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Plant roots exude a complex mixture of metabolites into the rhizosphere. Primary and secondary metabolites exuded from roots are key drivers of root-soil microbe interactions that contribute to the structure and function of microbial communities in agricultural and natural ecosystems.
ABSTRACT Field pennycress ( Thlaspi arvense L.) is an annual in the Brassicaceae family and is currently being developed as an oilseed intermediate crop suitable for renewable biodiesel and jet fuel. It displays many desirable characteristics for this role including cold tolerance, a rapid life cycle, and a seed fatty acid profile conducive to bioenergy generation. These traits make field pennycress favorable for winter oilseed cultivation in the inland Pacific Northwest (iPNW). Simultaneously, intermediate crops are an increasingly recognized component of both agronomic sustainability and soil health management. Intermediate crops enhance soil microbial diversity, which benefits both soil and plant health. To understand the impact of field pennycress on soil microbial diversity, two natural accessions and seven experimental accessions were grown at three sites in Eastern Washington. Aboveground biomass and rhizosphere soil were then collected. Soil genomic DNA was extracted from rhizosphere samples and used to generate an amplicon library for bacterial (16S) and fungal (ITS) rRNA sequences. The resulting libraries were analyzed in QIIME2, which revealed that not only did the fad2 deficient line from the Spring32‐10 background have significantly increased aboveground biomass production compared to other pennycress genotypes, but also displayed significantly higher β‐diversity in the rhizosphere community specifically at the site experiencing the driest conditions. ANCOM analysis showed that multiple sequences similar to beneficial plant and soil health enhancing organisms such as Trichoderma spirale , Pseudomonas spp., and Methylobacterium goesingense were found to be enriched in the microbiome of the fad2 Spring32‐10 background also at that site. To add additional context to rhizosphere community data, root exudates from two pennycress genotypes were captured in magenta boxes and analyzed using HPLC. Future work will expand our understanding of the mechanisms by which field pennycress creates diversity in the rhizosphere, thus expanding our ability to cultivate this crop in the iPNW.
The rapidly growing industry of crop biostimulants leverages the application of plant growth promoting rhizobacteria (PGPR) to promote plant growth and health. However, introducing nonnative rhizobacteria may impact other aspects of ecosystem functioning and have legacy effects; these potential consequences are largely unexplored. Nontarget consequences of PGPR may include changes in resident microbiomes, nutrient cycling, pollinator services, functioning of other herbivores, disease suppression, and organic matter persistence. Importantly, we lack knowledge of whether these ecosystem effects may manifest in adjacent ecosystems. The introduced PGPR can leave a functional legacy whether they persist in the community or not. Legacy effects include shifts in resident microbiomes and their temporal dynamics, horizontal transfer of genes from the PGPR to resident taxa, and changes in resident functional groups and interaction networks. Ecosystem functions may be affected by legacies PGPR leave following niche construction, such as when PGPR alter soil pH that in turn alters biogeochemical cycling rates. Here, we highlight new research directions to elucidate how introduced PGPR impact resident microbiomes and ecosystem functions and their capacity for legacy effects.
Coccidioidomycosis, also known as Valley fever, is a disease caused by the fungal pathogen Coccidioides. Unfortunately, patients are often misdiagnosed with bacterial pneumonia, leading to inappropriate antibiotic treatment. The soil Bacillus subtilis-like species exhibits antagonistic properties against Coccidioides in vitro; however, the antagonistic capabilities of host microbiota against Coccidioides are unexplored. We sought to examine the potential of the tracheal and intestinal microbiomes to inhibit the growth of Coccidioides in vitro. We hypothesized that an uninterrupted lawn of microbiota obtained from antibiotic-free mice would inhibit the growth of Coccidioides, while partial in vitro depletion through antibiotic disk diffusion assays would allow a niche for fungal growth. We observed that the microbiota grown on 2×GYE (GYE) and Columbia colistin and nalidixic acid with 5% sheep’s blood agar inhibited the growth of Coccidioides, but microbiota grown on chocolate agar did not. Partial depletion of the microbiota through antibiotic disk diffusion revealed diminished inhibition and comparable growth of Coccidioides to controls. To characterize the bacteria grown and identify potential candidates contributing to the inhibition of Coccidioides, 16S rRNA sequencing was performed on tracheal and intestinal agar cultures and murine lung extracts. We found that the host bacteria likely responsible for this inhibition primarily included Lactobacillus and Staphylococcus. The results of this study demonstrate the potential of the host microbiota to inhibit the growth of Coccidioides in vitro and suggest that an altered microbiome through antibiotic treatment could negatively impact effective fungal clearance and allow a niche for fungal growth in vivo.
