A guide to deciphering microbial interactions and metabolic fluxes in microbiome communities

Deciphering and designing microbial communities by genome-scale metabolic modelling

Microbial communities are shaped by the complex interactions among organisms and the environment. Genome-scale metabolic models (GEMs) can provide deeper insights into the complexity and ecological properties of various microbial communities, revealing their intricate interactions. Many researchers have modified GEMs for the microbial communities based on specific needs. Thus, GEMs need to be comprehensively summarized to better understand the trends in their development. In this review, we summarized the key developments in deciphering and designing microbial communities using different GEMs. A timeline of selected highlights in GEMs indicated that this area is evolving from the single-strain level to the microbial community level. Then, we outlined a framework for constructing GEMs of microbial communities. We also summarized the models and resources of static and dynamic community-level GEMs. We focused on the role of external environmental and intracellular resources in shaping the assembly of microbial communities. Finally, we discussed the key challenges and future directions of GEMs, focusing on the integration of GEMs with quorum sensing mechanisms, microbial ecology interactions, machine learning algorithms, and automatic modeling, all of which contribute to consortia-based applications in different fields.

Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D in vitro tissue models of disease

Rapid advances in tissue engineering have resulted in more complex and physiologically relevant 3D in vitro tissue models with applications in fundamental biology and therapeutic development. However, the complexity provided by these models is often not leveraged fully due to the reductionist methods used to analyze them. Computational and mathematical models developed in the field of systems biology can address this issue. Yet, traditional systems biology has been mostly applied to simpler in vitro models with little physiological relevance and limited cellular complexity. Therefore, integrating these two inherently interdisciplinary fields can result in new insights and move both disciplines forward. In this review, we provide a systematic overview of how systems biology has been integrated with 3D in vitro tissue models and discuss key application areas where the synergies between both fields have led to important advances with potential translational impact. We then outline key directions for future research and discuss a framework for further integration between fields.

Interactions-based classification of a single microbial sample

To address the limitation of overlooking crucial ecological interactions due to relying on single time point samples, we developed a computational approach that analyzes individual samples based on the interspecific microbial relationships. We verify, using both numerical simulations as well as real and shuffled microbial profiles from the human oral cavity, that the method can classify single samples based on their interspecific interactions. By analyzing the gut microbiome of people with autistic spectrum disorder, we found that our interaction-based method can improve the classification of individual subjects based on a single microbial sample. These results demonstrate that the underlying ecological interactions can be practically utilized to facilitate microbiome-based diagnosis and precision medicine.

Formation of a constructed microbial community in a nutrient-rich environment indicates bacterial interspecific competition

Understanding the organizational principles of microbial communities is essential for interpreting ecosystem stability. Previous studies have investigated the formation of bacterial communities under nutrient-poor conditions or obligate relationships to observe cooperative interactions among different species. How microorganisms form stabilized communities in nutrient-rich environments, without obligate metabolic interdependency for growth, is still not fully disclosed. In this study, three bacterial strains isolated from the Populus deltoides rhizosphere were co-cultured in complex medium, and their growth behavior was tracked. These strains co-exist in mixed culture over serial transfer for multiple growth-dilution cycles. Competition is proposed as an emergent interaction relationship among the three bacteria based on their significantly decreased growth levels. The effects of different initial inoculum ratios, up to three orders of magnitude, on community structure were investigated, and the final compositions of the mixed communities with various starting composition indicate that community structure is not dependent on the initial inoculum ratio. Furthermore, the competitive relationships within the community were not altered by different initial inoculum ratios. The community structure was simulated by generalized Lotka-Volterra and dynamic flux balance analysis to provide mechanistic predictions into emergence of community structure under a nutrient-rich environment. Metaproteomic analyses provide support for the metabolite exchanges predicted by computational modeling and for highly altered physiologies when microbes are grown in co-culture. These findings broaden our understanding of bacterial community dynamics and metabolic diversity in higher-order interactions and could be significant in the management of rhizospheric bacterial communities.

