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At least 559 records · Page 31

Development and Validation of a Process Model and Open-Source Process Simulator for Microalgae-Based Tertiary Phosphorus Recovery

Microalgae-based tertiary wastewater treatment has the potential to meet stringent effluent phosphorus limits, with the added benefit of producing a marketable feedstock. However, the lack of validated mechanistic models and their implementation in process simulators have limited the adoption of this technology. In this study, an updated lumped pathway metabolic model (Phototrophic-Mixotrophic Process Model, PM 2 ), including both photoautotrophic and heterotrophic metabolisms of microalgae, was developed to predict effluent phosphorus concentration and biomass yield in response to dynamic influent and varying environmental conditions. The model was implemented in QSDsan – an open-source, Python-based design and simulation platform – for robust simulation under uncertainty. A global sensitivity analysis was performed to prioritize model parameters for calibration. The model was then calibrated and validated using batch experimental data and 45 days of continuous online monitoring data from a full-scale (568 m 3 ·d -1 ) microalgae-based tertiary wastewater treatment plant (EcoRecover process). In particular, along with dynamic influent composition, temperature and light intensity data with diel variation were provided as model inputs to reflect the microalgal behavior under day-night cycling. Overall, the QSDsan-based microalgae process simulator was able to predict effluent phosphorus within 0.02–0.04 mg-P·L -1 , while also capturing the general trends of state variables according to nutrient availability.

Lumped pathway metabolic model↗

Analytical Modeling of Biomass Transport and Feeding Systems

The processing of biomass solids in a biorefinery consists of pretreatment, enzyme hydrolysis / concurrent fermentation of sugars to ethanol, product recovery, and drying. Sustainable operation requires a front end that transforms wet solids into a pumpable slurry. Otherwise the biorefinery will suffer unscheduled shut-downs and inefficient operation due to solids that obstruct pumps and other equipment and resist mixing in a bioreactor. Downtime in pioneer biorefineries due to interruptions from materials handling problems has been 50% or more, leading to unsustainable manufacturing processes. This work addresses new technology, predictive computational models, and definition of operational conditions that result in formation of slurries of corn stover at up to 300 g/L using low enzyme loadings (1 to 3 FPU cellulase/g) before the biomass (corn stover) enters the pretreatment step. A team of researchers from Purdue University, Idaho National Laboratory (INL), Forest Concepts, AdvanceBio, Argonne National Laboratory, and DOE BETO have combined their knowledge in agricultural and biological engineering, bioprocess engineering, mechanical engineering, chemical engineering, agricultural economics, materials engineering and enzyme and microbial technology to address the challenge of making lignocellulose flow. This team effort has resulted in the development and validation of conditions that employ low levels of commercial enzyme in an agitated bioreactor to which corn stover pellets are added resulting in formation of slurries at high solids loadings, before pretreatment. This approach overcomes challenges caused by handling of dry, particulate biomass materials at the front end of the biorefinery. The subsequent materials handling issues cause obstruction at pumps, pipes and valves. Formation of high loadings slurries with low yield stress, as reported here, significantly decreases the potential for process interruption and enhances plant operability. Key advances in the knowledge of how slurry formation occurs is reported here and in recently published journal papers. We found that pellets are needed to achieve high solids loading, and that commercial enzymes are effective in forming slurries of corn stover particles from pellets that have not been pretreated. Our work has resulted in models that predict solids behavior for formation of compressed solids and pellets that in turn facilitate slurries made of high concentrations of corn stover particles. A computational model was developed that gives mechanistic insights into properties of particles and mixing process that gives the slurry rheology needed to facilitate pumping. Hence, the corn stover may be pumped into a pretreatment reactor in place of auguring in solids against high pressure which is a root cause of interruptions at the front end of a biorefinery. Subsequent mixing in enzyme and microbial bioreactors results in conversion of lignocellulose to sugars in a biorefinery in agitated bioreactors, with flows in and out of the vessels being less likely to be interrupted due to plugging or materials handling problems. The obtained data coupled to process models, techno-economic assessment (TEA) and Life Cycle Analysis (LCA) were used to assess whether this approach is practical. These results are based on a foundation of laboratory characterization and pilot runs. The NREL biochemical sugar model was utilized to carry out techno-economic analysis of enzyme catalyzed liquefaction followed by enzyme hydrolysis. The minimum sugar selling price was between 17.5 and 18.3 ¢/pound or about the same as calculated by the NREL model for dilute acid pretreatment followed by enzyme hydrolysis. Life cycle analysis (LCA) based on Argonne’s Greet Model showed the enzyme catalyzed route had the lowest greenhouse gas emissions of the three combinations studied (i.e., enzyme, enzyme mimetic, and enzyme + mimetic combined). GHG emissions for enzyme-based corn stover liquefaction step, alone, were about 21 g CO 2 -equivalent/kg of liquefied slurry. We believe this approach will further enhance operability of a pioneer biorefinery, and bring large-scale conversion of lignocellulosic biomass to low carbon footprint biofuels closer to implementation.

