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DOE OSTI2016

Monoterpene ‘thermometer’ of tropical forest-atmosphere response to climate warming

Tropical forests absorb large amounts of atmospheric CO 2 through photosynthesis but elevated temperatures suppress this absorption and promote monoterpene emissions. Using 13 CO 2 labeling, in this paper we show that monoterpene emissions from tropical leaves derive from recent photosynthesis and demonstrate distinct temperature optima for five groups (Groups 1–5), potentially corresponding to different enzymatic temperature-dependent reaction mechanisms within β-ocimene synthases. As diurnal and seasonal leaf temperatures increased during the Amazonian 2015 El Niño event, leaf and landscape monoterpene emissions showed strong linear enrichments of β-ocimenes (+4.4% °C -1 ) at the expense of other monoterpene isomers. The observed inverse temperature response of α-pinene (-0.8% °C -1 ), typically assumed to be the dominant monoterpene with moderate reactivity, was not accurately simulated by current global emission models. Given that β-ocimenes are highly reactive with respect to both atmospheric and biological oxidants, the results suggest that highly reactive β-ocimenes may play important roles in the thermotolerance of photosynthesis by functioning as effective antioxidants within plants and as efficient atmospheric precursors of secondary organic aerosols. Monoterpene composition may represent a new sensitive ‘thermometer’ of leaf oxidative stress and atmospheric reactivity, and therefore a new tool in future studies of warming impacts on tropical biosphere-atmosphere carbon-cycle feedbacks.

13Co2 labeling↗

DOE OSTI2022

An automated workflow that generates atom mappings for large‐scale metabolic models and its application to Arabidopsis thaliana

SUMMARY Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large‐scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large‐scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana . We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating 15 N isotope enrichment and identifying nitrogen (N)‐containing metabolites which show enrichment patterns that are informative for flux estimation in future 15 N‐MFA studies of A. thaliana . The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph‐theoretic structural analyses with large‐scale metabolic networks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

SU-E-J-166: Sensitivity of Clinically Relevant Dosimetric Parameters to Contouring Uncertainty During Post Implant Dosimetry of Prostate Permanent Seed Implants

Purpose: There is a strong evidence relating post-implant dosimetry for permanent seed prostate brachytherpy to local control rates. The delineation of the prostate on CT images, however, represents a challenge as it is difficult to confidently identify the prostate borders from soft tissue surrounding it. This study aims at quantifying the sensitivity of clinically relevant dosimetric parameters to prostate contouring uncertainty. Methods: The post-implant CT images and plans for a cohort of 43 patients, who have received I–125 permanent prostate seed implant in our centre, were exported to MIM Symphony LDR brachytherapy treatment planning system (MIM Software Inc., Cleveland, OH). The prostate contours in post-implant CT images were expanded/contracted uniformly for margins of ±1.00mm, ±2.00mm, ±3.00mm, ±4.00mm and ±5.00mm (±0.01mm). The values for V100 and D90 were extracted from Dose Volume Histograms for each contour and compared. Results: The mean value of V100 and D90 was obtained as 92.3±8.4% and 108.4±12.3% respectively (Rx=145Gy). V100 was reduced by −3.2±1.5%, −7.2±3.0%, −12.8±4.0%, −19.0±4.8%, − 25.5±5.4% for expanded contours of prostate with margins of +1mm, +2mm, +3mm, +4mm, and +5mm, respectively, while it was increased by 1.6±1.2%, 2.4±2.4%, 2.7±3.2%, 2.9±4.2%, 2.9±5.1% for the contracted contours. D90 was reduced by −6.9±3.5%, −14.5±6.1%, −23.8±7.1%, − 33.6±8.5%, −40.6±8.7% and increased by 4.1±2.6%, 6.1±5.0%, 7.2±5.7%, 8.1±7.3% and 8.1±7.3% for the same set of contours. Conclusion: Systematic expansion errors of more than 1mm may likely render a plan sub-optimal. Conversely contraction errors may Result in labeling a plan likely as optimal. The use of MRI images to contour the prostate should results in better delineation of prostate organ which increases the predictive value of post-op plans. Since observers tend to overestimate the prostate volume on CT, compared with MRI, the impact of the contouring uncertainty on V100 and D90 fortunately, has a conservative effect of underestimating the prostate coverage.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Research Projects for Interrogations of Biological Systems: Training for the Development of Novel Radiotracers

