Network relationships of bacteria in a stable mixed culture

Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two Escherichia coli mutants that are metabolically dependent (due to an inability to synthesize essential amino acids) but competitively grow on a shared substrate. The analysis of the E. coli binary consortium using our model not only showed how interactions between the two amino acid auxotrophic mutants are controlled by the dynamic shifts in limiting substrates but also enabled quantifying previously uncharacterizable complex aspects of microbial interactions, such as asymmetry in interactions. Our approach can be extended to other ecological systems to model their environment-dependent interspecies interactions from growth kinetics.IMPORTANCEModeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.

Concepts and consequences of the hyphosphere core microbiome for arbuscular mycorrhizal fungal fitness and function

Arbuscular mycorrhizal (AM) fungi-associated hyphosphere microbiomes can be considered as the second genome of the mycorrhizal phosphorus uptake pathway. Their composition can be thought of as a stably recurring component of a holobiont, defined by the hyphosphere core microbiome, which is thought to benefit AM fungal fitness. Here, we review evidence indicating the existence of the hyphosphere core microbiome, highlight its functions linked to those functions lacking in AM fungi, and further explore the mechanisms by which different core members ensure their stable coexistence. We conclude that deciphering and utilizing the hyphosphere core microbiome provides an entry point for understanding the complex interactions among plants, AM fungi, and bacteria.

Two-tiered mutualism improves survival and competitiveness of cross-feeding soil bacteria

Metabolic cross-feeding is a pervasive microbial interaction type that affects community stability and functioning and directs carbon and energy flows. The mechanisms that underlie these interactions and their association with metal/metalloid biogeochemistry, however, remain poorly understood. Here, we identified two soil bacteria, Bacillus sp. BP-3 and Delftia sp. DT-2, that engage in a two-tiered mutualism. Strain BP-3 has low utilization ability of pyruvic acid while strain DT-2 lacks hexokinase, lacks a phosphotransferase system, and is defective in glucose utilization. When strain BP-3 is grown in isolation with glucose, it releases pyruvic acid to the environment resulting in acidification and eventual self-killing. However, when strain BP-3 is grown together with strain DT-2, strain DT-2 utilizes the released pyruvic acid to meet its energy requirements, consequently rescuing strain BP-3 from pyruvic acid-induced growth inhibition. The two bacteria further enhance their collective competitiveness against other microbes by using arsenic as a weapon. Strain DT-2 reduces relatively non-toxic methylarsenate [MAs(V)] to highly toxic methylarsenite [MAs(III)], which kills or suppresses competitors, while strain BP-3 detoxifies MAs(III) by methylation to non-toxic dimethylarsenate [DMAs(V)]. These two arsenic transformations are enhanced when strains DT-2 and BP-3 are grown together. The two strains, along with their close relatives, widely co-occur in soils and their abundances increase with the soil arsenic concentration. Our results reveal that these bacterial types employ a two-tiered mutualism to ensure their collective metabolic activity and maintain their ecological competitive against other soil microbes. These findings shed light on the intricateness of bacterial interactions and their roles in ecosystem functioning.

Metabolomic insight into the synergistic mechanism of action of a bacterial consortium in plant growth promotion

It has been established that a consortium consisting of compatible plant growth promoting rhizobacterial strains outperforms their individual impacts on plant attributes. While the phenomenon of synergism is extensively reported, the mechanism that underpins it is yet to be elucidated. In the present study the impact of three plant growth promoting bacteria, Azotobacter chroococcum (A), Priestia megaterium (formerly Bacillus megaterium) (B), and Pseudomonas sp. SK3 (P) was studied as a consortium on the growth attributes of pigeonpea. In addition, microbe-microbe interactions were investigated through metabolomic profiling to understand the mechanism of synergism. Plant growth experiments revealed that bacterial consortium A + B + P showed a significant increase in plant attributes such as shoot length, root length, fresh weight, and dry weight as compared to monocultures and two-membered consortia. Metabolomic profiling through high resolution liquid chromatograph mass spectrometer revealed the presence of a few bioactive compounds in the consortium that might play a potential role in the enhancement of biometric parameters of the plant. Several compounds, such as antipyrine, 6,6-dimethoxy-2,5,5-trimethyl-2-hexene, N-methyltryptamine, 2,2-dimethyl-3,4-bis(4-methoxyphenyl)-2H-1-benzopyran-7-ol acetate, N6-hydroxy-l-lysine, and l-furosin, were detected in the metabolome of the consortium, which was unique among all the treatments. The study also detected a few metabolites involved in sphingolipid biosynthesis (ketosphinganine and sphinganine) known for cell signaling in the consortium. This unravels the possible mechanism of synergism between bacterial strains in a consortium. The metabolomic profile would be helpful to strategically develop unique and more effective consortia that are tailored to the soil type.

