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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Plant–soil feedback under drought: does history shape the future?

Plant–soil feedback (PSF) is widely recognised as a driver of plant community composition, but understanding of its response to drought remains in its infancy. Here, we provide a conceptual framework for the role of drought in PSF, considering plant traits, drought severity, and historical precipitation over ecological and evolutionary timescales. Comparing experimental studies where plants and microbes do or do not share a drought history (through co-sourcing or conditioning), we hypothesise that plants and microbes with a shared drought history experience more positive PSF under subsequent drought. To reflect real-world responses to drought, future studies need to explicitly include plant–microbial co-occurrence and potential co-adaptation and consider the precipitation history experienced by both plants and microbes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Techno-Economic and Life Cycle Assessments for Sustainable Rare Earth Recovery from Coal Byproducts using Biosorption

Coal byproducts could be a promising feedstock to alleviate the supply risk of critical rare earth elements (REEs) due to their abundance and REE content. Herein, we investigated the economic and environmental potential of producing REEs from coal fly ash and lignite through an integrated process of leaching, biosorption, and oxalic precipitation on the basis of experimental data and modeling results. Two microbe immobilization systems (polyethylene glycol diacrylate (PEGDA) microbe beads and Si sol–gels) were examined for their efficiency in immobilizing Arthrobacter nicotianae to selectively recover REEs. Techno-economic analysis revealed that North Dakota lignite could be a profitable feedstock when Si sol–gel is used due to its high cell loading and REE adsorption capacity as well as high reuse cycles. Life cycle analysis revealed that Si sol–gel-based biosorption could be more environmental friendly than the prevailing REE production in China due to the use of less toxic chemicals. However, fly ash sourced from Powder River Basin coals was neither profitable nor environmentally sustainable, primarily due to low solubility of high-value scandium at an economical pulp density (100 g ash/L of acid solution). To further improve the proposed biotechnology, future research could focus on scandium recovery, leaching efficiency at a high pulp density, and reuse cycles of the immobilized microbes.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Root exudate composition reflects drought severity gradient in blue grama (Bouteloua gracilis)

Abstract Plant survival during environmental stress greatly affects ecosystem carbon (C) cycling, and plant–microbe interactions are central to plant stress survival. The release of C-rich root exudates is a key mechanism plants use to manage their microbiome, attracting beneficial microbes and/or suppressing harmful microbes to help plants withstand environmental stress. However, a critical knowledge gap is how plants alter root exudate concentration and composition under varying stress levels. In a greenhouse study, we imposed three drought treatments (control, mild, severe) on blue grama ( Bouteloua gracilis Kunth Lag. Ex Griffiths), and measured plant physiology and root exudate concentration and composition using GC–MS, NMR, and FTICR. With increasing drought severity, root exudate total C and organic C increased concurrently with declining predawn leaf water potential and photosynthesis. Root exudate composition mirrored the physiological gradient of drought severity treatments. Specific compounds that are known to alter plant drought responses and the rhizosphere microbiome mirrored the drought severity-induced root exudate compositional gradient. Despite reducing C uptake, these plants actively invested C to root exudates with increasing drought severity. Patterns of plant physiology and root exudate concentration and composition co-varied along a gradient of drought severity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Accounting for linkages between wildfire-driven shifts in plant-microbial interactions and soil carbon dynamics in Arctic tundra

Increasing wildfire regimes in the rapidly changing Arctic tundra are altering the soil carbon budget through increased permafrost degradation, shrubs expansion, and shifts in microbial activities. Whether future arctic wildfires will result in net C losses or gains in the future will depend on complex biotic and abiotic interactions that regulate belowground C biogeochemical processes, including linkages among biotic communities. One important linkage is plant-microbe interactions. While these interactions are likely shaped or altered by wildfires, they remain little explored in the context of successional trajectories. Yet, incorporating plant-microbe interactions in frameworks for defining and understanding post-fire soil C trajectories is critical to predict belowground C responses to future tundra wildfires. Here, we provide examples of and discuss how fire-mediated changes in plant-soil-microbe (PSM) interactions can impact soil C dynamics in the Arctic tundra. We consider different impacts of wildfires on PSM interactions and their implications to soil C dynamics, as well as the nuances associated with particular wildfire regimes (severity and intensity) and successional timescales. We suggest that accounting for plant-microbial linkages in future wildfire-succession interactions frameworks can inform future experimental designs and reduce uncertainties in our ability to predict the net effect of Arctic wildfires on ecosystem C.

