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

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Abstract Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization

Plant roots release a wide array of metabolites into the rhizosphere, shaping microbial communities and their functions. While metagenomics has expanded our understanding of these communities, little is known about the physiology of their members in host environments. Transcriptome analysis via RNA sequencing is a common approach to learning more, but its use has been challenging because of low bacterial biomass and interference from plant RNA. To overcome this, we developed a randomly-barcoded promoter-library insertion sequencing (RB-PI-seq) combined with chassis-independent recombinase-assisted genome engineering (CRAGE). Using Pseudomonas simiae WCS417 as a model rhizobacterium, this method enabled targeted amplification of barcoded transcripts, bypassing plant RNA interference and allowing measurement of thousands of promoter activities during Arabidopsis root colonization. Our analysis revealed temporally resolved transcriptional regulation, including those associated with cell growth, chemotaxis, plant immune suppression, biofilm formation, and stress responses, reflecting the coordinated physiological adaptation to the root environment. Additionally, we discovered that transcriptional activation of xanthine dehydrogenase and a lysozyme inhibitor is crucial for evading plant immune systems. This framework is scalable to other bacterial species and provides new opportunities for understanding rhizobacterial gene regulation in native environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Crystal Structure of an i‐Motif from the HRAS Oncogene Promoter

Abstract An i‐motif is a non‐canonical DNA structure implicated in gene regulation and linked to cancers. The C‐rich strand of the HRAS oncogene, 5′‐CG CCC GTG CCC TGCG CCC GCAA CCC GA‐3′ (herein referred to as iHRAS), forms an i‐motif in vitro but its exact structure was unknown. HRAS is a member of the RAS proto‐oncogene family. About 19 % of US cancer patients carry mutations in RAS genes. We solved the structure of iHRAS at 1.77 Å resolution. The structure reveals that iHRAS folds into a double hairpin. The two double hairpins associate in an antiparallel fashion, forming an i‐motif dimer capped by two loops on each end and linked by a connecting region. Six C−C + base pairs form each i‐motif core, and the core regions are extended by a G−G base pair and a cytosine stacking. Extensive canonical and non‐canonical base pairing and stacking stabilizes the connecting region and loops. The iHRAS structure is the first atomic resolution structure of an i‐motif from a human oncogene. This structure sheds light on i‐motifs folding and function in the cell.

Li, Kevin S.↗
DOE OSTI2023

Crystal Structure of an i‐Motif from the HRAS Oncogene Promoter

Abstract An i‐motif is a non‐canonical DNA structure implicated in gene regulation and linked to cancers. The C‐rich strand of the HRAS oncogene, 5′‐CG CCC GTG CCC TGCG CCC GCAA CCC GA‐3′ (herein referred to as iHRAS), forms an i‐motif in vitro but its exact structure was unknown. HRAS is a member of the RAS proto‐oncogene family. About 19 % of US cancer patients carry mutations in RAS genes. We solved the structure of iHRAS at 1.77 Å resolution. The structure reveals that iHRAS folds into a double hairpin. The two double hairpins associate in an antiparallel fashion, forming an i‐motif dimer capped by two loops on each end and linked by a connecting region. Six C−C + base pairs form each i‐motif core, and the core regions are extended by a G−G base pair and a cytosine stacking. Extensive canonical and non‐canonical base pairing and stacking stabilizes the connecting region and loops. The iHRAS structure is the first atomic resolution structure of an i‐motif from a human oncogene. This structure sheds light on i‐motifs folding and function in the cell.

Li, Kevin S.↗
DOE OSTI2026

An expanded registry of candidate cis -regulatory elements

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, the ENCODE consortium mapped biochemical signals across hundreds of cell types and tissues and integrated these data to develop a registry containing 0.9 million human and 300,000 mouse candidate cis-regulatory elements (cCREs) annotated with potential functions. Here we have expanded the registry to include 2.37 million human and 967,000 mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays such as STARR-seq, massively parallel reporter assay, CRISPR perturbation and transgenic mouse assays have profiled more than 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer and silencer roles in different cellular contexts. Integrating the registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by the identification of KLF1 as a novel causal gene for red blood cell traits. This expanded registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

Moore, Jill E. [Univ. of Massachusetts, Worchester↗
DOE OSTI2024

Highly multiplexed design of an allosteric transcription factor to sense new ligands

Allosteric transcription factors (aTF) regulate gene expression through conformational changes induced by small molecule binding. Although widely used as biosensors, aTFs have proven challenging to design for detecting new molecules because mutation of ligand-binding residues often disrupts allostery. Here, we develop Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screen a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures – four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone – as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identifies biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design shows shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we develop cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid and scalable design of new biosensors, overcoming constraints of natural biosensors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nonclassical autophagy activation pathways are essential for production of infectious Influenza A virus in vitro

Autophagy is a critical mechanism deployed by eukaryotic cells in response to stress, including viral infection, to boost the innate antimicrobial responses. However, an increasing number of pathogens hijack the autophagic machinery to facilitate their own replication. Influenza A virus (IAV), responsible for several global pandemics, has an intricate dependence on autophagy for successful replication in mammalian cells. To elucidate key chokepoints in the host stress responses facilitating IAV replication, we constructed a meta-transcriptome of IAV and host gene expression dynamics during early (1–3 hpi), mid (4–6 hpi), and late (8–12 hpi) stages of the viral replication cycle at two multiplicities of infection (MOI): 1 and 5. We supplemented the global transcriptome study with phosphoproteomic analysis of stress-activated protein kinase (SAPK/JNK) signaling in lung carcinoma (predominantly used as an in vitro model of IAV replication) and normal human bronchial epithelial cells. We report significant differences in the activation profiles of autophagy regulating genes upon IAV infection at the two MOI as well as divergent dependence on ULK1 signaling within the normal and cancer cells. Regardless of the cell model, JNK-Thr187 signaling was crucial for the production of infectious viral particles.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

Genetic Regulation of Bone and Cells by Electromagnetic Stimulation Fields and Uses Thereof

The present invention provides methods to modify the genetic regulation of mammalian tissue, bone, cells or any combination thereof by preferential activation, up-regulation and/or down-regulation. The method comprises steps of tuning the predetermined profiles of one or more time-varying stimulation fields by manipulating the B-Field magnitude, rising slew rate, rise time, falling slew rate, fall time, frequency, wavelength, and duty cycle, and exposing mammalian cells or tissues to one or more tuned time-varying stimulation fields with predetermined profiles. Examples of mammalian cells or tissues are chondrocytes, osteoblasts, osteocytes, osteoclasts, nucleus pulposus, associated tissue, or any combination. The resulted modification on gene regulation of these cells, tissues or bones may promote the retention, repair of and reduction of compromised mammalian cartilage, bone, and associated tissue.

Goodwin, Thomas J.↗
DOE OSTI2025

PERCEPTIVE: an R shiny $\underline{p}$ipelin$\underline{e}$ for the p$\underline{r}$edi$\underline{c}$tion of $\underline{ep}$igenetic modula$\underline{t}$ors $\underline{i}$n no$\underline{v}$el sp$\underline{e}$cies

Epigenetic processes are central to regulating gene expression, genome stability, and metabolic function across the tree of life; yet, their roles remain underexplored in microalgae, especially as new species continue to be identified and characterized. This is likely due to the cumbersome nature and species-dependent attributes of epigenetic wet-lab methodologies, which preclude the rapid identification of epigenetic modifications and modulators. However, there is high conservation of epigenetic processes from budding yeast to humans; in many cases, one may infer how behavior and function are epigenetically regulated in novel species by identifying epigenetic modulators, or the proteins responsible for conferring epigenetic modifications. Here, to this end, we have developed a graphical software package, titled PERCEPTIVE (pipeline for the prediction of epigenetic modulators in novel species). This platform solely uses the genomic sequence of an algal species, and preexisting information from other model organisms, to predict the epigenetic modulators and associated modifications in algae. Predictions are presented to the user in a graphical interface, which provides literature-based interpretation of results, enabling users to quickly understand potential epigenetic processes in their algal species of interest and plan follow-up experiments. To test PERCEPTIVE, we predicted epigenetic modulators in several feedstock candidate algae species. To validate these predictions, wet-lab studies were performed, including mass spectrometry; these results underscore the high accuracy of PERCEPTIVE predictions. Overall, PERCEPTIVE represents a powerful in silico tool for the research and manipulation of algal species, which does not require a priori knowledge of epigenetics and is accessible to a broad set of investigators.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Gene regulatory networks controlling carbohydrate selective deconstruction pathways in fungi