IMPORTANCE

Bacteria naturally co-exist in multispecies consortia, and the ability to engineer such systems can be useful in biotechnology. Despite this, few studies have been performed to understand how bacteria form a stable community and interact with each other under nutrient-rich conditions. In this study, we investigated the effects of initial inoculum ratios on bacterial community structure using a complex medium and found that the initial inoculum ratio has no significant impact on resultant community structure or on interaction patterns between community members. The microbial population profiles were simulated using computational tools in order to understand intermicrobial relationships and to identify potential metabolic exchanges that occur during stabilization of the bacterial community. Studying microbial community assembly processes is essential for understanding fundamental ecological principles in microbial ecosystems and can be critical in predicting microbial community structure and function.

Application of cold-adapted microbial agents in soil contaminate remediation: biodegradation mechanisms, case studies, and safety assessments

The microbial agent technology has made significant progress in remediating nitro-aromatic compounds (NACs), such as p-nitrophenol, 2,4-dinitrophenol, and 2,4,6-Trinitrotoluene, in farmland soil over the past decade. However, there are still gaps in our understanding of the bioavailability and degradation mechanisms of these compounds in low-temperature environments. In this review, we provide a comprehensive summary of the strategies employed by cold-adapted microorganisms and elucidate the degradation pathways of NACs pollutants. To further analyze their metabolic mechanisms, we propose using mass balance to improve our understanding of biochemical processes and refine the degradation pathways through stoichiometry analysis. Additionally, we suggest employing 13C-metabolic flux analysis to track enzyme activity and intermediate products during bio-degradation processes with the aim of accelerating the remediation of nitro-aromatic compounds, particularly in cold regions. Through a comprehensive analysis of pollutant metabolic activities and a commitment to the 'One Health' approach, with an emphasis on selecting non-pathogenic strains, the environmental management strategies for soil remediation could be positioned to develop and implement safe and effective measure.

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Fungal biodeterioration and preservation of cultural heritage, artwork, and historical artifacts: extremophily and adaptation

SUMMARYFungi are ubiquitous and important biosphere inhabitants, and their abilities to decompose, degrade, and otherwise transform a massive range of organic and inorganic substances, including plant organic matter, rocks, and minerals, underpin their major significance as biodeteriogens in the built environment and of cultural heritage. Fungi are often the most obvious agents of cultural heritage biodeterioration with effects ranging from discoloration, staining, and biofouling to destruction of building components, historical artifacts, and artwork. Sporulation, morphological adaptations, and the explorative penetrative lifestyle of filamentous fungi enable efficient dispersal and colonization of solid substrates, while many species are able to withstand environmental stress factors such as desiccation, ultra-violet radiation, salinity, and potentially toxic organic and inorganic substances. Many can grow under nutrient-limited conditions, and many produce resistant cell forms that can survive through long periods of adverse conditions. The fungal lifestyle and chemoorganotrophic metabolism therefore enable adaptation and success in the frequently encountered extremophilic conditions that are associated with indoor and outdoor cultural heritage. Apart from free-living fungi, lichens are a fungal growth form and ubiquitous pioneer colonizers and biodeteriogens of outdoor materials, especially stone- and mineral-based building components. This article surveys the roles and significance of fungi in the biodeterioration of cultural heritage, with reference to the mechanisms involved and in relation to the range of substances encountered, as well as the methods by which fungal biodeterioration can be assessed and combated, and how certain fungal processes may be utilized in bioprotection.

