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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Biogeographic classification of streams using fish community– and trait–environment relationships

Abstract Aim Present a hybrid biogeographic and environmentally constrained clustering approach to classify ~853,000 stream reaches in the eastern United States. Examine the frequency of stream typologies in the landscape relative to anthropogenic stressors to identify potential stream conservation needs. Location Eastern United States. Methods Fish communities at 956 least‐disturbed sampling reaches were characterized using taxonomic and functional composition of native species. Environmental variables summarized within stream reaches included stream discharge, channel gradient, hydrologic regime, summer water temperature and boundaries of freshwater ecoregions. Multivariate regression trees were used to relate environmental variables to fish communities while simultaneously developing taxa‐ and trait‐specific biogeographic classifications. We then overlaid stream classifications with indices of anthropogenic disturbances to evaluate rarity and risk of complete loss of natural representation of stream types. Results Taxonomically based classes represented a combination of ecoregional boundaries and environmental gradients, whereas temperature gradients were most important in differentiating functional composition. An optimal taxonomy‐based classification contained 13 classes and explained 26.4% of community variation, and the optimal trait‐based classification contained 6 classes, explaining 25.2% of community variation. Overlaying class maps with an anthropogenic disturbance index revealed substantial variation in the severity of degradation among classes relative to their abundance in the landscape, especially rare classes (i.e., large rivers and cold headwater systems). Main conclusions We demonstrate the value of integrating local, regional and historical biogeographic factors with taxonomic and functional characteristics of freshwater biota to classify ecosystems based on mechanistic biota–environment relationships. This approach is important to addressing the challenge of developing stream classifications that reconcile the environmental drivers of community trait composition with the constraints of biogeographic regionality at large spatial scales. Furthermore, the spatially explicit and high‐resolution maps disseminated here can uniquely inform management decisions regarding anthropogenic threats to the biodiverse freshwaters of the eastern United States.

Troia, Matthew J.↗
DOE OSTI2023

Accounting for herbaceous communities in process‐based models will advance our understanding of “grassy” ecosystems

Abstract Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process‐based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Sustained Ability of a Natural Microbial Community to Remove Nitrate from Groundwater

Abstract Microbial‐mediated nitrate removal from groundwater is widely recognized as the predominant mechanism for nitrate attenuation in contaminated aquifers and is largely dependent on the presence of a carbon‐bearing electron donor. The repeated exposure of a natural microbial community to an electron donor can result in the sustained ability of the community to remove nitrate; this phenomenon has been clearly demonstrated at the laboratory scale. However, in situ demonstrations of this ability are lacking. For this study, ethanol (electron donor) was repeatedly injected into a groundwater well (treatment) for six consecutive weeks to establish the sustained ability of a microbial community to remove nitrate. A second well (control) located upgradient was not injected with ethanol during this time. The treatment well demonstrated strong evidence of sustained ability as evident by ethanol, nitrate, and subsequent sulfate removal up to 21, 64, and 68%, respectively, as compared to the conservative tracer (bromide) upon consecutive exposures. Both wells were then monitored for six additional weeks under natural (no injection) conditions. During the final week, ethanol was injected into both treatment and control wells. The treatment well demonstrated sustained ability as evident by ethanol and nitrate removal up to 20 and 21%, respectively, as compared to bromide, whereas the control did not show strong evidence of nitrate removal (5% removal). Surprisingly, the treatment well did not indicate a sustained and selective enrichment of a microbial community. These results suggested that the predominant mechanism(s) of sustained ability likely exist at the enzymatic‐ and/or genetic‐levels. The results of this study demonstrated the in situ ability of a microbial community to remove nitrate can be sustained in the prolonged absence of an electron donor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Improving collaborations between empiricists and modelers to advance grassland community dynamics in ecosystem models

