Environments that induce synthetic microbial ecosystems

Interactions between microbial species are sometimes mediated by the exchange of small molecules, secreted by one species and metabolized by another. Both one-way (commensal) and two-way (mutualistic) interactions may contribute to complex networks of interdependencies. Understanding these interactions constitutes an open challenge in microbial ecology, with applications ranging from the human microbiome to environmental sustainability. In parallel to natural communities, it is possible to explore interactions in artificial microbial ecosystems, e.g. pairs of genetically engineered mutualistic strains. Here we computationally generate artificial microbial ecosystems without re-engineering the microbes themselves, but rather by predicting their growth on appropriately designed media. We use genome-scale stoichiometric models of metabolism to identify media that can sustain growth for a pair of species, but fail to do so for one or both individual species, thereby inducing putative symbiotic interactions. We first tested our approach on two previously studied mutualistic pairs, and on a pair of highly curated model organisms, showing that our algorithms successfully recapitulate known interactions, robustly predict new ones, and provide novel insight on exchanged molecules. We then applied our method to all possible pairs of seven microbial species, and found that it is always possible to identify putative media that induce commensalism or mutualism. Our analysis also suggests that symbiotic interactions may arise more readily through environmental fluctuations than genetic modifications. We envision that our approach will help generate microbe-microbe interaction maps useful for understanding microbial consortia dynamics and evolution, and for exploring the full potential of natural metabolic pathways for metabolic engineering applications.     

Observing the invisible through imaging mass spectrometry, a window into the metabolic exchange patterns of microbes

Many microbes can be cultured as single-species communities. Often, these colonies are controlled and maintained via the secretion of metabolites. Such metabolites have been an invaluable resource for the discovery of therapeutics (e.g. penicillin, taxol, rapamycin, epothilone). In this article, written for a special issue on imaging mass spectrometry, we show that MALDI-imaging mass spectrometry can be adapted to observe, in a spatial manner, the metabolic exchange patterns of a diverse array of microbes, including thermophilic and mesophilic fungi, cyanobacteria, marine and terrestrial actinobacteria, and pathogenic bacteria. Dependent on media conditions, on average and based on manual analysis, we observed 11.3 molecules associated with each microbial IMS experiment, which was split nearly 50:50 between secreted and colony-associated molecules. The spatial distributions of these metabolic exchange factors are related to the biological and ecological functions of the organisms. This work establishes that MALDI-based IMS can be used as a general tool to study a diverse array of microbes. Furthermore the article forwards the notion of the IMS platform as a window to discover previously unreported molecules by monitoring the metabolic exchange patterns of organisms when grown on agar substrates.     

Impact of genomics on microbial food safety

Genome sequences are now available for many of the microbes that cause food-borne diseases. The information contained in pathogen genome sequences, together with the development of themed and whole-genome DNA microarrays and improved proteomics techniques, might provide tools for the rapid detection and identification of such organisms, for assessing their biological diversity and for understanding their ability to respond to stress. The genomic information also provides insight into the metabolic capacity and versatility of microbes; for example, specific metabolic pathways might contribute to the growth and survival of pathogens in a range of niches, such as food-processing environments and the human host. New concepts are emerging about how pathogens function, both within foods and in interactions with the host. The future should bring the first practical benefits of genome sequencing to the field of microbial food safety, including strategies and tools for the identification and control of emerging pathogens.     

Microbial physiology: Problems and prospects

Physiology is a science of functions. The functions of microorganisms, as for every living being, are metabolism and energy provision; reproduction and death; and regulation of vital activity on the intracellular level and on the level of interactions between microbial cells and abiogenous factors, and on the level of microbe-microbial interactions and interactions of microorganisms with plants, animals, and man. According to metabolic and energetic potentials, microorganisms are subdivided into photo-and chemotrophs, litho-and organotrophs, auto-and heterotrophs; prokaryotic organisms assimilate molecular nitrogen. The noted functions are subjected to versatile regulation that is a basis for intra-and intercellular communications. Microbial responses to exposure to macroorganisms are the introduction or prevention of programmed cell death (PCD) in infected organisms, and a change to the inactive state (persistence). The induction of programmed cell death in cells affected by illness that can extend to sound cells and organisms, the induction of PCD in pathogens that penetrate into the macroorganism, the change of persisters into the active state, and suppression of density effects in microbial populations (quorum sensing) are important trends in microbial physiology and biotechnology of medical and prophylactic preparations.     

