Application of ecological and evolutionary theory to microbiome community dynamics across systems

A fundamental aim of microbiome research is to understand the factors that influence the assembly and stability of host-associated microbiomes, and their impact on host phenotype, ecology and evolution. However, ecological and evolutionary theories applied to predict microbiome community dynamics are largely based on macroorganisms and lack microbiome-centric hypotheses that account for unique features of the microbiome. This special feature sets out to drive advancements in the application of eco-evolutionary theory to microbiome community dynamics through the development of microbiome-specific theoretical and conceptual frameworks across plant, human and non-human animal systems. The feature comprises 11 research and review articles that address: (i) the effects of the microbiome on host phenotype, ecology and evolution; (ii) the application and development of ecological and evolutionary theories to investigate microbiome assembly, diversity and stability across broad taxonomic scales; and (iii) general principles that underlie microbiome diversity and dynamics. This cross-disciplinary synthesis of theoretical, conceptual, methodological and analytical approaches to characterizing host–microbiome ecology and evolution across systems addresses key research gaps in the field of microbiome research and highlights future research priorities.     

Harnessing ecological and evolutionary principles to guide the design of microbial production consortia

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Understanding evolutionary and ecological dynamics using a continuum limit

Continuum limits in the form of stochastic differential equations are typically used in theoretical population genetics to account for genetic drift or more generally, inherent randomness of the model. In evolutionary game theory and theoretical ecology, however, this method is used less frequently to study demographic stochasticity. Here, we review the use of continuum limits in ecology and evolution. Starting with an individual‐based model, we derive a large population size limit, a (stochastic) differential equation which is called continuum limit. By example of the Wright–Fisher diffusion, we outline how to compute the stationary distribution, the fixation probability of a certain type, and the mean extinction time using the continuum limit. In the context of the logistic growth equation, we approximate the quasi‐stationary distribution in a finite population.     

The evolutionary dynamics of self-incompatibility systems

Self-incompatible flowering plants reject pollen that expresses the same mating specificity as the pistil (female reproductive tract). In most plant families, pollen and pistil mating specificities segregate as a single locus, the S locus. In at least two self-incompatibility systems, distinct pollen and pistil specificity genes are embedded in an extensive nonrecombining tract. To facilitate consideration of how new S locus specificities arise in systems with distinct pollen and pistil genes, we present a graphical model for the generation of hypotheses. It incorporates the evolutionary principle that nonreciprocal siring success (cross-pollinations between two plants produce seeds in only one direction) tends to favor the rejecting partner. This model suggests that selection within S-allele specificity classes could accelerate the rate of nonsynonymous (amino acid-changing) substitutions, with periodic selective sweeps removing segregating variation within classes. Accelerated substitution within specificity classes could also promote the origin of new S-allele specificities.     

Transient dynamics and persistence of ecological systems

Using spatially coupled predator–prey systems as an example of a cyclic ecological system where coexistence depends on oscillations, transient dynamics of models where there are no stable persistent solutions are shown to be a reasonable explanation of persistence over ecological time scales. The parameter values leading to transients within the context of a particular model may be far from parameter values that lead to stable solutions, so transients will need to be explicitly considered in model analysis. Since natural systems with many coupled oscillating species are common, and natural communities are often reset by disturbances or seasonality, transients should play a central role in understanding natural systems.     

The ecological dynamics of pest-resource-people systems

Abstract

Pest problems involve people who value a resource affected by a pest that is managed by people, ideally the same as those who value the resource. Management that is not inclusive of pests, resources, people, and their interactions usually fails. Mammalian pests in New Zealand are of two sorts: those that are pests in their native land (usually r-strategists), and those that are not (usually K-strategists). The impact on New Zealand resources of r-strategists tends to be periodic and acute when their densities are high. Control works best against them when it is applied once densities become intolerable, or once such densities can be predicted. The impact of K-strategists is more stable but is chronic. Control operations against them need to be sustained and regular to retain the stability of the pest-resource interaction, but to drive it in favour of the resource. The basic strategies to deal with the impact of pests are: those for which a one-off management action has a permanent benefit (e.g., eradication); those that require ongoing action to gain a permanent benefit (e.g., sustained control); and those for which no management action is possible or justified. Idealist and cynical approaches to pest policies are discussed and rejected in favour of a pragmatic policy.     