Xylose and shikimate transporters facilitates microbial consortium as a chassis for benzylisoquinoline alkaloid production

Plant-sourced aromatic amino acid (AAA) derivatives are a vast group of compounds with broad applications. Here, we present the development of a yeast consortium for efficient production of (S)-norcoclaurine, the key precursor for benzylisoquinoline alkaloid biosynthesis. A xylose transporter enables the concurrent mixed-sugar utilization in Scheffersomyces stipitis, which plays a crucial role in enhancing the flux entering the highly regulated shikimate pathway located upstream of AAA biosynthesis. Two quinate permeases isolated from Aspergillus niger facilitates shikimate translocation to the co-cultured Saccharomyces cerevisiae that converts shikimate to (S)-norcoclaurine, resulting in the maximal titer (11.5 mg/L), nearly 110-fold higher than the titer reported for an S. cerevisiae monoculture. Our findings magnify the potential of microbial consortium platforms for the economical de novo synthesis of complex compounds, where pathway modularization and compartmentalization in distinct specialty strains enable effective fine-tuning of long biosynthetic pathways and diminish intermediate buildup, thereby leading to increases in production.

Species' functional traits and interactions drive nitrate-mediated sulfur-oxidizing community structure and functioning

IMPORTANCE

Understanding the processes and mechanisms governing microbial community assembly and their linkages to ecosystem functioning has long been a core issue in microbial ecology. An in-depth insight still requires combining with analyses of species' functional traits and microbial interactions. Our study showed how species' functional traits and interactions determined microbial community structure and functions by a well-controlled laboratory experiment with nitrate-mediated sulfur oxidation systems using high-throughput sequencing and culture-dependent technologies. The results provided solid evidences that species' functional traits and interactions were the intrinsic factors determining community structure and function. More importantly, our study established quantitative links between community structure and function based on species' functional traits and interactions, which would have important implications for the design and synthesis of microbiomes with expected functions.

Construction and Modeling of a Coculture Microplate for Real-Time Measurement of Microbial Interactions

The dynamic structures of microbial communities emerge from the complex network of interactions between their constituent microorganisms. Quantitative measurements of these interactions are important for understanding and engineering ecosystem structure. Here, we present the development and application of the BioMe plate, a redesigned microplate device in which pairs of wells are separated by porous membranes. BioMe facilitates the measurement of dynamic microbial interactions and integrates easily with standard laboratory equipment. We first applied BioMe to recapitulate recently characterized, natural symbiotic interactions between bacteria isolated from the Drosophila melanogaster gut microbiome. Specifically, the BioMe plate allowed us to observe the benefit provided by two Lactobacillus strains to an Acetobacter strain. We next explored the use of BioMe to gain quantitative insight into the engineered obligate syntrophic interaction between a pair of Escherichia coli amino acid auxotrophs. We integrated experimental observations with a mechanistic computational model to quantify key parameters associated with this syntrophic interaction, including metabolite secretion and diffusion rates. This model also allowed us to explain the slow growth observed for auxotrophs growing in adjacent wells by demonstrating that, under the relevant range of parameters, local exchange between auxotrophs is essential for efficient growth. The BioMe plate provides a scalable and flexible approach for the study of dynamic microbial interactions. IMPORTANCE Microbial communities participate in many essential processes from biogeochemical cycles to the maintenance of human health. The structure and functions of these communities are dynamic properties that depend on poorly understood interactions among different species. Unraveling these interactions is therefore a crucial step toward understanding natural microbiota and engineering artificial ones. Microbial interactions have been difficult to measure directly, largely due to limitations of existing methods to disentangle the contribution of different organisms in mixed cocultures. To overcome these limitations, we developed the BioMe plate, a custom microplate-based device that enables direct measurement of microbial interactions, by detecting the abundance of segregated populations of microbes that can exchange small molecules through a membrane. We demonstrated the possible application of the BioMe plate for studying both natural and artificial consortia. BioMe is a scalable and accessible platform that can be used to broadly characterize microbial interactions mediated by diffusible molecules.