09 BIOMASS FUELS↗

Increased salinity decreases annual gross primary productivity at a Northern California brackish tidal marsh

Tidal marshes sequester 11.4–87.0 Tg C yr –1 globally, but climate change impacts can threaten the carbon capture potential of these ecosystems. Tidal marshes occur across a wide range of salinity, with brackish marshes (0.5–18 ppt (parts per thousand)) dominating global tidal marsh extents. A diverse mix of freshwater- and saltwater-tolerant plant and microbial communities has led researchers to predict that carbon cycling in brackish wetlands may be less sensitive to changes in salinity than fresh- or saltwater wetlands. Rush Ranch, a well-monitored brackish tidal wetland of the San Francisco Bay National Estuarine Research Reserve, experiences highly variable annual salinity regimes. Within a five-year period (2014–2018), Rush Ranch experienced particularly extreme drought-induced salinization during the 2014 and 2015 growing seasons. During drought years, tidal channel salinity rose from a 15 year baseline of 4.7 ppt to growing season peaks of 10.3 ppt and 12.5 ppt. Continuous eddy covariance data from 2014 to 2018 demonstrate that during drought summers, gross primary productivity (GPP) decreased by 24%, whereas ecosystem respiration remained similar among all five years. Stepwise linear regression revealed that salinity, not air temperature or tidal height, was the dominant driver of annual GPP. A random forest model trained to predict GPP based on environmental data from low salinity years (i.e. naive to salinization) significantly over predicted GPP in drought years. When growing season salinities were doubled, annual estimates of net ecosystem exchange of CO 2 decreased by up to 30%. These results provide ecosystem-scale evidence that increased salinity influences CO 2 fluxes dominantly through reductions in GPP. This relationship provides a starting point for incorporating the effect of changes in salinity in wetland carbon models, which could improve wetland carbon forecasting and management for climate resilience.

54 ENVIRONMENTAL SCIENCES↗

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

This closeout presentation summarizes a Department of Energy–funded study that evaluated whether large amounts of hydrogen can be safely stored underground in the North Dakota portion of the Williston Basin. The project combined lab testing, computer simulations, and basin‑wide analysis to assess saline formations, depleted oil and gas reservoirs, and salt formations for hydrogen storage capacity, recovery, and risks. Results show that underground hydrogen storage is technically feasible across multiple formation types, with depleted oil and gas reservoirs offering higher recovery and saline formations providing large long‑term storage potential. The study also identifies key challenges—such as wellbore material durability and gas purity management—and recommends pilot projects and further site‑specific studies to support future commercialization.

