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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Corrected Score Function Framework for Modelling Circadian Gene Expression

Many biological processes display oscillatory behaviour based on an approximately 24 h internal timing system specific to each individual. One process of particular interest is gene expression, for which several circadian transcriptomic studies have identified associations between gene expression during a 24 h period and an individual's health. A challenge with analysing data from these studies is that each individual's internal timing system is offset relative to the 24 h day-night cycle, where day–night cycle time is recorded for each collected sample. Laboratory procedures can accurately determine each individual's offset and determine the internal time of sample collection. However, these laboratory procedures are labour-intensive and expensive. Here, in this paper, we propose a corrected score function framework to obtain a regression model of gene expression given internal time when the offset of each individual is too burdensome to determine. A feature of this framework is that it does not require the probability distribution generating offsets to be symmetric with a mean of zero. Simulation studies validate the use of this corrected score function framework for cosinor regression, which is prevalent in circadian transcriptomic studies. Illustrations with data from three circadian transcriptomic studies further demonstrate that the proposed framework consistently mitigates bias relative to using a score function that does not account for this offset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Increased acid resistance of the archaeon, Metallosphaera sedula by adaptive laboratory evolution

Abstract Extremely thermoacidophilic members of the Archaea such as the lithoautotroph, Metallosphaera sedula, are among the most acid resistant forms of life and are of great relevance in bioleaching. Here, adaptive laboratory evolution was used to enhance the acid resistance of this organism while genomics and transcriptomics were used in an effort to understand the molecular basis for this trait. Unlike the parental strain, the evolved derivative, M. sedula SARC-M1, grew well at pH of 0.90. Enargite (Cu3AsS4) bioleaching conducted at pH 1.20 demonstrated SARC-M1 leached 23.78 % more copper relative to the parental strain. Genome re-sequencing identified two mutations in SARC-M1 including a nonsynonymous mutation in Msed_0408 (an amino acid permease) and a deletion in pseudogene Msed_1517. Transcriptomic studies by RNA-seq of wild type and evolved strains at various low pH values demonstrated there was enhanced expression of genes in M. sedula SARC-M1 encoding membrane complexes and enzymes that extrude protons or that catalyze proton-consuming reactions. In addition, M. sedula SARC-M1 exhibited reduced expression of genes encoding enzymes that catalyze proton-generating reactions. These unique genomic and transcriptomic features support a model for increased acid resistance arising from enhanced control over cytoplasmic pH.

Ai, Chenbing↗
DOE OSTI2013

Pairwise comparisons of ten porcine tissues identify differential transcriptional regulation at the gene, isoform, promoter and transcription start site level

Highlights: •Transcriptome sequencing yielded 223 mill porcine RNA-seq reads, and 59,000 transcribed locations. •Establishment of unique transcription profiles for ten porcine tissues including four brain tissues. •Comparison of transcription profiles at gene, isoform, promoter and transcription start site level. •Highlights a high level of regulation of neuro-related genes at both gene, isoform, and TSS level. •Our results emphasize the pig as a valuable animal model with respect to human biological issues. -- Abstract: The transcriptome is the absolute set of transcripts in a tissue or cell at the time of sampling. In this study RNA-Seq is employed to enable the differential analysis of the transcriptome profile for ten porcine tissues in order to evaluate differences between the tissues at the gene and isoform expression level, together with an analysis of variation in transcription start sites, promoter usage, and splicing. Totally, 223 million RNA fragments were sequenced leading to the identification of 59,930 transcribed gene locations and 290,936 transcript variants using Cufflinks with similarity to approximately 13,899 annotated human genes. Pairwise analysis of tissues for differential expression at the gene level showed that the smallest differences were between tissues originating from the porcine brain. Interestingly, the relative level of differential expression at the isoform level did generally not vary between tissue contrasts. Furthermore, analysis of differential promoter usage between tissues, revealed a proportionally higher variation between cerebellum (CBE) versus frontal cortex and cerebellum versus hypothalamus (HYP) than in the remaining comparisons. In addition, the comparison of differential transcription start sites showed that the number of these sites is generally increased in comparisons including hypothalamus in contrast to other pairwise assessments. A comprehensive analysis of one of the tissue contrasts, i.e. cerebellum versus heart for differential variation at the gene, isoform, and transcription start site (TSS), and promoter level showed that several of the genes differed at all four levels. Interestingly, these genes were mainly annotated to the “electron transport chain” and neuronal differentiation, emphasizing that “tissue important” genes are regulated at several levels. Furthermore, our analysis shows that the “across tissue approach” has a promising potential when screening for possible explanations for variations, such as those observed at the gene expression levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Network signatures of cellular immortalization in human lymphoblastoid cell lines