Cross-scale ecological dynamics and microbial size spectra in marine ecosystems

Evaluating the component features of 'scaling' planktonic size spectra, commonly observed in marine ecosystems, is crucial for understanding the ecological and evolutionary processes from which they emerge. Here, we develop a theoretical framework that describes such spectra in terms of the size distributions of individual species, and test it against actual datasets of microbial size spectra from the Atlantic Ocean. We describe characteristics of size probability distributions of component species that are sufficient to support the observational evidence and infer that, when a power law describes the community size spectrum (thus suggesting critical self-organization of microbial ecosystem structure and function), a related power law links the total number of individuals of a given species to its mean size.     

Mechanical sensitivity reveals evolutionary dynamics of mechanical systems

A classic question in evolutionary biology is how form–function relationships promote or limit diversification. Mechanical metrics, such as kinematic transmission (KT) in linkage systems, are useful tools for examining the evolution of form and function in a comparative context. The convergence of disparate systems on equivalent metric values (mechanical equivalence) has been highlighted as a source of potential morphological diversity under the assumption that morphology can evolve with minimal impact on function. However, this assumption does not account for mechanical sensitivity—the sensitivity of the metric to morphological changes in individual components of a structure. We examined the diversification of a four-bar linkage system in mantis shrimp (Stomatopoda), and found evidence for both mechanical equivalence and differential mechanical sensitivity. KT exhibited variable correlations with individual linkage components, highlighting the components that influence KT evolution, and the components that are free to evolve independently from KT and thereby contribute to the observed pattern of mechanical equivalence. Determining the mechanical sensitivity in a system leads to a deeper understanding of both functional convergence and morphological diversification. This study illustrates the importance of multi-level analyses in delineating the factors that limit and promote diversification in form–function systems.     

Engineering microbial systems for the production and functionalization of biomaterials

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Evolutionary dynamics of predator-prey systems: an ecological perspective

 Evolution takes place in an ecological setting that typically involves interactions with other organisms. To describe such evolution, a structure is needed which incorporates the simultaneous evolution of interacting species. Here a formal framework for this purpose is suggested, extending from the microscopic interactions between individuals – the immediate cause of natural selection, through the mesoscopic population dynamics responsible for driving the replacement of one mutant phenotype by another, to the macroscopic process of phenotypic evolution arising from many such substitutions. The process of coevolution that results from this is illustrated in the context of predator–prey systems. With no more than qualitative information about the evolutionary dynamics, some basic properties of predator–prey coevolution become evident. More detailed understanding requires specification of an evolutionary dynamic; two models for this purpose are outlined, one from our own research on a stochastic process of mutation and selection and the other from quantitative genetics. Much of the interest in coevolution has been to characterize the properties of fixed points at which there is no further phenotypic evolution. Stability analysis of the fixed points of evolutionary dynamical systems is reviewed and leads to conclusions about the asymptotic states of evolution rather different from those of game-theoretic methods. These differences become especially important when evolution involves more than one species. Received 10 November 1993; received in revised form 25 July 1994     

Elevational diversity patterns as an example for evolutionary and ecological dynamics in ferns and lycophytes

Evolutionary processes such as adaptation, ecological filtering, and niche conservatism involve the interaction of organisms with their environment and are thus commonly studied along environmental gradients. Elevational gradients have become among the most studied environmental gradients to understand large-scale patterns of species richness and composition because they are highly replicated with different combinations of geographical, environmental and historical factors. We here review the literature on using elevational gradients to understand evolutionary processes in ferns. Some phylogenetic studies of individual fern clades have considered elevation in the analysis or interpretation and postulated that fern diversification is linked to the colonization of mountain habitats. Other studies that have linked elevational community composition and hence ecological filtering with phylogenetic community composition and morphological traits, usually only found limited phylogenetic signal. However, these studies are ultimately only correlational, and there are few actual tests of the evolutionary mechanisms leading to these patterns. We identify a number of challenges for improving our understanding of how evolutionary and ecological processes are linked to elevational richness patterns in ferns: i) limited information on traits and their ecological relevance, ii) uncertainties on the dispersal kernels of ferns and hence the delimitation of regional species pools from which local assemblages are recruited, iii) limited genomic data to identify candidate genes under selection and hence actually document adaptation and selection, and iv) conceptual challenges in developing clear and testable hypotheses to how specific evolutionary processes can be linked to patterns in community composition and species richness.     

