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At least 37 records · Page 2

Improved chemical and isotopic labeling of biomembranes in Bacillus subtilis by leveraging CRISPRi inhibition of beta-ketoacyl-ACP synthase (fabF)

Assessing the structure of living microbial cell membranes is a challenging analytical goal. The cell membrane is defined by its transverse structure, an approximately 5 nm-thick selectively permeable bilayer that serves many important cellular functions. Compositionally complex, dynamic, and organized in both the transverse and lateral dimensions, understanding the cell membrane structure—and the role that structure plays in cellular function, communication, and environmental sensing is an active scientific effort. Previously, we have devised a novel isotopic labeling approach for membrane lipids to enable direct in vivo structural studies of the cell membrane in the Gram-positive bacterium, Bacillus subtilis , using small-angle neutron scattering. This was accomplished through a genetic inhibition of fatty acid (FA) degradation (Δ fadN ) and a chemical inhibition of FA biosynthesis using cerulenin, an irreversible inhibitor of type II fatty acid synthases. Here, we improve upon the previous system by introducing a dCas9/sgRNA- fabF complex that blocks transcription of the essential fabF gene when under xylose induction. This leads to greater sensitivity to cerulenin in the mutant strain (JEBS102) and more robust cell growth when supplementary FAs are introduced to the culture medium. A subtle change in FA uptake is noted when compared to the prior labeling strategy. This is seen in the gas chromatography/mass spectrometry (GC/MS) data as a higher ratio of n 16:0 to a 15:0, and manifests in an apparent increase in the membrane thickness determined via neutron scattering. This represents an improved method of isotopic labeling for the cell membrane of Bacillus subtilis; enabling improved investigations of cellular uptake and utilization of FAs, cell membrane structure and organization as a phenotypic response to metabolic and environmental changes.

59 BASIC BIOLOGICAL SCIENCES↗

Multilevel-in-width training for deep neural network regression

A common challenge in regression is that for many problems, the degrees of freedom required for a high-quality solution also allows for overfitting. Regularization is a class of strategies that seek to restrict the range of possible solutions so as to discourage overfitting while still enabling good solutions, and different regularization strategies impose different types of restrictions. In this paper, we present a multilevel regularization strategy that constructs and trains a hierarchy of neural networks, each of which has layers that are wider versions of the previous network's layers. Here, we draw intuition and techniques from the field of Algebraic Multigrid (AMG), traditionally used for solving linear and nonlinear systems of equations, and specifically adapt the Full Approximation Scheme (FAS) for nonlinear systems of equations to the problem of deep learning. Training through V-cycles then encourage the neural networks to build a hierarchical understanding of the problem. We refer to this approach as multilevel-in-width to distinguish from prior multilevel works which hierarchically alter the depth of neural networks. The resulting approach is a highly flexible framework that can be applied to a variety of layer types, which we demonstrate with both fully connected and convolutional layers. We experimentally show with PDE regression problems that our multilevel training approach is an effective regularizer, improving the generalize performance of the neural networks studied.

97 MATHEMATICS AND COMPUTING↗

Higher-order interaction effects among operating conditions and feedstocks shape reactor microbiomes and fatty acid production profiles

Arrested anaerobic digestion (AAD) offers a promising route for producing fatty acids (FAs) from organic residues, yet optimal conditions for selectively generating medium-chain fatty acids (MCFAs) remain poorly defined. Here, we systematically evaluated the main and interaction effects of pH (5, 7, 9), feedstock (food waste, manure), temperature (35 and 45 °C), and inoculum source on microbiome composition and FA production. Anaerobic digester sludge and a novel bison rumen inoculum were compared. Significant higher-order interactions among operating parameters governed FA profiles and microbiome structure. Butyric acid production was driven by a three-way interaction among pH, feedstock, and temperature (p < 0.001), with maximum concentrations achieved in food waste reactors at pH 5.0 and 35 °C (1.2 ± 0.1 g L −1 with sludge and 1.1 ± 0.3 g L −1 with rumen). MCFA production exhibited significant four-way interactions (p < 0.1 to p < 0.001). At 45 °C and pH 5.0, inoculum source tuned MCFA selectivity: sludge favored pentanoic acid (0.4 ± 0.1 g L −1 ), whereas rumen favored hexanoic and heptanoic acids (up to 0.4 ± 0.2 g L −1 ). Manure reactors produced < 0.2 g L −1 MCFAs under all conditions. Genera, including Megasphaera, Prevotella, and Lactobacillus, were associated with production of specific MCFAs. PICRUSt2-based pathway predictions were consistent with MCFA production patterns and suggested a potential role for lactic acid–driven chain elongation pathways. This study provides insights into how interacting operating conditions shape AAD microbiomes, their FA profiles, and advances the trajectory of research aimed at engineering robust and controllable microbiomes for waste valorization.

