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

Synergic interactions between Trichoderma and the soil microbiomes improve plant iron availability and growth

Iron bioavailability is often limited especially in calcareous soils. Trichoderma harzianum strongly improves plant iron uptake and growth in calcareous soils. However, little is known about the mechanisms by which T. harzianum mobilizes iron in calcareous soils. Here, the model strain T. harzianum NJAU4742 and a synthetic microbial community (SynCom) was used to show that the efficacy of T. harzianum in enhancing plant iron nutrition in calcareous soils depends on the soil microbiome. Enhanced iron-mobilization functions of the SynCom were observed in the presence of T. harzianum NJAU4742. Concurrently, T. harzianum NJAU4742 improved the iron-mobilization capacity of the SynCom by enriching strains that are able to do so. Finally, Chryseobacterium populi was identified as a key driver of iron mobilization, while their synergistic colonization further enhances this process. This study unveils a pivotal mechanism by which T. harzianum NJAU4742-mediated re-structuring of the soil microbiome and ameliorates plant iron nutrition.

Microbiome selection and evolution within wild and domesticated plants

Microbes are ubiquitously found across plant surfaces and even within their cells, forming the plant microbiome. Many of these microbes contribute to the functioning of the host and consequently affect its fitness. Therefore, in many contexts, including microbiome effects enables a better understanding of the phenotype of the plant rather than considering the genome alone. Changes in the microbiome composition are also associated with changes in the functioning of the host, and there has been considerable focus on how environmental variables regulate plant microbiomes. More recently, studies suggest that the host genome also preconditions the microbiome to the environment of the plant, and the microbiome is therefore subject to evolutionary forces. Here, we outline how plant microbiomes are governed by both environmental variables and evolutionary processes and how they can regulate plant health together.

Diversity and composition of soil microbial communities in the rhizospheres of late blight-resistant tomatoes after Phytophthora infestans inoculation

Late blight caused by the oomycete Phytophthora infestans poses a severe threat to global tomato (Solanum lycopersicum L.) production. While genetic resistance forms the cornerstone of disease control, the mechanisms underlying cultivar-specific resistance, particularly their interactions with rhizosphere microbiomes, remain poorly understood. To elucidate the mechanisms of tomato cultivar resistance to late blight and screen out antagonistic microorganisms against P. infestans, we investigated the microbial compositions in the rhizospheres of tomato cultivars with different late blight-resistance levels under both natural and P. infestans-inoculated conditions. Considerable differences in soil microbial diversity and composition of rhizospheres were found between late blight-resistant and -susceptible tomato cultivars. Under natural conditions, the resistant tomato cultivar exhibited higher bacterial diversity and lower fungal diversity than that of the susceptible cultivar. Additionally, after P. infestans inoculation, both the resistant and susceptible cultivars showed enrichment of microorganisms with potential antagonistic effects in the rhizospheres. Among them, bacterial genera, such as Pseudomonas, Azospirillum, and Acidovorax, and fungal genera, including Phoma, Arthrobotrys, Pseudallescheria, and Pseudolabrys, were enriched in the rhizospheres of the late blight-resistant tomato cultivar. In contrast, bacterial genera, including Flavobacterium, Pseudolabrys, and Burkholderia-Caballeronia-Paraburkholderia, and the Trichoderma fungal genus were enriched in the rhizospheres of the late blight-susceptible tomato cultivar. Simultaneously, the enrichment of pathogenic microorganisms, such as Neocosmospora and Plectosphaerella, was also detected in the rhizospheres of the susceptible tomato cultivar. Moreover, no enrichment of pathogenic microorganisms occurred in the late blight-resistant tomato cultivar after P. infestans inoculation. These findings suggest that these traits serve as effective defense mechanisms against pathogen invasion in resistant tomato cultivar. Overall, this study provides a comprehensive analysis of the rhizosphere microbial community structures in late blight-resistant and -susceptible tomato cultivars under natural conditions and their response following pathogen inoculation. Additionally, potential antagonistic microorganisms against late blight were also identified. The findings offer valuable insights for effective late blight management in tomatoes and contribute to the development of sustainable agricultural practices.

