Inferring Metabolic Mechanisms of Interaction within a Defined Gut Microbiota

Community living causes changes in metabolic behavior and is permitted by specific growth conditions in two bacterial co-culture systems

Although bacteria exist in complex microbial communities in the environment, their features and behavior are most often studied in monoculture. While environmental enrichments or complex co-cultures with tens or hundreds of members might more accurately represent the natural communities of bacteria, we sought to create simple pairs of organisms to learn what conditions create successful co-culture and how bacteria change transcriptionally when a partner species is present. We grew two pairs of organisms in co-culture, Pseudomonas aeruginosa and Escherichia coli and Lacticaseibacillus rhamnosus and Bacteroides thetaiotaomicron. At first, both co-cultures failed, with one organism outcompeting the other. However, through manipulating media and environmental conditions, we created co-cultures with stable member ratios over many generations for each community. We then show that changes in the expression of metabolic genes are present in all studied species, with key catabolic and anabolic pathways often upregulated in the presence of another organism. These changes in gene expression fail to occur in conditions that will not lead to successful co-culture, suggesting they are essential for adapting to and surviving in the presence of others.

IMPORTANCE

In 1882, Robert Koch and Fanny Hesse developed the agar plate, which enabled microbiologists to separate individual microbial cells from each other and create monocultures of a single strain of bacteria. This powerful tool has been used in the almost 150 years since to develop a robust understanding of how bacterial cells are structured, how they manage and process their information, and how they respond to the environment to produce behaviors that match their circumstances. We were curious about how the behavior of bacteria, as measured by their gene expression, changes between well-studied monoculture conditions and co-culture. We found that only specific growth conditions permit co-culture and that bacteria change their metabolic strategies in the presence of a partner.

Correlation between the structures of natural polysaccharides and their properties in regulating gut microbiota: Current understanding and beyond

Natural polysaccharides have complex structural properties and a wide range of health-promoting effects. Accumulating evidence suggests that the effects are significantly mediated through fermentation by gut microbiota. In recent years, the relationship between the structures of natural polysaccharides and their properties in regulating gut microbiota has garnered significant research attention as researchers attempt to precisely understand the role of gut microbiota in the bioactivities of natural polysaccharides. Progress in this niche, however, remains limited. In this review, we first provide an overview of current research investigating this structure-property relationship. We then present a detailed correlation analysis between the structural characteristics of 159 purified natural polysaccharides and their effects on gut microbiota reported over the past two decades. The analysis revealed that diverse gut bacteria show specific correlations with the molecular weight, glycosidic linkages, and monosaccharide composition of natural polysaccharides. Multifaceted molecular mechanisms, including carbohydrate binding, enzymatic degradation, and cross-feeding, were proposed to be collectively involved in these correlations. Finally, we offer our perspective on future studies to further improve our understanding of the relationship between polysaccharide structure and gut microbiota regulation.

Unravelling metabolite-microbiome interactions in inflammatory bowel disease through AI and interaction-based modelling

Inflammatory Bowel Diseases (IBDs) are chronic inflammatory disorders of the gastrointestinal tract and colon affecting approximately 7 million individuals worldwide. The knowledge of specific pathology and aetiological mechanisms leading to IBD is limited, however a reduced immune system, antibiotic use and reserved diet may initiate symptoms. Dysbiosis of the gut microbiome, and consequently a varied composition of the metabolome, has been extensively linked to these risk factors and IBD. Metagenomic sequencing and liquid-chromatography mass spectrometry (LC-MS) of N = 220 fecal samples by Fransoza et al., provided abundance data on microbial genera and metabolites for use in this study. Identification of differentially abundant microbes and metabolites was performed using a Wilcoxon test, followed by feature selection of random forest (RF), gradient-boosting (XGBoost) and least absolute shrinkage operator (LASSO) models. The performance of these features was then validated using RF models on the Human Microbiome Project 2 (HMP2) dataset and a microbial community (MICOM) model was utilised to predict and interpret the interactions between key microbes and metabolites. The Flavronifractor genus and microbes of the families Lachnospiraceae and Oscillospiraceae were found differential by all models. Metabolic pathways commonly influenced by such microbes in IBD were CoA biosynthesis, bile acid metabolism and amino acid production and degradation. This study highlights distinct interactive microbiome and metabolome profiles within IBD and the highly potential pathways causing disease pathology. It therefore paves way for future investigation into new therapeutic targets and non-invasive diagnostic tools for IBD.

An in silico framework for the rational design of vaginal probiotic therapy

Bacterial vaginosis (BV) is a common condition characterized by a shift in vaginal microbiome composition that is linked to negative reproductive outcomes and increased susceptibility to sexually transmitted infections. Despite the commonality of BV, standard-of-care antibiotics provide limited control of recurrent BV episodes and development of new biotherapies is limited by the lack of controlled models needed to evaluate new dosing and treatment regimens. Here, we develop an in silico framework to evaluate selection criteria for potential probiotic strains, test adjunctive therapy with antibiotics, and alternative dosing strategies. This computational framework highlighted the importance of resident microbial species on the efficacy of hypothetical probiotic strains, identifying specific interaction parameters between resident non-optimal anaerobic bacteria (nAB) and Lactobacillus spp. with candidate probiotic strains as a necessary selection criterion. Model predictions were able to replicate results from a recent phase 2b clinical trial for the live biotherapeutic product, Lactin-V, demonstrating the relevance of the in silico platform. Results from the computational model support that the probiotic strain in Lactin-V requires adjunctive antibiotic therapy to be effective, and that increasing the dosing frequency of the probiotic could have a moderate impact on BV recurrence at 12 and 24 weeks. Altogether, this framework could provide evidence for the rational selection of probiotic strains and help optimize dosing frequency or adjunctive therapies.

Feruloylacetone and Its Analog Demethoxyferuloylacetone Mitigate Obesity-Related Muscle Atrophy and Insulin Resistance in Mice

Obesity-induced muscle alterations, such as inflammation, metabolic dysregulation, and myosteatosis, lead to a decline in muscle mass and function, often resulting in sarcopenic obesity. Currently, there are no definitive treatments for sarcopenic obesity beyond lifestyle changes and dietary supplementation. Feruloylacetone (FER), a thermal degradation product of curcumin, and its analog demethoxyferuloylacetone (DFER), derived from the thermal degradation of bisdemethoxycurcumin, have shown potential antiobesity effects in previous studies. This study investigates the impact of FER and DFER on obesity-related glucose intolerance and muscle atrophy. High-fat diet (HFD) feeding resulted in muscle mass reduction and increased intramuscular triglyceride accumulation, both of which were mitigated by FER and DFER supplementation. The supplements activated the PI3K/Akt/mTOR signaling pathway, enhanced muscle protein synthesis, and decreased markers of muscle protein degradation. Additionally, FER and DFER supplementation improved glucose homeostasis in HFD-fed mice. The supplements also promoted the formation of a gut microbial consortium comprising Blautia intestinalis, Dubosiella newyorkensis, Faecalicatena fissicatena, Waltera intestinalis, Clostridium viride, and Caproiciproducens galactitolivorans, which contributed to the reduction of obesity-induced chronic inflammation. These findings suggest, for the first time, that FER and DFER may prevent obesity-related complications, including muscle atrophy and insulin resistance, thereby warranting further research into their long-term efficacy and safety.

