Abstract
The isolation, purification, and clinical deployment of antibiotics is one of the major drivers of decrease in morbidity and mortality from infectious bacteria in the 20th century. The rapid, ubiquitous deployment of antibiotics encouraged swift development and distribution of antibiotic resistance. New, novel techniques, technologies, and ultimately therapeutic antimicrobial compounds will be required to counter the rise of antibiotic resistant microbes. Historically, mimicking naturally occurring compounds has been the most fruitful method for discovering new antibiotics; unsurprisingly, many recent efforts have focused on expanding the cultivation and detection of previously unknown microbes and compounds, respectively. Other techniques explore developing compounds de novo, reverse-engineering potential therapies from a detailed understanding of the biochemistry of pathogens. We describe a novel peptide screening tool in E. coli designed to be used for such an application. This platform, termed PepSeq, is capable of screening millions of peptides simultaneously by using Illumina sequencing technology. Additionally, we have explored several peptide scaffolds that have a conserved secondary structure with a large randomizable domain of several amino acids, which allows the screening for new and novel biochemical interactions with more stable structure than a simple linear peptide. Finally, we have developed a bioinformatics workflow that complements PepSeq that allows analysis of PepSeq data for peptide motifs of interest, vastly streamlining motif identification and verification.
Degree
MS
College and Department
Life Sciences; Microbiology and Molecular Biology
Rights
https://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Erikson, Alexander K., "Antimicrobial Peptide Development: From Massively Parallel Peptide Sequencing to Bioinformatic Motif Identification" (2020). Theses and Dissertations. 8761.
https://scholarsarchive.byu.edu/etd/8761
Date Submitted
2020-12-09
Document Type
Thesis
Handle
http://hdl.lib.byu.edu/1877/etd11505
Keywords
antimicrobial peptide, bioinformatics, peptide motif, antibiotics, PepSeq
Language
english