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In this study, we aimed to evaluate Biological Nutrient Removal (BNR) and investigate microbial community changes when the DO is reduced in the aerated portions of wastewater treatment trains. We present a dataset of metagenomes obtained from activated sludge collected from the Los Angeles Sanitary District BNR pilot plant at the beginning of operation, when the DO was high, and at the end of operation, when the DO was low.
The primary objective of the EGS Collab Project sponsored by DOE is to increase the understanding needed to efficiently implement enhanced geothermal systems (EGS). One goal of the EGS Collab project is to create a collaborative research environment in which to study stimulation of crystalline rock at the 10 meter scale. Key to this effort is the collection of high quality data to allow comparison to numerical coupled process models in an effort to build confidence in the codes and modeling techniques used. In response to this, the EGS Collab team has created an underground test bed at the Sanford Underground Research Facility (SURF) in Lead SD at a depth of approximately 1.5 km to examine hydraulic fracturing (Experiment 1). We are currently designing a second test bed aimed at investigating shear stimulation (Experiment 2). At the Experiment 1 location, we have characterized our host rock using laboratory testing and numerous field-based geophysical and geological techniques, and created a well-instrumented test bed to allow us to carefully monitor stimulation events and flow tests. In addition to the installed geophysical sensors, we have used tracer tests, differences in the ambient microbial communities at flow collection locations, and cold water injection to inform us about dynamic flow pathways. In Experiment 1, we have hydraulically stimulated the host rock in a number times at several locations in one well, creating new fractures that connect to existing fractures between the injection and production boreholes. We have performed long-term ambient and chilled water injection tests as an analog to EGS, and have monitored system changes resulting from these water injections through geophysical monitoring, flow and pressure measurements, tracer tests, and microbiology. Here, we summarize the tests performed, issues identified including poroelastic and thermoelastic effects, Joule-Thomson effects, restarting effects, indications of flow channeling, and the primary learnings from Experiment 1.
Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.
A standard method in unconventional oil and gas production is the process of hydraulic fracturing followed by a shut-in period, during which the fracture fluid remains pressurized in the reservoir for up to three weeks before production begins. Despite this widely used process, very little is known about what occurs in the reservoir during this shut-in process. In order to properly delineate potential reservoir reactions that may occur during shut-in that would lead to corrosion and scaling events, experiments were conducted in high pressure, high temperature reactors to simulate conditions of the Wolfcamp Formation in the Delaware Basin. Experimental design allowed the assessment of the effect of proppant, microbiology, and time on the mineralogy and fluid chemistry in the reservoir. Results suggest the biggest impact on fluid chemistry and shale mineralogy during shut-in is time. Analyses demonstrate dissolution of the shale material, with maximum dissolved ions occurring after 7 days of the shut-in period. After 21 days, results suggest precipitation occurs. The Delaware Basin is demonstrated to be high in sulfate content, which further increases in the fluid due to dissolution reactions during shut-in. The pressure vessel experiments suggest there was no significant contribution to reactions from microbiology during the shut-in period. However, early production samples demonstrate a significant selection of the microorganism Caminicella, a genus of which has previously been correlated to corrosion and sulfide production. Results suggest shut-in conditions may provide high sulfate concentrations that could later be utilized by a shifted microbial community to drive potential well infrastructure failure. This is the first study to incorporate microbiology, mineralogy, and fluid chemistry to investigate the fundamental geochemical reactions that occur during shut-in and early phase production of the Delaware Basin. Results from this study can complement observations from the Hydraulic Fracture Test Site 2 observations.
