Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Biochemistry

Supervisor

Brandl, Christopher J.

Abstract

Genetic information is passed from DNA to RNA to protein through the processes of transcription and translation. Transfer RNAs (tRNA) are the adaptors that bring amino acids to the growing polypeptide chain during translation and decode the three base codons that define protein sequence. Mistranslation occurs when an amino acid different from what is specified by the genetic code is inserted into a protein. tRNA variants cause mistranslation by decreasing the accuracy of amino acid charging or by altering decoding at the ribosome. My goal was to characterize mistranslating tRNA variants, identify their effects on cells and determine mechanisms used to cope with the resulting proteotoxicity.

First, I focus on anticodon variants of Saccharomyces cerevisiae tRNASer. In isolation these are lethal due to a toxic level of mistranslation, but using a genetic suppression assay, I identify second site mutations in tRNASer that decrease function and allow viable mistranslation levels. I propose that for mistranslating tRNAs to arise, cells first acquire an “ambivalent intermediate” mutation that decreases tRNA function. I characterize additional mutations in tRNASer that allow different mistranslation frequencies at a variety of non-serine codons. To further regulate the toxicity of mistranslation tRNAs and allow high levels of mistranslation, I develop an inducible tRNA expression system, negatively regulated by an RNA polymerase II promoter downstream of the tRNA. My studies demonstrate a mechanism by which mistranslating tRNA variants arise, factors that determine their toxicity and how mistranslation can be engineered for applications in synthetic biology.

Next, I investigate naturally occurring tRNA variants in human populations. Using a custom DNA capture array for the 610 human tRNA genes and a novel bioinformatics pipeline to accurately map variants, I identify ~66 tRNA variants per person including potential mistranslating variants and loss of function variants that could alter tRNA pools. I then perform a genetic screen in yeast demonstrating that mistranslation synergistically exacerbates growth defects caused by loss of a variety of genes, including those involved in protein quality control and actin cytoskeleton. I hypothesize that tRNA variation is a modulator of disease, particularly diseases characterized by loss of proteostasis.

Summary for Lay Audience

Proteins carry out the tasks required for life. The blueprint to make each protein is stored in DNA in three letter words called codons that use a four-letter nucleotide alphabet. Specific words/codons define the 20 amino acids found in protein sequences. The genetic information in DNA is first passed through an mRNA intermediate then in a process called translation is decoded into the amino acid sequence of each protein.

Transfer RNAs (tRNA) are adaptors that link codons to protein sequence, sequentially reading each three-nucleotide codon. Each tRNA is assigned to one of the 20 amino acids by its three-letter anticodon and is physically attached to a specific amino acid. Errors in translation, known as mistranslation, occurs when an amino acid different from what is specified by the DNA blueprint is incorporated into a protein. These errors often change a protein’s function and can lead to disease.

My thesis focuses on tRNA variants that cause mistranslation. These normally kill yeast cells, due to the build-up of mis-made proteins, but additional mutations in a tRNA variant that decrease its function lower mistranslation to a non-lethal level that can be tolerated. I characterize a range of tRNA mutations that allow erroneous incorporation of different amino acids into proteins at various frequencies. I also design a system to regulate the tRNA variant so as to achieve high levels of mistranslation. My studies demonstrate how mistranslation arises in cells and the mechanisms that determine their impact on cellular physiology. The tRNA variants I have engineered have applications in creating novel proteins.

I also characterize naturally occurring tRNA variation in human populations, finding that everyone has more variation than previously predicted, including variants that potentially mistranslate. I find that mistranslation exacerbates the effects of mutations in sequences encoding other proteins. These results suggest that tRNA variation can increase the severity of human diseases, including neurodegenerative diseases and cardiomyopathies, or decrease their age of onset.

Overall, my thesis demonstrates the importance of tRNAs in human health and how to adapt mistranslation to create protein diversity for applications in biotechnology.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Supplemental File S3-1 - SerRS_coevolution_sequences.fasta (339 kB)
Supplemental File S3-1 - SerRS coevolution sequences

Supplemental File S3-2 - SerRS_coevolution_mutualinformationoutput.txt (5009 kB)
Supplemental File S3-2 - SerRS coevolution analysis results

Supplemental File S6-1 - Locus specific tRNA query sequences.txt (125 kB)
Supplemental File S6-1 - Locus specific tRNA query sequences

Supplemental File S6-2 - Human tRNA variants.xlsx (47 kB)
Supplemental File S6-2 - Human tRNA variants

Supplemental File S7-1 - Analysis R script.R (11 kB)
Supplemental File S7-1 - Data Analysis R script

Supplemental File S7-2 - AZC Initial Screen Z scores.xlsx (283 kB)
Supplemental File S7-2 - AZC Initial Screen Z scores

Supplemental File S7-3 - AZC Validation Growth Curve Results.xlsx (46 kB)
Supplemental File S7-3 - AZC Validation Growth Curve Results

Supplemental File S7-4 - Canavanine and Thialysine Growth Curve Results.xlsx (29 kB)
Supplemental File S7-4 - Canavanine and Thialysine Growth Curve Results

Supplemental File S7-5 - Mistranslating tRNA SGA Results.xlsx (18 kB)
Supplemental File S7-5 - Mistranslating tRNA SGA Results

Supplemental File S7-6 - Overexpression AZC Suppression Results.xlsx (17 kB)
Supplemental File S7-6 - Overexpression AZC Suppression Results

Available for download on Friday, October 01, 2021

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