Order among chaos: High throughput MYCroplanters can distinguish interacting drivers of host infection in a highly stochastic system

The likelihood that a host will be susceptible to infection is influenced by the interaction of diverse biotic and abiotic factors. As a result, substantial experimental replication and scalability are required to identify the contributions of and interactions between the host, the environment, and biotic factors such as the microbiome. For example, pathogen infection success is known to vary by host genotype, bacterial strain identity and dose, and pathogen dose. Elucidating the interactions between these factors in vivo has been challenging because testing combinations of these variables quickly becomes experimentally intractable. Here, we describe a novel high throughput plant growth system (MYCroplanters) to test how multiple host, non-pathogenic bacteria, and pathogen variables predict host health. Using an Arabidopsis-Pseudomonas host-microbe model, we found that host genotype and bacterial strain order of arrival predict host susceptibility to infection, but pathogen and non-pathogenic bacterial dose can overwhelm these effects. Host susceptibility to infection is therefore driven by complex interactions between multiple factors that can both mask and compensate for each other. However, regardless of host or inoculation conditions, the ratio of pathogen to non-pathogen emerged as a consistent correlate of disease. Our results demonstrate that high-throughput tools like MYCroplanters can isolate interacting drivers of host susceptibility to disease. Increasing the scale at which we can screen drivers of disease, such as microbiome community structure, will facilitate both disease predictions and treatments for medicine and agricultural applications.

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.

Paenibacillus polymyxa J2-4 induces cucumber to enrich rhizospheric Pseudomonas and contributes to Meloidogyne incognita management under field conditions

BACKGROUND

Root knot nematodes (RKNs) pose a great threat to agricultural production worldwide. The bacterial nematocides have received increasing attention due to their safe and efficient control against RKNs. Here, we investigated the biocontrol efficacy of Paenibacillus polymyxa J2-4 against Meloidogyne incognita in the field and analyzed the rhizosphere microbiome of cucumber under nematode infection after application of the J2-4 strain. Furthermore, a biomarker strain of Pseudomonas spp. was isolated from the J2-4-inoculated rhizosphere soil, and its nematocidal activity and growth-promoting effect on host plants were determined. In addition, chemotaxis assay of P. fluroescens ZJ5 toward root exudates was carried out.

RESULTS

The field experiment demonstrated that P. polymyxa J2-4 could effectively suppressed gall formation in cucumber plants, with the galling index reduced by 67.63% in 2022 and 65.50% in 2023, respectively, compared with controls. Meanwhile, plant height and yield were significantly increased in J2-4 treated plants compared with controls. Metagenomic analysis indicated that J2-4 altered the rhizosphere microbial communities. The relative abundance of Pseudomonas spp. was notably enhanced in the J2-4 group, which was consistent with Linear discriminant analysis Effect Size results that Pseudomonas was determined as one of the biomarkers in the J2-4 group. Furthermore, the ZJ5 strain, one of the biomarker Pseudomonas strains, was isolated from the J2-4-inoculated rhizosphere soil and was identified as Pseudomonas fluorescens. In addition, P. fluorescens ZJ5 exhibited high nematicidal activity in vitro and in vivo, with 99.20% of the mortality rate of M. incognita at 24 h and 69.75% of gall index reduction. The biocontrol efficiency of the synthetic community of ZJ5 plus J2-4 was superior to that of any other single bacteria against M. incognita. Additionally, ZJ5 exhibited great chemotaxis ability toward root exudates inoculated with J2-4.

CONCLUSION

Paenibacillus polymyxa J2-4 has good potential in the biological control against M. incognita under field conditions. Enrichment of the beneficial bacteria Pseudomonas fluorescens ZJ5 in the J2-4-inoculated rhizosphere soil contributes to M. incognita management. © 2024 Society of Chemical Industry.