The virtual microbiome: A computational framework to evaluate microbiome analyses

Microbiomes have been the focus of a substantial research effort in the last decades. The composition of microbial populations is normally determined by comparing DNA sequences sampled from those populations with the sequences stored in genomic databases. Therefore, the amount of information available in databanks should be expected to constrain the accuracy of microbiome analyses. Albeit normally ignored in microbiome studies, this constraint could severely compromise the reliability of microbiome data. To test this hypothesis, we generated virtual bacterial populations that exhibit the ecological structure of real-world microbiomes. Confronting the analyses of virtual microbiomes with their original composition revealed critical issues in the current approach to characterizing microbiomes, issues that were empirically confirmed by analyzing the microbiome of Galleria mellonella larvae. To reduce the uncertainty of microbiome data, the effort in the field must be channeled towards significantly increasing the amount of available genomic information and optimizing the use of this information.

Phototroph-heterotroph interactions during growth and long-term starvation across Prochlorococcus and Alteromonas diversity

Due to their potential impact on ecosystems and biogeochemistry, microbial interactions, such as those between phytoplankton and bacteria, have been studied intensively using specific model organisms. Yet, to what extent interactions differ between closely related organisms, or how these interactions change over time, or culture conditions, remains unclear. Here, we characterize the interactions between five strains each of two globally abundant marine microorganisms, Prochlorococcus (phototroph) and Alteromonas (heterotroph), from the first encounter between individual strains and over more than a year of repeated cycles of exponential growth and long-term nitrogen starvation. Prochlorococcus-Alteromonas interactions had little effect on traditional growth parameters such as Prochlorococcus growth rate, maximal fluorescence, or lag phase, affecting primarily the dynamics of culture decline, which we interpret as representing cell mortality and lysis. The shape of the Prochlorococcus decline curve and the carrying capacity of the co-cultures were determined by the phototroph and not the heterotroph strains involved. Comparing various mathematical models of culture mortality suggests that Prochlorococcus death rate increases over time in mono-cultures but decreases in co-cultures, with cells potentially becoming more resistant to stress. Our results demonstrate intra-species differences in ecologically relevant co-culture outcomes. These include the recycling efficiency of N and whether the interactions are mutually synergistic or competitive. They also highlight the information-rich growth and death curves as a useful readout of the interaction phenotype.

A critical review on microbial ecology in the novel biological nitrogen removal process: Dynamic balance of complex functional microbes for nitrogen removal

The novel biological nitrogen removal process has been extensively studied for its high nitrogen removal efficiency, energy efficiency, and greenness. A successful novel biological nitrogen removal process has a stable microecological equilibrium and benign interactions between the various functional bacteria. However, changes in the external environment can easily disrupt the dynamic balance of the microecology and affect the activity of functional bacteria in the novel biological nitrogen removal process. Therefore, this review focuses on the microecology in existing the novel biological nitrogen removal process, including the growth characteristics of functional microorganisms and their interactions, together with the effects of different influencing factors on the evolution of microbial communities. This provides ideas for achieving a stable dynamic balance of the microecology in a novel biological nitrogen removal process. Furthermore, to investigate deeply the mechanisms of microbial interactions in novel biological nitrogen removal process, this review also focuses on the influence of quorum sensing (QS) systems on nitrogen removal microbes, regulated by which bacteria secrete acyl homoserine lactones (AHLs) as signaling molecules to regulate microbial ecology in the novel biological nitrogen removal process. However, the mechanisms of action of AHLs on the regulation of functional bacteria have not been fully determined and the composition of QS system circuits requires further investigation. Meanwhile, it is necessary to further apply molecular analysis techniques and the theory of systems ecology in the future to enhance the exploration of microbial species and ecological niches, providing a deeper scientific basis for the development of a novel biological nitrogen removal process.

The rhizosphere bacterial community contributes to the nutritional competitive advantage of weedy rice over cultivated rice in paddy soil

Background

Weedy rice competes for nutrients and living space with cultivated rice, which results in serious reductions in rice production. The rhizosphere bacterial community plays an important role in nutrient competition between species. It is therefore important to clarify the differences in the diversities of the inter rhizosphere bacterial community between cultivated rice and weedy rice. The differences in compositions and co-occurrence networks of the rhizosphere bacterial community of cultivated rice and weedy rice are largely unknown and thus the aim of our study.

