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Medicinal plants produce specialized metabolites (SM) that are used as drugs. However, due to low yields of field cultivation and the increasing market demand, this production method often failed to meet supply needs. Biotechnological alternatives, such as in vitro plant cultures, offer promising solutions. Nonetheless, SM production in these systems remains too low for industrial exploitation, necessitating an elicitation step to induce the plant defense metabolism. Traditional elicitation methods mimic environmental conditions that trigger plant-specialized metabolism, often with an artificial signal that mimics microbial interaction. Recent insights into the essential role of the plant microbiota, provides new opportunities for elicitation strategies by microbial coculture in a controlled environment. The successful co-culture of in vitro medicinal plants with synthetic microbial communities could enable sustainable production of pharmaceutically important SM.

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While research on the sourdough microbiome has primarily focused on lactic acid bacteria (LAB) and yeast, recent studies have found that acetic acid bacteria (AAB) are also common members. However, the ecology, genomic diversity, and functional contributions of AAB in sourdough remain unknown. To address this gap, we sequenced 29 AAB genomes, including three that represent putatively novel species, from a collection of over 500 sourdough starters surveyed globally from community scientists. We found variations in metabolic traits related to carbohydrate utilization, nitrogen metabolism, and alcohol production, as well as in genes related to mobile elements and defense mechanisms. Sourdough AAB genomes did not cluster when compared to AAB isolated from other environments, although a subset of gene functions was enriched in sourdough isolates. The lack of a sourdough-specific genomic cluster may reflect the nomadic lifestyle of AAB. To assess the consequences of AAB on the emergent function of sourdough starter microbiomes, we constructed synthetic starter microbiomes, varying only the AAB strain included. All AAB strains increased the acidification of synthetic sourdough starters relative to yeast and LAB by 18.5% on average. Different strains of AAB had distinct effects on the profile of synthetic starter volatiles. Taken together, our results begin to define the ways in which AAB shape emergent properties of sourdough and suggest that differences in gene content resulting from intraspecies diversification can have community-wide consequences on emergent function. IMPORTANCE: This study is a comprehensive genomic and ecological survey of acetic acid bacteria (AAB) isolated from sourdough starters. By combining comparative genomics with manipulative experiments using synthetic microbiomes, we demonstrate that even strains with >97% average nucleotide identity can shift important microbiome functions, underscoring the importance of species and strain diversity in microbial systems. We also demonstrate the utility of sourdough starters as a model system to understand the consequences of genomic diversity at the strain and species level on multispecies communities. These results are also relevant to industrial and home-bakers as we uncover the importance of AAB in shaping properties of sourdough starters that have direct impacts on sensory notes and the quality of sourdough bread.

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Synthetic biology conceptualizes biological complexity as a network of biological parts, devices, and systems with predetermined functionalities and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesize and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms, can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multispecies communities. We argue for a shift in perspective from single organism-centred approaches to emphasizing the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities. Graphical Abstract.

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Root metaproteome analysis can reveal the functions that govern plant-microbe and microbe-microbe interactions under specific environmental conditions. Efficient protein extraction method from microbes associated with plant roots is crucial for the comprehensive analysis of the metaproteome. In this chapter, a straightforward protein extraction method for roots of Arabidopsis inoculated with a microbial community that uses only milligrams of tissue is outlined. In addition, the plant inoculation using a synthetic community (SynCom) and the methods for a nanoflow liquid chromatography coupled to a high-resolution/high-accuracy mass spectrometer (LC-MS/MS) are described.

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Our understanding of region-specific microbial function within the gut is limited due to reliance on stool. Using a recently developed capsule device, we exploit regional sampling from the human intestines to develop models for interrogating small intestine (SI) microbiota composition and function. In vitro culturing of human intestinal contents produced stable, representative communities that robustly colonize the SI of germ-free mice. During mouse colonization, the combination of SI and stool microbes altered gut microbiota composition, functional capacity, and response to diet, resulting in increased diversity and reproducibility of SI colonization relative to stool microbes alone. Using a diverse strain library representative of the human SI microbiota, we constructed defined communities with taxa that largely exhibited the expected regional preferences. Response to a fiber-deficient diet was region-specific and reflected strain-specific fiber-processing and host mucus-degrading capabilities, suggesting that dietary fiber is critical for maintaining SI microbiota homeostasis. These tools should advance mechanistic modeling of the human SI microbiota and its role in disease and dietary responses.