09 BIOMASS FUELS↗

An aggregation-based nonlinear multigrid solver for two-phase flow and transport in porous media

A nonlinear multigrid solver for two-phase flow and transport in a mixed fractional-flow velocity-pressure-saturation formulation is proposed. The solver, which is under the framework of the full approximation scheme (FAS), extends our previous work on nonlinear multigrid for heterogeneous diffusion problems. The coarse spaces in the multigrid hierarchy are constructed by first aggregating degrees of freedom, and then solving some local flow problems. The mixed formulation and the choice of coarse spaces allow us to assemble the coarse problems without visiting finer levels during the solving phase, which is crucial for the scalability of multigrid methods. Specifically, a natural generalization of the upwind flux can be evaluated directly on coarse levels using the precomputed coarse flux basis vectors. We find that the resulting solver is applicable to problems discretized on general unstructured grids. The performance of the proposed nonlinear multigrid solver in comparison with the standard single level Newton's method is demonstrated through challenging numerical examples. It is observed that the proposed solver is robust for highly nonlinear problems and clearly outperforms Newton's method in the case of high Courant-Friedrichs-Lewy (CFL) numbers.

58 GEOSCIENCES↗

Sustainable co-production of plant lipids and cellulosic sugars from transgenic energycane at an industrially relevant scale: A proof of concept for alternative feedstocks

Development of sustainable and scalable technologies to convert lignocellulosic biomass to biofuels is critical to achieving carbon neutrality. The potential of transgenic bioenergy crops as a renewable source of sugars and lipids has been demonstrated at bench-scale. However, scaling up these processes is important for holistic analysis. Here proof-of-concept for chemical-free hydrothermal pretreatment of transgenic energycane-oilcane line L13 at an industrially relevant scale to recover vegetative lipids along with cellulosic sugars is presented. Here, pilot-scale processing of 97 kg of transgenic energycane-oilcane L13 stems and high solids pretreatment of bagasse enhanced the recovery of cellulosic glucose and xylose by 5-fold as compared to untreated bagasse and helped in the enrichment of vegetative lipids in the biomass residues which allowed its recovery at the end of the bioprocess. Palmitic and oleic acids were the predominant fatty acids (FAs) extracted from stems and leaves. The processing did not affect lipid composition. The efficiency of lipid recovery from untreated biomass was 75.9% which improved to 88.7% upon pretreatment. The vegetative tissues of transgenic energycane-oilcane L13 contained 0.42 metric tons/hectare of lipids. Processing vegetative tissues yielded 0.38 metric tons/hectare of lipids. This approaches an oil yield similar to soybean (global average 0.44 metric tons/hectare) and is almost twice as high as the oil yield from sugarcane engineered to hyperaccumulate lipids (0.20 metric tons/hectare). The study suggests that further optimization by state-of-the-art metabolic engineering and biomass processing can establish transgenic bioenergy crops for commercial drop-in fuel production.

59 BASIC BIOLOGICAL SCIENCES↗

Optimizing pressurized-water reactor equilibrium cycle using a novel loading pattern encoding and rule-based genetic crossover operators

This work presents an extended multi-batch approach applied in shuffling scheme optimization for equilibrium cycle for pressurized water reactors using Genetic Algorithms (GAs). A new ruled based GA crossover operator called Inherited Location and Batch (ILB) was introduced to enhance offsprings reproduction efficiency specialized for equilibrium cycle optimization problem. This approach was implemented within the Plant ReLoad Optimization (PRLO) framework and validated using a generic reactor model based on the AP1000 design, with core parameters calculated via the CASMO/SIMULATE software package. The ILB approach is then applied for both single and multi-objective problems in maximizing cycle length and core average exposure while minimizing the average enrichment of the 57 fresh fuel assemblies (FAs) per cycle. The optimal solutions are selected based on their dominance to the objectives from all feasible solutions. This research identified three optimal solutions satisfied safety constraints: The first solution minimizes feed enrichment costs with a cycle length of 338.8 days and core exposure of 25.39 MWd/MT; the second solution extends cycle length to 361.2 days, with the highest core exposure of 26.84 MWd/MT, using 3.75 wt% average fuel enrichment; the third solution balances both objectives with a cycle length of 349.6 days, core exposure of 25.82 MWd/MT with a slight enrichment increase compared to the first solution. Collectively, these findings underscore the efficiency and effectiveness of the proposed approach in achieving practical multi-objective optimal equilibrium cycle designs using GAs optimizer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Kindlin-2 promoted the progression of keloids through the Smad pathway and Fas/FasL pathway

Keloids are benign skin tumors characterized by aggressive growth. To date, there is no exact treatment because little is known about its pathological mechanism. Therefore, it is important to investigate the mechanism of its occurrence and development to identify therapeutic targets. In this study, the expression of Kindlin-2 was higher in keloid fibroblasts (KFs) than in normal skin fibroblasts (NFs). In vitro experiments showed that knocking down Kindlin-2 in KFs could promote cell apoptosis and inhibit cell proliferation, cell migration and invasion, and contractile capability. Western blot results showed that the phosphorylation of Smad3 in KFs was inhibited after knocking down Kindlin-2, inhibiting the activation of the Smad pathway. Moreover, knocking down Kindlin-2 increased the expression of Fas and FasL in KFs, which demonstrated that knocking down Kindlin-2 promoted the activation of the exogenous apoptotic pathway of KFs and then facilitated apoptosis. The above results revealed that knocking down Kindlin-2 in KFs can inhibit the activation of the Smad pathway and promote the activation of the Fas/FasL exogenous apoptosis pathway, thereby altering the cytological function of KFs. Therefore, Kindlin-2 might play an important role in the occurrence and development of keloids and could become a new target to treat keloids.

60 APPLIED LIFE SCIENCES↗

Learning earthquake ground motions via conditional generative modeling

Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake locations, while physics-based methods are computationally intensive and require accurate representations of Earth structures and earthquake sources. We propose an artificial intelligence (AI) spectrogram generator, Conditional Generative Modeling for Ground Motion (CGM-GM). CGM-GM leverages earthquake magnitudes and geographic coordinates of earthquakes and sensors as inputs, when postprocessed with phase information, capturing spatially continuous Fourier amplitude spectra (FAS) as well as properties such as P and S arrivals, and waveform durations, without explicit physics constraints. This is achieved through a probabilistic autoencoder that extracts latent distributions in the time-frequency domain and variational sequential models for prior and posterior distributions. We evaluate the performance of CGM-GM using small-magnitude earthquake records from the San Francisco Bay Area, a region with high seismic risks. Here, we report that CGM-GM demonstrates potential for complementing physics-based simulations and non-ergodic empirical ground motion models, as well as shows promise in seismology and beyond.

geophysics↗

Towards rational control of seed oil composition: dissecting cellular organization and flux control of lipid metabolism

Plant lipids represent a fascinating field of scientific study, in part due to a stark dichotomy in the limited fatty acid (FA) composition of cellular membrane lipids vs the huge diversity of FAs that can accumulate in triacylglycerols (TAGs), the main component of seed storage oils. With few exceptions, the strict chemical, structural, and biophysical roles imposed on membrane lipids since the dawn of life have constrained their FA composition to predominantly lengths of 16–18 carbons and containing 0–3 methylene-interrupted carbon-carbon double bonds in cis-configuration. However, over 450 “unusual” FA structures can be found in seed oils of different plants, and we are just beginning to understand the metabolic mechanisms required to produce and maintain this dichotomy. Here we review the current state of plant lipid research, specifically addressing the knowledge gaps in membrane and storage lipid synthesis from 3 angles: pathway fluxes including newly discovered TAG remodeling, key acyltransferase substrate selectivities, and the possible roles of “metabolons.”

59 BASIC BIOLOGICAL SCIENCES↗

Multiplexed CRISPR/Cas9 editing of the long-chain acyl-CoA synthetase family in the diatom Phaeodactylum tricornutum reveals that mitochondrial ptACSL3 is involved in the synthesis of storage lipids

Long-chain acyl-CoA synthetases (LACS) play diverse and fundamentally important roles in lipid metabolism. While their functions have been well established in bacteria, yeast and plants, the mechanisms by which LACS isozymes regulate lipid metabolism in unicellular oil-producing microalgae, including the diatom Phaeodactylum tricornutum , remain largely unknown. In P. tricornutum , a family of five genes ( ptACSL1 – ptACSL5 ) encodes LACS activities. For this work, we generated single lacs knockout/knockdown mutants using multiplexed CRISPR/Cas9 method, and determined their substrate specificities towards different fatty acids (FAs) and subcellular localisations. ptACSL3 is localised in the mitochondria and its disruption led to compromised growth and reduced triacylglycerol (TAG) content when cells were bubbled with air. The ptACSL3 mutants showed altered FA profiles in two galactoglycerolipids and phosphatidylcholine (PC) with significantly reduced distribution of 16:0 and 16:1. ptACSL5 is localised in the peroxisome and its knockdown resulted in reduced growth rate and altered molecular species of PC and TAG, indicating a role in controlling the composition of acyl-CoAs for lipid synthesis. Our work demonstrates the potential of generating gene knockout mutants with the mutation of large fragment deletion using multiplexed CRISPR/Cas9 and provides insight into the functions of LACS isozymes in lipid metabolism in the oleaginous microalgae.

59 BASIC BIOLOGICAL SCIENCES↗

Purple acid phosphatase2 stimulates a futile cycle of lipid synthesis and degradation, and mitigates the negative growth effects of triacylglycerol accumulation in vegetative tissues

Storage lipids (mostly triacylglycerols, TAGs) serve as an important energy and carbon reserve in plants and hyperaccumulation of TAG in vegetative tissues can cause negative effects on plant growth. Purple acid phosphatase2 (PAP2) was shown previously to affect carbon metabolism and boost plant growth. However, the effects of PAP2 on lipid metabolism remain unknown. Here, we demonstrated PAP2 as a factor that can stimulate a futile cycle of fatty acid (FA) synthesis and degradation and mitigate negative growth effects associated with TAG accumulation in vegetative tissues. Constitutive expression of PAP2 in Arabidopsis thaliana enhanced both lipid synthesis and degradation in leaves and led to substantial increase in seed oil yield. Suppressing lipid degradation in a PAP2-overexpressing line by disrupting sugar-dependent1 (SDP1), a predominant TAG lipase, significantly elevated vegetative TAG content and improved plant growth. Diverting FAs from membrane lipids to TAGs in PAP2-overexpressing plants by constitutively expressing phospholipid:diacylglycerol acyltransferase1 (PDAT1) increased TAG contents to up to 6% of dry weight in vegetative tissues without compromising biomass yield. Overall, these results highlight the potential of combining PAP2 with TAG-promoting factors to enhance carbon assimilation, FA synthesis and allocation to TAGs for optimized plant growth and storage lipid accumulation in vegetative tissues.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding the dynamic nature of plant lipid anabolic and catabolic metabolism is key to sustainable oilseed engineering

Plant-derived oils are essential sources of reduced carbon and various fatty acid (FA) structures for food, biofuels, and the oleochemical industry. Despite extensive efforts, engineering mainstream oilseed crops to produce high levels of industrially valuable unusual FAs (UFAs) remains challenging. This review synthesizes recent advances in the understanding of lipid metabolic networks, emphasizing how species-specific regulation of FA synthesis, activation, and delivery influences triacylglycerol (TAG) assembly to govern the efficiency of UFA accumulation. Key insights reveal that acyl flux through anabolic and catabolic branches of lipid metabolism is tightly controlled by enzyme substrate selectivities, diacylglycerol (DAG) pool compartmentalization, and metabolic context, including lipid remodeling and degradation pathways. Engineering success is often constrained by incompatibilities between UFA biosynthetic enzymes and endogenous host metabolism, leading to flux imbalances, futile cycles, and undesired phenotypes. We highlight emerging strategies to overcome these barriers, such as the use of UFA-selective acyltransferases, coordinated manipulation of DAG source pools, suppression of competing endogenous enzymes, and exploitation of TAG remodeling mechanisms. This integrated synthesis provides a conceptual framework for logic-based engineering of oilseeds with enhanced UFA content by offering new avenues for sustainable biomanufacturing of valuable lipids.

