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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Phyllosphere exudates select for distinct microbiome members in sorghum epicuticular wax and aerial root mucilage

Phyllosphere exudates create specialized microhabitats that shape microbial community diversity. We explored the microbiome associated with two sorghum phyllosphere exudates, the epicuticular wax and aerial root mucilage. We assessed the microbiome associated with the wax from sorghum plants over two growth stages, and the root mucilage additionally from nitrogen-fertilized and non-fertilized plants. In parallel, we isolated and characterized hundreds of bacteria from wax and mucilage, and integrated data from cultivation-independent and cultivation-dependent approaches to gain insights into exudate diversity and bacterial phenotypes. We found that Sphingomonadaceae and Rhizobiaceae families were the major taxa in the wax regardless of water availability and plant developmental stage to plants. The cultivation-independent mucilage-associated bacterial microbiome contained Erwiniaceae, Flavobacteriaceae, Rhizobiaceae, Pseudomonadaceae, Sphingomonadaceae, and its structure was strongly influenced by sorghum development but only modestly influenced by fertilization. In contrast, the fungal community structure of mucilage was strongly affected by the year of sampling but not by fertilization or plant developmental stage, suggesting a decoupling of fungal-bacterial dynamics in the mucilage. Our bacterial isolate collection from wax and mucilage had several isolates that matched 100% to detected amplicon sequence variants, and were enriched on media that selected for phenotypes including phosphate solubilization, putative diazotrophy, resistance to desiccation, capability to grow on methanol as a carbon source, and ability to grow in the presence of linalool and β-caryophyllene (terpenes in sorghum wax). This work expands our understanding of the microbiome of phyllosphere exudates and supports our long-term goal to translate microbiome research to support sorghum cultivation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Metaphenomic Responses of a Native Prairie Soil Microbiome to Moisture Perturbations

Climate change is causing shifts in precipitation patterns in the central grasslands of the United States, with largely unknown consequences on the collective physiological responses of the soil microbial community, i.e., the metaphenome. Here, we used an untargeted omics approach to determine the soil microbial community’s metaphenomic response to soil moisture and to define specific metabolic signatures of the response. Specifically, we aimed to develop the technical approaches and metabolic mapping framework necessary for future systematic ecological studies. We collected soil from three locations at the Konza Long-Term Ecological Research (LTER) field station in Kansas, and the soils were incubated for 15 days under dry or wet conditions and compared to field-moist controls. The microbiome response to wetting or drying was determined by 16S rRNA amplicon sequencing, metatranscriptomics, and metabolomics, and the resulting shifts in taxa, gene expression, and metabolites were assessed. Soil drying resulted in significant shifts in both the composition and function of the soil microbiome. In contrast, there were few changes following wetting. The combined metabolic and metatranscriptomic data were used to generate reaction networks to determine the metaphenomic response to soil moisture transitions. Site location was a strong determinant of the response of the soil microbiome to moisture perturbations. However, some specific metabolic pathways changed consistently across sites, including an increase in pathways and metabolites for production of sugars and other osmolytes as a response to drying. Using this approach, we demonstrate that despite the high complexity of the soil habitat, it is possible to generate insight into the effect of environmental change on the soil microbiome and its physiology and functions, thus laying the groundwork for future, targeted studies. Climate change is predicted to result in increased drought extent and intensity in the highly productive, former tallgrass prairie region of the continental United States. These soils store large reserves of carbon. The decrease in soil moisture due to drought has largely unknown consequences on soil carbon cycling and other key biogeochemical cycles carried out by soil microbiomes. In this study, we found that soil drying had a significant impact on the structure and function of soil microbial communities, including shifts in expression of specific metabolic pathways, such as those leading toward production of osmoprotectant compounds. This study demonstrates the application of an untargeted multi-omics approach to decipher details of the soil microbial community’s metaphenotypic response to environmental perturbations and should be applicable to studies of other complex microbial systems as well.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Microbiome dynamics in the congregate environment of U.S. Army Infantry training