fungi, bacteria↗
DOE OSTI2025

BONCAT-Live for isolation and cultivation of active environmental bacteria

In diverse environments, microbes drive a myriad of processes, from geochemical and nutrient cycling to interspecies interactions, including associations with plants and animals. Their physiological state is dynamic and impacted by abiotic and biotic conditions, responding to environmental fluctuations by changes in cellular metabolism, according to their genetic potential. Molecular, cellular, and genomic approaches can identify and measure microbial responses and adaptation to environmental changes in native communities. However, isolating individual microbial cells that respond to specific changes for cultivation has been difficult. To address this, we implemented a novel bacterial isolation approach (BONCAT-Live) by integrating bio-orthogonal non-canonical amino acid tagging (BONCAT) in diverse native communities, with isolation and cultivation of cells responding to specific stimuli, at different time scales. In frozen Arctic permafrost samples, we identified and isolated dormant bacteria that become active after thawing under native or nutrient-enriched conditions. From the Populus tree rhizosphere, we isolated strains that thrive under high concentrations of root exudates that act as defense compounds and nutrients. In the human microbiome, we identified and isolated bacteria that rapidly proliferated when exposed to metabolites provided by the host or other co-occurring microbes. Further characterization of isolated bacterial strains will provide opportunities for in-depth determination of how these microbes adapt to changes in their environments, individually and as part of model communities.

Analytical Methods↗
DOE OSTI2020

CeMbio - The Caenorhabditis elegans Microbiome Resource

The study of microbiomes by sequencing has revealed a plethora of correlations between microbial community composition and various life-history characteristics of the corresponding host species. However, inferring causation from correlation is often hampered by the sheer compositional complexity of microbiomes, even in simple organisms. Synthetic communities offer an effective approach to infer cause-effect relationships in host-microbiome systems. Yet the available communities suffer from several drawbacks, such as artificial (thus non-natural) choice of microbes, microbe-host mismatch (e.g., human microbes in gnotobiotic mice), or hosts lacking genetic tractability. Here we introduce CeMbio, a simplified natural Caenorhabditis elegans microbiota derived from our previous meta-analysis of the natural microbiome of this nematode. The CeMbio resource is amenable to all strengths of the C. elegans model system, strains included are readily culturable, they all colonize the worm gut individually, and comprise a robust community that distinctly affects nematode life-history. Several tools have additionally been developed for the CeMbio strains, including diagnostic PCR primers, completely sequenced genomes, and metabolic network models. With CeMbio, we provide a versatile resource and toolbox for the in-depth dissection of naturally relevant host-microbiome interactions in C. elegans.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Digital Droplet PCR and Mesocosm-Based Methods to Evaluate Biocontainment Strategies in a Native Soil Ecosystem

Genetically modified industrial production microbes and their associated bioproducts have emerged as an integral component of a sustainable bioeconomy. However, the rapid development of these innovative technologies raises biosecurity concerns, namely, the risk of environmental escape. Thus, the realization of a bioeconomy hinges not only on the development and deployment of microbial production hosts, but also on the development of secure biosystems and biocontainment designs. Current laboratory-based biocontainment testing systems do not accurately reflect the complexities found in natural environments, necessitating an environmentally relevant analysis pipeline that allows for the detection of rare escapees within a complex soil microbiome and differentiation between closely related strains. To this end, we have developed an approach that utilizes soil mesocosms and integrated digital droplet PCR (ddPCR) system to evaluate the efficacy of novel biocontainment strategies. We demonstrate the utility of this approach by modeling contamination with industrial microbial chasses versus their biocontained counterparts. Here we demonstrate the broad utility of this system by highlighting findings from strains of Saccharomyces cerevisiae that are contained with an inducible toxin anti-toxin system, strains of Synechocystis sp. PCC 6803 contained via gene knockout or toxin anti-toxin system, and strains of Escherichia coli that are contained via genomic recoding. We also show that ddPCR can be used to detect gene copies from E. coli equal to those counted by traditional spot plating assays. The resultant data demonstrates that this system has broad utility across diverse microbial chassis and biocontainment strategies and enables researchers to track the fate of our contaminating microbe with high sensitivity in the soil. The findings presented here support the use of this mesocosm-based approach to assess the environmental impact of industrial microbes and to validate biocontainment strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Identifying microbial drivers in biological phenotypes with a Bayesian network regression model