acyltransferase specificity↗

Multigrid Reduction in Time for Chaotic Dynamical Systems

As CPU clock speeds have stagnated and high performance computers continue to have ever higher core counts, increased parallelism is needed to take advantage of these new architectures. Traditional serial time-marching schemes can be a significant bottleneck, as many types of simulations require large numbers of time-steps which must be computed sequentially. Parallel-in-time schemes, such as the Multigrid Reduction in Time (MGRIT) method, remedy this by parallelizing across time-steps and have shown promising results for parabolic problems. However, chaotic problems have proved more difficult, since chaotic initial value problems (IVPs) are inherently ill-conditioned. MGRIT relies on a hierarchy of successively coarser time-grids to iteratively correct the solution on the finest time-grid, but due to the nature of chaotic systems, small inaccuracies on the coarser levels can be greatly magnified and lead to poor coarse-grid corrections. Here we introduce a modified MGRIT algorithm based on an existing quadratically converging nonlinear extension to the multigrid Full Approximation Scheme (FAS), as well as a novel time-coarsening scheme. Together, these approaches better capture long-term chaotic behavior on coarse-grids and greatly improve convergence of MGRIT for chaotic IVPs. Further, we introduce a novel low-memory variant of the algorithm for solving chaotic PDEs with MGRIT which not only solves the IVP, but also provides estimates for the unstable Lyapunov vectors of the system. Finally, we provide supporting numerical results for the Lorenz system and demonstrate parallel speedup for the chaotic Kuramoto–Sivashinsky PDE over a significantly longer time-domain than in previous works.

97 MATHEMATICS AND COMPUTING↗

Data for Purple Acid Phosphatase2 Stimulates a Futile Cycle of Lipid Synthesis and Degradation, and Mitigates the Negative Growth Effects of Triacylglycerol Accumulation in Vegetative Tissues

Storage lipids (mostly triacylglycerols, TAGs) serve as an important energy and carbon reserve in plants, and hyperaccumulation of TAG in vegetative tissues can have negative effects on plant growth. Purple acid phosphatase2 (PAP2) was previously shown to affect carbon metabolism and boost plant growth. However, the effects of PAP2 on lipid metabolism remain unknown. Here, we demonstrated that PAP2 can stimulate a futile cycle of fatty acid (FA) synthesis and degradation, and mitigate negative growth effects associated with high accumulation of TAG in vegetative tissues. Constitutive expression of PAP2 in Arabidopsis thaliana enhanced both lipid synthesis and degradation in leaves and led to a substantial increase in seed oil yield. Suppressing lipid degradation in a PAP2-overexpressing line by disrupting sugar-dependent1 (SDP1), a predominant TAG lipase, significantly elevated vegetative TAG content and improved plant growth. Diverting FAs from membrane lipids to TAGs in PAP2-overexpressing plants by constitutively expressing phospholipid:diacylglycerol acyltransferase1 (PDAT1) greatly increased TAG content in vegetative tissues without compromising biomass yield. These results highlight the potential of combining PAP2 with TAG-promoting factors to enhance carbon assimilation, FA synthesis and allocation to TAGs for optimized plant growth and storage lipid accumulation in vegetative tissues.

