Demonstrating the suitability of genetic algorithms for driving microbial ecosystems in desirable directions

The functioning of natural microbial ecosystems is determined by biotic interactions, which are in turn influenced by abiotic environmental conditions. Direct experimental manipulation of such conditions can be used to purposefully drive ecosystems toward exhibiting desirable functions. When a set of environmental conditions can be manipulated to be present at a discrete number of levels, finding the right combination of conditions to obtain the optimal desired effect becomes a typical combinatorial optimisation problem. Genetic algorithms are a class of robust and flexible search and optimisation techniques from the field of computer science that may be very suitable for such a task. To verify this idea, datasets containing growth levels of the total microbial community of four different natural microbial ecosystems in response to all possible combinations of a set of five chemical supplements were obtained. Subsequently, the ability of a genetic algorithm to search this parameter space for combinations of supplements driving the microbial communities to high levels of growth was compared to that of a random search, a local search, and a hill-climbing algorithm, three intuitive alternative optimisation approaches. The results indicate that a genetic algorithm is very suitable for driving microbial ecosystems in desirable directions, which opens opportunities for both fundamental ecological research and industrial applications.     

Maximizing microbial degradation of perchlorate using a genetic algorithm: Media optimization

Microbial communities are under constant influence of physical and chemical components in ecosystems. Shifts in conditions such as pH, temperature or carbon source concentration can translate into shifts in overall ecosystem functioning. These conditions can be manipulated in a laboratory setup using evolutionary computation methods such as genetic algorithms (GAs). In work described here, a GA methodology was successfully applied to define sets of environmental conditions for microbial enrichments and pure cultures to achieve maximum rates of perchlorate degradation. Over the course of 11 generations of optimization using a GA, we saw a statistically significant 16.45 and 16.76-fold increases in average perchlorate degradation rates by Dechlorosoma sp. strain KJ and Dechloromonas sp. strain Miss R, respectively. For two bacterial consortia, Pl6 and Cw3, 5.79 and 5.75-fold increases in average perchlorate degradation were noted. Comparison of zero-order kinetic rate constants for environmental conditions in GA-determined first and last generations of all bacterial cultures additionally showed marked increases.     

Soil microbial diversity: Methodological strategy, spatial overview and functional interest

Since the development of industrialization, urbanization and agriculture, soils have been subjected to numerous variations in environmental conditions, which have resulted in modifications of the taxonomic diversity and functioning of the indigenous microbial communities. As a consequence, the functional significance of these losses/modifications of biodiversity, in terms of the capacity of ecosystems to maintain the functions and services on which humanity depends, is now of pivotal importance. In this context, one of the main challenges in soil microbial ecology is to better understand and predict the processes that drive soil microbial diversity and the link between diversity and ecosystem process. This review describes past, present and ongoing conceptual and methodological strategies employed to better assess and understand the distribution and evolution of soil microbial diversity with the aim of increasing our capacity to translate such diversity into soil biological functioning and, more widely, into ecosystem services.     

Effects of plant diversity,community composition and environmental parameters on productivity in montane European grasslands

In the past years, a number of studies have used experimental plant communities to test if biodiversity influences ecosystem functioning such as productivity. It has been argued, however, that the results achieved in experimental studies may have little predictive value for species loss in natural ecosystems. Studies in natural ecosystems have been equivocal, mainly because in natural ecosystems differences in diversity are often confounded with differences in land use history or abiotic parameters. In this study, we investigated the effect of plant diversity on ecosystem functioning in semi-natural grasslands. In an area of 10×20 km, we selected 78 sites and tested the effects of various measures of diversity and plant community composition on productivity. We separated the effects of plant diversity on ecosystem functioning from potentially confounding effects of community composition, management or environmental parameters, using multivariate statistical analyses. In the investigated grasslands, simple measures of biodiversity were insignificant predictors of productivity. However, plant community composition explained productivity very well (R²=0.31) and was a better predictor than environmental variables (soil and site characteristics) or management regime. Thus, complex measures such as community composition and structure are important drivers for ecosystem functions in semi-natural grasslands. Furthermore, our data show that it is difficult to extrapolate results from experimental studies to semi-natural ecosystems, although there is a need to investigate natural ecosystems to fully understand the relationship of biodiversity and ecosystem functioning.     

