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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Atmospheric methane consumption in arid ecosystems acts as a reverse chimney and is accelerated by plant-methanotroph biomes

Drylands cover one-third of the Earth’s surface and are one of the largest terrestrial sinks for methane. Understanding the structure–function interplay between members of arid biomes can provide critical insights into mechanisms of resilience toward anthropogenic and climate-change-driven environmental stressors—water scarcity, heatwaves, and increased atmospheric greenhouse gases. This study integrates in situ measurements with culture-independent and enrichment-based investigations of methane-consuming microbiomes inhabiting soil in the Anza-Borrego Desert, a model arid ecosystem in Southern California, United States. The atmospheric methane consumption ranged between 2.26 and 12.73 μmol m 2 h −1 , peaking during the daytime at vegetated sites. Metagenomic studies revealed similar soil-microbiome compositions at vegetated and unvegetated sites, with Methylocaldum being the major methanotrophic clade. Eighty-four metagenome-assembled genomes were recovered, six represented by methanotrophic bacteria (three Methylocaldum , two Methylobacter , and uncultivated Methylococcaceae ). The prevalence of copper-containing methane monooxygenases in metagenomic datasets suggests a diverse potential for methane oxidation in canonical methanotrophs and uncultivated Gammaproteobacteria. Five pure cultures of methanotrophic bacteria were obtained, including four Methylocaldum . Genomic analysis of Methylocaldum isolates and metagenome-assembled genomes revealed the presence of multiple stand-alone methane monooxygenase subunit C paralogs, which may have functions beyond methane oxidation. Furthermore, these methanotrophs have genetic signatures typically linked to symbiotic interactions with plants, including tryptophan synthesis and indole-3-acetic acid production. Based on in situ fluxes and soil microbiome compositions, we propose the existence of arid-soil reverse chimneys, an empowered methane sink represented by yet-to-be-defined cooperation between desert vegetation and methane-consuming microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cyanobacterial Phycobilisome Allostery as Revealed by Quantitative Mass Spectrometry

Phycobilisomes (PBSs) are the major photosynthetic light-harvesting complexes in cyanobacteria and red algae. PBS, a multisubunit protein complex, has two major interfaces that comprise intrinsically disordered regions (IDRs): rod–core and core-membrane. IDRs do not form regular, three-dimensional structures on their own. Their presence in the photosynthetic pigment–protein complexes portends their structural and functional importance. A recent model suggests that PB-loop, an IDR located on the PBS subunit ApcE and C-terminal extension (CTE) of the PBS subunit ApcG, forms a structural protrusion on the PBS core-membrane side, facing the thylakoid membrane. Here, the structural synergy between the rod–core region and the core-membrane region was investigated using quantitative mass spectrometry (MS). The AlphaFold-predicted CpcG-CTE structure was first modeled onto the PBS rod–core region, guided and justified by the isotopically encoded structural MS data. Quantitative cross-linking MS analysis revealed that the structural proximity of the PB-loop in ApcE and ApcG-CTE is significantly disturbed in the absence of six PBS rods, which are attached to PBS via CpcG-CTE, indicative of drastic conformational changes and decreased structural integrity. Furthermore, these results suggest that CpcG-rod attachment on the PBS rod–core side is essentially required for the PBS core-membrane structural assembly. The hypothesized long-range synergy between the rod–core interface (where the orange carotenoid protein also functions) and the terminal energy emitter of PBS must have important regulatory roles in PBS core assembly, light-harvesting, and excitation energy transmission. These data also lend strategies that genetic truncation of the light-harvesting antennas aimed for improved photosynthetic productivity must rely on an in-depth understanding of their global structural integrity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Binding of the substrate analog methanol in the oxygen-evolving complex of photosystem II in the D1-N87A genetic variant of cyanobacteria

