Marine microbial communities experience daily fluctuations in light and temperature that can have important ramifications for carbon and nutrient cycling. Elucidation of such short time scale community-wide dynamics is hindered by system complexity. Hypersaline aquatic environments have lower species richness than marine environments and can be well-defined spatially, hence they provide a model system for diel cycle analysis. We conducted a 3-day time series experiment in a well-defined pool in hypersaline Lake Tyrrell, Australia. Microbial communities were tracked by combining cultivation-independent lipidomic, metagenomic and microscopy methods. The ratio of total bacterial to archaeal core lipids in the planktonic community increased by up to 58% during daylight hours and decreased by up to 32% overnight. However, total organism abundances remained relatively consistent over 3 days. Metagenomic analysis of the planktonic community composition, resolved at the genome level, showed dominance by Haloquadratum species and six uncultured members of the Halobacteriaceae. The post 0.8 μm filtrate contained six different nanohaloarchaeal types, three of which have not been identified previously, and cryo-transmission electron microscopy imaging confirmed the presence of small cells. Notably, these nano-sized archaea showed a strong diel cycle, with a pronounced increase in relative abundance over the night periods. We detected no eukaryotic algae or other photosynthetic primary producers, suggesting that carbon resources may derive from patchily distributed microbial mats at the sediment-water interface or from surrounding land. Results show the operation of a strong community-level diel cycle, probably driven by interconnected temperature, light abundance, dissolved oxygen concentration and nutrient flux effects.

Metagenomics projects based on shotgun sequencing of populations of micro-organisms yield insight into protein families. We used sequence similarity clustering to explore proteins with a comprehensive dataset consisting of sequences from available databases together with 6.12 million proteins predicted from an assembly of 7.7 million Global Ocean Sampling (GOS) sequences. The GOS dataset covers nearly all known prokaryotic protein families. A total of 3,995 medium- and large-sized clusters consisting of only GOS sequences are identified, out of which 1,700 have no detectable homology to known families. The GOS-only clusters contain a higher than expected proportion of sequences of viral origin, thus reflecting a poor sampling of viral diversity until now. Protein domain distributions in the GOS dataset and current protein databases show distinct biases. Several protein domains that were previously categorized as kingdom specific are shown to have GOS examples in other kingdoms. About 6,000 sequences (ORFans) from the literature that heretofore lacked similarity to known proteins have matches in the GOS data. The GOS dataset is also used to improve remote homology detection. Overall, besides nearly doubling the number of current proteins, the predicted GOS proteins also add a great deal of diversity to known protein families and shed light on their evolution. These observations are illustrated using several protein families, including phosphatases, proteases, ultraviolet-irradiation DNA damage repair enzymes, glutamine synthetase, and RuBisCO. The diversity added by GOS data has implications for choosing targets for experimental structure characterization as part of structural genomics efforts. Our analysis indicates that new families are being discovered at a rate that is linear or almost linear with the addition of new sequences, implying that we are still far from discovering all protein families in nature.

The world's oceans contain a complex mixture of micro-organisms that are for the most part, uncharacterized both genetically and biochemically. We report here a metagenomic study of the marine planktonic microbiota in which surface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition. These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal and ending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp). Though a few major microbial clades dominate the planktonic marine niche, the dataset contains great diversity with 85% of the assembled sequence and 57% of the unassembled data being unique at a 98% sequence identity cutoff. Using the metadata associated with each sample and sequencing library, we developed new comparative genomic and assembly methods. One comparative genomic method, termed "fragment recruitment," addressed questions of genome structure, evolution, and taxonomic or phylogenetic diversity, as well as the biochemical diversity of genes and gene families. A second method, termed "extreme assembly," made possible the assembly and reconstruction of large segments of abundant but clearly nonclonal organisms. Within all abundant populations analyzed, we found extensive intra-ribotype diversity in several forms: (1) extensive sequence variation within orthologous regions throughout a given genome; despite coverage of individual ribotypes approaching 500-fold, most individual sequencing reads are unique; (2) numerous changes in gene content some with direct adaptive implications; and (3) hypervariable genomic islands that are too variable to assemble. The intra-ribotype diversity is organized into genetically isolated populations that have overlapping but independent distributions, implying distinct environmental preference. We present novel methods for measuring the genomic similarity between metagenomic samples and show how they may be grouped into several community types. Specific functional adaptations can be identified both within individual ribotypes and across the entire community, including proteorhodopsin spectral tuning and the presence or absence of the phosphate-binding gene PstS.