Community succession and straw degradation characteristics using a microbial decomposer at low temperature

This study explored changes in the microbial community structure during straw degradation by a microbial decomposer, M44. The microbial community succession at different degradation periods was analyzed using MiSeq high-throughput sequencing. The results showed that 14 days after inoculation, the filter paper enzyme and endoglucanase activities increased to 2.55 U·mL^-1 and 2.34 U·mL^-1. The xylanase, laccase, and lignin peroxidase activities rose to 9.86 U·mL^-1, 132.16 U·L^-1, and 85.43 U·L^-1 after 28 d, which was consistent with changes in the straw degradation rate. The degradation rates of straw, lignin, cellulose, and hemicellulose were 31.43%, 13.67%, 25.04%, and 21.69%, respectively, after 28 d of fermentation at 15°C. Proteobacteria, Firmicutes, and Bacteroidetes were the main bacterial species in samples at different degradation stages. The dominant genera included Pseudomonas, Delftia, and Paenibacillus during the initial stage (1 d, 7 d) and the mid-term stage (14 d). The key functional microbes during the late stage (21 d, 28 d) were Rhizobium, Chryseobacterium, Sphingobacterium, Brevundimonas, and Devosia. Changes in the bacterial consortium structure and straw degradation characteristics during different degradation periods were clarified to provide a theoretical basis for the rational utilization of microbial decomposer M44.

Characterizing the Microbial Consortium L1 Capable of Efficiently Degrading Chlorimuron-Ethyl via Metagenome Combining 16S rDNA Sequencing

Excessive application of the herbicide chlorimuron-ethyl (CE) severely harms subsequent crops and poses severe risks to environmental health. Therefore, methods for efficiently decreasing and eliminating CE residues are urgently needed. Microbial consortia show potential for bioremediation due to their strong metabolic complementarity and synthesis. In this study, a microbial consortium entitled L1 was enriched from soil contaminated with CE by a “top-down” synthetic biology strategy. The consortium could degrade 98.04% of 100 mg L−1 CE within 6 days. We characterized it from the samples at four time points during the degradation process and a sample without degradation activity via metagenome and 16S rDNA sequencing. The results revealed 39 genera in consortium L1, among which Methyloversatilis (34.31%), Starkeya (28.60%), and Pseudoxanthomonas (7.01%) showed relatively high abundances. Temporal succession and the loss of degradability did not alter the diversity and community composition of L1 but changed the community structure. Taxon-functional contribution analysis predicted that glutathione transferase [EC 2.5.1.18], urease [EC 3.5.1.5], and allophanate hydrolase [EC 3.5.1.54] are relevant for the degradation of CE and that Methyloversatilis, Pseudoxanthomonas, Methylopila, Hyphomicrobium, Stenotrophomonas, and Sphingomonas were the main degrading genera. The degradation pathway of CE by L1 may involve cleavage of the CE carbamide bridge to produce 2-amino-4-chloro-6-methoxypyrimidine and ethyl o-sulfonamide benzoate. The results of network analysis indicated close interactions, cross-feeding, and co-metabolic relationships between strains in the consortium, and most of the above six degrading genera were keystone taxa in the network. Additionally, the degradation of CE by L1 required not only “functional bacteria” with degradation capacity but also “auxiliary bacteria” without degradation capacity but that indirectly facilitate/inhibit the degradation process; however, the abundance of “auxiliary bacteria” should be controlled in an appropriate range. These findings improve the understanding of the synergistic effects of degrading bacterial consortia, which will provide insight for isolating degrading bacterial resources and constructing artificial efficient bacterial consortia. Furthermore, our results provide a new route for pollution control and biodegradation of sulfonylurea herbicides.

Bioaugmentation with methanogens cultured in a micro-aerobic microbial community for overloaded anaerobic digestion recovery

Anaerobic digestion (AD) is widely used for conversion of waste materials into biogas, but inhibition of methane production caused by overloading can be a major problem. The micro-aerobic microbial community MC1 was used to successfully culture methanogens, Methanosarcina acetivorans C2A and Methanosaeta thermophila NBRC 101360. The maximum 16S rRNA gene concentrations of Methanosarcina acetivorans C2A and Methanosaeta thermophila NBRC101360 were 1.06 × 10⁶ and 1.35 × 10³ copies/mL, respectively. The five key bacteria in MC1 were quantified to assess the effect of inoculation on the abundances of the bacteria in the mixed culture. The original MC1 total 16S rRNA gene concentration was 1.93 × 10⁸ copies/mL, and the total 16S rRNA gene concentration had increased to 4.79 × 10⁹ copies/mL on day 9 (p < 0.05). The proportions of the key strains in MC1+MST had changed by day 9. Cells were harvested and used to bioaugment and increase the pH values of the high- and medium-temperature anaerobic systems. After bioaugmentation, thermophilic AD recovered well. The cumulative amounts of gas produced were 44.78% and 28.28% higher in the MC1+MST and MC1 groups, respectively, than the sterilized control. The MC1+MST group gave better results than the chemical addition control group (CaCO₃). There was no clear effect of bioaugmentation in mesophilic AD. When compared with traditional pure culture of methanogens as inoculants, methanogen cultivation in MC1 was simple and there was no need to separate and purify the target strains. This simplified methanogenic bioaugmentation agent was useful to study the mechanism of bioaugmentation for the recovery from low pH inhibition, showing the potential for practical application.

