Molecular Evidence for Metabolically Active Bacteria in the Atmosphere

Abstract

Bacterial metabolisms are responsible for critical chemical transformations in nearly all environments, including oceans, freshwater, and soil. Despite the ubiquity of bacteria in the atmosphere, little is known about the metabolic functioning of atmospheric bacterial communities. To gain a better understanding of the metabolism of bacterial communities in the atmosphere, we used a combined empirical and model-based approach to investigate the structure and composition of potentially active bacterial communities in air sampled at a high elevation research station. We found that the composition of the putatively active bacterial community (assayed via rRNA) differed significantly from the total bacterial community (assayed via rDNA). Rare taxa in the total (rDNA) community were disproportionately active relative to abundant taxa, and members of the order Rhodospirillales had the highest potential for activity. We developed theory to explore the effects of random sampling from the rRNA and rDNA communities on observed differences between the communities. We found that random sampling, particularly in cases where active taxa are rare in the rDNA community, will give rise to observed differences in community composition including the occurrence of "phantom taxa", taxa which are detected in the rRNA community but not the rDNA community. We show that the use of comparative rRNA/rDNA techniques can reveal the structure and composition of the metabolically active portion of bacterial communities. Our observations suggest that metabolically active bacteria exist in the atmosphere and that these communities may be involved in the cycling of organic compounds in the atmosphere.

Keywords: Rhodospirillales; atmosphere; metabolic activity; rarity; sampling theory.

FIGURE 1

Conceptual representation of model parameters for the ecological community that is randomly sampled. (A) Example taxa abundance distributions. The shape of the underlying rDNA taxa abundance distribution can be varied. (B) Bacterial cells with chromosomal DNA and varying number of ribosomes per cell. Activity intensity (m(k)), or the number of rRNAs per rDNA, can be constant or vary across rDNA abundance k. (C) Example taxa abundance distributions with activity profiles (α(k)) shown in red. The activity profile specifies the proportion of active taxa at each abundance k. This can be varied such that low abundance values contain a higher proportion of active taxa than high abundant values (left) or vice versa (right).

FIGURE 2

Order-level taxonomic composition of rRNA and rDNA communities. Errors bars are standard deviations.

FIGURE 3

Relationship between rRNA: rDNA ratio and abundance in the rDNA community. rRNA: rDNA ratio is analogous to the activity intensity parameter (m(k)) in the sampling model. Colored points represent taxa significantly overrepresented in the active community. Points are colored by taxonomic order.

FIGURE 4

Model results. The first column shows the rDNA taxa abundance distribution (negative binomial with shape parameter 1 in blue and the proportion of active taxa in orange [activity profile, α(k)]. Column two shows the change in the intensity profile [i.e., rRNA: rDNA ratio, m(k)] across abundance classes. Rarefaction curves for rDNA (orange), rRNA (green), and phantoms (blue) are displayed in the third column. In row a, the proportion of active taxa increases (10%, 60%, 100%) with increasing abundance; activity intensity also increases (1, 10, 2000) with increasing abundance class. In row b, the proportion of active taxa decreases with increasing abundance (100%, 60%, 10%); activity intensity also decreases with increasing abundance (2000, 10, 1).