Highlights: •We identified network signatures of LCL immortalization from transcriptomic profiles. •More than 41% of DEGs are possibly regulated by miRNAs in LCLs. •MicroRNA target genes in LCLs are involved in apoptosis and immune-related functions. •This approach is useful to find functional miRNA targets in specific cell conditions. -- Abstract: Human lymphoblastoid cell line (LCL) has been used as an in vitro cell model in genetic and pharmacogenomic studies, as well as a good model for studying gene expression regulatory machinery using integrated genomic analyses. In this study, we aimed to identify biological networks of LCL immortalization from transcriptomic profiles of microRNAs and their target genes in LCLs. We first selected differentially expressed genes (DEGs) and microRNAs (DEmiRs) between early passage LCLs (eLCLs) and terminally differentiated late passage LCLs (tLCLs). The in silico and correlation analysis of these DEGs and DEmiRs revealed that 1098 DEG–DEmiR pairs were found to be positively (n = 591 pairs) or negatively (n = 507 pairs) correlated with each other. More than 41% of DEGs are possibly regulated by miRNAs in LCL immortalizations. The target DEGs of DEmiRs were enriched for cellular functions associated with apoptosis, immune response, cell death, JAK–STAT cascade and lymphocyte activation while non-miRNA target DEGs were over-represented for basic cell metabolisms. The target DEGs correlated negatively with miR-548a-3p and miR-219-5p were significantly associated with protein kinase cascade, and the lymphocyte proliferation and apoptosis, respectively. In addition, the miR-106a and miR-424 clusters located in the X chromosome were enriched in DEmiR–mRNA pairs for LCL immortalization. In this study, the integrated transcriptomic analysis of LCLs could identify functional networks of biologically active microRNAs and their target genes involved in LCL immortalization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Transcriptional pathways linked to fetal and maternal hepatic dysfunction caused by gestational exposure to perfluorooctanoic acid (PFOA) or hexafluoropropylene oxide-dimer acid (HFPO-DA or GenX) in CD-1 mice

Per- and polyfluoroalkyl substances (PFAS) comprise a diverse class of chemicals used in industrial processes, consumer products, and fire-fighting foams which have become environmental pollutants of concern due to their persistence, ubiquity, and associations with adverse human health outcomes, including in pregnant persons and their offspring. Multiple PFAS are associated with adverse liver outcomes in adult humans and toxicological models, but effects on the developing liver are not fully described. Here we performed transcriptomic analyses in the mouse to investigate the molecular mechanisms of hepatic toxicity in the dam and its fetus after exposure to two different PFAS, perfluorooctanoic acid (PFOA) and its replacement, hexafluoropropylene oxide-dimer acid (HFPO-DA, known as GenX). Pregnant CD-1 mice were exposed via oral gavage from embryonic day (E) 1.5-17.5 to PFOA (0, 1, or 5 mg/kg-d) or GenX (0, 2, or 10 mg/kg-d). Maternal and fetal liver RNA was isolated (N = 5 per dose/group) and the transcriptome analyzed by Affymetrix Array. Differentially expressed genes (DEG) and differentially enriched pathways (DEP) were obtained. DEG patterns were similar in maternal liver for 5 mg/kg PFOA, 2 mg/kg GenX, and 10 mg/kg GenX (R2: 0.46-0.66). DEG patterns were similar across all 4 dose groups in fetal liver (R2: 0.59-0.81). There were more DEGs in fetal liver compared to maternal liver at the low doses for both PFOA (fetal = 69, maternal = 8) and GenX (fetal = 154, maternal = 93). Upregulated DEPs identified across all groups included Fatty Acid Metabolism, Peroxisome, Oxidative Phosphorylation, Adipogenesis, and Bile Acid Metabolism. Transcriptome-phenotype correlation analyses demonstrated > 1000 maternal liver DEGs were significantly correlated with maternal relative liver weight (R 2 >0.92). These findings show shared biological pathways of liver toxicity for PFOA and GenX in maternal and fetal livers in CD-1 mice. The limited overlap in specific DEGs between the dam and fetus suggests the developing liver responds differently than the adult liver to these chemical stressors. This work helps define mechanisms of hepatic toxicity of two structurally unique PFAS and may help predict latent consequences of developmental exposure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Predictive toxicology using systemic biology and liver microfluidic “on chip” approaches: Application to acetaminophen injury

