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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Design of a high power 8 MeV electron beam injector for the LERF

We present the beamline design for a high power 8 MeV electron injector to be installed at the Low Energy Recirculator Facility (LERF). The injector is designed to provide beam power of up to 80 kW for testing positron source target candidates. We discuss the results of beam dynamics simulations conducted using the General Particle Tracer (GPT) software, where electromagnetic beamline elements were optimized using multi-objective genetic algorithm tools. Additionally, we present preliminary studies on secondary particle generation from both rotating solid and free surface liquid metal jet targets described elsewhere in this workshop.

Lizarraga-Rubio, Victor [Thomas Jefferson National↗
DOE OSTI2026

Design of a high power 8 MeV electron beam injector for the LERF

Here, we present the beamline design for a high power 8 MeV electron injector to be installed at the Low Energy Recirculator Facility (LERF). The injector is designed to provide beam power of up to 80 kW for testing positron source target candidates. We discuss the results of beam dynamics simulations conducted using the General Particle Tracer (GPT) software, where electromagnetic beamline elements were optimized using multi-objective genetic algorithm tools. Additionally, we present preliminary studies on secondary particle generation from both rotating solid and free surface liquid metal jet targets described elsewhere in this workshop.

Lizarraga-Rubio, Victor Manuel [Thomas Jefferson N↗
DOE OSTI2021

Predictive Models of Genetic Redundancy in Arabidopsis thaliana

Abstract Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features derived from accumulating omics and mutant phenotype data is yet to be established. In addition, the relative importance of these features for genetic redundancy remains largely unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including posttranslational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used significantly affected model performance based on holdout, testing phenotype data. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. We also explored the potential reasons underlying mispredictions and limitations of our studies. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Stream and ocean hydrodynamics mediate partial migration strategies in an amphidromous Hawaiian goby

Abstract Partial migration strategies, in which some individuals migrate but others do not, are widely observed in populations of migratory animals. Such patterns could arise via variation in migratory behaviors made by individual animals, via genetic variation in migratory predisposition, or simply by variation in migration opportunities mediated by environmental conditions. Here we use spatiotemporal variation in partial migration across populations of an amphidromous Hawaiian goby to test whether stream or ocean conditions favor completing its life cycle entirely within freshwater streams rather than undergoing an oceanic larval migration. Across 35 watersheds, microchemical analysis of otoliths revealed that most adult Awaous stamineus were freshwater residents (62% of n = 316 in 2009, 83% of n = 274 in 2011), but we found considerable variation among watersheds. We then tested the hypothesis that the prevalence of freshwater residency increases with the stability of stream flows and decreases with the availability of dispersal pathways arising from ocean hydrodynamics. We found that streams with low variation of daily discharge were home to a higher incidence of freshwater residents in each survey year. The magnitude of the shift in freshwater residency between survey years was positively associated with predicted interannual variability in the success of larval settlement in streams on each island based on passive drift in ocean currents. We built on these findings by developing a theoretical model of goby life history to further evaluate whether mediation of migration outcomes by stream and ocean hydrodynamics could be sufficient to explain the range of partial migration frequency observed across populations. The model illustrates that the proportion of larvae entering the ocean and differential survival of freshwater‐resident versus ocean‐going larvae are plausible mechanisms for range‐wide shifts in migration strategies. Thus, we propose that hydrologic variation in both ocean and stream environments contributes to spatiotemporal variation in the prevalence of migration phenotypes in A. stamineus . Our empirical and theoretical results suggest that the capacity for partial migration could enhance the persistence of metapopulations of diadromous fish when confronted with variable ocean and stream conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Apomixis in Farmers’ Fields: Overview, Case Studies from Forage Grasses and Considerations for Future Apomictic Crops