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The spread of antibiotic resistance genes (ARGs) in agroecosystems through the application of animal manure is a global threat to human and environmental health. However, the adaptability and colonization ability of animal manure-derived bacteria determine the spread pathways of ARG in agroecosystems, which have rarely been studied. Here, we performed an invasion experiment by creating a synthetic communities (SynCom) with ten isolates from pig manure and followed its assembly during gnotobiotic cultivation of a soil-Arabidopsis thaliana (A. thaliana) system. We found that Firmicutes in the SynCom were efficiently filtered out in the rhizosphere, thereby limiting the entry of tetracycline resistance genes (TRGs) into the plant. However, Proteobacteria and Actinobacteria in the SynCom were able to establish in all compartments of the soil-plant system thereby spreading TRGs from manure to soil and plant. The presence of native soil bacteria prevented the establishment of manure-borne bacteria and effectively reduced the spread of TRGs. Achromobacter mucicolens and Pantoea septica were the main vectors for the entry of tetA into plants. Furthermore, doxycycline stress promoted the horizontal gene transfer (HGT) of the conjugative resistance plasmid RP4 within the SynCom in A. thaliana by upregulating the expression of HGT-related mRNAs. Therefore, this study provides evidence for the dissemination pathways of ARGs in agricultural systems through the invasion of manure-derived bacteria and HGT by conjugative resistance plasmids and demonstrates that the priority establishment of soil bacteria in the rhizosphere limited the spread of TRGs from pig manure to soil-plant systems.

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We present complete genome sequences from 30 bacterial species that can be used to construct defined synthetic communities that stably form in the laboratory under controlled conditions.

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In the understanding of the molecular interaction between plants and their microbiome, a key point is to identify simplified models of the microbiome including relevant bacterial and fungal partners which could also be effective in plant growth promotion. Here, as proof-of-concept, we aim to identify the possible molecular interactions between symbiotic nitrogen-fixing rhizobia and soil fungi (Trichoderma spp.), hence shed light on synergistic roles rhizospheric fungi could have in the biology of symbiotic nitrogen fixation bacteria. We selected 4 strains of the model rhizobium Sinorhizobium meliloti and 4 Trichoderma species (T. velutinum, T. tomentosum, T. gamsii and T. harzianum). In an experimental scheme of 4 ×4 strains x species combinations, we investigated the rhizobia physiological and transcriptomic responses elicited by fungal spent media, as well as spent media effects on rhizobia-host legume plant (alfalfa, Medicago sativa L.) symbiosis. Fungal spent media had large effects on rhizobia, specific for each fungal species and rhizobial strains combination, indicating a generalized rhizobia genotype x fungal genotype interaction, including synergistic, neutral and antagonistic effects on alfalfa symbiotic phenotypes. Differential expression of a high number of genes was shown in rhizobia strains with up to 25% of total genes differentially expressed upon treatment of cultures with fungal spent media. Percentages over total genes and type of genes differentially expressed changed according to both fungal species and rhizobial strain. To support the hypothesis of a relevant rhizobia genotype x fungal genotype interaction, a nested Likelihood Ratio Test indicated that the model considering the fungus-rhizobium interaction explained 23.4% of differentially expressed genes. Our results provide insights into molecular interactions involving nitrogen-fixing rhizobia and rhizospheric fungi, highlighting the panoply of genes and genotypic interactions (fungus, rhizobium, host plant) which may concur to plant symbiosis.

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Microbiomes feature complex interactions between diverse bacteria and bacteriophages. Synthetic microbiomes offer a powerful way to study these interactions; however, a major challenge is obtaining a representative bacteriophage population during the bacterial isolation process. We demonstrate that colony isolation reliably excludes virulent viruses from sample sources with low virion-to-bacteria ratios such as feces, creating "virulent virus-free" controls. When the virulent dsDNA virome is reintroduced to a 73-strain synthetic gut microbiome in a bioreactor model of the human colon, virulent viruses target susceptible strains without significantly altering community structure or metabolism. In addition, we detected signals of prophage induction that associate with virulent predation. Overall, our findings indicate that dilution-based isolation methods generate synthetic gut microbiomes that are heavily depleted, if not devoid, of virulent viruses and that such viruses, if reintroduced, have a targeted effect on community assembly, metabolism, and prophage replication.

