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Development of experimental and computational tools for high-throughput microbial "omics"

  • Author(s): Bean, Gordon Jeff
  • et al.
Abstract

As the study of biology has increasingly utilized high- throughput experimental platforms, the need for rigorous, computational analysis of systems biology data has never been greater. Here I present three aims towards solving important computational problems in the field of high- throughput genetic interaction mapping and screening. In Chapter 1, I review the context of my work and describe the technologies I build upon. Chapter 2 is a reproduction of published work in which we present a novel, quantitative differential interaction score, which performs favorably compared to previous differential scores. We also discuss the added utility of differential genetic-similarity in differential network analysis. Chapter 3 is a reproduction of published work in which we present an ultra-high-density, 6144-colony arraying system and analysis toolbox. Using budding yeast as a benchmark, we find that these tools boost genetic screening throughput 4-fold and yield significant cost and time reductions at quality levels equal to or better than current methods. We conclude that the new ultra-high- density screening tools enable researchers to significantly increase the size and scope of their genetic screens. In Chapter 4, I present work being prepared for publication, in which we utilize the new 6144-colony agar format to perform genome-wide time-lapse analysis of the yeast gene deletion collection to quantify dynamic growth phenotypes and identify key biological processes involved in adaptation to metabolic stress through nutrient depletion. We then apply our method to study the dynamic response to UV-radiation and observe that growth profiles recapitulate key biological processes in DNA repair and suggest novel relationships. I conclude in Chapter 5 with a review of my thesis and a discussion of the possibility my work enables in the future. As a whole, this thesis is a combined work of both computational and biological research. In Aim 1, I develop a new statistical score and make biological insights from genetic interaction profiles. In Aim 2, I developed an image analysis toolkit that supports the emerging 6144-colony format. In Aim 3, I use the new 6144 format and image analysis toolkit to develop a novel experimental platform using time-lapse imaging of yeast on agar

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