Modeling for microbial communities with cross-feeding and predator-prey interactions

Wang, Tong

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Description

Title

Modeling for microbial communities with cross-feeding and predator-prey interactions

Author(s)

Wang, Tong

Issue Date

2021-04-13

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

Maslov, Sergei

Doctoral Committee Chair(s)

Goldenfeld, Nigel

Committee Member(s)

• Golding, Ido
• O'Dwyer, James

Department of Study

Physics

Discipline

Physics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

Microbial communities, mathematical modeling

Abstract

Microbial communities exist nearly everywhere on our planet, from extreme environments such as hydrothermal vents to host environments like the human gut, where microbes interact in diverse ways, such as resource competition and predator-prey interactions. In ecology, mathematical models have been proved effective in simulating diverse interactions and studying the stability of ecosystems under different interacting patterns and strengths. However, such a community-level understanding of microbial communities is still limited. This thesis focuses on two types of interactions: (1) cross-feeding interaction where a metabolite produced by one microbial species is consumed by another species and (2) predator-prey interaction between microbes and their viruses. The network composed of cross-feeding interactions between microbes can be utilized to systematically understand the mechanistic relationship between species and metabolites. Here, we proposed a trophic model comprising rounds of resource consumption and the following byproduct generation to predict metabolite levels according to the relative abundance of microbial species. Later, a machine learning algorithm compatible with the trophic model is used to computationally predict new cross-feeding interactions that are not yet tested by experiments. Besides, on the microscopic level of microbial metabolism, a biophysical model with two cross-feeding microbial strains modulated by the thermodynamics of the overflow pathway is investigated. Apart from the cross-feeding interactions, the predation of viruses on microbes acts as a top-down control of microbial abundances. When viruses infect migrating bacteria, whether the bacterial abundance is limited by nutrient capacity (nutrient-limited regime) or the viral predation (virus-limited regime) is not explored. To quantitatively explore possible regimes and the transition between different regimes, we designed a model based on partial differential equations with microbial ecology and evolution being considered to match and explain the experimental results. When bacteria fail to spatially escape from viral predation, they usually rely on immunity or resistance to survive. At the end of this thesis, the CRISPR-induced arms-race co-evolution between bacteria and viruses in a well-mixed environment is examined.

Graduation Semester

2021-05

Type of Resource

Thesis

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Copyright and License Information

Copyright 2021 Tong Wang

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