Rapid methicillin resistance diversification in Staphylococcus epidermidis colonizing human neonates.

Early in life, infants are colonized with multiple bacterial strains whose differences in gene content can have important health consequences. Metagenomics-based approaches have revealed gene content differences between different strains co-colonizing newborns, but less is known about the rate, mechanism, and phenotypic consequences of gene content diversification within strains. Here, focusing on Staphylococcus epidermidis, we whole-genome sequence and phenotype more than 600 isolates from newborns. Within days of birth, infants are co-colonized with a highly personalized repertoire of S. epidermidis strains, which are spread across the newborn body. Comparing the genomes of multiple isolates of each strain, we find very little evidence of adaptive evolution via single-nucleotide polymorphisms. By contrast, we observe gene content differences even between otherwise genetically identical cells, including variation of the clinically important methicillin resistance gene, mecA, suggesting rapid gene gain and loss events at rates higher than point mutations. Mapping the genomic architecture of structural variants by long-read Nanopore sequencing, we find that deleted regions were always flanked by direct repeats, consistent with site-specific recombination. However, we find that even within a single genetic background, recombination occurs at multiple, often non-canonical repeats, leading to the rapid evolution of patient-specific diverse structural variants in the SCCmec island and to differences in antibiotic resistance.

Modular Assembly of Polysaccharide-Degrading Marine Microbial Communities.

Understanding the principles that govern the assembly of microbial communities across earth's biomes is a major challenge in modern microbial ecology. This pursuit is complicated by the difficulties of mapping functional roles and interactions onto communities with immense taxonomic diversity and of identifying the scale at which microbes interact [1]. To address this challenge, here, we focused on the bacterial communities that colonize and degrade particulate organic matter in the ocean [2-4]. We show that the assembly of these communities can be simplified as a linear combination of functional modules. Using synthetic polysaccharide particles immersed in natural bacterioplankton assemblages [1, 5], we showed that successional particle colonization dynamics are driven by the interaction of two types of modules: a first type made of narrowly specialized primary degraders, whose dynamics are controlled by particle polysaccharide composition, and a second type containing substrate-independent taxa whose dynamics are controlled by interspecific interactions-in particular, cross-feeding via organic acids, amino acids, and other metabolic byproducts. We show that, as a consequence of this trophic structure, communities can assemble modularly-i.e., by a simple sum of substrate-specific primary degrader modules, one for each complex polysaccharide in the particle, connected to a single broad-niche range consumer module. Consistent with this model, a linear combination of the communities on single-polysaccharide particles accurately predicts community composition on mixed-polysaccharide particles. Our results suggest that the assembly of heterotrophic communities that degrade complex organic materials follows simple design principles that could be exploited to engineer heterotrophic microbiomes.

Inter-individual variability in copepod microbiomes reveals bacterial networks linked to host physiology.

Copepods harbor diverse bacterial communities, which collectively carry out key biogeochemical transformations in the ocean. However, bulk copepod sampling averages over the variability in their associated bacterial communities, thereby limiting our understanding of the nature and specificity of copepod-bacteria associations. Here, we characterize the bacterial communities associated with nearly 200 individual Calanus finmarchicus copepods transitioning from active growth to diapause. We find that all individual copepods sampled share a small set of "core" operational taxonomic units (OTUs), a subset of which have also been found associated with other marine copepod species in different geographic locations. However, most OTUs are patchily distributed across individual copepods, thereby driving community differences across individuals. Among patchily distributed OTUs, we identified groups of OTUs correlated with common ecological drivers. For instance, a group of OTUs positively correlated with recent copepod feeding served to differentiate largely active growing copepods from those entering diapause. Together, our results underscore the power of individual-level sampling for understanding host-microbiome relationships.

Adaptive radiation by waves of gene transfer leads to fine-scale resource partitioning in marine microbes.

Adaptive radiations are important drivers of niche filling, since they rapidly adapt a single clade of organisms to ecological opportunities. Although thought to be common for animals and plants, adaptive radiations have remained difficult to document for microbes in the wild. Here we describe a recent adaptive radiation leading to fine-scale ecophysiological differentiation in the degradation of an algal glycan in a clade of closely related marine bacteria. Horizontal gene transfer is the primary driver in the diversification of the pathway leading to several ecophysiologically differentiated Vibrionaceae populations adapted to different physical forms of alginate. Pathway architecture is predictive of function and ecology, underscoring that horizontal gene transfer without extensive regulatory changes can rapidly assemble fully functional pathways in microbes.

Microbial interactions lead to rapid micro-scale successions on model marine particles.

In the ocean, organic particles harbour diverse bacterial communities, which collectively digest and recycle essential nutrients. Traits like motility and exo-enzyme production allow individual taxa to colonize and exploit particle resources, but it remains unclear how community dynamics emerge from these individual traits. Here we track the taxon and trait dynamics of bacteria attached to model marine particles and demonstrate that particle-attached communities undergo rapid, reproducible successions driven by ecological interactions. Motile, particle-degrading taxa are selected for during early successional stages. However, this selective pressure is later relaxed when secondary consumers invade, which are unable to use the particle resource but, instead, rely on carbon from primary degraders. This creates a trophic chain that shifts community metabolism away from the particle substrate. These results suggest that primary successions may shape particle-attached bacterial communities in the ocean and that rapid community-wide metabolic shifts could limit rates of marine particle degradation.

Microbial interactions and community assembly at microscales.

In most environments, microbial interactions take place within microscale cell aggregates. At the scale of these aggregates (∼100µm), interactions are likely to be the dominant driver of population structure and dynamics. In particular, organisms that exploit interspecific interactions to increase ecological performance often co-aggregate. Conversely, organisms that antagonize each other will tend to spatially segregate, creating distinct micro-communities and increased diversity at larger length scales. We argue that, in order to understand the role that biological interactions play in microbial community function, it is necessary to study microscale spatial organization with enough throughput to measure statistical associations between taxa and possible alternative community states. We conclude by proposing strategies to tackle this challenge.

Cross-kingdom chemical communication drives a heritable, mutually beneficial prion-based transformation of metabolism.

In experimental science, organisms are usually studied in isolation, but in the wild, they compete and cooperate in complex communities. We report a system for cross-kingdom communication by which bacteria heritably transform yeast metabolism. An ancient biological circuit blocks yeast from using other carbon sources in the presence of glucose. [GAR(+)], a protein-based epigenetic element, allows yeast to circumvent this "glucose repression" and use multiple carbon sources in the presence of glucose. Some bacteria secrete a chemical factor that induces [GAR(+)]. [GAR(+)] is advantageous to bacteria because yeast cells make less ethanol and is advantageous to yeast because their growth and long-term viability is improved in complex carbon sources. This cross-kingdom communication is broadly conserved, providing a compelling argument for its adaptive value. By heritably transforming growth and survival strategies in response to the selective pressures of life in a biological community, [GAR(+)] presents a unique example of Lamarckian inheritance.

Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids.

Inactivation of ß-lactam antibiotics by resistant bacteria is a 'cooperative' behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a ß-lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used ß-lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance.