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DOE OSTI2019

Divergent methyl-coenzyme M reductase genes in a deep-subseafloor Archaeoglobi

Abstract The methyl-coenzyme M reductase (MCR) complex is a key enzyme in archaeal methane generation and has recently been proposed to also be involved in the oxidation of short-chain hydrocarbons including methane, butane, and potentially propane. The number of archaeal clades encoding the MCR continues to grow, suggesting that this complex was inherited from an ancient ancestor, or has undergone extensive horizontal gene transfer. Expanding the representation of MCR-encoding lineages through metagenomic approaches will help resolve the evolutionary history of this complex. Here, a near-complete Archaeoglobi metagenome-assembled genome (MAG; Ca. Polytropus marinifundus gen. nov. sp. nov.) was recovered from the deep subseafloor along the Juan de Fuca Ridge flank that encodes two divergent McrABG operons similar to those found in Ca. Bathyarchaeota and Ca. Syntrophoarchaeum MAGs. Ca. P. marinifundus is basal to members of the class Archaeoglobi, and encodes the genes for β-oxidation, potentially allowing an alkanotrophic metabolism similar to that proposed for Ca. Syntrophoarchaeum. Ca. P. marinifundus also encodes a respiratory electron transport chain that can potentially utilize nitrate, iron, and sulfur compounds as electron acceptors. Phylogenetic analysis suggests that the Ca. P. marinifundus MCR operons were horizontally transferred, changing our understanding of the evolution and distribution of this complex in the Archaea.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Enzymatic reconstitution of ribosomal peptide backbone thioamidation

Methyl-coenzyme M reductase (MCR) is an essential enzyme found strictly in methanogenic and methanotrophic archaea. MCR catalyzes a reversible reaction involved in the production and consumption of the potent greenhouse gas methane. The α-subunit of this enzyme (McrA) contains several unusual posttranslational modifications, including the only known naturally occurring example of protein thioamidation. We have recently demonstrated by genetic deletion and mass spectrometry that the tfuA and ycaO genes of Methanosarcina acetivorans are involved in thioamidation of Gly465 in the MCR active site. Modification to thioGly has been postulated to stabilize the active site structure of MCR. Herein, we report the in vitro reconstitution of ribosomal peptide thioamidation using heterologously expressed and purified YcaO and TfuA proteins from M. acetivorans . Like other reported YcaO proteins, this reaction is ATP-dependent but requires an external sulfide source. We also reconstitute the thioamidation activity of two TfuA-independent YcaOs from the hyperthermophilic methanogenic archaea Methanopyrus kandleri and Methanocaldococcus jannaschii . Using these proteins, we demonstrate the basis for substrate recognition and regioselectivity of thioamide formation based on extensive mutagenesis, biochemical, and binding studies. Finally, we report nucleotide-free and nucleotide-bound crystal structures for the YcaO proteins from M. kandleri . Sequence and structure-guided mutagenesis with subsequent biochemical evaluation have allowed us to assign roles for residues involved in thioamidation and confirm that the reaction proceeds via backbone O -phosphorylation. We conclude these data assign a new biochemical reaction to the YcaO superfamily and paves the way for further characterization of additional peptide backbone posttranslational modifications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Ecology of methyl-coenzyme M reductase encoding Thermoproteota

The recent demonstration that members of at least three classes of archaea affiliated with the Thermoproteota superphylum are involved in the production of the climate-active gas methane has sparked discussions about how well we understand the diversity of methanogens. Here, in this work, we show that members of all three of these lineages, as well as several other, yet uncultured and physiologically uncharacterized groups within the Thermoproteota that encode the key enzyme of anaerobic methane cycling, methyl-coenzyme M reductase (MCR), are widely distributed in anoxic ecosystems. We postulate that the taxonomic, metabolic, and ecological diversity of methanogenic and MCR-encoding Thermoproteota are poorly understood, and that the contribution of methylotrophic and thermoproteotal methanogenesis to methane production is largely unknown. We hypothesize that thermoproteotal methanogens could contribute, potentially substantially, to methane emissions in many anoxic environments that harbor methylated precursors, including wetlands, sediments, peat, rice paddies, wastewater sludge, and geothermal systems. We highlight the necessity to experimentally test the (eco)physiology of these widely distributed archaea using both culture-dependent ( in vitro ) and culture-independent ( in situ ) approaches to assess their potential contribution to methane emissions. Last, we stress the importance of remaining agnostic about the physiology of MCR-encoding Thermoproteota in the absence of experimental data because most of these archaea also carry the genetic potential to grow non-methanogenically.

MCR↗

DOE OSTI2020

Genomic and Transcriptomic Evidence Supports Methane Metabolism in Archaeoglobi

Euryarchaeal lineages have been believed to have a methanogenic last common ancestor. However, members of euryarchaeal Archaeoglobi have long been considered nonmethanogenic and their evolutionary history remains elusive. Here, three high-quality metagenomic-assembled genomes (MAGs) retrieved from high-temperature oil reservoir and hot springs, together with three newly assembled Archaeoglobi MAGs from previously reported hot spring metagenomes, are demonstrated to represent a novel genus of Archaeoglobaceae, “Candidatus Methanomixophus.” All “Ca. Methanomixophus” MAGs encode an M methyltransferase (MTR) complex and a traditional type of methyl-coenzyme M reductase (MCR) complex, which is different from the divergent MCR complexes found in “Ca. Polytropus marinifundus.” In addition, “Ca. Methanomixophus dualitatem” MAGs preserve the genomic capacity for dissimilatory sulfate reduction. Comparative phylogenetic analysis supports a laterally transferred origin for an MCR complex and vertical heritage of the MTR complex in this lineage. Metatranscriptomic analysis revealed concomitant in situ activity of hydrogen-dependent methylotrophic methanogenesis and heterotrophic fermentation within populations of “Ca. Methanomixophus hydrogenotrophicum” in a high-temperature oil reservoir.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The crystal structure of methanogen McrD , a methyl‐coenzyme M reductase‐associated protein

Methyl‐coenzyme M reductase (MCR) is a multi‐subunit (α 2 β 2 γ 2 ) enzyme responsible for methane formation via its unique F 430 cofactor. The genes responsible for producing MCR ( mcrA , mcrB and mcrG ) are typically colocated with two other highly conserved genes mcrC and mcrD . We present here the high‐resolution crystal structure for McrD from a human gut methanogen Methanomassiliicoccus luminyensis strain B10. The structure reveals that McrD comprises a ferredoxin‐like domain assembled into an α + β barrel‐like dimer with conformational flexibility exhibited by a functional loop. The description of the M. luminyensis McrD crystal structure contributes to our understanding of this key conserved methanogen protein typically responsible for promoting MCR activity and the production of methane, a greenhouse gas.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Preparation of coenzyme F430 biosynthetic enzymes and intermediates

Methyl-coenzyme M reductase (MCR) is the key enzyme in pathways for the formation and anaerobic oxidation of methane. As methane is a potent greenhouse gas and biofuel, investigations of MCR catalysis and maturation are of interest for the development of both methanogenesis inhibitors and natural gas conversion strategies. Here, the activity of MCR is dependent on a unique, nickel-containing coenzyme F430, the most highly reduced tetrapyrrole found in nature. Coenzyme F430 is biosynthesized from sirohydrochlorin in four steps catalyzed by the CfbABCDE enzymes. Here, methods for the expression and purification of the coenzyme F430 biosynthesis enzymes are described along with conditions for the synthesis and purification of biosynthetic intermediates on the milligram scale from commercially available porphobilinogen.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Interpreting mixing relationships in energetic melts to estimate vapor contribution and composition

Heterogeneous, glassy debris can be produced by energetic events such as near surface nuclear explosions and asteroid impacts. In these events, the resultant debris comprises a rapidly-cooled mixture of the projectile or bomb material with proximate materials such as soil and anthropogenic structures. Glasses formed in these events preserve inter and/or intra sample compositional variation reflecting complex mixtures of the precursor materials or their chemically fractionated products. Understanding formation mechanisms and chemical processes relating to energetic glass formation based on study of the end products requires an objective method for calculating the precursor components that mixed together to produce the final product. Here, we compare a set of multivariate linear-least squares approaches to address the unmixing problem of heterogeneous glasses including classical least squares (CLS), principal component analysis (PCA) and two multivariate curve resolution – alternating least squares (MCR-ALS) approaches. We generate a synthetic data set representing spatially resolved, compositional data in a set of heterogeneously mixed glasses to understand model sensitivity to precursor abundance and composition. We explore the impact of incomplete knowledge of the system prior to the formation of the melts on the resulting confidence and accuracy of the solution (i.e., the number, composition, and abundances of the precursor materials). We conclude that a closure and equality constrained MCR-ALS approach succeeds in identifying unrecognized precursor components and is a suitable alternative to CLS approaches when the investigator has incomplete knowledge of the starting precursor chemical compositions. Finally, we demonstrate application of this MCR-ALS approach to measurements of Trinitite.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2018

Microstructural Materials Design Via Deep Adversarial Learning Methodology

Identifying the key microstructure representations is crucial for computational materials design (CMD). However, existing microstructure characterization and reconstruction (MCR) techniques have limitations to be applied for microstructural materials design. Some MCR approaches are not applicable for microstructural materials design because no parameters are available to serve as design variables, while others introduce significant information loss in either microstructure representation and/or dimensionality reduction. In this work, we present a deep adversarial learning methodology that overcomes the limitations of existing MCR techniques. In the proposed methodology, generative adversarial networks (GAN) are trained to learn the mapping between latent variables and microstructures. Thereafter, the low-dimensional latent variables serve as design variables, and a Bayesian optimization framework is applied to obtain microstructures with desired material property. Due to the special design of the network architecture, the proposed methodology is able to identify the latent (design) variables with desired dimensionality, as well as capturing complex material microstructural characteristics. The validity of the proposed methodology is tested numerically on a synthetic microstructure dataset and its effectiveness for microstructural materials design is evaluated through a case study of optimizing optical performance for energy absorption. Additional features, such as scalability and transferability, are also demonstrated in this work. In essence, the proposed methodology provides an end-to-end solution for microstructural materials design, in which GAN reduces information loss and preserves more microstructural characteristics, and the GP-Hedge optimization improves the efficiency of design exploration.

Engineering↗

DOE OSTI2018

Assembly of Methyl Coenzyme M Reductase in the Methanogenic Archaeon Methanococcus maripaludis

Methyl coenzyme M reductase (MCR) is a complex enzyme that catalyzes the final step in biological methanogenesis. To better understand its assembly, the recombinant MCR from the thermophile Methanothermococcus okinawensis (rMCRok) was expressed in the mesophile Methanococcus maripaludis. The rMCRok was posttranslationally modified correctly and contained McrD and the unique nickel tetrapyrrole coenzyme F 430 . Subunits of the native M. maripaludis (MCRmar) were largely absent, suggesting that the recombinant enzyme was formed by an assembly of cotranscribed subunits. Strong support for this hypothesis was obtained by expressing a chimeric operon comprising the His-tagged mcrA from M. maripaludis and the mcrBDCG from M. okinawensis in M. maripaludis. The His-tagged purified rMCR then contained the M. maripaludis McrA and the M. okinawensis McrBDG. The present study prompted us to form a working model for MCR assembly, which can be further tested by the heterologous expression system established here.

03 NATURAL GAS↗

DOE OSTI2022

Demonstration and Evaluation of the Human-Technology Integration Function Allocation Methodology

There is an imminent need for the existing nuclear power plants to reduce their operating and maintenance (O&M) costs to remain economically viable. Digital technology, including automation, provides a significant opportunity for the existing nuclear power plant fleet to transform the way in which work is accomplished, reducing O&M costs, and allowing the fleet to remain economically competitive. One notable opportunity to significantly reduce O&M costs pertains to modifications to the plant equipment and main control room (MCR). Existing instrumentation and control (I&C) technologies in the MCR are highly analog, costly to operate and maintain, and demand a high cognitive and physical workload from plant staff (i.e., operators). Digitalizing the MCR has a range of broad economic benefits, including improved plant performance and reduced manual work. Further, digital I&C systems can fundamentally change the way in which plant staff operate the plant; this is the concept of operation. Human-technology integration is important to ensure that impacts to the concept of operation are done in a way that account for capabilities of people and technology. Human-technology integration employs human factors engineering (HFE) methods and principles to maximize the benefits of digital technology, reducing human error, improving overall decision-making and usability. The U.S. Department of Energy Light Water Reactor Sustainability Program is applying human-technology integration research to ensure digital technologies are safe, reliable, and efficient. This paper documents the demonstration of the human-technology guidance developed by the Light Water Reactor Sustainability Program from a first-of-a-kind digital I&C upgrade, specifically addressing function analysis and allocation for a new digital I&C system that included changes in automation levels. The program’s specific approach is included in this work, following lessons learned. This document serves as a resource for industry to follow in applying human-technology integration and HFE to digital modifications, specific to function analysis and allocation. The lessons learned should be considered in the planning and execution of HFE activities that support such digital modifications.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Review of Reactor Facilities without Main Control Rooms

Small, advanced reactors may require few, if any, safety-related human actions (HAs) and fewer HAs to monitor and control the plant. In comparison to large light water reactors, these are significant changes that have implications for many aspects of an applicant's human factors engineering (HFE), including control room design, plant staffing, and the management of safety functions. To support the Nuclear Regulatory Commission's (NRC) ability to evaluate these changes, information needs to be developed addressing the characteristics and potential issues. The objectives of our research were to (1) identify when a traditional main control room (MCR) may not be necessary, (2) identify workplace design alternatives to traditional MCRs, and (3) develop guidance for reviewing an applicant's workplace designs with and without a MCR. We determined that the safety question isn't so much justifying why a design has no MCR, but rather verifying that important human actions can be accurately and reliably performed under a range of challenging conditions using the HSIs provided regardless of their location. We developed guidance to review alternatives to MCRs based on HFE analyses for determining workplace location and design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Identification of Metal Stresses in Arabidopsis thaliana Using Hyperspectral Reflectance Imaging

Industrial accidents, such as the Fukushima and Chernobyl disasters, release harmful chemicals into the environment, covering large geographical areas. Natural flora may serve as biological sensors for detecting metal contamination, such as cesium. Spectral detection of plant stresses typically employs a few select wavelengths and often cannot distinguish between different stress phenotypes. In this study, we apply hyperspectral reflectance imaging in the visible and near-infrared along with multivariate curve resolution (MCR) analysis to identify unique spectral signatures of three stresses in Arabidopsis thaliana : salt, copper, and cesium. While all stress conditions result in common stress physiology, hyperspectral reflectance imaging and MCR analysis produced unique spectral signatures that enabled classification of each stress. As the level of potassium was previously shown to affect cesium stress in plants, the response of A. thaliana to cesium stress under variable levels of potassium was also investigated. Increased levels of potassium reduced the spectral response of A. thaliana to cesium and prevented changes to chloroplast cellular organization. While metal stress mechanisms may vary under different environmental conditions, this study demonstrates that hyperspectral reflectance imaging with MCR analysis can distinguish metal stress phenotypes, providing the potential to detect metal contamination across large geographical areas.

multivariate curve resolution↗

NASA NTRS1985

Quality of remote sensing measurements of cloud physical parameters in the cooperative convective precipitation experiment

In order to develop the remote sensing techniques to infer cloud physical parameters, a multispectral cloud radiometer (MCR) was mounted on a NASA high-altitude aircraft in conjunction with the Cooperative Convective Precipitation Experiment in 1981. The MCR has seven spectral channels, of which three are centered near windows associated with water vapor bands in the near infrared, two are centered near the oxygen A band at 0.76 microns, one is centered at the 1.14-micron water vapor band, and one is centered in the thermal infrared. The reflectance and temperature measured on May 31, 1981, are presented together with theoretical calculations. The results indicate that the MCR produces quality measurements. Therefore several cloud parameters can be derived with good accuracy. The parameters are the cloud-scaled optical thickness, cloud top pressure, volume scattering coefficient, particle thermodynamic phase, effective mean particle size, and cloud-top temperature.

Wu, M.-L.↗

NASA NTRS2007

New and Improved T-wave Morphology Parameters to Differentiate Healthy Individuals from those with Cardiomyopathy and Coronary Artery Disease

We investigated the ability of several known as well as new ECG repolarization parameters to differentiate healthy individuals from patients with obstructive coronary artery disease (CAD) and cardiomyopathy (CM). Advanced high-fidelity 12-lead ECG tests (approx. 5-min supine) were first performed on a "training set" of 99 individuals: 33 with ischemic or dilated CM and low ejection fraction (EF less than 40%); 33 with catheterization-proven obstructive CAD but normal EF; and 33 age-/gender-matched healthy controls. The following multiple parameters of T-wave morphology (TWM) were derived via signal averaging and singular value decomposition (SVD, which yields 8 eigenvalues, rho(sub 1) greater than rho(sub 2)...greater than rho(sub 8) and studied for their retrospective accuracy in detecting underlying disease: 1) Principal component analysis ratio of the T wave (T-PCA) = 100*rho(sub 2)/rho(sub 1); 2) Relative T-wave residuum (rTWR) = 100* SIGMA (rho(sub 4)(sup 2) +...+ rho(sub 8)(sup 2)); 3) Modified complexity ratio of the T wave (T-mCR) = 100*SIGMA(rho(sub 3)(sup 2) +...+rho(sb 8) (sup 2)); and 4) Normalized 3-dimensional volume of the T wave (nTV) = 100*(rho(sub 2)*rho(sub 3)/rho(sub 1)(sup 2). All TWM parameters significantly differentiated CAD from controls (p less than 0.0001), and also CM from controls (p less than 0.0001). Retrospective areas under the ROC curve were 0.77, 0.81, 0.82, and 0.83 (CAD vs. controls) and 0.93, 0.89, 0.95 and 0.96 (CM vs. controls) for T-PCA, rTWR, T-mCR and nTV respectively. The newer TWM parameters (T-mCR and nTV) thus outperformed the more established parameters (T-PCA and rTWR), presumably by putting a greater emphasis on the third T-wave eigenvalue, which in most healthy subjects has little energy compared to the first two eigenvalues. Subsequent prospective analyses have also yielded similar results, such that we conclude that diagnostic differentiation of pathology from non-pathology may be especially aided by detecting the transference of energy from the first and second T-wave eigenvalues into the third T-wave eigenvalue.

