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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Pipeline for Assessing the Quality of Rna-Seq Datasets in GeneLab

Transcriptome profiling by RNA sequencing (RNA-seq) is a powerful approach to identify gene expression changes in organisms exposed to unique environments such as spaceflight. One of the challenges of evaluating RNA-seq data both within and across different space-relevant studies is the ability to control for technical differences, including the use of different library preparation kits, sequencing platforms, RNA yield, and person-to-person variation. To help address this issue, the National Institute of Standards and Technology (NIST, nist.gov) initiated a consortium, at the request of industry and academia, to develop a set of controls for gene expression measurements. The result was a set of 92 unlabeled, polyadenylated transcripts that range from 250 – 2,000 nucleotides in length to mimic natural eukaryotic mRNAs. These External RNA Controls Consortium (ERCC) genes can be used in any RNA-seq experiment, by adding known concentrations of the ERCC genes to samples after RNA extraction, to offer a standard measurement for data comparison. At NASA GeneLab, we employ these controls as part of our standard operating procedures for every in-house RNA-seq study to assess the limit of detection, dynamic range, and power of differential expression analysis both within and across experiments. Here we will discuss the use, benefits, and limitations of ERCC genes and other types of controls, such as universal RNA references, to generate quality control information for RNA-seq studies conducted at GeneLab.

GeneLab↗
NASA NTRS2022

A Multi-omics Longitudinal Study of the Murine Retinal Response to Chronic Low-dose Irradiation and Simulated Microgravity

The space environment includes unique hazards like radiation and microgravity which can adversely affect biological systems. We assessed a multi-omics NASA GeneLab dataset where mice were hindlimb unloaded and/or gamma irradiated for 21 days followed by retinal analysis at 7 days, 1 month or 4 months post-exposure. We compared time-matched epigenomic and transcriptomic retinal profiles resulting in a total of 4,178 differentially methylated loci or regions, and 457 differentially expressed genes. Highest correlation in methylation difference was seen across different conditions at the same time point. Nucleotide metabolism biological processes were enriched in all groups with activation at 1 month and suppression at 7 days and 4 months. Genes and processes related to Notch and Wnt signaling showed alterations 4 months post-exposure. A total of 23 genes showed significant changes in methylation and expression compared to unexposed controls, including genes involved in retinal function and inflammatory response. This multi-omics analysis interrogates the epigenomic and transcriptomic impacts of radiation and hindlimb unloading on the retina in isolation and in combination and highlights important molecular mechanisms at different post-exposure stages.

Prachi Kothiyal↗
NASA NTRSDate not supplied

A Multi-omics Longitudinal Study of the Murine Retinal Response to Chronic Low-dose Irradiation and/or Simulated Microgravity

The space environment includes unique hazards like radiation and microgravity which adversely affect physiology and behavior of humans and rodent models. To better characterize the retinal response to spaceflight, we assessed a multi-omics NASA GeneLab dataset where 6-month-old female mice were gamma irradiated and/or hindlimb unloaded for 21 days followed by whole transcriptome shotgun sequencing (RNA-Seq) and reduced representation bisulfite sequencing (RRBS) of retina samples collected at 7 days, 1 month or 4 months post-exposure. We compared time-matched epigenomic and transcriptomic retinal profiles revealing a total of 4,178 differentially methylated loci or regions, and 457 differentially expressed genes. Highest correlation in methylation differences was seen across different conditions at the same time point (e.g., between radiation exposure and hindlimb unloaded at 7 days). Biological processes related to nucleotide metabolism were enriched in all groups with activation at 1 month and suppression at 7 days and 4 months. Genes and processes related to Notch and Wnt signaling showed alterations 4 months post-exposure. Interestingly, Notch3 and Lrg1 showed differential patterns in the NASA Twins Study in-flight samples and in response to stressors in the murine retina in the current study. A total of 23 genes were both differentially methylated and expressed, including genes involved in retinal disease or cataract development (Crybb3, Fgfr1, Pitpnm3, Sipa1l3, Sox9) and inflammatory response (B4galt6, Ppm1a, Sphk1). To our knowledge, the current multi-omics analysis is the first multi-omics study to interrogate the epigenomic and transcriptomic impacts of radiation and hindlimb unloading on the retina in isolation and in combination. The results provide an insight into the retinal response to individual spaceflight hazard analogs and their interplay at different post-exposure stages and contributes towards a mechanistic understanding of spaceflight-induced vision impairment using ground-based models.