Measuring complexity to infer changes in the dynamics of ecological systems under stress

Despite advances in our mechanistic understanding of ecological processes, the inherent complexity of real-world ecosystems still limits our ability in predicting ecological dynamics especially in the face of on-going environmental stress. Developing a model is frequently challenged by structure uncertainty, unknown parameters, and limited data for exploring out-of-sample predictions. One way to address this challenge is to look for patterns in the data themselves in order to infer the underlying processes of an ecological system rather than to build system-specific models. For example, it has been recently suggested that statistical changes in ecological dynamics can be used to infer changes in the stability of ecosystems as they approach tipping points. For computer scientists such inference is similar to the notion of a Turing machine: a computational device that could execute a program (the process) to produce the observed data (the pattern). Here, we make use of such basic computational ideas introduced by Alan Turing to recognize changing patterns in ecological dynamics in ecosystems under stress. To do this, we use the concept of Kolmogorov algorithmic complexity that is a measure of randomness. In particular, we estimate an approximation to Kolmogorov complexity based on the Block Decomposition Method (BDM). We apply BDM to identify changes in complexity in simulated time-series and spatial datasets from ecosystems that experience different types of ecological transitions. We find that in all cases, K_BDM complexity decreased before all ecological transitions both in time-series and spatial datasets. These trends indicate that loss of stability in the ecological models we explored is characterized by loss of complexity and the emergence of a regular and computable underlying structure. Our results suggest that Kolmogorov complexity may serve as tool for revealing changes in the dynamics of ecosystems close to ecological transitions.     

Distinguishing ecological from evolutionary approaches to transposable elements

Considerable variation exists not only in the kinds of transposable elements (TEs) occurring within the genomes of different species, but also in their abundance and distribution. Noting a similarity to the assortment of organisms among ecosystems, some researchers have called for an ecological approach to the study of transposon dynamics. However, there are several ways to adopt such an approach, and it is sometimes unclear what an ecological perspective will add to the existing co‐evolutionary framework for explaining transposon‐host interactions. This review aims to clarify the conceptual foundations of transposon ecology in order to evaluate its explanatory prospects. We begin by identifying three unanswered questions regarding the abundance and distribution of TEs that potentially call for an ecological explanation. We then offer an operational distinction between evolutionary and ecological approaches to these questions. By determining the amount of variance in transposon abundance and distribution that is explained by ecological and evolutionary factors, respectively, it is possible empirically to assess the prospects for each of these explanatory frameworks. To illustrate how this methodology applies to a concrete example, we analyzed whole‐genome data for one set of distantly related mammals and another more closely related group of arthropods. Our expectation was that ecological factors are most informative for explaining differences among individual TE lineages, rather than TE families, and for explaining their distribution among closely related as opposed to distantly related host genomes. We found that, in these data sets, ecological factors do in fact explain most of the variation in TE abundance and distribution among TE lineages across less distantly related host organisms. Evolutionary factors were not significant at these levels. However, the explanatory roles of evolution and ecology become inverted at the level of TE families or among more distantly related genomes. Not only does this example demonstrate the utility of our distinction between ecological and evolutionary perspectives, it further suggests an appropriate explanatory domain for the burgeoning discipline of transposon ecology. The fact that ecological processes appear to be impacting TE lineages over relatively short time scales further raises the possibility that transposons might serve as useful model systems for testing more general hypotheses in ecology.     

The promise of cryo-EM to explore RNA structural dynamics

Conformational dynamics are essential to macromolecular function. This is certainly true of RNA, whose ability to undergo programmed conformational dynamics is essential to create and regulate complex biological processes. However, methods to easily and simultaneously interrogate both the structure and conformational dynamics of fully functional RNAs in isolation and in complex with proteins have not historically been available. Due to its ability to image and classify single particles, cryogenic electron microscopy (cryo-EM) has the potential to address this gap and may be particularly amenable to exploring structural dynamics within the three-dimensional folds of biologically active RNAs. We discuss the possibilities and current limitations of applying cryo-EM to simultaneously study RNA structure and conformational dynamics, and present one example that illustrates this (as of yet) not fully realized potential.