A Gulf Stream frontal eddy harbors a distinct microbiome compared to adjacent waters.

Mesoscale oceanographic features, including eddies, have the potential to alter productivity and other biogeochemical rates in the ocean. Here, we examine the microbiome of a cyclonic, Gulf Stream frontal eddy, with a distinct origin and environmental parameters compared to surrounding waters, in order to better understand the processes dominating microbial community assembly in the dynamic coastal ocean. Our microbiome-based approach identified the eddy as distinct from the surround Gulf Stream waters. The eddy-associated microbial community occupied a larger area than identified by temperature and salinity alone, increasing the predicted extent of eddy-associated biogeochemical processes. While the eddy formed on the continental shelf, after two weeks both environmental parameters and microbiome composition of the eddy were most similar to the Gulf Stream, suggesting the effect of environmental filtering on community assembly or physical mixing with adjacent Gulf Stream waters. In spite of the potential for eddy-driven upwelling to introduce nutrients and stimulate primary production, eddy surface waters exhibit lower chlorophyll a along with a distinct and less even microbial community, compared to the Gulf Stream. At the population level, the eddy microbiome exhibited differences among the cyanobacteria (e.g. lower Trichodesmium and higher Prochlorococcus) and in the heterotrophic alpha Proteobacteria (e.g. lower relative abundances of specific SAR11 phylotypes) versus the Gulf Stream. However, better delineation of the relative roles of processes driving eddy community assembly will likely require following the eddy and surrounding waters since inception. Additionally, sampling throughout the water column could better clarify the contribution of these mesoscale features to primary production and carbon export in the oceans.

Rapid changes in coastal ocean microbiomes uncoupled with shifts in environmental variables.

Disturbances, here defined as events that directly alter microbial community composition, are commonly studied in host-associated and engineered systems. In spite of global change both altering environmental averages and increasing extreme events, there has been relatively little research into the causes, persistence and population-level impacts of disturbance in the dynamic coastal ocean. Here, we utilize 3 years of observations from a coastal time series to identify disturbances based on the largest week-over-week changes in the microbiome (i.e. identifying disturbance as events that alter the community composition). In general, these microbiome disturbances were not clearly linked to specific environmental factors and responsive taxa largely differed, aside from SAR11, which generally declined. However, several disturbance metagenomes identified increased phage-associated genes, suggesting that unexplained community shifts might be caused by increased mortality. Furthermore, a category 1 hurricane, the only event that would likely be classified a priori as an environmental disturbance, was not an outlier in microbiome composition, but did enhance a bloom in seasonally abundant phytoplankton. Thus, as extreme environmental changes intensify, assumptions of what constitutes a disturbance should be re-examined in the context of ecological history and microbiome responses.

Microbial communities across nearshore to offshore coastal transects are primarily shaped by distance and temperature.

Recent studies have focused on linking marine microbial communities with environmental factors, yet, relatively little is known about the drivers of microbial community patterns across the complex gradients from the nearshore to open ocean. Here, we examine microbial dynamics in 15 five-station transects beginning at the estuarine Piver's Island Coastal Observatory (PICO) time-series site and continuing 87 km across the continental shelf to the oligotrophic waters of the Sargasso Sea. 16S rRNA gene libraries reveal strong clustering by sampling site with distinct nearshore, continental shelf and offshore oceanic communities. Water temperature and distance from shore (which serves as a proxy for gradients in factors such as productivity, terrestrial input and nutrients) both most influence community composition. However, at the phylotype level, modelling shows the distribution of some taxa is linked to temperature, others to distance from shore and some by both factors, highlighting that taxa with distinct environmental preferences underlie apparent clustering by station. Thus, continental margins contain microbial communities that are distinct from those of either the nearshore or the offshore environments and contain mixtures of phylotypes with nearshore or offshore preferences rather than those unique to the shelf environment.

Programmed evolution for optimization of orthogonal metabolic output in bacteria.

Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields - evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation.