Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities

Synthetic transitions: towards a new synthesis

The evolution of life in our biosphere has been marked by several major innovations. Such major complexity shifts include the origin of cells, genetic codes or multicellularity to the emergence of non-genetic information, language or even consciousness. Understanding the nature and conditions for their rise and success is a major challenge for evolutionary biology. Along with data analysis, phylogenetic studies and dedicated experimental work, theoretical and computational studies are an essential part of this exploration. With the rise of synthetic biology, evolutionary robotics, artificial life and advanced simulations, novel perspectives to these problems have led to a rather interesting scenario, where not only the major transitions can be studied or even reproduced, but even new ones might be potentially identified. In both cases, transitions can be understood in terms of phase transitions, as defined in physics. Such mapping (if correct) would help in defining a general framework to establish a theory of major transitions, both natural and artificial. Here, we review some advances made at the crossroads between statistical physics, artificial life, synthetic biology and evolutionary robotics.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

A conceptual framework for invasion in microbial communities

There is a growing interest in controlling-promoting or avoiding-the invasion of microbial communities by new community members. Resource availability and community structure have been reported as determinants of invasion success. However, most invasion studies do not adhere to a coherent and consistent terminology nor always include rigorous interpretations of the processes behind invasion. Therefore, we suggest that a consistent set of definitions and a rigorous conceptual framework are needed. We define invasion in a microbial community as the establishment of an alien microbial type in a resident community and argue how simple criteria to define aliens, residents, and alien establishment can be applied for a wide variety of communities. In addition, we suggest an adoption of the community ecology framework advanced by Vellend (2010) to clarify potential determinants of invasion. This framework identifies four fundamental processes that control community dynamics: dispersal, selection, drift and diversification. While selection has received ample attention in microbial community invasion research, the three other processes are often overlooked. Here, we elaborate on the relevance of all four processes and conclude that invasion experiments should be designed to elucidate the role of dispersal, drift and diversification, in order to obtain a complete picture of invasion as a community process.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms.

The extent of functional redundancy changes as species' roles shift in different environments

Assessing the ecological impacts of environmental change requires knowledge of the relationship between biodiversity and ecosystem functioning. The exact nature of this relationship can differ considerably between ecosystems, with consequences for the efficacy of species diversity as a buffer against environmental change. Using a microbial model system, we show that the relationship can vary depending on environmental conditions. Shapes suggesting functional redundancy in one environment can change, suggesting functional differences in another environment. We find that this change is due to shifting species roles and interactions. Species that are functionally redundant in one environment may become pivotal in another. Thus, caution is advised in drawing conclusions about functional redundancy based on a single environmental situation. It also implies that species richness is important because it provides a pool of species with potentially relevant traits. These species may turn out to be essential performers or partners in new interspecific interactions after environmental change. Therefore, our results challenge the generality of functional redundancy.

Interspecies interactions are an integral determinant of microbial community dynamics

This study investigated the factors that determine the dynamics of bacterial communities in a complex system using multidisciplinary methods. Since natural and engineered microbial ecosystems are too complex to study, six types of synthetic microbial ecosystems (SMEs) were constructed under chemostat conditions with phenol as the sole carbon and energy source. Two to four phenol-degrading, phylogenetically and physiologically different bacterial strains were used in each SME. Phylogeny was based on the nucleotide sequence of 16S rRNA genes, while physiologic traits were based on kinetic and growth parameters on phenol. Two indices, J parameter and “interspecies interaction,” were compared to predict which strain would become dominant in an SME. The J parameter was calculated from kinetic and growth parameters. On the other hand, “interspecies interaction,” a new index proposed in this study, was evaluated by measuring the specific growth activity, which was determined on the basis of relative growth of a strain with or without the supernatant prepared from other bacterial cultures. Population densities of strains used in SMEs were enumerated by real-time quantitative PCR (qPCR) targeting the gene encoding the large subunit of phenol hydroxylase and were compared to predictions made from J parameter and interspecies interaction calculations. In 4 of 6 SEMs tested the final dominant strain shown by real-time qPCR analyses coincided with the strain predicted by both the J parameter and the interspecies interaction. However, in SMEII-2 and SMEII-3 the final dominant Variovorax strains coincided with prediction of the interspecies interaction but not the J parameter. These results demonstrate that the effects of interspecies interactions within microbial communities contribute to determining the dynamics of the microbial ecosystem.

Unraveling interactions in microbial communities - from co-cultures to microbiomes

Microorganisms do not exist in isolation in the environment. Instead, they form complex communities among themselves as well as with their hosts. Different forms of interactions not only shape the composition of these communities but also define how these communities are established and maintained. The kinds of interaction a bacterium can employ are largely encoded in its genome. This allows us to deploy a genomescale modeling approach to understand, and ultimately predict, the complex and intertwined relationships in which microorganisms engage. So far, most studies on microbial communities have been focused on synthetic co-cultures and simple communities. However, recent advances in molecular and computational biology now enable bottom up methods to be deployed for complex microbial communities from the environment to provide insight into the intricate and dynamic interactions in which microorganisms are engaged. These methods will be applicable for a wide range of microbial communities involved in industrial processes, as well as understanding, preserving and reconditioning natural microbial communities present in soil, water, and the human microbiome.

Deciphering microbial community robustness through synthetic ecology and molecular systems synecology

Microbial ecosystems exhibit specific robustness attributes arising from the assembly and interaction networks of diverse, heterogeneous communities challenged by fluctuating environmental conditions. Synthetic ecology provides new insights into key biodiversity-stability relationships and robustness determinants of host-associated or environmental microbiomes. Driven by the advances of meta-omics technologies and bioinformatics, community-centered approaches (defined as molecular systems synecology) combined with the development of dynamic and mechanistic mathematical models make it possible to decipher and predict the outcomes of microbial ecosystems under disturbances. Beyond discriminating the normal operating range and natural, intrinsic dynamics of microbial processes from systems-level responses to environmental forcing, predictive modeling is poised to be integrated within prescriptive analytical frameworks and thus provide guidance in decision-making and proactive microbial resource management.

Thermophilic and cellulolytic consortium isolated from composting plants improves anaerobic digestion of cellulosic biomass: Toward a microbial resource management approach

A cellulolytic consortium was isolated from a composting plant in order to boost the initial hydrolysis step encountered in anaerobic digestion. Improvement of the cellulose degradation, as well as biogas production, was observed for the cultures inoculated with the exogenous consortium. Metagenomics analyses pointed out a weak richness (related to the number of OTUs) of the exogenous consortium induced by the selective pressure (cellulose as sole carbon source) met during the initial isolation steps. Main microbial strains determined were strictly anaerobic and belong to the Clostridia class. During cellulose anaerobic degradation, pH drop induced a strong modification of the microbial population. Despite the fact that richness and evenness were very weak, the exogenous consortium was able to adapt and to maintain the cellulolytic degradation potential. This important result point out the fact that simplified microbial communities could be used in order to increase the robustness of mixed cultures involved in environmental biotechnology.

Mass spectrometric metabolomic imaging of biofilms on corroding steel surfaces using laser ablation and solvent capture by aspiration

Ambient laser ablation and solvent capture by aspiration (LASCA) mass spectrometric imaging was combined with metabolomics high-performance liquid chromatography (HPLC) mass spectrometry analysis and light profilometry to investigate the correlation between chemical composition of marine bacterial biofilms on surfaces of 1018 carbon steel and corrosion damage of steel underneath the biofilms. Pure cultures of Marinobacter sp. or a wild population of bacteria present in coastal seawater served as sources of biofilms. Profilometry data of biofilm-free surfaces demonstrated heterogeneous distributions of corrosion damage. LASCA data were correlated with areas on the coupons varying in the level of corrosion attack, to reveal differences in chemical composition within biofilm regions associated with corroding and corrosion-free zones. Putative identification of selected compounds was carried out based on HPLC results and subsequent database searches. This is the first report of successful ambient chemical and metabolomic imaging of marine biofilms on corroding metallic materials. The metabolic analysis of such biofilms is challenging due to the presence in the biofilm of large amounts of corrosion products. However, by using the LASCA imaging interface, images of more than 1000 ions (potential metabolites) are generated, revealing striking heterogeneities within the biofilm. In the two model systems studied here, it is found that some of the patterns observed in selected ion images closely correlate with the occurrence and extent of corrosion in the carbon steel substrate as revealed by profilometry, while others do not. This approach toward the study of microbially influenced corrosion (MIC) holds great promise for approaching a fundamental understanding of the mechanisms involved in MIC.

Towards a holistic understanding of the beneficial interactions across the Populus microbiome

Interactions between trees and microorganisms are tremendously complex and the multispecies networks resulting from these associations have consequences for plant growth and productivity. However, a more holistic view is needed to better understand trees as ecosystems and superorganisms, where many interacting species contribute to the overall stability of the system. While much progress has been made on microbial communities associated with individual tree niches and the molecular interactions between model symbiotic partners, there is still a lack of knowledge of the multi-component interactions necessary for holistic ecosystem-level understanding. We review recent studies in Populus to emphasize the importance of such holistic efforts across the leaf, stem and rooting zones, and discuss prospects for future research in these important ecosystems.