Pre-culturing soil microbial inoculum in plant residues enhanced the resilience of tolerant bacteria and bioneutralization efficacy in alkaline bauxite residues

Bioneutralization of alkaline bauxite residues (BR) may be achieved through in situ organic acids produced from fermentative decomposition of carbohydrates-rich organic matters (e.g., plant residues), which are driven by organophilic and heterotrophic prokaryotes tolerant of extremely saline and alkaline conditions. The present study investigated if the resilience of tolerant prokaryotes in soil microbial inoculums could be improved by pre-culturing them in carbohydrate-rich plant residues, leading to enhanced bioneutralization efficacy in strongly alkaline BR. In a 2-week microcosm experiment with BR (pH ~ 10.5), it was found that the resilience of prokaryotic communities and their functional modules and bioneutralization efficacy were significantly boosted in BR admixed with plant residues (i.e., SM: sugarcane mulch, LH: Lucerne hay) pre-cultured with soil microbial inoculum. The results showed that 10-20% of the initially inoculated soil prokaryotic features were recovered in treatments with pre-cultured plant residues. Besides, the enriched diverse prokaryotes formed highly clustered networks in the amended BR. These modules actively drove C and N mineralization and sustained 0.8-2.0 units of pH reduction, despite the buffering effects of alkaline minerals in BR solid phase. In contrast, soil microbial inoculation cultured in the growth medium lost >99% of the original prokaryotic features in soil inoculums, resulting in merely 0.2-0.7 unit pH reduction in the treated BR. Therefore, pre-culturing soil inoculum in plant residues would be preferred as an integral system to treat BR for effective bioneutralization.

Biotechnological basis of microbial consortia for the removal of pesticides from the environment

The application of microbial strains as axenic cultures has frequently been employed in a diverse range of sectors. In the natural environment, microbes exist as multispecies and perform better than monocultures. Cell signaling and communication pathways play a key role in engineering microbial consortia, because in a consortium, the microorganisms communicate via diffusible signal molecules. Mixed microbial cultures have gained little attention due to the lack of proper knowledge about their interactions with each other. Some ideas have been proposed to deal with and study various microbes when they live together as a community, for biotechnological application purposes. In natural environments, microbes can possess unique metabolic features. Therefore, microbial consortia divide the metabolic burden among strains in the group and robustly perform pesticide degradation. Synthetic microbial consortia can perform the desired functions at naturally contaminated sites. Therefore, in this article, special attention is paid to the microbial consortia and their function in the natural environment. This review comprehensively discusses the recent applications of microbial consortia in pesticide degradation and environmental bioremediation. Moreover, the future directions of synthetic consortia have been explored. The review also explores the future perspectives and new platforms for these approaches, besides highlighting the practical understanding of the scientific information behind consortia.

Artificial consortium demonstrates emergent properties of enhanced cellulosic-sugar degradation and biofuel synthesis

Planktonic cultures, of a rationally designed consortium, demonstrated emergent properties that exceeded the sums of monoculture properties, including a >200% increase in cellobiose catabolism, a >100% increase in glycerol catabolism, a >800% increase in ethanol production, and a >120% increase in biomass productivity. The consortium was designed to have a primary and secondary-resource specialist that used crossfeeding with a positive feedback mechanism, division of labor, and nutrient and energy transfer via necromass catabolism. The primary resource specialist was Clostridium phytofermentans (a.k.a. Lachnoclostridium phytofermentans), a cellulolytic, obligate anaerobe. The secondary-resource specialist was Escherichia coli, a versatile, facultative anaerobe, which can ferment glycerol and byproducts of cellobiose catabolism. The consortium also demonstrated emergent properties of enhanced biomass accumulation when grown as biofilms, which created high cell density communities with gradients of species along the vertical axis. Consortium biofilms were robust to oxic perturbations with E. coli consuming O₂, creating an anoxic environment for C. phytofermentans. Anoxic/oxic cycling further enhanced biomass productivity of the biofilm consortium, increasing biomass accumulation ~250% over the sum of the monoculture biofilms. Consortium emergent properties were credited to several synergistic mechanisms. E. coli consumed inhibitory byproducts from cellobiose catabolism, driving higher C. phytofermentans growth and higher cellulolytic enzyme production, which in turn provided more substrate for E. coli. E. coli necromass enhanced C. phytofermentans growth while C. phytofermentans necromass aided E. coli growth via the release of peptides and amino acids, respectively. In aggregate, temporal cycling of necromass constituents increased flux of cellulose-derived resources through the consortium. The study establishes a consortia-based, bioprocessing strategy built on naturally occurring interactions for improved conversion of cellulose-derived sugars into bioproducts.

Skin Microbiome and its Interplay with the Environment

Advances in sequencing, bioinformatics and analytics now allow the structure, function and interrelations of whole microbial communities to be studied in greater detail. Collaborative efforts and multidisciplinary studies, crossing the boundary between environmental and medical microbiology, have allowed specific environmental, animal and human microbiomes to be characterized. One of the main challenges for microbial ecology is to link the phylogenetic diversity of host-associated microbes to their functional roles within the community. Much remains to be learned on the way microbes colonize the skin of different living organisms and the way the skin microbiome reacts to the surrounding environment (air, water, etc.). In this review, we discuss examples of recent studies that have used modern technology to provide insights into microbial communities in water and on skin, such as those in natural resources (thermal spring water), large mammals (humpback whales) and humans (the skin microbiome). The results of these studies demonstrate how a greater understanding of the structure and functioning of microbiota, together with their interactions with the environment, may facilitate the discovery of new probiotics or postbiotics, provide indicators for the quality of the environment, and show how changes in lifestyle and living environment, such as urbanization, can impact on the skin microbiome and skin health and disease in humans.