The solar water-splitting protein complex, photosystem II (PSII), catalyzes one of the most energetically demanding reactions in nature by using light energy to drive a catalyst capable of oxidizing water. The water oxidation reaction is catalyzed at the Mn 4 Ca-oxo cluster in the oxygen-evolving complex (OEC), which cycles through five light-driven S-state intermediates (S 0 –S 4 ). A detailed mechanism of the reaction remains elusive as it requires knowledge of the delivery and binding of substrate water in the higher S-state intermediates. In this paper, we use two-dimensional (2D) hyperfine sublevel correlation spectroscopy, in conjunction with quantum mechanics/molecular mechanics (QM/MM) and density functional theory (DFT), to probe the binding of the substrate analog, methanol, in the S 2 state of the D1-N87A variant of PSII from Synechocystis sp. PCC 6803. The results indicate that the size and specificity of the “narrow” channel is altered in D1-N87A PSII, allowing for the binding of deprotonated 13 C-labeled methanol at the Mn4(IV) ion of the catalytic cluster in the S 2 state. This has important implications on the mechanistic models for water oxidation in PSII.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Sex Determination and Ovarian Development in Reptiles and Amphibians: From Genetic Pathways to Environmental Influences

Background: Reptiles and amphibians provide untapped potential for discovering how a diversity of genetic pathways and environmental conditions are incorporated into developmental processes that can lead to similar functional outcomes. These groups display a multitude of reproductive strategies, and whereas many attributes are conserved within groups and even across vertebrates, several aspects of sexual development show considerable variation. Summary: Here, in this review, we focus our attention on the development of the reptilian and amphibian ovary. First, we review and describe the events leading to ovarian development, including sex determination and ovarian maturation, through a comparative lens. We then describe how these events are influenced by environmental factors, focusing on temperature and exposure to anthropogenic chemicals. Lastly, we identify critical knowledge gaps and future research directions that will be crucial to moving forward in our understanding of ovarian development and the influences of the environment in reptiles and amphibians. Key Messages: Reptiles and amphibians provide excellent models for understanding the diversity of sex determination strategies and reproductive development. However, a greater understanding of the basic biology of these systems is necessary for deciphering the adaptive and potentially disruptive implications of embryo-by-environment interactions in a rapidly changing world.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

GA-Based Voltage Optimization of Distribution Feeder with High-Penetration of DERs Using Megawatt-Scale Units

In this paper, genetic algorithm (GA)-based voltage optimization of a modified IEEE-34 node distribution feeder with high penetration of distributed energy resources (DERs) is proposed using two megawatt-scale reactive power sources. Traditional voltage support units present in distribution grids are not suitable for DER-rich feeders, while voltage support using small-scale DERs present in the feeder requires considerable communication effort to reach a global solution. In this work, two megawatt-scale units are placed to improve the voltage profile across the IEEE 34-node feeder, which has been modified to include several PV units and an energy storage unit. The megawatt-scale units are optimized using GA for fast and accurate operation. The performance of the proposed scheme is verified using simulation results with a multi-platform setup where the modified IEEE-34 node feeder is modeled in OpenDSS while the GA optimization scheme is programmed in MATLAB.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Chemical and genetic characterization of the ungrouped pallasite Lieksa

The meteorite Lieksa was found in 2017 in Löpönvaara, Finland, and later donated to the Finnish Museum of Natural History. Here, we report siderophile element concentrations, genetic isotopic data, and a metal–silicate segregation age for the meteorite. The ~280 g Lieksa is ~80% metal and ~20% silicate and oxide inclusions by volume, with the inclusions consisting primarily of Fe-rich olivine. Due to Lieksa's silicate content, coupled with a texture characterized by metal enclosing the silicates, it has been classified as a pallasite. Lieksa's olivine and bulk chemical characteristics are distinct from those of the known pallasite and iron meteorite groups, consistent with its classification as ungrouped. The meteorite exhibits a flat, chondrite-normalized highly siderophile element pattern, consistent with an origin as an early crystallization product from a metallic melt with chondritic relative abundances. Molybdenum, Ru, and 183 W isotopic data indicate that Lieksa formed in the non-carbonaceous (NC) domain of the solar nebula. Radiogenic 182 W abundances for Lieksa yield a model metal–silicate segregation age of 1.5 ± 0.8 Myr after calcium-aluminum-rich inclusion formation, which is within the range established for other NC-type pallasite and iron meteorite parent bodies.

