Global and Single Cell Analyses to Connect P53 Dynamics With Gene Expression
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CitationHafner, Antonina. 2017. Global and Single Cell Analyses to Connect P53 Dynamics With Gene Expression. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.
AbstractThe dynamics of transcription factors have been shown to play important roles in a variety of biological systems. However, the mechanisms by which these dynamics are decoded to trigger different transcriptional responses are not well understood. Here we focus on the dynamics of tumor suppressor protein p53, whose dynamics have been shown to control cell fate decisions in response to DNA damage. p53 is known to regulate several hundred target genes but the selection of which genes to activate in response to a specific type of stress and in specific cellular background remain unsolved. In this work, we studied how p53 dynamics control gene expression at a global level (genome wide) and in single cells.
In Chapter 2, we focused on a particular type of p53 dynamics: the pulses in p53 protein level that are induced in response to γ irradiation. To determine how p53 pulses are linked to gene expression genome wide, we performed time-course RNA-Seq and ChIP-Seq measurements. We discovered multiple distinct patterns of gene expression in response to p53 pulses. Surprisingly, p53 binding dynamics were uniform across all genomic loci even for genes that exhibited distinct mRNA dynamics. Using a mathematical model, supported by additional experimental measurements in response to a sustained p53 input, we concluded that p53 binds to and activates transcription of its target genes uniformly, while posttranscriptional mechanisms are responsible for the differences in gene expression dynamics.
In Chapter 3, we developed a single cell system that allows us to follow the dynamics of the p53 protein together with the transcription and protein of one of its target genes, p21. We found that p21 transcription dynamics qualitatively track p53 protein levels in response to γ irradiation, as well for two additional treatments. In addition, we found that in response to p53 pulses, p21 transcription terminated prior to the decrease in p53 protein level. This suggests that transcriptionally active p53 represents a subset of total p53 level. We have constructed a mathematical model that capture this behavior and suggest experiments to test the hypothesis guided by the model.
The combination of population level and single cell approaches allowed us to identify a general mechanism that enables differential expression between genes in response to p53 pulses as well as get a detailed picture of p21 regulation at the single cell level. Chapter 4 discusses the significance of our findings for p53 biology and future directions that need to be taken to gain a systematic understanding of p53 function under different cellular contexts and treatments.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:41141869
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