A trait-based framework for predicting when and where microbial adaptation to climate change will affect ecosystem functioning

As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.     

Biodiversity and ecosystem functioning in aquatic microbial systems: a new analysis of temporal variation and species richness-predictability relations

Studies of microbial communities from aquatic ecosystems provide important insights into relations between various aspects of ecosystem functioning and changes in biodiversity. Aquatic microbial systems provide a valuable counterpoint to studies of terrestrial systems, because patterns reflect consequences of interactions occurring over many generations of community development, and are unlikely to represent artifacts of the initial conditions established in experimental communities. In this paper we re-analyse our previously published data to separate the contributions of temporal and spatial variation to overall variation in ecosystem functioning. A new analysis based on re-sampling confirms a negative relationship between richness and the variability of one ecosystem process, carbon dioxide flux. The negative relationship reflects high variation among communities of low species richness, rather than high temporal variation within communities of low richness. We also review the various transformations and summary statistics proposed as alternate measures of variability in ecosystem functioning, to point out that different measures are often appropriate for different kinds of data. Finally, we conclude that arguments about the cosmopolitan distribution of microbes do not preclude the existence of important relations between microbial species richness and ecosystem functioning.     

Environmental conditions influence the plant functional diversity effect on potential denitrification

Global biodiversity loss has prompted research on the relationship between species diversity and ecosystem functioning. Few studies have examined how plant diversity impacts belowground processes; even fewer have examined how varying resource levels can influence the effect of plant diversity on microbial activity. In a field experiment in a restored wetland, we examined the role of plant trait diversity (or functional diversity, (FD)) and its interactions with natural levels of variability of soil properties, on a microbial process, denitrification potential (DNP). We demonstrated that FD significantly affected microbial DNP through its interactions with soil conditions; increasing FD led to increased DNP but mainly at higher levels of soil resources. Our results suggest that the effect of species diversity on ecosystem functioning may depend on environmental factors such as resource availability. Future biodiversity experiments should examine how natural levels of environmental variability impact the importance of biodiversity to ecosystem functioning.     

Do experiments exploring plant diversity–ecosystem functioning relationships inform how biodiversity loss impacts natural ecosystems?

An enormous recent research effort focused on how plant biodiversity (notably species richness) influences ecosystem functioning, usually through experiments in which diversity is varied through random draws of species from a species pool. Such experiments are increasingly used to predict how species losses influence ecosystem functioning in ‘real’ ecosystems. However, this assumes that comparisons of experimental communities with low vs high species richness are analogous to comparisons of natural communities from which species either have or have not been lost. I explore the validity of this assumption, and highlight difficulties in using such experiments to draw conclusions about the ecosystem consequences of biodiversity loss in natural systems. Notably, these experiments do not mimic what happens in real ecosystems either when local extinctions occur or when species losses are offset by gains of new species. Despite limitations, this single experimental approach for studying how biodiversity loss affects ecosystems has often been advocated and implemented at the expense of other approaches; this limits understanding of how natural ecosystems respond to biodiversity loss. I conclude that a broader spectrum of approaches, and more explicit consideration of how species losses and gains operate in concert to influence ecosystems, will help progress this field.     

The relationship between biodiversity and ecosystem functioning in food webs

Recent theoretical and experimental work provides clear evidence that biodiversity loss can have profound impacts on functioning of natural and managed ecosystems and the ability of ecosystems to deliver ecological services to human societies. Work on simplified ecosystems in which the diversity of a single trophic level is manipulated shows that diversity can enhance ecosystem processes such as primary productivity and nutrient retention. Theory also strongly suggests that biodiversity can act as biological insurance against potential disruptions caused by environmental changes. However, these studies generally concern a single trophic level, primary producers for the most part. Changes in biodiversity also affect ecosystem functioning through trophic interactions. Here we review, through the analysis of a simple ecosystem model, several key aspects inherent in multitrophic systems that may strongly affect the relationship between diversity and ecosystem processes. Our analysis shows that trophic interactions have a strong impact on the relationships between diversity and ecosystem functioning, whether the ecosystem property considered is total biomass or temporal variability of biomass at the various trophic levels. In both cases, food-web structure and trade-offs that affect interaction strength have major effects on these relationships. Multitrophic interactions are expected to make biodiversity–ecosystem functioning relationships more complex and non-linear, in contrast to the monotonic changes predicted for simplified systems with a single trophic level.     

