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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Neurons die with heightened but functional macro- and chaperone mediated autophagy upon increased amyloid-ß induced toxicity with region-specific protection in prolonged intermittent fasting

Highlights: • Macroautophagy (MA) is strongly engaged upon APP overexpression and remains high over time. • APP colocalization with macroautophagy components remains increased until late, promoting continuous recruitment to the autophagy machinery. • Robust chaperone-mediated autophagy (CMA) engagement is observed in late APP overexpression. • Macroautophagic flux during APP overexpression is preserved, even at late time points, suggesting functional autophagy in the face of apoptosis onset. • Macroautophagy impairment increases markers of amyloidogenesis and further exacerbates the onset of apoptotic cell death. Alzheimer's disease (AD) is a devastating neurodegenerative condition with significant socio-economic impact that is exacerbated by the rapid increase in population aging, particularly impacting already burdened health care systems of poorly resourced countries. Accumulation of the amyloid-β (Aβ) peptide, generated through amyloid precursor protein (APP) processing, manifesting in senile plaques, is a well-established neuropathological feature. Aβ plays a key role in driving synaptic dysfunction, neuronal cell loss, glial cell activation and oxidative stress associated with the pathogenesis of AD. Thus, the enhanced clearance of Aβ peptide though modulation of the mechanisms that regulate intracellular Aβ metabolism and clearance during AD progression have received major attention. Autophagy, a lysosome-based major proteolytic pathway, plays a crucial role in intracellular protein quality control and has been shown to contribute to the clearance of Aβ peptide. However, to what extent autophagy activity remains upregulated and functional in the process of increasing Aβ neurotoxicity is largely unclear. Here, we investigated the extent of neuronal toxicity in vitro by characterising autophagic flux, the expression profile of key amyloidogenic proteins, and proteins associated with prominent subtypes of the autophagy pathway to dissect the interplay between the engagement of proteolytic pathways and cell death onset in the context of APP overexpression. Moreover, we assessed the neuroprotective effects of a caloric restriction regime in vivo on the modulation of autophagy in specific brain regions. Our results reveal that autophagy is upregulated in the presence of high levels of APP and Aβ and remains heightened and functional despite concomitant apoptosis induction, suggestive of a mismatch between autophagy cargo generation and clearance capacity. These findings were confirmed when implementing a prolonged intermittent fasting (IF) intervention in a model of paraquat-induced neuronal toxicity, where markers of autophagic activity were increased, while apoptosis onset and lipid peroxidation were robustly decreased in brain regions associated with neurodegeneration. This work highlights that especially caloric restriction mimetics and controlled prolonged IF may indeed be a highly promising therapeutic strategy at all stages of AD-associated pathology progression, for a cell-inherent and cell specific augmentation of Aβ clearance through the powerful engagement of autophagy and thereby robustly contributing to neuronal protection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Ligand- and Structure-Based Analysis of Deep Learning-Generated Potential α2a Adrenoceptor Agonists

The α2a adrenoceptor is a particularly medically relevant subtype of the G protein-couple receptor family. Unfortunately, high-throughput techniques aimed at producing novel drug leads targeted to this receptor have been largely unsuccessful due to the complex pharmacology of adrenergic receptors. As such, cutting-edge in silico ligand- and structure-based assessment and de novo deep learning methods are well-positioned to provide new insights into protein-ligand interactions and potential active compounds. In this work, we (i) collect a dataset of α2a adrenoceptor agonists and provide it as a resource for the drug design community; (ii) use the dataset as a basis to generate candidate active structures via deep learning; and (iii) apply computational ligand- and structure-based analysis techniques to gain new insight into α2a adrenoceptor agonists and assess the quality of the computer-generated compounds. Additionally, we further describe how such assessment techniques can be applied to putative chemical probes with a case study involved proposed medetomidine-based probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2009

Chromosomal Aberrations in DNA Repair Defective Cell Lines: Comparisons of Dose Rate and Radiation Quality

Chromosome aberration yields were assessed in DNA double-strand break repair (DSB) deficient cells after acute doses of gamma-rays or high-LET iron nuclei, or low dose-rate (0.018 Gy/hr) gamma-rays. We studied several cell lines including fibroblasts deficient in ATM (product of the gene that is mutated in ataxia telangiectasia patients) or NBS (product of the gene mutated in the Nijmegen breakage syndrome), and gliomablastoma cells that are proficient or lacking in DNA-dependent protein kinase, DNA-PK activity. Chromosomes were analyzed using the fluorescence in-situ hybridization (FISH) chromosome painting method in cells at the first division post-irradiation and chromosome aberrations were identified as either simple exchanges (translocations and dicentrics) or complex exchanges (involving >2 breaks in 2 or more chromosomes). Gamma radiation induced higher yields of both simple and complex exchanges in the DSB repair defective cells than in the normal cells. The quadratic dose-response terms for both chromosome exchange types were significantly higher for the ATM and NBS defective lines than for normal fibroblasts. However, the linear dose-response term was significantly higher only for simple exchanges in the NBS cells. Large increases in the quadratic dose response terms indicate the important roles of ATM and NBS in chromatin modifications that facilitate correct DSB repair and minimize aberration formation. Differences in the response of AT and NBS deficient cells at lower doses suggests important questions about the applicability of observations of radiation sensitivity at high dose to low dose exposures. For all iron nuclei irradiated cells, regression models preferred purely linear and quadratic dose responses for simple and complex exchanges, respectively. All the DNA repair defective cell lines had lower Relative biological effectiveness (RBE) values than normal cells, the lowest being for the DNA-PK-deficient cells, which was near unity. To further investigate the sensitivity differences for low and low high doses, we performed chronic low dose-rate irradiation, and have begun studies with ATM and Nibrin inhibitors and siRNA knockout of these proteins. Results support the conclusion that for the endpoint of simple chromosomal aberrations (translocation or dicentrics), the increased radiation sensitivity of AT cells found at high doses (>1 Gy) does not carry over to low doses or doserates, while NBS cells show increased sensitivity for both high and low dose exposures.

George, K. A.↗
DOE OSTI2020

MEMOTE for standardized genome-scale metabolic model testing

Reconstructing metabolic reaction networks enables the development of testable hypotheses of an organism’s metabolism under different conditions. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Gene–protein–reaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

Pollination and embryo development in Brassica rapa L. in microgravity

Plant reproduction under spaceflight conditions has been problematic in the past. In order to determine what aspect of reproductive development is affected by microgravity, we studied pollination and embryo development in Brassica rapa L. during 16 d in microgravity on the space shuttle (STS-87). Brassica is self-incompatible and requires mechanical transfer of pollen. Short-duration access to microgravity during parabolic flights on the KC-135A aircraft was used initially to confirm that equal numbers of pollen grains could be collected and transferred in the absence of gravity. Brassica was grown in the Plant Growth Facility flight hardware as follows. Three chambers each contained six plants that were 13 d old at launch. As these plants flowered, thin colored tape was used to indicate the date of hand pollination, resulting in silique populations aged 8-15 d postpollination at the end of the 16-d mission. The remaining three chambers contained dry seeds that germinated on orbit to produce 14-d-old plants just beginning to flower at the time of landing. Pollen produced by these plants had comparable viability (93%) with that produced in the 2-d-delayed ground control. Matched-age siliques yielded embryos of equivalent developmental stage in the spaceflight and ground control treatments. Carbohydrate and protein storage reserves in the embryos, assessed by cytochemical localization, were also comparable. In the spaceflight material, growth and development by embryos rescued from siliques 15 d after pollination lagged behind the ground controls by 12 d; however, in the subsequent generation, no differences between the two treatments were found. The results demonstrate that while no stage of reproductive development in Brassica is absolutely dependent upon gravity, lower embryo quality may result following development in microgravity.

short duration↗
NASA NTRS2022

Are Soybean Models Ready for Climate Change Food Impact Assessments?

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO 2 concentration [CO 2 ] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO 2 ]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO 2 ] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO 2 ] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO 2 ] and temperature is needed to reduce the uncertainty from the individual models.

Agricultural Model Inter-comparison and Improvemen↗
DOE OSTI2024

Structural studies of intrinsically disordered MLL -fusion protein AF9 in complex with peptidomimetic inhibitors

AF9 (MLLT3) and its paralog ENL(MLLT1) are members of the YEATS family of proteins with important role in transcriptional and epigenetic regulatory complexes. These proteins are two common MLL fusion partners in MLL -rearranged leukemias. The oncofusion proteins MLL-AF9/ENL recruit multiple binding partners, including the histone methyltransferase DOT1L, leading to aberrant transcriptional activation and enhancing the expression of a characteristic set of genes that drive leukemogenesis. The interaction between AF9 and DOT1L is mediated by an intrinsically disordered C-terminal ANC1 homology domain (AHD) in AF9, which undergoes folding upon binding of DOT1L and other partner proteins. We have recently reported peptidomimetics that disrupt the recruitment of DOT1L by AF9 and ENL, providing a proof-of-concept for targeting AHD and assessing its druggability. Intrinsically disordered proteins, such as AF9 AHD, are difficult to study and characterize experimentally on a structural level. In this study, we present a successful protein engineering strategy to facilitate structural investigation of the intrinsically disordered AF9 AHD domain in complex with peptidomimetic inhibitors by using maltose binding protein (MBP) as a crystallization chaperone connected with linkers of varying flexibility and length. The strategic incorporation of disulfide bonds provided diffraction-quality crystals of the two disulfide-bridged MBP–AF9 AHD fusion proteins in complex with the peptidomimetics. These successfully determined first series of 2.1–2.6 Å crystal complex structures provide high-resolution insights into the interactions between AHD and its inhibitors, shedding light on the role of AHD in recruiting various binding partner proteins. We show that the overall complex structures closely resemble the reported NMR structure of AF9 AHD/DOT1L with notable difference in the conformation of the β-hairpin region, stabilized through conserved hydrogen bonds network. These first series of AF9 AHD/peptidomimetics complex structures are providing insights of the protein–inhibitor interactions and will facilitate further development of novel inhibitors targeting the AF9/ENL AHD domain.

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

Improving AlphaFold2-based protein tertiary structure prediction with MULTICOM in CASP15

Since the 14th Critical Assessment of Techniques for Protein Structure Prediction (CASP14), AlphaFold2 has become the standard method for protein tertiary structure prediction. One remaining challenge is to further improve its prediction. We developed a new version of the MULTICOM system to sample diverse multiple sequence alignments (MSAs) and structural templates to improve the input for AlphaFold2 to generate structural models. The models are then ranked by both the pairwise model similarity and AlphaFold2 self-reported model quality score. The top ranked models are refined by a novel structure alignment-based refinement method powered by Foldseek. Moreover, for a monomer target that is a subunit of a protein assembly (complex), MULTICOM integrates tertiary and quaternary structure predictions to account for tertiary structural changes induced by protein-protein interaction. The system participated in the tertiary structure prediction in 2022 CASP15 experiment. Our server predictor MULTICOM_refine ranked 3rd among 47 CASP15 server predictors and our human predictor MULTICOM ranked 7th among all 132 human and server predictors. The average GDT-TS score and TM-score of the first structural models that MULTICOM_refine predicted for 94 CASP15 domains are ~0.80 and ~0.92, 9.6% and 8.2% higher than ~0.73 and 0.85 of the standard AlphaFold2 predictor respectively.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Vascular Patterning Analysis by VESGEN 2D/3D with Bioinformatics: Updates for Rodent Tissues

Fractally branching vascular systems are a complex physiological requirement shared by humans with all higher terrestrial life forms, including other vertebrates, insects, and higher land plants. Vascular trees, networks, and tree-network composites are therefore mapped and quantified by the VESsel GENeration Analysis (VESGEN) software according to weighted physiological vascular rules that include vessel connectivity, tapering and bifurcational branching. According to fluid dynamics, successful vascular transport depends upon a complex distributed system of highly regulated laminar flow. VESGEN has elucidated changes in vascular patterning resulting from inflammatory, developmental and other signaling pathways within numerous tissues of major model organisms important for Space Biology, especially for rodents. Important early stage regenerative opportunities have been identified by VESGEN vascular analysis for visual impairments in the human retina, and is currently being used for research into astronaut visual and ocular disorders associated with long duration missions. The VESGEN 2D software is a mature, automated, widely published capability for which beta testing and public release by NASA is planned for the upcoming year. Early-stage capabilities for VESGEN 3D analysis are under development for the rodent retina and intestine as prototype tissues. A prototype VESGEN 2D Bioinformatics software capability has also been developed to associate phenotypic changes in molecular expression with vascular structure and function. By new VESGEN bioinformatic innovations, expression patterns of the genetic, transcriptional, protein and other markers for regulatory molecules such as vascular endothelial growth factor (VEGF) and their receptors, often indicators of tissue oxygenation status, are co-localized with alterations in vascular pattern. Biomarkers are therefore mapped and quantified as information dimensions directly correlated with the spatial dimensions of a vascular pattern. Further important technology innovations by NASA include substantial image segmentation advances for more automated binary extraction of the grayscale vascular patterns, together with informative associated image quality assessments. Vascular mapping and quantification capabilities for the rodent retina and intestine are illustrated for VESGEN 2D, along with technology status reports on VESGEN 3D and Bioinformatic capabilities. Research partially supported by Ames Center Innovation Awards.

