Metabolic interaction models recapitulate leaf microbiota ecology

Integrating ecological and evolutionary frameworks for SynCom success

Use of synthetic microbial communities (SynComs) is a promising approach that harnesses nature-based solutions to support soil fertility and food security, mitigate climate change impacts, and restore terrestrial ecosystems. Several microbial products are in the market, and many others are at different stages of development and commercialization. Yet, we are still far from being able to fully harness the potential and successful applications of such biotechnological tools. The limited field efficiency and efficacy of SynComs have significantly constrained commercial opportunities, resulting in market growth falling below expectations. To overcome these challenges and manage expectations, it is critical to address current limitations, failures, and potential environmental consequences of SynComs. In this Viewpoint, we explore how using multiple eco-evolutionary theories can inform SynCom design and success. We further discuss the current status of SynComs and identify the next steps needed to develop and deploy the next generation of tools to boost their ability to support multiple ecosystem services, including food security and environmental sustainability.

Automated adjustment of metabolic niches enables the control of natural and engineered microbial co-cultures

Much attention has focused on understanding microbial interactions leading to stable co-cultures. In this work, substrate pulsing was performed to promote better control of the metabolic niches (MNs) corresponding to each species, leading to the continuous co-cultivation of diverse microbial organisms. We used a cell-machine interface, which allows adjustment of the temporal profile of two MNs according to a rhythm, ensuring the successive growth of two species, in our case, a yeast and a bacterium. The resulting approach, called 'automated adjustment of metabolic niches' (AAMN), was effective for stabilizing both cooperative and competitive co-cultures. AAMN can be considered an enabling technology for the deployment of co-cultures in bioprocesses, demonstrated here based on the continuous bioproduction of p-coumaric acid. The data accumulated suggest that AAMN could be used not only for a wider range of biological systems, but also to gain fundamental insights into microbial interaction mechanisms.

Seed-borne bacteria drive wheat rhizosphere microbiome assembly via niche partitioning and facilitation

Microbial communities play a crucial role in supporting plant health and productivity. Reproducible, natural plant-associated microbiomes can help disentangle microbial dynamics across time and space. Here, using a sequential propagation strategy, we generated a complex and reproducible wheat rhizosphere microbiome (RhizCom) to study successional dynamics and interactions between the soil and heritable seed-borne rhizosphere microbiomes (SbRB) in a microcosm. Using 16S rRNA sequencing and genome-resolved shotgun metagenomics, we find that SbRB surpassed native soil microbes as the dominant rhizosphere-associated microbiome source. SbRB genomes were enriched in host-associated traits including degradation of key saccharide (niche partitioning) and cross-feeding interactions that supported partner strains (niche facilitation). In vitro co-culture experiments confirmed that helper SbRB strains facilitated the growth of partner bacteria on disaccharides as sole carbon source. These results reveal the importance of seed microbiota dynamics in microbial succession and community assembly, which could inform strategies for crop microbiome manipulation.

New insights in metabolism modelling to decipher plant-microbe interactions

Plant disease outbreaks, exacerbated by climate change, threaten food security and environmental sustainability world-wide. Plants interact with a wide range of microorganisms. The quest for resilient agriculture requires a deep insight into the molecular and ecological interplays between plants and their associated microbial communities. Omics methods, by profiling entire molecular sets, have shed light on these complex interactions. Nonetheless, deciphering the relationships among thousands of molecular components remains a formidable challenge, and studies that integrate these components into cohesive biological networks involving plants and associated microbes are still limited. Systems biology has the potential to predict the effects of biotic and abiotic perturbations on these networks. It is therefore a promising framework for addressing the full complexity of plant-microbiome interactions.

Host-virus coevolution drives soil microbial function succession along a millennium land reclamation chronosequence

INTRODUCTION

Gene exchange between viruses and hosts plays an important role in driving virus-host coevolution, enabling adaptation of both viruses and hosts to environmental changes. However, the mechanisms and functional significance of virus-host gene exchanges over long-term scales remain largely unexplored.

OBJECTIVE

The present study aimed to gain insights into the role of viruses in virus-host interactions and coevolution by monitoring virome dynamics along a millennium-long land reclamation chronosequence.

METHODS

We collected 24 soil samples from 8 stages of a millennium-long land reclamation chronosequence, including non-reclamation, and reclamation periods of 10, 50, 100, 300, 500, 700, and 1000 years. We characterized their metagenomes, and identified DNA viruses within these metagenomes.

RESULTS

Our findings reveal a significant shift in viral community composition after 50 years of land reclamation, but soil viral diversity reached a stable phase approximately 300 years after the initial reclamation. Analysis of the virus-host network showed a scale-free degree distribution and a reduction in complexity over time, with generalist viruses emerging as key facilitators of horizontal gene transfer.

CONCLUSION

These findings highlight the integral role of viruses, especially generalist types, in mediating gene exchanges between viruses and hosts, thereby influencing the coevolutionary dynamics in soil ecosystems over significant timescales. This study offers novel insights into long-term virus-host interactions, showing how the virome responds to environmental changes, driving shifts in various microbial functions in reclaimed land.

Biotic resistance predictably shifts microbial invasion regimes

Invading new territory is a central aspect of the microbial lifestyle. However, invading microbes rarely find novel territories uninhabited; resident microbes can interact with the newcomers and, in many cases, impede their invasion - an effect known as 'biotic resistance'. Accordingly, invasions are shaped by the interplay between dispersal and resistance. However, these two factors are difficult to disentangle or manipulate in natural systems, making their interplay challenging to understand. To address this challenge, we track microbial invasions in the lab over space and time - first in a model system of two interacting microbes, then in a multi-strain system involving a pathogen invading resident communities. In the presence of biotic resistance, we observe three qualitatively different invasion regimes: 'consistent', 'pulsed', and 'pinned', where, in the third regime, strong biotic resistance stalls the invasion entirely despite ongoing invader dispersal. These rich invasion dynamics could be qualitatively predicted with a simple, parameter-free framework that ignores individual species interactions, even for rather complex communities. Moreover, we show that this simple framework could accurately predict simulated invasions from different mechanistic models, indicating its broad applicability. Our work offers an understanding of how biotic resistance impacts invasions and introduces a predictive tool to identify invasion-resistant communities.

Plant pathogens, microbiomes, and soil health

Healthy soil is vital for ecosystem sustainability and global food security. However, anthropogenic activities that promote intensive agriculture, landscape and biodiversity homogenization, and climate change disrupt soil health. The soil microbiome is a critical component of healthy soils, and increasing evidence suggests that soils with low diversity or homogenized microbial systems are more susceptible to soil pathogen invasion, but the extent and mechanisms that increase the threat of pathogen invasion (i.e., increase in prevalence of existing species and introduction of new species) remain unclear. This article aims to fill this knowledge gap by synthesizing the literature and providing novel insights for the scientific community and policy advisors. We also present the current and future global distribution of some dominant soil-borne pathogens. We argue that an improved understanding of the interplay between the soil microbiome, soil health, host, and pathogen distribution, and their responses to environmental changes is urgently needed to ensure the future of productive farms, safe food, sustainable environments, and holistic global well-being.

The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions

Researchers have invested much effort into developing kinetic models due to their ability to capture dynamic behaviors, transient states, and regulatory mechanisms of metabolism, providing a detailed and realistic representation of cellular processes. Historically, the requirements for detailed parametrization and significant computational resources created barriers to their development and adoption for high-throughput studies. However, recent advancements, including the integration of machine learning with mechanistic metabolic models, the development of novel kinetic parameter databases, and the use of tailor-made parametrization strategies, are reshaping the field of kinetic modeling. In this Review, we discuss these developments and offer future directions, highlighting the potential of these advances to drive progress in systems and synthetic biology, metabolic engineering, and medical research at an unprecedented scale and pace.

A critical review on bioaugmentation assisted anaerobic digestion for methane production: Performances, microbiome-functionalities and challenges

Bioaugmentation technology is considered as a straightforward approach to improve anaerobic digestion performances, with advantages of high efficiency and sustainability. However, the mechanisms and challenges of bioaugmentation in anaerobic digestion have yet to been well reviewed. In this review, the advantages of bioaugmentation in anaerobic digestion are systematically identified and discussed, covering enhancing anaerobic digestion process, relieving toxic inhibition of ammonia, and overcoming limitation of psychrophilic anaerobic digestion. This review find that the underlying mechanisms of bioaugmentation enhancing anaerobic digestion are the improvement of microbial community metabolism activity, interspecies electron transfer, and microbial adaptability to environment stress. In addition, future challenges and research directions are discussed from theoretical and practical perspectives, including preparation of bioaugmentation microorganisms, immobilization of bioaugmentation microorganisms, and economic feasibility of bioaugmentation technology. This review contributes to understanding the positive effect of bioaugmentation on anaerobic digestion and promoting the applicability of bioaugmentation technology in anaerobic digestion.

The community succession mechanisms and interactive dynamics of microorganisms under high salinity and alkalinity conditions during composting

Microorganisms drive organic matter degradation and humification during composting. However, the mechanisms underlying microbial community succession and their interactions under saline-alkali stress are poorly understood. In this study, we investigated the microbial community assembly processes and microbial niche dynamics during composting in the high-saline-alkaline region. The niche breadth of the microbial community expanded from 5.8 to 15 and salt-alkali conditions alleviation prompted a shift in microbial community assembly towards stochastic processes. Alkalinity (R = 69.08%) and available phosphorus (AP) (R = 45.70%) are identified as the primary environmental stress factors. Salinity primarily impacted the niche breadth, while alkalinity predominantly determined the assembly processes of microorganisms. The degradation of organic matter in high-temperature environments enhanced the release of AP, altering the processes of microbial community assembly and driving niche differentiation within the microbial community. The abundant taxa actively responded to the changes in the environmental conditions, while the rare taxa maintained the community stability by expanding their ecological niches. The interactions between microorganisms are mainly based on synergism. The native microorganisms, such as Alcanivorax, Corynebacterium, and Rhodohalobacter, played a key role in promoting compost maturity. They tolerated the high-salinity and alkaline environments and also withstood high temperatures. This study revealed for the first time the succession mechanisms and interaction characteristics of microbial communities under salinity and temperature stress, providing theoretical guidance for microbial inoculation during the composting of high-saline and alkaline organic waste.

Comprehensive evaluation of the capacities of microbial cell factories

Systems metabolic engineering is facilitating the development of high-performing microbial cell factories for producing chemicals and materials. However, constructing an efficient microbial cell factory still requires exploring and selecting various host strains, as well as identifying the best-suited metabolic engineering strategies, which demand significant time, effort, and costs. Here, we comprehensively evaluate the capacities of various microbial cell factories and propose strategies for systems metabolic engineering steps, including host strain selection, metabolic pathway reconstruction, and metabolic flux optimization. We analyze the metabolic capacities of five representative industrial microorganisms as cell factories for the production of 235 different bio-based chemicals and suggest the most suitable host strain for the corresponding chemical production. To improve the innate metabolic capacity by constructing more efficient metabolic pathways, heterologous metabolic reactions, and cofactor exchanges are systematically analyzed. Additionally, we present metabolic engineering strategies, which include up- and down-regulation target reactions, for the improved production of chemicals. Altogether, this study will serve as a comprehensive resource for the systems metabolic engineering of microorganisms in the bio-based production of chemicals.

Exploring the plant microbiome: A pathway to climate-smart crops

The advent of semi-dwarf crop varieties and fertilizers during the Green Revolution boosted yields and food security. However, unintended consequences such as environmental pollution and greenhouse gas emissions underscore the need for strategies to mitigate these impacts. Manipulating rhizosphere microbiomes, an aspect overlooked during crop domestication, offers a pathway for sustainable agriculture. We propose that modulating plant microbiomes can help establish "climate-smart crops" that improve yield and reduce negative impacts on the environment. Our proposed framework integrates plant genotype, root exudates, and microbes to optimize nutrient cycling, improve stress resilience, and expedite carbon sequestration. Integrating unselected ecological traits into crop breeding can promote agricultural sustainability, illuminating the nexus between plant genetics and ecosystem functioning.

Incorporating microbiome analyses can enhance conservation of threatened species and ecosystem functions

Conservation genomics is a rapidly growing subdiscipline of conservation biology that uses genome-wide information to inform management of biodiversity at all levels. Such efforts typically focus on species or systems of conservation interest, but rarely consider associated microbes. At least three major approaches have been used to study how microorganisms broadly contribute to conservation areas: (1) diversity surveys map out microbial species distribution patterns in a variety of hosts, natural environments or regions; (2) functional surveys associate microbial communities with factors of interest, such as host health, symbiotic interactions, environmental characteristics, ecosystem processes, and biological invasions; and (3) manipulative experiments examine the response of changes to microbial communities or determine the functional roles of specific microbes within hosts or communities by adding, removing, or genetically modifying microbes. In practice, multiple approaches are often applied simultaneously. The results from all three conservation genomics approaches can be used to help design practical interventions and improve management actions, some of which we highlight below. However, experimental manipulations allow for more robust causal inferences and should be the ultimate goal of future work. Here we discuss how further integration of microbial research of a host's microbiome and of free living microbes into conservation biology will be an essential advancement for conservation of charismatic organisms and ecosystem functions in light of ongoing global environmental change.

Individual leaf microbiota tunes a genetic regulatory network to promote leaf growth

In natural ecosystems, microbes have the ability to stably colonize plant leaves, overcoming the fluctuating environmental conditions that the leaves represent. How the phyllosphere microbiota influences the growth of individual leaves remains poorly understood. Here, we investigate the growth of Zea mays (maize/corn) leaves in plants grown in three soils with differing amounts of nutrients and water and identify a leaf-growth-promoting effect driven by the leaf microbiota, which we also validate in field studies. We built and used a bacterial strain collection for recolonization experiments to study the microbiota-mediated mechanisms involved in leaf growth promotion. We demonstrate that prevalent bacteria inhabiting young leaves promote individual leaf growth. Using transcriptomic analyses, we reveal a defense-related genetic network that integrates the beneficial effect of the phyllosphere microbiota into the leaf development program. We demonstrate that the individual leaf microbiota differentially represses this genetic network to modulate the growth-defense trade-off at single-leaf resolution.

Sulfur traits in the plant microbiome: implications for sustainable agriculture

Owing to its biochemical flexibility, sulfur (S) is uniquely poised to fulfill versatile roles in plant-microbe interactions - impacting their metabolism with significant consequences for plant health and the global S cycle. We present evidence that the diversity of S-metabolic genes in plant-associated microbiomes (phytobiomes) is underappreciated, and plant niches are hotspots of bacterial S-metabolism with implications for S emissions. Building upon emerging findings, we posit that coordination of S-metabolism between plants and phytobiomes is a common mechanism for plant-microbe homeostasis and agriculturally beneficial microbial services. Finally, we summarize strategies to harness S-metabolic traits of plants and phytobiomes to sustainably enhance agricultural productivity under the stresses associated with climate change.

Root exudates and microbial metabolites: signals and nutrients in plant-microbe interactions

Plant roots meticulously select and attract particular microbial taxa from the surrounding bulk soil, thereby establishing a specialized and functionally diverse microbial community within the rhizosphere. Rhizosphere metabolites, including root exudates and microbial metabolites, function as both signals and nutrients that govern the assembly of the rhizosphere microbiome, playing crucial roles in mediating communications between plants and microbes. The environment and their feedback loops further influence these intricate interactions. However, whether and how specific metabolites shape plant-microbe interactions and facilitate diverse functions remains obscure. This review summarizes the current progress in plant-microbe communications mediated by chemical compounds and their functions in plant fitness and ecosystem functioning. Additionally, we raise some prospects on future directions for manipulating metabolite-mediated plant-microbe interactions to enhance crop productivity and health. Unveiling the biological roles of specific metabolites produced by plants and microbes will bridge the gap between fundamental research and practical applications.

Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine

Nontyphoidal Salmonella strains (NTS) are among the most common foodborne enteropathogens and constitute a major cause of global morbidity and mortality, imposing a substantial burden on global health. The increasing antibiotic resistance of NTS bacteria has attracted a lot of research on understanding their modus operandi during infection. Growth in the gut lumen is a critical phase of the NTS infection. This might offer opportunities for intervention. However, the metabolic richness of the gut lumen environment and the inherent complexity and robustness of the metabolism of NTS bacteria call for modeling approaches to guide research efforts. In this study, we reconstructed a thermodynamically constrained and context-specific genome-scale metabolic model (GEM) for S. Typhimurium SL1344, a model strain well-studied in infection research. We combined sequence annotation, optimization methods and in vitro and in vivo experimental data. We used GEM to explore the nutritional requirements, the growth limiting metabolic genes, and the metabolic pathway usage of NTS bacteria in a rich environment simulating the murine gut. This work provides insight and hypotheses on the biochemical capabilities and requirements of SL1344 beyond the knowledge acquired through conventional sequence annotation and can inform future research aimed at better understanding NTS metabolism and identifying potential targets for infection prevention.

Plant Diversity Reduces the Risk of Antibiotic Resistance Genes in Agroecosystems

Despite advances in dispersal mechanisms and risk assessment of antibiotic resistance genes (ARGs), how plants influence ARG contamination in agricultural soils remains underexplored. Here, the impacts of plant species and diversity on ARGs and mobile genetic elements (MGEs) in three agricultural soils are comprehensively investigated in a pot experiment. The results indicate that increased plant diversity reduces ARGs and MGEs abundance by 19.2%-51.2%, whereas plant species exhibit inconsistent and soil-dependent effects. Potential bacterial hosts harboring abundant ARGs have greater relative abundance than nonhosts, and both their richness and cumulative relative abundance are reduced by plant diversity. Notably, hosts inhibited by plant diversity present a greater relative abundance than the other hosts. The enriched compounds in root exudates due to plant diversity play a more important role in the metabolic network and contribute to rebalancing of the abundance of potential hosts and nonhosts. An independent test using pure organics reveals that higher resource diversity, resulting from increased plant diversity, reduces the relative abundance and mobility of abundant and high-risk ARGs. This study highlights the resource-mediated mitigation of the risks posed by ARG contamination and indicates that ensuring plant and resource diversity is a promising strategy for controlling ARGs in agroecosystems.

The role of bacterial metabolism in human gut colonization

Can we anticipate the emergence of the next pandemic antibiotic-resistant bacterial clone? Addressing such an ambitious question relies on our ability to comprehensively understand the ecological and epidemiological factors fostering the evolution of high-risk clones. Among these factors, the ability to persistently colonize and thrive in the human gut is crucial for most high-risk clones. Nonetheless, the causes and mechanisms facilitating successful gut colonization remain obscure. Here, we review recent evidence that suggests that bacterial metabolism plays a pivotal role in determining the ability of high-risk clones to colonize the human gut. Subsequently, we outline novel approaches that enable the exploration of microbial metabolism at an unprecedented scale and level of detail. A thorough understanding of the constraints and opportunities of bacterial metabolism in gut colonization will foster our ability to predict the emergence of high-risk clones and take appropriate containment strategies.

Composing a microbial symphony: synthetic communities for promoting plant growth

Plant microbiomes are pivotal for host development, influencing growth, health, fitness, and evolution, and have emerged as promising resources for sustainable agriculture. However, leveraging these microbiomes to improve crop yield and resilience is challenging due to the huge diversity of plant-associated and soil microorganisms and their intricate interactions. Recently, synthetic microbial communities (SynComs) have been exploited as a reductionist approach to harness microbial benefits and to understand multispecies interactions. Additionally, the advanced functionality of SynComs promises to surpass classic single-strain-based biosolutions. Nevertheless, challenges remain in designing customized, robust, and predictable SynComs for agronomic use. Here, we synthesize and discuss the logical and implemented approaches used to design and assemble SynComs, highlighting important principles, challenges, and trends in utilizing SynComs as alternatives to agrochemicals.

