OOS 5-2 - Energy limitation in bacteria: A trait-based approach

Monday, August 7, 2017: 1:50 PM
Portland Blrm 258, Oregon Convention Center
Jay T. Lennon, Department of Biology, Indiana University, Bloomington, IN and Stuart E. Jones, Biological Sciences, University of Notre Dame, Notre Dame, IN

In nature, most organisms experience conditions that are suboptimal for growth and reproduction. This is particularly true for bacteria, which are the most abundant and diverse forms of life on Earth. Although some bacteria have the capacity to double in minutes, energy limitation commonly constrains the activity and turnover of microbial communities in natural, engineered, and host-associated ecosystems. We tested the effects of extreme energy limitation on replicate populations of bacteria from diverse phylogenetic backgrounds in starvation trials that lasted 1,000 days. We modeled the persistence of each population in addition to measuring single-cell metabolic activity and a suite of functional traits, including growth rate, lag time, biofilm production, and motility.


In response to energy limitation, the initial death rate varied over four orders of magnitude. Nevertheless, all but one population persisted over the duration of the experiment suggesting that bacteria are well adapted to feast and famine conditions found in nature. Despite logarithmic declines in population size, we did not observe an accumulation of dead bacteria, suggesting that scavenging may be a microbial trait that contributes to persistence in low-energy environments. Interestingly, for 90% of the populations that we investigated, survivorship deviated from first-order expectations suggesting that bacterial death rates were not constant, but rather declined over time. We developed a model to explore this behavior, which allowed for microorganisms to transition from an active to dormant state, which was accompanied by lower maintenance energy costs and reduced rates of mortality. Single-cell metabolic assays confirm that dormancy is a bet-hedging strategy that contributes to long-term persistence in energy-limited conditions. We will discuss the findings in a trait-based framework that considers trade-offs and bacterial evolutionary history.