Microbial model communities: To understand complexity, harness the power of simplicity

Bengtsson‐Palme, Johan

doi:10.1016/j.csbj.2020.11.043

Cited by 32 publications

(28 citation statements)

References 101 publications

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“…This means that the signal-to-noise ratio at the higher temperatures is substantially higher than in the lower end of the temperature spectrum. Together, these results highlight the need for standards and transparency in research on microbial model communities (Bengtsson-Palme, 2020).…”

Section: Discussionmentioning

confidence: 80%

“…Taken together, these studies show that seemingly innocuous factors can greatly affect how microbial communities behave. In this study, we link these changes in behavior to specific differences in growth between the members of a model community, showing the power offered by such models to explain phenomena occurring in natural settings (Bengtsson-Palme, 2020).…”

Section: Discussionmentioning

confidence: 96%

“…This allows us to use total biofilm production as a reporter of community behavior in THOR. Thus, in contrast with previous studies on complex natural microbial communities and how their interactions are affected by changes in temperature, we will in this study be able to link, e.g., growth rates of the individual community members to changes in interaction patterns, providing more direct explanations of communityintrinsic properties (Bengtsson-Palme, 2020).…”

Section: Introductionmentioning

confidence: 94%

“…While microbes typically have high reproduction rates, allowing for analysis of microbial communities with high throughput, many natural communities have networks of often undefined interactions of antagonisms and synergisms, making these interactions strenuous to analyze in vitro. Model microbial communities have been suggested as a remedy to this complexity, permitting elucidation of the mechanisms behind community interactions at the genetic and molecular level (Chevrette et al, 2019;Bengtsson-Palme, 2020). These simplified model microbial communities are often more suitable than full-scale complex communities for in vitro dissection, thanks to that many of the member interactions are already defined.…”

Section: Introductionmentioning

confidence: 99%

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Microbial Community Interactions Are Sensitive to Small Changes in Temperature

Burman

Bengtsson‐Palme

2021

Front. Microbiol.

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Microbial communities are essential for human and environmental health, often forming complex interaction networks responsible for driving ecosystem processes affecting their local environment and their hosts. Disturbances of these communities can lead to loss of interactions and thereby important ecosystem functionality. The research on what drives interactions in microbial communities is still in its infancy, and much information has been gained from the study of model communities. One purpose of using these model microbial communities is that they can be cultured under controlled conditions. Yet, it is not well known how fluctuations of abiotic factors such as temperature affect their interaction networks. In this work, we have studied the effect of temperature on interactions between the members of the model community THOR, which consists of three bacterial species: Pseudomonas koreensis, Flavobacterium johnsoniae, and Bacillus cereus. Our results show that the community-intrinsic properties resulting from their interspecies interactions are highly dependent on incubation temperature. We also found that THOR biofilms had remarkably different abundances of their members when grown at 11, 18, and 25°C. The results suggest that the sensitivity of community interactions to changes in temperature is influenced, but not completely dictated, by different growth rates of the individual members at different temperatures. Our findings likely extend to other microbial communities and environmental parameters. Thus, temperature could affect community stability and may influence diverse processes including soil productivity, bioprocessing, and disease suppression. Moreover, to establish reproducibility between laboratories working with microbial model communities, it is crucial to ensure experimental stability, including carefully managed temperature conditions.

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Section: Discussionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Microbial Community Interactions Are Sensitive to Small Changes in Temperature

Burman

Bengtsson‐Palme

2021

Front. Microbiol.

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“…The inherent complexity of natural microbial communities makes it difficult to test most hypothesis directly. Model systems of reduced complexity where each variable can be controlled provide a way to test ecological theories ( Heyse et al, 2019 ; Bengtsson-Palme, 2020 ). Indeed, cell systems biology benefited greatly from the choice of a simple but powerful model, the budding yeast Saccharomyces cerevisiae , a eukaryotic cell with relatively few components (~6,000 genes), easily grown and genetically manipulated in laboratory conditions ( Giaever and Nislow, 2014 ; Marsit et al, 2017 ), and for which tractable strains collections were created and made available to the scientific community ( Giaever and Nislow, 2014 ).…”

Section: Scaling Up Systems Biology Approaches From Cellular Systems To Microbial Ecosystemsmentioning

confidence: 99%

Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions

2021

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Microorganisms are a fundamental part of virtually every ecosystem on earth. Understanding how collectively they interact, assemble, and function as communities has become a prevalent topic both in fundamental and applied research. Owing to multiple advances in technology, answering questions at the microbial system or network level is now within our grasp. To map and characterize microbial interaction networks, numerous computational approaches have been developed; however, experimentally validating microbial interactions is no trivial task. Microbial interactions are context-dependent, and their complex nature can result in an array of outcomes, not only in terms of fitness or growth, but also in other relevant functions and phenotypes. Thus, approaches to experimentally capture microbial interactions involve a combination of culture methods and phenotypic or functional characterization methods. Here, through our perspective of food microbiologists, we highlight the breadth of innovative and promising experimental strategies for their potential to capture the different dimensions of microbial interactions and their high-throughput application to answer the question; are microbial interaction patterns or network architecture similar along different contextual scales? We further discuss the experimental approaches used to build various types of networks and study their architecture in the context of cell biology and how they translate at the level of microbial ecosystem.

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