The work performed at Clark University (PI, David Hibbett) was a subcomponent of the research lead by Jonathan Schilling at University of Minnesota (award number DE-SC0019427). The overall goal of this project was to address how fungi metabolize lignocellulose. Specifically, we targeted a carbohydrate-selective group of fungi known as 'brown rot' fungi that are well-aligned to be harness for bioconversion to biofuels and other products. These organisms orchestrate a two-step mechanism that initiates decomposition using oxidative radical-based chemistry and follows with enzymatic attack. We have helped characterize that this mechanism occurs in this sequence, but currently lack the fundamental regulatory information needed to harness these fungi for application. Thus, the major goal of this project was to use systems biology to create an integrated model of brown rot wood decay that couples fungal gene regulation with the metabolite feedbacks used to coordinate a two-step oxidative-hydrolytic mechanism. The research at Clark University focused on phylogenomic analyses of data produced by other project partners. Hence, the Clark component of the research was staged to initiate somewhat after that in other partner laboratories. The major Clark-based accomplishment was to advise on selection of fungal species for analyses of brown rot decay chemistry, and to interpret results in a phylogenetic context. The Clark University group also performed complementary analyses of gene families encoding plant cell wall-degrading enzymes in the the basidiomycete genus Lentinula, as well as analyses of substrate-specific gene expression and RNA editing in brown rot fungi.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Learning genetic perturbation effects with variational causal inference

Advances in sequencing technologies have enhanced the understanding of gene regulation in cells. In particular, Perturb-seq has enabled high-resolution profiling of the transcriptomic response to genetic perturbations at the single-cell level. This understanding has implications in functional genomics and potentially for identifying therapeutic targets. Various computational models have been developed to predict perturbational effects. While deep learning models excel at interpolating observed perturbational data, they tend to overfit in the lack of enough data and may not generalize well to unseen perturbations. In contrast, mechanistic models, such as linear causal models based on gene regulatory networks, hold greater potential for extrapolation, as they encapsulate regulatory information that can predict responses to unseen perturbations. However, their application has been limited to small studies due to overly simplistic assumptions, making them less effective in handling noisy, large-scale single-cell data. We propose a hybrid approach that combines a mechanistic causal model with variational deep learning, termed Single Cell Causal Variational Autoencoder (SCCVAE). The mechanistic model employs a learned regulatory network to represent perturbational changes as shift interventions that propagate through the learned network. SCCVAE integrates this mechanistic causal model into a variational autoencoder, generating rich, comprehensive transcriptomic responses. Our results indicate that SCCVAE exhibits superior performance over current state-of-the-art baselines for extrapolating to predict unseen perturbational responses. Additionally, for the observed perturbations, the latent space learned by SCCVAE allows for the identification of functional perturbation modules and simulation of single-gene knockdown experiments of varying penetrance, presenting a robust tool for interpreting and interpolating perturbational responses at the single-cell level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria

Abstract Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ 70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ 70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.

