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DOE OSTI2023

Exploring novel alkane-degradation pathways in uncultured bacteria from the North Atlantic Ocean

Microbes play a significant role in the degradation of petroleum hydrocarbons in the oceans, yet little is known about the native bacteria that metabolize hydrocarbons before an oil spill. The Faroe-Shetland Channel (FSC) is a deepwater subarctic region of the North Atlantic with prominent oil production and a diverse microbial community associated with the degradation of petroleum. Here, we combine DNA-based stable-isotope probing (DNA-SIP) with metagenomics to elucidate the metabolic underpinnings of native alkane-degrading bacteria from the FSC. From two 13C n-hexadecane SIP experiments using seawater from 5 and 700 m depths in the FSC, we obtained 42 metagenome-assembled genomes (MAGs) belonging to 19 genera, including two previously overlooked hydrocarbon-degrading bacteria, Lentibacter (Alphaproteobacteria) and Dokdonia (Bacteroidetes). Diversity surveys indicated Lentibacter were dominant members of the FSC, constituting up to 17% of these communities. Many of the SIP-enriched MAGs (20/42) encoded a complete alkane oxidation pathway, including alkane monooxygenase (AlkB), rubredoxin reductase (AlkT), and rubredoxin-2 (AlkG). Fourteen Aphaproteobacteria MAGs lacked AlkG for electron transfer. Instead, they encoded novel disulfide isomerases with iron-binding cysteine motifs conserved across rubredoxins. Dokdonia lacked AlkT and AlkG, however, their central alkane-degradation catabolic pathways were complete. We describe previously unrecognized bacteria capable of hydrocarbon degradation, including the dominant genera Lentibacter, which may continuously purge hydrocarbons released from oil exploration activities in the FSC. This advances the understanding of the diversity and physiologies of alkane degradation in the North Atlantic and provides evidence of new mechanisms used to metabolize alkanes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well. Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites. Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Degradation and Accelerated Recovery of Surface Passivation in n+ Poly-Si/SiOx Passivating Contacts for TOPCon Solar Cells

We studied the surface degradation and recovery of fired poly-Si/SiOx passivating contacts during subsequent dark and illuminated annealing. We report on an industrially-viable path for accelerated recovery of surface passivation. The degradation is influenced by the type of doping in the poly-Si. Phosphorus doped n+ poly-Si/SiOx contacts show degradation followed by recovery, undoped poly-Si/SiOx contacts only show recovery during annealing. Boron doped p+ poly-Si/SiOx contacts show neither degradation nor improvement with annealing. Both degradation and recovery are thermally-activated processes and are completely reversible and cyclic in nature. The activation energy of degradation and recovery in dark for n+ poly-Si/SiOx contacts are 1.27 and 1.33 eV respectively. Dark annealing at elevated temperatures is effective for complete recovery but takes a long time (~30 min at 350 degrees C) due to higher activation energies. Annealing under 7.5 Suns of illumination lowers the activation energy for degradation and recovery to 0.88 and 0.90 eV, respectively. Using this data, we have developed an industrially viable post-firing treatment for accelerated recovery of TOPCon cells by annealing them at elevated temperatures and under intense illumination for a few minutes.

