Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism

The Exometabolome of Xylella fastidiosa in Contact with Paraburkholderia phytofirmans Supernatant Reveals Changes in Nicotinamide, Amino Acids, Biotin, and Plant Hormones

Microbial competition within plant tissues affects invading pathogens' fitness. Metabolomics is a great tool for studying their biochemical interactions by identifying accumulated metabolites. Xylella fastidiosa, a Gram-negative bacterium causing Pierce's disease (PD) in grapevines, secretes various virulence factors including cell wall-degrading enzymes, adhesion proteins, and quorum-sensing molecules. These factors, along with outer membrane vesicles, contribute to its pathogenicity. Previous studies demonstrated that co-inoculating X. fastidiosa with the Paraburkholderia phytofirmans strain PsJN suppressed PD symptoms. Here, we further investigated the interaction between the phytopathogen and the endophyte by analyzing the exometabolome of wild-type X. fastidiosa and a diffusible signaling factor (DSF) mutant lacking quorum sensing, cultivated with 20% P. phytofirmans spent media. Liquid chromatography-mass spectrometry (LC-MS) and the Method for Metabolite Annotation and Gene Integration (MAGI) were used to detect and map metabolites to genomes, revealing a total of 121 metabolites, of which 25 were further investigated. These metabolites potentially relate to host adaptation, virulence, and pathogenicity. Notably, this study presents the first comprehensive profile of X. fastidiosa in the presence of a P. phytofirmans spent media. The results highlight that P. phytofirmans and the absence of functional quorum sensing affect the ratios of glutamine to glutamate (Gln:Glu) in X. fastidiosa. Additionally, two compounds with plant metabolism and growth properties, 2-aminoisobutyric acid and gibberellic acid, were downregulated when X. fastidiosa interacted with P. phytofirmans. These findings suggest that P. phytofirmans-mediated disease suppression involves modulation of the exometabolome of X. fastidiosa, impacting plant immunity.

Construction of stable microbial consortia for effective biochemical synthesis

Microbial consortia can complete otherwise arduous tasks through the cooperation of multiple microbial species. This concept has been applied to produce commodity chemicals, natural products, and biofuels. However, metabolite incompatibility and growth competition can make the microbial composition unstable, and fluctuating microbial populations reduce the efficiency of chemical production. Thus, controlling the populations and regulating the complex interactions between different strains are challenges in constructing stable microbial consortia. This Review discusses advances in synthetic biology and metabolic engineering to control social interactions within microbial cocultures, including substrate separation, byproduct elimination, crossfeeding, and quorum-sensing circuit design. Additionally, this Review addresses interdisciplinary strategies to improve the stability of microbial consortia and provides design principles for microbial consortia to enhance chemical production.

Generation of Stable, Light-Driven Co-cultures of Cyanobacteria with Heterotrophic Microbes

Co-cultivation of an autotrophic species with one or more heterotrophic microbes is a strategy for photobiological production of high-value compounds and is relatively underexplored in comparison to cyanobacterial or microalgal monocultures. Long-term stability of such consortia is required for useful collaboration between the partners, and this property can be increased by encapsulation of phototrophic partners within a hydrogel. Encapsulated cyanobacteria have advantages relative to planktonic cultures that may be useful to explore the potential for artificial microbial communities for targeted biomolecule synthesis, such as increased control over population sizes and reduced liquid handling requirements. In this chapter, we describe a method for encapsulation of genetically modified cyanobacterial strain (Synechococcus elongatus PCC 7942, CscB+) into a sodium alginate matrix, and the utilization of these encapsulated cells to construct stable, artificial autotroph/heterotroph co-cultures. This method has applications for the study of phototroph-based synthetic microbial consortia, and multi-species photobiological production.

Biofilm Interaction Mapping and Analysis (BIMA) of Interspecific Interactions in Pseudomonas Co-culture Biofilms

Pseudomonas species are ubiquitous in nature and include numerous medically, agriculturally and technologically beneficial strains of which the interspecific interactions are of great interest for biotechnologies. Specifically, co-cultures containing Pseudomonas stutzeri have been used for bioremediation, biocontrol, aquaculture management and wastewater denitrification. Furthermore, the use of P. stutzeri biofilms, in combination with consortia-based approaches, may offer advantages for these processes. Understanding the interspecific interaction within biofilm co-cultures or consortia provides a means for improvement of current technologies. However, the investigation of biofilm-based consortia has been limited. We present an adaptable and scalable method for the analysis of macroscopic interactions (colony morphology, inhibition, and invasion) between colony-forming bacterial strains using an automated printing method followed by analysis of the genes and metabolites involved in the interactions. Using Biofilm Interaction Mapping and Analysis (BIMA), these interactions were investigated between P. stutzeri strain RCH2, a denitrifier isolated from chromium (VI) contaminated soil, and 13 other species of pseudomonas isolated from non-contaminated soil. One interaction partner, Pseudomonas fluorescens N1B4 was selected for mutant fitness profiling of a DNA-barcoded mutant library; with this approach four genes of importance were identified and the effects on interactions were evaluated with deletion mutants and mass spectrometry based metabolomics.

