scholarly journals Estimating taxon‐specific population dynamics in diverse microbial communities

Ecosphere ◽  
2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Benjamin J. Koch ◽  
Theresa A. McHugh ◽  
Michaela Hayer ◽  
Egbert Schwartz ◽  
Steven J. Blazewicz ◽  
...  
PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e112846 ◽  
Author(s):  
Karlette A. Fernandes ◽  
Sandra Kittelmann ◽  
Christopher W. Rogers ◽  
Erica K. Gee ◽  
Charlotte F. Bolwell ◽  
...  

Ecosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
Author(s):  
Christopher B. Satter ◽  
Ben C. Augustine ◽  
Bart J. Harmsen ◽  
Rebecca J. Foster ◽  
Marcella J. Kelly

2015 ◽  
Vol 5 (4) ◽  
Author(s):  
Zak Frentz ◽  
Seppe Kuehn ◽  
Stanislas Leibler

2017 ◽  
Author(s):  
Yuhang Fan ◽  
Yandong Xiao ◽  
Babak Momeni ◽  
Yang-Yu Liu

Horizontal gene transfer and species coexistence are two focal points in the study of microbial communities. The evolutionary advantage of horizontal gene transfer has not been well-understood and is constantly being debated. Here we propose a simple population dynamics model based on the frequency-dependent interactions between different genotypes to evaluate the influence of horizontal gene transfer on microbial communities. We find that both structural stability and robustness of the microbial community are strongly affected by the gene transfer rate and direction. An optimal gene flux can stablize the ecosystem, helping it recover from disturbance and maintain the species coexistence.


eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Thibaud Taillefumier ◽  
Anna Posfai ◽  
Yigal Meir ◽  
Ned S Wingreen

Metagenomics has revealed hundreds of species in almost all microbiota. In a few well-studied cases, microbial communities have been observed to coordinate their metabolic fluxes. In principle, microbes can divide tasks to reap the benefits of specialization, as in human economies. However, the benefits and stability of an economy of microbial specialists are far from obvious. Here, we physically model the population dynamics of microbes that compete for steadily supplied resources. Importantly, we explicitly model the metabolic fluxes yielding cellular biomass production under the constraint of a limited enzyme budget. We find that population dynamics generally leads to the coexistence of different metabolic types. We establish that these microbial consortia act as cartels, whereby population dynamics pins down resource concentrations at values for which no other strategy can invade. Finally, we propose that at steady supply, cartels of competing strategies automatically yield maximum biomass, thereby achieving a collective optimum.


2015 ◽  
Vol 12 (108) ◽  
pp. 20150121 ◽  
Author(s):  
Xiang-Yi Li ◽  
Cleo Pietschke ◽  
Sebastian Fraune ◽  
Philipp M. Altrock ◽  
Thomas C. G. Bosch ◽  
...  

Microbial communities display complex population dynamics, both in frequency and absolute density. Evolutionary game theory provides a natural approach to analyse and model this complexity by studying the detailed interactions among players, including competition and conflict, cooperation and coexistence. Classic evolutionary game theory models typically assume constant population size, which often does not hold for microbial populations. Here, we explicitly take into account population growth with frequency-dependent growth parameters, as observed in our experimental system. We study the in vitro population dynamics of the two commensal bacteria ( Curvibacter sp. (AEP1.3) and Duganella sp. (C1.2)) that synergistically protect the metazoan host Hydra vulgaris (AEP) from fungal infection. The frequency-dependent, nonlinear growth rates observed in our experiments indicate that the interactions among bacteria in co-culture are beyond the simple case of direct competition or, equivalently, pairwise games. This is in agreement with the synergistic effect of anti-fungal activity observed in vivo . Our analysis provides new insight into the minimal degree of complexity needed to appropriately understand and predict coexistence or extinction events in this kind of microbial community dynamics. Our approach extends the understanding of microbial communities and points to novel experiments.


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