The Annual Site Environmental Report (ASER) from a U.S. Department of Energy (DOE) Site summarizes environmental data; environmental management performance; compliance with applicable DOE, federal, state, and local regulations; and restoration and surveillance monitoring programs. The Savannah River Site (SRS) produces ASERs that include results of monitoring mercury levels in fish samples obtained in the vicinity of SRS. Mercury is a toxic trace metal and the methylated organic form is a neurotoxin that bioaccumulates in the food web, endangering humans and other organisms. In United States, power plants are the largest source of mercury emissions. Research Objective: To determine the patterns of mercury levels in fish samples reported in the SRS environmental monitoring reports. We developed box plot visualizations to make sense of the data as well as identify fish species, dates and location with outlier mercury content. The integration and visual representation of multi-year datasets can support decision making processes on environmental compliance and environmental sustainability conducted at U.S. DOE Sites. We are constructing datasets from textual, image and multivariable data sources in the multi-year ASERs of the U.S. DOE Savannah River Site (SRS https://www.srs.gov/general/pubs/ERsum/index.html). The Fish Surveillance for mercury presents a case study for the intersection of food, energy and water systems. The dataset of 864 records (2008 and 2009) of mercury levels includes water location of fish, fish species, collection date and mercury content of fish sample. The patterns of mercury levels in the fish species as well as locations provide knowledge for further investigations. A research area for future studies is the composition of microbial communities in fish guts of varying levels of mercury.
The first “Changing Microbiomes” conference was successfully held at the Pennsylvania State University from May 31st – June 3rd, 2022. The overall goal of the symposium was to provide space for researchers to connect, exchange knowledge, and partner to advance our understanding of the mechanisms and applications of ecological and evolutionary changes in microbiomes across systems. The symposium spanned terrestrial and aquatic contexts and host-associated and free-living microbial communities. As such, the symposium will enable cross-disciplinary knowledge and idea exchange to promote future interdisciplinary collaborations. In addition, the program allowed formal and informal interactions between and among students, postdocs, PIs, and industry scientists.
The U.S. Department of Energy (DOE) has implemented bioremediation strategies for chlorinated volatile organic compounds (cVOCs) for more than three decades across multiple contaminated groundwater sites. A retrospective analysis conducted by the Savannah River National Laboratory (SRNL) and collaborating field sites evaluated the design, performance, and outcomes of bioremediation projects at DOE’s Savannah River, Hanford, Idaho, Mound, and Pinellas sites. This retrospective was based on a series of case studies, leveraging historical documentation and site interviews. Technical approaches employed at the various sites were explored, including active bioremediation, enhanced attenuation (EA), and monitored natural attenuation, with specific sub-sections discussing anaerobic, aerobic, and combined anaerobic-aerobic strategies. Each case study includes detailed descriptions of the site-specific conditions, deployment strategies, regulatory considerations, metrics, and performance. Key findings include general cost savings compared to traditional remedies such as pump and treat (P&T), significant success in applying enhanced attenuation to transition remedies toward a passive site management strategy, and documentation of robust subsurface microbial communities at most sites limiting the need for bioaugmentation. Challenges highlighted in the study include underperformance due to poor amendment delivery in low-permeability zones and unfavorable biogeochemical conditions, emphasizing the importance of site-specific designs. Cost analysis across DOE sites suggests bioremediation may offer long-term economic benefits. The retrospective study underscores valuable lessons that can help inform current and future bioremediation efforts.
Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.
Studying plant-microbe-soil interactions is challenging due to their high complexity and variability in natural ecosystems. While fabricated ecosystems provide opportunities to recapitulate aspects of these systems in reduced complexity and controlled environments, inoculation can be a significant source of variation. To tackle this, we evaluated how different bacteria inoculation practices and plant harvesting time points affect the reproducibility of a microbial synthetic community (SynCom) in association with the model grass Brachypodium distachyon. We tested three microbial inoculation practices: seed inoculation, transplant inoculation, and seedling inoculation; and two harvesting points: early (14-day-old plants) and late (21 days post-inoculation). We grew our plants and bacterial strains in sterile devices (EcoFABs) and characterized the microbial community from root, rhizosphere, and sand using 16S ribosomal RNA gene sequencing. The results showed that inoculation practices significantly affected the rhizosphere microbial community only when harvesting at an early time point but not at the late stage. As the SynCom showed a persistent association with B. distachyon at 21 days post-inoculation regardless of inoculation practices, we assessed the reproducibility of each inoculation method and found that transplant inoculation showed the highest reproducibility. Moreover, plant biomass was not adversely affected by transplant inoculation treatment. We concluded that bacteria inoculation while transplanting coupled with a later harvesting time point gives the most reproducible microbial community in the EcoFAB-B. distachyon-SynCom fabricated ecosystem and recommend this method as a standardized protocol for use with fabricated ecosystem experimental systems.
