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NASA NTRS1992

Identification of a major continuous epitope of human alpha crystallin

Human lens proteins were digested with trypsin or V8 protease, and the resulting peptides resolved on a C18 reverse phase column. Fractions from this column were probed with polyclonal antiserum made against the whole alpha crystallin molecule. Peptides in the seropositive fraction were purified to homogeneity, then characterized by mass spectral analysis and partial Edman degradation. The tryptic and V8 digests contained only one seropositive peptide that was derived from the C-terminal region of the alpha-A molecule. To determine the exact boundaries of the epitope, various size analogues of this region were synthesized and probed with anti-alpha serum. Together, these studies demonstrate that the major continuous epitope of the alpha-A chain includes the sequence KPTSAPS, corresponding to residues 166-172 of the human alpha-A crystallin chain.

Non-NASA Center↗

NASA NTRS1992

Crystal structure of four-stranded Oxytricha telomeric DNA

The sequence d(GGGGTTTTGGGG) from the 3' overhang of the Oxytricha telomere has been crystallized and its three-dimensional structure solved to 2.5 A resolution. The oligonucleotide forms hairpins, two of which join to make a four-stranded helical structure with the loops containing four thymine residues at either end. The guanine residues are held together by cyclic hydrogen bonding and an ion is located in the centre. The four guanine residues in each segment have a glycosyl conformation that alternates between anti and syn. There are two four-stranded molecules in the asymmetric unit showing that the structure has some intrinsic flexibility.

NASA Discipline Exobiology↗

NASA NTRS1992

Recent evidence for evolution of the genetic code

The genetic code, formerly thought to be frozen, is now known to be in a state of evolution. This was first shown in 1979 by Barrell et al. (G. Barrell, A. T. Bankier, and J. Drouin, Nature [London] 282:189-194, 1979), who found that the universal codons AUA (isoleucine) and UGA (stop) coded for methionine and tryptophan, respectively, in human mitochondria. Subsequent studies have shown that UGA codes for tryptophan in Mycoplasma spp. and in all nonplant mitochondria that have been examined. Universal stop codons UAA and UAG code for glutamine in ciliated protozoa (except Euplotes octacarinatus) and in a green alga, Acetabularia. E. octacarinatus uses UAA for stop and UGA for cysteine. Candida species, which are yeasts, use CUG (leucine) for serine. Other departures from the universal code, all in nonplant mitochondria, are CUN (leucine) for threonine (in yeasts), AAA (lysine) for asparagine (in platyhelminths and echinoderms), UAA (stop) for tyrosine (in planaria), and AGR (arginine) for serine (in several animal orders) and for stop (in vertebrates). We propose that the changes are typically preceded by loss of a codon from all coding sequences in an organism or organelle, often as a result of directional mutation pressure, accompanied by loss of the tRNA that translates the codon. The codon reappears later by conversion of another codon and emergence of a tRNA that translates the reappeared codon with a different assignment. Changes in release factors also contribute to these revised assignments. We also discuss the use of UGA (stop) as a selenocysteine codon and the early history of the code.

Review↗

NASA NTRS1992

The contribution of the extracellular matrix to gravisensing in characean cells

The cell-extracellular matrix junction, which includes the cell wall and the outer surface of the plasma membrane, may be an essential region for the perception of gravity by the internodal cells of Chara corallina. Typically, when an internodal cell is oriented vertically, the downwardly directed cytoplasmic stream travels at a velocity that is 10% faster than that of the upwardly directed stream. However when the cells are treated with impermeant hydrolytic enzymes that partially digest cellulose or hemicellulose, the cells lose their ability to respond to gravity even though streaming continues. By contrast, enzymes that digest pectins have no effect on the gravity-induced polarity of cytoplasmic streaming. Furthermore, gravisensing is sensitive to protease treatment; Proteinase K, thermolysin and collagenase but not trypsin, alpha-chymotrypsin or carboxypeptidase B, inhibit gravisensing. These findings indicate that proteins in the cell-extracellular matrix junction may be required for gravisensing. Moreover, the tetrapeptide Arg-Gly-Asp-Ser (RGDS) inhibits gravisensing in a concentration-dependent manner, indicating that the gravireceptor may be an integrin-like protein. The macromolecules necessary for gravisensing have been localized to the cell ends. As a consequence of the exoplasmic site of action of the enzymes and the tetrapeptides, we interpret the results to mean that they are acting on the gravireceptor, although we cannot eliminate the possibility that they are acting on the signal transduction chain. On the whole, our observations indicate that the cell-extracellular matrix junction is a sine qua non for graviperception in statolith-free Chara internodal cells and we suggest that the gravireceptor is located in this region.

