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The genetic law of the minimum
Abstract
No abstract available.
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In Situ Chemotaxis Assay to Examine Microbial Behavior in Aquatic Ecosystems
Abstract
Microbial behaviors, such as motility and chemotaxis (the ability of a cell to alter its movement in response to a chemical gradient), are widespread across the bacterial and archaeal domains. Chemotaxis can result in substantial resource acquisition advantages in heterogeneous environments. It also plays a crucial role in symbiotic interactions, disease, and global processes, such as biogeochemical cycling. However, current techniques restrict chemotaxis research to the laboratory and are not easily applicable in the field. Presented here is a step-by-step protocol for the deployment of the in situ chemotaxis assay (ISCA), a device that enables robust interrogation of microbial chemotaxis directly in the natural environment. The ISCA is a microfluidic device consisting of a 20 well array, in which chemicals of interest can be loaded. Once deployed in aqueous environments, chemicals diffuse out of the wells, creating concentration gradients that microbes sense and respond to by swimming into the wells via chemotaxis. The well contents can then be sampled and used to (1) quantify strength of the chemotactic responses to specific compounds through flow cytometry, (2) isolate and culture responsive microorganisms, and (3) characterize the identity and genomic potential of the responding populations through molecular techniques. The ISCA is a flexible platform that can be deployed in any system with an aqueous phase, including marine, freshwater, and soil environments.
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Constrained optimal foraging by marine bacterioplankton on particulate organic matter
Abstract
Optimal foraging theory provides a framework to understand how organisms balance the benefits of harvesting resources within a patch with the sum of the metabolic, predation, and missed opportunity costs of foraging. Here, we show that, after accounting for the limited environmental information available to microorganisms, optimal foraging theory and, in particular, patch use theory also applies to the behavior of marine bacteria in particle seascapes. Combining modeling and experiments, we find that the marine bacterium Vibrio ordalii optimizes nutrient uptake by rapidly switching between attached and planktonic lifestyles, departing particles when their nutrient concentration is more than hundredfold higher than background. In accordance with predictions from patch use theory, single-cell tracking reveals that bacteria spend less time on nutrient-poor particles and on particles within environments that are rich or in which the travel time between particles is smaller, indicating that bacteria tune the nutrient concentration at detachment to increase their fitness. A mathematical model shows that the observed behavioral switching between exploitation and dispersal is consistent with foraging optimality under limited information, namely, the ability to assess the harvest rate of nutrients leaking from particles by molecular diffusion. This work demonstrates how fundamental principles in behavioral ecology traditionally applied to animals can hold right down to the scale of microorganisms and highlights the exquisite adaptations of marine bacterial foraging. The present study thus provides a blueprint for a mechanistic understanding of bacterial uptake of dissolved organic matter and bacterial production in the ocean—processes that are fundamental to the global carbon cycle.
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Microbial evolutionary strategies in a dynamic ocean
Abstract
Marine microbes form the base of ocean food webs and drive ocean biogeochemical cycling. Yet little is known about the ability of microbial populations to adapt as they are advected through changing conditions. Here, we investigated the interplay between physical and biological timescales using a model of adaptation and an eddy-resolving ocean circulation climate model. Two criteria were identified that relate the timing and nature of adaptation to the ratio of physical to biological timescales. Genetic adaptation was impeded in highly variable regimes by nongenetic modifications but was promoted in more stable environments. An evolutionary trade-off emerged where greater short-term nongenetic transgenerational effects (low-γ strategy) enabled rapid responses to environmental fluctuations but delayed genetic adaptation, while fewer short-term transgenerational effects (high-γ strategy) allowed faster genetic adaptation but inhibited short-term responses. Our results demonstrate that the selective pressures for organisms within a single water mass vary based on differences in generation timescales resulting in different evolutionary strategies being favored. Organisms that experience more variable environments should favor a low-γ strategy. Furthermore, faster cell division rates should be a key factor in genetic adaptation in a changing ocean. Understanding and quantifying the relationship between evolutionary and physical timescales is critical for robust predictions of future microbial dynamics.
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Community level signatures of ecological succession in natural bacterial communinties.