SubTap, a Versatile 3D Printed Platform for Eavesdropping on Extracellular Interactions

Communication within the microbiome occurs through an immense diversity of small molecules. Capturing these microbial interactions is a significant challenge due to the complexity of the exometabolome and its sensitivity to environmental stimuli. Traditional methods for acquiring exometabolomic data from interacting microorganisms are limited by their low throughput or lack of sampling depth. To address this challenge, we introduce subtapping (short for substrate tapping), a technique for tapping into extracellular metabolites that are being transferred through the growth substrate during coculture. High-throughput subtapping is made possible by a new coculturing platform, named SubTap, that we engineered to resemble a 96-well plate. The three-dimensional (3D) printed SubTap platform captures the exometabolome in an agar compartment that connects physically separated growth chambers, which permits cell growth without competition for space. We show how SubTap facilitates replicable and quick detection of exometabolites via direct infusion mass spectrometry analysis. Using bacterial isolates from the soil, we apply SubTap to characterize the effects of growth medium, growth duration, and mixed versus unmixed coculturing on the exometabolome. Finally, we demonstrate SubTap's versatility by interrogating microbial interactions in multicultures with up to four strains. IMPORTANCE Improvements in experimental techniques and instrumentation have led to the discovery that the microbiome plays an essential role in human and environmental health. Nevertheless, there remain major impediments to conducting large-scale interrogations of the microbiome in a high-throughput manner, particularly in the field of exometabolomics. Existing methods to coculture microorganisms and interrogate their interactions are labor-intensive and low throughput. This inspired us to develop a solution for coculturing that was (i) open source, (ii) inexpensive, (iii) scalable, (iv) customizable, and (v) compatible with existing mass spectrometry instrumentation. Here, we present SubTap-a 3D printed coculturing platform that permits tapping directly into the growth substrate between physically separated, but interconnected, growth compartments. SubTap allows multiculture (with up to four distinct growth compartments) in spatially mixed or unmixed configurations and enables repeatable results with mass spectrometry, as shown by our validation with known compounds and cultures of one to four organisms.

Drawing up a collaborative contract: Amino acid cross-feeding between interspecies bacterial pairs

Synthetic microbial communities have the potential to enable new platforms for bioproduction of biofuels and biopharmaceuticals. However, using engineered communities is often assumed to be difficult because of anticipated challenges in establishing and controlling community composition. Cross-feeding between microbial auxotrophs has the potential to facilitate coculture growth and stability through a mutualistic ecological interaction. We assessed cross-feeding between 13 Escherichia coli amino acid auxotrophs paired with a leucine auxotroph of Bacillus megaterium. We developed a minimal medium capable of supporting the growth of both bacteria and used the media to study coculture growth of the 13 interspecies pairs of auxotrophs in batch and continuous culture, as well as on semi-solid media. In batch culture, 8 of 13 pairs of auxotrophs were observed to grow in coculture. We developed a new metric to quantify the impact of cross-feeding on coculture growth. Six pairs also showed long-term stability in continuous culture, where coculture growth at different dilution rates highlighted differences in cross-feeding amongst the pairs. Finally, we found that cross-feeding-dependent growth on semi-solid media is highly stringent and enables identification of the most efficient pairs. These results demonstrate that cross-feeding is a viable approach for controlling community composition within diverse synthetic communities.

Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.

Pinpointing secondary metabolites that shape the composition and function of the plant microbiome

One of the major questions in contemporary plant science involves determining the functional mechanisms that plants use to shape their microbiome. Plants produce a plethora of chemically diverse secondary metabolites, many of which exert bioactive effects on microorganisms. Several recent publications have unequivocally shown that plant secondary metabolites affect microbiome composition and function. These studies have pinpointed that the microbiome can be influenced by a diverse set of molecules, including: coumarins, glucosinolates, benzoxazinoids, camalexin, and triterpenes. In this review, we summarize the role of secondary metabolites in shaping the plant microbiome, highlighting recent literature. A body of knowledge is now emerging that links specific plant metabolites with distinct microbial responses, mediated via defined biochemical mechanisms. There is significant potential to boost agricultural sustainability via the targeted enhancement of beneficial microbial traits, and here we argue that the newly discovered links between root chemistry and microbiome composition could provide a new set of tools for rationally manipulating the plant microbiome.

Microbial model communities: To understand complexity, harness the power of simplicity

Natural microbial communities are complex ecosystems with myriads of interactions. To deal with this complexity, we can apply lessons learned from the study of model organisms and try to find simpler systems that can shed light on the same questions. Here, microbial model communities are essential, as they can allow us to learn about the metabolic interactions, genetic mechanisms and ecological principles governing and structuring communities. A variety of microbial model communities of varying complexity have already been developed, representing different purposes, environments and phenomena. However, choosing a suitable model community for one's research question is no easy task. This review aims to be a guide in the selection process, which can help the researcher to select a sufficiently well-studied model community that also fulfills other relevant criteria. For example, a good model community should consist of species that are easy to grow, have been evaluated for community behaviors, provide simple readouts and - in some cases - be of relevance for natural ecosystems. Finally, there is a need to standardize growth conditions for microbial model communities and agree on definitions of community-specific phenomena and frameworks for community interactions. Such developments would be the key to harnessing the power of simplicity to start disentangling complex community interactions.

From Microbiome to Traits: Designing Synthetic Microbial Communities for Improved Crop Resiliency

Plants teem with microorganisms, whose tremendous diversity and role in plant-microbe interactions are being increasingly explored. Microbial communities create a functional bond with their hosts and express beneficial traits capable of enhancing plant performance. Therefore, a significant task of microbiome research has been identifying novel beneficial microbial traits that can contribute to crop productivity, particularly under adverse environmental conditions. However, although knowledge has exponentially accumulated in recent years, few novel methods regarding the process of designing inoculants for agriculture have been presented. A recently introduced approach is the use of synthetic microbial communities (SynComs), which involves applying concepts from both microbial ecology and genetics to design inoculants. Here, we discuss how to translate this rationale for delivering stable and effective inoculants for agriculture by tailoring SynComs with microorganisms possessing traits for robust colonization, prevalence throughout plant development and specific beneficial functions for plants. Computational methods, including machine learning and artificial intelligence, will leverage the approaches of screening and identifying beneficial microbes while improving the process of determining the best combination of microbes for a desired plant phenotype. We focus on recent advances that deepen our knowledge of plant-microbe interactions and critically discuss the prospect of using microbes to create SynComs capable of enhancing crop resiliency against stressful conditions.

Developing a Microbial Consortium for Enhanced Metabolite Production from Simulated Food Waste

Food waste disposal and transportation of commodity chemicals to the point-of-need are substantial challenges in military environments. Here, we propose addressing these challenges via the design of a microbial consortium for the fermentation of food waste to hydrogen. First, we simulated the exchange metabolic fluxes of monocultures and pairwise co-cultures using genome-scale metabolic models on a food waste proxy. We identified that one of the top hydrogen producing co-cultures comprised Clostridium beijerinckii NCIMB 8052 and Yokenella regensburgei ATCC 43003. A consortium of these two strains produced a similar amount of hydrogen gas and increased butyrate compared to the C. beijerinckii monoculture, when grown on an artificial garbage slurry. Increased butyrate production in the consortium can be attributed to cross-feeding of lactate produced by Y. regensburgei. Moreover, exogenous lactate promotes the growth of C. beijerinckii with or without a limited amount of glucose. Increasing the scale of the consortium fermentation proved challenging, as two distinct attempts to scale-up the enhanced butyrate production resulted in different metabolic profiles than observed in smaller scale fermentations. Though the genome-scale metabolic model simulations provided a useful starting point for the design of microbial consortia to generate value-added products from waste materials, further model refinements based on experimental results are required for more robust predictions.

Metabolomics activity screening for identifying metabolites that modulate phenotype. Nat Biotechnol. 2018;36:316-320. [PMID: 29621222 DOI: 10.1038/nbt.4101]

Metabolomics, in which small-molecule metabolites (the metabolome) are identified and quantified, is broadly acknowledged to be the omics discipline that is closest to the phenotype. Although appreciated for its role in biomarker discovery programs, metabolomics can also be used to identify metabolites that could alter a cell's or an organism's phenotype. Metabolomics activity screening (MAS) as described here integrates metabolomics data with metabolic pathways and systems biology information, including proteomics and transcriptomics data, to produce a set of endogenous metabolites that can be tested for functionality in altering phenotypes. A growing literature reports the use of metabolites to modulate diverse processes, such as stem cell differentiation, oligodendrocyte maturation, insulin signaling, T-cell survival and macrophage immune responses. This opens up the possibility of identifying and applying metabolites to affect phenotypes. Unlike genes or proteins, metabolites are often readily available, which means that MAS is broadly amenable to high-throughput screening of virtually any biological system.

