Characterizing the higher order metabolism of oral streptococci

The metabolism of microbial species is very diverse, displaying a wide range of capabilities. This diversity is often explainable by differences in the metabolic networks that underly microbial metabolism. However, closely related microbial species that have structurally conserved metabolic networks with relatively few differences still display diverse growth profiles under the same growth conditions. This diversity cannot be explained by metabolic capabilities given the similarity in metabolism across these closely related species. In this dissertation, I explore this phenomenon by comparing the growth fitness of a group of closely related oral streptococci using high throughput combinatorial growth experiments. I compare these experimental results to predictions from genome-scale metabolic models that I constructed for each species under study. These models capture the entire metabolism of a species and predict its metabolic capabilities. Disagreements between experimental results and model predictions point to differences in utilization of metabolism that can help explain diversity in growth phenotypes despite similarity in metabolic networks. I develop an algorithm that can analyze these differences and suggest gene suppressions that reconcile model predictions with experimental results, suggesting points of genetic or enzymatic regulation.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Bioengineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Jijakli, Kenan

Contributors dc:contributor

• Jensen, Paul A
• Maslov, Sergei
• Sirk, Shannon
• Vanderpool, Cari

• oral streptococci, genpme-scale metabolic models, gene regulation, prediction

Statement dc:rights

• Copyright 2021 Kenan Jijakli

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/113271

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/113271