Climate change, increasing atmospheric CO 2 , and land use change have altered biogeochemical and hydrologic cycles world-wide, with grassland systems being particularly vulnerable to resulting vegetation shifts (Komatsu et al., 2019). Therefore, incorporating plant community dynamics into ecosystem models is critical for accurate forecasting of ecosystem responses to global change (Levine, 2016). Process-based ecosystem models, which simulate the biogeochemical transfers of mass and energy among biota, the subsurface, and atmosphere, require representation of dynamic composition of organisms within ecosystems. For example, these models simulate leaf and plant-level characteristics, such as electron transport rate and allometry of carbon (C) allocation, to predict how net primary productivity and other ecosystem processes respond to abiotic drivers. These models are particularly useful in scaling from organismal to ecosystem levels but are still underdeveloped in their ability to capture community change, especially in grassland ecosystems. To represent compositional changes, these models must simulate competition, mortality, establishment, and reproduction of plant populations within communities. Yet, current ecosystem modeling approaches to forecast plant community change have derived from studies of forested systems and are either too coarse to capture fine-scale community dynamics (e.g. dynamic global vegetation models (DGVMs)) or too complex to be used at large spatial scales (e.g. forest gap models).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Warming drives a ‘hummockification’ of microbial communities associated with decomposing mycorrhizal fungal necromass in peatlands

Dead fungal mycelium (necromass) represents a critical component of soil carbon (C) and nutrient cycles. Assessing how the microbial communities associated with decomposing fungal necromass change as global temperatures rise will help in determining how these belowground organic matter inputs contribute to ecosystem responses. Here, in this study, we characterized the structure of bacterial and fungal communities associated with multiple types of decaying mycorrhizal fungal necromass incubated within mesh bags across a 9°C whole ecosystem temperature enhancement in a boreal peatland. We found major taxonomic and functional shifts in the microbial communities present on decaying mycorrhizal fungal necromass in response to warming. These changes were most pronounced in hollow microsites, which showed convergence towards the necromass-associated microbial communities present in unwarmed hummocks. We also observed a high colonization of ericoid mycorrhizal fungal necromass by fungi from the same genera as the necromass. These results indicate that microbial communities associated with mycorrhizal fungal necromass decomposition are likely to change significantly with future climate warming, which may have strong impacts on soil biogeochemical cycles in peatlands. Additionally, the high enrichment of congeneric fungal decomposers on ericoid mycorrhizal necromass may help to explain the increase in ericoid shrub dominance in warming peatlands.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Microbial community assembly and metabolic function during mammalian corpse decomposition

Vertebrate corpse decomposition provides an important stage in nutrient cycling in most terrestrial habitats, yet microbially mediated processes are poorly understood. Here we combine deep microbial community characterization, community-level metabolic reconstruction, and soil biogeochemical assessment to understand the principles governing microbial community assembly during decomposition of mouse and human corpses on different soil substrates. We find a suite of bacterial and fungal groups that contribute to nitrogen cycling and a reproducible network of decomposers that emerge on predictable time scales. Our results show that this decomposer community is derived primarily from bulk soil, but key decomposers are ubiquitous in low abundance. Soil type was not a dominant factor driving community development, and the process of decomposition is sufficiently reproducible to offer new opportunities for forensic investigations.

Metcalf, J. L.↗
DOE OSTI2024

Measurements of soil protist richness and community composition are influenced by primer pair, annealing temperature, and bioinformatics choices

ABSTRACT Protists are a diverse and understudied group of microbial eukaryotic organisms especially in terrestrial environments. Advances in molecular methods are increasing our understanding of the distribution and functions of these creatures; however, there is a vast array of choices researchers make including barcoding genes, primer pairs, PCR settings, and bioinformatic options that can impact the outcome of protist community surveys. Here, we tested four commonly used primer pairs targeting the V4 and V9 regions of the 18S rRNA gene using different PCR annealing temperatures and processed the sequences with different bioinformatic parameters in 10 diverse soils to evaluate how primer pair, amplification parameters, and bioinformatic choices influence the composition and richness of protist and non-protist taxa using Illumina sequencing. Our results showed that annealing temperature influenced sequencing depth and protist taxon richness for most primer pairs, and that merging forward and reverse sequencing reads for the V4 primer pairs dramatically reduced the number of sequences and taxon richness of protists. The data sets of primers that targeted the same 18S rRNA gene region (e.g., V4 or V9) had similar protist community compositions; however, data sets from primers targeting the V4 18S rRNA gene region detected a greater number of protist taxa compared to those prepared with primers targeting the V9 18S rRNA region. There was limited overlap of protist taxa between data sets targeting the two different gene regions (80/549 taxa). Together, we show that laboratory and bioinformatic choices can substantially affect the results and conclusions about protist diversity and community composition using metabarcoding. IMPORTANCE Ecosystem functioning is driven by the activity and interactions of the microbial community, in both aquatic and terrestrial environments. Protists are a group of highly diverse, mostly unicellular microbes whose identity and roles in terrestrial ecosystem ecology have been largely ignored until recently. This study highlights the importance of choices researchers make, such as primer pair, on the results and conclusions about protist diversity and community composition in soils. In order to better understand the roles protist taxa play in terrestrial ecosystems, biases in methodological and analytical choices should be understood and acknowledged.