Prediction of Neighbor-Dependent Microbial Interactions From Limited Population Data

Modulation of interspecies interactions by the presence of neighbor species is a key ecological factor that governs dynamics and function of microbial communities, yet the development of theoretical frameworks explicit for understanding context-dependent interactions are still nascent. In a recent study, we proposed a novel rule-based inference method termed the Minimal Interspecies Interaction Adjustment (MIIA) that predicts the reorganization of interaction networks in response to the addition of new species such that the modulation in interaction coefficients caused by additional members is minimal. While the theoretical basis of MIIA was established through the previous work by assuming the full availability of species abundance data in axenic, binary, and complex communities, its extension to actual microbial ecology can be highly constrained in cases that species have not been cultured axenically (e.g., due to their inability to grow in the absence of specific partnerships) because binary interaction coefficients - basic parameters required for implementing the MIIA - are inestimable without axenic and binary population data. Thus, here we present an alternative formulation based on the following two central ideas. First, in the case where only data from axenic cultures are unavailable, we remove axenic populations from governing equations through appropriate scaling. This allows us to predict neighbor-dependent interactions in a relative sense (i.e., fractional change of interactions between with versus without neighbors). Second, in the case where both axenic and binary populations are missing, we parameterize binary interaction coefficients to determine their values through a sensitivity analysis. Through the case study of two microbial communities with distinct characteristics and complexity (i.e., a three-member community where all members can grow independently, and a four-member community that contains member species whose growth is dependent on other species), we demonstrated that despite data limitation, the proposed new formulation was able to successfully predict interspecies interactions that are consistent with experimentally derived results. Therefore, this technical advancement enhances our ability to predict context-dependent interspecies interactions in a broad range of microbial systems without being limited to specific growth conditions as a pre-requisite.

Synthetic microbial consortia for biosynthesis and biodegradation: promises and challenges

Functional differentiation and metabolite exchange enable microbial consortia to perform complex metabolic tasks and efficiently cycle the nutrients. Inspired by the cooperative relationships in environmental microbial consortia, synthetic microbial consortia have great promise for studying the microbial interactions in nature and more importantly for various engineering applications. However, challenges coexist with promises, and the potential of consortium-based technologies is far from being fully harnessed. Thorough understanding of the underlying molecular mechanisms of microbial interactions is greatly needed for the rational design and optimization of defined consortia. These knowledge gaps could be potentially filled with the assistance of the ongoing revolution in systems biology and synthetic biology tools. As current fundamental and technical obstacles down the road being removed, we would expect new avenues with synthetic microbial consortia playing important roles in biological and environmental engineering processes such as bioproduction of desired chemicals and fuels, as well as biodegradation of persistent contaminants.

Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that – in many cases – adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future.

Microbial coexistence through chemical-mediated interactions

Many microbial functions happen within communities of interacting species. Explaining how species with disparate growth rates can coexist is important for applications such as manipulating host-associated microbiota or engineering industrial communities. Here, we ask how microbes interacting through their chemical environment can achieve coexistence in a continuous growth setup (similar to an industrial bioreactor or gut microbiota) where external resources are being supplied. We formulate and experimentally constrain a model in which mediators of interactions (e.g. metabolites or waste-products) are explicitly incorporated. Our model highlights facilitation and self-restraint as interactions that contribute to coexistence, consistent with our intuition. When interactions are strong, we observe that coexistence is determined primarily by the topology of facilitation and inhibition influences not their strengths. Importantly, we show that consumption or degradation of chemical mediators moderates interaction strengths and promotes coexistence. Our results offer insights into how to build or restructure microbial communities of interest.

Improving Ethyl Acetate Production in Baijiu Manufacture by Wickerhamomyces anomalus and Saccharomyces cerevisiae Mixed Culture Fermentations

Ethyl acetate content has strong influence on the style and quality of Baijiu. Therefore, this study investigated the effect of Saccharomyces cerevisiae Y3401 on the production of ethyl acetate by Wickerhamomyces anomalus Y3604. Analysis of cell growth showed that Y3401 influences Y3604 by nutrient competition and inhibition by metabolites, while the effect of Y3604 on Y3401 was mainly competition for nutrients. Mixed fermentation with two yeasts was found to produce more ethyl acetate than a single fermentation. The highest yield of ethyl acetate was 2.99 g/L when the inoculation ratio of Y3401:Y3604 was 1:2. Synergistic fermentation of both yeasts improved ethyl acetate production and increased the content of other flavor compounds in liquid and simulated solid-state fermentation for Baijiu. Saccharomyces cerevisiae had a positive effect on ethyl acetate production in mixed culture and provides opportunities to alter the aroma and flavor perception of Baijiu.