Within military training and operational environments, individuals from diverse backgrounds share common spaces, follow structured routines and diets, and engage in physically demanding tasks. While there has been interest in leveraging microbiome features to predict and improve military health and performance, the longitudinal convergence of microbiomes in such constrained environments has not been established. To assess the degree of microbiome convergence, we performed shotgun metagenomic sequencing on swab samples from a military trainee cohort. Samples were taken across four different body sites, three timepoints, and two spatially distinct platoons. We observed evidence of convergence in one platoon, whereby similarity in microbiome composition increased over time, with numerous differentially abundant species. We found no indication of strain transfer between individuals, suggesting that convergence was influenced by external environmental factors, diet, and lifestyle. Microbial shifts observed in the convergence process included a decrease in fungal species, such as Malassezia restricta in nasal cavities, and a decrease in Prevotella species at inguinal regions across time. Shifts in multiple Corynebacterium species were also observed with varying magnitudes depending on the body site. Overall, we provide preliminary evidence of convergence of host microbial communities in military-associated environments that were distinguishable using shotgun metagenomic sequencing approaches. The data presented here on microbiome convergence, dynamics, and stability may inform risk-based mitigation in congregate military settings facilitating development of targeted microbial, dietary, or other interventions to optimize health and performance of military populations.

Biological and medical sciences↗
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 OSTI2018

Microbiomes Associated With Foods From Plant and Animal Sources

Food microbiome composition impacts food safety and quality. The resident microbiota of many food products is influenced throughout the farm to fork continuum by farming practices, environmental factors, and food manufacturing and processing procedures. Currently, most food microbiology studies rely on culture-dependent methods to identify bacteria. However, advances in high-throughput DNA sequencing technologies have enabled the use of targeted 16S rRNA gene sequencing to profile complex microbial communities including non-culturable members. In this study we used 16S rRNA gene sequencing to assess the microbiome profiles of plant and animal derived foods collected at two points in the manufacturing process; post-harvest/pre-retail (cilantro) and retail (cilantro, masala spice mixes, cucumbers, mung bean sprouts, and smoked salmon). Our findings revealed microbiome profiles, unique to each food, that were influenced by the moisture content (dry spices, fresh produce), packaging methods, such as modified atmospheric packaging (mung bean sprouts and smoked salmon), and manufacturing stage (cilantro prior to retail and at retail). The masala spice mixes and cucumbers were comprised mainly of Proteobacteria, Firmicutes, and Actinobacteria. Cilantro microbiome profiles consisted mainly of Proteobacteria, followed by Bacteroidetes, and low levels of Firmicutes and Actinobacteria. The two brands of mung bean sprouts and the three smoked salmon samples differed from one another in their microbiome composition, each predominated by either by Firmicutes or Proteobacteria. These data demonstrate diverse and highly variable resident microbial communities across food products, which is informative in the context of food safety, and spoilage where indigenous bacteria could hamper pathogen detection, and limit shelf life.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗
DOE OSTI2022

Defining the Sphagnum Core Microbiome across the North American Continent Reveals a Central Role for Diazotrophic Methanotrophs in the Nitrogen and Carbon Cycles of Boreal Peatland Ecosystems