Biomass Analytics↗

Data for Sustainable Co-Production of Plant Lipids and Cellulosic Sugars from Transgenic Energycane at an Industrially Relevant Scale: A Proof of Concept for Alternative Feedstocks

Development of sustainable and scalable technologies to convert lignocellulosic biomass to biofuels is critical to achieving carbon neutrality. The potential of transgenic bioenergy crops as a renewable source of sugars and lipids has been demonstrated at bench-scale. However, scaling up these processes is important for holistic analysis. Here proof-of-concept for chemical-free hydrothermal pretreatment of transgenic energycane-oilcane line L13 at an industrially relevant scale to recover vegetative lipids along with cellulosic sugars is presented. Pilot-scale processing of 97 kg of transgenic energycane-oilcane L13 stems and high solids pretreatment of bagasse enhanced the recovery of cellulosic glucose and xylose by 5-fold as compared to untreated bagasse and helped in the enrichment of vegetative lipids in the biomass residues which allowed its recovery at the end of the bioprocess. Palmitic and oleic acids were the predominant fatty acids (FAs) extracted from stems and leaves. The processing did not affect lipid composition. The efficiency of lipid recovery from untreated biomass was 75.9% which improved to 88.7% upon pretreatment. The vegetative tissues of transgenic energycane-oilcane L13 contained 0.42 metric tons/hectare of lipids. Processing vegetative tissues yielded 0.38 metric tons/hectare of lipids. This approaches an oil yield similar to soybean (global average 0.44 metric tons/hectare) and is almost twice as high as the oil yield from sugarcane engineered to hyperaccumulate lipids (0.20 metric tons/hectare). The study suggests that further optimization by state-of-the-art metabolic engineering and biomass processing can establish transgenic bioenergy crops for commercial drop-in fuel production.

Biomass Analytics↗

Reactor System Facility Modification to Detect Compromised Human Machine Interfaces

This study focuses on a multi-layered Industrial Control System (ICS)/Operational Technology (OT) security architecture to aid in the discovery and mitigation of compromised Human Machine Interface (HMI)/Instrumentation & Control (I&C) based systems for modifying a prototypical reactor condition test facility called the Flowing Autoclave System (FAS) at Idaho National Laboratory (INL). This is achieved through a three-layered combination of network security solutions, hash-based algorithms, and blockchain technologies. Hash algorithms are mathematical functions used to generate a predetermined set of fixed-length values. They are widely used in computer security to verify the integrity of system information and data, both on a local network and the wider internet. Even small amounts of unauthorized system modification will cause the hash algorithm to output a set of characters that deviate significantly from its original value. Assisting secure hash functions, blockchain technology is a secure and distributed technology used to provide an immutable set of records replicated on all devices within a decentralized network. Blockchain offers a cost-effective solution to detect system compromise by providing a traceable breadcrumb trail of all network activity and data modification happening on a system. If both are used in conjunction with network monitoring tools, the integration of this three-pronged approach can become an asset in detecting suspected system compromises before any real damage can occur.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SUHMO: an adaptive mesh refinement SUbglacial Hydrology MOdel v1.0

Abstract. Water flowing under ice sheets and glaciers can have a strong influence on ice dynamics, particularly through pressure changes, suggesting that a comprehensive ice sheet model should include the effect of basal hydrology. Modeling subglacial hydrology remains a challenge, however, mainly due to the range of spatial and temporal scales involved – from subglacial channels to vast subglacial lakes. Additionally, networks of subglacial drainage channels dynamically evolve over time. To address some of these challenges, we have developed an adaptive mesh refinement (AMR) model based on the Chombo software framework. We extend the model proposed by Sommers et al. (2018) with a small but significant change to accommodate the transition from unresolved to resolved flow features. We handle the strong nonlinearities present in the equations by resorting to an efficient nonlinear full approximation scheme multigrid (FAS-MG) algorithm. We outline the details of the algorithm and present convergence analysis results demonstrating its good performance. Additionally, we present results validating our approach, using test cases from the Subglacial Hydrology Model Intercomparison Project (SHMIP) (de Fleurian et al., 2018). We finish by presenting a more complex, 100 km-by-100 km synthetic test case with peaks and valleys that we use to investigate the effective pressure distribution as the number of AMR levels increases. These preliminary results suggest that a minimum spatial resolution is needed to properly capture channel features, but additional work is required to precisely quantify this and its impact on accurately modeling the coupled ice sheet–hydrology system. The efficiency of our approach, relying on localized refinement, is also demonstrated. Future work will include coupling the SUbglacial Hydrology MOdel (SUHMO) with the BISICLES AMR ice sheet model (Cornford et al., 2013), both built on the same numerical framework.

58 GEOSCIENCES↗