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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.

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Microbes and animals have a symbiotic relationship that greatly influences nutrient uptake and animal health. This relationship can be studied using selections of microbes termed synthetic communities, or SynComs. SynComs are used in many different animal hosts, including agricultural animals, to investigate microbial interactions with nutrients and how these affect animal health. The most common host focuses for SynComs are currently mouse and human, from basic mechanistic research through to translational disease models and live biotherapeutic products (LBPs) as treatments. We discuss SynComs used in basic research models and findings that relate to human and animal health and nutrition. Translational use cases of SynComs are discussed, followed by LBPs, especially within the context of agriculture. SynComs still face challenges, such as standardization for reproducibility and contamination risks. However, the future of SynComs is hopeful, especially in the areas of genome-guided SynCom design and custom SynCom-based treatments.

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IMPORTANCE: Synthetic communities (SynComs) are an invaluable tool to characterize and model plant-microbe interactions. Multimember SynComs approximate intricate real-world interactions between plants and their microbiome, but the complexity and time required for their construction increase enormously for each additional member added to the SynCom. Therefore, researchers who study a diversity of microbiomes using SynComs are looking for ways to simplify the use of SynComs. In this manuscript, we evaluate the feasibility of creating ready-to-use freezer stocks of a well-studied seven-member SynCom for maize roots. The frozen ready-to-use SynCom stocks work according to the principle of "just add buffer and apply to sterilized seeds or seedlings" and thus can save time applied in multiple days of laborious growing and combining of multiple microorganisms. We show that ready-to-use SynCom stocks provide comparable results to those of freshly constructed SynComs and thus allow for significant time savings when working with SynComs.

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Yeast research is entering into a new period of scholarship, with new scientific tools, new questions to ask and new issues to consider. The politics of emerging and critical technology can no longer be separated from the pursuit of basic science in fields, such as synthetic biology and engineering biology. Given the intensifying race for technological leadership, yeast research is likely to attract significant investment from government, and that it offers huge opportunities to the curious minded from a basic research standpoint. This article provides an overview of new directions in yeast research with a focus on Saccharomyces cerevisiae, and places these trends in their geopolitical context. At the highest level, yeast research is situated within the ongoing convergence of the life sciences with the information sciences. This convergent effect is most strongly pronounced in areas of AI-enabled tools for the life sciences, and the creation of synthetic genomes, minimal genomes, pan-genomes, neochromosomes and metagenomes using computer-assisted design tools and methodologies. Synthetic yeast futures encompass basic and applied science questions that will be of intense interest to government and nongovernment funding sources. It is essential for the yeast research community to map and understand the context of their research to ensure their collaborations turn global challenges into research opportunities.

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Considering our growing population and our continuous degradation of soil environments, understanding the fundamental ecology of soil biota and plant microbiomes will be imperative to sustaining soil systems. Arbuscular mycorrhizal (AM) fungi extend their hyphae beyond plant root zones, creating microhabitats with bacterial symbionts for nutrient acquisition through a tripartite symbiotic relationship along with plants. Nonetheless, it is unclear what drives these AM fungal-bacterial relationships and how AM fungal functional traits contribute to these relationships. By delving into the literature, we look at the drivers and complexity behind AM fungal-bacterial relationships, describe the shift needed in AM fungal research towards the inclusion of interdisciplinary tools, and discuss the utilization of bacterial datasets to provide contextual evidence behind these complex relationships, bringing insights and new hypotheses to AM fungal functional traits. From this synthesis, we gather that interdependent microbial relationships are at the foundation of understanding microbiome functionality and deciphering microbial functional traits. We suggest using pattern-based inference tools along with machine learning to elucidate AM fungal-bacterial relationship trends, along with the utilization of synthetic communities, functional gene analyses, and metabolomics to understand how AM fungal and bacterial communities facilitate communication for the survival of host plant communities. These suggestions could result in improving microbial inocula and products, as well as a better understanding of complex relationships in terrestrial ecosystems that contribute to plant-soil feedbacks.