14 SOLAR ENERGY↗

NASA NTRS2015

Insulation Resistance Degradation in Ni-BaTiO3 Multilayer Ceramic Capacitors

Insulation resistance (IR) degradation in NiBaTiO3 multilayer ceramic capacitors has been characterized by the measurement of both time to failure (TTF) and direct current leakage current as a function of stress time under highly accelerated life test conditions. The measured leakage current time dependence data fit well to an exponential form, and a characteristic growth time tau (sub SD) can be determined. A greater value of tau (sub SD) represents a slower IR degradation process. Oxygen vacancy migration and localization at the grain boundary region results in the reduction of the Schottky barrier height and has been found to be the main reason for IR degradation in NiBaTiO3 capacitors. The reduction of barrier height as a function oftime follows an exponential relation of phi (t ) = phi (0) e (exp -2Kt), where 13 the degradation rate constant K Koe (Ek/kT) is inversely proportional to the mean TTF (MTTF) and can be determined using an Arrhenius plot. For oxygen vacancy electromigration, a lower barrier height phi (0) will favor a slow IR degradation process, but a lower phi (0) will also promote electronic carrier conduction across the barrier and decrease the IR. As a result, a moderate barrier height phi (0) (and therefore a moderate IR value) with a longer MTTF (smaller degradation rate constant K) will result in a minimized IR degradation process and the most improved reliability in NiBaTiO3 multilayer ceramic capacitors.

reliability↗

NASA NTRS2015

Insulation Resistance Degradation in Ni-BaTiO3 Multilayer Ceramic Capacitors

Insulation resistance (IR) degradation in Ni-BaTiO3 multilayer ceramic capacitors has been characterized by the measurement of both time to failure and direct-current (DC) leakage current as a function of stress time under highly accelerated life test conditions. The measured leakage current-time dependence data fit well to an exponential form, and a characteristic growth time SD can be determined. A greater value of tau(sub SD) represents a slower IR degradation process. Oxygen vacancy migration and localization at the grain boundary region results in the reduction of the Schottky barrier height and has been found to be the main reason for IR degradation in Ni-BaTiO3 capacitors. The reduction of barrier height as a function of time follows an exponential relation of phi (𝑡)=phi (0)e(exp -2Κt), where the degradation rate constant 𝐾=𝐾o𝑒(𝐸𝑘/𝑘𝑇) is inversely proportional to the mean time to failure (MTTF) and can be determined using an Arrhenius plot. For oxygen vacancy electromigration, a lower barrier height phi(0) will favor a slow IR degradation process, but a lower phi(0) will also promote electronic carrier conduction across the barrier and decrease the insulation resistance. As a result, a moderate barrier height phi(0) (and therefore a moderate IR value) with a longer MTTF (smaller degradation rate constant 𝐾) will result in a minimized IR degradation process and the most improved reliability in Ni-BaTiO3 multilayer ceramic capacitors.

dielectric degradation↗

NASA NTRSDate not supplied

Using Degradation Modeling to Identify Fragile Operational Conditions in Human- and Component-driven Resilience Assessment

Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models–specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.

resilience↗

DOE OSTI2021

Deciphering Degradation: Machine Learning on Real-World Performance Data (Final Report)

This project addresses a fundamental flaw in solar PV research and solar project financing; the assumed rate of degradation for solar plants. The solar industry currently relies on an out-dated report that observed a 0.5% degradation rate based on a small sample size of systems (~100). While the research conducted at the time was new and innovative, the solar community has not updated this research and universally applies this 0.5% degradation assumption in financial models. Our project updates this assumption by analyzing observed degradation from the industry’s largest dataset of operating solar assets (>10,000 systems) and creating the first machine-learning model based on these observed results to quantify and identify features that drive degradation. There are two strategic goals for this award: reduce the cost of capital (enable solar to attract more capital) and improve the reliability of solar itself. These dual goals are achieved by leveraging an industry dataset to observe system degradation on a large scale, deploying advanced data analysis and machine learning methods to quantify and predict system reliability, and engaging with industry stakeholders to help them accurately price degradation in financial models.