Mesocosms of Aquatic Bacterial Communities from the Cuatro Cienegas Basin (Mexico): A Tool to Test Bacterial Community Response to Environmental Stress

Microbial communities are responsible for important ecosystem processes, and their activities are regulated by environmental factors such as temperature and solar ultraviolet radiation. Here we investigate changes in aquatic microbial community structure, diversity, and evenness in response to changes in temperature and UV radiation. For this purpose, 15 mesocosms were seeded with both microbial mat communities and plankton from natural pools within the Cuatro Cienegas Basin (Mexico). Clone libraries (16S rRNA) were obtained from water samples at the beginning and at the end of the experiment (40 days). Phylogenetic analysis indicated substantial changes in aquatic community composition and structure in response to temperature and UV radiation. Extreme treatments with elevation in temperature or UV radiation reduced diversity in relation to the Control treatments, causing a reduction in richness and increase in dominance, with a proliferation of a few resistant operational taxonomic units. Each phylum was affected differentially by the new conditions, which translates in a differential modification of ecosystem functioning. This suggests that the impact of environmental stress, at least at short term, will reshape the aquatic bacterial communities of this unique ecosystem. This work also demonstrates the possibility of designing manageable synthetic microbial community ecosystems where controlled environmental variables can be manipulated. Therefore, microbial model systems offer a complementary approach to field and laboratory studies of global research problems associated with the environment.     

Fungal diversity increases soil fungistasis and resistance to microbial invasion by a non resident species

Biodiversity decline is a major concern for ecosystem functioning. Recent research efforts have been mostly focused on terrestrial plants, while, despite their importance in both natural and artificial ecosystems, little is known about soil microbial communities. This work aims at investigating the effects of fungal species richness on soil invasion by non resident microbes. Synthetic fungal communities with a species diversity ranging from 1 to 8 were assembled in laboratory microcosms and used in three factorial experiments to assess the effect of diversity on soil fungistasis, microbial invasion of soil amended with plant litter and of plant rhizosphere. The capability of different microbes to colonize environments characterized by different resident microbial communities was measured. The number of microbial species in the microcosms positively affected soil fungistasis that was also induced more rapidly in presence of synthetic communities with more species. Moreover, the increase of resident fungal diversity dramatically reduced the invasibility of both soil and plant rhizosphere. We found lower variability of soil fungistasis and invasibility in microcosms with higher species richness of microbial communities. Our study pointed out the existence of negative relationships between fungal diversity and soil invasibility by non resident microbes. Therefore, the loss of microbial species may adversely affect ecosystem functionality under specific environmental conditions.     

Testing the functional significance of microbial composition in natural communities

Ecologists have long studied the relationship between biotic composition and ecosystem functioning in larger organisms; however, only recently has this relationship been investigated widely in microorganisms. Recent studies are reviewed within a framework of three experimental approaches that are often used to study larger organisms: environmental treatment, common garden, and reciprocal transplant experiments. Although the composition of microorganisms cannot be easily manipulated in the field, applying these approaches to intact microbial communities can begin to tease apart the effects of microbial composition from environmental parameters on ecosystem functioning. The challenges in applying these approaches to microorganisms are highlighted and it is discussed how the experimental approach and duration affects a study's interpretation. In general, long-term environmental treatment experiments identify correlative relationships between microbial composition and ecosystem functioning, whereas short-term common garden experiments demonstrate that microbial composition influences ecosystem functioning. Finally, reciprocal transplants simultaneously test for interactive effects of the environment and composition on functioning. The studies reviewed provide evidence that, at least in some cases, microbial composition influences ecosystem functioning. It is concluded that whole-community experiments offer a way to test whether information about microbial composition will help predict ecosystem responses to global change.     