Modeling bacterial interactions uncovers the importance of outliers in the coastal lignin-degrading consortium

Lignin, as the abundant carbon polymer, is essential for carbon cycle and biorefinery. Microorganisms interact to form communities for lignin biodegradation, yet it is a challenge to understand such complex interactions. Here, we develop a coastal lignin-degrading bacterial consortium (LD), through "top-down" enrichment. Sequencing and physiological analyses reveal that LD is dominated by the lignin degrader Pluralibacter gergoviae (>98%), with additional rare non-degraders. Interestingly, LD, cultured in lignin-MB medium, significantly enhances cell growth and lignin degradation as compared to P. gergoviae alone, implying a role of additional outliers. Using genome-scale metabolic models, metabolic profiling and culture experiments, modeling of inter-species interactions between P. gergoviae, Vibrio alginolyticus, Aeromonas hydrophila and Shewanella putrefaciens, unravels cross-feeding of amino acids, organic acids and alcohols between the degrader and non-degraders. Furthermore, the sub-population ratio is essential to enforce the synergy. Our study highlights the unrecognized role of outliers in lignin degradation.

Environment-Organism Feedbacks Drive Changes in Ecological Interactions

Ecological interactions are foundational to our understanding of community composition and function. While interactions are known to change depending on the environmental context, it has generally been assumed that external environmental factors are responsible for driving these dependencies. Here, we derive a theoretical framework which instead focuses on how intrinsic environmental changes caused by the organisms themselves alter interaction values. Our central concept is the 'instantaneous interaction', which captures the feedback between the current environmental state and organismal growth, generating spatiotemporal context-dependencies as organisms modify their environment over time and/or space. We use small microbial communities to illustrate how this framework can predict time-dependencies in a toxin degradation system, and relate time- and spatial-dependencies in crossfeeding communities. By re-centring the relationship between organisms and their environment, our framework predicts the variations in interactions wherever intrinsic, organism-driven environmental change dominates over external drivers.

Plant microbiota feedbacks through dose-responsive expression of general non-self response genes

The ability of plants to perceive and react to biotic and abiotic stresses is critical for their health. We recently identified a core set of genes consistently induced by members of the leaf microbiota, termed general non-self response (GNSR) genes. Here we show that GNSR components conversely impact leaf microbiota composition. Specific strains that benefited from this altered assembly triggered strong plant responses, suggesting that the GNSR is a dynamic system that modulates colonization by certain strains. Examination of the GNSR to live and inactivated bacteria revealed that bacterial abundance, cellular composition and exposure time collectively determine the extent of the host response. We link the GNSR to pattern-triggered immunity, as diverse microbe- or danger-associated molecular patterns cause dynamic GNSR gene expression. Our findings suggest that the GNSR is the result of a dose-responsive perception and signalling system that feeds back to the leaf microbiota and contributes to the intricate balance of plant-microbiome interactions.

Sowing success: ecological insights into seedling microbial colonisation for robust plant microbiota engineering

Manipulating the seedling microbiota through seed or soil inoculations has the potential to improve plant health. Mixed in-field results have been attributed to a lack of consideration for ecological processes taking place during seedling microbiota assembly. In this opinion article, we (i) assess the contribution of ecological processes at play during seedling microbiota assembly (e.g., propagule pressure and priority effects); (ii) investigate how life history theory can help us identify microbial traits involved in successful seedling colonisation; and (iii) suggest how different plant microbiota engineering methods could benefit from a greater understanding of seedling microbiota assembly processes. Finally, we propose several research hypotheses and identify outstanding questions for the plant microbiota engineering community.

Differential Responses of Methylobacterium and Sphingomonas Species to Multispecies Interactions in the Phyllosphere

The leaf surface, known as the phylloplane, presents an oligotrophic and heterogeneous environment due to its topography and uneven distribution of resources. Although it is a challenging environment, leaves support abundant bacterial communities that are spatially structured. However, the factors influencing these spatial distribution patterns are not well understood. To study the changes in population density and spatial distribution of bacteria in synthetic communities, the behaviour of two common bacterial groups in the Arabidopsis thaliana leaf microbiota-Methylobacterium (methylobacteria) and Sphingomonas (sphingomonads)-was examined. Using synthetic communities consisting of two or three species, the hypothesis was tested that the presence of a third species affects the density and spatial interaction of the other two species. Results indicated that methylobacteria exhibit greater sensitivity to changes in population densities and spatial patterns, with higher intra-genus competition and lower densities and aggregation compared to sphingomonads. Pairwise comparisons were insufficient to explain the shifts observed in three-species communities, suggesting that higher-order interactions influence the structuring of complex communities. This emphasises the role of multispecies interactions in determining spatial patterns and community dynamics on the phylloplane.

A mechanistic framework for complex microbe-host symbioses

Virtually all multicellular organisms on Earth live in symbiotic associations with complex microbial communities: the microbiome. This ancient relationship is of fundamental importance for both the host and the microbiome. Recently, the analyses of numerous microbiomes have revealed an incredible diversity and complexity of symbionts, with different mechanisms identified as potential drivers of this diversity. However, the interplay of ecological and evolutionary forces generating these complex associations is still poorly understood. Here we explore and summarise the suite of ecological and evolutionary mechanisms identified as relevant to different aspects of microbiome complexity and diversity. We argue that microbiome assembly is a dynamic product of ecology and evolution at various spatio-temporal scales. We propose a theoretical framework to classify mechanisms and build mechanistic host-microbiome models to link them to empirical patterns. We develop a cohesive foundation for the theoretical understanding of the combined effects of ecology and evolution on the assembly of complex symbioses.

From synthetic communities to synthetic ecosystems: exploring causalities in plant-microbe-environment interactions

The plant microbiota research field has rapidly shifted from efforts aimed at gaining a descriptive understanding of microbiota composition to a focus on acquiring mechanistic insights into microbiota functions and assembly rules. This evolution was driven by our ability to establish comprehensive collections of plant-associated microbes and to reconstruct meaningful microbial synthetic communities (SynComs). We argue that this powerful deconstruction-reconstruction strategy can be used to reconstitute increasingly complex synthetic ecosystems (SynEcos) and mechanistically understand high-level biological organization. The transitioning from simple to more advanced, fully tractable and programmable gnotobiotic SynEcos is ongoing and aims at rationally simplifying natural ecosystems by engineering them. Such reconstitution ecology approaches represent an untapped strategy for bridging the gap between ecology and functional biology and for unraveling plant-microbiota-environment mechanisms that modulate ecosystem health, assembly, and functioning.