42 ENGINEERING↗
DOE OSTI2025

Multiplexed profiling of transcriptional regulators in plant cells

Transcriptional regulators play key roles in plant growth, development and environmental responses; however, understanding how their regulatory activity is encoded at the protein level has been hindered by a lack of multiplexed large-scale methods to characterize protein libraries in planta. Here we present enrichment of nuclear trans-elements reporter assay in plants with sequencing (ENTRAP-seq), a high-throughput method that introduces protein-coding libraries into plant cells to drive a nuclear magnetic sorting-based reporter, enabling multiplexed measurement of regulatory activity from thousands of protein variants. Using ENTRAP-seq and machine learning, we screen 1,495 plant viruses and identify hundreds of putative transcriptional regulatory domains found in structural proteins and enzymes not associated with gene regulation. In addition, we combine ENTRAP-seq with machine-guided design to engineer the activity of a plant transcription factor in a semirational fashion. Our findings demonstrate how scalable protein function assays deployed in planta will enable the characterization of natural and synthetic coding diversity in plants.

Alamos, Simon↗
NASA NTRS1999

Delayed expression of hpS2 and prolonged expression of CIP1/WAF1/SDI1 in human tumour cells irradiated with X-rays, fission neutrons or 1 GeV/nucleon Fe ions

PURPOSE: Differences in gene expression underlie the phenotypic differences between irradiated and unirradiated cells. The goal was to identify late-transcribed genes following irradiations differing in quality, and to determine the RBE of 1 GeV/n Fe ions. MATERIALS AND METHODS: Clonogenic assay was used to determine the RBE of Fe ions. Differential hybridization to cDNA target clones was used to detect differences in expression of corresponding genes in mRNA samples isolated from MCF7 cells irradiated with iso-survival doses of Fe ions (0 or 2.5 Gy) or fission neutrons (0 or 1.2 Gy) 7 days earlier. Northern analysis was used to confirm differential expression of cDNA-specific mRNA and to examine expression kinetics up to 2 weeks after irradiation. RESULTS: Fe ion RBE values were between 2.2 and 2.6 in the lines examined. Two of 17 differentially expressed cDNA clones were characterized. hpS2 mRNA was elevated from 1 to 14 days after irradiation, whereas CIP1/WAF1/SDI1 remained elevated from 3 h to 14 days after irradiation. Induction of hpS2 mRNA by irradiation was independent of p53, whereas induction of CIP1/WAF1/SDI1 was observed only in wild-type p53 lines. CONCLUSIONS: A set of coordinately regulated genes, some of which are independent of p53, is associated with change in gene expression during the first 2 weeks post-irradiation.

NASA Discipline Radiation Health↗
DOE OSTI2023

Influence of Mild Chronic Stress and Social Isolation on Acute Ozone-Induced Alterations in Stress Biomarkers and Brain-Region-Specific Gene Expression in Male Wistar–Kyoto Rats

Individuals with psychosocial stress often experience an exaggerated response to air pollutants. Ozone (O 3 ) exposure has been associated with the activation of the neuroendocrine stress-response system. We hypothesized that preexistent mild chronic stress plus social isolation (CS), or social isolation (SI) alone, would exacerbate the acute effects of O 3 exposure on the circulating adrenal-derived stress hormones, and the expression of the genes regulating glucocorticoid stress signaling via an altered stress adaptation in a brain-region-specific manner. Male Wistar–Kyoto rats (5 weeks old) were socially isolated, plus were subjected to either CS (noise, confinement, fear, uncomfortable living, hectic activity, and single housing), SI (single housing only, restricted handling and no enrichment) or no stress (NS; double housing, frequent handling and enrichment provided) for 8 weeks. The rats were then exposed to either air or O 3 (0.8 ppm for 4 h), and the samples were collected immediately after. The indicators of sympathetic and hypothalamic–pituitary axis (HPA) activation (i.e., epinephrine, corticosterone, and lymphopenia) increased with O 3 exposure, but there were no effects from CS or SI, except for the depletion of serum BDNF. CS and SI revealed small changes in brain-region-specific glucocorticoid-signaling-associated markers of gene expression in the air-exposed rats (hypothalamic Nr3c1, Nr3c2 Hsp90aa1, Hspa4 and Cnr1 inhibition in SI; hippocampal HSP90aa1 increase in SI; and inhibition of the bed nucleus of the stria terminalis (BNST) Cnr1 in CS). Gene expression across all brain regions was altered by O 3 , reflective of glucocorticoid signaling effects, such as Fkbp5 in NS, CS and SI. The SI effects on Fkbp5 were greatest for SI in BNST. O 3 increased Cnr2 expression in the hypothalamus and olfactory bulbs of the NS and SI groups. O 3 , in all stress conditions, generally inhibited the expression of Nr3c1 in all brain regions, Nr3c2 in the hippocampus and hypothalamus and Bdnf in the hippocampus. SI, in general, showed slightly greater O 3 -induced changes when compared to NS and CS. Serum metabolomics revealed increased sphingomyelins in the air-exposed SI and O 3 -exposed NS, with underlying SI dampening some of the O 3 -induced changes. These results suggest a potential link between preexistent SI and acute O 3 -induced increases in the circulating adrenal-derived stress hormones and brain-region-specific gene expression changes in glucocorticoid signaling, which may partly underlie the stress dynamic in those with long-term SI.