Model Microbial Consortia as Tools for Understanding Complex Microbial Communities

A major biological challenge in the postgenomic era has been untangling the composition and functions of microbes that inhabit complex communities or microbiomes. Multi-omics and modern bioinformatics have provided the tools to assay molecules across different cellular and community scales; however, mechanistic knowledge over microbial interactions often remains elusive. This is due to the immense diversity and the essentially undiminished volume of not-yet-cultured microbes. Simplified model communities hold some promise in enabling researchers to manage complexity so that they can mechanistically understand the emergent properties of microbial community interactions. In this review, we surveyed several approaches that have effectively used tractable model consortia to elucidate the complex behavior of microbial communities. We go further to provide some perspectives on the limitations and new opportunities with these approaches and highlight where these efforts are likely to lead as advances are made in molecular ecology and systems biology.

Synthetic microbial ecology and the dynamic interplay between microbial genotypes

Assemblages of microbial genotypes growing together can display surprisingly complex and unexpected dynamics and result in community-level functions and behaviors that are not readily expected from analyzing each genotype in isolation. This complexity has, at least in part, inspired a discipline of synthetic microbial ecology. Synthetic microbial ecology focuses on designing, building and analyzing the dynamic behavior of ‘ecological circuits’ (i.e. a set of interacting microbial genotypes) and understanding how community-level properties emerge as a consequence of those interactions. In this review, we discuss typical objectives of synthetic microbial ecology and the main advantages and rationales of using synthetic microbial assemblages. We then summarize recent findings of current synthetic microbial ecology investigations. In particular, we focus on the causes and consequences of the interplay between different microbial genotypes and illustrate how simple interactions can create complex dynamics and promote unexpected community-level properties. We finally propose that distinguishing between active and passive interactions and accounting for the pervasiveness of competition can improve existing frameworks for designing and predicting the dynamics of microbial assemblages.

Characterization of cellulolytic microbial consortium enriched on Napier grass using metagenomic approaches

Energy grass is a promising substrate for production of biogas by anaerobic digestion. However, the conversion efficiency is limited by the enzymatically recalcitrant nature of cellulosic wastes. In this study, an active, structurally stable mesophilic lignocellulolytic degrading microbial consortium (Np-LMC) was constructed from forest compost soil microbiota by successive subcultivation on Napier grass under facultative anoxic conditions. According to tagged 16S rRNA gene amplicon sequencing, increasing abundance of facultative Proteobacteria was found in the middle of batch cycle which was then subsequently replaced by the cellulose degraders Firmicutes and Bacteroidetes along with decreasing CMCase, xylanase, and β-glucanase activity profiles in the supernatant after 5 days of incubation. Anaerobic/facultative bacteria Dysgonomonas and Sedimentibacter and aerobic bacteria Comamonas were the major genera found in Np-LMC. The consortium was active on degradation of the native and delignified grass. Direct shotgun sequencing of the consortium metagenome revealed relatively high abundance of genes encoding for various lignocellulose degrading enzymes in 23 glycosyl hydrolase (GH) families compared to previously reported cellulolytic microbial communities in mammalian digestive tracts. Enzymes attacking cellulose and hemicellulose were dominated by GH2, 3, 5, 9, 10, 26, 28 and 43 in addition to a variety of carbohydrate esterases (CE) and auxiliary activities (AA), reflecting adaptation of the enzyme systems to the native herbaceous substrate. The consortium identified here represents the microcosm specifically bred on energy grass, with potential for enhancing degradation of fibrous substrates in bioenergy industry.

Assembly of microbial communities in replicate nutrient-cycling model ecosystems follows divergent trajectories, leading to alternate stable states

We studied in detail the reproducibility of community development in replicate nutrient-cycling microbial microcosms that were set up identically and allowed to develop under the same environmental conditions. Multiple replicate closed microcosms were constructed using pond sediment and water, enriched with cellulose and sulphate, and allowed to develop over several months under constant environmental conditions, after which their microbial communities were characterized using 16S rRNA gene sequencing. Our results show that initially similar microbial communities can follow alternative - yet stable - trajectories, diverging in time in a system size-dependent manner. The divergence between replicate communities increased in time and decreased with larger system size. In particular, notable differences emerged in the heterotrophic degrader communities in our microcosms; one group of steady state communities was enriched with Firmicutes, while the other was enriched with Bacteroidetes. The communities dominated by these two phyla also contained distinct populations of sulphate-reducing bacteria. This biomodality in community composition appeared to arise during recovery from a low-diversity state that followed initial cellulose degradation and sulphate reduction.

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics.

Living together in biofilms: the microbial cell factory and its biotechnological implications

In nature, bacteria alternate between two modes of growth: a unicellular life phase, in which the cells are free-swimming (planktonic), and a multicellular life phase, in which the cells are sessile and live in a biofilm, that can be defined as surface-associated microbial heterogeneous structures comprising different populations of microorganisms surrounded by a self-produced matrix that allows their attachment to inert or organic surfaces. While a unicellular life phase allows for bacterial dispersion and the colonization of new environments, biofilms allow sessile cells to live in a coordinated, more permanent manner that favors their proliferation. In this alternating cycle, bacteria accomplish two physiological transitions via differential gene expression: (i) from planktonic cells to sessile cells within a biofilm, and (ii) from sessile to detached, newly planktonic cells. Many of the innate characteristics of biofilm bacteria are of biotechnological interest, such as the synthesis of valuable compounds (e.g., surfactants, ethanol) and the enhancement/processing of certain foods (e.g., table olives). Understanding the ecology of biofilm formation will allow the design of systems that will facilitate making products of interest and improve their yields.