Abstract
A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units. We profiled (16S rRNA sequencing) > 700 semi-aquatic bacterial communities while measuring their functional capacity when grown in laboratory conditions. This approach allowed us to investigate the relationship between composition and function excluding confounding environmental factors. Simulated data allowed us to reject the hypothesis that stochastic processes were responsible for community assembly, suggesting that niche effects prevailed. Consistent with this idea we identified six distinct community classes that contained samples collected from distant locations. Structural equation models showed there was a functional signature associated with each community class. We obtained a more mechanistic understanding of the classes using metagenomic predictions (PiCRUST). This approach allowed us to show that the classes contained distinct genetic repertoires reflecting community-level ecological strategies. The ecological strategies resemble the classical distinction between r- and K-strategists, suggesting that bacterial community assembly may be explained by simple ecological mechanisms.
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functionInk: An efficient method to detect functional groups in multidimensional networks reveals the hidden structure of ecological communities.
Abstract
Complex networks have been useful to link experimental data with mechanistic models, and have become widely used across many scientific disciplines. Recently, the increasing amount and complexity of data, particularly in biology, has prompted the development of multidimensional networks, where dimensions reflect the multiple qualitative properties of nodes, links or both. As a consequence, traditional quantities computed in single dimensional networks should be adapted to incorporate this new information. A particularly important problem is the detection of communities, namely sets of nodes sharing certain properties, which reduces the complexity of the networks, hence facilitating its interpretation. In this work, we propose an operative definition of ‘function’ for the nodes in multidimensional networks. We exploit this definition to show that it is possible to detect two types of communities: (a) modules, which are communities more densely connected within their members than with nodes belonging to other communities, and (b) guilds, which are sets of nodes connected with the same neighbours, even if they are not connected themselves. We provide two quantities to optimally detect both types of communities, whose relative values reflect their importance in the network. The flexibility of the method allowed us to analyse different ecological examples encompassing mutualistic, trophic and microbial networks. We showed that by considering both metrics we were able to obtain deeper ecological insights about how these different ecological communities were structured. The method mapped pools of species with properties that were known in advance, such as plants and pollinators. Other types of communities found, when contrasted with external data, turned out to be ecologically meaningful, allowing us to identify species with important functional roles or the influence of environmental variables. Furthermore, we found that the method was sensitive to community‐level topological properties like nestedness. In ecology there is often a need to identify groupings including trophic levels, guilds, functional groups or ecotypes. The method is therefore important in providing an objective means of distinguishing modules and guilds. The method we developed, functionInk (functional linkage), is computationally efficient at handling large multidimensional networks since it does not require optimization procedures or tests of robustness. The method is available at: https://github.com/apascualgarcia/functionInk.
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Metabolically cohesive microbial consortia and ecosystem functioning
Abstract
Recent theory and experiments have reported a reproducible tendency for the coexistence of microbial species under controlled environmental conditions. This observation has been explained in the context of competition for resources and metabolic complementarity given that, in microbial communities (MCs), many excreted by-products of metabolism may also be resources. MCs therefore play a key role in promoting their own stability and in shaping the niches of the constituent taxa. We suggest that an intermediate level of organization between the species and the community level may be pervasive, where tightly knit metabolic interactions create discrete consortia that are stably maintained. We call these units Metabolically Cohesive Consortia (MeCoCos) and we discuss the environmental context in which we expect their formation, and the ecological and evolutionary consequences of their existence. We argue that the ability to identify MeCoCos would open new avenues to link the species-, community- and ecosystem-level properties, with consequences for our understanding of microbial ecology and evolution, and an improved ability to predict ecosystem functioning in the wild.
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Raman-based sorting of microbial cells to link functions to their genes
Abstract
In our recent work, we developed an optofluidic platform that allows a direct link to be made between the phenotypes (functions) and the genotypes (genes) of microbial cells within natural communities. By combining stable isotope probing, optical tweezers, Raman microspectroscopy, and microfluidics, the platform performs automated Raman-based sorting of taxa from within a complex community in terms of their functional properties. In comparison with manual sorting approaches, our method provides high throughput (up to 500 cells per hour) and very high sorting accuracy (98.3 ± 1.7%), and significantly reduces the human labour required. The system provides an efficient manner to untangle the contributions of individual members within environmental and host-associated microbiomes. In this News and Thoughts, we provide an overview of our platform, describe potential applications, suggest ways in which the system could be improved, and discuss future directions in which Raman-based analysis of microbial populations might be developed.
