Metabolic interaction models recapitulate leaf microbiota ecology

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Interspecific interactions facilitate keystone species in a multispecies biofilm that promotes plant growth

Microorganisms colonizing plant roots co-exist in complex, spatially structured multispecies biofilm communities. However, little is known about microbial interactions and the underlying spatial organization within biofilm communities established on plant roots. Here, a well-established four-species biofilm model (Stenotrophomonas rhizophila, Paenibacillus amylolyticus, Microbacterium oxydans, and Xanthomonas retroflexus, termed as SPMX) was applied to Arabidopsis roots to study the impact of multispecies biofilm on plant growth and the community spatial dynamics on the roots. SPMX co-culture notably promoted root development and plant biomass. Co-cultured SPMX increased root colonization and formed multispecies biofilms, structurally different from those formed by monocultures. By combining 16S rRNA gene amplicon sequencing and fluorescence in situ hybridization with confocal laser scanning microscopy, we found that the composition and spatial organization of the four-species biofilm significantly changed over time. Monoculture P. amylolyticus colonized plant roots poorly, but its population and root colonization were highly enhanced when residing in the four-species biofilm. Exclusion of P. amylolyticus from the community reduced overall biofilm production and root colonization of the three species, resulting in the loss of the plant growth-promoting effects. Combined with spatial analysis, this led to identification of P. amylolyticus as a keystone species. Our findings highlight that weak root colonizers may benefit from mutualistic interactions in complex communities and hereby become important keystone species impacting community spatial organization and function. This work expands the knowledge on spatial organization uncovering interspecific interactions in multispecies biofilm communities on plant roots, beneficial for harnessing microbial mutualism promoting plant growth.

Leveraging genome-scale metabolic models to understand aerobic methanotrophs

Genome-scale metabolic models (GEMs) are valuable tools serving systems biology and metabolic engineering. However, GEMs are still an underestimated tool in informing microbial ecology. Since their first application for aerobic gammaproteobacterial methane oxidizers less than a decade ago, GEMs have substantially increased our understanding of the metabolism of methanotrophs, a microbial guild of high relevance for the natural and biotechnological mitigation of methane efflux to the atmosphere. Particularly, GEMs helped to elucidate critical metabolic and regulatory pathways of several methanotrophic strains, predicted microbial responses to environmental perturbations, and were used to model metabolic interactions in cocultures. Here, we conducted a systematic review of GEMs exploring aerobic methanotrophy, summarizing recent advances, pointing out weaknesses, and drawing out probable future uses of GEMs to improve our understanding of the ecology of methane oxidizers. We also focus on their potential to unravel causes and consequences when studying interactions of methane-oxidizing bacteria with other methanotrophs or members of microbial communities in general. This review aims to bridge the gap between applied sciences and microbial ecology research on methane oxidizers as model organisms and to provide an outlook for future studies.

Leaf microbiome dysbiosis triggered by T2SS-dependent enzyme secretion from opportunistic Xanthomonas pathogens

In healthy plants, the innate immune system contributes to maintenance of microbiota homoeostasis, while disease can be associated with microbiome perturbation or dysbiosis, and enrichment of opportunistic plant pathogens like Xanthomonas. It is currently unclear whether the microbiota change occurs independently of the opportunistic pathogens or is caused by the latter. Here we tested if protein export through the type-2 secretion system (T2SS) by Xanthomonas causes microbiome dysbiosis in Arabidopsis thaliana in immunocompromised plants. We found that Xanthomonas strains secrete a cocktail of plant cell wall-degrading enzymes that promote Xanthomonas growth during infection. Disease severity and leaf tissue degradation were increased in A. thaliana mutants lacking the NADPH oxidase RBOHD. Experiments with gnotobiotic plants, synthetic bacterial communities and wild-type or T2SS-mutant Xanthomonas revealed that virulence and leaf microbiome composition are controlled by the T2SS. Overall, a compromised immune system in plants can enrich opportunistic pathogens, which damage leaf tissues and ultimately cause microbiome dysbiosis by facilitating growth of specific commensal bacteria.