Abstract In Bayesian Network Regression models, networks are considered the predictors of continuous responses. These models have been successfully used in brain research to identify regions in the brain that are associated with specific human traits, yet their potential to elucidate microbial drivers in biological phenotypes for microbiome research remains unknown. In particular, microbial networks are challenging due to their high dimension and high sparsity compared to brain networks. Furthermore, unlike in brain connectome research, in microbiome research, it is usually expected that the presence of microbes has an effect on the response (main effects), not just the interactions. Here, we develop the first thorough investigation of whether Bayesian Network Regression models are suitable for microbial datasets on a variety of synthetic and real data under diverse biological scenarios. We test whether the Bayesian Network Regression model that accounts only for interaction effects (edges in the network) is able to identify key drivers (microbes) in phenotypic variability. We show that this model is indeed able to identify influential nodes and edges in the microbial networks that drive changes in the phenotype for most biological settings, but we also identify scenarios where this method performs poorly which allows us to provide practical advice for domain scientists aiming to apply these tools to their datasets. BNR models provide a framework for microbiome researchers to identify connections between microbes and measured phenotypes. We allow the use of this statistical model by providing an easy‐to‐use implementation which is publicly available Julia package at https://github.com/solislemuslab/BayesianNetworkRegression.jl .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Fermentative conversion of unpretreated plant biomass: A thermophilic threshold for indigenous microbial growth

Here, naturally occurring, microbial contaminants were found in plant biomasses from common bioenergy crops and agricultural wastes. Unexpectedly, indigenous thermophilic microbes were abundant, raising the question of whether they impact thermophilic consolidated bioprocessing fermentations that convert biomass directly into useful bioproducts. Candidate microbial platforms for biomass conversion, Acetivibrio thermocellus (basionym Clostridium thermocellum; T opt 60 °C) and Caldicellulosiruptor bescii (T opt 78 °C), each degraded a wide variety of plant biomasses, but only A. thermocellus was significantly affected by the presence of indigenous microbial populations harbored by the biomass. Indigenous microbial growth was eliminated at ≥75 °C, conditions where C. bescii thrives, but where A. thermocellus cannot survive. Therefore, 75 °C is the thermophilic threshold to avoid sterilizing pre-treatments on the biomass that prevents native microbes from competing with engineered microbes and forming undesirable by-products. Thermophiles that naturally grow at and above 75 °C offer specific advantages as platform microorganisms for biomass conversion into fuels and chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Dairy manure acidogenic fermentation at hyperthermophilic temperature enabled superior activity of thermostable hydrolytic enzymes linked to the genus Caldicoprobacter

In this study, fermentation experiments were conducted under mesophilic, thermophilic, and hyperthermophilic conditions to investigate adaptation of microbial communities and its effect on extracellular enzyme activities toward degradation of cellulose, hemicellulose and proteins in dairy manure. Here, hyperthermophilic conditions transformed the microbiome structure and stimulated activity of extracellular proteolytic, cellulolytic, and hemicellulolytic enzymes. Specifically, the activities of protease, cellulose 1,4-β-cellobiosidase, and β-glucosidase secreted by hyperthermophilic microbes were higher by 22%, 47% and 49% compared to those produced by mesophilic and thermophilic communities. Enhanced hydrolytic activity of hyperthermophilic microbes enabled improved feedstock solubilization and production of 39% and 22% more soluble COD than mesophilic and thermophilic microbes, respectively. Connections between hydrolytic function and microbial community structure at various temperatures were assessed using the PICRUSt2 computational tool. Genus Caldicoprobacter was identified as the primary candidate responsible for increased production of thermostable endo-1,4-β-glucanase, β-glucosidase and endo-1,4-β-xylanase, and enhanced hydrolytic performance of hyperthermophilic microbial community.

