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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 307 records · Page 17

Omics-Lethal Human Viruses, Ebola Experiment EHUVEC001

The purpose of this experiment was to evaluate the human host response to Zaire Ebola wild-type virus and mutant virus infection in VP30 expression background. Samples were obtained from human umbilical cord endothelial cells (HUVEC) infected with wild-type Zaire Ebola virus in the ΔVP30 background (deltaVP30-WT) and mutant lacking the mucin domain (deltaVP30-deltamucin) encoding a glycoprotein lacking the mucin domain for mRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific Ebola virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics Lethal Human Viruses, Ebola Experiment EU937001

The purpose of this experiment was to evaluate the human host response to Zaire Ebola wild-type virus and mutant virus infection. Samples were obtained from human histiocytic lymphoma cells (U937), expressing the Ebola VP30 protein, infected with wild-type Zaire Ebola (in ΔVP30 background) and Δmucin mutant virus encoding a glycoprotein lacking the mucin domain for mRNA and miRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific Ebola virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, Interferon-Stimulated Response Experiment IFNaCL001

The purpose of this experiment was to evaluate the host interferon-stimulated cellular response to interferon alpha (IFNα) treatment. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) treated with or without IFNα for mRNA and miRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset download have a direct relationship to a primary sample submission corresponding to a specific interferon response to viral infection.

59 BASIC BIOLOGICAL SCIENCES↗

Dried Plum Protects From Radiation-Induced Bone Loss by Attenuating Pro-Osteoclastic and Oxidative Stress Responses

Future space explorations beyond the earths magnetosphere will increase human exposure to space radiation and associated risks to skeletal health. We hypothesize that oxidative stress resulting from radiation exposure plays a major role in progressive bone loss and dysfunction in associated tissue. In animal studies, increased free radical formation is associated with pathological changes in bone structure, enhanced bone resorption, reduced bone formation and decreased bone mineral density, which can lead to skeletal fragility. Our long-term goals are to define the mechanisms and risk of bone loss in the spaceflight environment and to facilitate the development of effective countermeasures. We had previously reported that exposure to low or high-LET radiation correlates with an acute increase in the expression of pro-osteoclastic and oxidative stress genes in bone during the early response to radiation followed by pathological changes in skeletal structure. We then conducted systematic screening for potential countermeasures against bone loss where we tested the ability of various antioxidants to mitigate the radiation-induced increase in expression of these markers. For the screen, 16-week old C57Bl6J mice were treated with a dietary antioxidant cocktail, injectable DHLA or a dried plum-enriched diet (DP). Mice were then exposed to 2Gy 137Cs radiation and one day later, marrow cells were collected and the relevant genes analyzed for expression levels. Among the candidate countermeasures tested, DP was most effective in reducing the expression of genes associated with bone loss. Furthermore, analysis of skeletal structure by microcomputed tomography (microCT) revealed that DP also prevents the radiation-induced deterioration in skeletal microarchitecture as indicated by parameters such as percent bone volume (BVTV), trabecular spacing and trabecular number. We also found that DP has similar protective effects on skeletal structure in a follow-up study using 1 Gy of sequential proton and iron, radiation species relevant to spaceflight. When cultured ex vivo under osteogenic conditions, bone marrow-derived cells from DP-fed animals exhibited increased colony numbers compared to control diet-fed animals. These findings suggest that DP exerts pro-osteogenic effects apart from its previously demonstrated anti-resorptive action, which may be one of the mechanisms underlying its radioprotective effect on bone. In conclusion, a diet enriched in certain types of antioxidants may be useful as an intervention for radiation-induced bone loss.

Bone-loss↗

Targeting CCL2/CCR2 Signaling Overcomes MEK Inhibitor Resistance in Acute Myeloid Leukemia

