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At least 91 records · Page 5

Performance of a phonon-mediated kinetic inductance detector at the NEXUS cryogenic facility

Microcalorimeters that leverage microwave kinetic inductance detectors to read out phonon signals in the particle-absorbing target, referred to as kinetic inductance phonon-mediated (KIPM) detectors, offer an attractive detector architecture to probe dark matter (DM) down to the fermionic thermal relic mass limit. A prototype KIPM detector featuring a single aluminum resonator patterned onto a 1-gram silicon substrate was operated in the Northwestern EXerimental Underground Site (NEXUS) low-background facility at Fermilab for characterization and evaluation of this detector architecture’s efficacy for a DM search. An energy calibration was performed by exposing the bare substrate to a pulsed source of 470-nm photons, resulting in a baseline resolution on the energy absorbed by the phonon sensor of 2.1 ± 0.2 eV, a factor of two better than the current state of the art, enabled by quasiparticle lifetimes extending up to 6.5 ms. However, due to the subpercent phonon collection efficiency, the resolution on energy deposited in the substrate is limited to σ E = 318 ± 29 eV. We further model both the signal pulse shape as a function of device temperature to extract quasiparticle lifetimes, and the observed noise spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

First Direct-Detection Results on Sub-GeV Dark Matter Using the SENSEI Detector at SNOLAB

Here, we present the first results from a dark matter search using six Skipper-CCDs in the SENSEI detector operating at SNOLAB. We employ a bias-mitigation technique of hiding approximately 46% of our total data and aggressively mask images to remove backgrounds. Given a total exposure after masking of 100.72 gram-days from well-performing sensors, we observe 55 two-electron events, 4 three-electron events, and no events containing 4–10 electrons. The two-electron events are consistent with pileup from one-electron events. Among the 4 three-electron events, 2 appear in pixels that are likely impacted by detector defects, although not strongly enough to trigger our “hot-pixel” mask. We use these data to set world-leading constraints on sub-GeV dark matter interacting with electrons and nuclei.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SENSEI at SNOLAB: Single-Electron Event Rate and Implications for Dark Matter

We present results from data acquired by the SENSEI experiment at SNOLAB after a major upgrade in May 2023, which includes deploying 16 new sensors and replacing the copper trays that house the CCDs with a new light-tight design. We observe a single-electron event rate of (1.39±0.11)×10^{-5} e^{-}/pix/day, corresponding to (39.8±3.1) e^{-}/gram/day. This is an order-of-magnitude improvement compared to the previous lowest single-electron rate in a silicon detector and the lowest for any photon detector in the wavelength range between near-infrared and ultraviolet. We use these data to obtain a 90% confidence level upper bound of 1.53×10^{-5} e^{-}/pix/day and to set constraints on sub-GeV dark matter candidates that produce single-electron events. We hypothesize that the data taken at SNOLAB in the previous run, with an older tray design for the sensors, contained a larger rate of single-electron events due to light leaks. We test this hypothesis using data from the SENSEI detector located in the MINOS cavern at Fermilab.

dark matter↗

Enhanced sensitivity to trace 238 U impurity of sapphire via coincidence neutron activation analysis

Sapphire has mechanical and electrical properties that are advantageous for the construction of internal components of radiation detectors such as time projection chambers and bolometers. However, it has proved difficult to assess its 232 Th and 238 U content down to the picogram per gram level. Here, this work reports an experimental verification of a computational study that demonstrates 𝛾⁢𝛾 coincidence counting, coupled with neutron activation analysis (NAA), can reach ppt sensitivities. Combining results from 𝛾⁢𝛾 coincidence counting with those of earlier single-𝛾 counting based NAA shows that a sample of Saint Gobain sapphire has 232 Th and 238 U concentrations of <0.26 ppt and <2.3 ppt, respectively; the best constraints on the radiopurity of sapphire.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Glycosyl transferase GT2 genes mediate the biosynthesis of an unusual (1,3;1,4)‐β‐glucan exopolysaccharide in the bacterium Sarcina ventriculi

Abstract Linear, unbranched (1,3;1,4)‐β‐glucans (mixed‐linkage glucans or MLGs) are commonly found in the cell walls of grasses, but have also been detected in basal land plants, algae, fungi and bacteria. Here we show that two family GT2 glycosyltransferases from the Gram‐positive bacteriumSarcina ventriculiare capable of synthesizing MLGs. Immunotransmission electron microscopy demonstrates that MLG is secreted as an exopolysaccharide, where it may play a role in organizing individual cells into packets that are characteristic ofSarcinaspecies. Heterologous expression of these two genes shows that they are capable of producing MLGsin planta, including an MLG that is chemically identical to the MLG secreted fromS. ventriculicells but which has regularly spaced (1,3)‐β‐linkages in a structure not reported previously for MLGs. The tandemly arranged, paralogous pair of genes are designatedSvBmlgs1andSvBmlgs2. The data indicate that MLG synthases have evolved different enzymic mechanisms for the incorporation of (1,3)‐β‐ and (1,4)‐β‐glucosyl residues into a single polysaccharide chain. Amino acid variants associated with the evolutionary switch from (1,4)‐β‐glucan (cellulose) to MLG synthesis have been identified in the active site regions of the enzymes. The presence of MLG synthesis in bacteria could prove valuable for large‐scale production of MLG for medical, food and beverage applications.

Biochemistry & Molecular Biology↗

Elongation Factor Tu Acts as a Chaperone to Activate an Antibacterial RNase Toxin

Many Gram-negative bacterial species use contact-dependent growth inhibition (CDI) systems to deliver toxic proteins into neighboring competitors. CDI + strains deploy CdiA effector proteins, which translocate their C-terminal toxin (CT) domains into target bacteria through a receptor-mediated delivery pathway. To protect against auto-intoxication, CDI + bacteria also produce CdiI immunity proteins that neutralize CT toxin activity. Here, we present the crystal structure of the CT·CdiI O32:H37 complex from Escherichia coli O32:H37. CT O32:H37 adopts the same fold as the tRNase domain of colicin D, and the nucleases share similar catalytic centers. However, unlike colicin D, which cleaves the anticodon loops of tRNA Arg isoacceptors, CT O32:H37 exhibits nonspecific RNase activity. Notably, we find that endogenous elongation factor Tu (EF-Tu) co-purifies with the over-produced CT·CdiI O32:H37 complex. Although EF-Tu does not bind stably to CT O32:H37 in the absence of CdiI O32:H37 , the translation factor is required for toxic RNase activity in vitro. AlphaFold 3 modeling and site-directed mutagenesis indicate that CT O32:H37 interacts with the N-terminal GTPase domain of EF-Tu. EF-Tu appears to stabilize residue Trp52 within the hydrophobic core of the toxin, which in turn supports the RNase active site through an unusual hydrogen-bonding interaction with the catalytic His67 residue. Furthermore, EF-Tu is hijacked as an essential co-factor to organize the toxin's catalytic center.

Nhan, Dinh Quan [University of California, Santa B↗

Enhancing cathode composites with conductive alignment synergy for solid-state batteries

Enhancing transport and chemomechanical properties in cathode composites is crucial for the performance of solid-state batteries. Our study introduces the filler-aligned structured thick (FAST) electrode, which notably improves mechanical strength and ionic/electronic conductivity in solid composite cathodes. The FAST electrode incorporates vertically aligned nanoconducting carbon nanotubes within an ion-conducting polymer electrolyte, creating a low-tortuosity electron/ion transport path while strengthening the electrode’s structure. This design not only mitigates recrystallization of the polymer electrolyte but also establishes a densified local electric field distribution and accelerates the migration of lithium ions. The FAST electrode showcases outstanding electrochemical performance with lithium iron phosphate as the active material, achieving a high capacity of 148.2 milliampere hours per gram at 0.2 C over 100 cycles with substantial material loading (49.3 milligrams per square centimeter). This innovative electrode design marks a remarkable stride in addressing the challenges of solid-state lithium metal batteries.

Science & Technology - Other Topics↗

Unravelling electro-chemo-mechanical interplay in layered oxide cathode degradation in solid-state batteries

Solid-state batteries (SSBs) hold notable promise for advancing energy storage technologies. However, their commercial viability is limited by the poor cycle stability and complex degradation mechanism. This study underscores the pivotal role of electro-chemo-mechanical interactions in driving the failure of SSBs. Leveraging advanced x-ray imaging and spectroscopy techniques, we analyzed LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes from cycled Li x In||Li 6 PS 5 Cl (LPSC)||NMC811 SSBs, uncovering the interplay between microstructure, chemical heterogeneity, mechanical characteristics, and electrochemical performance. Our results show that revealing electro-chemo-mechanical interactions is essential to develop strategies to suppress the degradation of SSBs. Particularly, we revisit a LiNbO 3 (LNO) coating layer to mitigate electrochemical degradation. The LNO@NMC811 cathode retains 116 milliampere-hours per gram after 200 cycles, showing excellent stability, while the uncoated NMC811 cathode keeps degrading over time, with suppressed chemical heterogeneity and mechanical failure. This work highlights the importance of synergizing advanced material design with coating techniques, ensuring uniform lithium flux and improving mechanical properties to achieve stable, high-performance SSBs.

Zheng, Xueli [SLAC National Accelerator Laboratory↗

Mutations in the proximal binding site and F-loop of AdeJ confer resistance to efflux pump inhibitors

Multidrug efflux is one of the major mechanisms of antibiotic resistance in gram-negative bacteria. Inhibitors of efflux pumps potentiate the activities of antibiotics, and their discovery could lead to new therapeutic options. The AdeIJK pump in Acinetobacter baumannii is a promising target for efflux pump inhibitors (EPIs) due to its high clinical importance and conservation, and several classes of EPIs targeting this and other A. baumannii efflux transporters have been recently reported. However, the mechanisms of action of these EPIs and their resistance liability remain underexplored. Here, we analyzed the impact of site-specific substitutions in the substrate/EPI translocation path of the inner membrane transporter AdeJ on efflux of substrate antibiotics and fluorescent probes and activities of substituted 4,6-diaminoquinoline EPIs. We found that substitutions in amino acid residues located in the entrance cleft (R701) and the flexible loop (E675) of AdeJ lead to resistance specifically against biphenyl-substituted EPIs, whereas the substitution of F178 in the distal binding pocket increased AdeJ sensitivity to certain naphthyl- and biphenyl-substituted EPIs. No major differences in docking scores and poses of substrates and EPIs were observed between the wild type and corresponding AdeJ variants for any of the mutations considered. This study concludes that substrates and EPIs bound along the translocation path of AdeJ participate in its conformational transitions and can either increase or decrease the rate of transport and therefore the efficiency of EPIs.

Acinetobacter↗

Physiological roles of an Acinetobacter -specific σ factor

ABSTRACT The Gram-negative pathogen Acinetobacter baumannii is considered an “urgent threat” to human health due to its propensity to become antibiotic resistant. Understanding the distinct regulatory paradigms used by A. baumannii to mitigate cellular stresses may uncover new therapeutic targets. Many γ-proteobacteria use the extracytoplasmic function (ECF) σ factor, RpoE, to invoke envelope homeostasis networks in response to stress. Acinetobacter species contain the poorly characterized ECF “SigAb”; however, it is unclear if SigAb has the same physiological role as RpoE. Here, we show that SigAb is a metal stress-responsive ECF that appears unique to Acinetobacter species and distinct from RpoE-like ECFs. We combine promoter mutagenesis, motif scanning, and chromatin immunoprecipitation-sequencing (ChIP-seq) to define the direct SigAb regulon, which consists of genes encoding SigAb itself, the stringent response mediator, RelA, and the uncharacterized small RNA, “SabS.” However, RNA-seq of strains overexpressing SigAb revealed a large, indirect regulon containing hundreds of genes. Metal resistance genes are key elements of the indirect regulon, as CRISPRi knockdown of sigAb or sabS resulted in increased copper sensitivity and excess copper-induced SigAb-dependent transcription. Furthermore, we found that two uncharacterized genes in the sigAb operon, “ aabA ” and “ aabB ,” have anti-SigAb activity. Finally, employing a targeted Tn-seq approach that uses CRISPR-associated transposons, we show that sigAb , aabA , and aabB are important for fitness even during optimal growth conditions. Our work reveals new physiological roles for SigAb and SabS, provides a novel approach for assessing gene fitness, and highlights the distinct regulatory architecture of A. baumannii . IMPORTANCE Acinetobacter baumannii is a hospital-acquired pathogen, and many strains are resistant to multiple antibiotics. Understanding how A. baumannii senses and responds to stress may uncover novel routes to treat infections. Here, we examine how the Acinetobacter -specific transcription factor, SigAb, mitigates stress. We find that SigAb directly regulates only a small number of genes, but indirectly controls hundreds of genes that have substantial impacts on cell physiology. We show that SigAb is required for maximal growth, even during optimal conditions, and is acutely required during growth in the presence of elevated copper. Given that copper toxicity plays roles in pathogenesis and on copper-containing surfaces in hospitals, we speculate that SigAb function may be important in clinically relevant contexts.

Bacon, Emily E. (ORCID:0000000180907689)↗

Bactericidal effectors of the Stenotrophomonas maltophilia type IV secretion system: functional definition of the nuclease TfdA and structural determination of TfcB

ABSTRACT Stenotrophomonas maltophilia expresses a type IV protein secretion system (T4SS) that promotes contact-dependent killing of other bacteria and does so partly by secreting the effector TfcB. Here, we report the structure of TfcB, comprising an N-terminal domain similar to the catalytic domain of glycosyl hydrolase (GH-19) chitinases and a C-terminal domain for recognition and translocation by the T4SS. Utilizing a two-hybrid assay to measure effector interactions with the T4SS coupling protein VirD4, we documented the existence of five more T4SS substrates. One of these was protein 20845, an annotated nuclease. A S. maltophilia mutant lacking the gene for 20845 was impaired for killing Escherichia coli , Klebsiella pneumoniae , and Pseudomonas aeruginosa . Moreover, the cloned 20845 gene conferred robust toxicity, with the recombinant E. coli being rescued when 20845 was co-expressed with its cognate immunity protein. The 20845 effector was an 899 amino-acid protein, comprised of a GHH-nuclease domain in its N-terminus, a large central region of indeterminant function, and a C-terminus for secretion. Engineered variants of the 20845 gene that had mutations in the predicted catalytic site did not impede E. coli , indicating that the antibacterial effect of 20845 involves its nuclease activity. Using flow cytometry with DNA staining, we determined that 20845, but not its mutant variants, confers a loss in DNA content of target bacteria. Database searches revealed that uncharacterized homologs of 20845 occur within a range of bacteria. These data indicate that the S. maltophilia T4SS promotes interbacterial competition through the action of multiple toxic effectors, including a potent, novel DNase. IMPORTANCE Stenotrophomonas maltophilia is a multi-drug-resistant, Gram-negative bacterium that is an emerging pathogen of humans. Patients with cystic fibrosis are particularly susceptible to S. maltophilia infection. In hospital water systems and various types of infections, S. maltophilia co-exists with other bacteria, including other pathogens such as Pseudomonas aeruginosa . We previously demonstrated that S. maltophilia has a functional VirB/D4 type VI protein secretion system (T4SS) that promotes contact-dependent killing of other bacteria. Since most work on antibacterial systems involves the type VI secretion system, this observation remains noteworthy. Moreover, S. maltophilia currently stands alone as a model for a human pathogen expressing an antibacterial T4SS. Using biochemical, genetic, and cell biological approaches, we now report both the discovery of a novel antibacterial nuclease (TfdA) and the first structural determination of a bactericidal T4SS effector (TfcB).

59 BASIC BIOLOGICAL SCIENCES↗

Expanded genome and proteome reallocation in a novel, robust Bacillus coagulans strain capable of utilizing pentose and hexose sugars

Bacillus coagulans, a Gram-positive thermophilic bacterium, is recognized for its probiotic properties and recent development as a microbial cell factory. Despite its importance for biotechnological applications, the current understanding of B. coagulans’ robustness is limited, especially for undomesticated strains. To fill this knowledge gap, we characterized the metabolic capability and performed functional genomics and systems analysis of a novel, robust strain, B. coagulans B-768. Genome sequencing revealed that B-768 has the largest B. coagulans genome known to date (3.94 Mbp), about 0.63 Mbp larger than the average genome of sequenced B. coagulans strains, with expanded carbohydrate metabolism and mobilome. Functional genomics identified a well-equipped genetic portfolio for utilizing a wide range of C5 (xylose, arabinose), C6 (glucose, mannose, galactose), and C12 (cellobiose) sugars present in biomass hydrolysates, which was validated experimentally. For growth on individual xylose and glucose, the dominant sugars in biomass hydrolysates, B-768 exhibited distinct phenotypes and proteome profiles. Faster growth and glucose uptake rates resulted in lactate overflow metabolism, which makes B. coagulans a lactate overproducer; however, slower growth and xylose uptake diminished overflow metabolism due to the high energy demand for sugar assimilation. Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) made up 60%–65% of the measured proteomes but were allocated differently when growing on xylose and glucose. The trade-off in proteome reallocation, with high investment in COG-C over COG-G, explains the xylose growth phenotype with significant upregulation of xylose metabolism, pyruvate metabolism, and tricarboxylic acid (TCA) cycle. Strain B-768 tolerates and effectively utilizes inhibitory biomass hydrolysates containing mixed sugars and exhibits hierarchical sugar utilization with glucose as the preferential substrate.

carbohydrate metabolism↗

Multi-strain analysis of Pseudomonas putida reveals the metabolic and genetic diversity of the species

Pseudomonas putida is a gram-negative bacterial species increasingly utilized in biotechnology due to its robust growth, ability to degrade aromatic compounds, solvent tolerance, and genetic tractability. In this study, we report a comprehensive multi-strain analysis of 164 P. putida strains based on the reconstruction of a pan-putida metabolic network and the formulation of strain-specific genome-scale metabolic models (GEMs). We performed whole-genome sequencing and hybrid assembly for 40 strains, contributing a ~8% increase to the available genomic data for P. putida . Furthermore, high-throughput phenotypic profiling using the Biolog phenotype microarray system for 24 strains on 190 unique carbon sources, along with 15 aromatic compounds not present on Biolog plates, yielded 4,920 unique strain-phenotype measurements. These data were leveraged to curate GEMs for 24 representative strains, including a refined model for strain KT2440, which comprised 1,480 genes and 2,191 metabolites, achieving a prediction accuracy of 91.2% in carbon utilization. Systematic comparison of genomes and GEMs revealed both conserved core pathways and significant allelic and functional divergence across strains, highlighting strain-specific variation in aromatic degradation. While pathways for protocatechuate and phenylacetate degradation were widely conserved, metabolic capabilities for compounds such as ferulate, phenol, and cresols varied markedly, suggesting adaptation to distinct ecological niches. Alleleome analysis of enzymes, such as PcaI and PcaJ, revealed distinct, functionally similar clades, indicating possible convergent evolution or horizontal gene transfer. These results provide computable resources and informative models for selecting P. putida strains with desired traits for biomanufacturing and bioremediation and offer insights into the evolution and phylogeny of the P. putida species.

aromatics utilization↗

Molecular and structural characterization of a Bacillus cereus strain producing an anthrax-like capsule

