| dc.description.abstracteng | Biological causes of many human diseases can be understood more comprehensively by measuring molecular states of the cells. Characterization of cells based on their inherent molecular profiles as well as functional changes in their transcriptional programs, in response to environmental stimuli, could be investigated using high-throughput next generation sequencing (NGS) methodologies. However, these technologies rely on massive amounts of input material containing thousands or even millions of cells, which leads to averaging of gene profiles from all the sequenced cells. It is important to acknowledge however that tissues can contain various types of cells with different characteristics. Furthermore, even cells that are of the same cell type can exhibit very different behavior. It is possible either because of subtypes of cells or expression variation among individual cells. Cellular specialization is especially evident in tissues, which perform varieties of functions using the similar cell types. For instance, the same brain region contains millions of neuronal cells, which differ in their molecular and physiological properties and are involved in different processes. For this reason, it is essential to develop new techniques that can measure individual cells instead of cell collectives.
This thesis explores three cell type-specific techniques for obtaining molecular information and for investigation of biological mechanisms. At first, Chapter 3. describes an implementation of BiTS (Batch isolation of tissue-specific chromatin) coupled with ChIP-seq and MeDIP-seq approaches, which is used to reveal epigenetic changes associated with the formation and maintenance of memory, specifically in neuronal and non-neuronal cells. Such procedures may allow users to obtain cell type-specific genetic and epigenetic information based on a known marker. Chapter 4. introduces the Tagger system, which is the first in-vivo mouse system that enables cell type-specific analysis of multiple nucleic acids from the same tissue. The Tagger system is based on a single transgene insertion into the mouse genome. This system leads to the synthesis of four components (protein molecules) in specific cell types. It enables the researchers to isolate multiple nucleic acid species (such as mRNA, miRNA, 4-TU labeled RNA) as well as isolated nuclei for genetic and epigenetic studies. Finally, the Drop-seq method is implemented in Chapter 5. to characterize individual cells of the spinal cord and hippocampus at the single-cell resolution. Using the Drop-seq method two studies are conducted, where the first study was devoted to characterizing molecular properties of individual cell types from the spinal cord based on the unbiased single-cell RNA sequencing method (Drop-seq). The second study investigated the effect of erythropoietin (EPO) on unidentified precursor cells in the brain hippocampus. These precursor cells can differentiate into neurons and oligodendrocytes and reported to give rise to ~20% increase in the neuronal cell population (Hassouna et al., 2016).
Overall, the current thesis implements cutting-edge, robust, flexible and reliable technologies to understand the molecular mechanisms at the individual cell type as well as single cell level. The knowledge acquired in this thesis could be applied to resolving the precise molecular mechanisms of several diseases and to design targeted or personalized therapeutics in the near future. Notable examples are neuro-degeneration mediated memory deprivation, nervous system diseases affecting specific cell types such as ALS, Alzheimer’s disease, Parkinson’s and others. These diseases could be studied in more depth, with the cell types investigated in this thesis. | de |