NASA Discipline Plant Biology↗

NASA NTRS1992

Identification of a new EF-hand superfamily member from Trypanosoma brucei

We identified several open reading frames between the regions encoding calmodulin and ubiquitin-EP52/1 in the genome of Trypanosoma brucei. One of these, EFH5, encodes a protein 192 amino acids long. The EFH5 transcript is present in poly(A)+ mRNA and is present at similar levels in the mammalian bloodstream form and the insect procyclic form. EFH5 contains four EF-hand homolog domains, two of which are inferred to bind Ca2+ ions. We expressed EFH5 as a fusion protein in Escherichia coli and demonstrated calcium-binding activity of the fusion protein using the 45Ca-overlay technique. The function of EFH5 remains unknown; however, as the fourth EF-hand homolog identified in trypanosomes, it attests to the broad range of functions assumed by calcium functioning as a second messenger. EFH5, which is most closely related to LAV1-2 from Physarum, represents a distinct subfamily among the EF-hand-containing proteins.

Non-NASA Center↗

NASA NTRS2005

Carnobacterium pleistocenium sp. nov., a novel psychrotolerant, facultative anaerobe isolated from permafrost of the Fox Tunnel in Alaska

A novel, psychrotolerant, facultative anaerobe, strain FTR1T, was isolated from Pleistocene ice from the permafrost tunnel in Fox, Alaska. Gram-positive, motile, rod-shaped cells were observed with sizes 0.6-0.7 x 0.9-1.5 microm. Growth occurred within the pH range 6.5-9.5 with optimum growth at pH 7.3-7.5. The temperature range for growth of the novel isolate was 0-28 degrees C and optimum growth occurred at 24 degrees C. The novel isolate does not require NaCl; growth was observed between 0 and 5 % NaCl with optimum growth at 0.5 % (w/v). The novel isolate was a catalase-negative chemoorganoheterotroph that used as substrates sugars and some products of proteolysis. The metabolic end products were acetate, ethanol and CO2. Strain FTR1T was sensitive to ampicillin, tetracycline, chloramphenicol, rifampicin, kanamycin and gentamicin. 16S rRNA gene sequence analysis showed 99.8 % similarity between strain FTR1T and Carnobacterium alterfunditum, but DNA-DNA hybridization between them demonstrated 39+/-1.5 % relatedness. On the basis of genotypic and phenotypic characteristics, it is proposed that strain FTR1T (=ATCC BAA-754T=JCM 12174T=CIP 108033T) be assigned to the novel species Carnobacterium pleistocenium sp. nov.

Gram-Positive Asporogenous Rods/classification/gen↗

NASA NTRS2004

cWINNOWER algorithm for finding fuzzy dna motifs

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if a clique consisting of a sufficiently large number of mutated copies of the motif (i.e., the signals) is present in the DNA sequence. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum detectable clique size qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12,000 for (l, d) = (15, 4). Copyright Imperial College Press.

Evaluation Studies↗

NASA NTRS2004

Molecular evidence for a terrestrial origin of snakes

Biologists have debated the origin of snakes since the nineteenth century. One hypothesis suggests that snakes are most closely related to terrestrial lizards, and reduced their limbs on land. An alternative hypothesis proposes that snakes are most closely related to Cretaceous marine lizards, such as mosasaurs, and reduced their limbs in water. A presumed close relationship between living monitor lizards, believed to be close relatives of the extinct mosasaurs, and snakes has bolstered the marine origin hypothesis. Here, we show that DNA sequence evidence does not support a close relationship between snakes and monitor lizards, and thus supports a terrestrial origin of snakes.