Apomixis occurs naturally in several commercially important species from diverse plant families. While in some of these species apomixis is yet to be exploited in breeding schemes aimed at fixing heterosis, genetic progress and cultivar development, in other species apomixis has been integrated at different stages of breeding. Some of the most relevant examples come from the subfamily Panicoideae, the second largest subfamily of the Poaceae, and are the main focus of this review. The subfamily encompasses many tropical and sub-tropical grasses and grains of worldwide economic importance. Apomictic tropical forages are prime examples of how apomixis can be used and exploited in the development of marketable cultivars, which are essential to the meat and milk production industries globally. The main commercial forages used as grass pastures covering millions of hectares in tropical and sub-tropical regions are polyploids exhibiting gametophytic apomixis that belong to the genus Urochloa spp. (brachiariagrasses) and to the species Megathyrsus maximus (guineagrass). Buffel grass (Cenchrus ciliaris) and Paspalum spp. are other important apomictic forages bred and used in these regions. Breeding involves large germplasm collections from the centers of origin of the species, and for most of them, sexually reproducing diploid plants have been found. Chromosomically duplicated plants that maintain sexual reproduction are used in crosses with apomictic genotypes for the development and selection of cultivars to be marketed or used as progenitors in subsequent breeding cycles. The peculiarities of each genus/species breeding programs, the cultivars obtained from these programs, and the impact of use of marker assisted selection in cultivar development are presented. In addition, the test or implementation of new technologies such as high throughput phenotyping, and the use of machine learning methods for trait prediction and genomic selection are positively impacting the selection and speed of development of new polyploid apomictic cultivars. Furthermore, genetic transformation techniques, including genome editing, provide an additional layer for design of tailor-made, customer-oriented cultivars.

Cenchrus↗
DOE OSTI2020

Development of genetic tools for the thermophilic filamentous fungus Thermoascus aurantiacus

Abstract Background Fungal enzymes are vital for industrial biotechnology, including the conversion of plant biomass to biofuels and bio-based chemicals. In recent years, there is increasing interest in using enzymes from thermophilic fungi, which often have higher reaction rates and thermal tolerance compared to currently used fungal enzymes. The thermophilic filamentous fungus Thermoascus aurantiacus produces large amounts of highly thermostable plant cell wall-degrading enzymes. However, no genetic tools have yet been developed for this fungus, which prevents strain engineering efforts. The goal of this study was to develop strain engineering tools such as a transformation system, a CRISPR/Cas9 gene editing system and a sexual crossing protocol to improve the enzyme production. Results Here, we report Agrobacterium tumefaciens -mediated transformation (ATMT) of T. aurantiacus using the hph marker gene, conferring resistance to hygromycin B. The newly developed transformation protocol was optimized and used to integrate an expression cassette of the transcriptional xylanase regulator xlnR , which led to up to 500% increased xylanase activity. Furthermore, a CRISPR/Cas9 gene editing system was established in this fungus, and two different gRNAs were tested to delete the pyrG orthologue with 10% and 35% deletion efficiency, respectively. Lastly, a sexual crossing protocol was established using a hygromycin B- and a 5-fluoroorotic acid-resistant parent strain. Crossing and isolation of progeny on selective media were completed in a week. Conclusion The genetic tools developed for T. aurantiacus can now be used individually or in combination to further improve thermostable enzyme production by this fungus.

09 BIOMASS FUELS↗
DOE OSTI2020

A novel active optimization approach for rapid and efficient design space exploration using ensemble machine learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) which fits high-level information about the response surface, and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner, is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected to be evaluated using expensive function evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. This methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface. The performance of the new active learning approach is compared with traditional global optimization methods, namely micro-genetic algorithm (pGA) and particle swarm optimization (PSO). It is demonstrated that the new optimizer is able to reach the global optimum much faster with a significantly fewer number of function evaluations. Subsequently, the new optimizer is also applied to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is again found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to particle swarm and genetic algorithm-based optimization techniques.