This grant was situated at the University of Missouri to train Ph.D. scientists in radiochemistry and synthetic chemistry in conjunction with Faculty from the Interdisciplinary Plant Group, Division of Biological Sciences, the MU Research Reactor Center, Molecular Biology and the Radiopharmaceutical Sciences Institute. This project was collaborative with Brookhaven National Laboratory (Richard Ferrieri, PI). Projects for the Ph.D. candidates included novel probe development for peptides, nucleosides, small molecules or radiometals, the direct use of radiometals as probes, or nuclear techniques for analysis. The projects for the postdoctoral fellow involved synthetic chemistry for the preparation of precursors for novel tracers that will be radiolabeled with 18 F or other appropriate radionuclides. The skill sets of our team members allowed us to prepare probes with positron or single photon emitters, as well as ones that are dual-labeled (fluorescent and radiolabeled). We focused our technical advances to those that will be broadly applicable to any research field.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2016

Targeted Therapy for Melanoma

The research project, entitled ”Targeted Therapy for Melanoma,” was focused on investigating the use of kidney protection measures to lower the non-specific kidney uptake of the radiolabeled Pb-DOTA-ReCCMSH peptide. Previous published work demonstrated that the kidney exhibited the highest non-target tissue uptake of the 212Pb/203 Pb radiolabeled melanoma targeting peptide DOTA-ReCCMSH. The radiolabeled alpha-melanocyte stimulating hormone (α-MSH) peptide analog DOTA-Re(Arg 11 )CCMSH, which binds the melanocortin-1 receptor over-expressed on melanoma tumor cells, has shown promise as a PRRT agent in pre-clinical studies. High tumor uptake of 212 Pb labeled DOTA-Re(Arg 11 )CCMSH resulted in tumor reduction or eradication in melanoma therapy studies. Of particular note was the 20-50% cure rate observed when melanoma mice were treated with alpha particle emitter 212 Pb. However, as with most PRRT agents, high radiation doses to the kidneys where observed. To optimize tumor treatment efficacy and reduce nephrotoxicity, the tumor to kidney uptake ratio must be improved. Strategies to reduce kidney retention of the radiolabeled peptide, while not effecting tumor uptake and retention, can be broken into several categories including modification of the targeting peptide sequence and reducing proximal tubule reabsorption.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

SISGR: Room Temperature Single-Molecule Detection and Imaging by Stimulated Emission Microscopy