We have analyzed transcriptomic, proteomic and metabolomic profiles of hepatoma cells cultivated inside a microfluidic biochip with or without acetaminophen (APAP). Without APAP, the results show an adaptive cellular response to the microfluidic environment, leading to the induction of anti-oxidative stress and cytoprotective pathways. In presence of APAP, calcium homeostasis perturbation, lipid peroxidation and cell death are observed. These effects can be attributed to APAP metabolism into its highly reactive metabolite, N-acetyl-p-benzoquinone imine (NAPQI). That toxicity pathway was confirmed by the detection of GSH-APAP, the large production of 2-hydroxybutyrate and 3-hydroxybutyrate, and methionine, cystine, and histidine consumption in the treated biochips. Those metabolites have been reported as specific biomarkers of hepatotoxicity and glutathione depletion in the literature. In addition, the integration of the metabolomic, transcriptomic and proteomic collected profiles allowed a more complete reconstruction of the APAP injury pathways. To our knowledge, this work is the first example of a global integration of microfluidic biochip data in toxicity assessment. Our results demonstrate the potential of that new approach to predictive toxicology. -- Highlights: ► We cultivated liver cells in microfluidic biochips ► We integrated transcriptomic, proteomic and metabolomics profiles ► Pathways reconstructions were proposed in control and acetaminophen treated cultures ► Biomarkers were identified ► Comparisons with in vivo studies were proposed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Compound-specific effects of diverse neurodevelopmental toxicants on global gene expression in the neural embryonic stem cell test (ESTn)

Alternative assays for developmental toxicity testing are needed to reduce animal use in regulatory toxicology. The in vitro murine neural embryonic stem cell test (ESTn) was designed as an alternative for neurodevelopmental toxicity testing. The integration of toxicogenomic-based approaches may further increase predictivity as well as provide insight into underlying mechanisms of developmental toxicity. In the present study, we investigated concentration-dependent effects of six mechanistically diverse compounds, acetaldehyde (ACE), carbamazepine (CBZ), flusilazole (FLU), monoethylhexyl phthalate (MEHP), penicillin G (PENG) and phenytoin (PHE), on the transcriptome and neural differentiation in the ESTn. All compounds with the exception of PENG altered ESTn morphology (cytotoxicity and neural differentiation) in a concentration-dependent manner. Compound induced gene expression changes and corresponding enriched gene ontology biological processes (GO–BP) were identified after 24 h exposure at equipotent differentiation-inhibiting concentrations of the compounds. Both compound-specific and common gene expression changes were observed between subsets of tested compounds, in terms of significance, magnitude of regulation and functionality. For example, ACE, CBZ and FLU induced robust changes in number of significantly altered genes (≥ 687 genes) as well as a variety of GO–BP, as compared to MEHP, PHE and PENG (≤ 55 genes with no significant changes in GO–BP observed). Genes associated with developmentally related processes (embryonic morphogenesis, neuron differentiation, and Wnt signaling) showed diverse regulation after exposure to ACE, CBZ and FLU. In addition, gene expression and GO–BP enrichment showed concentration dependence, allowing discrimination of non-toxic versus toxic concentrations on the basis of transcriptomics. This information may be used to define adaptive versus toxic responses at the transcriptome level.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Decreased hepatotoxic bile acid composition and altered synthesis in progressive human nonalcoholic fatty liver disease