08 HYDROGEN↗

Assessing electrogenetic activation via a network model of biological signal propagation

Introduction: Molecular communication is the transfer of information encoded by molecular structure and activity. We examine molecular communication within bacterial consortia as cells with diverse biosynthetic capabilities can be assembled for enhanced function. Their coordination, both in terms of engineered genetic circuits within individual cells as well as their population-scale functions, is needed to ensure robust performance. We have suggested that “electrogenetics,” the use of electronics to activate specific genetic circuits, is a means by which electronic devices can mediate molecular communication, ultimately enabling programmable control. Methods: Here, we have developed a graphical network model for dynamically assessing electronic and molecular signal propagation schemes wherein nodes represent individual cells, and their edges represent communication channels by which signaling molecules are transferred. We utilize graph properties such as edge dynamics and graph topology to interrogate the signaling dynamics of specific engineered bacterial consortia. Results: We were able to recapitulate previous experimental systems with our model. In addition, we found that networks with more distinct subpopulations (high network modularity) propagated signals more slowly than randomized networks, while strategic arrangement of subpopulations with respect to the inducer source (an electrode) can increase signal output and outperform otherwise homogeneous networks. Discussion: We developed this model to better understand our previous experimental results, but also to enable future designs wherein subpopulation composition, genetic circuits, and spatial configurations can be varied to tune performance. We suggest that this work may provide insight into the signaling which occurs in synthetically assembled systems as well as native microbial communities.

Chun, Kayla↗

Cas3-Mediated Genome Reduction: Demonstration in Cupriavidus Necator H16 Improves Growth on Heterotrophic and Autotrophic Carbon Sources

Genome reduction is widely used to improve microbial bioprocessing hosts by reducing the burden of inessential physiology. Rationally identifying genomic regions that are dispensable or even detrimental to bioprocessing is challenged by our inability to map genome sequence to function across complex regulation and physiology. Thus, there is a need for tools that rapidly generate reduced genome strains with improved performance in process-relevant conditions. Here, we report a Cascade-Cas3-enabled method called TRIM3 that generates large deletions by targeting a randomly integrated transposon, enabling facile generation of a genome-reduced mutant library. Mutants with improved performance were isolated following growth-coupled selection and analyzed by long-read DNA sequencing to identify deletions in their genomes. We deploy this system iteratively in the industrial host Cupriavidus necator H16 on fructose and on formate. After two rounds of TRIM3, we isolate a strain containing a total reduction of 1.4 Mb (18.4% of the genome) that grows 25% faster in a bioreactor on fructose and a strain with a total reduction of 0.5 Mb (7.3% of the genome) that grows 14% faster on formate. This work demonstrates a method for random, iterative, growth-selectable genome reduction that represents a new avenue for large-scale genome modifications and the development of improved bioprocessing hosts.

09 BIOMASS FUELS↗

Consequences of Altered Root Nutrient Uptake for Soil Carbon Stabilization (Final Report)

Objectives: The primary objectives of this project are to improve our understanding of tropical forest belowground processes, and to increase representation of this biome in ecosystem-scale and global C cycle models. Belowground dynamics present a major source of uncertainty inhibiting our ability to predict C cycle responses to climate change. Representation of tropical forests in these models is particularly lacking, even though these ecosystems hold >25% of terrestrial C stocks. While the majority of humid tropical forests exist on relatively infertile soils (i.e. poor in rock-derived nutrients), enormous gradients in soil nutrient availability exist at landscape-scales due to shifts in geology and soil order. Soil fertility is likely to greatly influence how tropical soil C storage will respond to the declines in precipitation predicted for the tropics. In particular, root dynamics vary across soil fertility gradients, with roots representing the major input of C to subsurface soils. Root characteristics related to soil fertility include biomass, turnover, C exudates, tissue chemistry, and nutrient uptake rates, with each of these likely sensitive to changes in moisture. The proposed project will fully integrate field research with an existing ecosystem model to assess potential effects of drying on belowground tropical C dynamics across a range of soil fertilities. Project Description:. This project will identify key linkages among soil fertility, root nutrient uptake, root dynamics, and soil C storage. The hypothesized framework for understanding these linkages is: Tropical rainforest roots in relatively fertile soils have lesser root biomass, faster turnover, fewer exudates, and improved root tissue quality relative to infertile sites, all resulting from increased root nutrient uptake. Ultimately, these root characteristics in fertile soils promote proportionally greater long-term soil C storage in organo-mineral associations. Specifically, lower root exudates and improved root tissue quality in fertile soils reduce microbial respiration of extant soil C (i.e. “priming) and increase microbial C use efficiency, leading to sorption of protein-rich microbial and plant organic matter on soil mineral surfaces. However, the larger pools of mineral-associated C in fertile tropical soils are more vulnerable to decreased rainfall than smaller C pools in infertile soils, in part because of the lesser root biomass, faster turnover, and softer, more labile root tissues. Also, the shallower lateral rooting structures typical in fertile soils experience greater desiccation and death than deeper roots in infertile sites, with little short-term adaptation to drying.

