Cellular responses to external stimuli include but are not limited to changes in messenger RNA (mRNA) expression, morphological changes, and alteration to physiological processes. Understanding these basic processes in normal and pathological settings has been an overarching goal of modern biology for the past century. The introduction of modern molecular techniques has led scientists to investigate the structure – function relationship between the fundamental cellular building blocks, proteins and nucleic acids, in an attempt to understand disease states and to be able to treat underlying causes of disease rather than generic symptoms. Continual advances in technology have allowed scientists to design increasingly complex experiments and the application of statistical analyses to large datasets has ushered in a new “-omics” era of biology. Technologies such as next-generation sequencing, single-cell experimentation, and high-resolution arrays for probing neuronal physiology were being introduced to the general scientific community as I was beginning my doctoral studies. Here, over the course of 3 different projects I make use of these advancements to understand the molecular mechanisms underlying cellular responses to different environments and I help to develop novel analytical approaches for probing biological neuronal networks.
In the first part, we used an unbiased approach for capturing the expression profile of messenger RNA (mRNA) of bulk cellular samples, RNA sequencing (RNAseq), in order to uncover the molecular responses that take place when a cell recovers from apoptosis, a process termed anastasis. In collaboration with Dr. Denise Montell’s lab, I performed a statistical analysis of gene expression data and found that as cells undergo anastasis their transcriptional profile is actively regulated such that different biological process are being turned on and off as cells recover from apoptosis. This active response was broken down into early and late stages. Early stages represent cells that are transitioning from growth arrested to a proliferation state. In late stages, cells transition from proliferation to a migratory state.
In the second project, a collaboration with the laboratory of Dr. Li Gan, we explore how gender contributes to differences in disease phenotypes using wild type mice and transgenic mouse models of neurodegenerative disease. Making use of high-throughput sequencing methods, including microRNA (miRNA) sequencing, bulk RNAseq and single-cell RNA sequencing, we untangle a complex set of interactions that partially explains phenotypic differences between female and male in terms of disease progression as it relates to the microtubule associated protein Tau. Specifically, analysis of the miRNA expression profiles in microglia were different between female and male and when the effect of miRNA was abolished by knocking out a key miRNA processing enzyme, a clear pathogenic difference was observed between male and female with male brains showing greater extent of pathogenesis.
Finally, in the 4th chapter of this thesis we develop and test a method for detecting spiking relationships between individual neurons that resembles synaptically coupled neurons in-vitro. We utilized inherent properties of action potentials (APs) propagating through an axon to automate the detection of single neuron AP activity which we define as propagation signals. We extend this analysis method by using propagation signal activity as reference points to perform a cross-correlation computation to identify downstream neurons with statistical relationships to the upstream propagation signal. We validated these relationships by performing manipulations meant to alter mechanisms regulating synaptic transmission and demonstrated that these relationships behave in a manner consistent with synaptic mechanisms.