Bile acids (BAs) have many physiological roles and exhibit both toxic and protective influences within the liver. Alterations in the BA profile may be the result of disease induced liver injury. Nonalcoholic fatty liver disease (NAFLD) is a prevalent form of chronic liver disease characterized by the pathophysiological progression from simple steatosis to nonalcoholic steatohepatitis (NASH). The hypothesis of this study is that the ‘classical’ (neutral) and ‘alternative’ (acidic) BA synthesis pathways are altered together with hepatic BA composition during progression of human NAFLD. This study employed the use of transcriptomic and metabolomic assays to study the hepatic toxicologic BA profile in progressive human NAFLD. Individual human liver samples diagnosed as normal, steatosis, and NASH were utilized in the assays. The transcriptomic analysis of 70 BA genes revealed an enrichment of downregulated BA metabolism and transcription factor/receptor genes in livers diagnosed as NASH. Increased mRNA expression of BAAT and CYP7B1 was observed in contrast to decreased CYP8B1 expression in NASH samples. The BA metabolomic profile of NASH livers exhibited an increase in taurine together with elevated levels of conjugated BA species, taurocholic acid (TCA) and taurodeoxycholic acid (TDCA). Conversely, cholic acid (CA) and glycodeoxycholic acid (GDCA) were decreased in NASH liver. These findings reveal a potential shift toward the alternative pathway of BA synthesis during NASH, mediated by increased mRNA and protein expression of CYP7B1. Overall, the transcriptomic changes of BA synthesis pathway enzymes together with altered hepatic BA composition signify an attempt by the liver to reduce hepatotoxicity during disease progression to NASH. - Highlights: ► Altered hepatic bile acid composition is observed in progressive NAFLD. ► Bile acid synthesis enzymes are transcriptionally altered in NASH livers. ► Increased levels of taurine and conjugated bile acids are observed in NASH. ► Hepatic bile acid synthesis shifts toward the alternative pathway in NASH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Sex-related differences in murine hepatic transcriptional and proteomic responses to TCDD

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is an environmental contaminant that produces myriad toxicities in most mammals. In rodents alone, there is a huge divergence in the toxicological response across species, as well as among different strains within a species. But there are also significant differences between males and females animals of a single strain. These differences are inconsistent across model systems: the severity of toxicity is greater in female rats than males, while male mice and guinea pigs are more sensitive than females. Because the specific events that underlie this difference remain unclear, we characterized the hepatic transcriptional response of adult male and female C57BL/6 mice to 500 μg/kg TCDD at multiple time-points. The transcriptional profile diverged significantly between the sexes. Female mice demonstrated a large number of altered transcripts as early as 6 h following treatment, suggesting a large primary response. Conversely, male animals showed the greatest TCDD-mediated response 144 h following exposure, potentially implicating significant secondary responses. Nr1i3 was statistically significantly induced at all time-points in the sensitive male animals. This mRNA encodes the constitutive androstane receptor (CAR), a transcription factor involved in the regulation of xenobiotic metabolism, lipid metabolism, cell cycle and apoptosis. Surprisingly though, changes at the protein level (aside from the positive control, CYP1A1) were modest, with only FMO3 showing clear induction, and no genes with sex-differences. Thus, while male and female mice show transcriptional differences in their response to TCDD, their association with TCDD-induced toxicities remains unclear. - Highlights: • Differences exist between the toxicity phenotypes to TCDD in male and female mice. • TCDD-mediated transcriptomic differences were identified between the sexes. • Resistant female mice displayed a large, early-onset, transcriptomic response. • Sensitive male mice displayed a large, late-onset, transcriptomic response. • Fmo2, Fmo3 and Nr1i3 were induced across the time-course in only male mice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Transcriptional profiling of rat white adipose tissue response to 2,3,7,8-tetrachlorodibenzo-ρ-dioxin

