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Characterizing the landscape of aminoacyl-tRNA synthetase protein production in Bacillus subtilis

Author(s)
Parker, Darren John.
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Massachusetts Institute of Technology. Department of Biology.
Advisor
Gene-Wei Li.
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MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
The phenotype of a cell is a consequence of both the identity of the genes in the genome and the magnitude of their expression into proteins. While the biochemical function of many proteins has been uncovered, for most it is unclear how important native protein abundances are for cell fitness. Furthermore, linking changes in abundances with downstream effects on enzymatic output, pathway function, and ultimately cell fitness is unexplored in nearly all cases. Here I use a model enzyme family, the aminoacyl tRNA synthetases (aaRS), to explore how sensitive Bacillus subtilis are to changes in aaRS production from the molecular to phenotypic level. This culmination of protein levels, functional output, and fitness, leads to a complete "fitness landscape" for the aaRS proteins and provides a framework for future study in quantitative biology.
 
In Chapter I, I outline the conceptual questions explored in this thesis, review the current understandings of bacterial translation and aaRS function, and note the various regulatory strategies bacteria utilize to adapt to perturbations. In Chapter II, I find that the aaRS proteins are produced to optimize the growth rate of cells despite the presence of uncharged tRNAs. These native levels are positioned near a 'fitness cliff' as the underlying molecular processes of tRNA charging, translation, and regulation, are sensitive to reductions but not increases in synthetase production. In Chapter III, I complete the characterization of the aaRS fitness landscapes by exploring the source of the fitness defects of aaRS overproduction. In Chapter IV, I present a novel protocol for RNA-seq library preparation to reduce the cost and time associated with generating transcriptomic datasets.
 
In Chapter V, using the aforementioned protocol, I characterize the transcriptomes of over 70 strains within the Escherichia coli single gene knockout collection. With the help of a colleague we find that strong selective pressures to induce genes involved in motility leads to a large amount of transcriptome heterogeneity within the collection. Finally, in Chapter VI, I discuss the results of my work, setting up future directions within the context of gene expression, bacterial physiology, and beyond.
 
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biology, 2020
 
Cataloged from student-submitted PDF of thesis. Vita.
 
Includes bibliographical references.
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/129034
Department
Massachusetts Institute of Technology. Department of Biology
Publisher
Massachusetts Institute of Technology
Keywords
Biology.

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