Results

In our study, the different rhizosphere bacterial community structures in weedy rice (AW), cultivated rice (AY) and cultivated rice surrounded by weedy rice (WY) were determined based on 16S rRNA gene sequencing. The majority of the WY rhizosphere was enriched with unique types of microorganisms belonging to Burkholderia. The rhizosphere bacterial community showed differences in relative abundance among the three groups. Network analysis revealed a more complex co-occurrence network structure in the rhizosphere bacterial community of AW than in those of AY and WY due to a higher degree of Microbacteriaceae and Micrococcaceae in the network. Both network analysis and functional predictions reveal that weedy rice contamination dramatically impacts the iron respiration of the rhizosphere bacterial community of cultivated rice.

Conclusions

Our study shows that there are many differences in the rhizosphere bacterial community of weedy rice and cultivated rice. When cultivated rice was disturbed by weedy rice, the rhizosphere bacterial community and co-occurrence network also changed. The above differences tend to lead to a nutritional competitive advantage for weedy rice in paddy soils.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02648-1.

Metabolic framework of spontaneous and synthetic sourdough metacommunities to reveal microbial players responsible for resilience and performance

BACKGROUND

In nature, microbial communities undergo changes in composition that threaten their resiliency. Here, we interrogated sourdough, a natural cereal-fermenting metacommunity, as a dynamic ecosystem in which players are subjected to continuous environmental and spatiotemporal stimuli.

RESULTS

The inspection of spontaneous sourdough metagenomes and transcriptomes revealed dominant, subdominant and satellite players that are engaged in different functional pathways. The highest microbial richness was associated with the highest number of gene copies per pathway. Based on meta-omics data collected from 8 spontaneous sourdoughs and their identified microbiota, we de novo reconstructed a synthetic microbial community SDG. We also reconstructed SMC-SD43 from scratch using the microbial composition of its spontaneous sourdough equivalent for comparison. The KEGG number of dominant players in the SDG was not affected by depletion of a single player, whereas the subdominant and satellite species fluctuated, revealing unique contributions. Compared to SMC-SD43, SDG exhibited broader transcriptome redundancy. The invariant volatilome profile of SDG after in situ long-term back slopping revealed its stability. In contrast, SMC-SD43 lost many taxon members. Dominant, subdominant and satellite players together ensured gene and transcript redundancy.

CONCLUSIONS

Our study demonstrates how, by starting from spontaneous sourdoughs and reconstructing these communities synthetically, it was possible to unravel the metabolic contributions of individual players. For resilience and good performance, the sourdough metacommunity must include dominant, subdominant and satellite players, which together ensure gene and transcript redundancy. Overall, our study changes the paradigm and introduces theoretical foundations for directing food fermentations. Video Abstract.

Microbial containment device: A platform for comprehensive analysis of microbial metabolism without sample preparation

Metabolomics is a mainstream strategy for investigating microbial metabolism. One emerging application of metabolomics is the systematic quantification of metabolic boundary fluxes – the rates at which metabolites flow into and out of cultured cells. Metabolic boundary fluxes can capture complex metabolic phenotypes in a rapid assay, allow computational models to be built that predict the behavior of cultured organisms, and are an emerging strategy for clinical diagnostics. One advantage of quantifying metabolic boundary fluxes rather than intracellular metabolite levels is that it requires minimal sample processing. Whereas traditional intracellular analyses require a multi-step process involving extraction, centrifugation, and solvent exchange, boundary fluxes can be measured by simply analyzing the soluble components of the culture medium. To further simplify boundary flux analyses, we developed a custom 96-well sampling system—the Microbial Containment Device (MCD)—that allows water-soluble metabolites to diffuse from a microbial culture well into a bacteria-free analytical well via a semi-permeable membrane. The MCD was designed to be compatible with the autosamplers present in commercial liquid chromatography-mass spectrometry systems, allowing metabolic fluxes to be analyzed with minimal sample handling. Herein, we describe the design, evaluation, and performance testing of the MCD relative to traditional culture methods. We illustrate the utility of this platform, by quantifying the unique boundary fluxes of four bacterial species and demonstrate antibiotic-induced perturbations in their metabolic activity. We propose the use of the MCD for enabling single-step metabolomics sample preparation for microbial identification, antimicrobial susceptibility testing, and other metabolic boundary flux applications where traditional sample preparation methods are impractical.

