4.4 Article

Deciphering Interactions Within a 4-Strain Riverine Bacterial Community

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CURRENT MICROBIOLOGY
卷 80, 期 8, 页码 -

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SPRINGER
DOI: 10.1007/s00284-023-03342-9

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The dynamics of a community of four planktonic bacterial strains isolated from river water were studied in R2 broth for 72 hours. Two interaction networks were constructed to summarize the impact of the strains on each other's growth rate and carrying capacity. The results showed that growth rate and carrying capacity were positively correlated, and that a minor strain could greatly influence the dynamics of a dominant one.
The dynamics of a community of four planktonic bacterial strains isolated from river water was followed in R2 broth for 72 h in batch experiments. These strains were identified as Janthinobacterium sp., Brevundimonas sp., Flavobacterium sp. and Variovorax sp. 16S rRNA gene sequencing and flow cytometry analyses were combined to monitor the change in abundance of each individual strain in bi-cultures and quadri-culture. Two interaction networks were constructed that summarize the impact of the strains on each other's growth rate in exponential phase and carrying capacity in stationary phase. The networks agree on the absence of positive interactions but also show differences, implying that ecological interactions can be specific to particular growth phases. Janthinobacterium sp. was the fastest growing strain and dominated the co-cultures. However, its growth rate was negatively affected by the presence of other strains 10 to 100 times less abundant than Janthinobacterium sp. In general, we saw a positive correlation between growth rate and carrying capacity in this system. In addition, growth rate in monoculture was predictive of carrying capacity in co-culture. Taken together, our results highlight the necessity to take growth phases into account when measuring interactions within a microbial community. In addition, evidence that a minor strain can greatly influence the dynamics of a dominant one underlines the necessity to choose population models that do not assume a linear dependency of interaction strength to abundance of other species for accurate parameterization from such empirical data.

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