Microbial electrolysis is a promising technology for converting aqueous wastes into hydrogen. However, substrate adaptability is an important feature, seldom documented in microbial electrolysis cells (MECs). In addition, the correlation between substrate composition and community structure has not been well established. This study used an MEC capable of producing over 10 L/L-day of hydrogen from a switchgrass-derived bio-oil aqueous phase and investigated four additional substrates, tested in sequence on a mature biofilm. The additional substrates included a red oak-derived bio-oil aqueous phase, a corn stover fermentation product, a mixture of phenol and acetate, and acetate alone. The MECs fed with the corn stover fermentation product resulted in the highest performance among the complex feedstocks, producing an average current density of 7.3 ± 0.51 A/m 2 , although the acetate fed MECs outperformed complex substrates, producing 12.3 ± 0.01 A/m 2 . 16S rRNA gene sequencing showed that community structure and community diversity were not predictive of performance, and replicate community structures diverged despite identical inoculum and enrichment procedure. The trends in each replicate, however, were indicative of the influence of the substrates. Geobacter was the most dominant genus across most of the samples tested, but its abundance did not correlate strongly to current density. High-performance liquid chromatography (HPLC) showed that acetic acid accumulated during open circuit conditions when MECs were fed with complex feedstocks and was quickly degraded once closed circuit conditions were applied. The largest net acetic acid removal rate occurred when MECs were fed with red oak bio-oil aqueous phase, consuming 2.93 ± 0.00 g/L-day. Principal component analysis found that MEC performance metrics such as current density, hydrogen productivity, and chemical oxygen demand removal were closely correlated. Net acetic acid removal was also found to correlate with performance. However, no bacterial genus appeared to correlated to these performance metrics strongly, and the analysis suggested that less than 70% of the variance was accounted for by the two components. This study demonstrates the robustness of microbial communities to adapt to a range of feedstocks and conditions without relying on specific species, delivering high hydrogen productivities despite differences in community structure. The results indicate that functional adaptation may play a larger role in performance than community composition. Further investigation of the roles each microbe plays in these communities will help MECs to become integral in the 21st-century bioeconomy to produce zero-emission fuels.
We report Syntrophic consortia of anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB) consume large amounts of methane and serve as the foundational microorganisms in marine methane seeps. Despite their importance in the carbon cycle, research on the physiology of ANME-SRB consortia has been hampered by the slow growth and complex physicochemical environment the consortia inhabit. Here, we report successful sediment-free enrichment of ANME-SRB consortia from deep-sea methane seep sediments in the Santa Monica Basin, California. Anoxic Percoll density gradients and size-selective filtration were used to separate ANME-SRB consortia from sediment particles and single cells to accelerate the cultivation process. Over a 3-year period, a subset of the sediment-associated ANME and SRB lineages, predominantly comprised of ANME-2a/2b (“Candidatus Methanocomedenaceae”) and their syntrophic bacterial partners, SEEP-SRB1/2, adapted and grew under defined laboratory conditions. Metagenome-assembled genomes from several enrichments revealed that ANME-2a, SEEP-SRB1, and Methanococcoides in different enrichments from the same inoculum represented distinct species, whereas other coenriched microorganisms were closely related at the species level. This suggests that ANME, SRB, and Methanococcoides are more genetically diverse than other members in methane seeps. Flow cytometry sorting and sequencing of cell aggregates revealed that Methanococcoides, Anaerolineales, and SEEP-SRB1 were overrepresented in multiple ANME-2a cell aggregates relative to the bulk metagenomes, suggesting they were physically associated and possibly interacting. Overall, this study represents a successful case of selective cultivation of anaerobic slow-growing microorganisms from sediments based on their physical characteristics, introducing new opportunities for detailed genomic, physiological, biochemical, and ecological analyses. Biological anaerobic oxidation of methane (AOM) coupled with sulfate reduction represents a large methane sink in global ocean sediments. Methane consumption is carried out by syntrophic archaeal-bacterial consortia and fuels a unique ecosystem, yet the interactions in these slow-growing syntrophic consortia and with other associated community members remain poorly understood. The significance of this study is the establishment of sediment-free enrichment cultures of anaerobic methanotrophic archaea and sulfate-reducing bacteria performing AOM with sulfate using selective cultivation approaches based on size, density, and metabolism. By reconstructing microbial genomes and analyzing community composition of the enrichment cultures and cell aggregates, we shed light on the diversity of microorganisms physically associated with AOM consortia beyond the core syntrophic partners. These enrichment cultures offer simplified model systems to extend our understanding of the diversity of microbial interactions within marine methane seeps.