Emerging evidence underscores the critical role of extrinsic factors within the microenvironment in protecting leukemia cells from therapeutic interventions, driving disease progression, and promoting drug resistance in acute myeloid leukemia (AML). This finding emphasizes the need for the identification of targeted therapies that inhibit intrinsic and extrinsic signaling to overcome drug resistance in AML. We performed a comprehensive analysis utilizing a cohort of ~300 AML patient samples. This analysis encompassed the evaluation of secreted cytokines/growth factors, gene expression, and ex vivo drug sensitivity to small molecules. Our investigation pinpointed a notable association between elevated levels of CCL2 and diminished sensitivity to the MEK inhibitors (MEKi). We validated this association through loss-of-function and pharmacologic inhibition studies. Further, we deployed global phosphoproteomics and CRISPR/Cas9 screening to identify the mechanism of CCR2-mediated MEKi resistance in AML. Our multifaceted analysis unveiled that CCL2 activates multiple prosurvival pathways, including MAPK and cell-cycle regulation in MEKi-resistant cells. Employing combination strategies to simultaneously target these pathways heightened growth inhibition in AML cells. Both genetic and pharmacologic inhibition of CCR2 sensitized AML cells to trametinib, suppressing proliferation while enhancing apoptosis. These findings underscore a new role for CCL2 in MEKi resistance, offering combination therapies as an avenue to circumvent this resistance. Our study demonstrates a compelling rationale for translating CCL2/CCR2 axis inhibitors in combination with MEK pathway-targeting therapies, as a potent strategy for combating drug resistance in AML. This approach has the potential to enhance the efficacy of treatments to improve AML patient outcomes.

60 APPLIED LIFE SCIENCES↗

The stem cell-type transcriptome of bioenergy sorghum reveals the spatial regulation of secondary cell wall networks

Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type.

cell specificity↗

Generating Co-expression Networks for Three Cyanobacteria: Synechococcus sp. PCC 7942, Synechococcus sp. PCC 7002, Synechocystis sp. PCC 6803

Cyanobacteria are photosynthetic organisms capable of high growth rate and represent a promising bioplatform for harnessing the sun’s energy to make biofuel. Additionally, the process of photosynthesis absorbs CO2 from the environment. Understanding the metabolic processes involved in photosynthesis could lead to solutions to the recent rise of CO2 concentration in Earth’s atmosphere and the associated climate change. More research on the transcriptional regulation of these cells is needed to learn how to harness the untapped potential of cyanobacteria for these applications. Transcriptional analysis via RNA-seq provides an understanding of how gene expression changes at the mRNA level under diverse growing conditions. I systematically collected and analyzed RNA-Seq data obtained under a variety of conditions and available on the NCBI database for three cyanobacteria model organisms: Synechococcus elongatus sp. PCC 7942, Synechococcus sp. PCC 7002, and Synechocystis sp. PCC 6803. For each organism, the data was mapped to a reference genome to characterize the RNA expression profile. Samples were checked for quality based on the number of reads and the correlation of the expression profile between labeled replicates. All samples were transformed into transcripts per million reads, followed by a log transformation to account for the wide range of sample sizes. Gene co-expression networks were generated and analyzed for each species using Cytoscape. These networks provide a base level of gene expression for each species. The network topology and high-betweeness nodes of these networks need to be analyzed further to provide insight on potential ways to harness cyanobacteria genetics. Additionally, these datasets can be used together to form a core genome network analysis- one that includes only the genes that are homologous between the three species. This project has prepared the way for a more in-depth study on photosynthetic microbes on a genetic level.

59 BASIC BIOLOGICAL SCIENCES↗

Structural analysis of the NifL-NifA complex reveals the molecular basis of anti-activation of nitrogen fixation gene expression in Azotobacter vinelandii

Understanding the molecular basis of regulated nitrogen (N 2 ) fixation is essential for engineering N 2 -fixing bacteria that fulfill the demand of crop plants for fixed nitrogen, reducing our reliance on synthetic nitrogen fertilizers. In Azotobacter vinelandii and many other members of Proteobacteria, the two-component system comprising the anti-activator protein (NifL) and the Nif-specific transcriptional activator (NifA)controls the expression of nif genes, encoding the nitrogen fixation machinery. The NifL-NifA system evolved the ability to integrate several environmental cues, such as oxygen, nitrogen, and carbon availability. The nitrogen fixation machinery is thereby only activated under strictly favorable conditions, enabling diazotrophs to thrive in competitive environments. While genetic and biochemical studies have enlightened our understanding of how NifL represses NifA, the molecular basis of NifA sequestration by NifL depends on structural information on their interaction. Here, we present mechanistic insights into how nitrogen fixation is regulated by combining biochemical and genetic approaches with a low-resolution cryo-electron microscopy (cryo-EM) map of the oxidized NifL-NifA complex. Our findings define the interaction surface between NifL and NifA and reveal how this interaction can be manipulated to generate bacterial strains with increased nitrogen fixation rates able to secrete surplus nitrogen outside the cell, a crucial step in engineering improved nitrogen delivery to crop plants.

