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At least 91 records · Page 5

Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the lambda-exchange of free energy perturbation (FEP). Further, two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/lambda-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasma-Assisted Chemical-Looping Combustion: Low-Temperature Methane and Ethylene Oxidation with Nickel Oxide

The chemical reaction network of low-temperature plasma-assisted oxidation of methane (CH 4 ) and ethylene (C 2 H 4 ) with nickel oxide (NiO) was investigated in a heated plasma reactor through time-dependent species measurements by electron-ionization molecular beam mass spectrometry (EI-MBMS). Methane (ethylene) oxidation by NiO was explored in temperature ranges from 300-700 °C (300-500 °C) and 300-800 °C (300-600°C) for the plasma and non-plasma conditions, respectively. Significant enhancement of methane oxidation was observed with plasma between 400 and 500 °C, where no oxidation was observed under non-plasma conditions. For the oxidation of methane at higher temperatures three different oxidation stages were observed: I) a period of complete oxidation, II) a period of incomplete CO oxidation, and III) a period of carbon buildup. For the C 2 H 4 experiments, and unlike the CH 4 experiments, the plasma resulted in a significant amount of new intermediate oxygenated species, such as CH 2 O, CH 3 OH, C 2 H 4 O, and C 2 H 6 O. Carbon deposits were observed under both methane and ethylene conditions and verified by X-ray photoelectron spectroscopy (XPS). ReaxFF simulations were performed for the oxidation of CH 4 and C 2 H 4 in a non-plasma environment. The simulated intermediates and products largely agree with the species measured in the experiments, though the predicted intermediate oxygenated species such as CH 2 O and C 2 H 6 O were not observed in experiments under non-plasma conditions. A reaction pathway analysis for CH 4 and C 2 H 4 reacting with NiO was created based on the observed species from the MBMS spectra, along with ReaxFF simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗

Electrochemical production of H 2 O 2 on palladium-based clusters driven by metal–support interaction

Utilizing palladium (Pd) clusters as active sites offers a promising route to minimize noble metal consumption in electrochemical hydrogen peroxide (H 2 O 2 ) production. In this work, we present a synthesis approach for anchoring Pd-based clusters onto carbon-supported CeO 2 nanosubstrates to enable efficient H 2 O 2 generation via the two-electron oxygen reduction reaction (ORR) pathway. By systematically adjusting Pd loading, we evaluated its impact on H 2 O 2 yield and production rate. The catalyst with the lowest Pd content (0.027 wt%) exhibited outstanding performance, achieving 97% H 2 O 2 selectivity, 94.2 faradaic efficiency at 0.7 V vs. RHE, and a peak production rate of 195.8 mol g Pd −1 h −1 . A formulation containing 0.35 wt% Pd delivered a peak ORR mass activity nearly three times as high as that of commercial 10 wt% Pd/C, while retaining comparable electrochemical stability. These enhancements are attributed to synergistic effects among isolated PdO clusters, CeO 2 nanocrystals, and the conductive carbon support, which together facilitate oxygen adsorption and promote the two-electron ORR pathway. Analysis after accelerated durability testing further revealed a tendency toward cluster agglomeration and mass transfer from smaller to larger nanocrystals, indicative of a coarsening mechanism. Overall, this study underscores the promise of low-Pd PdO–CeO 2 –carbon hybrid catalysts for scalable and efficient H 2 O 2 electrosynthesis, while highlighting stability as a critical area for future improvement.

36 MATERIALS SCIENCE↗

Low-energy physics in neutrino LArTPCs

Here, in this paper, we review scientific opportunities and challenges related to detection and reconstruction of low-energy (less than 100 MeV) signatures in liquid argon time-projection chamber (LArTPC) neutrino detectors. LArTPC neutrino detectors designed for performing precise long-baseline oscillation measurements with GeV-scale accelerator neutrino beams also have unique sensitivity to a range of physics and astrophysics signatures via detection of event features at and below the few tens of MeV range. In addition, low-energy signatures are an integral part of GeV-scale accelerator neutrino interaction final-states, and their reconstruction can enhance the oscillation physics sensitivities of LArTPC experiments. New physics signals from accelerator and natural sources also generate diverse signatures in the low-energy range, and reconstruction of these signatures can increase the breadth of Beyond the Standard Model scenarios accessible in LArTPC-based searches. A variety of experimental and theory-related challenges remain to realizing this full range of potential benefits. Neutrino interaction cross-sections and other nuclear physics processes in argon relevant to sub-hundred-MeV LArTPC signatures are poorly understood, and improved theory and experimental measurements are needed; pion decay-at-rest sources and charged particle and neutron test beams are ideal facilities for improving this understanding. There are specific calibration needs in the low-energy range, as well as specific needs for control and understanding of radiological and cosmogenic backgrounds. Low-energy signatures, whether steady-state or part of a supernova burst or larger GeV-scale event topology, have specific triggering, DAQ and reconstruction requirements that must be addressed outside the scope of conventional GeV-scale data collection and analysis pathways. Novel concepts for future LArTPC technology that enhance low-energy capabilities should also be explored to help address these challenges.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Metabolic engineering of the oleaginous yeast Yarrowia lipolytica PO1f for production of erythritol from glycerol

Abstract Background Sugar alcohols are widely used as low-calorie sweeteners in the food and pharmaceutical industries. They can also be transformed into platform chemicals. Yarrowia lipolytica , an oleaginous yeast, is a promising host for producing many sugar alcohols. In this work, we tested whether heterologous expression of a recently identified sugar alcohol phosphatase (PYP) from Saccharomyces cerevisiae would increase sugar alcohol production in Y. lipolytica . Results Y. lipolytica was found natively to produce erythritol, mannitol, and arabitol during growth on glucose, fructose, mannose, and glycerol. Osmotic stress is known to increase sugar alcohol production, and was found to significantly increase erythritol production during growth on glycerol. To better understand erythritol production from glycerol, since it was the most promising sugar alcohol, we measured the expression of key genes and intracellular metabolites. Osmotic stress increased the expression of several key genes in the glycerol catabolic pathway and the pentose phosphate pathway. Analysis of intracellular metabolites revealed that amino acids, sugar alcohols, and polyamines are produced at higher levels in response to osmotic stress. Heterologous overexpression of the sugar alcohol phosphatase increased erythritol production and glycerol utilization in Y. lipolytica . We further increased erythritol production by increasing the expression of native glycerol kinase (GK), and transketolase (TKL). This strain was able to produce 27.5 ± 0.7 g/L erythritol from glycerol during batch growth and 58.8 ± 1.68 g/L erythritol during fed-batch growth in shake-flasks experiments. In addition, the glycerol utilization was increased by 2.5-fold. We were also able to demonstrate that this strain efficiently produces erythritol from crude glycerol, a major byproduct of the biodiesel production. Conclusions We demonstrated the application of a promising enzyme for increasing erythritol production in Y. lipolytica . We were further able to boost production by combining the expression of this enzyme with other approaches known to increase erythritol production in Y. lipolytica . This suggest that this new enzyme provides an orthogonal route for boosting production and can be stacked with existing designs known to increase sugar alcohol production in yeast such as Y. lipolytica . Collectively, this work establishes a new route for increasing sugar alcohol production and further develops Y. lipolytica as a promising host for erythritol production from cheap substrates such as glycerol.

09 BIOMASS FUELS↗

Global patterns of diversity and metabolism of microbial communities in deep-sea hydrothermal vent deposits

When deep-sea hydrothermal fluids mix with cold oxygenated fluids, minerals precipitate out of solution and form hydrothermal deposits. These actively venting deep-sea hydrothermal deposits support a rich diversity of thermophilic microorganisms which are involved in a range of carbon, sulfur, nitrogen, and hydrogen metabolisms. Global patterns of thermophilic microbial diversity in deep-sea hydrothermal ecosystems have illustrated the strong connectivity between geological processes and microbial colonization, but little is known about the genomic diversity and physiological potential of these novel taxa. Here we explore this genomic diversity in 42 metagenomes from four deep-sea hydrothermal vent fields and a deep-sea volcano collected from 2004 to 2018 and document their potential implications in biogeochemical cycles. Our dataset represents 3635 metagenome-assembled genomes encompassing 511 novel and recently identified genera from deep-sea hydrothermal settings. Some of the novel bacterial (107) and archaeal genera (30) that were recently reported from the deep-sea Brothers volcano were also detected at the deep-sea hydrothermal vent fields, while 99 bacterial and 54 archaeal genera were endemic to the deep-sea Brothers volcano deposits. We report some of the first examples of medium- (≥ 50% complete, ≤ 10% contaminated) to high-quality (> 90% complete, < 5% contaminated) MAGs from phyla and families never previously identified, or poorly sampled, from deep-sea hydrothermal environments. We greatly expand the novel diversity of Thermoproteia, Patescibacteria (Candidate Phyla Radiation, CPR), and Chloroflexota found at deep-sea hydrothermal vents and identify a small sampling of two potentially novel phyla, designated JALSQH01 and JALWCF01. Metabolic pathway analysis of metagenomes provides insights into the prevalent carbon, nitrogen, sulfur, and hydrogen metabolic processes across all sites and illustrates sulfur and nitrogen metabolic “handoffs” in community interactions. We confirm that Campylobacteria and Gammaproteobacteria occupy similar ecological guilds but their prevalence in a particular site is driven by shifts in the geochemical environment. Our study of globally distributed hydrothermal vent deposits provides a significant expansion of microbial genomic diversity associated with hydrothermal vent deposits and highlights the metabolic adaptation of taxonomic guilds. Collectively, our results illustrate the importance of comparative biodiversity studies in establishing patterns of shared phylogenetic diversity and physiological ecology, while providing many targets for enrichment and cultivation of novel and endemic taxa.