Polychlorinated dibenzodioxins are environmental contaminants commonly produced as a by-product of industrial processes. The most potent of these, 2,3,7,8-tetrachlorodibenzo-ρ-dioxin (TCDD), is highly lipophilic, leading to bioaccumulation. White adipose tissue (WAT) is a major site for energy storage, and is one of the organs in which TCDD accumulates. In laboratory animals, exposure to TCDD causes numerous metabolic abnormalities, including a wasting syndrome. We therefore investigated the molecular effects of TCDD exposure on WAT by profiling the transcriptomic response of WAT to 100 μg/kg of TCDD at 1 or 4 days in TCDD-sensitive Long-Evans (Turku/AB; L-E) rats. A comparative analysis was conducted simultaneously in identically treated TCDD-resistant Han/Wistar (Kuopio; H/W) rats one day after exposure to the same dose. We sought to identify transcriptomic changes coinciding with the onset of toxicity, while gaining additional insight into later responses. More transcriptional responses to TCDD were observed at 4 days than at 1 day post-exposure, suggesting WAT shows mostly secondary responses. Two classic AHR-regulated genes, Cyp1a1 and Nqo1, were significantly induced by TCDD in both strains, while several genes involved in the immune response, including Ms4a7 and F13a1 were altered in L-E rats alone. We compared genes affected by TCDD in rat WAT and human adipose cells, and observed little overlap. Interestingly, very few genes involved in lipid metabolism exhibited altered expression levels despite the pronounced lipid mobilization from peripheral fat pads by TCDD in L-E rats. Of these genes, the lipolysis-associated Lpin1 was induced slightly over 2-fold in L-E rat WAT on day 4. - Highlights: • Exposure to TCDD causes wasting syndrome in L-E rats but not in H/W rats. • We examined the transcriptome of TCDD-treated L-E and H/W rat white adipose tissue. • L-E WAT demonstrated altered abundance of several genes involved in immune response. • Few genes had altered abundance in both L-E rat WAT and human adipocytes (hMADS). • Pmepa1 was induced in both L-E WAT and differentiated hMADS cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

Roell, Garrett W.↗
DOE OSTI2021

Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer

Cervical lymph node metastasis is the leading cause of poor prognosis in oral tongue squamous cell carcinoma and also occurs in the early stages. The current clinical diagnosis depends on a physical examination that is not enough to determine whether micrometastasis remains. The transcriptome profiling technique has shown great potential for predicting micrometastasis by capturing the dynamic activation state of genes. However, there are several technical challenges in using transcriptome data to model patient conditions: (1) An Insufficient number of samples compared to the number of genes, (2) Complex dependence between genes that govern the cancer phenotype, and (3) Heterogeneity between patients between cohorts that differ geographically and racially. We developed a computational framework to learn the subnetwork representation of the transcriptome to discover network biomarkers and determine the potential of metastasis in early oral tongue squamous cell carcinoma. Our method achieved high accuracy in predicting the potential of metastasis in two geographically and racially different groups of patients. The robustness of the model and the reproducibility of the discovered network biomarkers show great potential as a tool to diagnose lymph node metastasis in early oral cancer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A multi-omic characterization of the physiological responses to salt stress in Scenedesmus obliquus UTEX393

Scenedesmus obliquus UTEX393 is a promising microalgal candidate for sustainable biomanufacturing but its limited halotolerance hinders large-scale cultivation in saline environments. To investigate the molecular basis of salt stress responses, we conducted a comprehensive multi-omic analysis integrating genomics, transcriptomics, proteomics, lipidomics, metabolomics, and DNA affinity purification sequencing (DAP-seq). An improved nuclear genome assembly and annotation yielded 19,017 gene models and a 97% BUSCO completeness score, enabling construction of a genome-scale metabolic model. Comparing 15 ppt salinity stress to 5 ppt control, growth and productivity were significantly reduced, accompanied by widespread transcriptomic and proteomic changes. Transcriptomic analysis revealed downregulation of photosynthetic machinery and energy conservation genes, and upregulation of stress-responsive elements such as expansins, flavodoxins, and osmoprotectants. Lipidomic profiling showed accumulation of triacylglycerols (TAGs) and degradation of galactosyl lipids, consistent with a shift toward lipid biosynthesis to mitigate redox imbalance. Depletion of key polar metabolites and branched-chain amino acids suggested a rerouting of central carbon metabolism under stress. DAP-seq identified key transcription factors, including LHY1 and SPL12, that target central metabolic enzymes involved in redox balancing, such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and malate dehydrogenase (MDH). These findings establish a regulatory-metabolic framework linking redox stress to lipid accumulation and reveal potential engineering targets to enhance salt tolerance. Overall, the multi-omic analysis supports the “overflow” hypothesis, where impaired photosynthesis results in excess reducing equivalents being diverted into TAG synthesis and highlights transcriptional regulators as candidates for improving algal robustness in brackish environments.