Droughts are becoming more frequent and intense with climate change. As plants and microbes respond to drought, there may be consequences for the vast stocks of organic carbon stored in soils. If microbes sustain their activity under drought, soils could lose carbon, especially if inputs from plants decline. Empirical and theoretical studies reveal multiple mechanisms of microbial drought resistance, including tolerance and avoidance. Physiological responses allow microbes to acclimate to drought within minutes to days. Along with dispersal, shifts in community composition could allow microbiomes to maintain functioning despite drought. Microbes might also adapt to drier conditions through evolutionary processes. Together, these mechanisms could result in soil carbon losses larger than currently anticipated under climate change.
Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.
A plant's neighborhood context can alter its interactions with other organisms, but little is known about how these dynamics occur belowground, especially with soil microbes. Microbial communities in rhizosphere soil are influenced by many factors, including abiotic conditions and root-derived signals. In particular, root exudates have strong effects on rhizosphere assembly, respond to changes in abiotic conditions, and help plants interact with neighbors. Therefore, we predicted that root exudates likely play a central role in neighbor-induced shifts in rhizosphere communities. We conducted a greenhouse experiment to test this and determine how the rhizosphere bacterial community of a focal plant, Panicum virgatum, changed when beside different neighbors, and whether these shifts were mediated by neighbor-induced changes in root exudation. We found that neighbor altered both focal plant exudates and rhizosphere community, and that changes were largest when the focal plant was beside the most competitive neighbor, Rudbeckia hirta, which reduced both focal plant growth and nitrogen uptake. Several factors contributed to neighbor impacts on rhizosphere assembly, including neighbor-induced changes in root exudates during nitrogen-limitation and microbial spillover from roots of larger neighbors. Using an additional soil incubation, we also found that these changes in exudates can have even greater effects on soil nutrients than on microbial assembly. Overall, we show that neighbors influence one another's microbiomes, and highlight neighbor-induced changes in root exudates as one mechanism through which this may occur. Furthermore, this work suggests that rhizosphere assembly may differ in mixed-species communities and thus emphasizes a need for microbiome studies that consider neighborhood context.
Wetlands are globally significant carbon storage hotspots. Recent research has suggested that microbially derived metabolites may contribute to soil organic matter formation. Identifying pathways driving the formation of such metabolites is critical to understand the global impact of wetland carbon cycling. Here, we evaluate the presence of chain-elongating organisms converting two to three carbon compounds (i.e., lactic and acetic acid) to medium-chain carboxylic acids (MCCA; i.e., six-carbon caproic acid) in wetland soils. We demonstrate the enrichment of a lactic acid-driven chain-elongating community from wetland soils producing a mixture of butyric and caproic acid. The enriched community was dominated by Clostridiaceae, Ruminococcaceae, and Lachnospiraceae, three families with known chain elongators. Amplicon sequencing identified three Ruminococcaceae and one Clostridiaceae zero-radius OTU (zOTU) that were (i) present in the soil, (ii) enriched over 1% relative abundance in the bioreactor, and (iii) were closely related to known chain elongators. Moreover, close relatives of the three Ruminococcaceae zOTU were also observed in several other wetland microbiomes. From this observation, we conclude that close relatives of known chain elongators, potentially capable of lactic acid-driven MCCA production themselves, are present in wetland soils. This observation may have implications for our understanding of carbon cycling and storage in wetland ecosystems.
Abstract Background Suboptimal nitrogen availability is a primary constraint for crop production in low-input agroecosystems, while nitrogen fertilization is a primary contributor to the energy, economic, and environmental costs of crop production in high-input agroecosystems. In this article we consider avenues to develop crops with improved nitrogen capture and reduced requirement for nitrogen fertilizer. Scope Intraspecific variation for an array of root phenotypes has been associated with improved nitrogen capture in cereal crops, including architectural phenotypes that colocalize root foraging with nitrogen availability in the soil; anatomical phenotypes that reduce the metabolic costs of soil exploration, improve penetration of hard soil, and exploit the rhizosphere; subcellular phenotypes that reduce the nitrogen requirement of plant tissue; molecular phenotypes exhibiting optimized nitrate uptake kinetics; and rhizosphere phenotypes that optimize associations with the rhizosphere microbiome. For each of these topics we provide examples of root phenotypes which merit attention as potential selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of soil hydrology and impedance, phenotypic plasticity, integrated phenotypes, in silico modeling, and breeding strategies using high throughput phenotyping for co-optimization of multiple phenes. Conclusions Substantial phenotypic variation exists in crop germplasm for an array of root phenotypes that improve nitrogen capture. Although this topic merits greater research attention than it currently receives, we have adequate understanding and tools to develop crops with improved nitrogen capture. Root phenotypes are underutilized yet attractive breeding targets for the development of the nitrogen efficient crops urgently needed in global agriculture.