Organic waste conversion through anaerobic digestion: A critical insight into the metabolic pathways and microbial interactions

Anaerobic digestion is a promising method for energy recovery through conversion of organic waste to biogas and other industrial valuables. However, to tap the full potential of anaerobic digestion, deciphering the microbial metabolic pathway activities and their underlying bioenergetics is required. In addition, the behavior of organisms in consortia along with the analytical abilities to kinetically measure their metabolic interactions will allow rational optimization of the process. This review aims to explore the metabolic bottlenecks of the microbial communities adopting latest advances of profiling and ¹³C tracer-based analysis using state of the art analytical platforms (GC, GC-MS, LC-MS, NMR). The review summarizes the phases of anaerobic digestion, the role of microbial communities, key process parameters of significance, syntrophic microbial interactions and the bottlenecks that are critical for optimal bioenergetics and enhanced production of valuables. Considerations into the designing of efficient synthetic microbial communities as well as the latest advances in capturing their metabolic cross talk will be highlighted. The review further explores how the presence of additives and inhibiting factors affect the metabolic pathways. The critical insight into the reaction mechanism covered in this review may be helpful to optimize and upgrade the anaerobic digestion system.     

When Cultures Meet: The Landscape of “Social” Interactions between the Host and Its Indigenous Microbes

Animals exist as biodiverse composite organisms that include microbial residents, eukaryotic cells, and organs that collectively form a human being. Through an interdependent relationship and an inherent ability to transmit and reciprocate stimuli in a bidirectional way, a human body or the holobiont secures growth, health, and reproduction. As such, the survival of a holobiont is dependent on the maintenance of biological order including metabolic homeostasis by tight regulation of the communication between its eukaryotic and prokaryotic residents. In this review an overview and perspective are provided on the bidirectional communication between microbes and their host in mutually nurturing biochemical, biological, and social interconnected relationships between the components of the holobiont. An emphasis is placed on exemplifying microbiome‐mediated effects on host functions—aiming to integrate microbiome functionality to host physiology, be it health or disease. Nutrition, immunology, and sexual dimorphism have been traversed extensively to reflect on health and mind states, social interactions, and urbanization defects/effects. Finally, examples of molecular mechanisms potentially orchestrating these complex transkingdom interactions are provided.     

Reprint of Organic waste conversion through anaerobic digestion: A critical insight into the metabolic pathways and microbial interactions

Anaerobic digestion is a promising method for energy recovery through conversion of organic waste to biogas and other industrial valuables. However, to tap the full potential of anaerobic digestion, deciphering the microbial metabolic pathway activities and their underlying bioenergetics is required. In addition, the behavior of organisms in consortia along with the analytical abilities to kinetically measure their metabolic interactions will allow rational optimization of the process. This review aims to explore the metabolic bottlenecks of the microbial communities adopting latest advances of profiling and ¹³C tracer-based analysis using state of the art analytical platforms (GC, GC-MS, LC-MS, NMR). The review summarizes the phases of anaerobic digestion, the role of microbial communities, key process parameters of significance, syntrophic microbial interactions and the bottlenecks that are critical for optimal bioenergetics and enhanced production of valuables. Considerations into the designing of efficient synthetic microbial communities as well as the latest advances in capturing their metabolic cross talk will be highlighted. The review further explores how the presence of additives and inhibiting factors affect the metabolic pathways. The critical insight into the reaction mechanism covered in this review may be helpful to optimize and upgrade the anaerobic digestion system.     

A mini-review of microbial consortia: Their roles in aquatic production and biogeochemical cycling

Molecular oxygen (O₂) is a potent inhibitor of key microbial processes, including photosynthesis, N₂ fixation, denitrification, sulfate reduction, methanogenesis, iron, and metal reduction reactions. Prokaryote survival and proliferation in aquatic environments is often controlled by the ability to tolerate exposure to oxic conditions. Many prokaryotes do not have subcellular organelles for isolating O₂-producing from O₂-consuming processes and have developed consortial associations with other prokaryotes and eukaryotes that alleviate metabolic constraints of high O₂. Nutrient transformations often rely on appropriate cellular and microenvironmental, or microzonal, redox conditions. The spatial and temporal requirements for microenvironmental overlap among microbial groups involved in nutrient transformations necessitates close proximity and diffusional exchange with other biogeochemically distinct, yet complementary, microbial groups. Microbial consortia exist at different levels of community and metabolic complexity, as shown for detrital, microbial mat, biofilm, and planktonic microalgal-bacterial assemblages. To assess the macroscale impacts of consortial interactions, studies should focus on the range of relevant temporal (minutes to hours) and spatial (microns to centimeters) scales controlling microbial production, nutrient exchange, and cycling. In this review, we discuss the utility and application of techniques suitable for determining microscale consortial activity, production, community composition, and interactions in the context of larger scale aquatic ecosystem structure and function. Correspondence to: Hans W. Paerl.     