Phocaeicola vulgatus shapes the long-term growth dynamics and evolutionary adaptations of Clostridioides difficile

Clostridioides difficile can transiently or persistently colonize the human gut, posing a risk for infections. This colonization is influenced by complex molecular and ecological interactions with the human gut microbiota. By investigating C. difficile dynamics in human gut communities over hundreds of generations, we show patterns of stable coexistence, instability, or competitive exclusion. Lowering carbohydrate concentrations shifted a community containing C. difficile and the prevalent human gut symbiont Phocaeicola vulgatus from competitive exclusion to coexistence, facilitated by increased cross-feeding. In this environment, two key mutations in C. difficile altered its metabolic niche from proline to glucose utilization. These metabolic changes in C. difficile substantially impacted gut microbiota inter-species interactions and reduced disease severity in mice. In sum, interactions with P. vulgatus are crucial in shaping the long-term growth dynamics and evolutionary adaptations of C. difficile, offering key insights for developing anti-C. difficile strategies.

Metabolic interactions of Limosilactobacillus reuteri ZJ625 and Ligilactobacillus salivarius ZJ614 in co-culture: implications for multi-strain probiotics

AIMS

Limosilactobacillus reuteri ZJ625 and Ligilactobacillus salivarius ZJ614 are potential probiotic bacteria. The mechanisms of enhanced benefits by muti-strain probiotics are yet fully understood. We elucidated the influence of co-culturing on the metabolite profiles of Limosilactobacillus reuteri ZJ625 and Ligilactobacillus salivarius ZJ614 to decipher the impacts of co-culturing on metabolic interactions between the strains.

METHODS AND RESULTS

Limosilactobacillus reuteri ZJ625 and Ligilactobacillus salivarius ZJ614 were grown in single and co-cultures in defined media. Bacterial cell metabolites were extracted at the mid-stationary growth phase and analysed using two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS). Mass-spectral data were preprocessed and analysed using unsupervised and supervised methods based on the group allocations. A total of 1387 metabolites were identified, with 18.31% significant metabolites (P < 0.05) and 10.17% differential metabolites (P < 0.05, variable importance on projection > 1). The differential metabolites identified include arabinofuranose, methyl-galactoside, N-acetylglutamic acid, phosphoric acid, and decanoic acid. The metabolites impacted carbohydrate and amino-sugar metabolism.

CONCLUSION

Co-culturing of Limosilactobacillus reuteri ZJ625 and Ligilactobacillus salivarius ZJ614 influenced the metabolite profiles of the strains and impacted metabolic/biosynthetic pathways, indicating cell-to-cell interactions between the strains.

Metagenomic discovery of microbial eukaryotes in stool microbiomes

Host-associated microbiota form complex microbial communities that are increasingly associated with host behavior and disease. While these microbes include bacterial, archaeal, viral, and eukaryotic constituents, most studies have focused on bacteria due to their dominance in the human host and available tools for investigation. Accumulating evidence suggests microbial eukaryotes in the microbiome play pivotal roles in host health, but our understandings of these interactions are limited to a few readily identifiable taxa because of technical limitations in unbiased eukaryote exploration. Here, we combined cell sorting, optimized eukaryotic cell lysis, and shotgun sequencing to accelerate metagenomic discovery and analysis of host-associated microbial eukaryotes. Using synthetic communities with a 1% microbial eukaryote representation, the eukaryote-optimized cell lysis and DNA recovery method alone yielded a 38-fold increase in eukaryotic DNA. Automated sorting of eukaryotic cells from stool samples of healthy adults increased the number of microbial eukaryote reads in metagenomic pools by up to 28-fold compared to commercial kits. Read frequencies for identified fungi increased by 10,000× on average compared to the Human Microbiome Project and allowed for the identification of novel taxa, de novo assembly of contigs from previously unknown microbial eukaryotes, and gene prediction from recovered genomic segments. These advances pave the way for the unbiased inclusion of microbial eukaryotes in deciphering determinants of health and disease in the host-associated microbiome.IMPORTANCEMicrobial eukaryotes are common constituents of the human gut where they can contribute to local ecology and host health, but they are often overlooked in microbiome studies. The lack of attention is due to current technical limitations that are heavily biased or poorly recovered DNA from microbial eukaryotes. We developed a method to increase the representation of these eukaryotes in metagenomic sequencing of microbiome samples that allows to improve their detection compared to prior methods and allows for the identification of new species. Application of the technique to gut microbiome samples improved detection of fungi, protists, and helminths. New eukaryotic taxa and their encoded genes could be identified by sequencing a small number of samples. This approach can improve the inclusion of eukaryotes into microbiome research.

Human gut microbiota interactions shape the long-term growth dynamics and evolutionary adaptations of Clostridioides difficile

Clostridioides difficile can transiently or persistently colonize the human gut, posing a risk factor for infections. This colonization is influenced by complex molecular and ecological interactions with human gut microbiota. By investigating C. difficile dynamics in human gut communities over hundreds of generations, we show patterns of stable coexistence, instability, or competitive exclusion. Lowering carbohydrate concentration shifted a community containing C. difficile and the prevalent human gut symbiont Phocaeicola vulgatus from competitive exclusion to coexistence, facilitated by increased cross-feeding. In this environment, C. difficile adapted via single-point mutations in key metabolic genes, altering its metabolic niche from proline to glucose utilization. These metabolic changes substantially impacted inter-species interactions and reduced disease severity in the mammalian gut. In sum, human gut microbiota interactions are crucial in shaping the long-term growth dynamics and evolutionary adaptations of C. difficile, offering key insights for developing anti-C. difficile strategies.

Unraveling the Metabolic Behavior and Interspecific Interaction Pattern of Lactic Acid Bacteria within Chinese Rice Wine

The synthetic community of lactic acid bacteria (LAB) is commonly utilized in the food industry for manipulating product properties. However, the intermediate interactions and ecological stability resulting from metabolic differences among various LAB types remain poorly understood. We aimed to analyze the metabolic behavior of single and combined lactic acid bacteria in China rice wine based on microbial succession. Three-stage succession patterns with obligate heterofermentative LAB dominating prefermentation and homofermentative LAB prevailing in main fermentation were observed. Facultative heterofermentative LAB exhibited significant growth. Pairwise coculture interactions revealed 63.5% positive, 34.4% negative, and 2.1% neutral interactions, forming nontransitive and transitive competition modes. Nontransitive competitive combinations demonstrated stability over ∼200 generations through amino acid (mainly aspartic acid, glutamine, and serine) cross-feeding and lactic acid detoxification, which also showed potential for controlling biogenic amines and developing LAB starter cultures. Our findings offer insights into the mechanistic underpinnings of LAB interaction networks.

Deciphering metabolic crosstalk in context: lessons from inflammatory diseases

Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.

Emerging tools and best practices for studying gut microbial community metabolism

The human gut microbiome vastly extends the set of metabolic reactions catalysed by our own cells, with far-reaching consequences for host health and disease. However, our knowledge of gut microbial metabolism relies on a handful of model organisms, limiting our ability to interpret and predict the metabolism of complex microbial communities. In this Perspective, we discuss emerging tools for analysing and modelling the metabolism of gut microorganisms and for linking microorganisms, pathways and metabolites at the ecosystem level, highlighting promising best practices for researchers. Continued progress in this area will also require infrastructure development to facilitate cross-disciplinary synthesis of scientific findings. Collectively, these efforts can enable a broader and deeper understanding of the workings of the gut ecosystem and open new possibilities for microbiome manipulation and therapy.