Peat mosses of the genus Sphagnum are ecosystem engineers that frequently predominate over photosynthetic production in boreal peatlands. Sphagnum spp. host diverse microbial communities capable of nitrogen fixation (diazotrophy) and methane oxidation (methanotrophy), thereby potentially supporting plant growth under severely nutrient-limited conditions. Moreover, diazotrophic methanotrophs represent a possible “missing link” between the carbon and nitrogen cycles, but the functional contributions of the Sphagnum-associated microbiome remain in question. A combination of metagenomics, metatranscriptomics, and dual-isotope incorporation assays was applied to investigate Sphagnum microbiome community composition across the North American continent and provide empirical evidence for diazotrophic methanotrophy in Sphagnum-dominated ecosystems. Remarkably consistent prokaryotic communities were detected in over 250 Sphagnum SSU rRNA libraries from peatlands across the United States (5 states, 17 bog/fen sites, 18 Sphagnum species), with 12 genera of the core microbiome comprising 60% of the relative microbial abundance. Additionally, nitrogenase (nifH) and SSU rRNA gene amplicon analysis revealed that nitrogen-fixing populations made up nearly 15% of the prokaryotic communities, predominated by Nostocales cyanobacteria and Rhizobiales methanotrophs. While cyanobacteria comprised the vast majority (>95%) of diazotrophs detected in amplicon and metagenome analyses, obligate methanotrophs of the genus Methyloferula (order Rhizobiales) accounted for one-quarter of transcribed nifH genes. Furthermore, in dual-isotope tracer experiments, members of the Rhizobiales showed substantial incorporation of 13 CH 4 and 15 N 2 isotopes into their rRNA. Our study characterizes the core Sphagnum microbiome across large spatial scales and indicates that diazotrophic methanotrophs, here defined as obligate methanotrophs of the rare biosphere (Methyloferula spp. of the Rhizobiales) that also carry out diazotrophy, play a keystone role in coupling of the carbon and nitrogen cycles in nutrient-poor peatlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A k-mer based approach for classifying viruses without taxonomy identifies viral associations in human autism and plant microbiomes

Viruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an essential role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus’ genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples, even if they do not have a taxonomy. To identify and quantify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses to create a database of metagenomic viruses. The resulting Kraken2 database of the metagenomic viruses can be found here: https://www.osti.gov/biblio/1615774 and is compatible with Kraken2. We then integrated the viral classification database with databases created with genomes from NCBI for use with ParaKraken (a parallelized version of Kraken provided in Supplemental Zip 1), a metagenomic/transcriptomic classifier. To illustrate the breadth of our utility for classifying metagenome viruses, we analyzed data from a plant metagenome study identifying genotypic and compartment specific differences between two Populus genotypes in three different compartments. We also identified a significant increase in abundance of eight viral sequences in post mortem brains in a human metatranscriptome study comparing Autism Spectrum Disorder patients and controls. We also show the potential accuracy for classifying viruses by utilizing both the JGI and NCBI viral databases to identify the uniqueness of viral sequences. Finally, we validate the accuracy of viral classification with NCBI databases containing viruses with taxonomy to identify pathogenic viruses in known COVID-19 and cassava brown streak virus infection samples. Our method represents the compulsory first step in better understanding the role of viruses in the microbiome by allowing for a more complete identification of sequences without taxonomy. Better classification of viruses will improve identifying associations between viruses and their hosts as well as viruses and other microbiome members. Despite the lack of taxonomy, this database of metagenomic viruses can be used with any tool that utilizes a taxonomy, such as Kraken, for accurate classification of viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Arsenic induces structural and compositional colonic microbiome change and promotes host nitrogen and amino acid metabolism

Chronic exposure to arsenic in drinking water causes cancer and non-cancer diseases. However, mechanisms for chronic arsenic-induced pathogenesis, especially in response to lower exposure levels, are unclear. In addition, the importance of health impacts from xeniobiotic-promoted microbiome changes is just being realized and effects of arsenic on the microbiome with relation to disease promotion are unknown. To investigate impact of arsenic exposure on both microbiome and host metabolism, the stucture and composition of colonic microbiota, their metabolic phenotype, and host tissue and plasma metabolite levels were compared in mice exposed for 2, 5, or 10 weeks to 0, 10 (low) or 250 (high) ppb arsenite (As(III)). Genotyping of colonic bacteria revealed time and arsenic concentration dependent shifts in community composition, particularly the Bacteroidetes and Firmicutes, relative to those seen in the time-matched controls. Arsenic-induced erosion of bacterial biofilms adjacent to the mucosal lining and changes in the diversity and abundance of morphologically distinct species indicated changes in microbial community structure. Bacterical spores increased in abundance and intracellular inclusions decreased with high dose arsenic. Interestingly, expression of arsenate reductase (arsA) and the As(III) exporter arsB, remained unchanged, while the dissimilatory nitrite reductase (nrfA) gene expression increased. In keeping with the change in nitrogen metabolism, colonic and liver nitrite and nitrate levels and ratios changed with time. In addition, there was a concomitant increase in pathogenic arginine metabolites in the mouse circulation. These data suggest that arsenic exposure impacts the microbiome and microbiome/host nitrogen metabolism to support disease enhancing pathogenic phenotypes. - Highlights: • Arsenic exposure induces changes in host and host nitrogen metabolism that cause progresive change in the microbiome. • A polyphasic approach reveals changes in microbial community structure, composition and nitrite reductase expression. • The profile of nitrogen and nitroamino acid change caused by arsenic may relect increased risk of cardiovascular pathogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Genistein prevention of hyperglycemia and improvement of glucose tolerance in adult non-obese diabetic mice are associated with alterations of gut microbiome and immune homeostasis

