Abstract

In the Hudson Lab, which is focused on discovering new antibiotics, bacteria samples are taken from the environment and cultured in large quantities. Then they are tested for antibiotic resistance before they are sequenced and their secondary metabolite compounds are extracted. This is both a lengthy and expensive process that becomes more and more difficult as the number of samples one is working increases. This project assessed a different approach to rejuvenate antibiotic development with antiSMASH. antiSMASH is an online tool created by collaborators from many different institutions that uses profile Hidden Markov Models (pHMMs) to detect gene clusters which produce secondary metabolites in bacteria. The antiSMASH tool has its own repository of these “profiles” which are position specific information about an amino acid from a protein encoding gene derived from multiple sequence alignments. Once a genome is entered into antiSMASH, if these profile modules are detected and they are outputted to the user if a certain metabolite/cluster is present. Many gene clusters are known to produce metabolites with antimicrobial properties which the antiSMASH tool could potentially detect. Using this tool, the goal was to identify a potential pipeline of antibiotic discovery that would be a great improvement in time and reduce costs by using the tool as a screen of a possible viable candidate for antibiotics. In this project 30 genomes were used and fed into antiSMASH. They were broken down into positive and negative controls, known producers and unknown producers. We then looked at the tools ability to screen for antibiotics in each of those data types.

Library of Congress Subject Headings

Drug development; Antibiotics--Biotechnology

Publication Date

2023

Document Type

Thesis

Student Type

Graduate

Degree Name

Bioinformatics (MS)

Department, Program, or Center

Thomas H. Gosnell School of Life Sciences (COS)

Advisor

Andre Hudson

Advisor/Committee Member

Gregory A. Babbitt

Advisor/Committee Member

Michael A. Savka

Campus

RIT – Main Campus

Plan Codes

BIOINFO-MS

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