14 SOLAR ENERGY↗

DOE OSTI2024

PVDeg: Development of a Streamlined Tool for PV Degradation Modeling

The photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 to 50 years. research efforts aim to achieve this while keeping performance degradation at a minimum for decades. This puts considerable pressure on improving the accuracy of long-term durability and reliability assessments. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. The tool will simplify many of the routine computational operations that are common to many degradation studies. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. This repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors.

degradation↗

DOE OSTI2021

Multiscale Characterization of Photovoltaic Modules—Case Studies of Contact and Interconnect Degradation

The current popularity of photovoltaic (PV) systems is due in large part to their exceptional reliability and significantly lower cost than other energy sources. Studying cell and module degradation is key to promote further development in the state of the art. Fielded or accelerated aged modules exhibit different failure modes, of which metallization degradation (contacts and interconnections) is prevalent. In this work, we discuss how multiscale characterization methods can be applied to a variety of module technologies that have been field exposed and have undergone accelerated age testing. These methods include performing characterization on the module level, cell level, and finally the materials level. The observed performance losses from the module- and cell-level characterization can be correlated with materials properties to find out the root cause of degradation. We recommend an initial nondestructive characterization suite, including module- and cell-level current-voltage ( I--V ), Suns-V OC , photoluminescence and electroluminescence imaging, quantum efficiency, ultraviolet fluorescence imaging, and thermal infrared imaging. Samples are then extracted from particularly degraded regions of the module and prepared for materials characterization techniques, such as top-down and cross-sectional scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, secondary ion mass spectrometry, Raman spectroscopy, and transmission electron microscopy, allowing a deeper look into the mechanism behind the metallization degradation. This article serves as an instructional review to introduce the different multiscale characterization methods and how they can be effectively applied to perform PV degradation studies. Furthermore, we also share some of our examples and discuss the strengths, limitations, and best practices for each of the characterization techniques.

14 SOLAR ENERGY↗

DOE OSTI2024

Nanoconfinement-induced shift in photooxidative degradation pathway of polystyrene

Polymer nanocomposites with high concentrations of nanoparticles (NPs) possess exceptional mechanical, transport, and thermal properties. To enable their widespread use in structural applications and functional coatings, it is crucial to understand how nanoconfinement and the polymer-NP interface influence polymer degradation under various environmental conditions, including prolonged UV exposure. In this study, we investigate the photooxidative degradation of polystyrene (PS)-confined in the interstices of SiO 2 NP films. These nanocomposite films are prepared by the capillary rise infiltration (CaRI) of PS into interstices of SiO 2 NP packings, and subsequently subjected to UV irradiation. Our investigation reveals that PS degradation progresses uniformly across the thickness, with degradation initiating from the center of the NP interstitial pores and extending towards the NP surface. We rationalize this degradation mechanism based on the disparity in the surface energies of PS and the NP surface, as well as slow oxygen diffusion through confined PS. Here, we also demonstrate that packing smaller NPs at a given thickness or thicker packing of a specific NP size facilitates photooxidative degradation, highlighting the critical role of the number of interstitial pores in influencing degradation processes.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Low and High LET Degradation Studies of Metal-Loaded Organic Phase Ligands in the ALSEP Process

Organic solutions comprising the Actinide Lanthanide Separation Process (ALSEP) solvent consisting of 0.5 M 2-ethylhexyl phosphonic acid mono-2-ethylhexyl ester (HEH[EHP]) and 0.05 M N,N,N’,N’-tetra(2-ethylhexyl)diglycolamide (T2EHDGA) in n-dodecane were subjected to low LET and high LET irradiation before and after equilibration with an aqueous phase of 3 M HNO 3 . Degradation dose constants revealed greater ligand degradation due to gamma irradiation than alpha irradiation for both ligands. Furthermore, equilibration with nitric acid did not have a significant impact on ligand degradation for either irradiation source. Identified degradation products were similar for both gamma and alpha irradiation and occurred mostly through the rupture of the N–C carbonyl and C–O ether bonds for T2EHDGA and the C–Oether bond in HEH[EHP]. Acid contact appears to alter the degradation pathway by favoring the formation of higher molecular weight recombination products. Furthermore, mixed T2EHDGA-HEH[EHP]-NO 3 complexes were formed with Nd(III) after extraction from 3 M HNO 3 , and low LET gamma irradiation of the Nd(III) loaded organic solution produced similar degradation products as the organic solution absent of Nd(III). Interestingly, and likely due to the greater radiolytic susceptibility of T2EHDGA than HEH[EHP], a HEH[EHP]-Nd(III) complex appears to form as the T2EHDGA degrades with increasing absorbed dose.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Field-Aged Glass/Backsheet and Glass/Glass PV Modules: Encapsulant Degradation Comparison

