Indiana University Bloomington Bloomington, Indiana, United States
Abstract: Background/Question/Methods
Understanding the origins and maintenance of complex traits has been a central challenge in ecology and evolution. The stability of a trait depends on its contribution to the fitness of the organism in an environment. Fitness, however, does not fully explain why costly traits are maintained. Even adaptive traits are lost over time due to the energetic demands, especially in constant environments. Dormancy, for example, is an adaptive trait that contributes to populations' long-term survival and persistence in fluctuating, unpredictable, and suboptimal environments by allowing organisms to enter and exit a state of reduced metabolic activity. However, this trait can be retained both under positive evolutionary selection and energetically efficient maintenance of the genetic information stored (e.g., in nucleotides) and structural requirements (e.g., protein expression). Since natural selection alone does not explain the evolution of complex traits, estimating the bioenergetic costs and energy-efficient strategies will improve our understanding of cellular energetics that we can translate into eco-evolutionary dynamics. We addressed this emerging concept, using an ancient well-studied microbial developmental program (i.e., Bacillus subtilis sporulation). The overwhelming amount of information on genomics, transcriptomics, and proteomics allowed us to estimate energetic costs paid by a cell during this program.
Results/Conclusions
We estimate that regulation and maintenance of a spore would cost about 109 ATPs at maximum (i.e., if precursors are synthesized from scratch). This number is one order of magnitude lower than the total energy budget of a cell and higher than many other cellular processes if put in a concept. We further show the distribution of costs during the developmental stages (i.e., reduced in time) and compartments (70% paid by the mother cell). Based on the success and efficiency of this trait among systems and conditions, we demonstrate that costs can be adjusted both at cellular (i.e., not all genes are essential) and population levels (about only 30% sporulate). Besides total numbers, we estimate individual costs of genes and coded proteins relative to the total energy budget of a cell. This is a proxy to the selection coefficient and allows us to estimate the proportion of features under-selection pressure or random drift when compared to the efficient population size. Overall, complex traits need the regulation of many cellular processes over a time course, and there is an enormous amount of individual variation. These estimates incorporate bioenergetics into the eco-evolutionary predictions to expand our understanding of the resilience of complex traits.
