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Interplay between microbial trait dynamics and population dynamics revealed by the combination of laboratory experiment and computational approaches.

Authors :
Suzuki, Kenta
Yamauchi, Yuji
Yoshida, Takehito
Source :
Journal of Theoretical Biology. Apr2017, Vol. 419, p201-210. 10p.
Publication Year :
2017

Abstract

Filament formation is a common bacterial defense mechanism and possibly has a broad impact on microbial community dynamics. In order to examine the impact of filament formation on population dynamics, we developed an experimental system with a filamentous bacterium Flectobacillus sp. MWH38 and a ciliate predator Tetrahymena pyriformis . In this system, the effective defense of Flectobacillus resulted in the extinction of Tetrahymena by allowing almost no population growth. The result of a kairomone experiment suggested the existence of chemical signals for filament formation. To examine the mechanism further, we developed a quantitative mechanistic model and optimized the model for the experimental result using the simulated annealing method. We also performed a global parameter sensitivity analysis using an approximated Bayesian computation based on the sequential Monte Carlo method to reveal parameters to which the model behavior is sensitive to. Our model reproduced the population dynamics, as well as the cell size dynamics of Flectobacillus . The model behavior is sensitive to the nutrient uptake of Flectobacillus and the propensity of filament formation. It robustly predicts the extinction of Tetrahymena at the condition used in the experiment and predicts the transition from equilibrium to population cycle at higher nutrient conditions. Contrary to the previous study that disproved the presence of chemical signals for filament formation, our result suggested the importance of chemical signals at low predator density, suggesting the variety in bacterial resistance mechanisms that act at different stages of predator-prey interactions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00225193
Volume :
419
Database :
Academic Search Index
Journal :
Journal of Theoretical Biology
Publication Type :
Academic Journal
Accession number :
122156839
Full Text :
https://doi.org/10.1016/j.jtbi.2017.02.014