54 ENVIRONMENTAL SCIENCES↗

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.

NMDC, Microbiome↗

Arctic Shrub Expansion, Plant Functional Trait Variation, and Effects on Belowground Carbon Cycling (Final Technical Report)

Terrestrial ecosystems are undergoing dramatic changes in response to climate warming, and these changes are expected to feedback to the atmosphere, potentially altering the trajectory of future climate change. Feedbacks from Arctic ecosystems are a major concern because the Arctic is projected to warm significantly in the 21 st century and because >50% of global belowground organic carbon is stored in permafrost and overlying soils. Warming-driven release of this carbon could drastically increase atmospheric greenhouse gas concentrations and accelerate climate warming. Plant communities are also responding to warming, as evidenced by the widely documented increase in woody-shrub growth and “greening” across much of the Arctic tundra biome. This vegetation shift may offset or amplify warming by altering carbon cycling. The direction and magnitude of shrub effects remain highly uncertain, however, due to limited understanding of the consequences of shrub expansion for belowground carbon cycling and simplification of these relationships in models. The major shrubs expanding in the Arctic (Betula, Salix, and Alnus) vary widely with respect to aboveground and belowground traits (e.g., tissue production and chemistry, rooting depth, microbial symbionts), and may also exhibit substantial intraspecific variation in these traits in response to environmental conditions. Such variation is likely to have profound implications for soil carbon cycling. The overarching goal of this project was to improve process-based understanding of the influence of shrub expansion on carbon cycling to enable improved representation of carbon dynamics in ecosystem and Earth system models. We investigated how plant functional traits vary among shrub genera, respond to environmental conditions, and affect belowground carbon and nutrient cycling by quantifying relationships among functional traits and biogeochemical cycling along edaphic gradients nested within a climate gradient in the Alaskan tundra. We found consistent differences in leaf and root traits among shrub genera and between shrubs and a widespread sedge species, indicating diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs. We also found striking differences in trait values among individuals within the same species or genera within sites. Soil parameters were more important than climate parameters for predicting size and leaf trait variation, and root trait responses were less dependent on climate overall. For all but one root trait, including parameters representing aboveground traits improved the predictive ability of models. These results demonstrate that tundra shrub traits vary considerably at local scales and soil factors drive this variation, especially belowground. Furthermore, leveraging information about aboveground traits and soil conditions can improve predictions of how belowground traits will respond to climate change. Despite these differences, soil carbon and nitrogen pools in the active layer did not vary among plots dominated by different shrub or sedge genera. Instead, pool sizes generally decreased from warmer to colder sites, consistent with a productivity gradient. Patterns of isotopic N composition indicate that shrubs tighten nitrogen cycling via nitrogen resorption or immobilization of shrub litter. Overall, these results suggest that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic. We also performed simulation experiments with the Terrestrial Ecosystem Model (TEM) incorporated in the Predictive Ecosystem Analyzer (PEcAn) framework, treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We performed simulations across different types of tundra, including shrub tundra. One key finding was that both model sensitivity and uncertainty to a given parameter could vary within the same type of tundra, but in a different geographical location, such as over the climate gradient of shrub tundra described above. We organized a special session at the annual meeting of the Ecological Society of America in August 2019 to disseminate our results, refine recommendations for model improvement, and initiate collaborations to implement these recommendations in existing models of tundra carbon dynamics at ecosystem to Earth system scales. Our results support DOE near-term priorities by providing mechanistic insights into the role of vegetation change in the terrestrial carbon cycle in a region that is inadequately represented in Earth system models. Current models reduce the complexity of Arctic vegetation to a small number of plant functional types (PFTs). This approach implicitly assumes that each PFT represents the average ecological function of its constituent species, thus ignoring the effects of trait variation on biogeochemical cycling and potentially leading to large uncertainty in the sign and magnitude of ecosystem feedbacks to climate. By quantifying variation of plant functional traits across broad gradients of climatic and edaphic conditions and elucidating the linkages of such variation with carbon and nutrient cycling, our results illustrate the need and create a foundation for further developing trait-based modeling approaches that allow the traits of PFTs to vary as a function of environmental conditions. These approaches should improve the capacity of simulation models to offer insights into ecosystem carbon dynamics associated with novel plant communities in a rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗

Taxon-specific microbial growth and mortality patterns reveal distinct temporal population responses to rewetting in a California grassland soil

Abstract Microbial activity increases after rewetting dry soil, resulting in a pulse of carbon mineralization and nutrient availability. The biogeochemical responses to wet-up are reasonably well understood and known to be microbially mediated. Yet, the population level dynamics, and the resulting changes in microbial community patterns, are not well understood as ecological phenomena. Here, we used sequencing of 16S rRNA genes coupled with heavy water (H218O) DNA quantitative stable isotope probing to estimate population-specific rates of growth and mortality in response to a simulated wet-up event in a California annual grassland soil. Bacterial growth and mortality responded rapidly to wet-up, within 3 h, and continued throughout the 168 h incubation, with patterns of sequential growth observed at the phylum level. Of the 37 phyla detected in the prewet community, growth was found in 18 phyla while mortality was measured in 26 phyla. Rapid growth and mortality rates were measurable within 3 h of wet-up but had contrasting characteristics; growth at 3 h was dominated by select taxa within the Proteobacteria and Firmicutes, whereas mortality was taxonomically widespread. Furthermore, across the community, mortality exhibited density-independence, consistent with the indiscriminate shock resulting from dry-down and wet-up, whereas growth was density-dependent, consistent with control by competition or predation. Total aggregated growth across the community was highly correlated with total soil CO2 production. Together, these results illustrate how previously “invisible” population responses can translate quantitatively to emergent observations of ecosystem-scale biogeochemistry.

58 GEOSCIENCES↗

The transformation of U(VI) and V(V) in carnotite group minerals during dissimilatory respiration by a metal reducing bacterium

Recent results from laboratory and field studies support that dissimilatory metal reducing (DMR) bacteria influence the fate and transport of uranium in anaerobic subsurface environments. To date, most research efforts have focused on the reduction of soluble U(VI) by DMR bacteria to form insoluble uraninite (UO 2 ). Subsurface environments harbor, however, large reservoirs of U(VI) in solid or mineral form. Uranium that is structure-bound in minerals is expected to be more refractory to microbial reduction than soluble U, based on analogy with Fe respiration. The reducibility of U(VI) could impact the fate of U(IV) by controlling mineral precipitation reactions, which has implications for the long-term immobilization of U in subsurface environments. Here, we studied anoxic cultures of Shewanella putrefaciens CN32 incubated with natural carnotite-group minerals by X-ray diffraction, electron microscopy, scanning transmission X-ray microscopy (STXM). Near-edge X-ray absorption fine structure (NEXAFS) spectroscopy measurements at U-N 4,5 , V-L 2,3 , and O-K edges on cultures incubated up to 10 months show that V(V) was reduced to V(IV), whereas U was not reduced. In contrast, V(V) and U(VI) in solution were both completely reduced to lower oxidation states by CN32, as precipitates within the exopolymer surrounding the bacteria. Assays for the toxicity of U and V to CN32 showed that biofilm formation was stimulated at 0.001 M U(VI), and growth was inhibited at concentrations of U(VI) greater than 0.001 M. Vanadium did not inhibit growth or stimulate biofilm formation at any concentration tested. Investigations of the bacteria-mineral and bacteria-metal interface at the nanometer and molecular scales provide new insights into the co-respiration of V and U that help explain their biogeochemical cycling and have implications for subsurface bioremediation of these elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quorum-driven microbial consortium for Bioplastic production from agro-waste