09 BIOMASS FUELS↗
DOE OSTI2023

Genetic determinants of switchgrass-root-associated microbiota in field sites spanning its natural range

A fundamental goal in plant microbiome research is to determine the relative impacts of host and environmental effects on root microbiota composition, particularly how host genotype impacts bacterial community composition. Most studies characterizing the effect of plant genotype on root microbiota undersample host genetic diversity and grow plants outside of their native ranges, making the associations between host and microbes difficult to interpret. Here, we characterized the root microbiota of a large diversity panel of switchgrass, a North American native C4 bioenergy crop, in three field locations spanning its native range. Our data, composed of 1,961 samples, suggest that field location is the primary determinant of microbiome composition; however, substantial heritable variation is widespread across bacterial taxa, especially those in the Sphingomonadaceae family. Despite diverse compositions, relatively few highly prevalent taxa make up the majority of the switchgrass root microbiota, a large fraction of which is shared across sites. Local genotypes preferentially recruit/filter for local microbes, supporting the idea of affinity between local plants and their microbiota. Using genome-wide association, we identified loci impacting the abundance of >400 microbial strains and found an enrichment of genes involved in immune responses, signaling pathways, and secondary metabolism. We found loci associated with over half of the core microbiota (i.e., microbes in >80% of samples), regardless of field location. Finally, we show a genetic relationship between a basal plant immunity pathway and relative abundances of root microbiota. Furthermore, this study brings us closer to harnessing and manipulating beneficial microbial associations via host genetics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Uncovering the dominant role of root metabolism in shaping rhizosphere metabolome under drought in tropical rainforest plants

Plant-soil-microbe interactions are crucial for driving rhizosphere processes that contribute to metabolite turnover and nutrient cycling. With the increasing frequency and severity of water scarcity due to climate warming, understanding how plant-mediated processes, such as root exudation, influence soil organic matter turnover in the rhizosphere is essential. In this study, we used 16S rRNA gene amplicon sequencing, rhizosphere metabolomics, and position-specific 13 C-pyruvate labeling to examine the effects of three different plant species (Piper auritum, Hibiscus rosa sinensis, and Clitoria fairchildiana) and their associated microbial communities on soil organic carbon turnover in the rhizosphere. Here, our findings indicate that in these tropical plants, the rhizosphere metabolome is primarily shaped by the response of roots to drought rather than direct shifts in the rhizosphere bacterial community composition. Specifically, the reduced exudation of plant roots had a notable effect on the metabolome of the rhizosphere of P. auritum, with less reliance on neighboring microbes. Contrary to P. auritum, H. rosa sinensis and C. fairchildiana experienced changes in their exudate composition during drought, causing alterations to the bacterial communities in the rhizosphere. This, in turn, had a collective impact on the rhizosphere's metabolome. Furthermore, the exclusion of phylogenetically distant microbes from the rhizosphere led to shifts in its metabolome. Additionally, C. fairchildiana appeared to be associated with only a subset of symbiotic bacteria under drought conditions. These results indicate that plant species-specific microbial interactions systematically change with the root metabolome. As roots respond to drought, their associated microbial communities adapt, potentially reinforcing the drought tolerance strategies of plant roots. These findings have significant implications for maintaining plant health and preference during drought stress and improving plant performance under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A biosorption-based approach for selective extraction of rare earth elements from coal byproducts

Coal byproducts could be a promising feedstock to alleviate the supply risk of critical rare earth elements (REEs) due to their abundance and REE content. Herein, we investigated the economic and environmental potential of producing REEs from coal fly ash and lignite through an integrated process of leaching, biosorption, and oxalic precipitation based on experimental data and modeling results. Two microbe immobilization systems (PEGDA) microbe beads and Si sol-gels) were examined for their efficiency in immobilizing Arthrobacter nicotianae to selectively recover REEs. Techno-economic analysis revealed that North Dakota lignite could be a profitable feedstock when Si sol-gel is used due to its high cell loading and REE adsorption capacity. Life cycle analysis revealed that Si sol-gel based biosorption could be more environmental friendly than the prevailing REE production in China due to use of less toxic chemicals. However, fly ash sourced from Powder River Basin coals was neither profitable or environmentally sustainable, primarily due to low solublity of high-value scandium at an economical pulp density (100 ash/L). To further improve the proposed biotechnology, future research could focus on scandium recovery, leaching efficiency, and microbe carriers.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

