The marine unicellular cyanobacterium Prochlorococcus is the smallest-known oxygen-evolving autotroph¹. It numerically dominates the phytoplankton in the tropical and subtropical oceans^2,3, and is responsible for a significant fraction of global photosynthesis. Here we compare the genomes of two Prochlorococcus strains that span the largest evolutionary distance within the Prochlorococcus lineage⁴ and that have different minimum, maximum and optimal light intensities for growth⁵. The high-light-adapted ecotype has the smallest genome (1,657,990 base pairs, 1,716 genes) of any known oxygenic phototroph, whereas the genome of its low-light-adapted counterpart is significantly larger, at 2,410,873 base pairs (2,275 genes). The comparative architectures of these two strains reveal dynamic genomes that are constantly changing in response to myriad selection pressures. Although the two strains have 1,350 genes in common, a significant number are not shared, and these have been differentially retained from the common ancestor, or acquired through duplication or lateral transfer. Some of these genes have obvious roles in determining the relative fitness of the ecotypes in response to key environmental variables, and hence in regulating their distribution and abundance in the oceans.

Prochlorococcus is the numerically dominant phytoplankter in the oligotrophic oceans, accounting for up to half of the photosynthetic biomass and production in some regions. Here, we describe how the abundance of six known ecotypes, which have small subunit ribosomal RNA sequences that differ by less than 3%, changed along local and basin-wide environmental gradients in the Atlantic Ocean. Temperature was significantly correlated with shifts in ecotype abundance, and laboratory experiments confirmed different temperature optima and tolerance ranges for cultured strains. Light, nutrients, and competitor abundances also appeared to play a role in shaping different distributions.

A marine ecosystem model seeded with many phytoplankton types, whose physiological traits were randomly assigned from ranges defined by field and laboratory data, generated an emergent community structure and biogeography consistent with observed global phytoplankton distributions. The modeled organisms included types analogous to the marine cyanobacterium Prochlorococcus . Their emergent global distributions and physiological properties simultaneously correspond to observations. This flexible representation of community structure can be used to explore relations between ecosystems, biogeochemical cycles, and climate change.

Metagenomics is expanding our knowledge of the gene content, functional significance, and genetic variability in natural microbial communities. Still, there exists limited information concerning the regulation and dynamics of genes in the environment. We report here global analysis of expressed genes in a naturally occurring microbial community. We first adapted RNA amplification technologies to produce large amounts of cDNA from small quantities of total microbial community RNA. The fidelity of the RNA amplification procedure was validated with Prochlorococcus cultures and then applied to a microbial assemblage collected in the oligotrophic Pacific Ocean. Microbial community cDNAs were analyzed by pyrosequencing and compared with microbial community genomic DNA sequences determined from the same sample. Pyrosequencing-based estimates of microbial community gene expression compared favorably to independent assessments of individual gene expression using quantitative PCR. Genes associated with key metabolic pathways in open ocean microbial species—including genes involved in photosynthesis, carbon fixation, and nitrogen acquisition—and a number of genes encoding hypothetical proteins were highly represented in the cDNA pool. Genes present in the variable regions of Prochlorococcus genomes were among the most highly expressed, suggesting these encode proteins central to cellular processes in specific genotypes. Although many transcripts detected were highly similar to genes previously detected in ocean metagenomic surveys, a significant fraction (≈50%) were unique. Thus, microbial community transcriptomic analyses revealed not only indigenous gene- and taxon-specific expression patterns but also gene categories undetected in previous DNA-based metagenomic surveys.