Improving genome-scale metabolic models of incomplete genomes with deep learning

Deciphering microbial metabolism is essential for understanding ecosystem functions. Genome-scale metabolic models (GSMMs) predict metabolic traits from genomic data, but constructing GSMMs for uncultured bacteria is challenging due to incomplete metagenome-assembled genomes, resulting in many gaps. We introduce the deep neural network guided imputation of reactomes (DNNGIOR), which uses AI to improve gap-filling by learning from the presence and absence of metabolic reactions across diverse bacterial genomes. Key factors for prediction accuracy are: (1) reaction frequency across all bacteria and (2) phylogenetic distance of the query to the training genomes. DNNGIOR predictions achieve an average F1 score of 0.85 for reactions present in over 30% of training genomes. DNNGIOR guided gap-filling was 14 times more accurate for draft reconstructions and 2-9 times for curated models than unweighted gap-filling.

Construction of a synthetic anaerobic dechlorination microbiome to degrade chlorinated ethenes by application of metabolic interactions principle

Bioaugmentation is a bioremediation approach to treat groundwater contaminated with chlorinated ethenes, but currently it faces challenges such as poor microbiome stability and effectiveness, due to blind species integration and metabolic inhibition. The objective of this study was to create a controllable and functionally stable microbial community for dichlorination application. For this, we utilized targeted screening to identify dechlorinating bacteria from contaminated groundwater, that in combination would form an anaerobic dechlorination microbial community with stabilizing metabolic interactions between the constituents. The results showed that two organohalide-respiring bacterial (OHRB) species were isolated, and these were identified as Enterobacter bugandensis X4 and Enterobacter sichuanensis C4. Upon co-cultivation with lactic acid as the carbon source, the strains demonstrated metabolic interactions and synergistic dehalogenation ability towards trichloroethene (TCE). It was further demonstrated that the functional microbiome constructed with the strains was stable over time and exhibited a robust TCE degradation rate of 80.85% at 13.13 mg/L TCE within 10 days. Additionally, the complete conversion of TCE was achieved through microbiome bioaugmentation, this augmented microbiome increased the degradation rate towards 52.55 mg/L TCE by approximately 30% within 6 days. Additionally, bioaugmentation stimulated the growth of indigenous OHRB, such as Dehalobacter and Desulfovibrio. It also promoted a positive succession of the microbial community. These findings offer valuable insights into the microbial remediation of chlorinated ethenes-contaminated groundwater and offers novel ideas for the construction of an artificial functional microbiome.

A systematic discussion and comparison of the construction methods of synthetic microbial community

Synthetic microbial community has widely concerned in the fields of agriculture, food and environment over the past few years. However, there is little consensus on the method to synthetic microbial community from construction to functional verification. Here, we review the concept, characteristics, history and applications of synthetic microbial community, summarizing several methods for synthetic microbial community construction, such as isolation culture, core microbiome mining, automated design, and gene editing. In addition, we also systematically summarized the design concepts, technological thresholds, and applicable scenarios of various construction methods, and highlighted their advantages and limitations. Ultimately, this review provides four efficient, detailed, easy-to-understand and -follow steps for synthetic microbial community construction, with major implications for agricultural practices, food production, and environmental governance.

Enhanced growth of wheat in contaminated fields via synthetic microbiome as revealed by genome-scale metabolic modeling

The relationship between plants and soil microbial communities is complex and subtle, with microbes playing a crucial role in plant growth. Autochthonous bioaugmentation and nutrient biostimulation are promising bioremediation methods for herbicides in contaminated agricultural soils, but how microbes interact to promote biodegradation and plant growth on barren fields, especially in response to the treatment of the herbicide bromoxynil after wheat seedlings, remains poorly understood. In this study, we explored the microbial community reassembly process from the three-leaf stage to the tillering stage of wheat and put forward the idea of using the overlapping results of three methods (network Zi-Pi analysis, LEfSe analysis, and Random Forest analysis) as keystones for the simplification and optimization of key microbial species in the soil. Then we used genome-scale metabolic models (GSMMs) to design a targeted synthetic microbiome for promoting wheat seedling growing. The results showed that carbon source was more helpful in enriching soil microbial diversity and promoting the role of functional microbial communities, which facilitated the degradation of bromoxynil. Designed a multifunctional synthetic consortium consisting of seven non-degraders which unexpectedly assisted in the degradation of indigenous bacteria, which increased the degradation rate of bromoxynil by 2.05 times, and when adding nutritional supplementation, it increased the degradation rate by 3.65 times. In summary, this study provides important insights for rational fertilization and precise microbial consortium management to improve plant seedling growth in contaminated fields.

Community standards and future opportunities for synthetic communities in plant-microbiota research

Harnessing beneficial microorganisms is seen as a promising approach to enhance sustainable agriculture production. Synthetic communities (SynComs) are increasingly being used to study relevant microbial activities and interactions with the plant host. Yet, the lack of community standards limits the efficiency and progress in this important area of research. To address this gap, we recommend three actions: (1) defining reference SynComs; (2) establishing community standards, protocols and benchmark data for constructing and using SynComs; and (3) creating an infrastructure for sharing strains and data. We also outline opportunities to develop SynCom research through technical advances, linking to field studies, and filling taxonomic blind spots to move towards fully representative SynComs.

Leaf abaxial and adaxial surfaces differentially affect the interaction of Botrytis cinerea across several eudicots

Eudicot plant species have leaves with two surfaces: the lower abaxial and the upper adaxial surface. Each surface varies in a diversity of components and molecular signals, resulting in potentially different degrees of resistance to pathogens. We tested how Botrytis cinerea, a necrotroph fungal pathogen, interacts with the two different leaf surfaces across 16 crop species and 20 Arabidopsis genotypes. This showed that the abaxial surface is generally more susceptible to the pathogen than the adaxial surface. In Arabidopsis, the differential lesion area between leaf surfaces was associated with jasmonic acid (JA) and salicylic acid (SA) signaling and differential induction of defense chemistry across the two surfaces. When infecting the adaxial surface, leaves mounted stronger defenses by producing more glucosinolates and camalexin defense compounds, partially explaining the differential susceptibility across surfaces. Testing a collection of 96 B. cinerea strains showed the genetic heterogeneity of growth patterns, with a few strains preferring the adaxial surface while most are more virulent on the abaxial surface. Overall, we show that leaf-Botrytis interactions are complex with host-specific, surface-specific, and strain-specific patterns.