Machine learning, active learning, design optimiza↗
DOE OSTI2024

Optimization and Experimental Validation of Annular Finned PCM-HX for a Domestic Hot Water Heater Application

The load profile for domestic water heating is time-dependent and can result in high energy demand during peak operating times. Shifting this peak load can have significant environmental and economic impacts. Phase change material (PCM)-based thermal energy storage (TES) is a potentially useful technology for peak load shifting in domestic hot water (DHW) applications thanks to its high latent heat and energy density. In this study, an annular finned-tube PCM-HX design concept was optimized for a load-shifting TES unit to meet the Department of Energy standard for a medium-usage DHW heater using a resistance-capacitance model (RCM) integrated with a Multi-Objective Genetic Algorithm. The optimized design comprised 70 identical annular finned-tube PCM-HX units connected in parallel and utilizing RT62HC as the PCM. A single PCM-HX unit was prototyped and tested in a vertically oriented setup with upward heat transfer fluid (HTF) flow. The hot water supply time was defined based on a cutoff temperature of 51.7°C. The as-designed mass flow rate (1.5 g/s) was tested to assess the performance of the prototyped PCM-HX unit for RCM validation. For the experimental investigation, RTD sensor bundles measured HTF temperature at the PCM-HX inlet and outlet, and a Coriolis flow meter accurately measured the HTF mass flow rate. The simulated discharging power underpredicted the experimental result by about 12%, and the simulated hot water supply time underpredicted the experimental result by approximately 13% for the as-designed mass flow rate (1.5 g/s). The average deviation of the hot water supply temperature between the experimental and RCM results during the complete PCM solidification process was 1.3 K for the as-designed mass flow rate. The overall good agreement between the experimental and RCM results provides confidence that computationally efficient models such as RCM can be utilized for design optimization of PCM-HXs.

42 ENGINEERING↗
DOE OSTI2026

Genetic variations and their interaction with thirdhand smoke exposure on anxiety and memory in Collaborative Cross mice

Thirdhand smoke (THS) is linked to adverse health effects, but the effect of genetic variations on behavioral outcomes is poorly understood. To investigate this, we assessed anxiety- and memory-related behaviors in 820 mice from 21 strains of the genetically diverse Collaborative Cross (CC) mouse that were exposed to THS from 4 through 10 weeks of age. Anxiety was evaluated with a light/dark box assay with a previously established risk score system. Females were generally more sensitive: THS reduced anxiety risk in strains CC013, CC019, and CC051, but increased risk in CC036 and CC061, while males showed no significant effects. Memory was tested using passive avoidance: impairments were observed in both sexes in CC016 and CC019, with sex-dependent effects in CC002 and CC051. A genome-wide association study identified 2,347 SNPs associated with anxiety and 1,568 SNPs with memory, with 32 and 85 SNPs, respectively, interacting with THS exposure. Enrichment analyses revealed distinct biological processes underlying susceptibility, including axonogenesis, synapse organization, cognition, and learning and memory. KEGG pathway analysis identified distinct genetic pathways, including GTPase binding and GTPase regulatory activity, that act as critical molecular switches in the brain that regulate synaptic plasticity, dendritic spine structure, and neuronal signaling, directly influencing anxiety-like behaviors and memory formation. These findings show that THS exposure affects neurobehavioral outcomes in a sex- and genotype-dependent manner, highlighting critical gene-environment interactions and providing a foundation for mechanistic insights into THS neurotoxicity

Anxiety↗
DOE OSTI2025

Combining genome-wide association studies and expression quantitative trait nucleotide mapping with molecular and genetic validations to identify transcriptional networks regulating drought tolerance in Populus

Objectives: (i). To deploy a large-scale experimental drought trial for up to 1000 unique genotypes of Populus equipping the sites with controlled irrigation and drought treatments that are fully automated and monitored. FULLY COMPLETED (ii) To test the hypothesis that a suite of traits identified for drought tolerance in P. nigra can be measured in drought and control treatments in the wide germplasm collection of P. trichocarpa. FULLY COMPLETED (iii) To use established and novel GWAS model approaches to identify gene loci linked to drought tolerance traits on interest in P. trichocarpa. FULLY COMPLETED (iv) To undertake comparative analysis of GWAS results for drought tolerance traits in P. nigra and P. trichocarpa. PARTIALLY COMPLETED – remains active (v) Using RNAseq in P. trichocarpa, in droughted and control treatments to identify cis- and trans-regulated eQTN. FULLY COMPLETED (vi) Validate up to 50 cis-QTNs, from network hubs using transient protoplast assays. FULLY COMPLETED (vii) To establish Agrobacterium-based gene editing protocols in Populus. FULLY COMPLETED (viii) To utilize early leads from previous research to investigate at least 6 candidate genes for drought tolerance in Populus. FULLY COMPLETED (ix) To validate up to 20 candidate genes for drought tolerance in P. trichocarpa refined from the long-list tested in the transient assays for cis-acting hub gene targets. PARTIALLY COMPLETED- remains active.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Cyanobacterial Biofertilizer Production by Guanidine-Producing Enzymes