Resource competition predicts assembly of gut bacterial communities in vitro

Microbial community dynamics arise through interspecies interactions, including resource competition, cross-feeding and pH modulation. The individual contributions of these mechanisms to community structure are challenging to untangle. Here we develop a framework to estimate multispecies niche overlaps by combining metabolomics data of individual species, growth measurements in spent media and mathematical models. We applied our framework to an in vitro model system comprising 15 human gut commensals in complex media and showed that a simple model of resource competition accounted for most pairwise interactions. Next, we built a coarse-grained consumer-resource model by grouping metabolomic features depleted by the same set of species and showed that this model predicted the composition of 2-member to 15-member communities with reasonable accuracy. Furthermore, we found that incorporation of cross-feeding and pH-mediated interactions improved model predictions of species coexistence. Our theoretical model and experimental framework can be applied to characterize interspecies interactions in bacterial communities in vitro.

High immigration rates critical for establishing emigration-driven diversity in microbial communities

Unraveling the mechanisms governing the diversity of ecological communities is a central goal in ecology. Although microbial dispersal constitutes an important ecological process, the effect of dispersal on microbial diversity is poorly understood. Here, we sought to fill this gap by combining a generalized Lotka-Volterra model with experimental investigations. Our model showed that emigration increases the diversity of the community when the immigration rate crosses a defined threshold, which we identified as Ineutral. We also found that at high immigration rates, emigration weakens the relative abundance of fast-growing species and thus enhances the mass effect and increases the diversity. We experimentally confirmed this finding using co-cultures of 20 bacterial strains isolated from the soil. Our model further showed that Ineutral decreases with the increase of species pool size, growth rate, and interspecies interaction. Our work deepens the understanding of the effects of dispersal on the diversity of natural communities.

Cultivating the uncultured: Harnessing the "sandwich agar plate" approach to isolate heme-dependent bacteria from marine sediment

In the classical microbial isolation technique, the isolation process inevitably destroys all microbial interactions and thus makes it difficult to culture the many microorganisms that rely on these interactions for survival. In this study, we designed a simple coculture technique named the "sandwich agar plate method," which maintains microbial interactions throughout the isolation and pure culture processes. The total yield of uncultured species in sandwich agar plates based on eight helper strains was almost 10-fold that of the control group. Many uncultured species displayed commensal lifestyles. Further study found that heme was the growth-promoting factor of some marine commensal bacteria. Subsequent genomic analysis revealed that heme auxotrophies were common in various biotopes and prevalent in many uncultured microbial taxa. Moreover, our study supported that the survival strategies of heme auxotrophy in different habitats varied considerably. These findings highlight that cocultivation based on the "sandwich agar plate method" could be developed and used to isolate more uncultured bacteria.

Richness and density jointly determine context dependence in bacterial interactions

Pairwise interactions are often used to predict features of complex microbial communities due to the challenge of measuring multi-species interactions in high dimensional contexts. This assumes that interactions are unaffected by community context. Here, we used synthetic bacterial communities to investigate that assumption by observing how interactions varied across contexts. Interactions were most often weakly negative and showed a phylogenetic signal among genera. Community richness and total density emerged as strong predictors of interaction strength and contributed to an attenuation of interactions as richness increased. Population level and per-capita measures of interactions both displayed such attenuation, suggesting factors beyond systematic changes in population size were involved; namely, changes to the interactions themselves. Nevertheless, pairwise interactions retained some explanatory power across contexts, provided those contexts were not substantially divergent in richness. These results suggest that understanding the emergent properties of microbial interactions can improve our ability to predict the features of microbial communities.

Lactobacillaceae differentially impact butyrate-producing gut microbiota to drive CNS autoimmunity

BACKGROUND

Short-chain fatty acids (SCFAs), produced by the gut microbiota, are thought to exert an anti-inflammatory effect on the host immune system. The levels of SCFAs and abundance of the microbiota that produce them are depleted in multiple sclerosis (MS), an autoimmune disease of the central nervous system (CNS). The mechanisms leading to this depletion are unknown. Using experimental autoimmune encephalomyelitis (EAE) as a model for MS, we have previously shown that gut microbiomes divergent in their abundance of specific commensal Lactobacillaceae, Limosilactobacillus reuteri (L. reuteri) and Ligilactobacillus murinus (L. murinus), differentially impact CNS autoimmunity. To determine the underlying mechanisms, we employed colonization by L. reuteri and L. murinus in disparate gut microbiome configurations in vivo and in vitro, profiling their impact on gut microbiome composition and metabolism, coupled with modulation of dietary fiber in the EAE model.

RESULTS

We show that stable colonization by L. reuteri, but not L. murinus, exacerbates EAE, in conjunction with a significant remodeling of gut microbiome composition, depleting SCFA-producing microbiota, including Lachnospiraceae, Prevotellaceae, and Bifidobacterium, with a net decrease in bacterial metabolic pathways involved in butyrate production. In a minimal microbiome culture model in vitro, L. reuteri directly inhibited SCFA-producer growth and depleted butyrate. Genomic analysis of L. reuteri isolates revealed an enrichment in bacteriocins with known antimicrobial activity against SCFA-producing microbiota. Functionally, provision of excess dietary fiber, as the prebiotic substrate for SCFA production, elevated SCFA levels and abrogated the ability of L. reuteri to exacerbate EAE.

CONCLUSTIONS

Our data highlight a potential mechanism for reduced SCFAs and their producers in MS through depletion by other members of the gut microbiome, demonstrating that interactions between microbiota can impact CNS autoimmunity in a diet-dependent manner. These data suggest that therapeutic restoration of SCFA levels in MS may require not only dietary intervention, but also modulation of the gut microbiome.

Control points for design of taxonomic composition in synthetic human gut communities

Microbial communities offer vast potential across numerous sectors but remain challenging to systematically control. We develop a two-stage approach to guide the taxonomic composition of synthetic microbiomes by precisely manipulating media components and initial species abundances. By combining high-throughput experiments and computational modeling, we demonstrate the ability to predict and design the diversity of a 10-member synthetic human gut community. We reveal that critical environmental factors governing monoculture growth can be leveraged to steer microbial communities to desired states. Furthermore, systematically varied initial abundances drive variation in community assembly and enable inference of pairwise inter-species interactions via a dynamic ecological model. These interactions are overall consistent with conditioned media experiments, demonstrating that specific perturbations to a high-richness community can provide rich information for building dynamic ecological models. This model is subsequently used to design low-richness communities that display low or high temporal taxonomic variability over an extended period. A record of this paper's transparent peer review process is included in the supplemental information.

Microbial interactions in theory and practice: when are measurements compatible with models?

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.

Systems-ecology designed bacterial consortium protects from severe Clostridioides difficile infection

Fecal Microbiota Transplant (FMT) is an emerging therapy that has had remarkable success in treatment and prevention of recurrent Clostridioides difficile infection (rCDI). FMT has recently been associated with adverse outcomes such as inadvertent transfer of antimicrobial resistance, necessitating development of more targeted bacteriotherapies. To address this challenge, we developed a novel systems biology pipeline to identify candidate probiotic strains that would be predicted to interrupt C. difficile pathogenesis. Utilizing metagenomic characterization of human FMT donor samples, we identified those metabolic pathways most associated with successful FMTs and reconstructed the metabolism of encoding species to simulate interactions with C. difficile . This analysis resulted in predictions of high levels of cross-feeding for amino acids in species most associated with FMT success. Guided by these in silico models, we assembled consortia of bacteria with increased amino acid cross-feeding which were then validated in vitro . We subsequently tested the consortia in a murine model of CDI, demonstrating total protection from severe CDI through decreased toxin levels, recovered gut microbiota, and increased intestinal eosinophils. These results support the novel framework that amino acid cross-feeding is likely a critical mechanism in the initial resolution of CDI by FMT. Importantly, we conclude that our predictive platform based on predicted and testable metabolic interactions between the microbiota and C. difficile led to a rationally designed biotherapeutic framework that may be extended to other enteric infections.

