. Each molecular assay is normally designed to interrogate one aspect of the cell state. However, a comprehensive understanding of the regulatory mechanism requires characterization from multiple levels such as genome, epigenome, and transcriptome. Integration of multi-omics data is urgently needed for understanding the global regulatory mechanism of gene expression. In recent years, single-cell technology offers unprecedented resolution for a deeper characterization of cellular diversity and states. High-quality single-cell suspensions from tissue biopsies are required for single-cell sequencing experiments. Tissue biopsies need to be processed as soon as being collected to avoid gene expression changes and RNA degradation. Although cryopreservation is a feasible solution to preserve freshly isolated samples, its effect on transcriptome profiles still needs to be investigated. Investigation of multi-omics data at the single-cell level can provide new insights into the biological process. In addition to the common method of integrating multi-omics data, it is also capable of simultaneously profiling the transcriptome and epigenome at single-cell resolution, enhancing the power of discovering new gene regulatory interactions. In this dissertation, we integrated bulk RNA-seq with ATAC-seq and several additional assays and revealed the complex mechanisms of ER–E2 interaction with nucleosomes. A comparison analysis was conducted for comparing fresh and frozen multiple myeloma single-cell RNA sequencing data and concluded that cryopreservation is a feasible protocol for preserving cells. We also analyzed the single-cell multiome data for mesenchymal stem cells. With the unified landscape from simultaneously profiling gene expression and chromatin accessibility, we discovered distinct osteogenic differentiation potential of mesenchymal stem cells and different associations with bone disease-related traits. We gained a deeper insight into the underlying gene regulatory mechanisms with this frontier single-cell mutliome sequencing technique.

No description available.

No abstract provided / Thesis / Master of Science (MSc)

Interleukin-1 (IL-1) is a multifunctional cytokine produced primarily by activated monocytes/macrophages and by a variety of other cell types. IL-1 plays an integral role in the immuno-inflammatory response of the body to a variety of stimuli including infection, trauma and other bodily injuries. Once IL-1 is released from the synthesizing cell, it acts as a hormone, initializing a variety of responses in different cells and tissues. These responses are believed to be crucial to survival and are termed acute-phase responses. NF-κB is a family of dimeric transcription factors that control the expression of hundreds of genes which regulate cellular stress responses, cell division, apoptosis, and inflammation. NF-κB dwells in the cytoplasm of the cell until activation in response to a wide range of extracellular stimuli including signaling molecules such as cytokines. NF-κB regulates transcription and gene expression through nucleocytoplasmic transport. Most previous studies on NF-κB activation have been performed using bulk assays to look at populations of cells. Determining cell variance at a single-cell level is crucial in understanding the full mechanisms of drug response. The goal of this study is to analyze the effects of variant concentrations of IL-1β on the activation of NF-κB in individual cells through use of a microfluidic gradient generator. The gradient generator was adopted from Jeon et al and used principles of diffusive mixing and splitting of flows in order create a solute concentration gradient. A soft lithography procedure was used. Briefly, the design was printed on a transparency using a high resolution printer. A master of the design is then created using an SU-8 photoresist and UV light to imprint the design on a silicon wafer. The master is then used to create a Polydimethylsiloxane (PDMS) mold of the design which can be irreversibly attached to a glass slide through oxidation in order to close off the microfluidic channels. FITC-conjugated β-Casein (a protein with similar molecular weight to IL-1β) was used in order to verify the gradient generated by the design. The concentration gradient was analyzed by measuring fluorescent intensity of images taken under a UV light microscope and found to agree with microfluidic simulations run on COMSOL. A procedure for culturing cells in a microfluidic device was then adapted from Jeon that is explained in detail in Chapter 3. Two main trends were revealed; firstly, as IL-1β concentration decreased, the percent of cells activated also decreased. Secondly, as IL-1β concentration decreased, the activation time of the responding cells increased. Cells were observed to act in a single-cell manner; in which multiple cells subjected to the same concentration would not all respond in the same fashion. No major activation threshold was observed but two minor thresholds were; the first at 0.02 ng/mL IL-1β where activation levels drop from 20% to around 5%. The second around 1 ng/mL, in which all greater concentrations show nearly complete activation of all cells exposed. Of the cells that activated, the activation times were recorded and analyzed as well. In general, a decrease in IL-1β concentration caused cells to take longer to activate. Concentrations greater than 5 ng/mL responded on average in 30 minutes with a significant amount of variation. Between 5 ng/mL and 0.1 ng/mL, activation time increased as IL-1β concentration decreased in a linear fashion when concentration was plotted on a base-10 log scale. Below 0.1 ng/mL, the trend disappears and an average activation time of around 95 minutes is observed that no longer depended on concentration. This is interesting because fewer and fewer cells are activating in this concentration range but activation time follows no trend and remains partially stochastic with times ranging from 80 to 105 minutes. The previous results were all observed with a continuous flow and stimulation of the cells. Experiments were also run by only exposing the cells to the IL-1β for 10 minutes and then replacing the flow with a buffer. These studies yielded interesting results; the fraction of activated cells reported the same trends and values as those that were continuously stimulated. The activation times, however, were delayed between 10 and 20 minutes but otherwise followed the same trend as the continuous stimulation. These results suggest that a brief exposure to an external stimulant is all it takes for the cascade of intercellular events to take place and cause NF-κB translocation. / Master of Science