Cyanobacterial production of a biofertilizer shows promise as an environmentally benign alternative to conventional nitrogen fertilizers, reducing environmental and energy burdens through light-driven nitrogen and carbon fixation. One route to realizing the potential for a nitrogen-rich, slow-releasing biofertilizer involves the genetic engineering of cyanobacteria to produce guanidine. Recent advances have demonstrated enzymatic guanidine production in cyanobacteria, but an understanding of cyanobacterial guanidine metabolism is still limited. This Perspective highlights strategies and opportunities for cyanobacterial guanidine production in a Design−Build−Test−Learn cycle. Exploring new guanidine-producing enzymes via phylogenetics could expand candidate enzymes, while understanding the metabolism of substrates can identify constraints and opportunities in substrate utilization. Additionally, guanidine sensing and export are crucial areas of study to enable continuous fertilizer production and stable nitrogen flux. These strategies will guide the development of advanced nitrogen biofertilizer strategies for the agricultural sector.

09 BIOMASS FUELS↗
DOE OSTI2020

Modular cell-free expression plasmids to accelerate biological design in cells

Industrial biotechnology aims to produce high-value products from renewable resources. This can be challenging because model microorganisms—organisms that are easy to use like Escherichia coli—often lack the machinery required to utilize desired feedstocks like lignocellulosic biomass or syngas. Non-model organisms, such as Clostridium, are industrially proven and have desirable metabolic features but have several hurdles to mainstream use. Namely, these species grow more slowly than conventional laboratory microbes, and genetic tools for engineering them are far less prevalent. To address these hurdles for accelerating cellular design, cell-free synthetic biology has matured as an approach for characterizing non-model organisms and rapidly testing metabolic pathways in vitro. Unfortunately, cell-free systems can require specialized DNA architectures with minimal regulation that are not compatible with cellular expression. In this work, we develop a modular vector system that allows for T7 expression of desired enzymes for cell-free expression and direct Golden Gate assembly into Clostridium expression vectors. Utilizing the Joint Genome Institute’s DNA Synthesis Community Science Program, we designed and synthesized these plasmids and genes required for our projects allowing us to shuttle DNA easily between our in vitro and in vivo experiments. We next validated that these vectors were sufficient for cell-free expression of functional enzymes, performing on par with the previous state-of-the-art. Lastly, we demonstrated automated six-part DNA assemblies for Clostridium autoethanogenum expression with efficiencies ranging from 68% to 90%. We anticipate this system of plasmids will enable a framework for facile testing of biosynthetic pathways in vitro and in vivo by shortening development cycles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Mini‐synplastomes for plastid genetic engineering

Summary In the age of synthetic biology, plastid engineering requires a nimble platform to introduce novel synthetic circuits in plants. While effective for integrating relatively small constructs into the plastome, plastid engineering via homologous recombination of transgenes is over 30 years old. Here we show the design–build–test of a novel synthetic genome structure that does not disturb the native plastome: the ‘mini‐synplastome’. The mini‐synplastome was inspired by dinoflagellate plastome organization, which is comprised of numerous minicircles residing in the plastid instead of a single organellar genome molecule. The first mini‐synplastome in plants was developed in vitro to meet the following criteria: (i) episomal replication in plastids; (ii) facile cloning; (iii) predictable transgene expression in plastids; (iv) non‐integration of vector sequences into the endogenous plastome; and (v) autonomous persistence in the plant over generations in the absence of exogenous selection pressure. Mini‐synplastomes are anticipated to revolutionize chloroplast biotechnology, enable facile marker‐free plastid engineering, and provide an unparalleled platform for one‐step metabolic engineering in plants.