Biotechnology & Applied Microbiology↗
DOE OSTI2025

Microbial ecology of acidic, biogenic gypsum: community structure and distribution of extremophiles on freshly formed and relict sulfate deposits in a hydrogen sulfide-rich cave

Sulfate minerals are abundant on the Martian surface, and many of these evaporite deposits are thought to have precipitated from acidic fluids. On Earth, gypsum (CaSO 4 •2H 2 O) and other sulfates sometimes form under acidic conditions, so exploring the extremophilic life that occurs in these mineral environments can help evaluate the astrobiological potential of acid sulfate depositional settings. Here, we characterized the microbial communities associated with acidic gypsum deposits in a sulfuric acid cave, where sulfate precipitation is driven by sulfide-oxidizing bacteria and archaea. We used 16S rRNA gene sequencing and cell counts to characterize gypsum-associated microorganisms in freshly formed and relict deposits throughout the cave, to test how microbial community composition and abundance would vary with distance from the sulfidic water table and with the concentration of H 2 S(g) and other gases in the cave atmosphere. We found that actively forming gypsum in the lower cave levels was colonized by low-diversity communities that have few cells compared to other environments in the cave. The most abundant taxa were Acidithiobacillus, Metallibacterium, Mycobacteria, and three different Thermoplasmatales-group archaea, which occupied distinct niches based on proximity to sulfidic streams and the concentration of gases in the cave air. By contrast, deposits in older cave levels had more diverse communities that were distinct from those associated with freshly formed gypsum and likely represent a community reliant on different energy resources. These findings show that acidic sulfate deposits serve as habitats for extremophilic microorganisms and broaden our knowledge of the life associated with terrestrial sulfates.

58 GEOSCIENCES↗
DOE OSTI2012

Heterotrophic Archaea Contribute to Carbon Cycling in Low-pH, Suboxic Biofilm Communities

Archaea are widely distributed and yet are most often not the most abundant members of microbial communities. Here, we document a transition from Bacteria- to Archaea-dominated communities in microbial biofilms sampled from the Richmond Mine acid mine drainage (AMD) system (pH 1.0,38 C) and in laboratory-cultivated biofilms. This transition occurs when chemoautotrophic microbial communities that develop at the air-solution interface sink to the sediment-solution interface and degrade under microaerobic and anaerobic conditions. The archaea identified in these sunken biofilms are from the class Thermoplasmata, and in some cases, the highly divergent ARMAN nanoarchaeal lineage. In several of the sunken biofilms, nanoarchaea comprise 10 to 25% of the community, based on fluorescent in situ hybridization and metagenomic analyses. Comparative community proteomic analyses show a persistence of bacterial proteins in sunken biofilms, but there is clear evidence for amino acid modifications due to acid hydrolysis. Given the low representation of bacterial cells in sunken biofilms based on microscopy, we infer that hydrolysis reflects proteins derived from lysed cells. For archaea, we detected 2,400 distinct proteins, including a subset involved in proteolysis and peptide uptake. Laboratory cultivation experiments using complex carbon substrates demonstrated anaerobic enrichment of Ferroplasma and Aplasma coupled to the reduction of ferric iron. These findings indicate dominance of acidophilic archaea in degrading biofilms and suggest that they play roles in anaerobic nutrient cycling at low pH.

Justice, Nicholas B↗
DOE OSTI2015

Natural bacterial communities serve as quantitative geochemical biosensors

Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive. Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Designing Metabolic Division of Labor in Microbial Communities

ABSTRACT Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Ectomycorrhizal fungi alter soil food webs and the functional potential of bacterial communities