Nutritional and host environments determine community ecology and keystone species in a synthetic gut bacterial community

A challenging task to understand health and disease-related microbiome signatures is to move beyond descriptive community-level profiling towards disentangling microbial interaction networks. Using a synthetic gut bacterial community, we aimed to study the role of individual members in community assembly, identify putative keystone species and test their influence across different environments. Single-species dropout experiments reveal that bacterial strain relationships strongly vary not only in different regions of the murine gut, but also across several standard culture media. Mechanisms involved in environment-dependent keystone functions in vitro include exclusive access to polysaccharides as well as bacteriocin production. Further, Bacteroides caecimuris and Blautia coccoides are found to play keystone roles in gnotobiotic mice by impacting community composition, the metabolic landscape and inflammatory responses. In summary, the presented study highlights the strong interdependency between bacterial community ecology and the biotic and abiotic environment. These results question the concept of universally valid keystone species in the gastrointestinal ecosystem and underline the context-dependency of both, keystone functions and bacterial interaction networks.

Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe Eggerthella lenta

Human gut bacteria perform diverse metabolic functions with consequences for host health. The prevalent and disease-linked Actinobacterium Eggerthella lenta performs several unusual chemical transformations, but it does not metabolize sugars and its core growth strategy remains unclear. To obtain a comprehensive view of the metabolic network of E. lenta, we generated several complementary resources: defined culture media, metabolomics profiles of strain isolates, and a curated genome-scale metabolic reconstruction. Stable isotope-resolved metabolomics revealed that E. lenta uses acetate as a key carbon source while catabolizing arginine to generate ATP, traits which could be recapitulated in silico by our updated metabolic model. We compared these in vitro findings with metabolite shifts observed in E. lenta-colonized gnotobiotic mice, identifying shared signatures across environments and highlighting catabolism of the host signaling metabolite agmatine as an alternative energy pathway. Together, our results elucidate a distinctive metabolic niche filled by E. lenta in the gut ecosystem. Our culture media formulations, atlas of metabolomics data, and genome-scale metabolic reconstructions form a freely available collection of resources to support further study of the biology of this prevalent gut bacterium.

Cross-feeding in the gut microbiome: Ecology and mechanisms

Microbial communities are shaped by positive and negative interactions ranging from competition to mutualism. In the context of the mammalian gut and its microbial inhabitants, the integrated output of the community has important impacts on host health. Cross-feeding, the sharing of metabolites between different microbes, has emergent roles in establishing communities of gut commensals that are stable, resistant to invasion, and resilient to external perturbation. In this review, we first explore the ecological and evolutionary implications of cross-feeding as a cooperative interaction. We then survey mechanisms of cross-feeding across trophic levels, from primary fermenters to H2 consumers that scavenge the final metabolic outputs of the trophic network. We extend this analysis to also include amino acid, vitamin, and cofactor cross-feeding. Throughout, we highlight evidence for the impact of these interactions on each species' fitness as well as host health. Understanding cross-feeding illuminates an important aspect of microbe-microbe and host-microbe interactions that establishes and shapes our gut communities.

New perspectives into the vaginal microbiome with systems biology

The vaginal microbiome (VMB) is critical to female reproductive health; however, the mechanisms associated with optimal and non-optimal states remain poorly understood due to the complex community structure and dynamic nature. Quantitative systems biology techniques applied to the VMB have improved understanding of community composition and function using primarily statistical methods. In contrast, fewer mechanistic models that use a priori knowledge of VMB features to develop predictive models have been implemented despite their use for microbiomes at other sites, including the gastrointestinal tract. Here, we explore systems biology approaches that have been applied in the VMB, highlighting successful techniques and discussing new directions that hold promise for improving understanding of health and disease.

Multi-dimensional experimental and computational exploration of metabolism pinpoints complex probiotic interactions

Multi-strain probiotics are widely regarded as effective products for improving gut microbiota stability and host health, providing advantages over single-strain probiotics. However, in general, it is unclear to what extent different strains would cooperate or compete for resources, and how the establishment of a common biofilm microenvironment could influence their interactions. In this work, we develop an integrative experimental and computational approach to comprehensively assess the metabolic functionality and interactions of probiotics across growth conditions. Our approach combines co-culture assays with genome-scale modelling of metabolism and multivariate data analysis, thus exploiting complementary data- and knowledge-driven systems biology techniques. To show the advantages of the proposed approach, we apply it to the study of the interactions between two widely used probiotic strains of Lactobacillus reuteri and Saccharomyces boulardii, characterising their production potential for compounds that can be beneficial to human health. Our results show that these strains can establish a mixed cooperative-antagonistic interaction best explained by competition for shared resources, with an increased individual exchange but an often decreased net production of amino acids and short-chain fatty acids. Overall, our work provides a strategy that can be used to explore microbial metabolic fingerprints of biotechnological interest, capable of capturing multifaceted equilibria even in simple microbial consortia.

Host metabolome and faecal microbiome shows potential interactions impacted by age and weaning times in calves

BACKGROUND

Calves undergo nutritional, metabolic, and behavioural changes from birth to the entire weaning period. An appropriate selection of weaning age is essential to reduce the negative effects caused by weaning-related dietary transitions. This study monitored the faecal microbiome and plasma metabolome of 59 female Holstein calves during different developmental stages and weaning times (early vs. late) and identified the potential associations of the measured parameters over an experimental period of 140 days.

RESULTS

A progressive development of the microbiome and metabolome was observed with significant differences according to the weaning groups (weaned at 7 or 17 weeks of age). Faecal samples of young calves were dominated by bifidobacterial and lactobacilli species, while their respective plasma samples showed high concentrations of amino acids (AAs) and biogenic amines (BAs). However, as the calves matured, the abundances of potential fiber-degrading bacteria and the plasma concentrations of sphingomyelins (SMs), few BAs and acylcarnitines (ACs) were increased. Early-weaning at 7 weeks significantly restructured the microbiome towards potential fiber-degrading bacteria and decreased plasma concentrations of most of the AAs and SMs, few BAs and ACs compared to the late-weaning event. Strong associations between faecal microbes, plasma metabolites and calf growth parameters were observed during days 42-98, where the abundances of Bacteroides, Parabacteroides, and Blautia were positively correlated with the plasma concentrations of AAs, BAs and SMs as well as the live weight gain or average daily gain in calves.

CONCLUSION

The present study reported that weaning at 17 weeks of age was beneficial due to higher growth rate of late-weaned calves during days 42-98 and a quick adaptability of microbiota to weaning-related dietary changes during day 112, suggesting an age-dependent maturation of the gastrointestinal tract. However, the respective plasma samples of late-weaned calves contained several metabolites with differential concentrations to the early-weaned group, suggesting a less abrupt but more-persistent effect of dietary changes on host metabolome compared to the microbiome.