Single-molecule spectroscopy has made considerable impact on many disciplines including chemistry, physics, and biology. To date, most single-molecule spectroscopy work is accomplished by detecting fluorescence. On the other hand, many naturally occurring chromophores, such as retinal, hemoglobin and cytochromes, do not have detectable fluorescence. There is an emerging need for single-molecule spectroscopy techniques that do not require fluorescence. In the last proposal period, we have successfully demonstrated stimulated emission microscopy, single molecule absorption, and stimulated Raman microscopy based on a high-frequency modulation transfer technique. These first-of-a- kind new spectroscopy/microscopy methods tremendously improved our ability to observe molecules that fluorescence weakly, even to the limit of single molecule detection for absorption measurement. All of these methods employ two laser beams: one (pump beam) excites a single molecule to a real or virtual excited state, and the other (probe beam) monitors the absorption/emission property of the single. We extract the intensity change of the probe beam with high sensitivity by implementing a high-frequency phase-sensitive detection scheme, which offers orders of magnitude improvement in detection sensitivity over direct absorption/emission measurement. However, single molecule detection based on fluorescence or absorption is fundamentally limited due to their broad spectral response. It is important to explore other avenues in single molecule detection and imaging which provides higher molecular specificity for studying a wide variety of heterogeneous chemical and biological systems. This proposal aimed to achieve single-molecule detection sensitivity with near resonance stimulated Raman scattering (SRS) microscopy. SRS microscopy was developed in our lab as a powerful technique for imaging heterogeneous samples based on their intrinsic vibrational contrasts, which provides much higher molecular specificity than absorption and fluorescence. Current sensitivity limit of SRS microscopy has not yet reached single molecule detection. We proposed to capitalize on our state-of-the-art SRS microscopy and develop near-resonance enhanced SRS for single molecule detection of carotenoids and heme proteins. The specific aims we pursued are: (1) building the next SRS generation microscope that utilizes near resonance enhancement to allow detection and imaging of single molecules with undetectable fluorescence, such as -carotene. (2) using near-resonance SRS as a contrast mechanism to study dye-sensitize semiconductor interface, elucidating the heterogeneous electron ejection kinetics with high spatial and temporal resolution. (3) studying the binding and unbinding of oxygen in single hemoglobin molecules in order to gain molecular level understanding of the long-standing issue of cooperativity. The new methods developed in the fund period of this grant have advanced the detection sensitivity in many aspects. Near-resonance SRS improved the signal by using shorter wavelengths for SRS microscopy. Frequency modulation and multi-color SRS target the reduction of background to improve the chemical specificity of SRS while maintaining the high imaging speed. Time-domain coherent Raman scattering microscopy targets to reduce the noise floor of coherent Raman microscopy. These methods have already demonstrated first-of-a-kind new applications in biology and medical research. However, we are still one order of magnitude away from single molecule limit. It is important to continue to improve the laser specification and develop new imaging methods to finally achieve label-free single molecule microscopy.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Hyperspectral Light Sheet Raman Imaging of Leaf Metabolism (Final Report)

This final technical report details the accomplishment and findings of a project that developed technology related to imaging metabolic processes in plants. The report gives technical details of the design, construction and characterization of a Raman microscope system capable of identifying chemical species using the wavelength shifts of scattered excitation light. Some of the unique aspects of the design include: use of a Bessel beam excitation source, which allow long excitation lines that are resistant to scattering in complex media such as plants; excitation at 785 nm to avoid fluorescence emission that can occur in photosynthetic organisms; and a flat optical design that makes construction and alignment significantly simpler. This project also used stable isotope labeling to look at photorespiratory flux in the leaves of three different types of plants that have different photosynthesis pathways. Gas chromatography–mass spectrometry was used to look at which metabolites and amino acids had altered oxygen, carbon and hydrogen uptake under various conditions of environmental oxygen. This generated a rich data set that is being further analyzed to understand metabolic pathways in plants. This project also used the natural fluorescence in sorghum and rice to conduct an extensive experiment across different developmental stages. Spectral differences were identified at most of the developmental stages and these can be attributed to differential pigment and pigment-protein complexes present in different relative abundances as the plant develops.

09 BIOMASS FUELS↗

DOE OSTI2024

Human Host Cellular Response to HCoV-229E Infection Proteomics (ACS-JM-DP2)

The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock and infected immortalized human lung epithelial cells (A549) (MOI 5) nuclear extracts, immortalized human lung fibroblasts cells (MRC5) (MOI5) nuclear extracts, and primary human airway epithelial (HAE) (MOI 3) cells from lung tissue and processed for proteome analysis. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files and supporting metadata materials. Experimental proteomics samples were prepared using Limited Proteolysis (LiP) methods for Label-free quantification (LFQ) and global proteomic evaluation. Sample data was acquired using a Q-Exactive HF-X mass spectrometer and was processed and compiled using MaxQuant software (v.1.6.17.0). Processed proteomic data downloads include a sample naming key, processed MaxQuant results/parameters, and protein annotated relative abundance files. See corresponding primary data accessions below and Viral Experiment LiP Analysis source code supporting data transparency and reuse. Experimental transcriptomics samples were collected in parallel and processed for RNA sequencing (RNA-Seq) as summarized under ACS-DP1 (https://data.pnnl.gov/group/nodes/dataset/34069).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