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Encounter rates between bacteria and sinking particles
Abstract
The ecological interaction between bacteria and sinking particles, such as bacterial degradation of marine snow particles, is regulated by their encounters. Current encounter models focus on the diffusive regime, valid for particles larger than the bacterial run length, yet the majority of marine snow particles are small, and the encounter process is then ballistic. Here, we analytically and numerically quantify the encounter rate between sinking particles and non-motile or motile micro-organisms in the ballistic regime, explicitly accounting for the hydrodynamic shear created by the particle and its coupling with micro-organism shape. We complement results with selected experiments on non-motile diatoms. The shape-shear coupling has a considerable effect on the encounter rate and encounter location through the mechanisms of hydrodynamic focusing and screening, whereby elongated micro-organisms preferentially orient normally to the particle surface downstream of the particle (focusing) and tangentially to the surface upstream of the particle (screening). Non-motile elongated micro-organisms are screened from sinking particles because shear aligns them tangentially to the particle surface, which reduces the encounter rate by a factor proportional to the square of the micro-organism aspect ratio. For motile elongated micro-organisms, hydrodynamic focusing increases the encounter rate when particle sinking speed is similar to micro-organism swimming speed, whereas for very quickly sinking particles hydrodynamic screening can reduce the encounter rate below that of non-motile micro-organisms. For natural ocean conditions, we connect the ballistic and diffusive limits and compute the encounter rate as a function of shape, motility and particle characteristics. Our results indicate that shear should be taken into account to predict the interactions between bacteria and sinking particles responsible for the large carbon flux in the ocean’s biological pump.
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On the collision of rods in a quiescent fluid
Abstract
Rods settling under gravity in a quiescent fluid can overcome the bottleneck associated with aggregation of equal-size spheres because they collide by virtue of their orientation-dependent settling velocity. We find the corresponding collision kernel Γrods=lβ1ΔρVrodg/(16Aμ), where l, A, and Vrod are the rods’ length, aspect ratio (length divided by width), and volume, respectively, Δρ is the density difference between rods and fluid, μ is the fluid’s dynamic viscosity, g is the gravitational acceleration, and β1(A) is a geometrical parameter. We apply this formula to marine snow formation following a phytoplankton bloom. Over a broad range of aspect ratios, the formula predicts a similar or higher encounter rate between rods as compared to the encounter rate between (equal volume) spheres aggregating either by differential settling or due to turbulence. Since many phytoplankton species are elongated, these results suggest that collisions induced by the orientation-dependent settling velocity can contribute significantly to marine snow formation, and that marine snow composed of elongated phytoplankton cells can form at high rates also in the absence of turbulence.
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Bursts characterize coagulation of rods in a quiescent fluid
Abstract
Under favorable conditions, microscopic phytoplankton cells dwelling in the oceans can divide rapidly and reach high concentrations, forming blooms that span kilometers and last for weeks. When blooms collapse, dead cells settle and aggregate into “marine snow” particles, resulting in a large and climatically important vertical flux of carbon from the ocean surface to its depth, a process known as the “biological pump.” To date, the formation of marine snow has been modeled as coagulation between spherical particles driven by gravitational settling and turbulent mixing, characterized by coagulation dynamics that converge onto time-independent concentrations of aggregates. However, many phytoplankton species are elongated and how their rodlike shape affects the aggregation process has remained unknown. Here, we study marine snow formation in a quiescent fluid assuming the constituent particles are elongated and form bundles upon encounter. We derive the collision kernel between dissimilar rods settling under gravity and discover that the most frequent collisions occur between the thinnest and thickest bundles, rather than between bundles of similar size. As a consequence, in the full coagulation model that combines exponential growth with settling, the thin-thick coupling can lead to statistically stationary states where the concentrations of aggregates of different size oscillate in time, exhibiting periodic bursts. The bursts are predicted to occur on the scale of a week and eventually lead to broadening of aggregate size spectra and may thus be highly relevant for plankton dynamics and the carbon cycle in the ocean.