Greco, E. C.↗

DOE OSTI2019

XAFS studies on battery materials: Data analysis supported by a chemometric approach

The large amount of data collected during a typical operando X-ray absorption fine structure (XAFS) experiment and the interest to thoroughly investigate and comprehend a redox process occurring in a Li-ion battery need an advanced data analysis approach. In this context, multivariate curve resolution (MCR) has gained attention as chemometric technique that allows the identification of the number of the species and their existence range without any a priori information on the studied system. Herein the call for an advanced data treatment is answered by a joint XAFS-MCR approach, able to unveil the local structural dynamics of the selected species, providing a quick and efficient data interpretation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Quantification of Coexisting Inner- and Outer-Sphere Complexation of Sulfate on Hematite Surfaces

Sulfate adsorption on hematite surfaces controls sulfate mobility and environmental behavior but whether sulfate forms both inner- and outer-sphere complexes and the type of the inner-sphere complexes remain contentious. With ionic strength tests and S K-edge X-ray absorption near-edge structure spectroscopy, we show that sulfate forms both outer- and inner-sphere complexes on hematite surfaces. Both S K-edge extended X-ray absorption fine structure spectroscopy and the differential pair distribution function analyses determine the S–Fe interatomic distance (~3.24 Å) of the inner-sphere complex, suggesting bidentate-binuclear complexation. A multivariate curve resolution (MCR) analysis of the attenuated total reflection–Fourier-transform infrared spectra of adsorption envelope samples shows that increasing ionic strength does not affect the inner-sphere but decreases the outer-sphere complex adsorption loading, consistent with the ionic strength effect. The extended triple layer model directly and successfully models the MCR-derived inner- and outer-sphere surface loadings at various ionic strengths, indicating weaker sulfate inner-sphere complexation on hematite than on ferrihydrite surfaces. Results also show that sample drying, lower pH, and higher ionic strength all favor sulfate inner-sphere complexation, but the hematite particle size does not affect the relative proportions of the two types of complexes. Sulfate adsorption kinetics show increasing ratio of exchanged OH– to adsorbed sulfate with time, attributed to inner- and outer-sphere complexation dominating at different adsorption stages and to the changes of the relative abundance of surface OH – and H 2 O groups with time. This work clarifies sulfate adsorption mechanisms on hematite and has implications for understanding sulfate availability, behavior and fate in the environment. Our work suggests that the simple macroscopic ionic strength test correlates well with directly measured outer-sphere complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Combining ToF‐SIMS and Multivariate Analysis to Resolve Active Sites on Ni‐Based HER Catalysts

Unambiguous identification of active sites in heterogeneous catalysis remains a major challenge, particularly for materials with ultrathin, chemically mixed surface layers. Here, we demonstrate a generalizable approach that combines time-of-flight secondary ion mass spectrometry (ToF-SIMS) with multivariate statistical analysis (principal component analysis [PCA] and multivariate curve resolution [MCR]) to resolve catalytically relevant motifs at the nanoscale. Using Ni electrodes as a model system, PCA distinguished hydroxide-enriched domains from oxide- and metal-rich regions, while MCR decomposed depth profiles and 3D images into hydroxide, oxide, and metallic layers with nanometer resolution. A unique secondary-ion fragment, NiO 3 H 3 − (m/z 108.94), emerged as a marker of hydroxide-rich environments and correlated with hydrogen evolution reaction (HER) activity across a series of Ni electrodes. Complementary density functional theory (DFT) calculations revealed that Ni(OH) 2 clusters adjacent to metallic Ni offer the most favorable water dissociation energetics, establishing the structural origin of the marker. While illustrated here for Ni-based HER, this workflow provides a broadly applicable framework to isolate and rank near-surface patterns that govern catalytic activity, thereby extending ToF-SIMS from a qualitative probe to a predictive tool for active site identification.

HER active sites↗