Ethylene vinyl acetate (EVA) is the predominant encapsulant in crystalline-silicon photovoltaic (PV) modules; however, its degradation is a subject of major concern, which causes significant power loss under field conditions. This article presents a comparison of EVA degradation in field-aged PV modules with glass/backsheet (G/B) and glass/glass (G/G) architectures. Modulelevel characterization included UV fluorescence imaging and I-V measurements. Material analytical techniques, including colorimetry, differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, and Raman spectroscopy, were performed to correlate the module performance parameters with EVA material properties. An intense EVA discoloration in G/G modules was observed, which was corroborated by higher module Isc and Pmax degradation rates compared with its counterpart G/B modules. Higher power degradation was accompanied by a significant increase in EVA crosslinking, vinyl acetate content, yellowness index, and presence of functional groups containing unsaturated moieties that are linked to degradation products of photothermal reaction, and a higher decrease in the degree of crystallinity. The absence of a polymeric backsheet in hermetically sealed G/G modules, which restricts photobleaching and enhances the entrapment of volatile acetic acid and other degradation by-products, plays a major role in causing higher EVA degradation in G/G modules. This article concludes that EVA might have been a good choice of an encapsulant for the G/B modules over the decades, but it may prove to be an inappropriate choice for the G/G modules because of potential degassing, corrosion, and/or discoloration issues. Ionomers or polyester-based encapsulants like polyolefins could be best suited for G/G modules as it appears to be a current trend in the industry.

14 SOLAR ENERGY↗

DOE OSTI2021

A selective WDR5 degrader inhibits acute myeloid leukemia in patient-derived mouse models

Interactions between WD40 repeat domain protein 5 (WDR5) and its various partners such as mixed lineage leukemia (MLL) and c-MYC are essential for sustaining oncogenesis in human cancers. However, inhibitors that block protein-protein interactions (PPIs) between WDR5 and its binding partners exhibit modest cancer cell killing effects and lack in vivo efficacy. Here, we present pharmacological degradation of WDR5 as a promising therapeutic strategy for treating WDR5-dependent tumors and report two high-resolution crystal structures of WDR5-degrader-E3 ligase ternary complexes. We identified an effective WDR5 degrader via structure-based design and demonstrated its in vitro and in vivo antitumor activities. On the basis of the crystal structure of an initial WDR5 degrader in complex with WDR5 and the E3 ligase von Hippel–Lindau (VHL), we designed a WDR5 degrader, MS67, and demonstrated the high cooperativity of MS67 binding to WDR5 and VHL by another ternary complex structure and biophysical characterization. MS67 potently and selectively depleted WDR5 and was more effective than WDR5 PPI inhibitors in suppressing transcription of WDR5-regulated genes, decreasing the chromatin-bound fraction of MLL complex components and c-MYC, and inhibiting the proliferation of cancer cells. In addition, MS67 suppressed malignant growth of MLL-rearranged acute myeloid leukemia patient cells in vitro and in vivo and was well tolerated in vivo. Collectively, our results demonstrate that structure-based design can be an effective strategy to identify highly active degraders and suggest that pharmacological degradation of WDR5 might be a promising treatment for WDR5-dependent cancers.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Membrane Thickness Impact on Chemical Degradation Rates