Wheat domestication alters root metabolic functions to drive the assembly of endophytic bacteria

The domestication process progressively differentiated wild relatives from modern cultivars, thus impacting plant-associated microorganisms. Endophytic bacterial communities play vital roles in plant growth, development, and health, which contribute to the crop's sustainable development. However, how plant domestication impacts endophytic bacterial communities and relevant root exudates in wheat remains unclear. First, we have observed that the domestication process increased the root endophytic microbial community diversity of wheat while decreasing functional diversity. Second, domestication decreased the endophytic bacterial co-occurrence network stability, and it did significantly alter the abundances of core microorganisms or potential probiotics. Third, untargeted LC-MS metabolomics revealed that domestication significantly altered the metabolite profiles, and the abundances of various root exudates released were significantly correlated with keystone taxa including the Chryseobacterium, Massilia, and Lechevalieria. Moreover, we found that root exudates, especially L-tyrosine promote the growth of plant-beneficial bacteria, such as Chryseobacterium. Additionally, with L-tyrosine and Chryseobacterium colonized in the roots, the growth of wild wheat's roots was significantly promoted, while no notable effect could be found in the domesticated cultivars. Overall, this study suggested that wild wheat as a key germplasm material, and its native endophytic microbes may serve as a resource for engineering crop microbiomes to improve the morphological and physiological traits of crops in widely distributed poor soils.

Inferring bacterial interspecific interactions from microcolony growth expansion

Bacterial species interactions significantly shape growth and behavior in communities, determining the emergence of community functions. Typically, these interactions are studied through bulk population measurements, overlooking the role of cell-to-cell variability and spatial context. This study uses real-time surface growth measurements of thousands of sparsely positioned microcolonies to investigate interactions and kinetic variations in monocultures and cocultures of Pseudomonas putida and P. veronii under substrate competition (succinate) or substrate independence (d-mannitol and putrescine). In monoculture, microcolonies exhibited expected substrate-dependent expansion rates, but individual colony sizes were affected by founder cell density, spatial positioning, growth rates, and lag times. In coculture, substrate competition favored P. putida, but unexpectedly, reduced the maximum growth rates of both species. In contrast, 10% of P. veronii microcolonies under competition grew larger than expected, likely due to founder cell phenotypic variation and stochastic spatial positioning. These effects were alleviated under substrate independence. A linear relationship between founder cell ratios and final colony area ratios in local neighborhoods (6.5-65 µm radius) was observed in coculture, with its slope reflecting interaction type and strength. Measured slopes in the P. putida to P. veronii biomass ratio under competition were one-third reduced compared to kinetic predictions using a cell-agent growth model, which exometabolite analysis and simulations suggested may be due to metabolite cross-feeding or inhibitory compound production. This indicates additional factors beyond inherent monoculture growth kinetics driving spatial interactions. Overall, the study demonstrates how microcolony growth experiments offer valuable insights into bacterial interactions, from local to community-level dynamics.

Interspecies synergistic interactions mediated by cofactor exchange enhance stress tolerance by inducing biofilm formation

Metabolic exchange plays a crucial role in shaping microbial community interactions and functions, including the exchange of small molecules such as cofactors. Cofactors are fundamental to enzyme catalytic activities; however, the role of cofactors in microbial stress tolerance is unclear. Here, we constructed a synergistic consortium containing two strains that could efficiently mineralize di-(2-ethylhexyl) phthalate under hyperosmotic stress. Integration of transcriptomic analysis, metabolic profiling, and a genome-scale metabolic model (GEM) facilitated the discovery of the potential mechanism of microbial interactions. Multi-omics analysis revealed that the vitamin B12-dependent methionine-folate cycle could be a key pathway for enhancing the hyperosmotic stress tolerance of synergistic consortium. Further GEM simulations revealed interspecies exchange of S-adenosyl-L-methionine and riboflavin, cofactors needed for vitamin B12 biosynthesis, which was confirmed by in vitro experiments. Overall, we proposed a new mechanism of bacterial hyperosmotic stress tolerance: bacteria might promote the production of vitamin B12 to enhance biofilm formation, and the species collaborate with each other by exchanging cofactors to improve consortium hyperosmotic stress tolerance. These findings offer new insights into the role of cofactors in microbial interactions and stress tolerance and are potentially exploitable for environmental remediation.

IMPORTANCE

Metabolic interactions (also known as cross-feeding) are thought to be ubiquitous in microbial communities. Cross-feeding is the basis for many positive interactions (e.g., mutualism) and is a primary driver of microbial community assembly. In this study, a combination of multi-omics analysis and metabolic modeling simulation was used to reveal the metabolic interactions of a synthetic consortium under hyperosmotic stress. Interspecies cofactor exchange was found to promote biofilm formation under hyperosmotic stress. This provides a new perspective for understanding the role of metabolic interactions in microbial communities to enhance environmental adaptation, which is significant for improving the efficiency of production activities and environmental bioremediation.

From Microbes to Microbiomes: Applications for Plant Health and Sustainable Agriculture

Plant-microbe interaction research has had a transformative trajectory, from individual microbial isolate studies to comprehensive analyses of plant microbiomes within the broader phytobiome framework. Acknowledging the indispensable role of plant microbiomes in shaping plant health, agriculture, and ecosystem resilience, we underscore the urgent need for sustainable crop production strategies in the face of contemporary challenges. We discuss how the synergies between advancements in 'omics technologies and artificial intelligence can help advance the profound potential of plant microbiomes. Furthermore, we propose a multifaceted approach encompassing translational considerations, transdisciplinary research initiatives, public-private partnerships, regulatory policy development, and pragmatic expectations for the practical application of plant microbiome knowledge across diverse agricultural landscapes. We advocate for strategic collaboration and intentional transdisciplinary efforts to unlock the benefits offered by plant microbiomes and address pressing global issues in food security. By emphasizing a nuanced understanding of plant microbiome complexities and fostering realistic expectations, we encourage the scientific community to navigate the transformative journey from discoveries in the laboratory to field applications. As companies specializing in agricultural microbes and microbiomes undergo shifts, we highlight the necessity of understanding how to approach sustainable agriculture with site-specific management solutions. While cautioning against overpromising, we underscore the excitement of exploring the many impacts of microbiome-plant interactions. We emphasize the importance of collaborative endeavors with societal partners to accelerate our collective capacity to harness the diverse and yet-to-be-discovered beneficial activities of plant microbiomes.