Understanding the spatiotemporal dynamics of microbial communities is essential for predicting their ecological roles and interactions with host plants. In a recent study, Wei and colleagues (Microbiol Spectr 13:e02097-24, 2024) investigated fungal diversity across multiple plant and soil compartments in rubber trees over two seasons and two geographically distinct regions in China. Their findings revealed that alpha diversity was primarily influenced by seasonal changes and physicochemical factors, while beta diversity exhibited a strong geographical pattern, shaped by leaf phosphorus and soil available potassium. These results highlight the role of environmental drivers in shaping within-community diversity, while other factors contribute to the differences between fungal communities across the soil–plant continuum. By distinguishing the effects of temporal and spatial factors, this study provides detailed insights into plant-associated microbiomes and emphasizes the need for further research on the functional implications of microbial diversity in the context of changing environmental and agricultural conditions.
The advance of high-throughput molecular biology tools allows in-depth profiling of microbial communities in soils, which possess a high diversity of prokaryotic microorganisms. Amplicon-based sequencing of 16S rRNA genes is the most common approach to studying the richness and composition of soil prokaryotes. To reliably detect different taxonomic lineages of microorganisms in a single soil sample, an adequate pipeline including DNA isolation, primer selection, PCR amplification, library preparation, DNA sequencing, and bioinformatic post-processing is required. Besides DNA sequencing quality and depth, the selection of PCR primers and PCR amplification reactions arguably have the largest influence on the results. This study tested the performance and potential bias of two primer pairs, i.e., 515F (Parada)-806R (Apprill) and 515F (Parada)-926R (Quince) in the standard pipelines of 16S rRNA gene Illumina amplicon sequencing protocol developed by the Earth Microbiome Project (EMP), against shotgun metagenome-based 16S rRNA gene reads. The evaluation was conducted using five differently managed soils. We observed a higher richness of soil total prokaryotes by using reverse primer 806R compared to 926R, contradicting to in silico evaluation results. Both primer pairs revealed various degrees of taxon-specific bias compared to metagenome-derived 16S rRNA gene reads. Nonetheless, we found consistent patterns of microbial community variation associated with different land uses, irrespective of primers used. Total microbial communities, as well as ammonia oxidizing archaea (AOA), the predominant ammonia oxidizers in these soils, shifted along with increased soil pH due to agricultural management. In the unmanaged low pH plot abundance of AOA was dominated by the acid-tolerant NS-Gamma clade, whereas limed agricultural plots were dominated by neutral-alkaliphilic NS-Delta/NS-Alpha clades. This study stresses how primer selection influences community composition and highlights the importance of primer selection for comparative and integrative studies, and that conclusions must be drawn with caution if data from different sequencing pipelines are to be compared.
Abstract The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost–climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post‐thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose that Assembly Theory provides a framework to better understand thaw‐mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well‐suited to thrive in changing environmental conditions. We predict that on a short timescale and following high‐disturbance thaw (e.g., thermokarst), stochasticity dominates post‐thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower‐intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post‐thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.
Background The prokaryotic antiviral defense systems are crucial for mediating prokaryote-virus interactions that influence microbiome functioning and evolutionary dynamics. Despite the prevalence and significance of prokaryotic antiviral defense systems, their responses to abiotic stress and ecological consequences remain poorly understood in soil ecosystems. We established microcosm systems with varying concentrations of hexavalent chromium (Cr(VI)) to investigate the adaptive modifications of prokaryotic antiviral defense systems under abiotic stress. Results Utilizing hybrid metagenomic assembly with long-read and short-read sequencing, we discovered that anti- viral defense systems were more diverse and prevalent in heavily polluted soils, which was corroborated by meta-analyses of public datasets from various heavy metal-contaminated sites. As the Cr(VI) concentration increased, prokaryotes with defense systems favoring prokaryote-virus mutualism gradually supplanted those with defense systems incurring high adaptive costs. Additionally, as Cr(VI) concentrations increased, enriched antiviral defense systems exhibited synchronization with microbial heavy metal resistance genes. Furthermore, the proportion of antiviral defense systems carried by mobile genetic elements (MGEs), including plasmids and viruses, increased by approximately 43% and 39%, respectively, with rising Cr concentrations. This trend is conducive to strengthening the dissemination and sharing of defense resources within microbial communities. Conclusions Overall, our study reveals the adaptive modification of prokaryotic antiviral defense systems in soil ecosystems under abiotic stress, as well as their positive contributions to establishing prokaryote-virus mutualism and the evolution of microbial heavy metal resistance. These findings advance our understanding of microbial adaptation in stressful environments and may inspire novel approaches for microbiome manipulation and bioremediation.