Most of Earth’s trees rely on critical soil nutrients that ectomycorrhizal fungi (EcMF) liberate and provide, and all of Earth’s land plants associate with bacteria that help them survive in nature. Yet, our understanding of how the presence of EcMF modifies soil bacterial communities, soil food webs, and root chemistry requires direct experimental evidence to comprehend the effects that EcMF may generate in the belowground plant microbiome. To this end, we grew Pinus muricata plants in soils that were either inoculated with EcMF and native forest bacterial communities or only native bacterial communities. We then profiled the soil bacterial communities, applied metabolomics and lipidomics, and linked omics data sets to understand how the presence of EcMF modifies belowground biogeochemistry, bacterial community structure, and their functional potential. We found that the presence of EcMF (i) enriches soil bacteria linked to enhanced plant growth in nature, (ii) alters the quantity and composition of lipid and non-lipid soil metabolites, and (iii) modifies plant root chemistry toward pathogen suppression, enzymatic conservation, and reactive oxygen species scavenging. Using this multi-omic approach, we therefore show that this widespread fungal symbiosis may be a common factor for structuring soil food webs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Multidecadal shifts in forest plant diversity and community composition across glacial landforms in northern lower Michigan, USA

Understanding how plant community assemblage is affected by spatial and temporal patterns is crucial to understanding forest ecosystem responses to disturbance, including future climate change. In this article, we tracked how diversity and composition are distributed through space and time in a midsuccessional mixed hardwood forest in northern lower Michigan, United States. This region’s geographically and abiotically distinct glacial landforms influence both the spatial and temporal dynamics of its forest communities. Vegetation sampling plots (n = 87) were established at the University of Michigan Biological Station in 1990 and resampled in 2015. Vegetation in the overstory, sapling, and groundcover layers was censused. Abiotic variables, including elevation, pH, and soil nutrients, were measured in a subset of plots (n = 40). There were strong differences in diversity and community composition among glacial landforms, with the moraine having a 31% greater species richness in the groundcover layer compared with those of the other glacial landforms. Surprisingly, plant communities across all three vegetation layers showed little change over the 25-year period, and we found no evidence of differences in successional rates among glacial landforms. Our findings indicate that glacial landforms have a large influence on the production and maintenance of local plant diversity and community composition in this area and suggest that successional dynamics may manifest themselves over much longer time periods in these northern biomes.

Forestry↗
DOE OSTI2014

Circumstances and outcomes of falls among high risk community-dwelling older adults

For older adults, falls threaten their health, independence, and quality of life. Knowing the circumstances surrounding falls is essential for understanding how behavioral and environmental factors interact in fall events. It is also important for developing and implementing interventions that are effective and acceptable to older adults. This study investigated the circumstances and injury outcomes of falls among community-dwelling older adults at high risk for falls. In this secondary analysis, we examined the circumstances and outcomes of falls experienced by 328 participants in the Dane County (Wisconsin) Safety Assessment for Elders (SAFE) Research Study. SAFE was a randomized controlled trial of a community-based multifactorial falls intervention for older adults at high risk for falls, conducted from October 2002 to December 2007. Participants were community-dwelling adults aged ≥65 years who reported at least one fall during the year after study enrollment. Falls were collected prospectively using monthly calendars. Everyone who reported a fall was contacted by telephone to determine the circumstances surrounding the event. Injury outcomes were defined as none, mild (injury reported but no treatment sought), moderate (treatment for any injury except head injury or fracture), and severe (treatment for head injury or fracture). Data were available for 1,172 falls. A generalized linear mixed model analysis showed that being aged ≥85 (OR = 2.1, 95% confidence interval [CI] = 1.2–3.9), female (OR = 2.1, 95% CI = 1.3–3.4), falling backward and landing flat (OR = 5.6, 95% CI = 2.9–10.5), sideways (OR = 4.6, 95% CI = 2.6–8.0) and forward (OR = 3.3, 95% CI = 2.0–5.7) were significantly associated with the likelihood of injury. Of 783 falls inside the home, falls in the bathroom were more than twice as likely to result in an injury compared to falls in the living room (OR = 2.4, 95% CI = 1.2–4.9). Most falls among these high risk older adults occurred inside the home. The likelihood of injury in the bathroom supports the need for safety modifications such as grab bars, and may indicate a need for assistance with bathing. These findings will help clinicians tailor fall prevention for their patients and have practical implications for retirement and assisted living communities and community-based fall prevention programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Warming-induced permafrost thaw exacerbates tundra soil carbon decomposition mediated by microbial community