Microbial consortia have high relevance in natural environments. Here we present the production of polyhydroxyalkanoates (PHA) from agro-industrial residues by a synthetic interkingdom consortium formed by the saprotrophic fungus Ophiostoma piceae CECT 20146, which encodes a wide range of lignocellulolytic enzymes, and a natural PHA producer, Pseudomonas putida KT2440. Two agro-industrial residues were utilized: Brewer's Spent Grain (BSG) as a carbon/nitrogen source and biofilm scaffold and waste cooking oil (WCO) as a carbon source for PHA synthesis. Through biochemistry, microscopy, and omics analyses, it is shown that P. putida accumulates up to 40.2% of intracellular PHA when the quorum sensing molecule, farnesol (naturally produced by O. piceae) is added, thanks to the increased proliferation of P. putida cells. An interactive Shiny application has also been developed for an easy visualization and comprehension of all the transcriptomics and metabolomics data: https://jgf-bioinformatics.shinyapps.io/Visualization_app/. These results support the increased PHA production of the consortium by an induction of gene phaG, which redirects intermediaries of the fatty acid biosynthesis to PHA precursors, and the repression of the PHA depolymerase phaZ in P. putida. The trophic interaction between microorganisms seems to rely on the citric acid produced by O. piceae and the glycerol liberated from WCO, which can both be consumed by P. putida. Bioreactor scale-up experiments allowed a 3.3-fold increase in the PHA concentration in the consortium (6.7 g·L-1) without pretreatment or sterilization of the substrates, laying the groundwork for the implementation of an industrial consolidated bioprocess (CBP).

Bacteria↗

Mercury Methylation and Soil Organic Matter Degradation in Incubations with Added Acetate, Isotope-Labeled Mercury, and Selective Microbial Inhibitors, Teller and Council Sites, Seward Peninsula, 2018-2019

This dataset provides the results of laboratory soil microcosm incubation experiments conducted under anaerobic conditions with added acetate, isotope-labeled mercury, and selective microbial inhibitors (2-bromoethanesulfonate and sodium molybdate). The microcosms contained soil collected in August 2018 from the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) near Intensive Site 9 (TL_IS_9) and from the Council Road Site (CN_MM71). Incubations were conducted at 8°C for 180 days (Teller incubations) or 60 days (Council incubations). The microcosm headspace was sampled at designated intervals for greenhouse gas concentrations, then destructively harvested and extracted using ultrapure water and 0.1 M KCl for analysis of the porewater geochemistry. This dataset contains one pdf, two csv data files, and one zipped file with raw data.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Sphingomonas clade and functional distribution with simulated climate change

Microbes are essential for the functioning of all ecosystems, and as global warming and anthropogenic pollution threaten ecosystems, it is critical to understand how microbes respond to these changes. We investigated the climate response of Sphingomonas, a widespread gram-negative bacterial genus, during an 18-month microbial community reciprocal transplant experiment across a Southern California climate gradient. We hypothesized that after 18 months, the transplanted Sphingomonas clade and functional composition would correspond with site conditions and reflect the Sphingomonas composition of native communities. We extracted Sphingomonas sequences from metagenomic data across the gradient and assessed their clade and functional composition. Representatives of at least 12 major Sphingomonas clades were found at varying relative abundances along the climate gradient, and transplanted Sphingomonas clade composition shifted after 18 months. Site had a significant effect (PERMANOVA; P < 0.001) on the distribution of both Sphingomonas functional (R 2 = 0.465) and clade composition (R 2 = 0.400), suggesting that Sphingomonas composition depends on climate parameters. Additionally, for both Sphingomonas clade and functional composition, ordinations revealed that the transplanted communities shifted closer to the native Sphingomonas composition of the grassland site compared with the site they were transplanted into. Overall, our results indicate that climate and substrate collectively determine Sphingomonas clade and functional composition.