Lessons From Insect Fungiculture: From Microbial Ecology to Plastics Degradation

Anthropogenic activities have extensively transformed the biosphere by extracting and disposing of resources, crossing boundaries of planetary threat while causing a global crisis of waste overload. Despite fundamental differences regarding structure and recalcitrance, lignocellulose and plastic polymers share physical-chemical properties to some extent, that include carbon skeletons with similar chemical bonds, hydrophobic properties, amorphous and crystalline regions. Microbial strategies for metabolizing recalcitrant polymers have been selected and optimized through evolution, thus understanding natural processes for lignocellulose modification could aid the challenge of dealing with the recalcitrant human-made polymers spread worldwide. We propose to look for inspiration in the charismatic fungal-growing insects to understand multipartite degradation of plant polymers. Independently evolved in diverse insect lineages, fungiculture embraces passive or active fungal cultivation for food, protection, and structural purposes. We consider there is much to learn from these symbioses, in special from the community-level degradation of recalcitrant biomass and defensive metabolites. Microbial plant-degrading systems at the core of insect fungicultures could be promising candidates for degrading synthetic plastics. Here, we first compare the degradation of lignocellulose and plastic polymers, with emphasis in the overlapping microbial players and enzymatic activities between these processes. Second, we review the literature on diverse insect fungiculture systems, focusing on features that, while supporting insects' ecology and evolution, could also be applied in biotechnological processes. Third, taking lessons from these microbial communities, we suggest multidisciplinary strategies to identify microbial degraders, degrading enzymes and pathways, as well as microbial interactions and interdependencies. Spanning from multiomics to spectroscopy, microscopy, stable isotopes probing, enrichment microcosmos, and synthetic communities, these strategies would allow for a systemic understanding of the fungiculture ecology, driving to application possibilities. Detailing how the metabolic landscape is entangled to achieve ecological success could inspire sustainable efforts for mitigating the current environmental crisis.

Contribution of single-cell omics to microbial ecology

Micro-organisms play key roles in various ecosystems, but many of their functions and interactions remain undefined. To investigate the ecological relevance of microbial communities, new molecular tools are being developed. Among them, single-cell omics assessing genetic diversity at the population and community levels and linking each individual cell to its functions is gaining interest in microbial ecology. By giving access to a wider range of ecological scales (from individual to community) than culture-based approaches and meta-omics, single-cell omics can contribute not only to micro-organisms' genomic and functional identification but also to the testing of concepts in ecology. Here, we discuss the contribution of single-cell omics to possible breakthroughs in concepts and knowledge on microbial ecosystems and ecoevolutionary processes.

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.

Retooling Microbiome Engineering for a Sustainable Future

Microbial communities (microbiomes) have been harnessed in biotechnology applications such as wastewater treatment and bioremediation for over a century. Traditionally, engineering approaches have focused on shaping the environment to steer microbiome function versus direct manipulation of the microbiome's metabolic network. While these selection-based approaches have proven to be invaluable for guiding bioprocess engineering, they do not enable the precise manipulation and control of microbiomes required for unlocking their full potential. Over the past 2 decades, systems biology has revolutionized our understanding of the metabolic networks driving microbiome processes, and more recently genetic engineering tools have started to emerge for nonmodel microorganisms and microbiomes. In this commentary, I discuss how systems biology approaches are being used to generate actionable understanding of microbiome functions in engineered ecosystems. I also highlight how integrating synthetic biology, automation, and machine learning can accelerate microbiome engineering to meet the sustainability challenges of the future.