Prachi Kothiyal↗
NASA NTRS2022

CryoEM Structures of the Nitrogenase Complex During Catalytic Turnover

The enzyme nitrogenase couples adenosine triphosphate (ATP) hydrolysis to the multi-electron reduction of atmospheric dinitrogen into ammonia. Despite extensive research, the mechanistic details of ATP-dependent energy transduction and dinitrogen reduction by nitrogenase are not well understood, requiring new strategies to monitor its structural dynamics during catalytic action. Here we report the cryogenic electron microscopic interrogation of the nitrogenase complex under enzymatic turnover conditions, which has enabled the structural characterization of the nitrogenase reaction intermediates at high resolution for the first time. Our structures show that asymmetry governs all aspects of nitrogenase mechanism including ATP hydrolysis, protein-protein interactions, and catalysis. Furthermore, they reveal several previously unobserved, mechanistically relevant conformational changes near the catalytic iron-molybdenum cofactor that are correlated with the nucleotide-hydrolysis state of the enzyme.

Hannah L. Rutledge↗
NASA NTRS2021

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Zishuo Zeng↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗
NASA NTRS2022

Structures of the Nitrogenase Complex Prepared Under Catalytic Turnover Conditions

The enzyme nitrogenase couples adenosine triphosphate (ATP) hydrolysis to the multielectron reduction of atmospheric dinitrogen into ammonia. Despite extensive research, the mechanistic details of ATP-dependent energy transduction and dinitrogen reduction by nitrogenase are not well understood, requiring new strategies to monitor its structural dynamics during catalytic action. Here, we report cryo–electron microscopy structures of the nitrogenase complex prepared under enzymatic turnover conditions. We observe that asymmetry governs all aspects of the nitrogenase mechanism, including ATP hydrolysis, protein-protein interactions, and catalysis. Conformational changes near the catalytic iron-molybdenum cofactor are correlated with the nucleotide-hydrolysis state of the enzyme.

Hannah L. Rutledge↗
NASA NTRSDate not supplied

A Dominant Arabidopsis Thaliana ACTIN7 Mutant for Studies of Cytoskeletal-Mediated Root Gravity and Spaceflight Stress Responses

A forward genetic screen for Arabidopsis thaliana mutants that exhibited differential sensitivity to the actin-disrupting compound, latrunculin B (LatB), was conducted to uncover new players involved in actin-mediated root gravity responses. This to the isolation of a mutant that exhibited robust primary root growth at 100 nM LatB, which is a concentration that severely inhibits wild-type root elongation. Phenotypic analysis revealed that hypocotyl elongation in the dark and root hair tip growth in the mutant could tolerate LatB concentrations that impaired these processes in wild type. A cross between the mutant and wild type resulted in progeny resistance to LatB, which indicated that the mutant is dominant (hereafter referred to as LBR1 for LatB Resistant1). Filamentous-actin (F-actin) organization in LBR1 primary roots remained intact at 100 nM LatB, while that of wild type exhibited fragmented F-actin. Next generation sequencing revealed that LBR1 had a single nucleotide polymorphism (SNP) in the AT5G09810 gene that changed cytosine to a thiamine at the first exon. AT5G09810 encodes ACTIN7 (ACT7), which is one of three vegetative actin isoforms in A. thaliana. The SNP in the ACT7 gene led to a change in a single amino acid from proline at position 32 to a serine. Transgenic complementation of LBR1 plants with wild-type ACT7 under the control of the ACT7 promoter (pACT7:ACT7) and wild-type plants with LBR1, which contained the proline to serine mutation, also under the ACT7 promoter (pACT7:LBR1) confirmed that LBR1 is ACT7. The pACT7:LBR1 construct was also able to confer LatB resistance to the act7-5 and act2-3 vegetative ACT mutants. Moreover, LBR1 exhibited partial tolerance to salt and low phosphate, and enhanced root skewing on a clinostat, suggesting that site-directed engineering of vegetative ACT presents a strategy for generating stress-tolerant plants for spaceflight applications and studies of actin-mediated gravity responses.