59 BASIC BIOLOGICAL SCIENCES↗

Investigating Material Properties of Subsurface Rock Formations Modified by Engineering Mineral Precipitation (Final Scientific and Technical Report)

Montana State University’s (MSU) Energy Research Institute (ERI), in collaboration with the Center for Biofilm Engineering (CBE) and the Department of Civil Engineering (CE), has conducted a long‐term research program aimed at developing a novel cementing agent to address wellbore integrity and reduce the unwanted upward migration of fluids and greenhouse gases from the subsurface. The primary technology developed through this research program is known as ureolysis‐induced calcite precipitation (UICP), which harnesses bio‐chemical processes to precipitate calcium carbonate (CaCO 3 ). The same general process can also be called microbially-induced calcium carbonate precipitation (MICP) when microbes provide the process-catalyzing urease enzyme. Both terms are used in this report. Results have conclusively demonstrated that, if properly controlled, UICP can successfully seal fractures, high permeability zones, and compromised cement in the vicinity of wellbores and in nearby caprock. This technology has been successfully deployed to mitigate annular leakage in two test wells and over sixty commercial wells with a 100% success rate. This success in downhole deployment generates consideration of other subsurface applications where UICP could provide benefit to the energy sector, such as shale property modification for unconventional oil and gas recovery. The focus of this research project was to investigate fundamental material and mechanical properties of select shale cores and analyze how these properties change due to engineered mineral precipitation with the intent to control these properties to achieve a range of engineering objectives. Ultimately, the project aim was to identify valuable new areas where application of UICP might contribute to national energy security and environmental protection. The research workplan coupled UICP treatment of core samples, nuclear magnetic resonance (NMR) characterization, and mechanical strength testing at MSU with advanced X‐Ray micro-computed tomography (μCT) imaging and numerical modeling performed by collaborators at two national laboratories, the National Energy Technology Laboratory (NETL) and Lawrence Berkeley National Laboratory (LBNL). Experimental results are useful to inform geo-mechanical models which could be applied to predict mineralized rock formation behavior at field scale. Our findings suggest that NMR and μCT methods to detect and quantify biomineral formation in shale fractures are complementary and consistent with each other. Either could be used to estimate the volume of new mineral formed by UICP in shale fractures. The use of surfactants and guar gum to enhance biomineral precipitation in shale fractures merits further research. UICP can, under some conditions, increase the tensile strength of sealed shale fractures beyond that of the intact shale. These findings demonstrate that continued research in this area may be valuable to understanding and improving shale resource recovery techniques.

58 GEOSCIENCES↗

An integrated process for butanol production from cellulosic biomass and CO 2 using engineered clostridia in a linear immobilized bioreactor