Occhialini, Alessandro↗
DOE OSTI2021

Design and Optimization of a Gas-Cooled, Airfoil Fin Microchannel Heat Exchanger

High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, was analyzed and optimized using a design of experiments with artificial intelligence and machine learning techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin PCHEs has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure was developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. STAR-CCM+ was used to analyze a simplified two-channel configuration where five parameters were varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods were compared for generating surrogate models – a 5D polynomial and a regression neural network. A response surface approximation was created from the surrogate models and input to a genetic algorithm. The genetic algorithm identified a set of optimal points on the Pareto front. The optimal geometry was found across six channel Reynolds numbers ranging from 1000 to 5000 to analyze how varying inlet conditions affects the optimal design. A set of optimal designs that maximizes heat transfer and minimizes pressure drop was identified, and a thermal stress analysis was performed on the optimal design. This work has developed a digital framework for the expedient topology design and evaluation of PCHE designs for gas-cooled microreactor applications. Correlations for the Nusselt number and Darcy friction factor were developed that can be useful for thermal hydraulic analyses using system codes. A thermal stress analysis was conducted and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.

42 ENGINEERING↗
DOE OSTI2020

Genetic identification of 91 poplar cultivars based on SSR markers

Accurate genetic identification and relationship analysis of poplar cultivars is necessary to establish commercial poplar plantations and select suitable breeding strategies. In this study, 91 poplar cultivars belonging to four sections (Aigeiros, Tacamahaca, Populus and Turanga) and inter/intra-sectional hybrids were genotyped using 18 polymorphic simple sequence repeat (SSR) markers. In total, 222 alleles were amplified with an average of 12.3 alleles per marker. The mean polymorphic information content and power of discrimination were 0.706 and 0.813, respectively. Five SSR markers (ORPM_103, ORPM_247, GCPM_1048, GCPM_1255 and LG_X_19) constituted a core fingerprint and were sufficient to identify all the tested cultivars. With some notable exceptions, cultivars of the same species generally clustered together in cluster (UPGMA) and ordination (PCO) analyses. Flow cytometry indicated that 11 poplar cultivars were triploid. Among these, seven had three alleles at some loci, suggesting that SSR markers could indicate the ploidy level to some extent. This study provides useful genetic information for the identification and protection of poplar cultivars in China and offers a guideline for the selection of poplar crossing parents based on ploidy level and genetic relationships.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Curvature Energetics Determined by Alchemical Simulation on Four Topologically Distinct Lipid Phases

The relative curvature energetics of two lipids are tested using thermodynamic integration (TI) on four topologically distinct lipid phases. Simulations use TI to switch between choline headgroup lipids (POPC; that prefers to be flat) and ethanolamine headgroup lipids (POPE; that prefer, for example, the inner monolayer of vesicles). Here, the thermodynamical moving of the lipids between planar, inverse hexagonal (H II ), cubic (Q II ; Pn3m space group), and vesicle topologies reveals differences in material parameters that were previously challenging to access. The methodology allows for predictions of two important lipid material properties: the difference in POPC/POPE monolayer intrinsic curvature (ΔJ 0 ) and the difference in POPC/POPE monolayer Gaussian curvature modulus (Δ$\bar{κ_m}$), both of which are connected to the energetics of topological variation. Analysis of the TI data indicates that, consistent with previous experiment and simulation, the J 0 of POPE is more negative than POPC (ΔJ 0 = –0.018 ± 0.001 Å –1 ). The theoretical framework extracts significant differences in $\bar{κ_m}$ of which POPE is less negative than POPC by 2.0 to 4.0 kcal/mol. The range of these values is determined by considering subsets of the simulations, and disagreement between these subsets suggests separate mechanical parameters at very high curvature. Finally, the fit of the TI data to the model indicates that the position of the pivotal plane of curvature is not constant across topologies at high curvature. Overall, the results offer insights into lipid material properties, the limits of a single HC model, and how to test them using simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