Proteogenomic approaches for the molecular characterization of natural microbial communities

At the present time we know little about how microbial communities function in their natural habitats. For example, how do microorganisms interact with each other and their physical and chemical surroundings and respond to environmental perturbations? We might begin to answer these questions if we could monitor the ways in which metabolic roles are partitioned amongst members as microbial communities assemble, determine how resources such as carbon, nitrogen, and energy are allocated into metabolic pathways, and understand the mechanisms by which organisms and communities respond to changes in their surroundings. Because many organisms cannot be cultivated, and given that the metabolisms of those growing in monoculture are likely to differ from those of organisms growing as part of consortia, it is vital to develop methods to study microbial communities in situ. Chemoautotrophic biofilms growing in mine tunnels hundreds of meters underground drive pyrite (FeS(2)) dissolution and acid and metal release, creating habitats that select for a small number of organism types. The geochemical and microbial simplicity of these systems, the significant biomass, and clearly defined biological-inorganic feedbacks make these ecosystem microcosms ideal for development of methods for the study of uncultivated microbial consortia. Our approach begins with the acquisition of genomic data from biofilms that are sampled over time and in different growth conditions. We have demonstrated that it is possible to assemble shotgun sequence data to reveal the gene complement of the dominant community members and to use these data to confidently identify a significant fraction of proteins from the dominant organisms by mass spectrometry (MS)-based proteomics. However, there are technical obstacles currently restricting this type of "proteogenomic" analysis. Composite genomic sequences assembled from environmental data from natural microbial communities do not capture the full range of genetic potential of the associated populations. Thus, it is necessary to develop bioinformatics approaches to generate relatively comprehensive gene inventories for each organism type. These inventories are critical for expression and functional analyses. In proteomic studies, for example, peptides that differ from those predicted from gene sequences can be measured, but they generally cannot be identified by database matching, even if the difference is only a single amino acid residue. Furthermore, many of the identified proteins have no known function. We propose that these challenges can be addressed by development of proteogenomic, biochemical, and geochemical methods that will be initially deployed in a simple, natural model ecosystem. The resulting approach should be broadly applicable and will enhance the utility and significance of genomic data from isolates and consortia for study of organisms in many habitats. Solutions draining pyrite-rich deposits are referred to as acid mine drainage (AMD). AMD is a very prevalent, international environmental problem associated with energy and metal resources. The biological-mineralogical interactions that define these systems can be harnessed for energy-efficient metal recovery and removal of sulfur from coal. The detailed understanding of microbial ecology and ecosystem dynamics resulting from the proposed work will provide a scientific foundation for dealing with the environmental challenges and technological opportunities, and yield new methods for analysis of more complex natural communities.     

Exit strategies of intracellular pathogens

The exit of intracellular pathogens from host cells is an important step in the infectious cycle, but is poorly understood. It has recently emerged that microbial exit is a process that can be directed by organisms from within the cell, and is not simply a consequence of the physical or metabolic burden that is imposed on the host cell. This Review summarizes our current knowledge on the diverse mechanisms that are used by intracellular pathogens to exit cells. An integrated understanding of the diversity that exists for microbial exit pathways represents a new horizon in the study of host-pathogen interactions.     

Adaptive Evolution of Synthetic Cooperating Communities Improves Growth Performance

Symbiotic interactions between organisms are important for human health and biotechnological applications. Microbial mutualism is a widespread phenomenon and is important in maintaining natural microbial communities. Although cooperative interactions are prevalent in nature, little is known about the processes that allow their initial establishment, govern population dynamics and affect evolutionary processes. To investigate cooperative interactions between bacteria, we constructed, characterized, and adaptively evolved a synthetic community comprised of leucine and lysine Escherichia coli auxotrophs. The co-culture can grow in glucose minimal medium only if the two auxotrophs exchange essential metabolites — lysine and leucine (or its precursors). Our experiments showed that a viable co-culture using these two auxotrophs could be established and adaptively evolved to increase growth rates (by ∼3 fold) and optical densities. While independently evolved co-cultures achieved similar improvements in growth, they took different evolutionary trajectories leading to different community compositions. Experiments with individual isolates from these evolved co-cultures showed that changes in both the leucine and lysine auxotrophs improved growth of the co-culture. Interestingly, while evolved isolates increased growth of co-cultures, they exhibited decreased growth in mono-culture (in the presence of leucine or lysine). A genome-scale metabolic model of the co-culture was also constructed and used to investigate the effects of amino acid (leucine or lysine) release and uptake rates on growth and composition of the co-culture. When the metabolic model was constrained by the estimated leucine and lysine release rates, the model predictions agreed well with experimental growth rates and composition measurements. While this study and others have focused on cooperative interactions amongst community members, the adaptive evolution of communities with other types of interactions (e.g., commensalism, ammensalism or parasitism) would also be of interest.     

