Genomic Variation Influences Methanothermococcus Fitness in Marine Hydrothermal Systems.

Hydrogenotrophic methanogens are ubiquitous chemoautotrophic archaea inhabiting globally distributed deep-sea hydrothermal vent ecosystems and associated subseafloor niches within the rocky subseafloor, yet little is known about how they adapt and diversify in these habitats. To determine genomic variation and selection pressure within methanogenic populations at vents, we examined five Methanothermococcus single cell amplified genomes (SAGs) in conjunction with 15 metagenomes and 10 metatranscriptomes from venting fluids at two geochemically distinct hydrothermal vent fields on the Mid-Cayman Rise in the Caribbean Sea. We observed that some Methanothermococcus lineages and their transcripts were more abundant than others in individual vent sites, indicating differential fitness among lineages. The relative abundances of lineages represented by SAGs in each of the samples matched phylogenetic relationships based on single-copy universal genes, and genes related to nitrogen fixation and the CRISPR/Cas immune system were among those differentiating the clades. Lineages possessing these genes were less abundant than those missing that genomic region. Overall, patterns in nucleotide variation indicated that the population dynamics of Methanothermococcus were not governed by clonal expansions or selective sweeps, at least in the habitats and sampling times included in this study. Together, our results show that although specific lineages of Methanothermococcus co-exist in these habitats, some outcompete others, and possession of accessory metabolic functions does not necessarily provide a fitness advantage in these habitats in all conditions. This work highlights the power of combining single-cell, metagenomic, and metatranscriptomic datasets to determine how evolution shapes microbial abundance and diversity in hydrothermal vent ecosystems.

Seasonal Succession and Spatial Patterns of Synechococcus Microdiversity in a Salt Marsh Estuary Revealed through 16S rRNA Gene Oligotyping.

Synechococcus are ubiquitous and cosmopolitan cyanobacteria that play important roles in global productivity and biogeochemical cycles. This study investigated the fine scale microdiversity, seasonal patterns, and spatial distributions of Synechococcus in estuarine waters of Little Sippewissett salt marsh (LSM) on Cape Cod, MA. The proportion of Synechococcus reads was higher in the summer than winter, and higher in coastal waters than within the estuary. Variations in the V4-V6 region of the bacterial 16S rRNA gene revealed 12 unique Synechococcus oligotypes. Two distinct communities emerged in early and late summer, each comprising a different set of statistically co-occurring Synechococcus oligotypes from different clades. The early summer community included clades I and IV, which correlated with lower temperature and higher dissolved oxygen levels. The late summer community included clades CB5, I, IV, and VI, which correlated with higher temperatures and higher salinity levels. Four rare oligotypes occurred in the late summer community, and their relative abundances more strongly correlated with high salinity than did other co-occurring oligotypes. The analysis revealed that multiple, closely related oligotypes comprised certain abundant clades (e.g., clade 1 in the early summer and clade CB5 in the late summer), but the correlations between these oligotypes varied from pair to pair, suggesting they had slightly different niches despite being closely related at the clade level. Lack of tidal water exchange between sampling stations gave rise to a unique oligotype not abundant at other locations in the estuary, suggesting physical isolation plays a role in generating additional microdiversity within the community. Together, these results contribute to our understanding of the environmental and ecological factors that influence patterns of Synechococcus microbial community composition over space and time in salt marsh estuarine waters.

Comparative mitochondrial and chloroplast genomics of a genetically distinct form of Sargassum contributing to recent "Golden Tides" in the Western Atlantic.

Over the past 5 years, massive accumulations of holopelagic species of the brown macroalga Sargassum in coastal areas of the Caribbean have created "golden tides" that threaten local biodiversity and trigger economic losses associated with beach deterioration and impact on fisheries and tourism. In 2015, the first report identifying the cause of these extreme events implicated a rare form of the holopelagic species Sargassum natans (form VIII). However, since the first mention of S. natans VIII in the 1930s, based solely on morphological characters, no molecular data have confirmed this identification. We generated full-length mitogenomes and partial chloroplast genomes of all representative holopelagic Sargassum species, S. fluitans III and S. natans I alongside the putatively rare S. natans VIII, to demonstrate small but consistent differences between S. natans I and VIII (7 bp differences out of the 34,727). Our comparative analyses also revealed that both S. natans I and S. natans VIII share a very close phylogenetic relationship with S. fluitans III (94- and 96-bp differences of 34,727). We designed novel primers that amplified regions of the cox2 and cox3 marker genes with consistent polymorphic sites that enabled differentiation between the two S. natans forms (I and VIII) from each other and both from S. fluitans III in over 150 Sargassum samples including those from the 2014 golden tide event. Despite remarkable gene synteny and sequence conservation, the three Sargassum forms differ in morphology, ecology, and distribution patterns, warranting more extensive interrogation of holopelagic Sargassum genomes as a whole.

Oligotyping: Differentiating between closely related microbial taxa using 16S rRNA gene data.

Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function is of prime importance. High-throughput sequencing technologies enable nearly comprehensive descriptions of bacterial diversity through 16S ribosomal RNA gene amplicons. Analyses of these communities generally rely upon taxonomic assignments through reference databases, or clustering approaches using de facto sequence similarity thresholds to identify operational taxonomic units. However, these methods often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial datasets.In this paper we describe oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms in final operational taxonomic units identified in environmental datasets through 16S ribosomal RNA gene data by the canonical approaches.Our analysis of two datasets from two distinct environments demonstrates the capacity of oligotyping at discriminating distinct microbial populations of ecological importance.Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.