scholarly journals Strongly Deterministic Population Dynamics in Closed Microbial Communities

2015 ◽  
Vol 5 (4) ◽  
Author(s):  
Zak Frentz ◽  
Seppe Kuehn ◽  
Stanislas Leibler
Keyword(s):  
Population Dynamics ◽  
Microbial Communities

scholarly journals Faecal Microbiota of Forage-Fed Horses in New Zealand and the Population Dynamics of Microbial Communities following Dietary Change

PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e112846 ◽  
Author(s):  
Karlette A. Fernandes ◽  
Sandra Kittelmann ◽  
Christopher W. Rogers ◽  
Erica K. Gee ◽  
Charlotte F. Bolwell ◽  
...  
Keyword(s):  
Population Dynamics ◽  
New Zealand ◽  
Microbial Communities ◽  
Dietary Change ◽  
Faecal Microbiota

scholarly journals Horizontal Gene Transfer Can Help Maintain the Equilibrium of Microbial Communities

2017 ◽  
Author(s):  
Yuhang Fan ◽  
Yandong Xiao ◽  
Babak Momeni ◽  
Yang-Yu Liu
Keyword(s):  
Population Dynamics ◽  
Gene Transfer ◽  
Horizontal Gene Transfer ◽  
Microbial Communities ◽  
Transfer Rate ◽  
Species Coexistence ◽  
Focal Points ◽  
Dynamics Model ◽  
Population Dynamics Model ◽  
Evolutionary Advantage

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.

scholarly journals Microbial consortia at steady supply

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Thibaud Taillefumier ◽  
Anna Posfai ◽  
Yigal Meir ◽  
Ned S Wingreen
Keyword(s):  
Population Dynamics ◽  
Microbial Communities ◽  
Biomass Production ◽  
Microbial Consortia ◽  
Maximum Biomass ◽  
Metabolic Fluxes ◽  
Almost All

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.

scholarly journals Which games are growing bacterial populations playing?

2015 ◽  
Vol 12 (108) ◽  
pp. 20150121 ◽  
Author(s):  
Xiang-Yi Li ◽  
Cleo Pietschke ◽  
Sebastian Fraune ◽  
Philipp M. Altrock ◽  
Thomas C. G. Bosch ◽  
...  
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Microbial Communities ◽  
Evolutionary Game Theory ◽  
Community Dynamics ◽  
Growth Parameters ◽  
Evolutionary Game ◽  
Frequency Dependent

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.

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 ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Microbial Communities ◽  
Specific Population

scholarly journals Thermodynamic modelling of synthetic communities predicts minimum free energy requirements for sulfate reduction and methanogenesis

2019 ◽  
Author(s):  
Hadrien Delattre ◽  
Jing Chen ◽  
Matthew Wade ◽  
Orkun S Soyer
Keyword(s):  
Population Dynamics ◽  
Microbial Communities ◽  
Thermodynamic Model ◽  
Community Dynamics ◽  
Energy Requirement ◽  
Minimum Energy ◽  
Building Blocks ◽  
Thermodynamic Modelling ◽  
Energy Requirements ◽  
Experimental Population

ABSTRACTMicrobial communities are complex dynamical systems harbouring many species interacting together to implement higher-level functions. Among these higher-level functions, conversion of organic matter into simpler building blocks by microbial communities underpins biogeochemical cycles and animal and plant nutrition, and is exploited in biotechnology. A prerequisite to predicting the dynamics and stability of community-mediated metabolic conversions, is the development and calibration of appropriate mathematical models. Here, we present a generic, extendable thermodynamic model for community dynamics accounting explicitly for metabolic activities of composing microbes, system pH, and chemical exchanges. We calibrate a key parameter of this thermodynamic model, the minimum energy requirement associated with growth-supporting metabolic pathways, using experimental population dynamics data from synthetic communities composed of a sulfate reducer and two methanogens. Our findings show that accounting for thermodynamics is necessary in capturing experimental population dynamics of these synthetic communities that feature relevant species utilising low-energy growth pathways. Furthermore, they provide the first estimates for minimum energy requirements of methanogenesis and elaborates on previous estimates of lactate fermentation by sulfate reducers. The open-source nature of the developed model and demonstration of its use for estimating a key thermodynamic parameter should facilitate further thermodynamic modelling of microbial communities.

scholarly journals Mapping the ecological networks of microbial communities

2017 ◽  
Author(s):  
Yandong Xiao ◽  
Marco Tulio Angulo ◽  
Jonathan Friedman ◽  
Matthew K. Waldor ◽  
Scott T. Weiss ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Microbial Communities ◽  
Simulated Data ◽  
Ecological Networks ◽  
Microbial Interactions ◽  
Volterra Model ◽  
Dynamical Response ◽  
Dynamics Model ◽  
Form Complex ◽  
Population Dynamics Model

Microbes form complex and dynamic ecosystems that play key roles in the health of the animals and plants with which they are associated. Such ecosystems are often represented by a directed, signed and weighted ecological network, where nodes represent microbial taxa and edges represent ecological interactions. Inferring the underlying ecological networks of microbial communities is a necessary step towards understanding their assembly rules and predicting their dynamical response to external stimuli. However, current methods for inferring such networks require assuming a particular population dynamics model, which is typically not known a priori. Moreover, those methods require fitting longitudinal abundance data, which is not readily available, and often does not contain the variation that is necessary for reliable inference. To overcome these limitations, here we develop a new method to map the ecological networks of microbial communities using steady-state data. Our method can qualitatively infer the inter-taxa interaction types or signs (positive, negative or neutral) without assuming any particular population dynamics model. Additionally, when the population dynamics is assumed to follow the classic Generalized Lotka-Volterra model, our method can quantitatively infer the inter-taxa interaction strengths and intrinsic growth rates. We systematically validate our method using simulated data, and then apply it to four experimental datasets of microbial communities. Our method offers a novel framework to infer microbial interactions and reconstruct ecological networks, and represents a key step towards reliable modeling of complex, real-world microbial communities, such as the human gut microbiota.

Sign in / Sign up

Export Citation Format

Share Document