Cellulose-Enriched Microbial Communities from Leaf-Cutter Ant (Atta colombica) Refuse Dumps Vary in Taxonomic Composition and Degradation Ability

Deconstruction of the cellulose in plant cell walls is critical for carbon flow through ecosystems and for the production of sustainable cellulosic biofuels. Our understanding of cellulose deconstruction is largely limited to the study of microbes in isolation, but in nature, this process is driven by microbes within complex communities. In Neotropical forests, microbes in leaf-cutter ant refuse dumps are important for carbon turnover. These dumps consist of decaying plant material and a diverse bacterial community, as shown here by electron microscopy. To study the portion of the community capable of cellulose degradation, we performed enrichments on cellulose using material from five Atta colombica refuse dumps. The ability of enriched communities to degrade cellulose varied significantly across refuse dumps. 16S rRNA gene amplicon sequencing of enriched samples identified that the community structure correlated with refuse dump and with degradation ability. Overall, samples were dominated by Bacteroidetes, Gammaproteobacteria, and Betaproteobacteria. Half of abundant operational taxonomic units (OTUs) across samples were classified within genera containing known cellulose degraders, including Acidovorax, the most abundant OTU detected across samples, which was positively correlated with cellulolytic ability. A representative Acidovorax strain was isolated, but did not grow on cellulose alone. Phenotypic and compositional analyses of enrichment cultures, such as those presented here, help link community composition with cellulolytic ability and provide insight into the complexity of community-based cellulose degradation.

Model-based media selection to minimize the cost of metabolic cooperation in microbial ecosystems

MOTIVATION

Simple forms of mutualism between microorganisms are widespread in nature. Nevertheless, the role played by the environmental nutrient composition in mediating cross-feeding in microbial ecosystems is still poorly understood.

RESULTS

Here, we use mixed-integer bilevel linear programming to investigate the cost of sharing metabolic resources in microbial communities. The algorithm infers an optimal combination of nutrients that can selectively sustain synergistic growth for a pair of species and guarantees minimum cost of cross-fed metabolites. To test model-based predictions, we selected a pair of Escherichia coli single gene knockouts auxotrophic, respectively, for arginine and leucine: ΔargB and ΔleuB and we experimentally verified that model-predicted medium composition significantly favors mutualism. Moreover, mass spectrometry profiling of exchanged metabolites confirmed the predicted cross-fed metabolites, supporting our constraint based modeling approach as a promising tool for engineering microbial consortia.

AVAILABILITY AND IMPLEMENTATION

The software is freely available as a matlab script in the Supplementary materials.

CONTACT

zampieri@imsb.biol.ethz.ch

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Flavor Profile of Chinese Liquor Is Altered by Interactions of Intrinsic and Extrinsic Microbes

The flavor profile of Chinese liquor is the result of the metabolic activity of its microbial community. Given the importance of the microbial interaction, a novel way to control the liquor's flavor is by regulating the composition of the community. In this study, we efficiently improved the liquor's flavor by perturbing the intrinsic microbial metabolism with extrinsic microbes. We first constructed a basic microbial group (intrinsic) containing Saccharomyces cerevisiae, Wickerhamomyces anomalus, and Issatchenkia orientalis and added special flavor producers (extrinsic), Saccharomyces uvarum and Saccharomyces servazzii, to this intrinsic group. Upon the addition of the extrinsic microbes, the maximum specific growth rates of S. cerevisiae and I. orientalis increased from 6.19 to 43.28/day and from 1.15 to 14.32/day, respectively, but that of W. anomalus changed from 1.00 to 0.96/day. In addition, most volatile compounds known to be produced by the extrinsic strains were not produced. However, more esters, alcohols, and acids were produced by S. cerevisiae and I. orientalis. Six compounds were significantly different by random forest analysis after perturbation. Among them, increases in ethyl hexanoate, isobutanol, and 3-methylbutyric acid were correlated with S. cerevisiae and I. orientalis, and a decrease in geranyl acetone was correlated with W. anomalus. Variations in ethyl acetate and 2-phenylethanol might be due to the varied activity of W. anomalus and S. cerevisiae. This work showed the effect of the interaction between the intrinsic and extrinsic microbes on liquor flavor, which would be beneficial for improving the quality of Chinese liquor.

Metabolic dependencies drive species co-occurrence in diverse microbial communities

Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture.

Co-culture systems and technologies: taking synthetic biology to the next level

Co-culture techniques find myriad applications in biology for studying natural or synthetic interactions between cell populations. Such techniques are of great importance in synthetic biology, as multi-species cell consortia and other natural or synthetic ecology systems are widely seen to hold enormous potential for foundational research as well as novel industrial, medical and environmental applications with many proof-of-principle studies in recent years. What is needed for co-cultures to fulfil their potential? Cell-cell interactions in co-cultures are strongly influenced by the extracellular environment, which is determined by the experimental set-up, which therefore needs to be given careful consideration. An overview of existing experimental and theoretical co-culture set-ups in synthetic biology and adjacent fields is given here, and challenges and opportunities involved in such experiments are discussed. Greater focus on foundational technology developments for co-cultures is needed for many synthetic biology systems to realize their potential in both applications and answering biological questions.