Plant Space Biology↗
NASA NTRSDate not supplied

Somatic Mutation in Mice on the International Space Station (ISS): Guanine Substitution Suggests Link to Cancer Risk

We conducted comprehensive analysis of single nucleotide somatic mutations in mice exposed to microgravity and other factors aboard the International Space Station (ISS), using data archived in GeneLab. Animals in the experimental cohort consisted of mice that spent 37 days on the ISS within the Rodent Habitat. Ground control animals consisted of mice of identical age, sex, strain, in a terrestrial Rodent Habitat controlled for temperature, humidity and carbon dioxide levels, to match ISS conditions as closely as possible. RNA extracted from eye, liver, skeletal muscle, and kidney tissue specimens was subjected to next-generation sequencing to acquire primary data. Our analysis employed cutting-edge software developed at NASA Ames Research Center, executed on the NASA Ames Supercomputer and on another high-performance computer, for accurate variant calling of single point mutations. ISS-flown mice exhibited a notably heightened level of somatic mutation compared to control mice. The degree of somatic mutation correlated with the degree of gene expression across the four tissue types, i.e., the greatest rate of mutation accumulation was seen in highly expressed genes. We discovered that guanine substitutions were the most common type of somatic mutation. This observation is consistent with the hypothesis that DNA mutation events stem from reactive oxygen/nitrogen/chlorine species-mediated guanine oxidation induced by the spaceflight environment. Since guanine oxidation is a prominent feature of the DNA mutation landscape that accompanies malignant transformation, our findings suggest a possible link between the spaceflight environment and cancer risk that is independent of radiation carcinogenesis.

ISS↗
NASA NTRSDate not supplied

A Dominant Arabidopsis Thaliana ACTIN7 Mutant for Studies of Cytoskeletal-Mediated Root Gravity and Spaceflight Stress Responses

A forward genetic screen for Arabidopsis thaliana mutants that exhibited differential sensitivity to the actin-disrupting compound, latrunculin B (LatB), was conducted to uncover new players involved in actin-mediated root gravity responses. This led to the isolation of a mutant that exhibited robust primary root growth at 100 nM LatB, which is a concentration that severely inhibits wild-type root elongation. Phenotypic analysis revealed that hypocotyl elongation in the dark and root hair tip growth in the mutant could tolerate LatB concentrations that impaired these processes in wild type. A cross between the mutant and wild type resulted in progeny resistance to LatB, which indicated that the mutant is dominant (hereafter referred to as LBR1 for LatB Resistant1). Filamentous-actin (F-actin) organization in LBR1 primary roots remained intact at 100 nM LatB, while that of wild type exhibited fragmented F-actin. Next generation sequencing revealed that LBR1 had a single nucleotide polymorphism (SNP) in the AT5G09810 gene that changed cytosine to a thiamine at the first exon. AT5G09810 encodes ACTIN7 (ACT7), which is one of three vegetative actin isoforms in A. thaliana. The SNP in the ACT7 gene led to a change in a single amino acid from proline at position 32 to a serine. Transgenic complementation of LBR1 plants with wild-type ACT7 under the control of the ACT7 promoter (pACT7:ACT7) and wild-type plants with LBR1, which contained the proline to serine mutation, also under the ACT7 promoter (pACT7:LBR1) confirmed that LBR1 is ACT7. The pACT7:LBR1 construct was also able to confer LatB resistance to the act7-5 and act2-3 vegetative ACT mutants. Moreover, LBR1 exhibited partial tolerance to salt and low phosphate, and enhanced root skewing on a clinostat, suggesting that site-directed engineering of vegetative ACT presents a strategy for generating stress-tolerant plants for spaceflight applications and studies of actin-mediated gravity responses.