Listening in on the conversation between the human gut microbiome and its host

The gut microbiome is an ecosystem. Natural selection favored microbes fit for the gut, which can utilize and convert molecules produced by the host for their own benefit. But natural selection also favored the host's mechanisms to sense and respond to the microbial ecosystem for its own benefit. We can listen in on the host-microbiome 'conversation' in the simultaneous responses of the microbiome and the host to strong perturbations. In laboratory animals a perturbation can be done for research; in human patients a perturbation can be caused by disease or therapy. Advances in metagenomics, metabolomics and computation amplify our means to listen in on the conversation between the gut microbiome and its host.

Kinetic, metabolic, and statistical analytics: addressing metabolic transport limitations among organelles and microbial communities

Microbial organisms engage in a variety of metabolic interactions. A crucial part of these interactions is the exchange of molecules between different organelles, cells, and the environment. The main forces mediating this metabolic exchange are transporters. This transport can be difficult to measure experimentally because several transport mechanisms remain opaque. However, theoretical calculations about the inputs and outputs of cells via metabolic exchanges have enabled the successful inference of the workings of intra-organismal and inter-organismal systems. Kinetic, metabolic, and statistical modeling approaches in combination with omics data are enhancing our knowledge and understanding about metabolic exchange and mass resource allocation. This model-driven analytics approach can guide effective experimental design and yield new insights into biological function and control.

Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes

Microbiomes are complex and ubiquitous networks of microorganisms whose seemingly limitless chemical transformations could be harnessed to benefit agriculture, medicine, and biotechnology. The spatial and temporal changes in microbiome composition and function are influenced by a multitude of molecular and ecological factors. This complexity yields both versatility and challenges in designing synthetic microbiomes and perturbing natural microbiomes in controlled, predictable ways. In this review, we describe factors that give rise to emergent spatial and temporal microbiome properties and the meta-omics and computational modeling tools that can be used to understand microbiomes at the cellular and system levels. We also describe strategies for designing and engineering microbiomes to enhance or build novel functions. Throughout the review, we discuss key knowledge and technology gaps for elucidating the networks and deciphering key control points for microbiome engineering, and highlight examples where multiple omics and modeling approaches can be integrated to address these gaps.

Reference values for intake of six types of soluble and insoluble fibre in healthy UK inhabitants based on the UK Biobank data

OBJECTIVE

To obtain a set of reference values for the intake of different types of dietary fibre in a healthy UK population.

DESIGN

This descriptive cross-sectional study used the UK Biobank data to estimate the dietary patterns of healthy individuals. Data on fibre content in different foods were used to calculate the reference values which were then calibrated using real-world data on total fibre intake.

SETTING

UK Biobank is a prospective cohort study of over 500 000 individuals from across the United Kingdom with the participants aged between 40 and 69 years.

PARTICIPANTS

UK Biobank contains information on over 500 000 participants. This study was performed using the data on 19 990 individuals (6941 men, 13 049 women) who passed stringent quality control and filtering procedures and had reported above-zero intake of the analysed foods.

RESULTS

A set of reference values for the intake of six different types of soluble and insoluble fibres (cellulose, hemicelluloses, pectin and lignin), including the corresponding totals, was developed and calibrated using real-world data.

CONCLUSIONS

To our knowledge, this is the first study to establish specific reference values for the intake of different types of dietary fibre. It is well known that effects exerted by different types of fibre both directly and through modulation of microbiota are numerous. Conceivably, a deficit or excess intake of specific types of dietary fibre may detrimentally affect human health. Filling this knowledge gap opens new avenues for research in discussion in studies of nutrition and microbiota and offers valuable tools for practitioners worldwide.