Engineered platforms using mixed microbial consortia to consolidate multiple reaction steps and perform disparate conversions simultaneously can substantially enhance the carbon efficiency of biomass conversion processes and lower the biofuel cost to an economically competitive level. In this project, an integrated process will be developed to produce n-butanol from cellulosic biomass and waste gas streams using two engineered clostridial strains, one butanol-tolerant solventogenic strain and one carboxydotrophic acetogen, co-immobilized in a “Linear Immobilized Bioreactor” (LIBR). The CO 2 and H 2 produced by the solventogenic strain will be used by the carboxydotrophic strain to produce acetate (and butyrate) that in turns can be used by the solventogenic strain to produce more butanol. Such a co-cultured fermentation has the potential to increase butanol production from biomass hydrolysate sugars by up to 50% with 100% reduction in CO 2 emission. Butanol produced in the fermentation will be stripped by the rising bubbles of fermentation produced gases (CO 2 and H 2 ) in the LIBR and separated via a condenser, alleviating butanol inhibition while achieving continuous butanol production at a high productivity and product titer, which can reduce both water and energy consumptions by over 50% compared to conventional ethanol and ABE fermentation processes. Phase I study proved the new bioprocess concept and verified our hypothesis that the proposed LIBR and co-cultured fermentation can enhance the conversion of lignocellulosic sugars to butanol with higher butanol yield, productivity and titer, leading to reduced biobutanol cost to compete more favorably with bioethanol and fossil fuels. A prototype lab-scale LIBR for multiphase fermentation was constructed to investigate and demonstrate the technical feasibility and advantages of the LIBR for multiphase fermentation involving sugars and gaseous substrates. The LIBR will be optimized and evaluated for its economic feasibility for biobutanol production from lignocellulosic biomass and industrial waste gases in Phase II.

09 BIOMASS FUELS↗

Investigating Electron Conductivity Regimes in the Bacterial Cytochrome Wire OmcS

The anaerobic bacterium Geobacter sulfurreducens produces extracellular, electronically conductive cytochrome polymer wires that are conductive over micron length scales. Structure models from cryo-electron microscopy data show OmcS wires form a linear chain of hemes along the protein wire axis, which is proposed as the structural basis supporting their electronic properties. However, the mechanism by which this heme arrangement supports long-range electronic conduction remains unknown. Structure models from cryo-electron microscopy data show these wires form a linear chain of hemes along the protein wire axis, which is proposed as the structural basis supporting their electronic properties. Existing computational models using static heme redox potentials and coupling energies fail to explain experimental observations, predicting conductances 10,000 to 100,000 times lower than measured values. Here, we investigate how dynamic disorder affects site energies, interheme coupling, and long-range electronic conductivity within these cytochrome wires. We introduce an approach to extract charge carrier site information directly from Kohn–Sham density functional theory, without employing projector schemes, and show that site and coupling energies are highly sensitive to changes in interheme geometry and the surrounding electrostatic environment. Unlike models that incorporate dynamic disorder as a thermally averaged quantity, our quantum charge carrier model incorporates proxies for dynamic disorder through decoherence corrections, yielding predicted diffusion coefficient closer to what is expected from experiment and comparable with other organic-based electronic materials. Based on these simulations, we propose that the instantaneous fluctuations of the local electrostatic environment can transiently lift energy degeneracies and delocalize charge carriers. Furthermore, these studies reveal how incorporating dynamic fluctuations associated with the environment resolves the discrepancy between theory and experiment in microbial cytochrome wires and highlight design principles for bioinspired, heme-based conductive materials.

Bioinorganic chemistry↗

Volumetric Soil Moisture Measurements at the Teller 27 Site, Seward Peninsula, Alaska, 2022-2023

The Teller 27 watershed on the Seward Peninsula, Alaska, has been well characterized by the NGEE Arctic project. The study site is underlain by discontinuous permafrost that is thawing as the climate warms. As a result, the site is experiencing a short-term wetting trend as a perched water table above the remaining permafrost provides plant available water during the growing season. Soil moisture patterns drive microbial activity and plant species compositions including plant density and height. This study aimed to understand how soil moisture patterns were influenced by tundra microtopography. To accomplish this, we placed a strategic network of soil moisture sensors in micro-highs, micro-lows, and control areas under different vegetation types within the Teller 27 watershed from summer of 2022 through fall of 2023. This data was used in conjunction with other soil data from the Teller 27 watershed to gain a more comprehensive understanding of soil moisture patterns in a rapidly thawing discontinuous permafrost region. This dataset includes six *.csv files: four of time series soil moisture data, one of field soil moisture data, and one of site conditions. The dataset also includes one *.kml file of the watershed and the soil moisture sensor sites as well as this user guide to provide details on data collection and processing methods. NGEE Arctic Project Summary The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