The effect of a chaotic environmental flow on the evolution of microbial social behaviors

• Grant number: 20/14169-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: April 01, 2021
• End date: July 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Physics - General Physics
• Principal Investigator: Ricardo Martinez Garcia
• Grantee: João Pedro Valeriano Miranda
• Host Institution: Instituto de Física Teórica (IFT). Universidade Estadual Paulista (UNESP). Campus de São Paulo. São Paulo , SP, Brazil
• Associated research grant: 19/05523-8 - Toward a mechanistic theory for biological patterns and their ecosystem management possibilities, AP.BTA.JP
• Associated scholarship(s): 22/04976-1 - Towards a framework for precise inference of microbial community stability: from models to experiment design, BE.EP.MS

Abstract

Microbial populations often secrete substances to the external medium to allow them to behave as a collective and perform some tasks more effectively. These behaviors are costly and hence prone to exploitation by mutants that do not participate in the collective action yet get their benefits. Understanding how natural populations avoid invasions by such mutants is a central question in evolutionary biology. Microbial habitats may feature a broad range of flows that may disperse cells and/or their secretions in different forms, from smooth transport by laminar flows to the chaotic mixing characteristic of turbulence. Although each form of mixing may influence the evolution of sociality in complex and unknown ways, the feedbacks between microbial ecology, social evolution, and flow physical properties remain unexplored. The goal of this project is to use mathematical modeling to investigate those connections. Specifically, how chaotic mixing influences the ecology and evolution of a cooperative behavior in a simple microbial ecosystem inhabiting a turbulent environment. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

VALERIANO, JOAO PEDRO; CINTRA, PEDRO HENRIQUE; LIBOTTE, GUSTAVO; REIS, IGOR; FONTINELE, FELIPE; SILVA, RENATO; MALTA, SANDRA. Sequential time-window learning with approximate Bayesian computation: an application to epidemic forecasting. NONLINEAR DYNAMICS, v. 111, n. 1, p. 10-pg., 2022-09-25. (21/02027-0, 20/14169-0)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

MIRANDA, João Pedro Valeriano. The evolution of microbial cooperation under chaotic environmental flows. 2023. Master's Dissertation - Universidade Estadual Paulista (Unesp). Instituto de Física Teórica (IFT). São Paulo São Paulo.