Bacillus cereus is a ubiquitous Gram-positive, spore-forming, rod-shaped saprophytic bacterium, occasionally reported to cause food-borne illnesses. However, instances of B. cereus strains harboring anthrax toxin and capsule genes have elevated certain strains as formidable pathogens and biothreats. This study focuses on the genomic analysis and the structural characterization of capsular material produced by the virulent B. cereus PATH2418 strain, isolated from the wound of a traumatic open fracture patient. The genome was sequenced using Nanopore MinION sequencing, revealing a chromosome of 5,270,283 bp and three plasmids. One plasmid, pATH1, was found to encode an operon for the biosynthesis of a bacterial capsule. This operon had sequence homology to the Bacillus anthracis capBCADE operon, which encodes the poly-γ-D-glutamate (PDGA) capsule. The capsule production in B. cereus PATH2418 was influenced by temperature and CO 2 levels. Structural analysis of the capsular material using a combined approach of nuclear magnetic resonance (NMR) and high-performance liquid chromatography (HPLC) techniques confirmed the presence of a high-molecular-weight poly-γ-glutamate capsule, with an enantiomeric composition of approximately 67% D-glutamic acid and 33% L-glutamic acid, matching that of B. anthracis.

Bacillus cereus↗

On the Training and Generalization of Deep Operator Networks

Here, we present a novel training method for deep operator networks (DeepONets), one of the most popular neural network models for operators. DeepONets are constructed by two subnetworks, namely the branch and trunk networks. Typically, the two subnetworks are trained simultaneously, which amounts to solving a complex optimization problem in a high dimensional space. In addition, the nonconvex and nonlinear nature makes training very challenging. To tackle such a challenge, we propose a two-step training method that trains the trunk network first and then sequentially trains the branch network. The core mechanism is motivated by the divide-and-conquer paradigm and is the decomposition of the entire complex training task into two subtasks with reduced complexity. Therein the Gram–Schmidt orthonormalization process is introduced which significantly improves stability and generalization ability. On the theoretical side, we establish a generalization error estimate in terms of the number of training data, the width of DeepONets, and the number of input and output sensors. Numerical examples are presented to demonstrate the effectiveness of the two-step training method, including Darcy flow in heterogeneous porous media.

deep operator networks↗

Miniaturize the Redox Flow Battery for Accelerated Materials Discovery and Development

Redox flow batteries are a promising technology for grid-scale energy storage. The aqueous organic redox flow battery is of particular interest for its potentially low material cost and sustainability. Developing novel organic active material for flow battery electrolytes typically entails molecular engineering toward desired properties, necessitating organic synthesis. In a research laboratory setting, the synthesis of specifically designed organic molecules featuring targeted functional groups is time and resources intensive. In the past, synthesizing materials required for battery testing has often required gram-scale production, presenting considerable constraints on the pace of novel organic material discovery. In this report, we introduce a miniaturized cell design that mandates only milligram-scale material synthesis while yielding testing outcomes equivalent or superior to those reported with other commercially available or homemade flow cells in the literature. The test results under various pH conditions validate the scale-down strategy to accelerate the flow battery material discovery and development using the newly designed mini cell. This approach offers researchers an efficient means to notably reduce the time and resources required to develop novel materials for flow batteries.

25 ENERGY STORAGE↗

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab↗

Increased triacylglycerol production in Rhodococcus opacus by overexpressing transcriptional regulators

Lignocellulosic biomass is currently underutilized, but it offers promise as a resource for the generation of commercial end-products, such as biofuels, detergents, and other oleochemicals. Rhodococcus opacus PD630 is an oleaginous, Gram-positive bacterium with an exceptional ability to utilize recalcitrant aromatic lignin breakdown products to produce lipid molecules such as triacylglycerols (TAGs), which are an important biofuel precursor. Lipid carbon storage molecules accumulate only under growth-limiting low nitrogen conditions, representing a significant challenge toward using bacterial biorefineries for fuel precursor production. In this work, we screened overexpression of 27 native transcriptional regulators for their abilities to improve lipid accumulation under nitrogen-rich conditions, resulting in three strains that accumulate increased lipids, unconstrained by nitrogen availability when grown in phenol or glucose. Transcriptomic analyses revealed that the best strain (#13) enhanced FA production via activation of the β-ketoadipate pathway. Gene deletion experiments confirm that lipid accumulation in nitrogen-replete conditions requires reprogramming of phenylalanine metabolism. By generating mutants decoupling carbon storage from low nitrogen environments, we move closer toward optimizing R. opacus for efficient bioproduction on lignocellulosic biomass.

09 BIOMASS FUELS↗