59 BASIC BIOLOGICAL SCIENCES↗

Metabolic Engineering of the Oleaginous Yeast Yarrowia lipolytica PO1f for Production of Erythritol from Glycerol

Yarrowia lipolytica was found natively to produce erythritol, mannitol, and arabitol during growth on glucose, fructose, mannose, and glycerol. Osmotic stress is known to increase sugar alcohol production, and was found to significantly increase erythritol production during growth on glycerol. To better understand erythritol production from glycerol, since it was the most promising sugar alcohol, we measured the expression of key genes and intracellular metabolites. Osmotic stress increased the expression of several key genes in the glycerol catabolic pathway and the pentose phosphate pathway. Analysis of intracellular metabolites revealed that amino acids, sugar alcohols, and polyamines are produced at higher levels in response to osmotic stress. Heterologous overexpression of the sugar alcohol phosphatase increased erythritol production and glycerol utilization in Y. lipolytica . We further increased erythritol production by increasing the expression of native glycerol kinase (GK), and transketolase (TKL). These data show the growth and titers produced.

Conversion↗

Low-Energy Physics in Neutrino LArTPCs

In this white paper, we outline some of the scientific opportunities and challenges related to detection and reconstruction of low-energy (less than 100 MeV) signatures in liquid argon time-projection chamber (LArTPC) detectors. Key takeaways are summarized as follows. 1) LArTPCs have unique sensitivity to a range of physics and astrophysics signatures via detection of event features at and below the few tens of MeV range. 2) Low-energy signatures are an integral part of GeV-scale accelerator neutrino interaction final states, and their reconstruction can enhance the oscillation physics sensitivities of LArTPC experiments. 3) BSM signals from accelerator and natural sources also generate diverse signatures in the low-energy range, and reconstruction of these signatures can increase the breadth of BSM scenarios accessible in LArTPC-based searches. 4) Neutrino interaction cross sections and other nuclear physics processes in argon relevant to sub-hundred-MeV LArTPC signatures are poorly understood. Improved theory and experimental measurements are needed. Pion decay-at-rest sources and charged particle and neutron test beams are ideal facilities for experimentally improving this understanding. 5) There are specific calibration needs in the low-energy range, as well as specific needs for control and understanding of radiological and cosmogenic backgrounds. 6) Novel ideas for future LArTPC technology that enhance low-energy capabilities should be explored. These include novel charge enhancement and readout systems, enhanced photon detection, low radioactivity argon, and xenon doping. 7) Low-energy signatures, whether steady-state or part of a supernova burst or larger GeV-scale event topology, have specific triggering, DAQ and reconstruction requirements that must be addressed outside the scope of conventional GeV-scale data collection and analysis pathways.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Light Water Reactor Sustainability Program: Upgrade of EMRALD to a Modern JavaScript-based Framework

Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is a software tool developed at Idaho National Laboratory for researching the capabilities of dynamic probabilistic risk assessment. It provides a simple interface to represent complex interactions often seen when developing dynamic models. EMRALD can also interface with other applications by modifying inputs, running, and using their results within EMRALD for dynamic and integrated assessment. This report goes over the work performed as part of the Risk-Informed Systems Analysis Pathway under the Light Water Reactor Sustainability program to upgrade the EMRALD software.