Microbial redox cycling enhances ecosystem thermodynamic efficiency and productivity

Microbial life in low-energy ecosystems relies on individual energy conservation, optimizing energy use in response to interspecific competition and mutualistic interspecific syntrophy. Our study proposes a novel community-level strategy for increasing energy use efficiency. By utilizing an oxidation–reduction (redox) reaction network model that represents microbial redox metabolic interactions, we investigated multiple species-level competition and cooperation within the network. Our results suggest that microbial functional diversity allows for metabolic handoffs, which in turn leads to increased energy use efficiency. Furthermore, the mutualistic division of labour and the resulting complexity of redox pathways actively drive material cycling, further promoting energy exploitation. Our findings reveal the potential of self-organized ecological interactions to develop efficient energy utilization strategies, with important implications for microbial ecosystem functioning and the co-evolution of life and Earth.     

Genetic mosaics of ecosystem functioning across aspen-dominated landscapes

Genetic diversity is the foundation of all biodiversity, and the genetic variation within species is increasingly recognized as being important to ecosystem level processes. Recent research demonstrates that plant genotype influences above- and belowground communities as well as basic ecosystem functions. However, the extent to which plant genotypes create spatial mosaics of genetically mediated ecosystem processes in natural forests is uncertain. We use Populus tremuloides as a model system to demonstrate the importance of plant genotype on carbon and nitrogen cycling in natural systems. We identified 24 distinct P. tremuloides clones with multiple ramets across 25 km² in southern Wisconsin, United States, using microsatellite makers. We then sampled clone leaf chemistry and belowground nutrient content and microbial extracellular enzyme activity. Aspen-induced variation in belowground carbon and nitrogen content, and microbial activity, varied widely among clones. Variation in green leaf chemistry and belowground microbial activity were correlated with genetic distance among clones, such that more genetically distant clones created more divergent patches of ecosystem processes. These data suggest that aspen genotypes create spatial mosaics of genetically mediated ecosystem functioning across natural landscapes and can therefore have evolutionary consequences for co-occurring species.     

New directions in coral reef microbial ecology

Microbial processes largely control the health and resilience of coral reef ecosystems, and new technologies have led to an exciting wave of discovery regarding the mechanisms by which microbial communities support the functioning of these incredibly diverse and valuable systems. There are three questions at the forefront of discovery: What mechanisms underlie coral reef health and resilience? How do environmental and anthropogenic pressures affect ecosystem function? What is the ecology of microbial diseases of corals? The goal is to understand the functioning of coral reefs as integrated systems from microbes and molecules to regional and ocean‐basin scale ecosystems to enable accurate predictions of resilience and responses to perturbations such as climate change and eutrophication. This review outlines recent discoveries regarding the microbial ecology of different microenvironments within coral ecosystems, and highlights research directions that take advantage of new technologies to build a quantitative and mechanistic understanding of how coral health is connected through microbial processes to its surrounding environment. The time is ripe for natural resource managers and microbial ecologists to work together to create an integrated understanding of coral reef functioning. In the context of long‐term survival and conservation of reefs, the need for this work is immediate.     

Stochastic simulations of a synthetic bacteria-yeast ecosystem

ABSTRACT: BACKGROUND: The eld of synthetic biology has greatly evolved and numerous functions can now be implemented by articially engineered cells carrying the appropriate genetic information. However, in order for the cells to robustly perform complex or multiple tasks, co-operation between them may be necessary. Therefore, various synthetic biological systems whose functionality requires cell-cell communication are being designed. These systems, microbial consortia, are composed of engineered cells and exhibit a wide range of behaviors. These include yeast cells whose growth is dependent on one another, or bacteria that kill or rescue each other, synchronize, behave as predator-prey ecosystems or invade cancer cells. RESULTS: In this paper, we study a synthetic ecosystem comprising of bacteria and yeast that communicate with and benet from each other using small diffusible molecules. We explore the behavior of this heterogeneous microbial consortium, composed of Saccharomyces cerevisiae and Escherichia coli cells, using stochastic modeling. The stochastic model captures the relevant intra-cellular and inter-cellular interactions taking place in and between the eukaryotic and prokaryotic cells. Integration of well-characterized molecular regulatory elements into these two microbes allows for communication through quorum sensing. A gene controlling growth in yeast is induced by bacteria via chemical signals and vice versa. Interesting dynamics that are common in natural ecosystems, such as obligatory and facultative mutualism, extinction, commensalism and predator-prey like dynamics are observed. We investigate and report on the conditions under which the two species can successfully communicate and rescue each other. CONCLUSIONS: This study explores the various behaviors exhibited by the cohabitation of engineered yeast and bacterial cells. The way that the model is built allows for studying the dynamics of any system consisting of two species communicating with one another via chemical signals. Therefore, key information acquired by our model may potentially drive the experimental design of various synthetic heterogeneous ecosystems.     