From microbiome composition to functional engineering, one step at a time

SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms. While nucleic acid sequencing technologies can chart microbiota composition with high precision, we mostly lack information about the functional roles and interactions of each strain present in a given microbiome. This limits our ability to predict microbiome function in natural habitats and, in the case of dysfunction or dysbiosis, to redirect microbiomes onto stable paths. Here, we will discuss a systematic approach (dubbed the N+1/N-1 concept) to enable step-by-step dissection of microbiome assembly and functioning, as well as intervention procedures to introduce or eliminate one particular microbial strain at a time. The N+1/N-1 concept is informed by natural invasion events and selects culturable, genetically accessible microbes with well-annotated genomes to chart their proliferation or decline within defined synthetic and/or complex natural microbiota. This approach enables harnessing classical microbiological and diversity approaches, as well as omics tools and mathematical modeling to decipher the mechanisms underlying N+1/N-1 microbiota outcomes. Application of this concept further provides stepping stones and benchmarks for microbiome structure and function analyses and more complex microbiome intervention strategies.

Identifying microbiota community patterns important for plant protection using synthetic communities and machine learning

Plant-associated microbiomes contribute to important ecosystem functions such as host resistance to biotic and abiotic stresses. The factors that determine such community outcomes are inherently difficult to identify under complex environmental conditions. In this study, we present an experimental and analytical approach to explore microbiota properties relevant for a microbiota-conferred host phenotype, here plant protection, in a reductionist system. We screened 136 randomly assembled synthetic communities (SynComs) of five bacterial strains each, followed by classification and regression analyses as well as empirical validation to test potential explanatory factors of community structure and composition, including evenness, total commensal colonization, phylogenetic diversity, and strain identity. We find strain identity to be the most important predictor of pathogen reduction, with machine learning algorithms improving performances compared to random classifications (94-100% versus 32% recall) and non-modelled predictions (0.79-1.06 versus 1.5 RMSE). Further experimental validation confirms three strains as the main drivers of pathogen reduction and two additional strains that confer protection in combination. Beyond the specific application presented in our study, we provide a framework that can be adapted to help determine features relevant for microbiota function in other biological systems.

Plant and microbial features governing an endophytic lifestyle

Beneficial microorganisms colonizing internal plant tissues, the endophytes, support their host through plant growth promotion, pathogen protection, and abiotic stress alleviation. Their efficient application in agriculture requires the understanding of the molecular mechanisms and environmental conditions that facilitate in planta accommodation. Accumulating evidence reveals that commensal microorganisms employ similar colonization strategies as their pathogenic counterparts. Fine-tuning of immune response, motility, and metabolic crosstalk accounts for their differentiation. For a holistic perspective, in planta experiments with microbial collections and comprehensive genome data exploration are crucial. This review describes the most recent findings on factors involved in endophytic colonization processes, focusing on bacteria and fungi, and discusses required methodological approaches to unravel their relevance within a community context.

Making waves: Enhancing pollutant biodegradation via rational engineering of microbial consortia

Biodegradation holds promise as an effective and sustainable process for the removal of synthetic chemical pollutants. Nevertheless, rational engineering of biodegradation for pollutant remediation remains an unfulfilled goal, while chemical pollution of waters and soils continues to advance. Efforts to (i) identify functional bacteria from aquatic and soil microbiomes, (ii) assemble them into biodegrading consortia, and (iii) identify maintenance and performance determinants, are challenged by large number of pollutants and the complexity in the enzymology and ecology of pollutant biodegradation. To overcome these challenges, approaches that leverage knowledge from environmental bio-chem-informatics and metabolic engineering are crucial. Here, we propose a novel high-throughput bio-chem-informatics pipeline, to link chemicals and their predicted biotransformation pathways with potential enzymes and bacterial strains. Our framework systematically selects the most promising candidates for the degradation of chemicals with unknown biotransformation pathways and associated enzymes from the vast array of aquatic and soil bacteria. We substantiated our perspective by validating the pipeline for two chemicals with known or predicted pathways and show that our predicted strains are consistent with strains known to biotransform those chemicals. Such pipelines can be integrated with metabolic network analysis built upon genome-scale models and ecological principles to rationally design fit-for-purpose bacterial communities for augmenting deficient biotransformation functions and study operational and design parameters that influence their structure and function. We believe that research in this direction can pave the way for achieving our long-term goal of enhancing pollutant biodegradation.