Phages indirectly maintain tomato plant pathogen defense through regulation of the commensal microbiome

As parasites of bacteria, phages can regulate microbiome diversity and composition and may therefore affect susceptibility to pathogens and disease. Many infectious diseases are associated with altered bacteriophage communities, but observational studies alone do not allow us to determine when altered phage community composition is a contributor to disease risk, a response to infection, or simply an indicator of dysbiosis. To address this question directly, we used size-selective filtration to deplete plant-associated microbial communities of phages, then challenged plants with the bacterial pathogen Pseudomonas syringae. Plants with phage-depleted microbiomes were more susceptible to infection, an effect that could not be explained by direct effects of the phage communities on either P. syringae or the plant host. Moreover, the presence of phages was most impactful when the phage communities were isolated from neighboring field locations rather than from the same host plant as the bacteria, possibly suggesting that moderate rates of lysis maintain a community structure that is most resistant to pathogen invasion. Overall, our results support the idea that phage communities contribute to plant defenses by modulating the microbiome.

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.

Seed tuber microbiome can predict growth potential of potato varieties

Potato vigour, the growth potential of seed potatoes, is a key agronomic trait that varies significantly across production fields due to factors such as genetic background and environmental conditions. Seed tuber microbiomes are thought to influence plant health and crop performance, yet the precise relationships between microbiome composition and potato vigour remain unclear. Here we conducted microbiome sequencing on seed tuber eyes and heel ends from 6 potato varieties grown in 240 fields. By using time-resolved drone imaging of three trial fields in the next season to track crop development, we were able to link microbiome composition with potato vigour. We used microbiome data at varying taxonomic resolutions to build random forest predictive models and found that amplicon sequence variants provided the highest predictive accuracy for potato vigour. The model revealed variety-specific relationships between the seed tuber microbiome and next season's crop vigour in independent trial fields. With a coefficient of determination value of 0.69 for the best-performing variety, the model accurately predicted vigour in seed tubers from fields not previously included in the analysis. Moreover, the model identified key microbial indicators of vigour from which a Streptomyces, an Acinetobacter and a Cellvibrio amplicon sequence variant stood out as the most important contributors to the model's accuracy. This study shows that seed potato vigour can be reliably predicted based on the microbiota associated with seed tuber eyes, potentially guiding future microbiome-informed breeding strategies.

Bacterial community function increases leaf growth in a pitcher plant experimental system

Across diverse ecosystems, bacteria and their hosts engage in complex relationships having negative, neutral, or positive interactions. However, the specific effects of leaf-associated bacterial community functions on plant growth are poorly understood. Although microbes can promote plant growth through various biochemical mechanisms, investigating the community's functional contributions to plant growth remains to be explored. To address this gap, we characterized the relationships between bacterial community function and host plant growth in the purple pitcher plant (Sarracenia purpurea). The main aim of our research was to investigate how different bacterial community functions affect the growth and nutrient content in the plant. Previous research has suggested that microbial communities aid in prey decomposition and subsequent nutrient acquisition in carnivorous plants, including S. purpurea. However, the specific functional roles of bacterial communities in plant growth and nutrient uptake are not well known. In this study, sterile, freshly opened pitchers were inoculated with three functionally distinct, pre-assembled bacterial communities. Bacterial community composition and function were measured over 8 weeks using physiological assays, metagenomics, and metatranscriptomics. Distinct community functions affected plant traits; a bacterial community enriched in decomposition was associated with larger leaves with almost double the biomass of control pitchers. Physiological differences in bacterial communities were supported by metatranscriptomics; for example, the bacterial community with the highest chitinase activity had greater expression of transcripts associated with chitinase enzymes. The relationship between bacterial community function and plant growth observed here indicates potential mechanisms, such as chitinase activity, for host-associated bacterial functions to support pitcher plant growth.

IMPORTANCE

This study addresses a gap in understanding the relationships between bacterial community function and plant growth. We inoculated sterile, freshly opened pitcher plant leaves with three functionally distinct bacterial communities to uncover potential mechanisms through which bacterial functions support plant health and growth. Our findings demonstrate that distinct community functions significantly influence plant traits, with some bacterial communities supporting more plant growth than in control pitchers. These results highlight the ecological roles of microbial communities in plants and thus ecosystems and suggest that nutrient cycling is an important pathway through which microbes support host plant health. This research provides valuable insights into plant-microbe interactions and the effects of diverse microbial community functions.