Embracing complexity in plant-microbiome systems

Despite recent advances in understanding the role of microorganisms in plant holobiont metabolism, physiology, and fitness, several relevant questions are yet to be answered, with implications for ecology, evolution, and sustainable agriculture. This article explores some of these questions and discusses emerging research areas in plant microbiomes. Firstly, it emphasizes the need to move beyond taxonomic characterization towards understanding microbial functions within plant ecosystems. Secondly, controlling methodological biases and enhancing OMICS technologies' standardization is imperative for a deeper comprehension of plant-microbiota interactions. Furthermore, while plant microbiota research has primarily centred on bacteria and fungi, other microbial players such as archaea, viruses, and microeukaryotes have been largely overlooked. Emerging evidence highlights their presence and potential roles, underscoring the need for thorough assessments. Future research should aim to elucidate the ecological microbial interactions, their impact on plant performance, and how the plant context shapes microbial community dynamics. Finally, a discussion is provided on how the multiple layers of abiotic and biotic factors influencing the spatiotemporal dynamics of plant-microbiome systems require in-depth attention. Examples illustrate how synthetic communities and computational methods such as machine learning and artificial intelligence provide alternatives to tackle these challenges and analyse the plant holobiont as a complex system.

Roots of synthetic ecology: microbes that foster plant resilience in the changing climate

Microbes orchestrate nearly all major biogeochemical processes. The ability to program their influence on plant growth and development is attractive for sustainable agriculture. However, the complexity of microbial ecosystems and our limited understanding of the mechanisms by which plants and microbes interact with each other and the environment make it challenging to use microbiomes to influence plant growth. Novel technologies at the intersection of microbial ecology, systems biology, and bioengineering provide new tools to probe the role of plant microbiomes across environments. Here, we summarize recent studies on plant and microbe responses to abiotic stresses, showcasing key molecules and micro-organisms that are important for plant health. We highlight opportunities to use synthetic microbial communities to understand the complexity of plant-microbial interactions and discuss future avenues of programming ecology to improve plant and ecosystem health.

Metabolomics and Microbial Metabolism: Toward a Systematic Understanding

Over the past decades, our understanding of microbial metabolism has increased dramatically. Metabolomics, a family of techniques that are used to measure the quantities of small molecules in biological samples, has been central to these efforts. Advances in analytical chemistry have made it possible to measure the relative and absolute concentrations of more and more compounds with increasing levels of certainty. In this review, we highlight how metabolomics has contributed to understanding microbial metabolism and in what ways it can still be deployed to expand our systematic understanding of metabolism. To that end, we explain how metabolomics was used to (a) characterize network topologies of metabolism and its regulation networks, (b) elucidate the control of metabolic function, and (c) understand the molecular basis of higher-order phenomena. We also discuss areas of inquiry where technological advances should continue to increase the impact of metabolomics, as well as areas where our understanding is bottlenecked by other factors such as the availability of statistical and modeling frameworks that can extract biological meaning from metabolomics data.

Effects of the nematode Litylenchus crenatae subsp. mccannii and beech leaf disease on leaf fungal and bacterial communities on Fagus grandifolia (American beech)

Beech leaf disease (BLD) is a newly emerging disease in North America that affects American beech (Fagus grandifolia). It is increasingly recognized that BLD is caused by a subspecies of the anguinid nematode Litylenchus crenatae subsp. mccannii (hereafter L. crenatae), which is likely native to East Asia. How nematode infestation of leaves affects the leaf microbiome and whether changes in the microbiome could contribute to BLD symptoms remain uncertain. In this study, we examined bacterial and fungal communities associated with the leaves of F. grandifolia across nine sites in Ohio and Pennsylvania that were either symptomatic or asymptomatic for BLD and used qPCR to measure relative nematode infestation levels. We found significantly higher levels of infestation at sites visibly symptomatic for BLD. Low levels of nematode infestation were also observed at asymptomatic sites, which suggests that nematodes can be present without visible symptoms evident. Bacterial and fungal communities were significantly affected by sampling site and symptomology, but only fungal communities were affected by nematode presence alone. We found many significant indicators of both bacteria and fungi related to symptoms of BLD, with taxa generally occurring in both asymptomatic and symptomatic leaves, suggesting that microbes are not responsible for BLD but could act as opportunistic pathogens. Of particular interest was the fungal genus Erysiphe, which is common in the Fagaceae and is reported to overwinter in buds-a strategy consistent with L. crenatae. The specific role microbes play in opportunistic infection of leaves affected by L. crenatae will require additional study.

IMPORTANCE

Beech leaf disease (BLD) is an emerging threat to American beech (Fagus grandifolia) and has spread quickly throughout the northeastern United States and into southern Canada. This disease leads to disfigurement of leaves and is marked by characteristic dark, interveinal banding, followed by leaf curling and drop in more advanced stages. BLD tends to especially affect understory leaves, which can lead to substantial thinning of the forest understory where F. grandifolia is a dominant tree species. Understanding the cause of BLD is necessary to employ management strategies that protect F. grandifolia and the forests where it is a foundation tree species. Current research has confirmed that the foliar nematode Litylenchus crenatae subsp. mccannii is required for BLD, but whether other organisms are involved is currently unknown. Here, we present a study that investigated leaf-associated fungi and bacteria of F. grandifolia to understand more about how microorganisms may contribute to BLD.

Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling

Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.

Emerging methods for genome-scale metabolic modeling of microbial communities

Genome-scale metabolic models (GEMs) are consolidating as platforms for studying mixed microbial populations, by combining biological data and knowledge with mathematical rigor. However, deploying these models to answer research questions can be challenging due to the increasing number of available computational tools, the lack of universal standards, and their inherent limitations. Here, we present a comprehensive overview of foundational concepts for building and evaluating genome-scale models of microbial communities. We then compare tools in terms of requirements, capabilities, and applications. Next, we highlight the current pitfalls and open challenges to consider when adopting existing tools and developing new ones. Our compendium can be relevant for the expanding community of modelers, both at the entry and experienced levels.

Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches

Genome-scale metabolic models (GEMs) of microbial communities offer valuable insights into the functional capabilities of their members and facilitate the exploration of microbial interactions. These models are generated using different automated reconstruction tools, each relying on different biochemical databases that may affect the conclusions drawn from the in silico analysis. One way to address this problem is to employ a consensus reconstruction method that combines the outcomes of different reconstruction tools. Here, we conducted a comparative analysis of community models reconstructed from three automated tools, i.e. CarveMe, gapseq, and KBase, alongside a consensus approach, utilizing metagenomics data from two marine bacterial communities. Our analysis revealed that these reconstruction approaches, while based on the same genomes, resulted in GEMs with varying numbers of genes and reactions as well as metabolic functionalities, attributed to the different databases employed. Further, our results indicated that the set of exchanged metabolites was more influenced by the reconstruction approach rather than the specific bacterial community investigated. This observation suggests a potential bias in predicting metabolite interactions using community GEMs. We also showed that consensus models encompassed a larger number of reactions and metabolites while concurrently reducing the presence of dead-end metabolites. Therefore, the usage of consensus models allows making full and unbiased use from aggregating genes from the different reconstructions in assessing the functional potential of microbial communities.