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.

Enhancing stress-resistance for efficient microbial biotransformations by synthetic biology

Chemical conversions mediated by microorganisms, otherwise known as microbial biotransformations, are playing an increasingly important role within the biotechnology industry. Unfortunately, the growth and production of microorganisms are often hampered by a number of stressful conditions emanating from environment fluctuations and/or metabolic imbalances such as high temperature, high salt condition, strongly acidic solution, and presence of toxic metabolites. Therefore, exploring methods to improve the stress tolerance of host organisms could significantly improve the biotransformation process. With the help of synthetic biology, it is now becoming feasible to implement strategies to improve the stress-resistance of the existing hosts. This review summarizes synthetic biology efforts to enhance the efficiency of biotransformations by improving the robustness of microbes. Particular attention will be given to strategies at the cellular and the microbial community levels.

Dynamic changes in the composite microbial system MC1 during and following its rapid degradation of lignocellulose

To monitor the dynamics of the composite microbial system MC1 during its degradation of lignocellulose and to improve our understanding of the microbial communities involved in this biomass conversion, MC1 was characterized at eight time points over an 18-day, thermophilic, aerobic, static cultivation. We found the microbial communities to be dynamic, rhythmic consortia capable of changing in response to lignocellulose degradation. The growth curve over 18 days was M-shaped. Based on the quantitative changes in five major components of MC1 (Clostridium straminisolvens CSK-1, Clostridium sp. FG4, Pseudoxanthomonas sp. M1-3, Brevibacillus sp. M1-5, and Bordetella sp. M1-6), reduction in rice straw weight, cellulase (CMCase) activity, xylanase activity, and changes in medium pH, we found that the process comprised two identifiable phases. Rapid degradation occurred from day 0 to day 9, while the post-rapid degradation phase included days 10 to 18. Day 3 and day 12 were two key time points in the rapid degradation phase and post-rapid degradation phase, respectively. Two anaerobes, C. straminisolvens CSK-1 and Clostridium sp. FG4, dominated the MC1 system from day 0 to day 18.

Synthetic microbial communities

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Microbial interactions and system function are two ways to study communities.

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Natural microbial communities are difficult to define and to study.

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Synthetic microbial communities are comprehensible systems of reduced complexity.

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Synthetic communities keep key features of natural ones and are amenable to modelling.

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Synthetic microbial communities are gaining importance in biotechnology.

While natural microbial communities are composed of a mix of microbes with often unknown functions, the construction of synthetic microbial communities allows for the generation of defined systems with reduced complexity. Used in a top-down approach, synthetic communities serve as model systems to ask questions about the performance and stability of microbial communities. In a second, bottom-up approach, synthetic microbial communities are used to study which conditions are necessary to generate interaction patterns like symbiosis or competition, and how higher order community structure can emerge from these. Besides their obvious value as model systems to understand the structure, function and evolution of microbial communities as complex dynamical systems, synthetic communities can also open up new avenues for biotechnological applications.

Synthetic microbial ecosystems for biotechnology

Most highly controlled and specific applications of microorganisms in biotechnology involve pure cultures. Maintaining single strain cultures is important for industry as contaminants can reduce productivity and lead to longer "down-times" during sterilisation. However, microbes working together provide distinct advantages over pure cultures. They can undertake more metabolically complex tasks, improve efficiency and even expand applications to open systems. By combining rapidly advancing technologies with ecological theory, the use of microbial ecosystems in biotechnology will inevitably increase. This review provides insight into the use of synthetic microbial communities in biotechnology by applying the engineering paradigm of measure, model, manipulate and manufacture, and illustrate the emerging wider potential of the synthetic ecology field. Systems to improve biofuel production using microalgae are also discussed.

A modular organization of the human intestinal mucosal microbiota and its association with inflammatory bowel disease

Abnormalities of the intestinal microbiota are implicated in the pathogenesis of Crohn's disease (CD) and ulcerative colitis (UC), two spectra of inflammatory bowel disease (IBD). However, the high complexity and low inter-individual overlap of intestinal microbial composition are formidable barriers to identifying microbial taxa representing this dysbiosis. These difficulties might be overcome by an ecologic analytic strategy to identify modules of interacting bacteria (rather than individual bacteria) as quantitative reproducible features of microbial composition in normal and IBD mucosa. We sequenced 16S ribosomal RNA genes from 179 endoscopic lavage samples from different intestinal regions in 64 subjects (32 controls, 16 CD and 16 UC patients in clinical remission). CD and UC patients showed a reduction in phylogenetic diversity and shifts in microbial composition, comparable to previous studies using conventional mucosal biopsies. Analysis of weighted co-occurrence network revealed 5 microbial modules. These modules were unprecedented, as they were detectable in all individuals, and their composition and abundance was recapitulated in an independent, biopsy-based mucosal dataset 2 modules were associated with healthy, CD, or UC disease states. Imputed metagenome analysis indicated that these modules displayed distinct metabolic functionality, specifically the enrichment of oxidative response and glycan metabolism pathways relevant to host-pathogen interaction in the disease-associated modules. The highly preserved microbial modules accurately classified IBD status of individual patients during disease quiescence, suggesting that microbial dysbiosis in IBD may be an underlying disorder independent of disease activity. Microbial modules thus provide an integrative view of microbial ecology relevant to IBD.