Anaerobic mineralization of 2,4,6-tribromophenol to CO2 by a synthetic microbial community comprising Clostridium, Dehalobacter, and Desulfatiglans

Anaerobic mineralization of 2,4,6-tribromophenol (2,4,6-TBP) was achieved by a synthetic anaerobe community comprising a highly enriched culture of Dehalobacter sp. phylotype FTH1 acting as a reductive debrominator; Clostridium sp. strain Ma13 acting as a hydrogen supplier via glucose fermentation; and a novel 4-chlorophenol-degrading anaerobe, Desulfatiglans parachlorophenolica strain DS. 2,4,6-TBP was debrominated to phenol by the combined action of Ma13 and FTH1, then mineralized into CO2 by sequential introduction of DS, confirmed using [ring-(14)C(U)] phenol. The optimum concentrations of glucose, SO4(2-), and inoculum densities were 0.5 or 2.5mM, 1.0 or 2.5mM, and the densities equivalent to 10(4)copiesmL(-1) of the 16S rRNA genes, respectively. This resulted in the complete mineralization of 23μM 2,4,6-TBP within 35days (0.58μmolL(-1)d(-1)). Thus, using a synthetic microbial community of isolates or highly enriched cultures would be an efficient, optimizable, low-cost strategy for anaerobic bioremediation of halogenated aromatics.

The effects of elevated CO2 concentration on competitive interaction between aceticlastic and syntrophic methanogenesis in a model microbial consortium

Investigation of microbial interspecies interactions is essential for elucidating the function and stability of microbial ecosystems. However, community-based analyses including molecular-fingerprinting methods have limitations for precise understanding of interspecies interactions. Construction of model microbial consortia consisting of defined mixed cultures of isolated microorganisms is an excellent method for research on interspecies interactions. In this study, a model microbial consortium consisting of microorganisms that convert acetate into methane directly (Methanosaeta thermophila) and syntrophically (Thermacetogenium phaeum and Methanothermobacter thermautotrophicus) was constructed and the effects of elevated CO2 concentrations on intermicrobial competition were investigated. Analyses on the community dynamics by quantitative RT-PCR and fluorescent in situ hybridization targeting their 16S rRNAs revealed that high concentrations of CO2 have suppressive effects on the syntrophic microorganisms, but not on the aceticlastic methanogen. The pathways were further characterized by determining the Gibbs free energy changes (ΔG) of the metabolic reactions conducted by each microorganism under different CO2 concentrations. The ΔG value of the acetate oxidation reaction (T. phaeum) under high CO2 conditions became significantly higher than -20 kJ per mol of acetate, which is the borderline level for sustaining microbial growth. These results suggest that high concentrations of CO2 undermine energy acquisition of T. phaeum, resulting in dominance of the aceticlastic methanogen. This study demonstrates that investigation on model microbial consortia is useful for untangling microbial interspecies interactions, including competition among microorganisms occupying the same trophic niche in complex microbial ecosystems.

Impact of interspecific interactions on antimicrobial activity among soil bacteria

Certain bacterial species produce antimicrobial compounds only in the presence of a competing species. However, little is known on the frequency of interaction-mediated induction of antibiotic compound production in natural communities of soil bacteria. Here we developed a high-throughput method to screen for the production of antimicrobial activity by monocultures and pair-wise combinations of 146 phylogenetically different bacteria isolated from similar soil habitats. Growth responses of two human pathogenic model organisms, Escherichia coli WA321 and Staphylococcus aureus 533R4, were used to monitor antimicrobial activity. From all isolates, 33% showed antimicrobial activity only in monoculture and 42% showed activity only when tested in interactions. More bacterial isolates were active against S. aureus than against E. coli. The frequency of interaction-mediated induction of antimicrobial activity was 6% (154 interactions out of 2798) indicating that only a limited set of species combinations showed such activity. The screening revealed also interaction-mediated suppression of antimicrobial activity for 22% of all combinations tested. Whereas all patterns of antimicrobial activity (non-induced production, induced production and suppression) were seen for various bacterial classes, interaction-mediated induction of antimicrobial activity was more frequent for combinations of Flavobacteria and alpha- Proteobacteria. The results of our study give a first indication on the frequency of interference competitive interactions in natural soil bacterial communities which may forms a basis for selection of bacterial groups that are promising for the discovery of novel, cryptic antibiotics.