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.

Meddling with the microbiota: Fungal tricks to infect plant hosts

Plants associate with a wealth of microbes, collectively referred to as the plant microbiota, whose composition is determined by host plant genetics, immune responses, environmental factors and intermicrobial relations. Unsurprisingly, microbiota compositions change during disease development. Recent evidence revealed that some of these changes can be attributed to effector proteins with antimicrobial activities that are secreted by plant pathogens to manipulate host microbiota to their advantage. Intriguingly, many of these effectors have ancient origins, predating land plant emergence, and evolved over long evolutionary trajectories to acquire selective antimicrobial activities to target microbial antagonists in host plant microbiota. Thus, we argue that host-pathogen co-evolution likely involved arms races within the host-associated microbiota.

A cross-systems primer for synthetic microbial communities

The design and use of synthetic communities, or SynComs, is one of the most promising strategies for disentangling the complex interactions within microbial communities, and between these communities and their hosts. Compared to natural communities, these simplified consortia provide the opportunity to study ecological interactions at tractable scales, as well as facilitating reproducibility and fostering interdisciplinary science. However, the effective implementation of the SynCom approach requires several important considerations regarding the development and application of these model systems. There are also emerging ethical considerations when both designing and deploying SynComs in clinical, agricultural or environmental settings. Here we outline current best practices in developing, implementing and evaluating SynComs across different systems, including a focus on important ethical considerations for SynCom research.

Leaf Endophytes Relationship with Host Metabolome Expression in Tropical Gymnosperms

Plant-microbe interactions play a pivotal role in shaping host fitness, especially concerning chemical defense mechanisms. In cycads, establishing direct correlations between specific endophytic microbes and the synthesis of highly toxic defensive phytochemicals has been challenging. Our research delves into the intricate relationship between plant-microbe associations and the variation of secondary metabolite production in two closely related Zamia species that grow in distinct habitats; terrestrial and epiphytic. Employing an integrated approach, we combined microbial metabarcoding, which characterize the leaf endophytic bacterial and fungal communities, with untargeted metabolomics to test if the relative abundances of specific microbial taxa in these two Zamia species were associated with different metabolome profiles. The two species studied shared approximately 90% of the metabolites spanning diverse biosynthetic pathways: alkaloids, amino acids, carbohydrates, fatty acids, polyketides, shikimates, phenylpropanoids, and terpenoids. Co-occurrence networks revealed positive associations among metabolites from different pathways, underscoring the complexity of their interactions. Our integrated analysis demonstrated to some degree that the intraspecific variation in metabolome profiles of the two host species was associated with the abundance of bacterial orders Acidobacteriales and Frankiales, as well as the fungal endophytes belonging to the orders Chaetothyriales, Glomerellales, Heliotiales, Hypocreales, and Sordariales. We further associate individual metabolic similarity with four specific fungal endophyte members of the core microbiota, but no specific bacterial taxa associations were identified. This study represents a pioneering investigation to characterize leaf endophytes and their association with metabolomes in tropical gymnosperms, laying the groundwork for deeper inquiries into this complex domain.

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.

Engineering agricultural soil microbiomes and predicting plant phenotypes

Plant growth-promoting rhizobacteria (PGPR) can improve crop yields, nutrient use efficiency, plant tolerance to stressors, and confer benefits to future generations of crops grown in the same soil. Unlocking the potential of microbial communities in the rhizosphere and endosphere is therefore of great interest for sustainable agriculture advancements. Before plant microbiomes can be engineered to confer desirable phenotypic effects on their plant hosts, a deeper understanding of the interacting factors influencing rhizosphere community structure and function is needed. Dealing with this complexity is becoming more feasible using computational approaches. In this review, we discuss recent advances at the intersection of experimental and computational strategies for the investigation of plant-microbiome interactions and the engineering of desirable soil microbiomes.

