Environmental cues structuring bacterial dormancy shift from hypersaline to freshwater lakes
Dormancy is often offered as a plausible explanation for how bacteria weather suboptimal temporal fluctuations in resource availability or adverse environmental conditions. Bacteria may exit this reversible, low-metabolic state and resuscitate, becoming metabolically active in response to favorable environmental cues. In extreme environments, the prevalence of dormancy is only expected to rise as stressful conditions intensify, however, the overriding effects of a constant stress in extreme environments may overshadow other environmental cues from influencing activity. We evaluated shifts in microbial community composition and dormancy and related these variables to water chemistry over one year in three hypersaline and three freshwater lakes in UT, USA. The lakes represented a salinity gradient ranging from 303.22 PSU in the North Arm of the Great Salt Lake to 0.52 PSU in Deer Creek Reservoir. We analyzed 16S rDNA-based communities (i.e., all bacteria present in the community) and 16S rRNA-based communities (i.e., only active bacteria) with target metagenomics and calculated dormancy based on rRNA to rDNA ratios of the relative recovery of individual operational taxonomic units. We measured changes in lake chemistry (i.e., temperature, pH, dissolved oxygen, total nitrogen, total phosphorus, dissolved organic carbon) and linked them to dormancy with multiple regression models in R.
We found that in hypersaline lakes, the best model to explain the proportion of the community that was dormant contained only salinity, regardless of season (i.e., November, February, May, and August) or changes in other lake chemistry variables (P <0.001). Dormancy demonstrated a negative linear relationship with salinity (R2 = .97 P <0.01), suggesting that increases in salinity decreased dormancy. We also found that without the presence of a single extreme environmental characteristic, changes in bacterial dormancy were associated with fluctuations of multiple lake chemistry variables. In the three freshwater lakes, the model of best fit explaining dormancy included seasonal changes in concentration of total phosphorus, nitrogen, and dissolved organic carbon (P <0.001). Furthermore, some bacterial taxa were more prone than others to enter dormancy. For example, Betaproteobacteria were highly abundant in freshwater lakes and were always active, while Verrucomicrobia were only active in times of low nutrient availability. In contrast, Actinobacteria and Bacteroidetes in hypersaline lakes dominated both active and dormant communities throughout the year. Our findings indicate that extreme stresses may dramatically regulate bacterial activity and mask the importance of other environmental drivers, while under more benign conditions dormancy is structured by multiple seasonal fluctuations in resource availability.