Knowledge of microbial gene functions comes from manipulating the DNA of individual strains in isolation from their natural communities. While this approach to microbial genetics has been foundational, its requirement for culturable microorganisms has left the majority of microbes and their interactions genetically unexplored. Here, we describe a generalizable strategy for editing the genomes of specific organisms within microbial communities. We identified genetically tractable bacteria within a community using Environmental Transformation Sequencing (ET-Seq), an approach in which non-targeted transposon integrations are mapped and quantified following community delivery. We next developed and used DNA-editing All-in-one RNA-guided CRISPR-Cas Transposase (DART) systems for targeted DNA insertion into organisms identified as tractable by ET-Seq, enabling organism- and locus-specific genetic manipulation within the community context. To illustrate the utility of our approach, we selectively edited closely related strains, measured gene fitness, and enriched targeted members within soil and infant gut microbiota. These results establish a new paradigm for targeted community editing relevant to research and applications on medical, agricultural, and industrial microbiomes.
The ecological drivers that concurrently act upon both a virus and its host and that drive community assembly are poorly understood despite known interactions between viral populations and their microbial hosts. Hydraulically fractured shale environments provide access to a closed ecosystem in the deep subsurface where constrained microbial and viral community assembly processes can be examined. Here, we used metagenomic analyses of time-resolved-produced fluid samples from two wells in the Appalachian Basin to track viral and host dynamics and to investigate community assembly processes. Hypersaline conditions within these ecosystems should drive microbial community structure to a similar configuration through time in response to common osmotic stress. However, viral predation appears to counterbalance this potentially strong homogeneous selection and pushes the microbial community toward undominated assembly. In comparison, while the viral community was also influenced by substantial undominated processes, it assembled, in part, due to homogeneous selection. When the overall assembly processes acting upon both these communities were directly compared with each other, a significant relationship was revealed, suggesting an association between microbial and viral community development despite differing selective pressures. These results reveal a potentially important balance of ecological dynamics that must be in maintained within this deep subsurface ecosystem in order for the microbial community to persist over extended time periods. More broadly, this relationship begins to provide knowledge underlying metacommunity development across trophic levels.
Ants play multiple roles in ecosystems, but their ability to affect decomposition processes in temperate grasslands is relatively unknown. We investigated whether the suppression of ant populations influenced litter decomposition in grasslands via predation of some decomposers (e.g., mites and springtails) and/or microbial activity and composition. We performed two successful ant suppression treatments (seven weeks, 37% suppression, year 1, 10 weeks, 70% suppression, year 2) over the course of a 59-week experiment. We then assayed the effects of ant suppression using coarse- and fine-mesh litterbags and evaluated litter chemistry, microbial and arthropod communities, and microbial enzyme activity. Ant suppression efforts reduced ant abundance and altered ant, arthropod decomposer, and non-ant predator community composition. However, ant suppression did not affect decomposer arthropod abundance, litter mass loss, microbial composition, or enzyme activity in litterbags. Litterbag mesh size did not alter microbial composition, perhaps due to a failure to exclude decomposers, as mites and springtails were more or equally abundant in fine-mesh bags. Nevertheless, mesh size did change litter chemistry, suggesting that mesh size-mediated microenvironments affect decomposition environment regardless of invertebrate exclusion. Coarse-mesh litterbags had higher concentrations of microbial sugars, lignin, and N and lower concentrations of litter C and crystalline cellulose than fine-mesh litterbags. Litterbag mesh size may alter decomposition processes irrespective of invertebrate abundance. We found no evidence that ant predation was an important driver of decomposer populations or decomposition in these systems, and we suspect redundancy at the top of the detrital food web dilutes the role of ants.
