Detection of mRNA decay machinery association with RNA during unstressed and stressed conditions

Open Access
- Author:
- Miller, Jason Eli
- Graduate Program:
- Biochemistry, Microbiology, and Molecular Biology
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- August 26, 2016
- Committee Members:
- Joseph C. Reese, Dissertation Advisor/Co-Advisor
Joseph C. Reese, Committee Chair/Co-Chair
Benjamin Franklin Pugh, Committee Member
Ross Cameron Hardison, Committee Member
Michael Axtell, Outside Member
David Scott Gilmour, Committee Member - Keywords:
- Gene regulation
RNA decay
RIP-seq
Oxidative Stress
Ccr4-NOT - Abstract:
- In order to characterize how living organisms respond to stress, it is crucial that we understand how gene expression at the RNA level is controlled. RNA abundance is a product of synthesis and decay and both are important for understanding how protein levels are eventually established. Additionally, identifying how proteins regulate these processes is important. Whereas a great deal of effort has been spent on understanding how transcriptional regulation effects RNA abundance, much less is known about how the stability of the RNA transcript contributes to mRNA abundance and more specifically how RNA binding proteins (RBPs) regulate individual transcripts during different environmental and developmental conditions. Having said that, a great deal of information about RNA decay has been gleaned from biochemistry assays on model genes. This has greatly influenced how we understand the paths an mRNA can take when going from being a translated mRNA to one that is being degraded. Additionally, genome-wide studies have used techniques to measure global changes in RNA abundance and decay after deleting or mutating genes that code for mRNA decay factors. Having said that, it remained unclear which RNAs the RBPs were recruited to in order to regulate individual mRNA levels across the transcriptome. To address these issues we developed a modified RIP-seq technique. Although previous techniques like CLIP-seq and native RIP-seq have been used to identify RNA-protein interactions on a genome-wide scale, these techniques when adapted to yeast, a model organism, place the cells in conditions that perturb RNA-protein interactions prior to isolation of the RNA. As described in chapter 2 and 3, our RIP-seq method includes the addition of a crosslinker (e.g. formaldehyde) prior to cell collection, which allows for capturing in vivo RNA-protein interactions without the perturbation that native RIP-seq or CLIP-seq studies are prone to. We chose to investigate the RNA-protein interactions of a core subunit of the Ccr4-Not complex,Ccr4, which is also the main cytoplasmic deadenylase in yeast. Additionally, Dhh1 and Puf5, two proteins that associate with the core subunits were also used in the RIP-seq study. Ccr4-Not is a multi-subunit protein complex that has a wide range of functions that regulate mRNA synthesis, post-translational modifications and mRNA decay to name a few. Thus prior attempts to characterize its role in establishing mRNA levels through its ability to associate with mRNA have been hampered by genetic techniques that cannot distinguish between its many functions. By identifying RNAs that the protein of interest is recruited to, we can start to gain mechanistic insight underlying changes in mRNA abundance and decay rates in genomic studies that deleted genes that code for Ccr4-Not subunits. Moreover, the more we learn about synthesis and decay, the more it has become commonly understood that proteins that regulate decay can also regulate synthesis, Ccr4-Not included. Thus, this study will help illustrate that taking multiple -omics approaches will be necessary to understand multifunctional proteins. Chapter 3 shows how RIP was adapted for high-throughput sequencing (RIP-seq). This process involved making sure the sequencing of RIP RNA could be done in a reproducible manner. Furthermore, we developed a workflow to determine the level of enrichment for each RNA Ccr4, Dhh1, and Puf5 were recruited to. Since Puf5 has a motif that it is known to recognize in mRNAs, motif analysis was used to confirm that our RIP-seq method could also identify the motif as a positive control. Moreover, we found that our method was not biased by abundance or length, providing further evidence these proteins were targeting the mRNAs and not associating with them indiscriminately. After creating a method to detect RNA-protein interactions, chapter 4 was devoted to understanding the biological significance of these interactions while the cells were growing in rich media. Ccr4, Dhh1 and Puf5 shared many of the same targets at their 3’ end, most of which were mRNAs. By comparing the correlations between RIP-seq enrichment, decay and synthesis rates it was concluded that Ccr4 has greater influence over mRNA abundance through decay relative to synthesis. Additionally, there are two deadenylase complexes (e.g. Ccr4-Not and Pan2/3) in yeast however little was known about which mRNAs they regulated. The RIP-seq results suggest there is division of labor between Ccr4 and Pan2/3. Interestingly, the decay machinery was also recruited to genes that fluctuate during the yeast metabolic cycle, suggesting these decay factors are important for sensing changes the metabolic state of the cell. In order to test if Ccr4-Not RNA-protein interactions were affected by the oxidative state of the cell, RIP-seq was performed with samples that had been treated with hydrogen peroxide. Chapter 5 describes how stress causes Ccr4 to have a unique response to oxidative stress, in the sense that it loses most of its targets. Most importantly, there is a significant redistribution of the mRNA decay machinery to upregulated mRNAs upon oxidative stress. Furthermore, these are genes that are important for the cell to counter the harmful affects of oxidative stress. Since Ccr4, Dhh1 and Puf5 were recruited to transcriptionally up-regulated mRNAs it suggests they are important for buffering the response oxidative stress and provides new mechanistic insights into broader gene regulation concepts like gene expression buffering.