Dissertation/Thesis Abstract

Using Computational Approaches to Investigate Streptococcal Species from the Food Industry
by Sun, Yukun, Ph.D., Illinois Institute of Technology, 2020, 172; 28027206
Abstract (Summary)

Streptococcal species are a major cause of concern in the Food industry. In the swine industry, Streptococcus suis is not only a major pathogen that can cause several systemic issues in pigs, but also an emergent zoonotic agent that can infect workers and consumers alike. However, not all S. suis strains are pathogenic and strain 90-1330, an avirulent Canadian serotype 2/sequence type 28 isolate, was previously found to produce a lantibiotic bacteriocin that kills several pathogenic Streptococcus species. This finding led to the suggestion that S. suis 90-1330 could be used as a probiotic in the swine industry for prophylactic purposes.

As part of my thesis (Chapter 2), I sequenced the complete genome of S. suis 90-1330 and used comparative genomic approaches to predict if this strain is indeed avirulent and suitable for probiotic purposes. Results from our comparative analyses suggested that this strain may not be as harmless as initially thought, as its genome was found to code for several virulence factors including a hemolysin that lyses blood cells. The bacteriocin it produces and the products that confer resistance to its effect were found encoded in a functional, mobile integrative and conjugative element (ICE), suggesting that use of this strain as probiotic without further engineering would facilitate the spread of resistance to this bacteriocin. Furthermore, the bacteriocin was found widely distributed across several streptococcal species, indicating that the use of this strain as a probiotic might provide fewer health benefits than originally thought.

In Chapter 3, I used the approaches and tools we developed as part of our work on S. suis strains to investigate the genetic diversity pertaining to Streptococcus parasuis and Streptococcus ruminantium. These two streptococcal species were recently removed taxonomically from S. suis based on phenotype assays and on limited genotype data, and the extent of their intra- and interspecific diversity as well as their potential for virulence were unknown. The two novel species were found to be genetically distinct from S. suis in our comparative analyses, as expected from previous studies, but the genetic differences responsible for their phenotypic differences could not be ascertained in large part due to the presence of many unique proteins of unknown functions, highlighting a need for improved methods to infer functions computationally.

In Chapter 4, I describe the computer pipeline that we built to facilitate and automate genetic diversity analyses between bacterial species, and which was used extensively for Chapters 2 and 3. Notably, to palliate for data missing from sequencing archives, we implemented a simple solution that generates in silico sequencing datasets from complete and/or draft genomes. I tested and validated our pipeline extensively and describe in this chapter its pros and cons and current limitations.

Indexing (document details)
Advisor: Pombert, Jean-Fran├žois
Commitee: Ayitou, Jean-Luc, Juarez, Oscar, Irving, Thomas C.
School: Illinois Institute of Technology
Department: Biology
School Location: United States -- Illinois
Source: DAI-B 82/3(E), Dissertation Abstracts International
Subjects: Bioinformatics
Keywords: Bacteriocin, Food industry, Genetic diversity, Prophylactic, Streptococcus suis, Synthetic short read generator
Publication Number: 28027206
ISBN: 9798664780543
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