scholarly journals Correction: Dynamic metabolic adaptation can promote species coexistence in competitive microbial communities

2021 ◽  
Vol 17 (2) ◽  
pp. e1008721
Author(s):  
Keyword(s):  
Microbial Communities ◽  
Species Coexistence ◽  
Metabolic Adaptation

scholarly journals Dynamic metabolic adaptation can promote species coexistence in competitive microbial communities

2020 ◽  
Vol 16 (5) ◽  
pp. e1007896 ◽  
Author(s):  
Leonardo Pacciani-Mori ◽  
Andrea Giometto ◽  
Samir Suweis ◽  
Amos Maritan
Keyword(s):  
Microbial Communities ◽  
Species Coexistence ◽  
Metabolic Adaptation

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 Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Li Xie ◽  
Wenying Shou
Keyword(s):  
Microbial Communities ◽  
Artificial Selection ◽  
Species Interactions ◽  
Evolutionary Dynamics ◽  
Species Coexistence ◽  
Evolutionary Trajectory ◽  
Community Function ◽  
Link Type ◽  
Selection Strategies ◽  
Effective Selection

AbstractMicrobial communities often perform important functions that depend on inter-species interactions. To improve community function via artificial selection, one can repeatedly grow many communities to allow mutations to arise, and “reproduce” the highest-functioning communities by partitioning each into multiple offspring communities for the next cycle. Since improvement is often unimpressive in experiments, we study how to design effective selection strategies in silico. Specifically, we simulate community selection to improve a function that requires two species. With a “community function landscape”, we visualize how community function depends on species and genotype compositions. Due to ecological interactions that promote species coexistence, the evolutionary trajectory of communities is restricted to a path on the landscape. This restriction can generate counter-intuitive evolutionary dynamics, prevent the attainment of maximal function, and importantly, hinder selection by trapping communities in locations of low community function heritability. We devise experimentally-implementable manipulations to shift the path to higher heritability, which speeds up community function improvement even when landscapes are high dimensional or unknown. Video walkthroughs: https://go.nature.com/3GWwS6j; https://online.kitp.ucsb.edu/online/ecoevo21/shou2/.

scholarly journals Adaptation of microbial communities in soil contaminated with polychlorinated biphenyls, leading to the transformation of more highly chlorinated congeners in biofilm communities

Biofilms ◽  
2006 ◽  
Vol 3 (1) ◽  
pp. 37-46 ◽  
Author(s):  
A. J. Macedo ◽  
T. R. Neu ◽  
U. Kuhlicke ◽  
W.-R. Abraham
Keyword(s):  
Polychlorinated Biphenyls ◽  
Microbial Communities ◽  
Contaminated Soil ◽  
Polluted Soil ◽  
Soil Samples ◽  
Metabolic Adaptation ◽  
Strong Increase ◽  
Pcb Congeners ◽  
A Site

ABSTRACTA site polluted for many years with polychlorinated biphenyls (PCB) was used to elucidate the metabolic adaptation of microbial communities to these xenobiotics. Soil samples taken along a gradient of PCB-pollution at this site were used to grow biofilm communities on PCB oil. The biofilm communities originating from the non-polluted soil formed rather uniform and thin bacterial layers on PCB oil, while the biofilms originating from contaminated soil samples formed agglomerated structures on the PCB droplets. Biofilm communities were very diverse but those from highly polluted soil were dominated byBurkholderiaspecies, a genus known for degrading several PCBs. All biofilm communities could transform low to medium chlorinated PCB congeners but a strong increase in the rate and degree of PCB transformation in communities from heavily polluted soil was observed. Notably, pentachlorinated congeners were transformed only by biofilms derived from the highly polluted soil but at the same time the content of trichlorinated congeners did not decrease. It is assumed that biofilms from the highly contaminated soil reductively dechlorinated PCB, converting pentachlorinated congeners to trichlorinated congeners in the spherical biofilm aggregates by diffusing to the surface of the aggregates, where aerobic transformation took place.

Species coexistence in simple microbial communities: unravelling the phenotypic landscape of co-occurringMetschnikowiaspecies in floral nectar

2015 ◽  
Vol 18 (6) ◽  
pp. 1850-1862 ◽  
Author(s):  
María I. Pozo ◽  
Carlos M. Herrera ◽  
Marc-André Lachance ◽  
Kevin Verstrepen ◽  
Bart Lievens ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Species Coexistence ◽  
Floral Nectar

scholarly journals Modeling microbial cross-feeding at intermediate scale portrays community dynamics and species coexistence

2020 ◽  
Author(s):  
Chen Liao ◽  
Tong Wang ◽  
Sergei Maslov ◽  
Joao B. Xavier
Keyword(s):  
Experimental Data ◽  
Mathematical Models ◽  
Microbial Communities ◽  
Species Coexistence ◽  
Human Microbiome ◽  
Intermediate Level ◽  
Scale Model ◽  
Individual Species ◽  
Intermediate Scale ◽  
Feeding Interactions

AbstractSocial interaction between microbes can be described at many levels of details: from the biochemistry of cell-cell interactions to the ecological dynamics of populations. Choosing an appropriate level to model microbial communities without losing generality remains a challenge. Here we show that modeling cross-feeding interactions at an intermediate level between genome-scale metabolic models of individual species and consumer-resource models of ecosystems is suitable to experimental data. We applied our modeling framework to three published examples of multi-strain Escherichia coli communities with increasing complexity: uni-, bi-, and multi-directional cross-feeding of either substitutable metabolic byproducts or essential nutrients. The intermediate-scale model accurately fit empirical data and quantified metabolic exchange rates that are hard to measure experimentally, even for a complex community of 14 amino acid auxotrophies. By studying the conditions of species coexistence, the ecological outcomes of cross-feeding interactions, and each community’s robustness to perturbations, we extracted new quantitative insights from these three published experimental datasets. Our analysis provides a foundation to quantify cross-feeding interactions from experimental data, and highlights the importance of metabolic exchanges in the dynamics and stability of microbial communities.Author summaryThe behavior of microbial communities such as the human microbiome is hard to predict by its species composition alone. Our efforts to engineer microbiomes—for example to improve human health—would benefit from mathematical models that accurately describe how microbes exchange metabolites with each other and how their environment shapes these exchanges. But what is an appropriate level of details for those models? We propose an intermediate level to model metabolic exchanges between microbes. We show that these models can accurately describe population dynamics in three laboratory communities and predicts their stability in response to perturbations such as changes in the nutrients available in the medium that they grow on. Our work suggests that a highly detailed metabolic network model is unnecessary for extracting ecological insights from experimental data and improves mathematical models so that one day we may be able to predict the behavior of real-world communities such as the human microbiome.

A peek in the micro-sized world: a review of design principles, engineering tools, and applications of engineered microbial community

2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Environmental Remediation ◽  
Real Life ◽  
Design Principles ◽  
Microbial Interactions ◽  
Potential Applications ◽  
New Gene ◽  
Global Biogeochemical Cycles ◽  
Synthetic Microbial Communities

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.

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