Plant Space Biology↗
NASA NTRS2021

A GTP-synthesizing ribozyme selected by metabolic coupling to an RNA polymerase ribozyme

Synthesis of RNA in early life forms required chemically activated nucleotides, perhaps in the same form of nucleoside 5′-triphosphates (NTPs) as in the contemporary biosphere. We show the development of a catalytic RNA (ribozyme) that generates the nucleoside triphosphate guanosine 5′-triphosphate (GTP) from the nucleoside guanosine and the prebiotically plausible cyclic trimetaphosphate. Ribozymes were selected from 1.6 × 1014 different randomized sequences by metabolically coupling 6-thio GTP synthesis to primer extension by an RNA polymerase ribozyme within 1016 emulsion droplets. Several functional RNAs were identified, one of which was characterized in more detail. Under optimized reaction conditions, this ribozyme produced GTP at a rate 18,000-fold higher than the uncatalyzed rate, with a turnover of 1.7-fold, and supported the incorporation of GTP into RNA oligomers in tandem with an RNA polymerase ribozyme. These results are discussed in the context of early life forms.

Arvin Akoopie↗
NASA NTRS2024

Isolation, Characterization and Genetic Manipulation of Cold-Tolerant, Manganese-Oxidizing Pseudomonas sp. Strains

Manganese-oxidizing bacteria (MnOB) produce Mn oxide minerals that can be used by humans for bioremediation but the purpose for the bacterium is less clear. This study describes the isolation and characterization of cold-tolerant MnOB strains isolated from a compost pile in Morris, Minnesota, USA: Pseudomonas sp. MS-1 and DSV-1. The strains were preliminarily identified as members of species Pseudomonas psychrophila by 16S rRNA analysis and a multi-locus phylogenetic study using a database of 88 genomes from the Pseudomonas genus. However, the average nucleotide identity (ANI) between these strains and the P. psychrophila sp. CF149 type strain was less than 93%. Thus, the two strains are members of a novel species that diverged from P. psychrophila . DSV-1 and MS-1 are cold tolerant; both grow at 4C but grow faster at 24C. Unlike the mesophilic MnOB P. putida GB-1, both strains are capable of robustly oxidizing Mn at low temperatures. Both DSV-1 and MS-1 genomes contain homologs of several Mn oxidation genes found in P. putida GB-1 ( mnxG, mcoA, mnxS1, mnxS2 and mnxR ). Random mutagenesis by transposon insertion was successfully performed in both strains and identified genes involved in Mn oxidation that were similar to those found in P. putida GB-1. Our results show that MnOB can be isolated from compost, supporting a role for Mn oxidation in plant waste degradation. The novel isolates Pseudomonas spp. DSV-1 and MS-1 both can oxidize Mn at low temperature and likely employ similar mechanisms and regulation as P. putida GB-1.

manganese oxidation↗
NASA NTRSDate not supplied

Benchmarking Computational Tools for Calling SNPs and Indels in Complex Microbial Populations

The NASA BioNutrients missions seek to understand the suitability of microorganisms for bioproduction during space flight. One topic of interest is the stability of microbial genomes during long-term ambient storage and subsequent rehydration and growth. To address these questions, samples from 8 species were flown to ISS for 5 years of desiccated storage at ambient temperature (Stasis Packs) and 2 species were packaged along with powdered media inside a bioreactor system to allow hydration and growth in microgravity (Production Packs). For both systems, Whole Genome Sequencing (WGS) of the DNA extracted from the returned samples and paired ground controls will be conducted to identify changes in genome stability due to time, storage conditions and growth in space. Across the technical replicates, ground controls, 10 timepoints, and multiple experimental conditions, ~300 samples have been selected for initial analysis with WGS sequencing to 100x coverage. A flexible and resource efficient mutation calling pipeline is needed to process this large dataset and allow for comparisons between species. Many bioinformatics tools for calling Indels and Single Nucleotide Variants (SNVs) are designed for use with pure isolates, where true variations from the reference genome are expected to dominate the reads aligning to the location of mutation. In contrast, DNA from the Stasis Pack (SP) samples was collected directly after recovery from desiccated storage and the Production Pack (PP) samples were collected after fermentation. In this context, reads with mutations are expected to be less frequent than reads that align with the reference genome, as each sample will include multiple lines of cells. Thus, BioNutrients samples are expected to be similar to samples from cancer cell or “pooled” sequencing approaches. In preparation for the analysis of the BioNutrients samples, we have tested three mutation calling tools (GATK for Microbes, BreSeq and DiscoSNP) designed for complex samples. A challenge of validating mutation identification pipelines is a lack of “Ground Truth” datasets, especially for complex samples. To compare these three tools, we sought to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO as part of the Space Algae-1 mission. Here we present a summary of these tools against the analysis originally conducted using the CRISP tool. Critical metrics are compared such as runtime, the number of SNPs, the number and size of Indels, and patterns of transversion and transitions identified by each tool are reported. By sharing these benchmarking results collected in support of the BioNutrients mission, we aim to guide others seeking to identify SNVs in similarly complex microbial samples.