Climate change will increase soil drying, altering microbial communities via increasing water stress and decreasing resource availability. The responses of these microbial communities to changing environments could be governed by physiological tradeoffs between high yield, resource acquisition, and stress tolerance (YAS framework). We leveraged a unique field experiment that manipulates both drought and carbon availability across two years and three land uses, and we measured both physiological (with bioassays) and genetic (with metagenomics) microbial traits at the community level to test the following hypotheses: 1. Drought increases microbial allocation to stress tolerance functions, at both physiological and genetic levels. 2. Because microbes are resource-limited under drought, increased carbon will enable greater expression of stress tolerance. 3. All three key life history traits described in the YAS framework will trade off. Drought did increase microbial physiological investment in stress tolerance (measured via trehalose production), but we saw few other changes in microbial communities under drought. Adding carbon to plots increased resource acquisition (measured via enzyme activity and resource acquisition gene abundance) and stress tolerance (trehalose assay), but did so in both drought and average rainfall environments. Here, we found little evidence of trait tradeoffs, as a negative correlation between rRNA copy number and resource acquisition gene abundance was the only significant negative correlation between traits that we found that was consistent across years (for physiological or genetic traits). In summary, we found C addition, and to a lesser extent, drought, altered microbial community function and functional genes. However, resources did not alter drought response in a way that was consistent with theory of life history tradeoffs.
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.
Atmospheric nitrogen pollution has altered fundamental soil processes, challenging our understanding of the extent to which soils will continue to sequester carbon and slow the pace of future environmental change. While most evidence shows that increases in soil nitrogen have enhanced carbon storage in temperate forests, it remains unclear whether these effects will persist as nitrogen pollution continues to decline. Moreover, there remains uncertainty as to why some forests gain more carbon in response to nitrogen pollution than others. At the heart of this knowledge gap is a failure to link nitrogen–induced shifts in microbial biodiversity with gains or losses in their functional ability to decompose, assimilate, and ultimately stabilize soil carbon. Given that this uncertainty impedes the ability of predictive models to project future soil carbon stocks, there is a critical need to determine how key microbial traits drive soil carbon responses to nitrogen pollution. As such the goals of this project were to: (1) Quantify variation in taxon–specific and community–level microbial traits across gradients in microbial community composition, mycorrhizal symbioses, and nitrogen availability. (2) Integrate empirical data into a novel predictive framework that enhances our ability to project the regional soil carbon consequences of historical nitrogen pollution in temperate forests.
Microbial necromass contributes significantly to both soil carbon (C) persistence and ecosystem nitrogen (N) availability, but quantitative estimates of C and N movement from necromass into soils and decomposer communities are lacking. Additionally, while melanin is known to slow fungal necromass decomposition, how it influences microbial C and N acquisition as well as elemental release into soils remains unclear. Here, we tracked decomposition of isotopically labeled low and high melanin fungal necromass and measured 13 C and 15 N accumulation in surrounding soils and microbial communities over 77 d in a temperate forest in Minnesota, USA. Mass loss was significantly higher from low melanin necromass, corresponding with greater 13 C and 15 N soil inputs. A taxonomically and functionally diverse array of bacteria and fungi was enriched in 13 C and/or 15 N at all sampling points, with enrichment being consistently higher on low melanin necromass and earlier in decomposition. Similar patterns of preferential C and N enrichment of many bacterial and fungal genera early in decomposition suggest that both microbial groups co-contribute to the rapid assimilation of resource-rich soil organic matter inputs. While overall richness of taxa enriched in C was higher than in N for both bacteria and fungi, there was a significant positive relationship between C and N in co-enriched taxa. Collectively, our results demonstrate that melanization acts as a key ecological trait mediating not only fungal necromass decomposition rate but also necromass C and N release and that both elements are rapidly co-utilized by diverse bacterial and fungal decomposers in natural settings.