Call number: LD2668 .T4 1984 L43 / Master of Science

Master of Science / Department of Chemistry / Christopher T. Culbertson / A microfluidic device integrated with valves and a peristaltic pump was fabricated using multilayer soft lithography to analyze single cells. Fluid flow was generated and mammalian cells were transported through the channel manifold using the peristaltic pump. A laser beam was focused at the cross-section of the channels so fluorescence of individual labeled intact cells could be detected. Triggered by the fluorescence signals of intact cells, valves could be actuated so fluid flow was stopped and a single cell was trapped at the intersection. The cell was then rapidly lysed through the application of large electric fields and injected into a separation channel. Various conditions such as channel geometry, pumping frequency, control channel size, and pump location were optimized for cell transport. A Labview program was developed to control the actuation of the trapping valves and a control device was fabricated for operation of the peristaltic pump. Cells were labeled with a cytosolic dye, Calcein AM or Oregon Green, and cell transport and lysis were visualized using epi-fluorescent microscope. The cells were transported at rates of [simular to] 1mm/s. This rate was optimized to obtain both high throughput and single cell trapping. An electric field of 850-900 V/cm was applied so cells could be efficiently lysed and cell lysate could be electrophoretically separated. Calcein AM and Oregon Green released from single cells were separated and detected by laser-induced fluorescence. The fluorescence signals were collected by PMT and sampled with a multi-function I/O card. This analyzing method using microchip may be applied to explore other cellular contents from single cells in the future.

The effects of oxygen, malonate, and acetate on the conversion of radioactively-labeled Coenzyme A thioesters of lauric and stearic acids to unsaturated fatty acids by 15,000 x g supernates of Penicilliumlehrysogenum were studied. Following the termination of reactions, the incubation products were saponified, acidified, extracted, and methylated. The resulting methyl esters were purified, separated, identified, and collected. Radioactivities of each fatty acid fraction were determined and converted to percentage of total radioactivity recovered.Desaturase activity was virtually non-existent in the anaerobic incubations indicating that this organism utilized the aerobic pathway of desaturation. The absence of acetate and malonate from incubation mixtures of either laurate or stearate markedly decreased the overall desaturase activity and the amount of linoleate produced. The failure of labeled laurate to be converted to long-chain unsaturated fatty acids in the absence of malonate indicates that chainelongation in this organism proceeds by the malonate pathway. The data presented suggest that laurate may be directly desaturated and then elongated to oleate instead of following the typical aerobic pathway. / Department of Biology