BUTTER - Empirical Deep Learning Dataset

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four learning rates, six minibatch sizes, four levels of label noise, and fourteen levels of L1 and L2 regularization each. Multiple repetitions (typically 30, sometimes 10) of each combination of hyperparameters were preformed, and statistics including training and test loss (using a 80% / 20% shuffled train-test split) are recorded at the end of each training epoch. In total, this dataset covers 178 thousand distinct hyperparameter settings ("experiments"), 3.55 million individual training runs (an average of 20 repetitions of each experiments), and a total of 13.3 billion training epochs (three thousand epochs were covered by most runs). Accumulating this dataset consumed 5,448.4 CPU core-years, 17.8 GPU-years, and 111.2 node-years.

Array↗

DOE OSTI2017

Vibrational spectroscopy for imaging single microbial cells in complex biological samples

Here, vibrational spectroscopy is increasingly used for the rapid and non-destructive imaging of environmental and medical samples. Both Raman and Fourier-transform infrared (FT-IR) imaging have been applied to obtain detailed information on the chemical composition of biological materials, ranging from single microbial cells to tissues. Due to its compatibility with methods such as stable isotope labeling for the monitoring of cellular activities, vibrational spectroscopy also holds considerable power as a tool in microbial ecology. Chemical imaging of undisturbed biological systems (such as live cells in their native habitats) presents unique challenges due to the physical and chemical complexity of the samples, potential for spectral interference, and frequent need for real-time measurements. This Mini Review provides a critical synthesis of recent applications of Raman and FT-IR spectroscopy for characterizing complex biological samples, with a focus on developments in single-cell imaging. We also discuss how new spectroscopic methods could be used to overcome current limitations of singlecell analyses. Given the inherent complementarity of Raman and FT-IR spectroscopic methods, we discuss how combining these approaches could enable us to obtain new insights into biological activities either in situ or under conditions that simulate selected properties of the natural environment.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

The Role of Mass Spectrometry in Structural Studies of Flavin-Based Electron Bifurcating Enzymes

For decades, biologists and biochemists have taken advantage of atomic resolution structural models of proteins from X-ray crystallography, nuclear magnetic resonance spectroscopy, and more recently cryo-electron microscopy. However, not all proteins relent to structural analyses using these approaches, and as the depth of knowledge increases, additional data elucidating a mechanistic understanding of protein function is desired. Flavin-based electron bifurcating enzymes, which are responsible for producing high energy compounds through the simultaneous endergonic and exergonic reduction of two intercellular electron carriers (i.e., NAD + and ferredoxin) are one class of proteins that have challenged structural biologists and in which there is great interest to understand the mechanism behind electron gating. A limited number of X-ray crystallography projects have been successful; however, it is clear that to understand how these enzymes function, techniques that can reveal detailed in solution information about protein structure, dynamics, and interactions involved in the bifurcating reaction are needed. In this review, we cover a general set of mass spectrometry-based techniques that, combined with protein modeling, are capable of providing information on both protein structure and dynamics. Techniques discussed include surface labeling, covalent cross-linking, native mass spectrometry, and hydrogen/deuterium exchange. We cover how biophysical data can be used to validate computationally generated protein models and develop mechanistic explanations for regulation and performance of enzymes and protein complexes. Our focus will be on flavin-based electron bifurcating enzymes, but the broad applicability of the techniques will be showcased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

EMUlator: An Elementary Metabolite Unit (EMU) Based Isotope Simulator Enabled by Adjacency Matrix

