Results for “Human Microbiome Project”

DOE OSTI2018

Qiita: rapid, web-enabled microbiome meta-analysis

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

microbiome, bioinformatics software, open source s↗

DOE OSTI2017

A microbial survey of the International Space Station (ISS)

Background: Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 surfaces sampled by swabs onboard the ISS. This sampling was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Learning more about the microbial inhabitants of the “buildings” in which we travel through space will take on increasing importance, as plans for human exploration continue, with the possibility of colonization of other planets and moons. Results: Sterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for (1) the Wildlife of Our Homes project and (2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rDNA genes amplified from DNA extracted from each swab was used to produce a census of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both homes on Earth and data from the Human Microbiome Project. Conclusions: While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are species-rich with 1,036–4,294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.

International space station↗

DOE OSTI2015

Using populations of human and microbial genomes for organism detection in metagenomes

Identifying causative disease agents in human patients from shotgun metagenomic sequencing (SMS) presents a powerful tool to apply when other targeted diagnostics fail. Numerous technical challenges remain, however, before SMS can move beyond the role of research tool. Accurately separating the known and unknown organism content remains difficult, particularly when SMS is applied as a last resort. The true amount of human DNA that remains in a sample after screening against the human reference genome and filtering nonbiological components left from library preparation has previously been underreported. In this study, we create the most comprehensive collection of microbial and reference-free human genetic variation available in a database optimized for efficient metagenomic search by extracting sequences from GenBank and the 1000 Genomes Project. The results reveal new human sequences found in individual Human Microbiome Project (HMP) samples. Individual samples contain up to 95% human sequence, and 4% of the individual HMP samples contain 10% or more human reads. In conclusion, left unidentified, human reads can complicate and slow down further analysis and lead to inaccurately labeled microbial taxa and ultimately lead to privacy concerns as more human genome data is collected.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Discovery and Characterization of FMN-Binding β-Glucuronidases in the Human Gut Microbiome

The human gut microbiota encodes β-glucuronidases (GUSs) that play key roles in health and disease via the metabolism of glucuronate-containing carbohydrates and drugs. Hundreds of putative bacterial GUS enzymes have been identified by metagenomic analysis of the human gut microbiome, but less than 10% have characterized structures and functions. Here in this paper we describe a set of unique gut microbial GUS enzymes that bind flavin mononucleotide (FMN). First, we show using mass spectrometry, isothermal titration calorimetry, and x-ray crystallography that a purified GUS from the gut commensal microbe Faecalibacterium prausnitzii binds to FMN on a surface groove located 30 Å away from the active site. Second, utilizing structural and functional data from this FMN-binding GUS, we analyzed the 279 unique GUS sequences from the Human Microbiome Project database and identified 14 putative FMN-binding GUSs. We characterized four of these hits and solved the structure of two, the GUSs from Ruminococcus gnavus and Roseburia hominis, which confirmed that these are FMN binders. Third, binding and kinetic analysis of the FMN-binding site mutants of these five GUSs show that they utilize a conserved site to bind FMN that is not essential for GUS activity, but can affect KM. Lastly, a comprehensive structural review of the PDB reveals that the FMN-binding site employed by these enzymes is unlike any structurally characterized FMN binders to date. These findings reveal the first instance of an FMN-binding glycoside hydrolase and suggest a potential link between FMN and carbohydrate metabolism in the human gut microbiota.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases

Inflammatory bowel diseases, which include Crohn’s disease and ulcerative colitis, affect several million individuals worldwide. Crohn’s disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Lastly, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study’s infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi’omics Database (http://ibdmdb.org), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

A Bayesian nonparametric analysis for zero-inflated multivariate count data with application to microbiome study

High-throughput sequencing technology has enabled researchers to profile microbial communities from a variety of environments, but analysis of multivariate taxon count data remains challenging. Here, we develop a Bayesian nonparametric (BNP) regression model with zero inflation to analyse multivariate count data from microbiome studies. A BNP approach flexibly models microbial associations with covariates, such as environmental factors and clinical characteristics. The model produces estimates for probability distributions which relate microbial diversity and differential abundance to covariates, and facilitates community comparisons beyond those provided by simple statistical tests. We compare the model to simpler models and popular alternatives in simulation studies, showing, in addition to these additional community-level insights, it yields superior parameter estimates and model fit in various settings. The model's utility is demonstrated by applying it to a chronic wound microbiome data set and a Human Microbiome Project data set, where it is used to compare microbial communities present in different environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

