Integration of Diverse Inputs Determines Developmental Outcomes

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 DESCRIPTION (provided by applicant): The focus of this project is to elucidate the underlying mechanism for lysis/lysogeny decision making in E. coli upon infection by phage lambda, a paradigmatic system for cell-fate determination and developmental genetic networks. This system offers appealing opportunities to examine how the stochasticity of gene expression from a single gene and spatial aspects involved in the process contribute to the stochasticity-determinism duality nature of the decision-making process which involves a regulatory genetic network. Through our recent study using live-cell microscopy, we hypothesized a different and surprising decision-making scenario from the classical picture. However, the underlying mechanism remains unclear. We propose a systematic investigation of this system in much more detail at the single-cell/single-virus/single-molecule level. The proposal has three specific aims. The first Aim focuses on elucidating how individual phage genome contributes to the lysis/lysogeny decision. It includes exploring how the spatiotemporal information of phage DNA inside the cell correlates with cell fates, how the description of lysis/lysogeny decision in response to the known deterministic factors (e.g. number of infecting phages per cell and cell size) is improved when examined at the single phage-DNA level, and how phages cooperate or compete with each other through mixed infection experiments. The second Aim focuses on determining the sensitivity and responsiveness of the lysis/lysogeny over a full spectrum of distinct growth conditions and phage factors systematically and investigating the gene expression with high-resolution and high-throughput methods. The final Aim is to develop mathematical and computational models of gene expression that account for phage replication, to explain the influence of various genetic and environmental factors on the lysis/lysogeny decision. Overall, our hope is to reach a quantitative understanding of how various deterministic factors and stochasticity contribute to the outcome of a well-known, but incompletely understood developmental process.