59 BASIC BIOLOGICAL SCIENCES↗

Spaceflight Alters Bacterial Gene Expression and Virulence and Reveals Role for Global Regulator Hfq

A comprehensive analysis of both the molecular genetic and phenotypic responses of any organism to the spaceflight environment has never been accomplished due to significant technological and logistical hurdles. Moreover, the effects of spaceflight on microbial pathogenicity and associated infectious disease risks have not been studied. The bacterial pathogen Salmonella typhimurium was grown aboard Space Shuttle mission STS-115 and compared to identical ground control cultures. Global microarray and proteomic analyses revealed 167 transcripts and 73 proteins changed expression with the conserved RNA-binding protein Hfq identified as a likely global regulator involved in the response to this environment. Hfq involvement was confirmed with a ground based microgravity culture model. Spaceflight samples exhibited enhanced virulence in a murine infection model and extracellular matrix accumulation consistent with a biofilm. Strategies to target Hfq and related regulators could potentially decrease infectious disease risks during spaceflight missions and provide novel therapeutic options on Earth.

Wilson, J. W.↗

Patterns of global gene expression in rat skeletal muscle during unloading and low-intensity ambulatory activity

Physical inactivity and unloading lead to diverse skeletal muscle alterations. Our goal was to identify the genes in skeletal muscle whose expression is most sensitive to periods of unloading/reduced physical activity and that may be involved in triggering initial responses before phenotypic changes are evident. The ability of short periods of physical activity/loading as an effective countermeasure against changes in gene expression mediated by inactivity was also tested. Affymetrix microarrays were used to compare mRNA levels in the soleus muscle under three experimental treatments (n = 20-29 rats each): 12-h hindlimb unloading (HU), 12-h HU followed by 4 h of intermittent low-intensity ambulatory and postural activity (4-h reloading), and control (with ambulatory and postural activity). Using a combination of criteria, we identified a small set of genes (approximately 1% of 8,738 genes on the array or 4% of significant expressed genes) with the most reproducible and largest responses to altered activity. Analysis revealed a coordinated regulation of transcription for a large number of key signaling proteins and transcription factors involved in protein synthesis/degradation and energy metabolism. Most (21 of 25) of the gene expression changes that were downregulated during HU returned at least to control levels during the reloading. In surprising contrast, 27 of 38 of the genes upregulated during HU remained significantly above control, but most showed trends toward reversal. This introduces a new concept that, in general, genes that are upregulated during unloading/inactivity will be more resistant to periodic reloading than those genes that are downregulated. This study reveals genes that are the most sensitive to loading/activity in rat skeletal muscle and indicates new targets that may initiate muscle alterations during inactivity.

NASA Discipline Musculoskeletal↗

Global Network Analysis of Neisseria gonorrhoeae Identifies Coordination between Pathways, Processes, and Regulators Expressed during Human Infection

Neisseria gonorrhoeae is a Gram-negative diplococcus that is responsible for the sexually transmitted infection gonorrhea, a high-morbidity disease in the United States and worldwide. Over the past several years, N. gonorrhoeae strains resistant to antibiotics used to treat this infection have begun to emerge across the globe. Thus, new treatment strategies are needed to combat this organism. Here, we utilized N. gonorrhoeae transcriptomic data sets, including those obtained from natural infection of the human genital tract, to infer the first global gene coexpression network of this pathogen. Interrogation of this network revealed genes central to the network that are likely critical for gonococcal growth, metabolism, and virulence, including genes encoding hypothetical proteins expressed during mucosal infection. In addition, network analysis revealed overlap in the response of N. gonorrhoeae to incubation with neutrophils and exposure to hydrogen peroxide stress in vitro. Network analysis also identified new targets of the gonococcal global regulatory protein Fur, while examination of the network neighborhood of genes allowed us to assign additional putative categories to several proteins. Collectively, the characterization of the first gene coexpression network for N. gonorrhoeae described here has revealed new regulatory pathways and new categories for proteins and has shown how processes important to gonococcal infection in both men and women are linked. This information fills a critical gap in our understanding of virulence strategies of this obligate human pathogen and will aid in the development of new treatment strategies for gonorrhea.