Abstract A comprehensive investigation of PFSA membrane chemical degradation rates as a function of thickness (8-20 µm) is reported. The two-pronged study was conducted on bare membranes and as components of chemically-mitigated and mechanically-reinforced, state-of-the-art (SOA) membrane electrode assemblies (MEAs). The bare membranes were subjected to H2O2 vapor test and MEAs were degraded under OCV conditions, both at 90°C. Both test types employed fluoride release rates (FRR) to monitor chemical degradation rates. Vapor tests revealed that area-specific degradation rates were positively correlated with membrane thickness, but thickness normalized degradation rates were independent of thickness. Open-circuit voltage (OCV) investigations spanning the membrane thickness series of MEAs was probed via a 27-experiment 3(4-1) fractional factorial experimental design. Statistical analysis of the FRR values revealed that chemical degradation rates were dominated by the relative humidity value and that the area-specific degradation rates of MEAs were independent of membrane thickness. The OCV chemical durability insensitivity to membrane thickness is supported by on-load membrane chemical durability studies at the stack level. The results suggest that ,despite smaller ionomer inventory, SOA thin membranes and MEAs are not greatly disadvantaged relative to thicker membranes from a chemical durability perspective, provided oxidative stress levels are controlled throughout application lifetime.

Coms, Frank D. (ORCID:0000000249160350)↗

DOE OSTI2022

Understanding of bacterial lignin extracellular degradation mechanisms by Pseudomonas putida KT2440 via secretomic analysis

Abstract Background Bacterial lignin degradation is believed to be primarily achieved by a secreted enzyme system. Effects of such extracellular enzyme systems on lignin structural changes and degradation pathways are still not clearly understood, which remains as a bottleneck in the bacterial lignin bioconversion process. Results This study investigated lignin degradation using an isolated secretome secreted by Pseudomonas putida KT2440 that grew on glucose as the only carbon source. Enzyme assays revealed that the secretome harbored oxidase and peroxidase/Mn 2+ -peroxidase capacity and reached the highest activity at 120 h of the fermentation time. The degradation rate of alkali lignin was found to be only 8.1% by oxidases, but increased to 14.5% with the activation of peroxidase/Mn 2+ -peroxidase. Gas chromatography–mass spectrometry (GC–MS) and two-dimensional 1 H– 13 C heteronuclear single-quantum coherence (HSQC) NMR analysis revealed that the oxidases exhibited strong C–C bond ( β-β , β -5, and β -1) cleavage. The activation of peroxidases enhanced lignin degradation by stimulating C–O bond ( β -O-4) cleavage, resulting in increased yields of aromatic monomers and dimers. Further mass spectrometry-based quantitative proteomics measurements comprehensively identified different groups of enzymes particularly oxidoreductases in P. putida secretome, including reductases, peroxidases, monooxygenases, dioxygenases, oxidases, and dehydrogenases, potentially contributed to the lignin degradation process. Conclusions Overall, we discovered that bacterial extracellular degradation of alkali lignin to vanillin, vanillic acid, and other lignin-derived aromatics involved a series of oxidative cleavage, catalyzed by active DyP-type peroxidase, multicopper oxidase, and other accessory enzymes. These results will guide further metabolic engineering design to improve the efficiency of lignin bioconversion. Graphical Abstract

09 BIOMASS FUELS↗

DOE OSTI2020

Surrogate Model Development of Spent Fuel Degradation for Repository Performance Assessment

In model simulations of deep geologic repositories, UO 2 fuel matrix degradation typically begins as soon as the waste package breaches and groundwater contacts the fuel surface. The initial degradation rate depends on the timing of these events, burnup of the fuel, temperature, and concentrations of dissolved reactants. Estimating the initial rate of degradation is fairly straightforward, but as UO 2 corrosion products precipitate on the fuel surface and the movement of dissolved species between the fuel surface and environment is impeded by the precipitated solids, the rate is more difficult to quantify. At that point, calculating the degradation rate becomes a reactive-transport problem in which a large number of equations must be solved by iteration for a large number of grid cells at each time step. The consequence is that repository simulations, which are already expensive, become much more expensive, especially when hundreds or thousands of waste packages breach. The Fuel Matrix Degradation (FMD) model is the process model of the Spent Fuel and Waste Science and Technology (SFWST) campaign of the US Department of Energy (DOE). It calculates spent fuel degradation rates as a function of radiolysis, redox reactions, electrochemical reactions, alteration layer growth, and diffusion of reactants through the alteration layer. Like other similar fuel degradation process models, it is a complicated model requiring a large number of calculations and iterations at each time step.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Characterization of Multiple Trichloroethene, cis-Dichloroethene and 1,1-Dichloroethene Degrading Propanotrophic Communities