Although studies have linked soy phytoestrogen 4,7,4-trihydroxyisoflavone genistein (GEN) to reduced type 1 diabetes (T1D) risk, the mechanism of dietary GEN on T1D remains unknown. In our studies, adult non-obese diabetic (NOD) mouse model was employed to investigate the effects of GEN exposure on blood glucose level (BGL), glucose tolerance, gut microbiome, and immune responses. Adult male and female NOD mice were fed with either soy-based or casein-based diet, and received GEN at 20 mg/kg body weight by gavage daily. The BGL and immune responses (represented by serum antibodies, cytokines and chemokines, and histopathology) were monitored, while the fecal gut microbiome was sequenced for 16S ribosomal RNA to reveal any alterations in gut microbial communities. A significantly reduced BGL was found in NOD males fed with soy-based diet on day 98 after initial dosing, and an improved glucose tolerance was observed on both diets. In addition, an anti-inflammatory response (suggested by reduced IgG{sub 2b} and cytokine/chemokine levels, and alterations in the microbial taxonomy) was accompanied by an altered β-diversity in gut microbial species. Among the NOD females exposed to GEN, a later onset of T1D was observed. However, the profiles of gut microbiome, antibodies and cytokines/chemokines were all indicative of pro-inflammation. This study demonstrated an association among GEN exposure, gut microbiome alteration, and immune homeostasis in NOD males. Although the mechanisms underlying the protective effects of GEN in NOD mice need to be explored further, the current study suggested a GEN-induced sex-specific effect in inflammatory status and gut microbiome. - Highlights: • GEN reduces blood glucose level and improves glucose tolerance in NOD males. • GEN delayed type 1 diabetes onset in NOD females. • GEN produces a perturbed gut microbiota in both NOD males and females. • GEN produces anti-inflammatory responses in NOD males. • GEN produces pro-inflammatory responses in NOD females.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Distinctive microbiomes and metabolites linked with weight loss after gastric bypass, but not gastric banding

Roux-en-Y gastric bypass (RYGB) and laparoscopic adjustable gastric banding (LAGB) are anatomically different bariatric operations. RYGB achieves greater weight loss compared with LAGB. Changes in the gut microbiome have been documented after RYGB, but not LAGB, and the microbial contribution to sustainable surgical weight loss warrants further evaluation. We hypothesized that RYGB imposes greater changes on the microbiota and its metabolism than LAGB, and that the altered microbiota may contribute to greater weight loss. Using multi-omic approaches, we analyzed fecal microbial community structure and metabolites of pre-bariatric surgery morbidly obese (PreB-Ob), normal weight (NW), post-RYGB, and post-LAGB participants. RYGB microbiomes were significantly different from those from NW, LAGB and PreB-Ob. Microbiome differences between RYGB and PreB- Ob populations were mirrored in their metabolomes. Diversity was higher in RYGB compared with LAGB, possibly because of an increase in the abundance of facultative anaerobic, bile-tolerant and acid-sensible microorganisms in the former. Possibly because of lower gastric acid exposure, phylotypes from the oral cavity, such as Escherichia, Veillonella and Streptococcus, were in greater abundance in the RYGB group, and their abundances positively correlated with percent excess weight loss. Many of these post-RYGB microorganisms are capable of amino-acid fermentation. Amino-acid and carbohydrate fermentation products—isovalerate, isobutyrate, butyrate and propionate—were prevalent in RYGB participants, but not in LAGB participants. RYGB resulted in greater alteration of the gut microbiome and metabolome than LAGB, and RYGB group exhibited unique microbiome composed of many amino-acid fermenters, compared with nonsurgical controls.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Meconium microbiome associates with the development of neonatal jaundice