59 BASIC BIOLOGICAL SCIENCES↗

Data for FUN-PROSE: A Deep Learning Approach to Predict Condition-Specific Gene Expression in Fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

Genomics↗

Speciation Underpinned by Unexpected Molecular Diversity in the Mycorrhizal Fungal Genus Pisolithus

The mutualistic ectomycorrhizal (ECM) fungal genus Pisolithus comprises 19 species defined to date which colonize the roots of >50 hosts worldwide suggesting that substantial genomic and functional evolution occurred during speciation. To better understand this intra-genus variation, we undertook a comparative multi-omic study of nine Pisolithus species sampled from North America, South America, Asia, and Australasia. We found that there was a small core set of genes common to all species (13%), and that these genes were more likely to be significantly regulated during symbiosis with a host than accessory or species-specific genes. Thus, the genetic “toolbox” foundational to the symbiotic lifestyle in this genus is small. Transposable elements were located significantly closer to gene classes including effector-like small secreted proteins (SSPs). Poorly conserved SSPs were more likely to be induced by symbiosis, suggesting that they may be a class of protein that tune host specificity. The Pisolithus gene repertoire is characterized by divergent CAZyme profiles when compared with other fungi, both symbiotic and saprotrophic. This was driven by differences in enzymes associated with symbiotic sugar processing, although metabolomic analysis suggest that neither copy number nor expression of these genes is sufficient to predict sugar capture from a host plant or its metabolism in fungal hyphae. Our results demonstrate that intra-genus genomic and functional diversity within ECM fungi is greater than previously thought, underlining the importance of continued comparative studies within the fungal tree of life to refine our focus on pathways and evolutionary processes foundational to this symbiotic lifestyle.

59 BASIC BIOLOGICAL SCIENCES↗

Increasing the Statistical Rigor of Cross-Species Differential Expression Analysis

Microgravity inflicts substantial, but undercharacterized, pressure on organisms that induces metabolic responses such as increased microbial virulence and antibiotic resistance, altered organ weights in developing rats, and loss of bone tissue in astronauts. Numerous studies have analyzed the effects of microgravity on specific organisms, tissues, or test conditions, but these projects are necessarily limited by the small sample size of space research. Increasing the sample size of spaceflight studies is non-trivial; however, pooling data from numerous studies can greatly increase the statistical rigor of comparative analyses. The GeneLab houses datasets from 73 spaceflight studies that performed transcription profiling assays. These data encompass a diverse array of organisms ranging from Escherichia coli to Mus musculus to Homo sapiens and comprise studies analyzing ionizing radiation, mammalian pregnancy, etc. Collectively, the GeneLab database contains a large quantity of transcription assays and RNA sequence data analyzing Differential Gene Expression (DGE) between microand normogravity. Xspecies, a cross-species analysis method for DGE developed by Kristiansson, et al. in 2012, identifies homologous genes between species that are universally up- or downregulated in response to test conditions. Previous work by an intern at GeneLab applied Xspecies to 19 datasets containing seven different species and identified 14 homologous groups differentially expressed under spaceflight conditions including several heat shock proteins and cytoskeletal components. Unfortunately, these results may be biased by the disproportionate number of studies on Arabidopsis thaliana (5) and Mus musculus (6) and the results are not normalized by evolutionary distances. Here, we present modifications to the Xspecies algorithm that permits incorporation of multi-omic data and normalizes data for effect size, directionality, and evolutionary distances. We then apply this algorithm to all currently available GeneLab studies

Xspecies↗

A Novel Kinesin-Like Protein with a Calmodulin-Binding Domain

Calcium regulates diverse developmental processes in plants through the action of calmodulin. A cDNA expression library from developing anthers of tobacco was screened with S-35-labeled calmodulin to isolate cDNAs encoding calmodulin-binding proteins. Among several clones isolated, a kinesin-like gene (TCK1) that encodes a calmodulin-binding kinesin-like protein was obtained. The TCK1 cDNA encodes a protein with 1265 amino acid residues. Its structural features are very similar to those of known kinesin heavy chains and kinesin-like proteins from plants and animals, with one distinct exception. Unlike other known kinesin-like proteins, TCK1 contains a calmodulin-binding domain which distinguishes it from all other known kinesin genes. Escherichia coli-expressed TCK1 binds calmodulin in a Ca(2+)-dependent manner. In addition to the presence of a calmodulin-binding domain at the carboxyl terminal, it also has a leucine zipper motif in the stalk region. The amino acid sequence at the carboxyl terminal of TCK1 has striking homology with the mechanochemical motor domain of kinesins. The motor domain has ATPase activity that is stimulated by microtubules. Southern blot analysis revealed that TCK1 is coded by a single gene. Expression studies indicated that TCKI is expressed in all of the tissues tested. Its expression is highest in the stigma and anther, especially during the early stages of anther development. Our results suggest that Ca(2+)/calmodulin may play an important role in the function of this microtubule-associated motor protein and may be involved in the regulation of microtubule-based intracellular transport.