gene expression↗
DOE OSTI2023

Grf10 regulates the response to copper, iron, and phosphate in Candida albicans

Abstract The pathogenic yeast, Candida albicans, and other microbes must be able to handle drastic changes in nutrient availability within the human host. Copper, iron, and phosphate are essential micronutrients for microbes that are sequestered by the human host as nutritional immunity; yet high copper levels are employed by macrophages to induce toxic oxidative stress. Grf10 is a transcription factor important for regulating genes involved in morphogenesis (filamentation, chlamydospore formation) and metabolism (adenylate biosynthesis, 1-carbon metabolism). The grf10Δ mutant exhibited resistance to excess copper in a gene dosage-dependent manner but grew the same as the wild type in response to other metals (calcium, cobalt, iron, manganese, and zinc). Point mutations in the conserved residues D302 and E305, within a protein interaction region, conferred resistance to high copper and induced hyphal formation similar to strains with the null allele. The grf10Δ mutant misregulated genes involved with copper, iron, and phosphate uptake in YPD medium and mounted a normal transcriptional response to high copper. The mutant accumulated lower levels of magnesium and phosphorus, suggesting that copper resistance is linked to phosphate metabolism. Our results highlight new roles for Grf10 in copper and phosphate homeostasis in C. albicans and underscore the fundamental role of Grf10 in connecting these with cell survival.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Revealing systematic changes in the transcriptome during the transition from exponential growth to stationary phase

ABSTRACT The composition of bacterial transcriptomes is determined by the transcriptional regulatory network (TRN). The TRN regulates the transition from one physiological state to another. Here, we use independent component analysis to monitor the composition of the transcriptome during the transition from the exponential growth phase to the stationary phase. With Escherichia coli K-12 MG1655 as a model strain, we trigger the transition using carbon, nitrogen, and sulfur starvation. We find that (i) the transition to the stationary phase accompanies common transcriptome changes, including increased stringent responses and reduced production of cellular building blocks and energy regardless of the limiting element; (ii) condition-specific changes are strongly associated with transcriptional regulators ( e.g. , Crp, NtrC, CysB, Cbl) responsible for metabolizing the limiting element; and (iii) the shortage of each limiting element differentially affects the production of amino acids and extracellular polymers. This study demonstrates how the combination of genome-scale datasets and new data analytics reveals the fundamental characteristics of a key transition in the life cycle of bacteria. IMPORTANCE Nutrient limitations are critical environmental perturbations in bacterial physiology. Despite its importance, a detailed understanding of how bacterial transcriptomes are adjusted has been limited. By utilizing independent component analysis (ICA) to decompose transcriptome data, this study reveals key regulatory events that enable bacteria to adapt to nutrient limitations. The findings not only highlight common responses, such as the stringent response, but also condition-specific regulatory shifts associated with carbon, nitrogen, and sulfur starvation. The insights gained from this work advance our knowledge of bacterial physiology, gene regulation, and metabolic adaptation.

Lim, Hyun Gyu (ORCID:0000000204692388)↗