Mechanistic modeling of complex microbial communities

Dubinkina, Veronika

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https://hdl.handle.net/2142/116181 Copy

Description

Title

Mechanistic modeling of complex microbial communities

Author(s)

Dubinkina, Veronika

Issue Date

2022-07-15

Director of Research (if dissertation) or Advisor (if thesis)

Maslov, Sergei

Doctoral Committee Chair(s)

Maslov, Sergei

Committee Member(s)

• Donovan, Sharon M.
• O'Dwyer, James
• Irudayaraj, Joseph Maria Kumar

Department of Study

Bioengineering

Discipline

Bioengineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• consumer-resource models
• microbial community
• dynamical modeling

Abstract

Microbial communities have many practical applications in human health, agriculture, industry, and civil engineering. Yet the attempts to explain patterns observed in them resulted in the understanding that complexity of these ecosystems should be attributed not only to the microbial species present, but also to the metabolites they consume and secrete. These metabolites shape microbial communities as they underlie competitive exclusion and mediate inter-species interactions. Models that explicitly incorporate nutrients have proven to be useful in gaining insights into principles governing various microbial communities due to their mechanistic nature. This dissertation aims to contribute to these efforts by developing consumer-resource models capturing different patterns of metabolite consumption and studying their effects on microbial interactions, community assembly, stability and resilience. We first studied a model for the community of diauxically shifting microbes, where every community member consumes one resource at a time. Using a game-theoretical as well as dynamic approach we demonstrated that coexistence of such species means that their resource preferences should be complementary and community members are selected based on their top choices. We then developed a model considering another limit: each species requires several essential resources for growth. This assumption leads to the existence of multistable states and complicates community assembly process. We also used fundamental ecological rules captured in such models to leverage existing multi-omics data and infer relevant parameters characterizing consumption and production of metabolites by various species. By developing models that incorporate key factors contributing to microbial growth, such as environmental state, we can expect to capture the right level of detail that permits the use of acquired understanding in practical tasks, e.g. design of viable strategies to control and manipulate complex microbial communities.

Graduation Semester

2022-08

Type of Resource

Thesis

Copyright and License Information

Copyright 2022 Veronika Dubinkina

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