Environment↗

NASA NTRS2005

Origin of the Eumetazoa: testing ecological predictions of molecular clocks against the Proterozoic fossil record

Molecular clocks have the potential to shed light on the timing of early metazoan divergences, but differing algorithms and calibration points yield conspicuously discordant results. We argue here that competing molecular clock hypotheses should be testable in the fossil record, on the principle that fundamentally new grades of animal organization will have ecosystem-wide impacts. Using a set of seven nuclear-encoded protein sequences, we demonstrate the paraphyly of Porifera and calculate sponge/eumetazoan and cnidarian/bilaterian divergence times by using both distance [minimum evolution (ME)] and maximum likelihood (ML) molecular clocks; ME brackets the appearance of Eumetazoa between 634 and 604 Ma, whereas ML suggests it was between 867 and 748 Ma. Significantly, the ME, but not the ML, estimate is coincident with a major regime change in the Proterozoic acritarch record, including: (i) disappearance of low-diversity, evolutionarily static, pre-Ediacaran acanthomorphs; (ii) radiation of the high-diversity, short-lived Doushantuo-Pertatataka microbiota; and (iii) an order-of-magnitude increase in evolutionary turnover rate. We interpret this turnover as a consequence of the novel ecological challenges accompanying the evolution of the eumetazoan nervous system and gut. Thus, the more readily preserved microfossil record provides positive evidence for the absence of pre-Ediacaran eumetazoans and strongly supports the veracity, and therefore more general application, of the ME molecular clock.

NASA Discipline Evolutionary Biology↗

NASA NTRS2008

MRO Sequence Checking Tool

The MRO Sequence Checking Tool program, mro_check, automates significant portions of the MRO (Mars Reconnaissance Orbiter) sequence checking procedure. Though MRO has similar checks to the ODY s (Mars Odyssey) Mega Check tool, the checks needed for MRO are unique to the MRO spacecraft. The MRO sequence checking tool automates the majority of the sequence validation procedure and check lists that are used to validate the sequences generated by MRO MPST (mission planning and sequencing team). The tool performs more than 50 different checks on the sequence. The automation varies from summarizing data about the sequence needed for visual verification of the sequence, to performing automated checks on the sequence and providing a report for each step. To allow for the addition of new checks as needed, this tool is built in a modular fashion.

Fisher, Forest↗

NASA NTRS2013

Building a 2.5D Digital Elevation Model from 2D Imagery

When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in a standard DEM format and used for projection.

Padgett, Curtis W.↗

NASA NTRS2016

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation↗

NASA NTRS2016

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Registration↗

NASA NTRS2017

Coordinated Analysis 101: A Joint Training Session Sponsored by LPI and ARES/JSC

The Lunar and Planetary Institute (LPI) and the Astromaterials Research and Exploration Science (ARES) Division, part of the Exploration Integration and Science Directorate at NASA Johnson Space Center (JSC), co-sponsored a training session in November 2016 for four early-career scientists in the techniques of coordinated analysis. Coordinated analysis refers to the approach of systematically performing high-resolution and -precision analytical studies on astromaterials, particularly the very small particles typical of recent and near-future sample return missions such as Stardust, Hayabusa, Hayabusa2, and OSIRIS-REx. A series of successive analytical steps is chosen to be performed on the same particle, as opposed to separate subsections of a sample, in such a way that the initial steps do not compromise the results from later steps in the sequence. The data from the entire series can then be integrated for these individual specimens, revealing important in-sights obtainable no other way. ARES/JSC scientists have played a leading role in the development and application of this approach for many years. Because the coming years will bring new sample collections from these and other planned NASA and international exploration missions, it is timely to begin disseminating specialized techniques for the study of small and precious astromaterial samples. As part of the Cooperative Agreement between NASA and the LPI, this training workshop was intended as the first in a series of similar training exercises that the two organizations will jointly sponsor in the coming years. These workshops will span the range of analytical capabilities and sample types available at ARES/JSC in the Astromaterials Research and Astro-materials Acquisition and Curation Offices. Here we summarize the activities and participants in this initial training.

Draper, D. S.↗

NASA NTRS2017

Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

Image registration↗

NASA NTRS2017

Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

image registration↗

NASA NTRS2024

AI Foundation Model for Heliophysics: Applications, Design, and Implementation

Deep learning-based methods have been widely researched in the areas of language and vision, demonstrating their capacity to understand long sequences of data and their usefulness in numerous helio-physics applications. Foundation models (FMs), which are pre-trained on a large-scale datasets, form the basis fora variety of downstream tasks. These models, especially those based on trans-formers in vision and language, show exceptional potential for adapting to a wide range of downstream applications. In this paper, we provide our perspective on the criteria for designing a FM for heliophysic and associated challenges and applications using the Solar Dynamics Observatory (SDO) dataset. We believe that this is the first study to design a foundation model in the domain of heliophysics.

Sujit Roy↗

DOE OSTI2024

From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology

Abstract Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.

59 BASIC BIOLOGICAL SCIENCES↗