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The effect of flow on swimming bacteria controls the initial colonisation of curved surfaces
Abstract
The colonization of surfaces by bacteria is a widespread phenomenon with consequences on environmental processes and human health. While much is known about the molecular mechanisms of surface colonization, the influence of the physical environment remains poorly understood. Here we show that the colonization of non-planar surfaces by motile bacteria is largely controlled by flow. Using microfluidic experiments with Pseudomonas aeruginosa and Escherichia coli, we demonstrate that the velocity gradients created by a curved surface drive preferential attachment to specific regions of the collecting surface, namely the leeward side of cylinders and immediately downstream of apexes on corrugated surfaces, in stark contrast to where nonmotile cells attach. Attachment location and rate depend on the local hydrodynamics and, as revealed by a mathematical model benchmarked on the observations, on cell morphology and swimming traits. These results highlight the importance of flow on the magnitude and location of bacterial colonization of surfaces.
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Trophic Interactions and the Drivers of Microbial Community Assembly
Abstract
Despite numerous surveys of gene and species content in heterotrophic microbial communities, such as those found in animal guts, oceans, or soils, it is still unclear whether there are generalizable biological or ecological processes that control their dynamics and function. Here, we review experimental and theoretical advances to argue that networks of trophic interactions, in which the metabolic excretions of one species are the primary resource for another, constitute the central drivers of microbial community assembly. Trophic interactions emerge from the deconstruction of complex forms of organic matter into a wealth of smaller metabolic intermediates, some of which are released to the environment and serve as a nutritional buffet for the community. The structure of the emergent trophic network and the rate at which primary resources are supplied control many features of microbial community assembly, including the relative contributions of competition and cooperation and the emergence of alternative community states. Viewing microbial community assembly through the lens of trophic interactions also has important implications for the spatial dynamics of communities as well as the functional redundancy of taxonomic groups. Given the ubiquity of trophic interactions across environments, they impart a common logic that can enable the development of a more quantitative and predictive microbial community ecology.
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Single-cell bacterial transcription measurements reveal the importance of dimethylsulfoniopropionate (DMSP) hotspots in ocean sulfur cycling
Abstract
Dimethylsulfoniopropionate (DMSP) is a pivotal compound in marine biogeochemical cycles and a key chemical currency in microbial interactions. Marine bacteria transform DMSP via two competing pathways with considerably different biogeochemical implications: demethylation channels sulfur into the microbial food web, whereas cleavage releases sulfur into the atmosphere. Here, we present single-cell measurements of the expression of these two pathways using engineered fluorescent reporter strains of Ruegeria pomeroyi DSS-3, and find that external DMSP concentration dictates the relative expression of the two pathways. DMSP induces an upregulation of both pathways, but only at high concentrations (>1 μM for demethylation; >35 nM for cleavage), characteristic of microscale hotspots such as the vicinity of phytoplankton cells. Co-incubations between DMSP-producing microalgae and bacteria revealed an increase in cleavage pathway expression close to the microalgae’s surface. These results indicate that bacterial utilization of microscale DMSP hotspots is an important determinant of the fate of sulfur in the ocean.
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Genome sequences and metagenome-assembled genome sequences of microbial communities enriched on phytoplankton exometabolites.
Abstract
We report 11 bacterial draft genome sequences and 38 metagenome-assembled genomes (MAGs) from marine phytoplankton exometabolite enrichments. The genomes and MAGs represent marine bacteria adapted to the metabolite environment of phycospheres, organic matter-rich regions surrounding phytoplankton cells, and are useful for exploring functional and taxonomic attributes of phytoplankton-associated bacterial communities.
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Ecological drivers of bacterial community assembly in synthetic phycospheres
Abstract
In the nutrient-rich region surrounding marine phytoplankton cells, heterotrophic bacterioplankton transform a major fraction of recently fixed carbon through the uptake and catabolism of phytoplankton metabolites. We sought to understand the rules by which marine bacterial communities assemble in these nutrient-enhanced phycospheres, specifically addressing the role of host resources in driving community coalescence. Synthetic systems with varying combinations of known exometabolites of marine phytoplankton were inoculated with seawater bacterial assemblages, and communities were transferred daily to mimic the average duration of natural phycospheres. We found that bacterial community assembly was predictable from linear combinations of the taxa maintained on each individual metabolite in the mixture, weighted for the growth each supported. Deviations from this simple additive resource model were observed but also attributed to resource-based factors via enhanced bacterial growth when host metabolites were available concurrently. The ability of photosynthetic hosts to shape bacterial associates through excreted metabolites represents a mechanism by which microbiomes with beneficial effects on host growth could be recruited. In the surface ocean, resource-based assembly of host-associated communities may underpin the evolution and maintenance of microbial interactions and determine the fate of a substantial portion of Earth’s primary production.