The effects of pH change and NO(-) (3) pulse on microbial community structure and function: a vernal pool microcosm study

Forest vernal pools experience strong environmental fluctuations, such as changes in water chemistry, which are often correlated with changes in microbial community structure. However, very little is known about the extent to which these community changes influence ecosystem processes in vernal pools. This study utilized experimental vernal pool microcosms to simulate persistent pH alteration and a pulse input of nitrate (NO3 -), which are common perturbations to temperate vernal pool ecosystems. pH was manipulated at the onset and microbial respiration was monitored throughout the study (122?days). On day 29, NO3 - was added and denitrification rate was measured and bacterial, fungal, and denitrifier communities were profiled on day 30 and day 31. Microbial respiration and both bacterial and fungal community structure were altered by the pH treatment, demonstrating both structural and functional microbial responses. The NO3 - pulse increased denitrification rate without associated changes in community structure, suggesting that microbial communities responded functionally without structural shifts. The functioning of natural vernal pools, which experience both persistent and short-term environmental change, may thus depend on the type and duration of the change or disturbance.     

Optimization of biomass composition explains microbial growth-stoichiometry relationships

Integrating microbial physiology and biomass stoichiometry opens far-reaching possibilities for linking microbial dynamics to ecosystem processes. For example, the growth-rate hypothesis (GRH) predicts positive correlations among growth rate, RNA content, and biomass phosphorus (P) content. Such relationships have been used to infer patterns of microbial activity, resource availability, and nutrient recycling in ecosystems. However, for microorganisms it is unclear under which resource conditions the GRH applies. We developed a model to test whether the response of microbial biomass stoichiometry to variable resource stoichiometry can be explained by a trade-off among cellular components that maximizes growth. The results show mechanistically why the GRH is valid under P limitation but not under N limitation. We also show why variability of growth rate-biomass stoichiometry relationships is lower under P limitation than under N or C limitation. These theoretical results are supported by experimental data on macromolecular composition (RNA, DNA, and protein) and biomass stoichiometry from two different bacteria. In addition, compared to a model with strictly homeostatic biomass, the optimization mechanism we suggest results in increased microbial N and P mineralization during organic-matter decomposition. Therefore, this mechanism may also have important implications for our understanding of nutrient cycling in ecosystems.     

Microbial diversity, producer-decomposer interactions and ecosystem processes: a theoretical model

Interactions between the diversity of primary producers and that of decomposers--the two key functional groups that form the basis of all ecosystems--might have major consequences on the functioning of depauperate ecosystems. I present a simple ecosystem model in which primary producers (plants) and decomposers (microbes) are linked through material cycling. The model considers a diversity of plant organic compounds and a diversity of microbial species. Nutrient recycling efficiency from organic compounds to decomposers is then the key parameter that controls ecosystem processes (primary productivity, secondary productivity, producer biomass and decomposer biomass). The model predicts that microbial diversity has a positive effect on nutrient recycling efficiency and ecosystem processes through either greater intensity of microbial exploitation of organic compounds or functional niche complementarity, much like in plants. Microbial niche breadth and overlap should not affect ecosystem processes unless they increase the number of organic compounds that are decomposed. In contrast, the model predicts that plant organic compound diversity can only have a negative effect or, at best, no effect on ecosystem processes, at least in a constant environment. This creates a tension between the effects of plant diversity and microbial diversity on ecosystem functioning, which may explain some recent experimental results.