Understanding the behavior of a cell requires that its molecular constituents, such as mRNA or protein levels, be profiled quantitatively. Typically, these measurements are performed in bulk and represent values aggregated from thousands of cells. Insights from such data can be very useful, but the loss of single-cell resolution can prove misleading for heterogeneous tissues and in diseases like cancer. Recently, technological advances have allowed us to profile multiple cellular parameters simultaneously at single-cell resolution, for thousands to millions of cells. While this provides an unprecedented opportunity to learn new biology, analyzing such massive and high-dimensional data requires efficient and accurate computational tools to extract the underlying biological phenomena. Such methods must take into account biological properties such as non-linear dependencies between measured parameters. In this dissertation, I contribute to the development of tools from harmonic analysis and computational geometry to study the shape and geometry of single-cell data collected using mass cytometry and single-cell RNA sequencing (scRNA-seq). In particular, I focus on diffusion maps, which can learn the underlying structure of the data by modeling cells as lying on a low-dimensional phenotype manifold embedded in high dimensions. Diffusion maps allow non-linear transformation of the data into a low-dimensional Euclidean space, in which pairwise distances robustly represent distances in the high-dimensional space. In addition to the underlying geometry, this work also attempts to study the shape of the data using archetype analysis. Archetype analysis characterizes extreme states in the data and complements traditional approaches such as clustering. It facilitates analysis at the boundary of the data enabling potentially novel insights about the system. I use these tools to study how the negative costimulatory molecules Ctla4 and Pdcd1 affect T-cell differentiation. Negative costimulatory molecules play a vital role in attenuating T-cell activation, in order to maintain activity within a desired physiological range and prevent autoimmunity. However, their potential role in T cell differentiation remains unknown. In this work, I analyze mass cytometry data profiling T cells in control and Ctla4- or Pdcd1-deficient mice and analyze differences using the tools above. I find that genetic loss of Ctla4 constrains CD4+ T-cell differentiation states, whereas loss of Pdcd1 subtly constrains CD8+ T-cell differentiation states. I propose that negative costimulatory molecules place limits on maximal protein expression levels to restrain differentiation states. I use similar approaches to study breast cancer cells, which are profiled using scRNA-seq as they undergo the pathological epithelial-to-mesenchymal transition (EMT). For this work, I introduce Markov Affinity based Graph Imputation of Cells (MAGIC), a novel algorithm designed in our lab to denoise and impute sparse single-cell data. The mRNA content of each cell is currently massively undersampled by scRNA-seq, resulting in 'zero' expression values for the majority of genes in a large fraction of cells. MAGIC circumvents this problem by using a diffusion process along the data to share information between similar cells and thereby denoise and impute expression values. In addition to MAGIC, I apply archetype analysis to study various cellular stages during EMT, and I find novel biological processes in the previously unstudied intermediate states. The work presented here introduces a mathematical modeling framework and advanced geometric tools to analyze single-cell data. These ideas can be generally applied to various biological systems. Here, I apply them to answer important biological questions in T cell differentiation and EMT. The obtained knowledge has applications in our basic understanding of the process of EMT, T cell biology and in cancer treatment.

High turnover in the haematopoietic system is sustained by stem and progenitor cells, which divide and mature to produce the range of cell types present in the blood. This complex system has long served as a model of differentiation in adult stem cell systems and its study has important clinical relevance. Maintaining a healthy blood system requires regulation of haematopoietic cell fate decisions, with severe dysregulation of these fate choices observed in diseases such as leukaemia. As transcriptional regulation is known to play a role in this regulation, the gene expression of many haematopoietic progenitors has been measured. However, many of the classic populations are actually extremely heterogeneous in both expression and function, highlighting the need for characterising the haematopoietic progenitor compartment at the level of individual cells. The first aim of this work was to chart the single-cell transcriptional landscape of the haematopoietic stem and progenitor cell (HSPC) compartment. To build a comprehensive map of this landscape, 1,654 HSPCs from mouse bone marrow were profiled using single-cell RNA-sequencing. Analysis of these data generated a useful resource, and reconstructed changes in gene expression, cell cycle and RNA content along differentiation trajectories to three blood lineages. To investigate how single-cell gene expression can be used to learn about regulatory relationships, data measuring the expression of 41 genes (including 31 transcription factors) in 2,167 stem and progenitor cells were used to construct Boolean gene regulatory network models describing the regulation of differentiation from stem cells to two different progenitor populations. The inferred relationships revealed positive regulation of Nfe2 and Cbfa2t3h by Gata2 that was unique to differentiation towards megakaryocyte-erythroid progenitors, which was subsequently experimentally validated. The next study focused on investigating the link between transcriptional and functional heterogeneity within blood progenitor populations. Single-cell profiles of human cord blood progenitors revealed a continuum of lympho-myeloid gene expression. Culture assays performed to assess the functional output of single cells found both unilineage and bilineage output and, by investigating the link between surface marker expression and function, a new sorting strategy was devised that was able to enrich for function within conventional lympho-myeloid progenitor sorting gates. The final project aimed to study changes to the HSPC compartment in a perturbed state. A droplet-based single-cell RNA-sequencing dataset of 44,802 cells was analysed to identify entry points to eight blood lineages and to characterise gene expression changes in this transcriptional landscape. Mapping single-cell data from W41/W41 Kit mutant mice highlighted quantitative shifts in progenitor populations such as a reduction in mast cell progenitors and an increase towards more mature progenitors along the erythroid trajectory. Differential gene expression identified upregulation of stress response and a reduction of apoptosis during erythropoiesis as potential compensatory mechanisms in the Kit mutant progenitors. Together this body of work characterises the HSPC compartment at single-cell level and provides methods for how single-cell data can be used to discover regulatory relationships, link expression heterogeneity to function, and investigate changes in the transcriptional landscape in a perturbed environment.