Deciphering Microbial Adaptation in the Rhizosphere: Insights into Niche Preference, Functional Profiles, and Cross-Kingdom Co-occurrences

Rhizosphere microbial communities are to be as critical factors for plant growth and vitality, and their adaptive differentiation strategies have received increasing amounts of attention but are poorly understood. In this study, we obtained bacterial and fungal amplicon sequences from the rhizosphere and bulk soils of various ecosystems to investigate the potential mechanisms of microbial adaptation to the rhizosphere environment. Our focus encompasses three aspects: niche preference, functional profiles, and cross-kingdom co-occurrence patterns. Our findings revealed a correlation between niche similarity and nucleotide distance, suggesting that niche adaptation explains nucleotide variation among some closely related amplicon sequence variants (ASVs). Furthermore, biological macromolecule metabolism and communication among abundant bacteria increase in the rhizosphere conditions, suggesting that bacterial function is trait-mediated in terms of fitness in new habitats. Additionally, our analysis of cross-kingdom networks revealed that fungi act as intermediaries that facilitate connections between bacteria, indicating that microbes can modify their cooperative relationships to adapt. Overall, the evidence for rhizosphere microbial community adaptation, via differences in gene and functional and co-occurrence patterns, elucidates the adaptive benefits of genetic and functional flexibility of the rhizosphere microbiota through niche shifts.

Hitching a Ride in the Phyllosphere: Surfactant Production of Pseudomonas spp. Causes Co-swarming of Pantoea eucalypti 299R

Here, we demonstrate the beneficial effect of surfactant-producing pseudomonads on Pantoea eucalypti 299R. We conducted a series of experiments in environments of increasing complexity. P. eucalypti 299R (Pe299R), and Pseudomonas sp. FF1 (Pff1) or Pe299R and surfactant-production deficient Pseudomonas sp. FF1::ΔviscB (Pff1ΔviscB) were co-inoculated in broth, on swarming agar plates, and on plants. In broth, there were no differences in the growth dynamics of Pe299R when growing in the presence of Pff1 or Pff1ΔviscB. By contrast, on swarming agar plates, Pe299R was able to co-swarm with Pff1 which led to a significant increase in Pe299R biomass compared to Pe299R growing with Pff1ΔviscB or in monoculture. Finally in planta, and using the single-cell bioreporter for reproductive success (CUSPER), we found a temporally distinct beneficial effect of Pff1 on co-inoculated Pe299R subpopulations that did not occur in the presence of Pff1ΔviscB. We tested three additional surfactant-producing pseudomonads and their respective surfactant knockout mutants on PE299R on swarming agar showing similar results. This led us to propose a model for the positive effect of surfactant production during leaf colonization. Our results indicate that co-motility might be common during leaf colonization and adds yet another facet to the already manyfold roles of surfactants.

Spatially distributed metabolites SWEETen the root for microbes

Limited understanding exists on the spatial configuration of underground plant-microbe interactions. In this issue of Cell Host & Microbe, Loo et al. illustrate the sugar transporter-involved interdependent interaction between root metabolites and microbial spatial colonization, providing insights into metabolic-associated organization of plant-microbe interactions.

Sugar transporters spatially organize microbiota colonization along the longitudinal root axis of Arabidopsis

Plant roots are functionally heterogeneous in cellular architecture, transcriptome profile, metabolic state, and microbial immunity. We hypothesized that axial differentiation may also impact spatial colonization by root microbiota along the root axis. We developed two growth systems, ArtSoil and CD-Rhizotron, to grow and then dissect Arabidopsis thaliana roots into three segments. We demonstrate that distinct endospheric and rhizosphere bacterial communities colonize the segments, supporting the hypothesis of microbiota differentiation along the axis. Root metabolite profiling of each segment reveals differential metabolite enrichment and specificity. Bioinformatic analyses and GUS histochemistry indicate microbe-induced accumulation of SWEET2, 4, and 12 sugar uniporters. Profiling of root segments from sweet mutants shows altered spatial metabolic profiles and reorganization of endospheric root microbiota. This work reveals the interdependency between root metabolites and microbial colonization and the contribution of SWEETs to spatial diversity and stability of microbial ecosystem.

Assessing microbiome population dynamics using wild-type isogenic standardized hybrid (WISH)-tags

Microbiomes feature recurrent compositional structures under given environmental conditions. However, these patterns may conceal diverse underlying population dynamics that require intrastrain resolution. Here we developed a genomic tagging system, termed wild-type isogenic standardized hybrid (WISH)-tags, that can be combined with quantitative polymerase chain reaction and next-generation sequencing for microbial strain enumeration. We experimentally validated the performance of 62 tags and showed that they can be differentiated with high precision. WISH-tags were introduced into model and non-model bacterial members of the mouse and plant microbiota. Intrastrain priority effects were tested using one species of isogenic barcoded bacteria in the murine gut and the Arabidopsis phyllosphere, both with and without microbiota context. We observed colonization resistance against late-arriving strains of Salmonella Typhimurium in the mouse gut, whereas the phyllosphere accommodated Sphingomonas latecomers in a manner proportional to their presence at the late inoculation timepoint. This demonstrates that WISH-tags are a resource for deciphering population dynamics underlying microbiome assembly across biological systems.

Predicting microbial interactions with approaches based on flux balance analysis: an evaluation

BACKGROUND

Given a genome-scale metabolic model (GEM) of a microorganism and criteria for optimization, flux balance analysis (FBA) predicts the optimal growth rate and its corresponding flux distribution for a specific medium. FBA has been extended to microbial consortia and thus can be used to predict interactions by comparing in-silico growth rates for co- and monocultures. Although FBA-based methods for microbial interaction prediction are becoming popular, a systematic evaluation of their accuracy has not yet been performed.

RESULTS

Here, we evaluate the accuracy of FBA-based predictions of human and mouse gut bacterial interactions using growth data from the literature. For this, we collected 26 GEMs from the semi-curated AGORA database as well as four previously published curated GEMs. We tested the accuracy of three tools (COMETS, Microbiome Modeling Toolbox and MICOM) by comparing growth rates predicted in mono- and co-culture to growth rates extracted from the literature and also investigated the impact of different tool settings and media. We found that except for curated GEMs, predicted growth rates and their ratios (i.e. interaction strengths) do not correlate with growth rates and interaction strengths obtained from in vitro data.

CONCLUSIONS

Prediction of growth rates with FBA using semi-curated GEMs is currently not sufficiently accurate to predict interaction strengths reliably.