Microbial interactions shape the structure and function of microbial communities; microbial association networks in specic environments have been widely developed to explore these complex systems, but their wired pattern across microbiomes in various environments at the global scale remains unexplored. Here we have inferred an Earth microbial association network from a communal catalogue with 23,595 samples and 12,646 exact sequence variants from 14 environments in the Earth Microbiome Project dataset. Results: This non-random scale-free Earth microbial association network consisted of 8 taxonomy distinct modules linked with dierent environments, which featured environment specic microbial associations. Dierent topological features of subnetworks inferred from datasets trimmed into uniform size indicate distinct association patterns in the microbiomes of various environments. The proportions of specialist edges, which ranged from 43.0% to 65.7%, highlight that environmental specic microbial associations are essential features of microbiomes in various environments. Based on edge-overlap similarity, the microbiomes of various environments were clustered into two groups, which were mainly bridged by the microbiomes of plant and animal surface. Acidobacteria Gp2 and Nisaea were identied as hubs in most of subnetworks. Negative edges proportions ranged from 1.9% in the soil subnetwork to 48.9% the non-saline surface subnetwork, suggesting various environments experience distinct intensities of competition or niche dierentiation. Conclusion: This investigation provides a new resource for examining Earth microbial association patterns across environments and emphasizes the network perspective for comprehensively understanding unique microbiome features. Keywords: Association pattern; Earth microbiomes; Genelist edges; Network hubs; Negative associations; Specialist edges; Topological properties
Antarctic environments are dominated by microorganisms, which are vulnerable to viral infection. Although several studies have investigated the phylogenetic repertoire of bacteria and viruses in these poly-extreme environments with freezing temperatures, high ultra violet irradiation levels, low moisture availability and hyper-oligotrophy, the evolutionary mechanisms governing microbial immunity remain poorly understood. Using genome-resolved metagenomics, we test the hypothesis that Antarctic poly-extreme high-latitude microbiomes harbour diverse adaptive immune systems. Our analysis reveals the prevalence of prophages in bacterial genomes (Bacteroidota and Verrucomicrobiota), suggesting the significance of lysogenic infection strategies in Antarctic soils. Furthermore, we demonstrate the presence of diverse CRISPR-Cas arrays, including Class 1 arrays (Types I-B, I-C, and I-E), alongside systems exhibiting novel gene architecture among their effector cas genes. Notably, a Class 2 system featuring type V variants lacks CRISPR arrays, encodes Cas1 and Cas2 adaptation module genes. Phylogenetic analysis of Cas12 effector proteins hints at divergent evolutionary histories compared to classified type V effectors and indicates that TnpB is likely the ancestor of Cas12 nucleases. Our findings suggest substantial novelty in Antarctic cas sequences, likely driven by strong selective pressures. These results underscore the role of viral infection as a key evolutionary driver shaping polar microbiomes.
This repository contains data and code for statistically comparing soil microbial communities across four different wetland sites and making publication quality figures. It is similar to other microbiome analysis but is specific for this project.
Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized , and so name our tool MetConSIN: Met abolically Con textualized S pecies I nteraction N etworks.
Rhizosphere arguably embodies the most diverse microbial ecosystem on the planet, yet it is largely a functional ‘black box’ of belowground plant-microbiome interactions. The rhizosphere is the primary site of entry for subsurface injection of fixed carbon (C) into soil with impacts on local to global scale C biogeochemistry and ultimately Earth’s climate. While spatial organization of rhizosphere is central to its function, small scale and steep microbial and geochemical gradients within this dynamic region make it easily disrupted by sampling. The significant challenge presented by sampling blocks elucidation of discreet functions, drivers, and interactions within rhizosphere ecosystems. Here, we describe a non-destructive sampling method linked to metaproteomic analysis in order to measure temporal shifts in the microbial composition and function of rhizosphere. A robust, non-destructive method of sampling microbial hotspots within rhizosphere provides an unperturbed window into the elusive functional interactome of this system over time and space.