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Plant-growth-promoting bacteria (PGPB) help plants thrive in polluted environments and increase crops yield using fewer inputs. Therefore, the design of tailored biofertilizers is of the utmost importance. The purpose of this work was to test two different bacterial synthetic communities (SynComs) from the microbiome of Mesembryanthemum crystallinum, a moderate halophyte with cosmetic, pharmaceutical, and nutraceutical applications. The SynComs were composed of specific metal-resistant plant-growth-promoting rhizobacteria and endophytes. In addition, the possibility of modulating the accumulation of nutraceutical substances by the synergetic effect of metal stress and inoculation with selected bacteria was tested. One of the SynComs was isolated on standard tryptone soy agar (TSA), whereas the other was isolated following a culturomics approach. For that, a culture medium based on M. crystallinum biomass, called Mesem Agar (MA), was elaborated. Bacteria of three compartments (rhizosphere soil, root endophytes, and shoot endophytes) were isolated on standard TSA and MA media, stablishing two independent collections. All bacteria were tested for PGP properties, secreted enzymatic activities, and resistance towards As, Cd, Cu, and Zn. The three best bacteria from each collection were selected in order to produce two different consortiums (denominated TSA- and MA-SynComs, respectively), whose effect on plant growth and physiology, metal accumulation, and metabolomics was evaluated. Both SynComs, particularly MA, improved plant growth and physiological parameters under stress by a mixture of As, Cd, Cu, and Zn. Regarding metal accumulation, the concentrations of all metals/metalloids in plant tissues were below the threshold for plant metal toxicity, indicating that this plant is able to thrive in polluted soils when assisted by metal/metalloid-resistant SynComs and could be safely used for pharmaceutical purposes. Initial metabolomics analyses depict changes in plant metabolome upon exposure to metal stress and inoculation, suggesting the possibility of modulating the concentration of high-value metabolites. In addition, the usefulness of both SynComs was tested in a crop plant, namely Medicago sativa (alfalfa). The results demonstrate the effectiveness of these biofertilizers in alfalfa, improving plant growth, physiology, and metal accumulation.

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Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.

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Microbial soil communities form commensal relationships with plants to promote the growth of both parties. The optimization of plant-microbe interactions to advance sustainable agriculture is an important field in agricultural research. However, investigation in this field is hindered by a lack of model microbial community systems and efficient approaches for building these communities. Two key challenges in developing standardized model communities are maintaining community diversity over time and storing/resuscitating these communities after cryopreservation, especially considering the different growth rates of organisms. Here, a model synthetic community (SynCom) of 16 soil microorganisms commonly found in the rhizosphere of diverse plant species, isolated from soil surrounding a single switchgrass plant, has been developed and optimized for in vitro experiments. The model soil community grows reproducibly between replicates and experiments, with a high community α-diversity being achieved through growth in low-nutrient media and through the adjustment of the starting composition ratios for the growth of individual organisms. The community can additionally be cryopreserved with glycerol, allowing for easy replication and dissemination of this in vitro system. Furthermore, the SynCom also grows reproducibly in fabricated ecosystem devices (EcoFABs), demonstrating the application of this community to an existing in vitro plant-microbe system. EcoFABs allow reproducible research in model plant systems, offering the precise control of environmental conditions and the easy measurement of plant microbe metrics. Our results demonstrate the generation of a stable and diverse microbial SynCom for the rhizosphere that can be used with EcoFAB devices and can be shared between research groups for maximum reproducibility. IMPORTANCE Microbes associate with plants in distinct soil communities to the benefit of both the soil microbes and the plants. Interactions between plants and these microbes can improve plant growth and health and are therefore a field of study in sustainable agricultural research. In this study, a model community of 16 soil bacteria has been developed to further the reproducible study of plant-soil microbe interactions. The preservation of the microbial community has been optimized for dissemination to other research settings. Overall, this work will advance soil microbe research through the optimization of a robust, reproducible model community.