Lanthanide-dependent isolation of phyllosphere methylotrophs selects for a phylogenetically conserved but metabolically diverse community

The influence of lanthanide biochemistry during methylotrophy demands a reassessment of how the composition and metabolic potential of methylotrophic phyllosphere communities are affected by the presence of these metals. To investigate this, methylotrophs were isolated from soybean leaves by selecting for bacteria capable of methanol oxidation with lanthanide cofactors. Of the 344 pink-pigmented facultative methylotroph isolates, none were obligately lanthanide-dependent. Phylogenetic analyses revealed that all strains were nearly identical to each other and to model strains from the extorquens clade of Methylobacterium, with rpoB providing higher resolution than 16s rRNA for strain-specific identification. Despite the low species diversity, the metabolic capabilities of the community diverged greatly. Strains encoding identical PQQ-dependent alcohol dehydrogenases displayed significantly different growth from each other on alcohols in the presence and absence of lanthanides. Several strains also lacked well-characterized lanthanide-associated genes thought to be important for phyllosphere colonization. Additionally, 3% of our isolates were capable of growth on sugars and 23% were capable of growth on aromatic acids, substantially expanding the range of multicarbon substrates utilized by members of the extorquens clade in the phyllosphere. Whole genome sequences of eleven novel strains are reported. Our findings suggest that the expansion of metabolic capabilities, as well as differential usage of lanthanides and their influence on metabolism among closely related strains, point to evolution of niche partitioning strategies to promote colonization of the phyllosphere.

Deep discovery informs difficult deployment in plant microbiome science

Plant-associated microbiota can extend plant immune system function, improve nutrient acquisition and availability, and alleviate abiotic stresses. Thus, naturally beneficial microbial therapeutics are enticing tools to improve plant productivity. The basic definition of plant microbiota across species and ecosystems, combined with the development of reductionist experimental models and the manipulation of plant phenotypes with microbes, has fueled interest in its translation to agriculture. However, the great majority of microbes exhibiting plant-productivity traits in the lab and greenhouse fail in the field. Therapeutic microbes must reach détente, the establishment of uneasy homeostasis, with the plant immune system, invade heterogeneous pre-established plant-associated communities, and persist in a new and potentially remodeled community. Environmental conditions can alter community structure and thus impact the engraftment of therapeutic microbes. We survey recent breakthroughs, challenges, and opportunities in translating beneficial microbes from the lab to the field.

The Architecture of Metabolic Networks Constrains the Evolution of Microbial Resource Hierarchies

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often use them sequentially according to a preference hierarchy, resulting in well-known patterns of diauxic growth. In theory, the evolutionary diversification of metabolic hierarchies could represent a mechanism supporting coexistence and biodiversity by enabling temporal segregation of niches. Despite this ecologically critical role, the extent to which substrate preference hierarchies can evolve and diversify remains largely unexplored. Here, we used genome-scale metabolic modeling to systematically explore the evolution of metabolic hierarchies across a vast space of metabolic network genotypes. We find that only a limited number of metabolic hierarchies can readily evolve, corresponding to the most commonly observed hierarchies in genome-derived models. We further show how the evolution of novel hierarchies is constrained by the architecture of central metabolism, which determines both the propensity to change ranks between pairs of substrates and the effect of specific reactions on hierarchy evolution. Our analysis sheds light on the genetic and mechanistic determinants of microbial metabolic hierarchies, opening new research avenues to understand their evolution, evolvability, and ecology.