Biology↗
NASA NTRSDate not supplied

A Pair of Trans-Golgi Network/Early Endosome-Localized Proteins Facilitate Cytoskeletal-Mediated Root Skewing in Arabidopsis Thaliana

Roots treated with the actin-disrupting compound Latrunculin B (LatB) show stronger gravitropic responses on Earth and dampened straightening responses on a 2-D clinostat. In related experiments using the Biological Research in Canisters (BRIC) hardware, it was found that knockouts to vegetative actin isoforms in Arabidopsis thaliana had more robust root skewing in microgravity and waved more strongly than wild type on hard agar surfaces. These results indicate that the actin cytoskeleton mediates directional root growth in space and on the ground. To gain new insights into the role of actin in directional root growth, we identified mutants that showed differential growth responses to low doses of LatB. In-depth studies of one mutant led to the identification of a trans-Golgi Network (TGN)/Early Endosome (EE)- localized protein that associates with actin. This protein called hypersensitive to LatB 1 (HLB1) colocalized with the ADP-ribosylation-factor guanine nucleotide exchange factor, MIN7/BEN1 (HOPM INTERACTOR7/BREFELDIN A-VISUALIZED ENDOCYTIC TRAFFICKING DEFECTIVE1), at the TGN/EE. HLB1 and MIN7/BEN1 were found to regulate exocytosis and endocytosis, respectively, suggesting that both proteins are involved in actin-mediated membrane traffic. Microtubules, another component of the cytoskeleton, is known to be involved in root skewing. Both hlb1 and min7/ben1 mutants exhibited dampened root skewing on the microtubule stabilizing compound taxol. Taken together, our results support the conclusion that cytoskeletal-membrane interactions contribute to directional root skewing in A. thaliana and is facilitated in part by the TGN/EE-localized HLB1 and MIN7/BEN1 proteins.

Plant Space Biology↗
DOE OSTI2021

Oxygen-responsive bacterial gene switch

The invention provided herein relates to sequence determinants that elicit certain levels of gene expression and methods for obtaining engineered ligand-responsive gene switches comprising these sequence determinants. More particularly, the invention provided herein relates to molecular building blocks (i.e., discrete nucleotide sequences), synthetic ligand-responsive gene switches comprising an assembly of these molecular building blocks, and methods of using synthetic ligand-responsive gene switches as customizable and controllable expression systems and sensors.

Kiley, Patricia J.↗
DOE OSTI2023

Translation control tool for plants

The present invention provides for a system comprising (a) first polynucleotide encoding a first promoter operatively linked to an open reading frame (ORF) encoding an endoribonuclease, or an enzymatic active fragment thereof, which cleaves a cognition sequence (cog), and (b) a second polynucleotide encoding a second promoter operatively linked to a nucleotide sequence encoding (i) a cog linked to a coding sequence of interest (COI), (ii) a cog linked to the 3′ end of a first COI and the 5′ end of a second COI, or (iii) a cog locating within a LS (or targeting sequence) linked to a COI.

Liang, Yan↗
DOE OSTI2023

Dyes in dye aggregate systems—engineering J, K, and dye packing

The present disclosure is directed to designing dyes and methods to alter the parameters controlling the dipole-dipole coupling of dyes bound to a nucleotide oligomer architecture, which are used to propagate excitons for use in next generation room temperature quantum information systems. The disclosed dyes and methods are directed to changing the dye stability, symmetry, overlap, and steric hindrance of the dyes to fine tune aggregate systems.

Knowlton, William B.↗