Aerobic cometabolism offers a viable strategy for the remediation of chlorinated solvent plumes at oxic sites where anaerobic approaches are limited. In this study, propane-enriched mixed cultures (derived from agricultural soils and an impacted site sediment) which previously degraded 1,4-dioxane, were evaluated for their capacity to also degrade trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), and 1,1-dichloroethene (1,1-DCE) over successive transfers. Sustained biodegradation of TCE and cDCE was observed across multiple enrichments, and cultures enriched on one compound generally degraded the other. In contrast, 1,1-DCE biodegradation was restricted to a subset of cultures and removal times increased over transfers. Further, 1,1-DCE removal was absent at elevated concentrations, both trends consistent with inhibitory or toxic effects. Whole genome sequencing analyses revealed pronounced substrate-dependent selection of microbial communities, with cDCE-degrading cultures being dominated by Mycobacterium and Mycolicibacterium, whereas TCE-degrading cultures were dominated by Rhodococcus. Rhodococcus metagenome-assembled genomes (MAGs) in the TCE degrading cultures classified as R. opacus or R. wratislaviensis. 1,1-DCE degrading cultures were dominated by Pseudonocardia, although the associated MAGs contained a truncated propane monooxygenase alpha subunit. Functional gene analysis identified both group 5 (prmABCD) and putative group 6 propane monooxygenases. The following KBase narratives contain the quality controlled reads, MAGs (fasta assemblies) and the prokka annotations for each assembly TCE Site 1A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254918) TCE Soil 2A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254919) TCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254920) TCE Soil T4 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254921) cDCE Site 1A 1B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254915) cDCE Soils T2 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254927) cDCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254928) cDCE Soil 4A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254942) 1,1-DCE T2 T3 Propanotrophic MAGs (https://narrative.kbase.us/narrative/254903)

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Metagenomic and Metatranscriptomic Analyses Revealed Uncultured Bacteroidales Populations as the Dominant Proteolytic Amino Acid Degraders in Anaerobic Digesters

Current understanding of amino acid (AA) degraders in anaerobic digesters is mainly based on cultured species, whereas microorganisms that play important roles in a complex microbial community remain poorly characterized. This study investigated short-term enrichments degrading single AAs using metagenomics and metatranscriptomics. Metagenomic analysis revealed that populations related to cultured AA degraders had an abundance <2.5% of the sequences. In contrast, metagenomic-assembled bins related to uncultured Bacteroidales collectively accounted for >35% of the sequences. Phylogenetic analyses suggested that these Bacteroidales populations represented a yet-to-be characterized family lineage, i.e., Bacteroidetes vadinHA17. The bins possessed the genetic capacity related to protein degradation, including surface adhesion (3–7 genes), secreted peptidase (52–77 genes), and polypeptide-specific transporters (2–5 genes). Furthermore, metatranscriptomics revealed that these Bacteroidales populations expressed the complete metabolic pathways for degrading 16 to 17 types of AAs in enrichments fed with respective substrates. These characteristics were distinct from cultured AA degraders including Acidaminobacter and Peptoclostridium, suggesting the uncultured Bacteroidales were the major protein-hydrolyzing and AA-degrading populations. These uncultured Bacteroidales were further found to be dominant and active in full-scale anaerobic digesters, indicating their important ecological roles in the native habitats. “Candidatus Aminobacteroidaceae” was proposed to represent the previously uncharted family Bacteroidetes vadinHA17.

59 BASIC BIOLOGICAL SCIENCES↗