Stable isotope based metabolic flux analysis is currently the unique methodology that allows the experimental study of the integrated responses of metabolic networks. This method primarily relies on isotope labeling and modeling, which could be a challenge in both experimental and computational biology. Specifically, the algorithm implementation for isotope simulation is a critical step, limiting extensive usage of this powerful approach. In this work, we introduce EMUlator a Python-based isotope simulator which is developed on Elementary Metabolite Unit (EMU) algorithm, an efficient and powerful algorithm for isotope modeling. We propose a novel adjacency matrix method to implement EMU modeling and exemplify it stepwise. This method is intuitively straightforward and can be conveniently mastered for various customized purposes. We apply this arithmetic pipeline to understand the phosphoketolase flux in the metabolic network of an industrial microbe Clostridium acetobutylicum . The resulting design enables a high-throughput and non-invasive approach for estimating phosphoketolase flux in vivo . Our computational insights allow the systematic design and prediction of isotope-based metabolic models and yield a comprehensive understanding of their limitations and potentials.

09 BIOMASS FUELS↗

DOE OSTI2022

Small-Angle Neutron Scattering for Studying Lipid Bilayer Membranes

Small-angle neutron scattering (SANS) is a powerful tool for studying biological membranes and model lipid bilayer membranes. The length scales probed by SANS, being from 1 nm to over 100 nm, are well-matched to the relevant length scales of the bilayer, particularly when it is in the form of a vesicle. However, it is the ability of SANS to differentiate between isotopes of hydrogen as well as the availability of deuterium labeled lipids that truly enable SANS to reveal details of membranes that are not accessible with the use of other techniques, such as small-angle X-ray scattering. In this work, an overview of the use of SANS for studying unilamellar lipid bilayer vesicles is presented. The technique is briefly presented, and the power of selective deuteration and contrast variation methods is discussed. Approaches to modeling SANS data from unilamellar lipid bilayer vesicles are presented. Finally, recent examples are discussed. While the emphasis is on studies of unilamellar vesicles, examples of the use of SANS to study intact cells are also presented.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Pentose Phosphate Pathway Reactions in Photosynthesizing Cells

The pentose phosphate pathway (PPP) is divided into an oxidative branch that makes pentose phosphates and a non-oxidative branch that consumes pentose phosphates, though the non-oxidative branch is considered reversible. A modified version of the non-oxidative branch is a critical component of the Calvin–Benson cycle that converts CO2 into sugar. The reaction sequence in the Calvin–Benson cycle is from triose phosphates to pentose phosphates, the opposite of the typical direction of the non-oxidative PPP. The photosynthetic direction is favored by replacing the transaldolase step of the normal non-oxidative PPP with a second aldolase reaction plus sedoheptulose-1,7-bisphosphatase. This can be considered an anabolic version of the non-oxidative PPP and is found in a few situations other than photosynthesis. In addition to the strong association of the non-oxidative PPP with photosynthesis metabolism, there is recent evidence that the oxidative PPP reactions are also important in photosynthesizing cells. These reactions can form a shunt around the non-oxidative PPP section of the Calvin–Benson cycle, consuming three ATP per glucose 6-phosphate consumed. A constitutive operation of this shunt occurs in the cytosol and gives rise to an unusual labeling pattern of photosynthetic metabolites while an inducible shunt in the stroma may occur in response to stress.

13C↗

DOE OSTI2020

Ultrastructural Location and Interactions of the Immunoglobulin Receptor Binding Sequence within Fibrillar Type I Collagen

Collagen type I is a major constituent of animal bodies. It is found in large quantities in tendon, bone, skin, cartilage, blood vessels, bronchi, and the lung interstitium. It is also produced and accumulates in large amounts in response to certain inflammations such as lung fibrosis. Our understanding of the molecular organization of fibrillar collagen and cellular interaction motifs, such as those involved with immune-associated molecules, continues to be refined. In this study, antibodies raised against type I collagen were used to label intact D-periodic type I collagen fibrils and observed with atomic force microscopy (AFM), and X-ray diffraction (XRD) and immunolabeling positions were observed with both methods. The antibodies bind close to the C-terminal telopeptide which verifies the location and accessibility of both the major histocompatibility complex (MHC) class I (MHCI) binding domain and C-terminal telopeptide on the outside of the collagen fibril. The close proximity of the C-telopeptide and the MHC1 domain of type I collagen to fibronectin, discoidin domain receptor (DDR), and collagenase cleavage domains likely facilitate the interaction of ligands and receptors related to cellular immunity and the collagen-based Extracellular Matrix.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Photosynthetic Co-production of Succinate and Ethylene in a Fast-Growing Cyanobacterium, Synechococcus elongatus PCC 11801