58 GEOSCIENCES↗
DOE OSTI2023

Kinetic Growth of Multicomponent Microcompartment Shells

An important goal of systems and synthetic biology is to produce high value chemical species in large quantities. Microcompartments, which are protein nanoshells encapsulating catalytic enzyme cargo, could potentially function as tunable nanobioreactors inside and outside cells to generate these high value species. Modifying the morphology of microcompartments through genetic engineering of shell proteins is one viable strategy to tune cofactor and metabolite access to encapsulated enzymes. However, this is a difficult task without understanding how changing interactions between the many different types of shell proteins and enzymes affect microcompartment assembly and shape. Here, we use multiscale molecular dynamics and experimental data to describe assembly pathways available to microcompartments composed of multiple types of shell proteins with varied interactions. As the average interaction between the enzyme cargo and the multiple types of shell proteins is weakened, the shell assembly pathway transitions from (i) nucleating on the enzyme cargo to (ii) nucleating in the bulk and then binding the cargo as it grows to (iii) an empty shell. Atomistic simulations and experiments using the 1,2-propanediol utilization microcompartment system demonstrate that shell protein interactions are highly varied and consistent with our multicomponent, coarse-grained model. Furthermore, our results suggest that intrinsic bending angles control the size of these microcompartments. Altogether, our simulations and experiments provide guidance to control microcomparmtent size and assembly by modulating the interactions between shell proteins.

defects↗
DOE OSTI2025

Sulfoquinovose is exclusively metabolized by the gut microbiota and degraded differently in mice and humans

Abstract Background Sulfoquinovose (SQ) is a green-diet-derived sulfonated glucose and a selective substrate for a limited number of human gut bacteria. Complete anaerobic SQ degradation via interspecies metabolite transfer to sulfonate-respiring bacteria produces hydrogen sulfide, which has dose- and context-dependent health effects. Here, we studied potential SQ degradation by the mammalian host and the impact of SQ supplementation on human and murine gut microbiota diversity and metabolism. Results 13 CO 2 breath tests with germ-free C57BL/6 mice gavaged with 13 C-SQ were negative. Also, SQ was not degraded by human intestinal cells in vitro, indicating that SQ is not directly metabolized by mice and humans. Addition of increasing SQ concentrations to human fecal microcosms revealed dose-dependent responses of the microbiota and corroborated the relevance ofAgathobacter rectalisandBilophila wadsworthiain cooperative degradation of SQ to hydrogen sulfide via interspecies transfer of 2,3-dihydroxy-1-propanesulfonate (DHPS). Similar to the human gut microbiome, the genetic capacity for SQ or DHPS degradation is sparsely distributed among bacterial species in the gut of conventional laboratory mice.Escherichia coliandEnterocloster clostridioformiswere identified as primary SQ degraders in the mouse gut. SQ and DHPS supplementation experiments with conventional laboratory mice and their intestinal contents showed that SQ was incompletely catabolized to DHPS. Although someE. clostridioformisgenomes encode an extended sulfoglycolytic pathway for both SQ and DHPS fermentation, SQ was only degraded to DHPS by a mouse-derivedE. clostridioformisstrain. Conclusions Our findings suggest that SQ is solely a nutrient for the gut microbiota and not for mice and humans, emphasizing its potential as a prebiotic. SQ degradation by the microbiota of conventional laboratory mice differs from the human gut microbiota by absence of DHPS degradation activity. Hence, the microbiota of conventional laboratory mice does not fully represent the SQ metabolism in humans, indicating the need for alternative model systems to assess the impact of SQ on human health. This study advances our understanding of how individual dietary compounds shape the microbial community structure and metabolism in the gut and thereby potentially influence host health.

Microbiology↗
DOE OSTI2020

Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease

Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, setting, an participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main outcomes and measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.

60 APPLIED LIFE SCIENCES↗
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 OSTI2021

Dynamics-Based Peptide–MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen–major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Finally, our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Extensive cellular multi-tasking within Bacillus subtilis biofilms

Bacillus subtilis is a soil-dwelling bacterium that can form biofilms, or communities of cells surrounded by a self-produced extracellular matrix. In biofilms, genetically identical cells often exhibit heterogeneous transcriptional phenotypes, so that subpopulations of cells carry out essential yet costly cellular processes that allow the entire population to thrive. Surprisingly, the extent of phenotypic heterogeneity and the relationships between subpopulations of cells within biofilms of even in well-studied bacterial systems like B. subtilis remains largely unknown. To determine relationships between these subpopulations of cells, we created 182 strains containing pairwise combinations of fluorescent transcriptional reporters for the expression state of 14 different genes associated with potential cellular subpopulations. We determined the spatial organization of the expression of these genes within biofilms using confocal microscopy, which revealed that many reporters localized to distinct areas of the biofilm, some of which were co-localized. We used flow cytometry to quantify reporter co-expression, which revealed that many cells “multi-task,” simultaneously expressing two reporters. These data indicate that prior models describing B. subtilis cells as differentiating into specific cell types, each with a specific task or function, were oversimplified. Only a few subpopulations of cells, including surfactin and plipastatin producers, as well as sporulating and competent cells, appear to have distinct roles based on the set of genes examined here. These data will provide us with a framework with which to further study and make predictions about the roles of diverse cellular phenotypes in B. subtilis biofilms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Comparative differential cuproproteomes of Rhodobacter capsulatus reveal novel copper homeostasis related proteins