Challenges for complex microbial ecosystems: combination of experimental approaches with mathematical modeling

In the past couple of decades, molecular ecological techniques have been developed to elucidate microbial diversity and distribution in microbial ecosystems. Currently, modern techniques, represented by meta-omics and single cell observations, are revealing the incredible complexity of microbial ecosystems and the large degree of phenotypic variation. These studies propound that microbiological techniques are insufficient to untangle the complex microbial network. This minireview introduces the application of advanced mathematical approaches in combination with microbiological experiments to microbial ecological studies. These combinational approaches have successfully elucidated novel microbial behaviors that had not been recognized previously. Furthermore, the theoretical perspective also provides an understanding of the plasticity, robustness and stability of complex microbial ecosystems in nature.

Consortia-mediated bioprocessing of cellulose to ethanol with a symbiotic Clostridium phytofermentans/yeast co-culture

BACKGROUND

Lignocellulosic ethanol is a viable alternative to petroleum-based fuels with the added benefit of potentially lower greenhouse gas emissions. Consolidated bioprocessing (simultaneous enzyme production, hydrolysis and fermentation; CBP) is thought to be a low-cost processing scheme for lignocellulosic ethanol production. However, no single organism has been developed which is capable of high productivity, yield and titer ethanol production directly from lignocellulose. Consortia of cellulolytic and ethanologenic organisms could be an attractive alternate to the typical single organism approaches but implementation of consortia has a number of challenges (e.g., control, stability, productivity).

RESULTS

Ethanol is produced from α-cellulose using a consortium of C. phytofermentans and yeast that is maintained by controlled oxygen transport. Both Saccharomyces cerevisiae cdt-1 and Candida molischiana "protect" C. phytofermentans from introduced oxygen in return for soluble sugars released by C. phytofermentans hydrolysis. Only co-cultures were able to degrade filter paper when mono- and co-cultures were incubated at 30°C under semi-aerobic conditions. Using controlled oxygen delivery by diffusion through neoprene tubing at a calculated rate of approximately 8 μmol/L hour, we demonstrate establishment of the symbiotic relationship between C. phytofermentans and S. cerevisiae cdt-1 and maintenance of populations of 105 to 106 CFU/mL for 50 days. Comparable symbiotic population dynamics were observed in scaled up 500 mL bioreactors as those in 50 mL shake cultures. The conversion of α-cellulose to ethanol was shown to improve with additional cellulase indicating a limitation in hydrolysis rate. A co-culture of C. phytofermentans and S. cerevisiae cdt-1 with added endoglucanase produced approximately 22 g/L ethanol from 100 g/L α-cellulose compared to C. phytofermentans and S. cerevisiae cdt-1 mono-cultures which produced approximately 6 and 9 g/L, respectively.

CONCLUSION

This work represents a significant step toward developing consortia-based bioprocessing systems for lignocellulosic biofuels production which utilize scalable, environmentally-mediated symbiosis mechanisms to provide consortium stability.

A versatile and robust aerotolerant microbial community capable of cellulosic ethanol production

The use of microbial communities in the conversion of cellulosic materials to bio-ethanol has the potential to improve the economic competitiveness of this biofuel and subsequently lessen our dependency on fossil fuel-based energy sources. Interactions between functionally different microbial groups within a community can expand habitat range, including the creation of anaerobic microenvironments. Currently, research focussing on exploring the nature of the interactions occurring during cellulose degradation and ethanol production within mixed microbial communities has been limited. The aim of this study was to enrich and characterize a cellulolytic bacterial community, and determine if ethanol is a major soluble end-product. Cellulolytic activity by the community was observed in both non-reduced and pre-reduced media, with ethanol and acetate being major fermentation products. Similar results were obtained when sterile wastewater extract was provided as nutrient. Several community members showed high similarity to Clostridium species with overlapping metabolic capabilities, suggesting clostridial functional redundancy.

Interspecies interaction between Pseudomonas aeruginosa and other microorganisms

Microbes interact with each other in multicellular communities and this interaction enables certain microorganisms to survive in various environments. Pseudomonas aeruginosa is a highly adaptable bacterium that ubiquitously inhabits diverse environments including soil, marine habitats, plants and animals. Behind this adaptivity, P. aeruginosa has abilities not only to outcompete others but also to communicate with each other to develop a multispecies community. In this review, we focus on how P. aeruginosa interacts with other microorganisms. P. aeruginosa secretes antimicrobial chemicals to compete and signal molecules to cooperate with other organisms. In other cases, it directly conveys antimicrobial enzymes to other bacteria using the Type VI secretion system (T6SS) or membrane vesicles (MVs). Quorum sensing is a central regulatory system used to exert their ability including antimicrobial effects and cooperation with other microbes. At least three quorum sensing systems are found in P. aeruginosa, Las, Rhl and Pseudomonas quinolone signal (PQS) systems. These quorum-sensing systems control the synthesis of extracellular antimicrobial chemicals as well as interaction with other organisms via T6SS or MVs. In addition, we explain the potential of microbial interaction analysis using several micro devices, which would bring fresh sensitivity to the study of interspecies interaction between P. aeruginosa and other organisms.