Metabolic Proximity in the Order of Colonization of a Microbial Community

Microbial biofilms are often composed of multiple bacterial species that accumulate by adhering to a surface and to each other. Biofilms can be resistant to antibiotics and physical stresses, posing unresolved challenges in the fight against infectious diseases. It has been suggested that early colonizers of certain biofilms could cause local environmental changes, favoring the aggregation of subsequent organisms. Here we ask whether the enzyme content of different microbes in a well-characterized dental biofilm can be used to predict their order of colonization. We define a metabolic distance between different species, based on the overlap in their enzyme content. We next use this metric to quantify the average metabolic distance between neighboring organisms in the biofilm. We find that this distance is significantly smaller than the one observed for a random choice of prokaryotes, probably reflecting the environmental constraints on metabolic function of the community. More surprisingly, this metabolic metric is able to discriminate between observed and randomized orders of colonization of the biofilm, with the observed orders displaying smaller metabolic distance than randomized ones. By complementing these results with the analysis of individual vs. joint metabolic networks, we find that the tendency towards minimal metabolic distance may be counter-balanced by a propensity to pair organisms with maximal joint potential for synergistic interactions. The trade-off between these two tendencies may create a “sweet spot” of optimal inter-organism distance, with possible broad implications for our understanding of microbial community organization.     

Glycan profiling of gel forming mucus layer from the scleractinian symbiotic coral Oculina arbuscula

The gel forming mucus layer surrounding scleractinian corals play fundamental functions in the maintenance of a favorable microenvironment required for the survival of these organisms. In particular, it harbors a rich partially species-specific symbiotic community through yet poorly understood molecular interactions. However, removal or contamination of this community by exogenous bacteria is closely linked to the worldwide bleaching events that are presently devastating coral colonies. The present study investigates the structure of major high molecular weight glycoconjugates that are responsible for both rheological properties of mucus and sugar-protein interactions with microbial communities. We demonstrated that it is composed by two distinct types of sulfated macromolecules: mucin type glycoproteins densely substituted by short unusual O-linked glycans and repetitive polysaccharides.     

Inter-phylum HGT has shaped the metabolism of many mesophilic and anaerobic bacteria

Genome sequencing has revealed that horizontal gene transfer (HGT) is a major evolutionary process in bacteria. Although it is generally assumed that closely related organisms engage in genetic exchange more frequently than distantly related ones, the frequency of HGT among distantly related organisms and the effect of ecological relatedness on the frequency has not been rigorously assessed. Here, we devised a novel bioinformatic pipeline, which minimized the effect of over-representation of specific taxa in the available databases and other limitations of homology-based approaches by analyzing genomes in standardized triplets, to quantify gene exchange between bacterial genomes representing different phyla. Our analysis revealed the existence of networks of genetic exchange between organisms with overlapping ecological niches, with mesophilic anaerobic organisms showing the highest frequency of exchange and engaging in HGT twice as frequently as their aerobic counterparts. Examination of individual cases suggested that inter-phylum HGT is more pronounced than previously thought, affecting up to ∼16% of the total genes and ∼35% of the metabolic genes in some genomes (conservative estimation). In contrast, ribosomal and other universal protein-coding genes were subjected to HGT at least 150 times less frequently than genes encoding the most promiscuous metabolic functions (for example, various dehydrogenases and ABC transport systems), suggesting that the species tree based on the former genes may be reliable. These results indicated that the metabolic diversity of microbial communities within most habitats has been largely assembled from preexisting genetic diversity through HGT and that HGT accounts for the functional redundancy among phyla.     