Objective: Neonatal jaundice is a common disease that affects up to 60% of newborns. Gut microbiota mediated the excretion of bilirubin from the human body. However, the relationship between early gut microbiome and development of neonatal jaundice is not fully understood. Here we sought to characterize meconium microbiome of newborns and to clarify its association with risk of neonatal jaundice. Methods: We conducted a nested case–control study with 301 newborns providing meconium samples from 2014 to 2015. The main outcome was the development of neonatal jaundice at 42 day follow-up. 16S rRNA gene sequencing was performed to profile the meconium microbiome. LEfSe was employed to identify different features between control and case groups. Logistic regression was used to estimate the risk effect of early gut microbiome on neonatal jaundice. Results: Logistic regression models suggested that higher α-diversity was significantly associated with lower risk of jaundice in cesarean infants (OR 0.72, 95% CI 0.52–0.98), but not in infants born naturally. Higher relative abundance of Bifidobacterium pseudolongum in newborn meconium was significantly associated with lower risk of jaundice both in cesarean-born infants and in the total subjects (OR 0.24, 95% CI 0.07–0.68; OR 0.55, 95% CI 0.31–0.95, respectively). Spearman’s correlations showed that relative abundance of B. pseudolongum was significantly correlated with α-diversity (P < 0.01). Conclusion: Preventive and treatment methods implying early gut microbiome intervention could be promising for the management of neonatal jaundice.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

STREAMS guidelines: standards for technical reporting in environmental and host-associated microbiome studies

The interdisciplinary nature of microbiome research, coupled with the generation of complex multi-omics data, makes knowledge sharing challenging. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines provide a checklist for the reporting of study information, experimental design and analytical methods within a scientific manuscript on human microbiome research. Here, in this Consensus Statement, we present the standards for technical reporting in environmental and host-associated microbiome studies (STREAMS) guidelines. The guidelines expand on STORMS and include 67 items to support the reporting and review of environmental (for example, terrestrial, aquatic, atmospheric and engineered), synthetic and non-human host-associated microbiome studies in a standardized and machine-actionable manner. Based on input from 248 researchers spanning 28 countries, we provide detailed guidance, including comparisons with STORMS, and case studies that demonstrate the usage of the STREAMS guidelines. In conclusion, STREAMS, like STORMS, will be a living community resource updated by the Consortium with consensus-building input of the broader community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Neotropical termite microbiomes as sources of novel plant cell wall degrading enzymes

In this study, we used shotgun metagenomic sequencing to characterise the microbial metabolic potential for lignocellulose transformation in the gut of two colonies of Argentine higher termite species with different feeding habits, Cortaritermes fulviceps and Nasutitermes aquilinus. Our goal was to assess the microbial community compositions and metabolic capacity, and to identify genes involved in lignocellulose degradation. Individuals from both termite species contained the same five dominant bacterial phyla (Spirochaetes, Firmicutes, Proteobacteria, Fibrobacteres and Bacteroidetes) although with different relative abundances. However, detected functional capacity varied, with C. fulviceps (a grass-wood-feeder) gut microbiome samples containing more genes related to amino acid metabolism, whereas N. aquilinus (a wood-feeder) gut microbiome samples were enriched in genes involved in carbohydrate metabolism and cellulose degradation. The C. fulviceps gut microbiome was enriched specifically in genes coding for debranching- and oligosaccharide-degrading enzymes. These findings suggest an association between the primary food source and the predicted categories of the enzymes present in the gut microbiomes of each species. To further investigate the termite microbiomes as sources of biotechnologically relevant glycosyl hydrolases, a putative GH10 endo-β-1,4-xylanase, Xyl10E, was cloned and expressed in Escherichia coli. Functional analysis of the recombinant metagenome-derived enzyme showed high specificity towards beechwood xylan (288.1 IU/mg), with the optimum activity at 50 °C and a pH-activity range from 5 to 10. These characteristics suggest that Xy110E may be a promising candidate for further development in lignocellulose deconstruction applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Climate induced microbiome alterations increase cadmium bioavailability in agricultural soils with pH below 7

