Density-Dependent Recycling Promotes the Long-Term Survival of Bacterial Populations during Periods of Starvation.
The amount of natural resources in the Earth's environment is in flux, which can trigger catastrophic collapses of ecosystems. How populations survive under nutrient-poor conditions is a central question in ecology. Curiously, some bacteria persist for a long time in nutrient-poor environments. Although this survival may be accomplished through cell death and the recycling of dead cells, the importance of these processes and the mechanisms underlying the survival of the populations have not been quantitated. Here, we use microbial laboratory experiments and mathematical models to demonstrate that death and recycling are essential activities for the maintenance of cell survival. We also show that the behavior of the survivors is governed by population density feedback, wherein growth is limited not only by the available resources but also by the population density. The numerical simulations suggest that population density-dependent recycling could be an advantageous behavior under starvation conditions.



How organisms survive after exhaustion of resources is a central question in ecology. Starving Escherichia coli constitute a model system to understand survival mechanisms during long-term starvation. Although death and the recycling of dead cells might play a key role in the maintenance of long-term survival, their mechanisms and importance have not been quantitated. Here, we verified the significance of social recycling of dead cells for long-term survival. We also show that the survivors restrained their recycling and did not use all available nutrients released from dead cells, which may be advantageous under starvation conditions. These results indicate that not only the utilization of dead cells but also restrained recycling coordinate the effective utilization of limited resources for long-term survival under starvation.
Department of Bioinformatic Engineering, Graduate School of information Science and Technology Osaka University, Osaka, Japan.
Sotaro
S
Takano
Biosciences, University of Exeter, Exeter, United Kingdom.
Bogna J
BJ
Pawlowska
Biosciences, University of Exeter, Exeter, United Kingdom.
Ivana
I
Gudelj
Department of Bioinformatic Engineering, Graduate School of information Science and Technology Osaka University, Osaka, Japan tetsuyayomo@gmail.com tsuru-saburo@ist.osaka-u.ac.jp.|Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan.|Exploratory Research for Advanced Technology (ERATO), Japan Science and Technology Agency (JST), Osaka, Japan.
Tetsuya
T
Yomo
Department of Bioinformatic Engineering, Graduate School of information Science and Technology Osaka University, Osaka, Japan tetsuyayomo@gmail.com tsuru-saburo@ist.osaka-u.ac.jp.
Saburo
S
Tsuru
D004926:Escherichia coli / Q000254:growth & development / Q000378:metabolism / Q000502:physiology*; D050296:Microbial Viability; D008962:Models, Theoretical