Cyanobacteria are emerging as hosts for photoautotrophic production of chemicals. Recent studies have attempted to stretch the limits of photosynthetic production, typically focusing on one product at a time, possibly to minimise the additional burden of product separation. Here, we explore the simultaneous production of two products that can be easily separated: ethylene, a gaseous product, and succinate, an organic acid that accumulates in the culture medium. This was achieved by expressing a single copy of the ethylene forming enzyme (efe) under the control of P cpcB , the inducer-free super-strong promoter of phycocyanin β subunit. We chose the recently reported, fast-growing and robust cyanobacterium, Synechococcus elongatus PCC 11801, as the host strain. A stable recombinant strain was constructed using CRISPR-Cpf1 in a first report of markerless genome editing of this cyanobacterium. Under photoautotrophic conditions, the recombinant strain shows specific productivities of 338.26 and 1044.18 μmole/g dry cell weight/h for ethylene and succinate, respectively. These results compare favourably with the reported productivities for individual products in cyanobacteria that are highly engineered. Metabolome profiling and 13 C labelling studies indicate carbon flux redistribution and suggest avenues for further improvement. Our results show that S. elongatus PCC 11801 is a promising candidate for metabolic engineering.

13C isotopic labelling↗

DOE OSTI2024

Characterization of Incremental Markings in the Sagittal Otolith of the Pacific Sardine ( Sardinops sagax ) Using Different Imaging Modalities

Teleost fish possess calcium carbonate otoliths located in separate chambers (utriculus, sacculus, and lagena) of their membranous labyrinth. This study analyzed the surface topography of the sagittal otolith of the Pacific sardine (Sardinops sagax) and the daily and annual increments in these otoliths. The otolith surface, characterized by laser scanning confocal microscopy for the first time, consisted of a system of prominent ridges and valleys (grooves), but it is unclear whether these structures are functional or represent time-resolving markings reflecting growth periodicity. Within the first-year volume, daily increments, each consisting of an incremental (more mineralized) and a discontinuous (less mineralized) zone, were resolved by optical microscopy and backscattered electron (BSE) imaging in the scanning electron microscope (SEM). Daily growth increments could, however, not be resolved in volumes formed after the first year, presumably because otolith growth markedly slows down and spacing of incremental markings narrows in older fish. Throughout otolith growth, the crystalline network continues across the discontinuous zones. Fluorochrome labeling provides additional information on growth after the first year. Compared with optical and BSE imaging, synchrotron microComputed Tomography of intact otoliths (with 0.69 µm volume elements) was less able to resolve daily increments; X-ray phase contrast reconstructions provided more detail than reconstructions with absorption contrast. Future research directions are proposed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Results of Experimental Additions of Organic Nitrogen on Soil Organic Matter Decomposition, Teller Road Site, Seward Peninsula, 2017 and 2018

This dataset provides the results of the experimental addition of glutamic acid on anaerobic organic matter decomposition as measured in the field and through laboratory methods. Field experiments were conducted during the summers of 2017 and 2018 at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) near Intensive Site 9 (TL_IS_9). At the field site, a solution of glutamate (13C- and 15N-labeled glutamate in 2017, unlabeled in 2018) was injected belowground and investigators observed the resulting changes in downslope porewater geochemistry and dissolved greenhouse gas concentrations. Soil collected near the site in 2017 was used in a laboratory column flow-through experiment with added glutamate. Results of porewater geochemistry, dissolved greenhouse gasses, and organic matter composition analyses for 2017 and 2018 experiments are provided. There are six *.csv data files and one *.pdf user guide.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↗