97 MATHEMATICS AND COMPUTING↗

Tools And Methods to Analyze Plant Outage Schedule and Assist Schedulers in Improving Outage Resilience

Refueling outages of nuclear power plants (NPPs) are considered one of the most critical phases throughout the plant lifetime. In such instances, tens of thousands of activities (e.g., maintenance, surveillance) are performed in a short amount of time (typically 2-3 weeks unless major backfitting or modernization projects are carried out) by a large number of crews (e.g., electricians, mechanics) that are hired as contractors. As a consequence, a plant outage can be expensive not only in terms of costs (e.g., contractor labor, material), but also in terms of loss generation since the plant is taken off the grid during the full outage duration (an indicative metric is about 1.2M$/day of loss of revenue). Thus, there is a continuous need to decrease the economic impact of outages on plant finances. This can be done by: decreasing the frequency of plant outages (e.g., from 18 to 24 months), reducing the time to complete the outage, and reducing the risk of outage delays. The Optimization of Outage Activities project under the Risk Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program focuses on developing tools and methods to support NPPs with outage schedule optimization. The developed tools and methods are designed to analyze plant outage schedule with the goal of identify critical elements in the schedule that might pose a high risk of delays. These methods and tools can be considered resource-centric in the sense that they address outage challenges as a resource optimization problem. In this context, resources are either time and crews; outage delays occurs when either (or both) resources are insufficient to complete the set of tasks assigned at a specific time instant of the outage. This report provides details on how plant resources (time and crews) can be allocated in such a way that delays are minimized. In this respect, two classes of methods have been developed: the first one focuses on the time resource and how variability of the time to complete outage tasks may impact outage delays. The second one integrates available resources to assess when dailies activities should be performed such that the risk of outage delays are minimized.

97 MATHEMATICS AND COMPUTING↗

Thermodynamic and Kinetic Modeling of Co-utilization of Glucose and Xylose for 2,3-BDO Production by Zymomonas mobilis

Prior engineering of the ethanologen Zymomonas mobilis has enabled it to metabolize xylose and to produce 2,3-butanediol (2,3-BDO) as a dominant fermentation product. When co-fermenting with xylose, glucose is preferentially utilized, even though xylose metabolism generates ATP more efficiently during 2,3-BDO production on a BDO-mol basis. To gain a deeper understanding of Z. mobilis metabolism, we first estimated the kinetic parameters of the glucose facilitator protein of Z. mobilis by fitting a kinetic uptake model, which shows that the maximum transport capacity of glucose is seven times higher than that of xylose, and glucose is six times more affinitive to the transporter than xylose. With these estimated kinetic parameters, we further compared the thermodynamic driving force and enzyme protein cost of glucose and xylose metabolism. It is found that, although 20% more ATP can be yielded stoichiometrically during xylose utilization, glucose metabolism is thermodynamically more favorable with 6% greater cumulative Gibbs free energy change, more economical with 37% less enzyme cost required at the initial stage and sustains the advantage of the thermodynamic driving force and protein cost through the fermentation process until glucose is exhausted. Glucose-6-phosphate dehydrogenase (g6pdh), glyceraldehyde-3-phosphate dehydrogenase (gapdh) and phosphoglycerate mutase (pgm) are identified as thermodynamic bottlenecks in glucose utilization pathway, as well as two more enzymes of xylose isomerase and ribulose-5-phosphate epimerase in xylose metabolism. Acetolactate synthase is found as potential engineering target for optimized protein cost supporting unit metabolic flux. Pathway analysis was then extended to the core stoichiometric matrix of Z. mobilis metabolism. Growth was simulated by dynamic flux balance analysis and the model was validated showing good agreement with experimental data. Dynamic FBA simulations suggest that a high agitation is preferable to increase 2,3-BDO productivity while a moderate agitation will benefit the 2,3-BDO titer. Taken together, this work provides thermodynamic and kinetic insights of Z. mobilis metabolism on dual substrates, and guidance of bioengineering efforts to increase hydrocarbon fuel production.

23-butanediol↗

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes

Background: Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics. Methods: Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls. Results: The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects. Conclusions: Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

60 APPLIED LIFE SCIENCES↗

Persistent Expression Changes of Fibrosis-Related Genes in the Lung Tissues of Rats Exposed to Lunar Dust Particles