09 BIOMASS FUELS↗
DOE OSTI2016

Ni induces the CRR1-dependent regulon revealing overlap and distinction between hypoxia and Cu deficiency responses in Chlamydomonas reinhardtii

The selectivity of metal sensors for a single metal ion is critical for cellular metal homeostasis. A suite of metal-responsive regulators is required to maintain a prescribed balance of metal ions ensuring that each apo-protein binds the correct metal. However, there are cases when non-essential metals ions disrupt proper metal sensing. Here, an analysis of the Ni-responsive transcriptome of the green alga Chlamydomonas reinhardtii reveals that Ni artificially turns on the CRR1-dependent Cu-response regulon. Since this regulon also responds to hypoxia, a combinatorial transcriptome analysis was leveraged to gain insight into the mechanisms by which Ni interferes with the homeostatic regulation of Cu and oxygen status. Based on parallels with the effect of Ni on the hypoxic response in animals, we propose that a possible link between Cu, oxygen and Ni sensing is an as yet uncharacterized prolyl hydroxylase that regulates a co-activator of CRR1. This analysis also identified transcriptional responses to the pharmacological activation of the Cu-deficiency regulon. Although the Ni-responsive CRR1 regulon is composed of 56 genes (defined as the primary response), 259 transcripts responded to Ni treatment only when a copy of the wild-type CRR1 gene was present. The genome-wide impact of CRR1 target genes on the transcriptome was also evident from the 210 transcripts that were at least 2-fold higher in the crr1 strain, where the abundance of many CRR1 targets was suppressed. Additionally, we identified 120 transcripts that responded to Ni independent of CRR1 function. Thus, the putative functions of the proteins encoded by these transcripts suggest that high Ni results in protein damage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations and splice variants identified in cancer cells are translated. Herein we therefore describe a proteogenomic data integration tool (QUILTS) and illustrate its application to whole genome, transcriptome and global MS peptide sequence datasets generated from a pair of luminal and basal-like breast cancer patient derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS process replicates. Despite over thirty sample replicates, only about 10% of all SNV (somatic and germline) were detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNV without a detectable mRNA transcript were also observed demonstrating the transcriptome coverage was also incomplete (~80%). In contrast to germ-line variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than the luminal tumor raising the possibility of differential translation or protein degradation effects. In conclusion, the QUILTS program integrates DNA, RNA and peptide sequencing to assess the degree to which somatic mutations are translated and therefore biologically active. By identifying gaps in sequence coverage QUILTS benchmarks current technology and assesses progress towards whole cancer proteome and transcriptome analysis.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2013

GIM3E: Condition-specific Models of Cellular Metabolism Developed from Metabolomics and Expression Data

Motivation: Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been reported. Results: GIMMME (Gene Inactivation Moderated by Metabolism, Metabolomics, and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics, and intracellular metabolomics data. GIMMME establishes metabolite utilization requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions, and also provides calculations of the turnover (production / consumption) flux of metabolites. GIMMME was employed to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. Availability: GIMMME has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/

Environmental Molecular Sciences Laboratory↗
DOE OSTI2026

Single-cell and spatial omics in plants: from cellular atlases to regulatory mechanisms

Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic studies by enabling gene expression profiling at the resolution of individual cells within and across a broad range of tissue types, revealing cellular heterogeneity that is obscured in bulk tissue transcriptomes. Over the past decade, improvements in microfluidics and library preparation have drastically increased throughput, allowing tens of thousands of cells to be assayed in a single experiment. Although initially developed in animal systems, scRNA-seq has rapidly emerged as a powerful and widely adopted approach in plant biology. Beyond transcriptomics, the integration of single-cell data with chromatin accessibility, proteomics, metabolomics, and spatial omics is enabling a system-level understanding of plant gene regulation and cellular organization. Network-based analytical frameworks further support the reconstruction of gene regulatory networks and the interpretation of complex single-cell data. In this review, we summarize the current technological landscape of plant single-cell studies, discuss key experimental and analytical challenges, and review emerging strategies for validating single-cell discoveries. We also discuss future directions in applying single-cell technologies to woody perennials plants and bioenergy-relevant crops, emphasizing their potential to accelerate the discovery of cell type-specific regulatory mechanisms underlying growth, stress resilience, and biomass production.

Li, Miaomiao [ORNL] (ORCID:0000000321326168)↗