A Novel Membrane-Associated Protein Aids Bacterial Colonization of Maize

The soil environment affected by plant roots and their exudates, termed the rhizosphere, significantly impacts crop health and is an attractive target for engineering desirable agricultural traits. Engineering microbes in the rhizosphere is one approach to improving crop yields that directly minimizes the number of genetic modifications made to plants. Soil microbes have the potential to assist with nutrient acquisition, heat tolerance, and drought response if they can persist in the rhizosphere in the correct numbers. Unfortunately, the mechanisms by which microbes adhere and persist on plant roots are poorly understood, limiting their application. This study examined the membrane proteome shift upon adherence to roots in two bacteria of interest, Klebsiella variicola and Pseudomonas putida. From this surface proteome data, we identified a novel membrane protein from a non-laboratory isolate of P. putida that increases binding to maize roots using unlabeled proteomics. When this protein was moved from the environmental isolate to a common lab strain (P. putida KT2440), we observed increased binding capabilities of P. putida KT2440 to both abiotic mimic surfaces and maize roots. We observed a similar increased binding capability to maize roots when the protein was heterologously expressed in K. variicola and Stutzerimonas stutzeri. With the discovery of this novel binding protein, we outline a strategy for harnessing natural selection and wild isolates to build more persistent strains of bacteria for field applications and plant growth promotion.

rhizosphere, colonization, membrane proteome, plan↗
DOE OSTI2022

Global Patterns and Controls of Nutrient Immobilization on Decomposing Cellulose in Riverine Ecosystems

Microbes play a critical role in plant litter decomposition and influence the fate of carbon in rivers and riparian zones. When decomposing low-nutrient plant litter, microbes acquire nitrogen (N) and phosphorus (P) from the environment (i.e., nutrient immobilization), and this process is potentially sensitive to nutrient loading and changing climate. Nonetheless, environmental controls on immobilization are poorly understood because rates are also influenced by plant litter chemistry, which is coupled to the same environmental factors. Here we used a standardized, low-nutrient organic matter substrate (cotton strips) to quantify nutrient immobilization at 100 paired stream and riparian sites representing 11 biomes worldwide. Immobilization rates varied by three orders of magnitude, were greater in rivers than riparian zones, and were strongly correlated to decomposition rates. In rivers, P immobilization rates were controlled by surface water phosphate concentrations, but N immobilization rates were not related to inorganic N. The N:P of immobilized nutrients was tightly constrained to a molar ratio of 10:1 despite wide variation in surface water N:P. Immobilization rates were temperature-dependent in riparian zones but not related to temperature in rivers. However, in rivers nutrient supply ultimately controlled whether microbes could achieve the maximum expected decomposition rate at a given temperature. Collectively, we demonstrated that exogenous nutrient supply and immobilization are critical control points for decomposition of organic matter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn↗
DOE OSTI2025

Representing Soil Microbial Dynamics and Organo‐Mineral Interactions in the E3SM Land Model (ELM‐ReSOM)

Explicit representation of soil microbial processes and interactions with biotic and abiotic processes in Earth System Models (ESMs) remains limited, despite their importance in biogeochemical cycles. To address this gap, which hinders prediction of global biogeochemial cycling and responses to atmospheric conditions, we integrated a microbe- and mineral-surface-explicit model, the Reaction-network-based model of soil organic matter and Microbes (ReSOM), into the Energy Exascale ESM (E3SM) land model (ELM). Here, we describe ELM-ReSOM and show a case study at a conifer forest in California. ELM-ReSOM accurately simulated surface CO 2 fluxes and SOM stocks, demonstrating improved representations of microbial and mineral interactions compared to the default ELM. We examined ELM-ReSOM sensitivity to microbial traits, enzyme properties, and organo-mineral interactions. Microbial traits such as the maximum mortality rate, transporter-density scaling factor, and maximum monomer assimilation rate were strong controllers of heterotrophic respiration, while these microbial traits and enzyme-related properties collectively influenced SOM stocks. Mineral surfaces primarily affected SOM stocks by adsorbing enzymes, thereby limiting depolymerization. Synergies among processes led to stronger impacts of parameters when evaluated together versus separately (i.e., most parameters had greater indirect than direct effects). For example, due to interactions of microbial necromass with mineral surface adsorption, the indirect effect of the maximum microbial mortality rate was 33% larger than its direct effect on SOM stock. Thus, microbial and enzyme dynamics and their interactions with mineral surfaces play critical roles in SOM cycling. Tackling the challenges of microbe-explicit models will advance understanding and modeling of SOM dynamics.

Tao, Jing [Lawrence Berkeley National Laboratory (↗