Manoshi Sen Datta

Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids

Inactivation of β‐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 β‐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 β‐lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance.

Range expansion promotes cooperation in an experimental microbial metapopulation

Natural populations throughout the tree of life undergo range expansions in response to changes in the environment. Recent theoretical work suggests that range expansions can have a strong effect on evolution, even leading to the fixation of deleterious alleles that would normally be outcompeted in the absence of migration. However, little is known about how range expansions might influence alleles under frequency- or density-dependent selection. Moreover, there is very little experimental evidence to complement existing theory, since expanding populations are difficult to study in the natural environment. In this study, we have used a yeast experimental system to explore the effect of range expansions on the maintenance of cooperative behaviors, which commonly display frequency- and density-dependent selection and are widespread in nature. We found that range expansions favor the maintenance of cooperation in two ways: (i) through the enrichment of cooperators at the front of the expanding population and (ii) by allowing cooperators to “outrun” an invading wave of defectors. In this system, cooperation is enhanced through the coupling of population ecology and evolutionary dynamics in expanding populations, thus providing experimental evidence for a unique mechanism through which cooperative behaviors could be maintained in nature.

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.

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.

Natural resource landscapes of a marine bacterium reveal distinct fitness‐determining genes across the genome

Summary Heterotrophic bacteria exploit diverse microhabitats in the ocean, from particles to transient gradients. Yet the degree to which genes and pathways can contribute to an organisms fitness on such complex and variable natural resource landscapes remains poorly understood. Here, we determine the gene‐by‐gene fitness of a generalist saprophytic marine bacterium (Vibrio sp. F13 9CS106) on complex resources derived from its natural habitats – copepods (Apocyclops royi) and brown algae (Fucus vesiculosus) – and as reference substrates, glucose and the polysaccharide alginate, derived from brown algal cell walls. We find that resource complexity strongly buffers fitness costs of mutations, and that anabolic rather than catabolic pathways are more stringently required, likely due to functional redundancy in the latter. Moreover, while carbohydrate‐rich algae requires several synthesis pathways, protein‐rich Apocyclops does not, suggesting this ancestral habitat for Vibrios is a replete medium with metabolically redundant substrates. We also identify a candidate fitness trade‐off for algal colonization: deletion of mshA increases mutant fitness. Our results demonstrate that gene fitness depends on habitat composition, and suggest that this generalist uses distinct resources in different natural habitats. The results further indicate that substrate replete conditions may lead to relatively relaxed selection on catabolic genes.

Modular assembly of polysaccharide-degrading microbial communities in the ocean

Many complex biological systems such as metabolic networks can be divided into functional and organizational subunits, called modules, which provide the flexibility to assemble novel multi-functional hierarchies by a mix and match of simpler components. Here we show that polysaccharide-degrading microbial communities in the ocean can also assemble in a modular fashion. Using synthetic particles made of a variety of polysaccharides commonly found in the ocean, we showed that the particle colonization dynamics of natural bacterioplankton assemblages can be understood as the aggregation of species modules of two main types: a first module type made of narrow niche-range primary degraders, whose dynamics are controlled by particle polysaccharide composition, and a second module type containing broad niche-range, substrate-independent taxa whose dynamics are controlled by interspecific interactions, in particular cross-feeding via organic acids, amino acids and other metabolic byproducts. As a consequence of this modular logic, communities can be predicted to assemble by a sum of substrate-specific primary degrader modules, one for each complex polysaccharide in the particle, connected to a single broad-niche range consumer module. We validate this model by showing that a linear combination of the communities on single-polysaccharide particles accurately predicts community composition on mixed-polysaccharide particles. Our results suggest thus that the assembly of heterotrophic communities that degrade complex organic materials follow simple design principles that can 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.