Wang, W.↗

MONTI: A Multi-Omics Non-negative Tensor Decomposition Framework for Gene-Level Integrative Analysis

Multi-omics data is frequently measured to enrich the comprehension of biological mechanisms underlying certain phenotypes. However, due to the complex relations and high dimension of multi-omics data, it is difficult to associate omics features to certain biological traits of interest. For example, the clinically valuable breast cancer subtypes are well-defined at the molecular level, but are poorly classified using gene expression data. Here, we propose a multi-omics analysis method called MONTI (Multi-Omics Non-negative Tensor decomposition for Integrative analysis), which goal is to select multi-omics features that are able to represent trait specific characteristics. Here, we demonstrate the strength of multi-omics integrated analysis in terms of cancer subtyping. The multi-omics data are first integrated in a biologically meaningful manner to form a three dimensional tensor, which is then decomposed using a non-negative tensor decomposition method. From the result, MONTI selects highly informative subtype specific multi-omics features. MONTI was applied to three case studies of 597 breast cancer, 314 colon cancer, and 305 stomach cancer cohorts. For all the case studies, we found that the subtype classification accuracy significantly improved when utilizing all available multi-omics data. MONTI was able to detect subtype specific gene sets that showed to be strongly regulated by certain omics, from which correlation between omics types could be inferred. Furthermore, various clinical attributes of nine cancer types were analyzed using MONTI, which showed that some clinical attributes could be well explained using multi-omics data. We demonstrated that integrating multi-omics data in a gene centric manner improves detecting cancer subtype specific features and other clinical features, which may be used to further understand the molecular characteristics of interest. The software and data used in this study are available at: https://github.com/inukj/MONTI.

59 BASIC BIOLOGICAL SCIENCES↗

Overexpression of REDUCED WALL ACETYLATION C increases xylan acetylation and biomass recalcitrance in Populus

Abstract Plant lignocellulosic biomass, i.e. secondary cell walls of plants, is a vital alternative source for bioenergy. However, the acetylation of xylan in secondary cell walls impedes the conversion of biomass to biofuels. Previous studies have shown that REDUCED WALL ACETYLATION (RWA) proteins are directly involved in the acetylation of xylan but the regulatory mechanism of RWAs is not fully understood. In this study, we demonstrate that overexpression of a Populus trichocarpa PtRWA-C gene increases the level of xylan acetylation and increases the lignin content and S/G ratio, ultimately yielding poplar woody biomass with reduced saccharification efficiency. Furthermore, through gene coexpression network and expression quantitative trait loci (eQTL) analysis, we found that PtRWA-C was regulated not only by the secondary cell wall hierarchical regulatory network but also by an AP2 family transcription factor HARDY (HRD). Specifically, HRD activates PtRWA-C expression by directly binding to the PtRWA-C promoter, which is also the cis-eQTL for PtRWA-C. Taken together, our findings provide insights into the functional roles of PtRWA-C in xylan acetylation and consequently saccharification and shed light on synthetic biology approaches to manipulate this gene and alter cell wall properties. These findings have substantial implications for genetic engineering of woody species, which could be used as a sustainable source of biofuels, valuable biochemicals, and biomaterials.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic Transcriptomic and Phosphoproteomic Analysis During Cell Wall Stress in Aspergillus nidulans

The fungal cell-wall integrity signaling (CWIS) pathway regulates cellular response to environmental stress to enable wall repair and resumption of normal growth. This complex, interconnected, pathway has been only partially characterized in filamentous fungi. To better understand the dynamic cellular response to wall perturbation, a β-glucan synthase inhibitor (micafungin) was added to a growing A. nidulans shake-flask culture. From this flask, transcriptomic and phosphoproteomic data were acquired over 10 and 120 min, respectively. To differentiate statistically-significant dynamic behavior from noise, a multivariate adaptive regression splines (MARS) model was applied to both data sets. Over 1800 genes were dynamically expressed and over 700 phosphorylation sites had changing phosphorylation levels upon micafungin exposure. Twelve kinases had altered phosphorylation and phenotypic profiling of all non-essential kinase deletion mutants revealed putative connections between PrkA, Hk-8–4, and Stk19 and the CWIS pathway. Our collective data implicate actin regulation, endocytosis, and septum formation as critical cellular processes responding to activation of the CWIS pathway, and connections between CWIS and calcium, HOG, and SIN signaling pathways.

59 BASIC BIOLOGICAL SCIENCES↗