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Cutting through the noise: bacterial chemotaxis in marine microenvironments
Abstract
The ability of marine microbes to navigate toward chemical hotspots can determine their nutrient uptake and has the potential to affect the cycling of elements in the ocean. The link between bacterial navigation and nutrient cycling highlights the need to understand how chemotaxis functions in the context of marine microenvironments. Chemotaxis hinges on the stochastic binding/unbinding of molecules with surface receptors, the transduction of this information through an intracellular signaling cascade, and the activation and control of flagellar motors. The intrinsic randomness of these processes is a central challenge that cells must deal with in order to navigate, particularly under dilute conditions where noise and signal are similar in magnitude. Such conditions are ubiquitous in the ocean, where nutrient concentrations are often extremely low and subject to rapid variation in space (e.g., particulate matter, nutrient plumes) and time (e.g., diffusing sources, fluid mixing). Stochastic, biophysical models of chemotaxis have the potential to illuminate how bacteria cope with noise to efficiently navigate in such environments. At the same time, new technologies for experimentation allow for continuous interrogation—from milliseconds through to days—of bacterial responses in custom dynamic nutrient landscapes, providing unprecedented access to the behavior of chemotactic cells in microenvironments engineered to mimic those cells navigate in the wild. These recent theoretical and experimental developments have created an opportunity to derive population-level uptake from single-cell motility characteristics in ways that could inform the next generation of marine biogeochemical cycling models.
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PhenoChip: A single-cell phenomic platform for high-throughput photophysiological analyses of microalgae
Abstract
Photosynthetic microorganisms are key players in aquatic ecosystems with strong potential for bioenergy production, yet their systematic selection at the single-cell level for improved productivity or stress resilience (“phenotyping”) has remained largely inaccessible. To facilitate the phenotyping of microalgae and cyanobacteria, we developed “PhenoChip,” a platform for the multiparametric photophysiological characterization and selection of unicellular phenotypes under user-controlled physicochemical conditions. We used PhenoChip to expose single cells of the coral symbiont Symbiodinium to thermal and chemical treatments and monitor single-cell photophysiology via chlorophyll fluorometry. This revealed strain-specific thermal sensitivity thresholds and distinct pH optima for photosynthetic performance, and permitted the identification of single cells with elevated resilience toward rising temperature. Optical expulsion technology was used to collect single cells from PhenoChip, and their propagation revealed indications of transgenerational preservation of photosynthetic phenotypes. PhenoChip represents a versatile platform for the phenotyping of photosynthetic unicells relevant to biotechnology, ecotoxicology, and assisted evolution.
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Phenotypic variation in spatially structured microbial communities: ecological origins and consequences
Abstract
Microbial cells in nature live within dense multispecies conglomerates, forming a self-organizing ecosystem. In such assemblies, genotypes interact with each other in a myriad of ways, driving community dynamics and functionalities. The role of interactions between genotypes and their consequences for spatial structure and functional outcomes are being increasingly studied to understand the ecology and evolution of microbial communities. An increasing body of work with simple microbial populations has elucidated that phenotypic variation, that is, differences within isogenic cells can have important consequences for population dynamics and evolution. However, the role of individual level behavioral differences for community level dynamics is relatively unknown. I argue that it is necessary to study phenotypic variation and microscale processes in order to understand the emergence and consequences of interactions within microbial communities. I highlight possible explanations that can explain the emergence of variation in multi-genotypic assemblages and propose possible consequences on community dynamics.
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Environmental drivers of metabolic heterogeneity in clonal microbial populations
Abstract
Microorganisms perform multiple metabolic functions that shape the global cycling of elements, health and disease of their host organisms, and biotechnological processes. The rates, at which different metabolic activities are performed by individual cells, can vary between genetically identical cells within clonal populations. While the molecular mechanisms that result in such metabolic heterogeneity have attracted considerable interest, the environmental conditions that shape heterogeneity and its consequences have received attention only in recent years. Here, we review the environmental drivers that lead to metabolic heterogeneity with a focus on nutrient limitation, temporal fluctuations and spatial structure, and the functional consequences of such heterogeneity. We highlight studies using single-cell methods that allow direct investigation of metabolic heterogeneity and discuss the relevance of metabolic heterogeneity in complex microbial communities.
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Understanding the evolution of interspecies interactions in microbial communities
Abstract
Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments.