The Systemic Imprint of Growth and Its Uses in Ecological (Meta)Genomics

Abstract

Microbial minimal generation times range from a few minutes to several weeks. They are evolutionarily determined by variables such as environment stability, nutrient availability, and community diversity. Selection for fast growth adaptively imprints genomes, resulting in gene amplification, adapted chromosomal organization, and biased codon usage. We found that these growth-related traits in 214 species of bacteria and archaea are highly correlated, suggesting they all result from growth optimization. While modeling their association with maximal growth rates in view of synthetic biology applications, we observed that codon usage biases are better correlates of growth rates than any other trait, including rRNA copy number. Systematic deviations to our model reveal two distinct evolutionary processes. First, genome organization shows more evolutionary inertia than growth rates. This results in over-representation of growth-related traits in fast degrading genomes. Second, selection for these traits depends on optimal growth temperature: for similar generation times purifying selection is stronger in psychrophiles, intermediate in mesophiles, and lower in thermophiles. Using this information, we created a predictor of maximal growth rate adapted to small genome fragments. We applied it to three metagenomic environmental samples to show that a transiently rich environment, as the human gut, selects for fast-growers, that a toxic environment, as the acid mine biofilm, selects for low growth rates, whereas a diverse environment, like the soil, shows all ranges of growth rates. We also demonstrate that microbial colonizers of babies gut grow faster than stabilized human adults gut communities. In conclusion, we show that one can predict maximal growth rates from sequence data alone, and we propose that such information can be used to facilitate the manipulation of generation times. Our predictor allows inferring growth rates in the vast majority of uncultivable prokaryotes and paves the way to the understanding of community dynamics from metagenomic data.

Author Summary

Microbial minimal generation times vary from a few minutes to several weeks. The reasons for this disparity have been thought to lie on different life-history strategies: fast-growing microbes grow extremely fast in rich media, but are less capable of dealing with stress and/or poor nutrient conditions. Prokaryotes have evolved a set of genomic traits to grow fast, including biased codon usage and transient or permanent gene multiplication for dosage effects. Here, we studied the relative role of these traits and show they can be used to predict minimal generation times from the genomic data of the vast majority of microbes that cannot be cultivated. We show that this inference can also be made with incomplete genomes and thus be applied to metagenomic data to test hypotheses about the biomass productivity of biotopes and the evolution of microbiota in the human gut after birth. Our results also allow a better understanding of the co-evolution between growth rates and genomic traits and how they can be manipulated in synthetic biology. Growth rates have been a key variable in microbial physiology studies in the last century, and we show how intimately they are linked with genome organization and prokaryotic ecology.