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With a growing world population and increasing frequency of climate disturbance events, we are in dire need of methods to improve plant productivity, resilience, and resistance to both abiotic and biotic stressors, both for agriculture and conservation efforts. Microorganisms play an essential role in supporting plant growth, environmental response, and susceptibility to disease. However, understanding the specific mechanisms by which microbes interact with each other and with plants to influence plant phenotypes is a major challenge due to the complexity of natural communities, simultaneous competition and cooperation effects, signalling interactions, and environmental impacts. Synthetic communities are a major asset in reducing the complexity of these systems by simplifying to dominant components and isolating specific variables for controlled experiments, yet there still remains a large gap in our understanding of plant microbiome interactions. This perspectives article presents a brief review discussing ways in which metabolic modelling can be used in combination with synthetic communities to continue progress toward understanding the complexity of plant-microbe-environment interactions. We highlight the utility of metabolic models as applied to a community setting, identify different applications for both flux balance and elementary flux mode simulation approaches, emphasize the importance of ecological theory in guiding data interpretation, and provide ideas for how the integration of metabolic modelling techniques with big data may bridge the gap between simplified synthetic communities and the complexity of natural plant-microbe systems.

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Sphagnum peatmosses are fundamental members of peatland ecosystems, where they contribute to the uptake and long-term storage of atmospheric carbon. Warming threatens Sphagnum mosses and is known to alter the composition of their associated microbiome. Here, we use a microbiome transfer approach to test if microbiome thermal origin influences host plant thermotolerance. We leveraged an experimental whole-ecosystem warming study to collect field-grown Sphagnum, mechanically separate the associated microbiome and then transfer onto germ-free laboratory Sphagnum for temperature experiments. Host and microbiome dynamics were assessed with growth analysis, Chla fluorescence imaging, metagenomics, metatranscriptomics and 16S rDNA profiling. Microbiomes originating from warming field conditions imparted enhanced thermotolerance and growth recovery at elevated temperatures. Metagenome and metatranscriptome analyses revealed that warming altered microbial community structure in a manner that induced the plant heat shock response, especially the HSP70 family and jasmonic acid production. The heat shock response was induced even without warming treatment in the laboratory, suggesting that the warm-microbiome isolated from the field provided the host plant with thermal preconditioning. Our results demonstrate that microbes, which respond rapidly to temperature alterations, can play key roles in host plant growth response to rapidly changing environments.

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A range of game-changing biodigital and biodesign technologies are coming of age all around us, transforming our world in complex ways that are hard to predict. Not a day goes by without news of how data-centric engineering, algorithm-driven modelling, and biocyber technologies-including the convergence of artificial intelligence, machine learning, automated robotics, quantum computing, and genome editing-will change our world. If we are to be better at expecting the unexpected in the world of wine, we need to gain deeper insights into the potential and limitations of these technological developments and advances along with their promise and perils. This article anticipates how these fast-expanding bioinformational and biodesign toolkits might lead to the creation of synthetic organisms and model systems, and ultimately new understandings of biological complexities could be achieved. A total of four future frontiers in wine yeast research are discussed in this article: the construction of fully synthetic yeast genomes, including minimal genomes; supernumerary pan-genome neochromosomes; synthetic metagenomes; and synthetic yeast communities. These four concepts are at varying stages of development with plenty of technological pitfalls to overcome before such model chromosomes, genomes, strains, and yeast communities could illuminate some of the ill-understood aspects of yeast resilience, fermentation performance, flavour biosynthesis, and ecological interactions in vineyard and winery settings. From a winemaker's perspective, some of these ideas might be considered as far-fetched and, as such, tempting to ignore. However, synthetic biologists know that by exploring these futuristic concepts in the laboratory could well forge new research frontiers to deepen our understanding of the complexities of consistently producing fine wines with different fermentation processes from distinctive viticultural terroirs. As the saying goes in the disruptive technology industry, it take years to create an overnight success. The purpose of this article is neither to glorify any of these concepts as a panacea to all ills nor to crucify them as a danger to winemaking traditions. Rather, this article suggests that these proposed research endeavours deserve due consideration because they are likely to cast new light on the genetic blind spots of wine yeasts, and how they interact as communities in vineyards and wineries. Future-focussed research is, of course, designed to be subject to revision as new data and technologies become available. Successful dislodging of old paradigms with transformative innovations will require open-mindedness and pragmatism, not dogmatism-and this can make for a catch-22 situation in an archetypal traditional industry, such as the wine industry, with its rich territorial and socio-cultural connotations.

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