Altered Faecal Microbiota Composition and Structure of Ghanaian Children with Acute Gastroenteritis

Acute gastroenteritis (AGE) is a disease of global public health importance. Recent studies show that children with AGE have an altered gut microbiota relative to non-AGE controls. Yet, how the gut microbiota differs in Ghanaian children with and without AGE remains unclear. Here, we explore the 16S rRNA gene-based faecal microbiota profiles of Ghanaian children five years of age and younger, comprising 57 AGE cases and 50 healthy controls. We found that AGE cases were associated with lower microbial diversity and altered microbial sequence profiles relative to the controls. The faecal microbiota of AGE cases was enriched for disease-associated bacterial genera, including Enterococcus, Streptococcus, and Staphylococcus. In contrast, the faecal microbiota of controls was enriched for potentially beneficial genera, including Faecalibacterium, Prevotella, Ruminococcus, and Bacteroides. Lastly, distinct microbial correlation network characteristics were observed between AGE cases and controls, thereby supporting broad differences in faecal microbiota structure. Altogether, we show that the faecal microbiota of Ghanaian children with AGE differ from controls and are enriched for bacterial genera increasingly associated with diseases.

Galactooligosaccharides ameliorate dietary advanced glycation end product-induced intestinal barrier damage in C57BL/6 mice by modulation of the intestinal microbiome

Advanced glycation end products (AGEs) are increasingly recognized as potentially pathogenic components of processed foods, and long-term consumption of dietary AGEs triggers disruption of the intestinal barrier integrity and increases the risk of chronic diseases. Galactooligosaccharides (GOS) as prebiotics can modulate the intestinal microbiota and improve the intestinal barrier integrity. In this study, we aimed to investigate whether GOS could ameliorate the intestinal barrier damage induced by AGEs. The results showed an increased number of goblet cells (AGEs vs. H-GOS, 133.4 vs. 174.7, p < 0.05) and neutral mucin area (PAS positive area, 7.29% vs. 10.05%, p < 0.05). Upregulated expressions of occludin and claudin-1 and improved intestinal barrier integrity were observed in the H-GOS group. Using 16S rRNA sequencing analysis, we found that GOS significantly reduced the high enrichment of Akkermansia (16.95% vs. 1.29%, p < 0.05) induced by dietary AGEs while increasing the content of short-chain fatty acids. Fecal microbiota transplantation (FMT) showed that AGE-induced damage to the intestinal mucus barrier was reversed in the H-GOS transplanted group. Collectively, GOS ameliorated dietary AGE-induced intestinal barrier damage by reversing the dysregulated state of the intestinal microbiota. Our study lays the foundation for further research on dietary guidelines for populations with high AGE diets.

Enhancing nutritional niche and host defenses by modifying the gut microbiome

The gut microbiome is essential for processing complex food compounds and synthesizing nutrients that the host cannot digest or produce, respectively. New model systems are needed to study how the metabolic capacity provided by the gut microbiome impacts the nutritional status of the host, and to explore possibilities for altering host metabolic capacity via the microbiome. Here, we colonized the nematode Caenorhabditis elegans gut with cellulolytic bacteria that enabled C. elegans to utilize cellulose, an otherwise indigestible substrate, as a carbon source. Cellulolytic bacteria as a community component in the worm gut can also support additional bacterial species with specialized roles, which we demonstrate by using Lactobacillus plantarum to protect C. elegans against Salmonella enterica infection. This work shows that engineered microbiome communities can be used to endow host organisms with novel functions, such as the ability to utilize alternate nutrient sources or to better fight pathogenic bacteria.

Histone Deacetylase Inhibition by Gut Microbe-Generated Short-Chain Fatty Acids Entrains Intestinal Epithelial Circadian Rhythms

BACKGROUND & AIMS

The circadian clock orchestrates ∼24-hour oscillations of gastrointestinal epithelial structure and function that drive diurnal rhythms in gut microbiota. Here, we use experimental and computational approaches in intestinal organoids to reveal reciprocal effects of gut microbial metabolites on epithelial timekeeping by an epigenetic mechanism.

METHODS

We cultured enteroids in media supplemented with sterile supernatants from the altered Schaedler Flora (ASF), a defined murine microbiota. Circadian oscillations of bioluminescent PER2 and Bmal1 were measured in the presence or absence of individual ASF supernatants. Separately, we applied machine learning to ASF metabolomics to identify phase-shifting metabolites.

RESULTS

Sterile filtrates from 3 of 7 ASF species (ASF360 Lactobacillus intestinalis, ASF361 Ligilactobacillus murinus, and ASF502 Clostridium species) induced minimal alterations in circadian rhythms, whereas filtrates from 4 ASF species (ASF356 Clostridium species, ASF492 Eubacterium plexicaudatum, ASF500 Pseudoflavonifactor species, and ASF519 Parabacteroides goldsteinii) induced profound, concentration-dependent phase shifts. Random forest classification identified short-chain fatty acid (SCFA) (butyrate, propionate, acetate, and isovalerate) production as a discriminating feature of ASF "shifters." Experiments with SCFAs confirmed machine learning predictions, with a median phase shift of 6.2 hours in murine enteroids. Pharmacologic or botanical histone deacetylase (HDAC) inhibitors yielded similar findings. Further, mithramycin A, an inhibitor of HDAC inhibition, reduced SCFA-induced phase shifts by 20% (P < .05) and conditional knockout of HDAC3 in enteroids abrogated butyrate effects on Per2 expression. Key findings were reproducible in human Bmal1-luciferase enteroids, colonoids, and Per2-luciferase Caco-2 cells.

CONCLUSIONS

Gut microbe-generated SCFAs entrain intestinal epithelial circadian rhythms by an HDACi-dependent mechanism, with critical implications for understanding microbial and circadian network regulation of intestinal epithelial homeostasis.

Classifying Interactions in a Synthetic Bacterial Community Is Hindered by Inhibitory Growth Medium

Predicting the fate of a microbial community and its member species relies on understanding the nature of their interactions. However, designing simple assays that distinguish between interaction types can be challenging. Here, we performed spent medium assays based on the predictions of a mathematical model to decipher the interactions among four bacterial species: Agrobacterium tumefaciens, Comamonas testosteroni, Microbacterium saperdae, and Ochrobactrum anthropi. While most experimental results matched model predictions, the behavior of C. testosteroni did not: its lag phase was reduced in the pure spent media of A. tumefaciens and M. saperdae but prolonged again when we replenished our growth medium. Further experiments showed that the growth medium actually delayed the growth of C. testosteroni, leading us to suspect that A. tumefaciens and M. saperdae could alleviate this inhibitory effect. There was, however, no evidence supporting such "cross-detoxification," and instead, we identified metabolites secreted by A. tumefaciens and M. saperdae that were then consumed or "cross-fed" by C. testosteroni, shortening its lag phase. Our results highlight that even simple, defined growth media can have inhibitory effects on some species and that such negative effects need to be included in our models. Based on this, we present new guidelines to correctly distinguish between different interaction types such as cross-detoxification and cross-feeding. IMPORTANCE Communities of microbes colonize virtually every place on earth. Ultimately, we strive to predict and control how these communities behave, for example, if they reside in our guts and make us sick. But precise control is impossible unless we can identify exactly how their member species interact with one another. To find a systematic way to measure interactions, we started very simply with a small community of four bacterial species and carefully designed experiments based on a mathematical model. This first attempt accurately mapped out interactions for all species except one. By digging deeper, we understood that our method failed for that species as it was suffering in the growth medium that we chose. A revised model that considered that growth media can be harmful could then make more accurate predictions. What we have learned with these four species can now be applied to decipher interactions in larger communities.

Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function

Animals colonized with a defined microbiota represent useful experimental systems to investigate microbiome function. The altered Schaedler flora (ASF) represents a consortium of eight murine bacterial species that have been used for more than 4 decades where the study of mice with a reduced microbiota is desired. In contrast to germ-free mice, or mice colonized with only one or two species, ASF mice show the normal gut structure and immune system development. To further expand the utility of the ASF, we have developed technical and bioinformatic resources to enable a systems-based analysis of microbiome function using this model. Here, we highlighted four distinct applications of these resources that enable and improve (i) measurements of the abundance of each ASF member by quantitative PCR; (ii) exploration and comparative analysis of ASF genomes and the metabolic pathways they encode that comprise the entire gut microbiome; (iii) global transcriptional profiling to identify genes whose expression responds to environmental changes within the gut; and (iv) discovery of genetic changes resulting from the evolutionary adaptation of the microbiota. These resources were designed to be accessible to a broad community of researchers that, in combination with conventionally-reared mice (i.e., with complex microbiome), should contribute to our understanding of microbiome structure and function. IMPORTANCE Improved experimental systems are needed to advance our understanding of how the gut microbiome influences processes of the mammalian host as well as microbial community structure and function. An approach that is receiving considerable attention is the use of animal models that harbor a stable microbiota of known composition, i.e., defined microbiota, which enables control over an otherwise highly complex and variable feature of mammalian biology. The altered Schaedler flora (ASF) consortium is a well-established defined microbiota model, where mice are stably colonized with 8 distinct murine bacterial species. To take better advantage of the ASF, we established new experimental and bioinformatics resources for researchers to make better use of this model as an experimental system to study microbiome function.

A Novel Probiotic Bacillus subtilis Strain Confers Cytoprotection to Host Pig Intestinal Epithelial Cells during Enterotoxic Escherichia coli Infection

Enteric infections caused by enterotoxic Escherichia coli (ETEC) negatively impact the growth performance of piglets during weaning, resulting in significant economic losses for the producers. With the ban on antibiotic usage in livestock production, probiotics have gained a lot of attention as a potential alternative. However, strain specificity and limited knowledge on the host-specific targets limit their efficacy in preventing ETEC-related postweaning enteric infections. We recently isolated and characterized a novel probiotic Bacillus subtilis bacterium (CP9) that demonstrated antimicrobial activity. Here, we report anti-ETEC properties of CP9 and its impact on metabolic activity of swine intestinal epithelial (IPEC-J2) cells. Our results showed that pre- or coincubation with CP9 protected IPEC-J2 cells from ETEC-induced cytotoxicity. CP9 significantly attenuated ETEC-induced inflammatory response by reducing ETEC-induced nitric oxide production and relative mRNA expression of the Toll-like receptors (TLRs; TLR2, TLR4, and TLR9), proinflammatory tumor necrosis factor alpha, interleukins (ILs; IL-6 and IL-8), augmenting anti-inflammatory granulocyte-macrophage colony-stimulating factor and host defense peptide mucin 1 (MUC1) mRNA levels. We also show that CP9 significantly (P < 0.05) reduced caspase-3 activity, reinstated cell proliferation and increased relative expression of tight junction genes, claudin-1, occludin, and zona occludens-1 in ETEC-infected cells. Finally, metabolomic analysis revealed that CP9 exposure induced metabolic modulation in IPEC J2 cells with the greatest impact seen in alanine, aspartate, and glutamate metabolism; pyrimidine metabolism; nicotinate and nicotinamide metabolism; glutathione metabolism; the citrate cycle (TCA cycle); and arginine and proline metabolism. Our study shows that CP9 incubation attenuated ETEC-induced cytotoxicity in IPEC-J2 cells and offers insight into potential application of this probiotic for ETEC infection control. IMPORTANCE ETEC remains one of the leading causes of postweaning diarrhea and mortality in swine production. Due to the rising concerns with the antibiotic use in livestock, alternative interventions need to be developed. In this study, we analyzed the cytoprotective effect of a novel probiotic strain in combating ETEC infection in swine intestinal cells, along with assessing its mechanism of action. To our knowledge, this is also the first study to analyze the metabolic impact of a probiotic on intestinal cells. Results from this study should provide effective cues in developing a probiotic intervention for ameliorating ETEC infection and improving overall gut health in swine production.

Distinct N and C Cross-Feeding Networks in a Synthetic Mouse Gut Consortium

The complex interactions between the gut microbiome and host or pathogen colonization resistance cannot be understood solely from community composition. Missing are causal relationships, such as metabolic interactions among species, to better understand what shapes the microbiome. Here, we focused on metabolic niches generated and occupied by the Oligo-Mouse-Microbiota (OMM) consortium, a synthetic community composed of 12 members that is increasingly used as a model for the mouse gut microbiome. Combining monocultures and spent medium experiments with untargeted metabolomics revealed broad metabolic diversity in the consortium, constituting a dense cross-feeding network with more than 100 pairwise interactions. Quantitative analysis of the cross-feeding network revealed distinct C and N food webs, highlighting the two Bacteroidetes members Bacteroides caecimuris and Muribaculum intestinale as primary suppliers of carbon and a more diverse group as nitrogen providers. Cross-fed metabolites were mainly carboxylic acids, amino acids, and the so far not reported nucleobases. In particular, the dicarboxylic acids malate and fumarate provided a strong physiological benefit to consumers, presumably used in anaerobic respiration. Isotopic tracer experiments validated the fate of a subset of cross-fed metabolites, such as the conversion of the most abundant cross-fed compound succinate to butyrate. Thus, we show that this consortium is tailored to produce the anti-inflammatory metabolite butyrate. Overall, we provide evidence for metabolic niches generated and occupied by OMM members that lays a metabolic foundation to facilitate an understanding of the more complex in vivo behavior of this consortium in the mouse gut. IMPORTANCE This article maps out the cross-feeding network among 10 members of a synthetic consortium that is increasingly used as the model mouse gut microbiota. Combining metabolomics with in vitro cultivations, two dense networks of carbon and nitrogen exchange are described. The vast majority of the ∼100 interactions are synergistic in nature, in several cases providing distinct physiological benefits to the recipient species. These networks lay the groundwork toward understanding gut community dynamics and host-gut microbe interactions.

In vitro interaction network of a synthetic gut bacterial community

A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM¹²) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM¹² interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, Enterococcus faecalis KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM¹² interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.

Chicory: Understanding the Effects and Effectors of This Functional Food

Industrial chicory has been the subject of numerous studies, most of which provide clinical observations on its health effects. Whether it is the roasted root, the flour obtained from the roots or the different classes of molecules that enter into the composition of this plant, understanding the molecular mechanisms of action on the human organism remains incomplete. In this study, we were interested in three molecules or classes of molecules present in chicory root: fructose, chlorogenic acids, and sesquiterpene lactones. We conducted experiments on the murine model and performed a nutrigenomic analysis, a metabolic hormone assay and a gut microbiota analysis, associated with in vitro observations for different responses. We have highlighted a large number of effects of all these classes of molecules that suggest a pro-apoptotic activity, an anti-inflammatory, antimicrobial, antioxidant, hypolipidemic and hypoglycemic effect and also an important role in appetite regulation. A significant prebiotic activity was also identified. Fructose seems to be the most involved in these activities, contributing to approximately 83% of recorded responses, but the other classes of tested molecules have shown a specific role for these different effects, with an estimated contribution of 23-24%.