A unified initiative to harness Earth's microbiomes

Despite their centrality to life on Earth, we know little about how microbes interact with each other, their hosts, or their environment. Although DNA sequencing technologies have enabled a new view of the ubiquity and diversity of microorganisms, this has mainly yielded snapshots that shed limited light on microbial functions or community dynamics. Given that nearly every habitat and organism hosts a diverse constellation of microorganisms—its “microbiome”—such knowledge could transform our understanding of the world and launch innovations in agriculture, energy, health, the environment, and more (see the photo). Here, we propose an interdisciplinary Unified Microbiome Initiative (UMI) to discover and advance tools to understand and harness the capabilities of Earth's microbial ecosystems. The impacts of oceans and soil microbes on atmospheric CO 2 are critical for understanding climate change. By manipulating interactions at the root-soil-microbe interface, we may reduce agricultural pesticide, fertilizer, and water use enrich marginal land and rehabilitate degraded soils. Microbes can degrade plant cell walls (for biofuels), and synthesize myriad small molecules for new bioproducts, including antibiotics. Restoring normal human microbial ecosystems can save lives [e.g., fecal microbiome transplantation for Clostridium difficile infections]. Rational management of microbial communities in and around us has implications for asthma, diabetes, obesity, infectious diseases, psychiatric illnesses, and other afflictions. The human microbiome is a target and a source for new drugs and an essential tool for precision medicine. The National Science Foundation's Microbial Observatories, the U.S. Department of Energy's Genomic Sciences program, the National Institutes of Health's Human Microbiome Project, and other efforts in the United States and abroad have served as critical first steps in revealing the diversity of microbes and their communities. However, we lack many tools required to advance beyond descriptive approaches to studies that enable a mechanistic, predictive, and actionable understanding of global microbiome processes. Developing these tools requires new collaborations between physical, life, and biomedical sciences; engineering; and other disciplines.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2015

PanFP: Pangenome-based functional profiles for microbial communities

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interest for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.

16S rRNA survey↗

DOE OSTI2017

Tracking microbial colonization in fecal microbiota transplantation experiments via genome-resolved metagenomics

Fecal microbiota transplantation (FMT) is an effective treatment for recurrent Clostridium difficile infection and shows promise for treating other medical conditions associated with intestinal dysbioses. However, we lack a sufficient understanding of which microbial populations successfully colonize the recipient gut, and the widely used approaches to study the microbial ecology of FMT experiments fail to provide enough resolution to identify populations that are likely responsible for FMT-derived benefits. Here, we used shotgun metagenomics together with assembly and binning strategies to reconstruct metagenome-assembled genomes (MAGs) from fecal samples of a single FMT donor. We then used metagenomic mapping to track the occurrence and distribution patterns of donor MAGs in two FMT recipients. Our analyses revealed that 22% of the 92 highly complete bacterial MAGs that we identified from the donor successfully colonized and remained abundant in two recipients for at least 8 weeks. Most MAGs with a high colonization rate belonged to the order Bacteroidales. The vast majority of those that lacked evidence of colonization belonged to the order Clostridiales, and colonization success was negatively correlated with the number of genes related to sporulation. Our analysis of 151 publicly available gut metagenomes showed that the donor MAGs that colonized both recipients were prevalent, and the ones that colonized neither were rare across the participants of the Human Microbiome Project. Although our dataset showed a link between taxonomy and the colonization ability of a given MAG, we also identified MAGs that belong to the same taxon with different colonization properties, highlighting the importance of an appropriate level of resolution to explore the functional basis of colonization and to identify targets for cultivation, hypothesis generation, and testing in model systems. Lastly, the analytical strategy adopted in our study can provide genomic insights into bacterial populations that may be critical to the efficacy of FMT due to their success in gut colonization and metabolic properties, and guide cultivation efforts to investigate mechanistic underpinnings of this procedure beyond associations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

A most wanted list of conserved microbial protein families with no known domains

The number and proportion of genes with no known function are growing rapidly. To quantify this phenomenon and provide criteria for prioritizing genes for functional characterization, we developed a bioinformatics pipeline that identifies robustly defined protein families with no annotated domains, ranks these with respect to phylogenetic breadth, and identifies them in metagenomics data. We applied this approach to 271 965 protein families from the SFams database and discovered many with no functional annotation, including >118 000 families lacking any known protein domain. From these, we prioritized 6 668 conserved protein families with at least three sequences from organisms in at least two distinct classes. These Function Unknown Families (FUnkFams) are present in Tara Oceans Expedition and Human Microbiome Project metagenomes, with distributions associated with sampling environment. Our findings highlight the extent of functional novelty in sequence databases and establish an approach for creating a “most wanted” list of genes to prioritize for further characterization.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

American Gut: an Open Platform for Citizen Science Microbiome Research

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Exabiome: Advancing Microbial Science through Exascale Computing

The Exabiome project seeks to improve the understanding of microbiomes through the development of methods for accelerating metagenomic science using exascale computing. This article gives an overview of scientific impact of the three components of the project: metagenome assembly, protein family detection, and comparative analysis of metagenomes. Exabiome developed MetaHipMer, the only metagenome assembler capable of scaling to full exascale systems. MetaHipMer has enabled ground-breaking assemblies on the Frontier supercomputer, with many scientific benefits, such as the discovery of rare species and viral genomes. To investigate protein families, Exabiome developed two exascale tools, PASTIS and HipMCL. Together, these can utilize exascale resources to understand the functional diversity of billions of dark matter proteins and novel protein families. For comparative analysis, Exabiome developed kmerprof, a tool that can be used to compare huge metagenomes for many different scientific purposes, for example, grouping human microbiomes according to body location.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request

Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.

Peyton, Brent↗

DOE OSTI2023

Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request

Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.

Peyton, Brent↗

DOE OSTI2023

Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request

Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.

Peyton, Brent↗

DOE OSTI2023

Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request

Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.

Peyton, Brent↗

DOE OSTI2023

Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request

Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.

Peyton, Brent↗

DOE OSTI2023

Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request

Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.

Peyton, Brent↗