Abstract Copper (Cu) is an essential, but toxic, micronutrient for living organisms and cells have developed sophisticated response mechanisms towards both the lack and the excess of Cu in their environments. In this study, we achieved a global view of Cu-responsive changes in the prokaryotic model organism Rhodobacter capsulatus using label-free quantitative differential proteomics. Semi-aerobically grown cells under heterotrophic conditions in minimal medium (∼0.3 μM Cu) were compared with cells supplemented with either 5 μM Cu or with 5 mM of the Cu-chelator bathocuproine sulfonate. Mass spectrometry based bottom-up proteomics of unfractionated cell lysates identified 2430 of the 3632 putative proteins encoded by the genome, producing a robust proteome dataset for R. capsulatus. Use of biological and technical replicates for each growth condition yielded high reproducibility and reliable quantification for 1926 of the identified proteins. Comparison of cells grown under Cu-excess or Cu-depleted conditions to those grown under minimal Cu-sufficient conditions revealed that 75 proteins exhibited statistically significant (p < 0.05) abundance changes, ranging from 2- to 300-fold. A subset of the highly Cu-responsive proteins was orthogonally probed using molecular genetics, validating that several of them were indeed involved in cellular Cu homeostasis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Variation in morpho-physiological and metabolic responses to low nitrogen stress across the sorghum association panel

Abstract Background Access to biologically available nitrogen is a key constraint on plant growth in both natural and agricultural settings. Variation in tolerance to nitrogen deficit stress and productivity in nitrogen limited conditions exists both within and between plant species. However, our understanding of changes in different phenotypes under long term low nitrogen stress and their impact on important agronomic traits, such as yield, is still limited. Results Here we quantified variation in the metabolic, physiological, and morphological responses of a sorghum association panel assembled to represent global genetic diversity to long term, nitrogen deficit stress and the relationship of these responses to grain yield under both conditions. Grain yield exhibits substantial genotype by environment interaction while many other morphological and physiological traits exhibited consistent responses to nitrogen stress across the population. Large scale nontargeted metabolic profiling for a subset of lines in both conditions identified a range of metabolic responses to long term nitrogen deficit stress. Several metabolites were associated with yield under high and low nitrogen conditions. Conclusion Our results highlight that grain yield in sorghum, unlike many morpho-physiological traits, exhibits substantial variability of genotype specific responses to long term low severity nitrogen deficit stress. Metabolic response to long term nitrogen stress shown higher proportion of variability explained by genotype specific responses than did morpho-pysiological traits and several metabolites were correlated with yield. This suggest, that it might be possible to build predictive models using metabolite abundance to estimate which sorghum genotypes will exhibit greater or lesser decreases in yield in response to nitrogen deficit, however further research needs to be done to evaluate such model.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Development of emerging model microorganisms: Megasphaera elsdenii for biomass and organic acid upgrading to fuels and chemicals

The metabolic diversity of microorganisms in nature represents a largely untapped source of valuable compounds that are difficult or impossible to produce in the limited number of available model systems. Efforts to produce longer-chain alcohols, such as hexanol, in organisms like Escherichia coli have met with limited success; production of C6 and larger products remains low, highlighting the challenges of extending chain elongation pathways beyond a single cycle. Megasphaera elsdenii naturally condenses acetyl-CoA to efficiently generate C4–C8 organic acids, making it a promising candidate for producing fuels and chemicals from lactate and plant-derived carbohydrates. This high native flux through the chain elongation pathway offers the potential for higher yields and titers of medium-chain products, such as hexanol, compared to conventional hosts. Recent advances—most notably the development of a transformation method for M. elsdenii—have further opened the organism to detailed physiological studies and bioengineering. While full development of M. elsdenii as a hexanol-producing platform was not achieved, significant progress was made in understanding its metabolism and building foundational genetic tools for future engineering.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Direct sensitivity analysis on the parameterization of crystal plasticity models

Various methods for calibrating crystal plasticity finite element (CPFE) models lead to non-unique input parameter values, which subsequently introduce uncertainty in the predicted mechanical response. Sensitivity analysis (SA) conducted on crystal plasticity models is used to identify how variability in these parameters contribute to output uncertainty. Traditional SA on CPFE parameters uses simplified surrogate models to save computational time. However, the accuracy of the surrogate models depends on the quantity of training data used, and any modeling error can propagate into the SA results, potentially affecting their reliability. In this work, the elementary effects test (EET) method, a global SA technique using direct CPFE simulations was employed, and the results obtained were compared with the First Order Second Moment (FOSM) method. ExaConstit, an open-source GPU-enabled CPFE code, was used to perform the simulations and direct SA. The EET method was accurately able to capture the non-linear effects of all the input parameters on the output and is a valuable approach for reliably attributing parameter sensitivities in CPFE models. Based on the results, efficient strategies to perform future parameter calibration and SA are discussed. Additionally, the SA trends observed in different single crystal orientations closely mirrored the activity of the slip systems.

Elementary Effects Test↗
DOE OSTI2022

High–throughput measurement of plant fitness traits with an object detection method using Faster R–CNN

Revealing the contributions of genes to plant phenotype is frequently challenging because loss-of-function effects may be subtle or masked by varying degrees of genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. An image segmentation-based method using the software ImageJ and an object detection-based method using the Faster Region-based Convolutional Neural Network (R-CNN) algorithm were used for measuring two Arabidopsis fitness traits: seed and fruit counts. The segmentation-based method was error-prone (correlation between true and predicted seed counts, r 2 = 0.849) because seeds touching each other were undercounted. By contrast, the object detection-based algorithm yielded near perfect seed counts (r 2 = 0.9996) and highly accurate fruit counts (r 2 = 0.980). Comparing seed counts for wild-type and 12 mutant lines revealed fitness effects for three genes; fruit counts revealed the same effects for two genes. Our study provides analysis pipelines and models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits when studying gene functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Sr-Nd-Pb isotope systematics of Australasian tektites: Implications for the nature and composition of target materials and possible volatile loss of Pb

The Australasian tektite (AAT) strewn field is the largest strewn field on the Earth with about ~10–30% coverage, both land and ocean, but a clearly identified source impact crater is absent despite the young age of AAT of ca. 790 ka. A genetic link between the Australasian tektites and their unequivocal parental materials is therefore largely impossible to establish. Nevertheless, the nature of the parental materials and the extent of volatilization can be constrained using the splash form tektites, carrying the chemical signatures of high-temperature processes, and the layered (so-called Muong Nong-type) tektites, which are less chemically homogenized and exceptionally abundant in the AAT field. New high-precision Sr, Nd and Pb isotopic measurements were obtained for a chemically and petrographically well-characterized suite of AAT, which included the Muong Nong-type (MN-AAT) with precisely known field locations in Laos and splash forms (SF-AAT) from different parts of the strewn field. Additionally, optically dark and light zones of the MN-AAT were also separately analyzed. Homogeneous ε Nd values from -11.8 to -11.2, combined with a narrow range of two-stage Nd model ages from 1.67 to 1.72 Ga for the entire AAT suite, point to a well-mixed source, in terms of REE, of the crustal segment from which the sedimentary material for tektites was ultimately derived. The Sr isotopic data largely overlap for SF-AAT and MN-AAT ( 87 Sr/ 86 Sr = 0.71636–0.72021) and indicate Paleozoic to Mesozoic sedimentary parentage. However, late Neogene to early Quaternary re-deposition and formation of a thick silt-sized sedimentary section with vertical stratification is required to comply with 10Be data. Lead isotope systematics documents at least three different components which can perhaps be represented by different mineral phases, such as feldspar, zircon, organic matter adsorbed on young sediments etc., sorted during fluvial transport and final deposition. In addition, the SF-AAT have systematically lower Pb contents than the MN-AAT, and generally show isotopically heavier Pb isotopic ratios. This is theoretically consistent with a preferential volatilization of lighter Pb isotopes during evaporation and considerably larger Pb loss from SF-AAT when compared to MN-AAT. Nevertheless, further experimental work would be necessary to unambiguously distinguish kinetic fractionation from source mixing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