BACKGROUND:It is well-known that global warming has effects on high-latitude tundra underlain with permafrost. This leads to a severe concern that decomposition of soil organic carbon (SOC) previously stored in this region, which accounts for about 50% of the world's SOC storage, will cause positive feedback that accelerates climate warming. We have previously shown that short-term warming (1.5 years) stimulates rapid, microbe-mediated decomposition of tundra soil carbon without affecting the composition of the soil microbial community (based on the depth of 42684 sequence reads of 16S rRNA gene amplicons per 3 g of soil sample). RESULTS:We show that longer-term (5 years) experimental winter warming at the same site altered microbial communities (p < 0.040). Thaw depth correlated the strongest with community assembly and interaction networks, implying that warming-accelerated tundra thaw fundamentally restructured the microbial communities. Both carbon decomposition and methanogenesis genes increased in relative abundance under warming, and their functional structures strongly correlated (R 2 > 0.725, p < 0.001) with ecosystem respiration or CH4 flux. CONCLUSIONS:Our results demonstrate that microbial responses associated with carbon cycling could lead to positive feedbacks that accelerate SOC decomposition in tundra regions, which is alarming because SOC loss is unlikely to subside owing to changes in microbial community composition. Video Abstract.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Adaptive Evolution of Synthetic Cooperating Communities Improves Growth Performance

Symbiotic interactions between organisms are important for human health and biotechnological applications. Microbial mutualism is a widespread phenomenon and is important in maintaining natural microbial communities. Although cooperative interactions are prevalent in nature, little is known about the processes that allow their initial establishment, govern population dynamics and affect evolutionary processes. To investigate cooperative interactions between bacteria, we constructed, characterized, and adaptively evolved a synthetic community comprised of leucine and lysine Escherichia coli auxotrophs. The co-culture can grow in glucose minimal medium only if the two auxotrophs exchange essential metabolites — lysine and leucine (or its precursors). Our experiments showed that a viable co-culture using these two auxotrophs could be established and adaptively evolved to increase growth rates (by ~3 fold) and optical densities. While independently evolved co-cultures achieved similar improvements in growth, they took different evolutionary trajectories leading to different community compositions. Experiments with individual isolates from these evolved co-cultures showed that changes in both the leucine and lysine auxotrophs improved growth of the co-culture. Interestingly, while evolved isolates increased growth of co-cultures, they exhibited decreased growth in mono-culture (in the presence of leucine or lysine). A genome-scale metabolic model of the co-culture was also constructed and used to investigate the effects of amino acid (leucine or lysine) release and uptake rates on growth and composition of the co-culture. When the metabolic model was constrained by the estimated leucine and lysine release rates, the model predictions agreed well with experimental growth rates and composition measurements. While this study and others have focused on cooperative interactions amongst community members, the adaptive evolution of communities with other types of interactions (e.g., commensalism, ammensalism or parasitism) would also be of interest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Vertical Structure of Phyllosphere Fungal Communities in a Tropical Forest in Thailand Uncovered by High-Throughput Sequencing

Phyllosphere fungi harbor a tremendous species diversity and play important ecological roles. However, little is known about their distribution patterns within forest ecosystems. We examined how species diversity and community composition of phyllosphere fungi change along a vertical structure in a tropical forest in Thailand. Fungal communities in 144 leaf samples from 19 vertical layers (1.28–34.4 m above ground) of 73 plant individuals (27 species) were investigated by metabarcoding analysis using Ion Torrent sequencing. In total, 1,524 fungal operational taxonomic units (OTUs) were detected among 890,710 reads obtained from the 144 leaf samples. Taxonomically diverse fungi belonging to as many as 24 orders of Ascomycota and 21 orders of Basidiomycota were detected, most of which inhabited limited parts of the lowest layers closest to the forest floor. Species diversity of phyllosphere fungi was the highest in the lowest layers closest to the forest floor, decreased with increasing height, and lowest in the canopy; 742 and 55 fungal OTUs were detected at the lowest and highest layer, respectively. On the layers close to the forest floor, phyllosphere fungal communities were mainly composed of low frequency OTUs and largely differentiated among plant individuals. Conversely, in the canopy, fungal communities consisted of similar OTUs across plant individuals, and as many as 86.1%–92.7% of the OTUs found in the canopy (≥22 m above ground) were also distributed in the lower layers. Overall, our study showed the variability of phyllosphere fungal communities along the vertical gradient of plant vegetation and environmental conditions, suggesting the significance of biotic and abiotic variation for the species diversity of phyllosphere fungi.

59 BASIC BIOLOGICAL SCIENCES↗