Genomic structure predicts metabolite dynamics in microbial communities

The metabolic activities of microbial communities play a defining role in the evolution and persistence of life on Earth, driving redox reactions that give rise to global biogeochemical cycles. Community metabolism emerges from a hierarchy of processes, including gene expression, ecological interactions, and environmental factors. In wild communities, gene content is correlated with environmental context, but predicting metabolite dynamics from genomes remains elusive. Here, we show, for the process of denitrification, that metabolite dynamics of a community are predictable from the genes each member of the community possesses. A simple linear regression reveals a sparse and generalizable mapping from gene content to metabolite dynamics for genomically diverse bacteria. A consumer-resource model correctly predicts community metabolite dynamics from single-strain phenotypes. Our results demonstrate that the conserved impacts of metabolic genes can predict community metabolite dynamics, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism.

Engineering temporal dynamics in microbial communities

Microbial communities are a key part to tackling global challenges in human health, environmental conservation, and sustainable agriculture in the coming decade. Recent advances in synthetic biology to study and modify microbial communities have led to important insights into their physiology and ecology. Understanding how targeted changes to microbial communities result in reproducible alterations of the community's intrinsic fluctuations and function is important for mechanistic reconstruction of microbiomes. Studies of synthetic microbial consortia and comparative analysis of communities in normal and disrupted states have revealed ecological principles that can be leveraged to engineer communities towards desired functions. Tools enabling temporal modulation and sensing of the community dynamics offer precise spatiotemporal control of functions, help to dissect microbial interaction networks, and improve predictions of population temporal dynamics. Here we discuss recent advances to manipulate microbiome dynamics through control of specific strain engraftment and abundance, modulation of cell-cell signaling for tuning population dynamics, infiltration of new functions in the existing community with in situ engineering, and in silico modeling of microbial consortia to predict community function and ecology.

Enhancing Microbiome Research through Genome-Scale Metabolic Modeling

Construction and analysis of genome-scale metabolic models (GEMs) is a well-established systems biology approach that can be used to predict metabolic and growth phenotypes. The ability of GEMs to produce mechanistic insight into microbial ecological processes makes them appealing tools that can open a range of exciting opportunities in microbiome research. Here, we briefly outline these opportunities, present current rate-limiting challenges for the trustworthy application of GEMs to microbiome research, and suggest approaches for moving the field forward.

Microbial Systems Ecology to Understand Cross-Feeding in Microbiomes

Understanding how microorganism-microorganism interactions shape microbial assemblages is a key to deciphering the evolution of dependencies and co-existence in complex microbiomes. Metabolic dependencies in cross-feeding exist in microbial communities and can at least partially determine microbial community composition. To parry the complexity and experimental limitations caused by the large number of possible interactions, new concepts from systems biology aim to decipher how the components of a system interact with each other. The idea that cross-feeding does impact microbiome assemblages has developed both theoretically and empirically, following a systems biology framework applied to microbial communities, formalized as microbial systems ecology (MSE) and relying on integrated-omics data. This framework merges cellular and community scales and offers new avenues to untangle microbial coexistence primarily by metabolic modeling, one of the main approaches used for mechanistic studies. In this mini-review, we first give a concise explanation of microbial cross-feeding. We then discuss how MSE can enable progress in microbial research. Finally, we provide an overview of a MSE framework mostly based on genome-scale metabolic-network reconstruction that combines top-down and bottom-up approaches to assess the molecular mechanisms of deterministic processes of microbial community assembly that is particularly suitable for use in synthetic biology and microbiome engineering.

Metagenome-Scale Metabolic Network Suggests Folate Produced by Bifidobacterium longum Might Contribute to High-Fiber-Diet-Induced Weight Loss in a Prader-Willi Syndrome Child

Gut-microbiota-targeted nutrition intervention has achieved success in the management of obesity, but its underlying mechanism still needs extended exploration. An obese Prader-Willi syndrome boy lost 25.8 kg after receiving a high-fiber dietary intervention for 105 days. The fecal microbiome sequencing data taken from the boy on intervention days 0, 15, 30, 45, 60, 75, and 105, along with clinical indexes, were used to construct a metagenome-scale metabolic network. Firstly, the abundances of the microbial strains were obtained by mapping the sequencing reads onto the assembly of gut organisms through use of reconstruction and analysis (AGORA) genomes. The nutritional components of the diet were obtained through the Virtual Metabolic Human database. Then, a community model was simulated using the Microbiome Modeling Toolbox. Finally, the significant Spearman correlations among the metabolites and the clinical indexes were screened and the strains that were producing these metabolites were identified. The high-fiber diet reduced the overall amount of metabolite secretions, but the secretions of folic acid derivatives by Bifidobacterium longum strains were increased and were significantly relevant to the observed weight loss. Reduced metabolites might also have directly contributed to the weight loss or indirectly contribute by enhancing leptin and decreasing adiponectin. Metagenome-scale metabolic network technology provides a cost-efficient solution for screening the functional microbial strains and metabolic pathways that are responding to nutrition therapy.

Two-species community design of lactic acid bacteria for optimal production of lactate

Microbial communities that metabolise pentose and hexose sugars are useful in producing high-value chemicals, resulting in the effective conversion of raw materials to the product, a reduction in the production cost, and increased yield. Here, we present a computational analysis approach called CAMP (Co-culture/Community Analyses for Metabolite Production) that simulates and identifies appropriate communities to produce a metabolite of interest. To demonstrate this approach, we focus on the optimal production of lactate from various Lactic Acid Bacteria. We used genome-scale metabolic models (GSMMs) belonging to Lactobacillus, Leuconostoc, and Pediococcus species from the Virtual Metabolic Human (VMH; https://vmh.life/) resource and well-curated GSMMs of L. plantarum WCSF1 and L. reuteri JCM 1112. We analysed 1176 two-species communities using a constraint-based modelling method for steady-state flux-balance analysis of communities. Flux variability analysis was used to detect the maximum lactate flux in the communities. Using glucose or xylose as substrates separately or in combination resulted in either parasitism, amensalism, or mutualism being the dominant interaction behaviour in the communities. Interaction behaviour between members of the community was deduced based on variations in the predicted growth rates of monocultures and co-cultures. Acetaldehyde, ethanol, acetate, among other metabolites, were found to be cross-fed between community members. L. plantarum WCSF1 was found to be a member of communities with high lactate yields. In silico community optimisation strategies to predict reaction knock-outs for improving lactate flux were implemented. Reaction knock-outs of acetate kinase, phosphate acetyltransferase, and fumarate reductase in the communities were found to enhance lactate production.

Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions

Microorganisms are a fundamental part of virtually every ecosystem on earth. Understanding how collectively they interact, assemble, and function as communities has become a prevalent topic both in fundamental and applied research. Owing to multiple advances in technology, answering questions at the microbial system or network level is now within our grasp. To map and characterize microbial interaction networks, numerous computational approaches have been developed; however, experimentally validating microbial interactions is no trivial task. Microbial interactions are context-dependent, and their complex nature can result in an array of outcomes, not only in terms of fitness or growth, but also in other relevant functions and phenotypes. Thus, approaches to experimentally capture microbial interactions involve a combination of culture methods and phenotypic or functional characterization methods. Here, through our perspective of food microbiologists, we highlight the breadth of innovative and promising experimental strategies for their potential to capture the different dimensions of microbial interactions and their high-throughput application to answer the question; are microbial interaction patterns or network architecture similar along different contextual scales? We further discuss the experimental approaches used to build various types of networks and study their architecture in the context of cell biology and how they translate at the level of microbial ecosystem.

Assessment of the state of intestinal microbiocenosis based on bacterial endotoxin and plasmalogen in elderly persons with type 2 diabetes mellitus pathology

The concentration of bacterial plasmalogen 18a and endotoxin in the blood of elderly people 45-90 years old with the pathology of type 2 diabetes mellitus (DM 2) - the main group and without diabetes mellitus - the comparison group was investigated. The concentration of both plasmalogen 18a and endotoxin in the blood of individuals with DM 2 pathology is statistically significantly higher than in the blood of individuals without DM 2 pathology. To assess the state of microbiocenosis and predict type 2 diabetes mellitus, decisive rules have been determined in the form of threshold values of plasma concentrations 18a and endotoxin in the blood of elderly people with a suspected or established diagnosis of type 2 diabetes. Using ROC analysis, it was found that values above 20.66 μg / ml for plasmalogen 18a, and 0.48 nmol / ml for endotoxin, determine the presence of type 2 diabetes mellitus pathology in the 45-90 age group.

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.

Potential Probiotic Bacillus subtilis Isolated from a Novel Niche Exhibits Broad Range Antibacterial Activity and Causes Virulence and Metabolic Dysregulation in Enterotoxic E. coli

Microbial life in extreme environments, such as deserts and deep oceans, is thought to have evolved to overcome constraints of nutrient availability, temperature, and suboptimal hygiene environments. Isolation of probiotic bacteria from such niche may provide a competitive edge over traditional probiotics. Here, we tested the survival, safety, and antimicrobial effect of a recently isolated and potential novel strain of Bacillus subtilis (CP9) from desert camel in vitro. Antimicrobial assays were performed via radial diffusion, agar spot, and co-culture assays. Cytotoxic analysis was performed using pig intestinal epithelial cells (IPEC-J2). Real time-PCR was performed for studying the effect on ETEC virulence genes and metabolomic analysis was performed using LC-MS. The results showed that CP9 cells were viable in varied bile salts and in low pH environments. CP9 showed no apparent cytotoxicity in IPEC-J2 cells. CP9 displayed significant bactericidal effect against Enterotoxic E. coli (ETEC), Salmonella Typhimurium, and Methicillin-resistant Staphylococcus aureus (MRSA) in a contact inhibitory fashion. CP9 reduced the expression of ETEC virulent genes during a 5 h co-culture. Additionally, a unique emergent metabolic signature in co-culture samples was observed by LC-MS analysis. Our findings indicate that CP9 exhibits a strong antibacterial property and reveals potential mechanisms behind.

Untargeted Metabolomics Reveals Species-Specific Metabolite Production and Shared Nutrient Consumption by Pseudomonas aeruginosa and Staphylococcus aureus

While bacterial metabolism is known to impact antibiotic efficacy and virulence, the metabolic capacities of individual microbes in cystic fibrosis lung infections are difficult to disentangle from sputum samples. Here, we show that untargeted metabolomic profiling of supernatants of multiple strains of Pseudomonas aeruginosa and Staphylococcus aureus grown in monoculture in synthetic cystic fibrosis media (SCFM) reveals distinct species-specific metabolic signatures despite intraspecies metabolic variability. We identify a set of 15 metabolites that were significantly consumed by both P. aeruginosa and S. aureus, suggesting that nutrient competition has the potential to impact community dynamics even in the absence of other pathogen-pathogen interactions. Finally, metabolites that were uniquely produced by one species or the other were identified. Specifically, the virulence factor precursor anthranilic acid, as well as the quinoline 2,4-quinolinediol (DHQ), were robustly produced across all tested strains of P. aeruginosa. Through the direct comparison of the extracellular metabolism of P. aeruginosa and S. aureus in a physiologically relevant environment, this work provides insight toward the potential for metabolic interactions in vivo and supports the development of species-specific diagnostic markers of infection. IMPORTANCE Interactions between P. aeruginosa and S. aureus can impact pathogenicity and antimicrobial efficacy. In this study, we aim to better understand the potential for metabolic interactions between P. aeruginosa and S. aureus in an environment resembling the cystic fibrosis lung. We find that S. aureus and P. aeruginosa consume many of the same nutrients, suggesting that metabolic competition may play an important role in community dynamics during coinfection. We further identify metabolites uniquely produced by either organism with the potential to be developed into species-specific biomarkers of infection in the cystic fibrosis lung.

Friends or Foes-Microbial Interactions in Nature

Simple Summary

Microorganisms like bacteria, archaea, fungi, microalgae, and viruses mostly form complex interactive networks within the ecosystem rather than existing as single planktonic cells. Interactions among microorganisms occur between the same species, with different species, or even among entirely different genera, families, or even domains. These interactions occur after environmental sensing, followed by converting those signals to molecular and genetic information, including many mechanisms and classes of molecules. Comprehensive studies on microbial interactions disclose key strategies of microbes to colonize and establish in a variety of different environments. Knowledge of the mechanisms involved in the microbial interactions is essential to understand the ecological impact of microbes and the development of dysbioses. It might be the key to exploit strategies and specific agents against different facing challenges, such as chronic and infectious diseases, hunger crisis, pollution, and sustainability.

Abstract

Microorganisms are present in nearly every niche on Earth and mainly do not exist solely but form communities of single or mixed species. Within such microbial populations and between the microbes and a eukaryotic host, various microbial interactions take place in an ever-changing environment. Those microbial interactions are crucial for a successful establishment and maintenance of a microbial population. The basic unit of interaction is the gene expression of each organism in this community in response to biotic or abiotic stimuli. Differential gene expression is responsible for producing exchangeable molecules involved in the interactions, ultimately leading to community behavior. Cooperative and competitive interactions within bacterial communities and between the associated bacteria and the host are the focus of this review, emphasizing microbial cell–cell communication (quorum sensing). Further, metagenomics is discussed as a helpful tool to analyze the complex genomic information of microbial communities and the functional role of different microbes within a community and to identify novel biomolecules for biotechnological applications.

Design of synthetic human gut microbiome assembly and butyrate production

The capability to design microbiomes with predictable functions would enable new technologies for applications in health, agriculture, and bioprocessing. Towards this goal, we develop a model-guided approach to design synthetic human gut microbiomes for production of the health-relevant metabolite butyrate. Our data-driven model quantifies microbial interactions impacting growth and butyrate production separately, providing key insights into ecological mechanisms driving butyrate production. We use our model to explore a vast community design space using a design-test-learn cycle to identify high butyrate-producing communities. Our model can accurately predict community assembly and butyrate production across a wide range of species richness. Guided by the model, we identify constraints on butyrate production by high species richness and key molecular factors driving butyrate production, including hydrogen sulfide, environmental pH, and resource competition. In sum, our model-guided approach provides a flexible and generalizable framework for understanding and accurately predicting community assembly and metabolic functions.