Metabolic Modeling to Interrogate Microbial Disease: A Tale for Experimentalists

The explosion of microbiome analyses has helped identify individual microorganisms and microbial communities driving human health and disease, but how these communities function is still an open question. For example, the role for the incredibly complex metabolic interactions among microbial species cannot easily be resolved by current experimental approaches such as 16S rRNA gene sequencing, metagenomics and/or metabolomics. Resolving such metabolic interactions is particularly challenging in the context of polymicrobial communities where metabolite exchange has been reported to impact key bacterial traits such as virulence and antibiotic treatment efficacy. As novel approaches are needed to pinpoint microbial determinants responsible for impacting community function in the context of human health and to facilitate the development of novel anti-infective and antimicrobial drugs, here we review, from the viewpoint of experimentalists, the latest advances in metabolic modeling, a computational method capable of predicting metabolic capabilities and interactions from individual microorganisms to complex ecological systems. We use selected examples from the literature to illustrate how metabolic modeling has been utilized, in combination with experiments, to better understand microbial community function. Finally, we propose how such combined, cross-disciplinary efforts can be utilized to drive laboratory work and drug discovery moving forward.

Enzymatic and non-enzymatic functional attributes of plant microbiome

Microbiome plays an important role in plant growth and adaptation to various environmental conditions. The cross-talk between host plant and microbes (including microbe-microbe interactions) plays a crucial role in shaping the microbiome. Recent studies have highlighted that plant microbiome is enriched in genes encoding enzymes and natural products. Several novel antimicrobial compounds, bioactive natural products and lytic/degrading enzymes with industrial implications are being identified from the microbiome. Moreover, advancements in metagenomics and culture techniques are facilitating the development of synthetic microbial communities to promote sustainable agriculture. We discuss the recent advancements, opportunities and challenges in harnessing the full potential of plant microbiome.

Metabolic modelling approaches for describing and engineering microbial communities

Microbes do not live in isolation but in microbial communities. The relevance of microbial communities is increasing due to growing awareness of their influence on a huge number of environmental, health and industrial processes. Hence, being able to control and engineer the output of both natural and synthetic communities would be of great interest. However, most of the available methods and biotechnological applications involving microorganisms, both in vivo and in silico, have been developed in the context of isolated microbes. In vivo microbial consortia development is extremely difficult and costly because it implies replicating suitable environments in the wet-lab. Computational approaches are thus a good, cost-effective alternative to study microbial communities, mainly via descriptive modelling, but also via engineering modelling. In this review we provide a detailed compilation of examples of engineered microbial communities and a comprehensive, historical revision of available computational metabolic modelling methods to better understand, and rationally engineer wild and synthetic microbial communities.

Secondary metabolites of Bacillus subtilis impact the assembly of soil-derived semisynthetic bacterial communities

Secondary metabolites provide Bacillus subtilis with increased competitiveness towards other microorganisms. In particular, nonribosomal peptides (NRPs) have an enormous antimicrobial potential by causing cell lysis, perforation of fungal membranes, enzyme inhibition, or disruption of bacterial protein synthesis. This knowledge was primarily acquired in vitro when B. subtilis was competing with other microbial monocultures. However, our understanding of the true ecological role of these small molecules is limited. In this study, we have established soil-derived semisynthetic mock communities containing 13 main genera and supplemented them with B. subtilis P5_B1 WT, the NRP-deficient strain sfp, or single-NRP mutants incapable of producing surfactin, plipastatin, or bacillaene. Through 16S amplicon sequencing, it was revealed that the invasion of NRP-producing B. subtilis strains had no major impact on the bacterial communities. Still, the abundance of the two genera Lysinibacillus and Viridibacillus was reduced. Interestingly, this effect was diminished in communities supplemented with the NRP-deficient strain. Growth profiling of Lysinibacillus fusiformis M5 exposed to either spent media of the B. subtilis strains or pure surfactin indicated the sensitivity of this strain towards the biosurfactant surfactin. Our study provides a more in-depth insight into the influence of B. subtilis NRPs on semisynthetic bacterial communities and helps to understand their ecological role.

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

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

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.