Dynamic co‐culture metabolic models reveal the fermentation dynamics,metabolic capacities and interplays of cheese starter cultures

In this study, we have investigated the cheese starter culture as a microbial community through a question: can the metabolic behaviour of a co‐culture be explained by the characterized individual organism that constituted the co‐culture? To address this question, the dairy‐origin lactic acid bacteria Lactococcus lactis subsp. cremoris, Lactococcus lactis subsp. lactis, Streptococcus thermophilus and Leuconostoc mesenteroides, commonly used in cheese starter cultures, were grown in pure and four different co‐cultures. We used a dynamic metabolic modelling approach based on the integration of the genome‐scale metabolic networks of the involved organisms to simulate the co‐cultures. The strain‐specific kinetic parameters of dynamic models were estimated using the pure culture experiments and they were subsequently applied to co‐culture models. Biomass, carbon source, lactic acid and most of the amino acid concentration profiles simulated by the co‐culture models fit closely to the experimental results and the co‐culture models explained the mechanisms behind the dynamic microbial abundance. We then applied the co‐culture models to estimate further information on the co‐cultures that could not be obtained by the experimental method used. This includes estimation of the profile of various metabolites in the co‐culture medium such as flavour compounds produced and the individual organism level metabolic exchange flux profiles, which revealed the potential metabolic interactions between organisms in the co‐cultures.     

农业土壤微生物基因与群落多样性研究进展

介绍了群落基因组多样性、结构多样性与功能多样性相互关系的研究方法 ,重点论述了近年来农业土壤微生物群落遗传、结构与功能多样性的研究进展。同时总结了耕作措施和养分管理对农业土壤微生物群落多样性的影响 ,提出微生物序列分析、比较基因组学和微生物芯片技术与传统研究技术结合将有助于对微生物群落结构与功能和生物与环境因素对土壤微生物群落影响的深刻理解     

Genomic and mechanistic insights into the biodegradation of organic pollutants

Several new methodologies have enabled recent studies on the microbial biodegradation mechanisms of organic pollutants. Culture-independent techniques for analysis of the genetic and metabolic potential of natural and model microbial communities that degrade organic pollutants have identified new metabolic pathways and enzymes for aerobic and anaerobic degradation. Furthermore, structural studies of the enzymes involved have revealed the specificities and activities of key catabolic enzymes, such as dioxygenases. Genome sequencing of several biodegradation-relevant microorganisms have provided the first whole-genome insights into the genetic background of the metabolic capability and biodegradation versatility of these organisms. Systems biology approaches are still in their infancy, but are becoming increasingly helpful to unravel, predict and quantify metabolic abilities within particular organisms or microbial consortia.     

营养相互作用对传统发酵食品微生物群落构建的推动作用研究进展

传统发酵食品是由自然接种的多微生物组成的混菌体系,了解微生物群落自发式构建的机制是认识发酵机理和调控发酵的关键。尽管大量的测序数据已经对传统发酵食品中微生物群落的结构和功能有了较为清晰的认识,但是仍然不清楚微生物群落自发式构建的机制。本文提出微生物群落是分布式的代谢系统,微生物之间的营养相互作用推动了传统发酵食品微生物群落的自发式构建。本文主要阐述了营养相互作用的概念、发生的机理以及研究方法体系,整理了传统发酵食品中微生物之间营养相互作用的研究进展,并提出了未来的研究方向。通过营养相互作用推动的传统发酵食品微生物群落的自发式构建有助于定向控制发酵过程中的微生物种类、提高生产效率和改善发酵质量。     

Integrative top-down system metabolic modeling in experimental disease states via data-driven Bayesian methods

Multivariate metabolic profiles from biofluids such as urine and plasma are highly indicative of the biological fitness of complex organisms and can be captured analytically in order to derive top-down systems biology models. The application of currently available modeling approaches to human and animal metabolic pathway modeling is problematic because of multicompartmental cellular and tissue exchange of metabolites operating on many time scales. Hence, novel approaches are needed to analyze metabolic data obtained using minimally invasive sampling methods in order to reconstruct the patho-physiological modulations of metabolic interactions that are representative of whole system dynamics. Here, we show that spectroscopically derived metabolic data in experimental liver injury studies (induced by hydrazine and alpha-napthylisothiocyanate treatment) can be used to derive insightful probabilistic graphical models of metabolite dependencies, which we refer to as metabolic interactome maps. Using these, system level mechanistic information on homeostasis can be inferred, and the degree of reversibility of induced lesions can be related to variations in the metabolic network patterns. This approach has wider application in assessment of system level dysfunction in animal or human studies from noninvasive measurements.