The Moon's surface is covered by a layer of fine, potential reactive dust. Lunar dust contain about 1‐2% of very fine respirable dust (less than 3 micrometers). The habitable area of any lunar landing vehicle and outpost would inevitably be contaminated with lunar dust that could pose a health risk. The purpose of the study is to evaluate the toxicity of Apollo moon dust in rodents to assess the health risk of dust exposures to humans. One of the particular interests in the study is to evaluate dust‐induced changes of the expression of fibrosis‐related genes, and to identify specific signaling pathways involved in lunar dustinduced toxicity. F344 rats were exposed for 4 weeks (6h/d; 5d/wk) in nose‐only inhalation chambers to concentrations of 0 (control air), 2.1, 6.8, 21, and 61 milligrams per cubic meters of lunar dust. Five rats per group were euthanized at 1 day, 1 week, 1 month, and 3 months after the last inhalation exposure. The bronchoalveolar lavage fluid (BALF) was collected by lavaging with phosphate‐buffered saline (PBS). A zymosan‐induced luminolbased chemiluminescence assay was used to assess the activity of BAL cells. The lavaged lung tissue was snap frozen in LN2 and total RNA was isolated using the Qigen RNeasy kit. The expression of 84 fibrosisrelated genes were analyzed using the RT2 Profiler PCR Array technique. The expression of 18 genes of interest were further measured using real‐time PCR technique in all the samples. 10 out of 18 genes of interest showed persistently significant expression changes in the local lung tissue exposed to lunar dust, indicating a prolonged proinflammatory response. The expressions of several of these genes were dose‐ and time‐dependent and were significantly correlated with other pathological parameters. The potential signaling pathways and upstream regulators were further analyzed using IPA pathway analysis tool based on the gene expression data. The data presented in this study, for the first time, explore the molecular mechanisms of lunar dust induced toxicity, contributing not only the risk assessment for future space exploration, but also understandings of the dust‐induced toxicity in humans on earth.

Zhang, Ye↗

Gene Expression Profiling of Lung Tissue of Rats Exposed to Lunar Dust Particles

The purpose of the study is to analyze the dynamics of global gene expression changes in the lung tissue of rats exposed to lunar dust particles. Multiple pathways and transcription factors were identified using the Ingenuity Pathway Analysis tool, showing the potential networks of these signaling regulations involved in lunar dust‐induced prolonged proflammatory response and toxicity. The data presented in this study, for the first time, explores the molecular mechanisms of lunar dust induced toxicity. This work contributes not only to the risk assessment for future space exploration, but also to the understanding of the dust‐induced toxicity to humans on earth.

Zhang, Ye↗

NASA Space Radiation Risk Project: Overview and Recent Results

The NASA Space Radiation Risk project is responsible for integrating new experimental and computational results into models to predict risk of cancer and acute radiation syndrome (ARS) for use in mission planning and systems design, as well as current space operations. The project has several parallel efforts focused on proving NASA's radiation risk projection capability in both the near and long term. This presentation will give an overview, with select results from these efforts including the following topics: verification, validation, and streamlining the transition of models to use in decision making; relative biological effectiveness and dose rate effect estimation using a combination of stochastic track structure simulations, DNA damage model calculations and experimental data; ARS model improvements; pathway analysis from gene expression data sets; solar particle event probabilistic exposure calculation including correlated uncertainties for use in design optimization.

Blattnig, Steve R.↗

Differential Responses to Mechanostimulation in Embryonic Stem Cells Versus the Embryoid Body Model of Development Assessed at Single Cell RNA-Seq Resolution

Mechanicalforces generated by gravity have shaped life on Earth and impact gene expression and morphogenesis during early development. In contrast disuse canreduce normal mechanical loading, resulting in altered cell and tissue function. Although loading in adult mammals is known to promote increased cell proliferation and differentiation, little is known about how cells respondto this stimulusduring early development. In this study we sought to understand, with single cell RNA-sequencing resolution, how a 60-minute pulse of 50xg hypergravity-generated 5kPa hydrostatic pressure, influences transcriptomic regulation of developmental processes in the Embryoid Body (EB) model. Our study included both day-9 EBs and progenitor mouse embryonic stem cells (ESCs) with or without the hydrostatic pressurepulse. Single cell tSNE mapping shows limited transcriptome shifts in response to thispulse in either ESCs or EBs; this pulse,however, induces greater positional shifts in EB mapping compared to ESCs, indicating the influence of mechanotransduction is more pronounced in later states of cell commitment within the developmental program.We assessed ESCs and EBs for differentially expressed (DE) genes with hydrostatic pressurepulse and found approximately 1/3 DE genes were shared. However, gene ontology (GO) pathway analysis show that EBs have choreographed responses associated with upregulation ofpathways formulticellular development, mechanical signal transduction, and DNA damage repair. Cluster transcriptome analysis of the EBs showsmechanostimulationpromotes maintenance of transitory cell phenotypes in early development,including EB cluster co-expression of markers for progenitor, post-implant epiblast and primitive endoderm phenotypes versus expression exclusivity in the non-pulsed clusters. Pseudotime analysisidentified three branching cell types susceptible tohydrostatic pressureinduction of cell fate decisions. In summary, this study provides novel evidence that ESC maintenance and EB development can be regulated by mechanostimulation,and that stem cells committed to a differentiation program are more sensitive to force-induced changes to their transcriptome.

Cassandra Juran↗