Web of microbes (WoM): a curated microbial exometabolomics database for linking chemistry and microbes

Background

As microbiome research becomes increasingly prevalent in the fields of human health, agriculture and biotechnology, there exists a need for a resource to better link organisms and environmental chemistries. Exometabolomics experiments now provide assertions of the metabolites present within specific environments and how the production and depletion of metabolites is linked to specific microbes. This information could be broadly useful, from comparing metabolites across environments, to predicting competition and exchange of metabolites between microbes, and to designing stable microbial consortia. Here, we introduce Web of Microbes (WoM; freely available at: http://webofmicrobes.org), the first exometabolomics data repository and visualization tool.

Description

WoM provides manually curated, direct biochemical observations on the changes to metabolites in an environment after exposure to microorganisms. The web interface displays a number of key features: (1) the metabolites present in a control environment prior to inoculation or microbial activation, (2) heatmap-like displays showing metabolite increases or decreases resulting from microbial activities, (3) a metabolic web displaying the actions of multiple organisms on a specified metabolite pool, (4) metabolite interaction scores indicating an organism’s interaction level with its environment, potential for metabolite exchange with other organisms and potential for competition with other organisms, and (5) downloadable datasets for integration with other types of -omics datasets.

Conclusion

We anticipate that Web of Microbes will be a useful tool for the greater research community by making available manually curated exometabolomics results that can be used to improve genome annotations and aid in the interpretation and construction of microbial communities.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1256-y) contains supplementary material, which is available to authorized users.

Exometabolomic Analysis of Cross-Feeding Metabolites

Microbial consortia have the potential to perform complex, industrially important tasks. The design of microbial consortia requires knowledge of the substrate preferences and metabolic outputs of each member, to allow understanding of potential interactions such as competition and beneficial metabolic exchange. Here, we used exometabolite profiling to follow the resource processing by a microbial co-culture of two biotechnologically relevant microbes, the bacterial cellulose degrader Cellulomonas fimi, and the oleaginous yeast Yarrowia lipolytica. We characterized the substrate preferences of the two strains on compounds typically found in lignocellulose hydrolysates. This allowed prediction that specific sugars resulting from hemicellulose polysaccharide degradation by C. fimi may serve as a cross-feeding metabolites to Y. lipolytica in co-culture. We also showed that products of ionic liquid-treated switchgrass lignocellulose degradation by C. fimi were channeled to Y. lipolytica in a co-culture. Additionally, we observed metabolites, such as shikimic acid accumulating in the co-culture supernatants, suggesting the potential for producing interesting co-products. Insights gained from characterizing the exometabolite profiles of individual and co-cultures of the two strains can help to refine this interaction, and guide strategies for making this an industrially viable co-culture to produce valuable products from lignocellulose material.

Yeast Creates a Niche for Symbiotic Lactic Acid Bacteria through Nitrogen Overflow

Many microorganisms live in communities and depend on metabolites secreted by fellow community members for survival. Yet our knowledge of interspecies metabolic dependencies is limited to few communities with small number of exchanged metabolites, and even less is known about cellular regulation facilitating metabolic exchange. Here we show how yeast enables growth of lactic acid bacteria through endogenous, multi-component, cross-feeding in a readily established community. In nitrogen-rich environments, Saccharomyces cerevisiae adjusts its metabolism by secreting a pool of metabolites, especially amino acids, and thereby enables survival of Lactobacillus plantarum and Lactococcus lactis. Quantity of the available nitrogen sources and the status of nitrogen catabolite repression pathways jointly modulate this niche creation. We demonstrate how nitrogen overflow by yeast benefits L. plantarum in grape juice, and contributes to emergence of mutualism with L. lactis in a medium with lactose. Our results illustrate how metabolic decisions of an individual species can benefit others.

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Yeast overflows amino acids that enable survival of lactic acid bacteria (LAB)

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Overflow is in proportion to nitrogen excess and regulated via TORC1 pathway

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Phenotype supporting LAB growth is conserved across diverse yeast isolates

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Yeast-LAB mutualism readily emerges when lactose is the main C-source

Zymomonas mobilis as a model system for production of biofuels and biochemicals

Zymomonas mobilis is a natural ethanologen with many desirable industrial biocatalyst characteristics. In this review, we will discuss work to develop Z. mobilis as a model system for biofuel production from the perspectives of substrate utilization, development for industrial robustness, potential product spectrum, strain evaluation and fermentation strategies. This review also encompasses perspectives related to classical genetic tools and emerging technologies in this context.

Decoding molecular interactions in microbial communities

Microbial communities govern numerous fundamental processes on earth. Discovering and tracking molecular interactions among microbes is critical for understanding how single species and complex communities impact their associated host or natural environment. While recent technological developments in DNA sequencing and functional imaging have led to new and deeper levels of understanding, we are limited now by our inability to predict and interpret the intricate relationships and interspecies dependencies within these communities. In this review, we highlight the multifaceted approaches investigators have taken within their areas of research to decode interspecies molecular interactions that occur between microbes. Understanding these principles can give us greater insight into ecological interactions in natural environments and within synthetic consortia.