Climate change and metals independently stress soil microbiomes, but their combined effects remain unresolved. Here we show that future climate affects soil cadmium through altered soil microbiome and nutrient cycles, with soil pH as critical factor. In soils with pH<7 and during summer temperatures, future climate increased porewater cadmium, shifting total and potentially active taxonomic microbiome structures. Microbial ammonium oxidation released protons liberating cadmium through cation exchange from mineral surfaces. When porewater cadmium levels became toxic to non-cadmium-tolerant bacteria, microbial activity, and nutrient cycling decreased, reducing carbon and nitrogen emissions. In contrast, pH>7 soil show no climate impacts on cadmium mobilization, though imprints on microbiome structure were apparent. Subsequent nutrient cycling increased under future climate, stimulating soil respiration and nitrous oxide release. These findings underscore complex interactions between climate change and soil contaminants affecting the soil microbiome and its activity and highlights potential impacts on crop production, groundwater quality, and climate feedback.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Microbiome assembly in thawing permafrost and its feedbacks to climate

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.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Metabolic multistability and hysteresis in a model aerobe-anaerobe microbiome community

Major changes in the microbiome are associated with health and disease. Some microbiome states persist despite seemingly unfavorable conditions, such as the proliferation of aerobe-anaerobe communities in oxygen-exposed environments in wound infections or small intestinal bacterial overgrowth. Mechanisms underlying transitions into and persistence of these states remain unclear. Using two microbial taxa relevant to the human microbiome, we combine genome-scale mathematical modeling, bioreactor experiments, transcriptomics, and dynamical systems theory to show that multistability and hysteresis (MSH) is a mechanism describing the shift from an aerobe-dominated state to a resilient, paradoxically persistent aerobe-anaerobe state. We examine the impact of changing oxygen and nutrient regimes and identify changes in metabolism and gene expression that lead to MSH and associated multi-stable states. In such systems, conceptual causation-correlation connections break and MSH must be used for analysis. Using MSH to analyze microbiome dynamics will improve our conceptual understanding of stability of microbiome states and transitions between states.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Illuminating gut microbiome signaling pathways that regulate host circadian rhythms

The gut microbiome affects host physiology by modulating nutrient acquisition and creating chemical signals that are received by host receptors. The molecular details of the orchestration of these microbial signaling processes remain largely unclear. We used a function-centric approach to interrogate the mechanistic links between gut microbiome metabolism and host circadian rhythms. We used rodent models, including germ-free mice, to determine how the gut microbiome influences host chronobiology by assaying metabolites in the gut and in circulation, and we used activity-based protein profiling to provide direct functional links to individual taxa. We specifically investigated how externally imposed behavioral schedules, such as feeding schedules, can desynchronize biological rhythms in metabolic organs (e.g., the gut, pancreas, and liver) from the central circadian rhythms regulated by the brain. We hypothesize that the gut microbiome creates chemical signals that can be entrained by feeding/fasting schedule to induce internal metabolic misalignment. Elaborating on the findings of this project will elucidate the chemical signals from the microbiome that modulate biological rhythms in the host’s metabolic organs.

59 BASIC BIOLOGICAL SCIENCES↗