Dynamics of Physiological Properties and Endophytic Fungal Communities in the Xylem of Aquilaria sinensis (Lour.) with Different Induction Times

Xylem-associated fungus can secrete many secondary metabolites to help Aquilaria trees resist various stresses and play a crucial role in facilitating agarwood formation. However, the dynamics of endophytic fungi in Aquilaria sinensis xylem after artificial induction have not been fully elaborated. Endophytic fungi communities and xylem physio-biochemical properties were examined before and after induction with an inorganic salt solution, including four different times (pre-induction (0M), the third (3M), sixth (6M) and ninth (9M) month after induction treatment). The relationships between fungal diversity and physio-biochemical indices were evaluated. The results showed that superoxide dismutase (SOD) and peroxidase (POD) activities, malondialdehyde (MDA) and soluble sugar content first increased and then decreased with induction time, while starch was heavily consumed after induction treatment. Endophytic fungal diversity was significantly lower after induction treatment than before, but the species richness was promoted. Fungal β-diversity was also clustered into four groups according to different times. Core species shifted from rare to dominant taxa with induction time, and growing species interactions in the network indicate a gradual complication of fungal community structure. Endophytic fungi diversity and potential functions were closely related to physicochemical indices that had less effect on the relative abundance of the dominant species. These findings help assess the regulatory mechanisms of microorganisms that expedite agarwood formation after artificial induction.

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.

Higher-order interactions and emergent properties of microbial communities: The power of synthetic ecology

Humans have long relied on microbial communities to create products, produce energy, and treat waste. The microbiota residing within our bodies directly impacts our health, while the soil and rhizosphere microbiomes influence the productivity of our crops. However, the complexity and diversity of microbial communities make them challenging to study and difficult to develop into applications, as they often exhibit the emergence of unpredictable higher-order phenomena. Synthetic ecology aims at simplifying complexity by constituting synthetic or semi-natural microbial communities with reduced diversity that become easier to study and analyze. This strategy combines methodologies that simplify existing complex systems (top-down approach) or build the system from its constituent components (bottom-up approach). Simplified communities are studied to understand how interactions among populations shape the behavior of the community and to model and predict their response to external stimuli. By harnessing the potential of synthetic microbial communities through a multidisciplinary approach, we can advance knowledge of ecological concepts and address critical public health, agricultural, and environmental issues more effectively.

Connecting microbial community assembly and function

Microbial ecology is moving away from purely descriptive analyses to experiments that can determine the underlying mechanisms driving changes in community assembly and function. More species-rich microbial communities generally have higher functional capabilities depending on if there is positive selection of certain species or complementarity among different species. When building synthetic communities or laboratory enrichment cultures, there are specific choices that can increase the number of species able to coexist. Higher resource complexity or the addition of physical niches are two of the many factors leading to greater biodiversity and associated increases in functional capabilities. We can use principles from community ecology and knowledge of microbial physiology to generate improved microbiomes for use in medicine, agriculture, or environmental management.

Strategies for tailoring functional microbial synthetic communities

Natural ecosystems harbor a huge reservoir of taxonomically diverse microbes that are important for plant growth and health. The vast diversity of soil microorganisms and their complex interactions make it challenging to pinpoint the main players important for the life support functions microbes can provide to plants, including enhanced tolerance to (a)biotic stress factors. Designing simplified microbial synthetic communities (SynComs) helps reduce this complexity to unravel the molecular and chemical basis and interplay of specific microbiome functions. While SynComs have been successfully employed to dissect microbial interactions or reproduce microbiome-associated phenotypes, the assembly and reconstitution of these communities have often been based on generic abundance patterns or taxonomic identities and co-occurrences but have only rarely been informed by functional traits. Here, we review recent studies on designing functional SynComs to reveal common principles and discuss multidimensional approaches for community design. We propose a strategy for tailoring the design of functional SynComs based on integration of high-throughput experimental assays with microbial strains and computational genomic analyses of their functional capabilities.