Parsons-Wingerter, P.↗
DOE OSTI2025

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew↗
DOE OSTI2024

Comparing plant litter molecular diversity assessed from proximate analysis and 13 C NMR spectroscopy

Accurate representation of the chemical diversity of litter in ecosystem-scale models is critical for improving predictions of decomposition rates and stabilization of plant material into soil organic matter. In this contribution, we conducted a systematic review to evaluate how conventional characterization of plant litter quality using proximate analysis compares with molecular-scale characterization using 13 C NMR spectroscopy. Using a molecular mixing model, we converted chemical shift regions from NMR into fractions of carbon (C) in five organic compound classes that are major constituents of plant material: carbohydrates, proteins, lignins, lipids, and carbonylic compounds. We found positive correlations between the acid soluble fraction and carbohydrates, and between the acid insoluble fraction and lignins. However, the acid-soluble fraction underestimated carbohydrates, and the acid insoluble fraction overestimated lignins by 243%. We identified two sources of uncertainties: i) disparities between litter chemical composition based on hydrolysability and actual chemical composition obtained from NMR and ii) conversion factors to translate proximate fractions into organic constituents. Both uncertainties are critical, potentially leading to misinterpretations of decay rates in litter decomposition models. Consequently, we recommend including explicit substrate chemistry data in the next generation of litter decomposition models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Effects of antibacterial peptide-producing Bacillus subtilis, gallic acid, and cellulase on fermentation quality and bacterial community of whole-plant corn silage

In the current study, we assessed the effects of antibacterial peptide-producing Bacillus subtilis (BS), gallic acid (GA) and cellulase (CL) on the fermentation quality and bacterial community of various varieties of whole-plant corn silage. Three different varieties of whole-plant corn (Yuqing386, Enxiai298, and Nonghe35) were treated with 0.02% BS (fresh material basis), 0.2% GA (fresh material basis) and 0.02% CL (fresh material basis), after which 45 days of anaerobic fermentation were conducted. With the exception of its low dry matter content, the results showed that Yuqing386’s crude protein, water-soluble carbohydrate, and lactic acid contents were significantly higher than those of the other two corn varieties. However, its acid detergent fiber and cellulose contents were significantly lower than those of the other two corn varieties. Among the three corn variety silages, Yuqing386 had the highest relative abundance of Lactobacillus at the genus level and the biggest relative abundance of Firmicutes at the phylum level. In addition, the three additives markedly enhanced the quantity of dry matter and crude protein as compared to the control group. The application of GA considerably decreased the level of neutral detergent fiber while significantly increasing the content of lactic acid and water-soluble carbohydrates. Even though all additives enhanced the structure of the bacterial community following silage, the GA group experienced the greatest enhancement. On a phylum and genus level, the GA group contains the highest relative abundance of Firmicutes and Lactobacillus , respectively. Overall, of the three corn varieties, Yuqing386 provides the best silage qualities. GA has the biggest impact among the additions employed in this experiment to enhance the nutritional preservation and fermentation quality of whole-plant corn silage.

Zhang, Zhiheng↗
DOE OSTI2021

Assessment of TMT Labeling Efficiency in Large-Scale Quantitative Proteomics: The Critical Effect of Sample pH

Isobaric labeling via tandem mass tag (TMT) reagents enables sample multiplexing prior to LC–MS/MS, facilitating high-throughput large-scale quantitative proteomics. Consistent and efficient labeling reactions are essential to achieve robust quantification; therefore, embedded in our clinical proteomic protocol is a quality control (QC) sample that contains a small aliquot from each sample within a TMT set, referred to as “Mixing QC.” This Mixing QC enables the detection of TMT labeling issues by LC–MS/MS before combining the full samples to allow for salvaging of poor TMT labeling reactions. While TMT labeling is a valuable tool, factors leading to poor reactions are not fully studied. We observed that relabeling does not necessarily rescue TMT reactions and that peptide samples sometimes remained acidic after resuspending in 50 mM HEPES buffer (pH 8.5), which coincided with low labeling efficiency (LE) and relatively low median reporter ion intensities (MRIIs). To obtain a more resilient TMT labeling procedure, we investigated LE, reporter ion missingness, the ratio of mean TMT set MRII to individual channel MRII, and the distribution of log 2 reporter ion ratios of Mixing QC samples. We discovered that sample pH is a critical factor in LE, and increasing the buffer concentration in poorly labeled samples before relabeling resulted in the successful rescue of TMT labeling reactions. Moreover, resuspending peptides in 500 mM HEPES buffer for TMT labeling resulted in consistently higher LE and lower missing data. By better controlling the sample pH for labeling and implementing multiple methods for assessing labeling quality before combining samples, we demonstrate that robust TMT labeling for large-scale quantitative studies is achievable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

KBase Narrative - Atacama Trench & Sn Clemente 2018 cruise Metagenomes -Sequence quality filtration & Assembly-

Deep-sea microbiomes sampled with traditional or pressure-retaining instrumentation A fundamental property of life in the sea is that with increasing depth must come increased adaptation to elevated hydrostatic pressures. This project aims to assess technology for the accurate characterization of microbial biodiversity and biochemistry at greater depths, and validate its use in some of the deepest and least-explored waters in the Ocean: Hadal Trench. Compared to the 0.1 megapascal (MPa) of surface waters, organisms inhabiting at the average depth of the Ocean (3800 m) have to deal with pressures of 38 MPa (5,500 psi). The effects of these high pressure have been most thoroughly investigated in microorganisms, where it has been found to affect membrane integrity and transport, cytoskeletal assembly and both DNA and protein synthesis. We will explore the diversity and activity of microorganisms from 2000 m to >8,000 m depths within the highly productive water column of hadal trenches, comparing seawater samples obtained with and without substantial pressure changes during recovery. A pressure retaining device was used to sample the microbial communities of the watercolumn with reduced decompression during retreival (Peoples et. al., 2019). References: Peoples LM, Norenberg M, Price D, McGoldrick M, Novotny M, Bochdansky A, Bartlett DH. A full-ocean-depth rated modular lander and pressure-retaining sampler capable of collecting hadal-endemic microbes under in situ conditions. Deep Sea Research Part I: Oceanographic Research Papers. 2019 Jan 1;143:50-7.

Plominsky, Alvaro M.↗
DOE OSTI2023

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Chromosome-Scale Genome Assembly of a Helicoverpa zea Strain Resistant to Bacillus thuringiensis Cry1Ac Insecticidal Protein

Helicoverpa zea (Lepidoptera: Noctuidae) is an insect pest of major cultivated crops in North and South America. The species has adapted to different host plants and developed resistance to several insecticidal agents, including Bacillus thuringiensis (Bt) insecticidal proteins in transgenic cotton and maize. Helicoverpa zea populations persist year-round in tropical and subtropical regions, but seasonal migrations into temperate zones increase the geographic range of associated crop damage. To better understand the genetic basis of these physiological and ecological characteristics, we generated a high-quality chromosome-level assembly for a single H. zea male from Bt-resistant strain, HzStark_Cry1AcR. Hi-C data were used to scaffold an initial 375.2 Mb contig assembly into 30 autosomes and the Z sex chromosome (scaffold N50 = 12.8 Mb and L50 = 14). The scaffolded assembly was error-corrected with a novel pipeline, polishCLR. The mitochondrial genome was assembled through an improved pipeline and annotated. Assessment of this genome assembly indicated 98.8% of the Lepidopteran Benchmark Universal Single-Copy Ortholog set were complete (98.5% as complete single copy). Repetitive elements comprised approximately 29.5% of the assembly with the plurality (11.2%) classified as retroelements. This chromosome-scale reference assembly for H. zea, ilHelZeax1.1, will facilitate future research to evaluate and enhance sustainable crop production practices.

59 BASIC BIOLOGICAL SCIENCES↗