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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Biomolecule Sequencer: Next-Generation DNA Sequencing Technology for In-Flight Environmental Monitoring, Research, and Beyond

On the International Space Station (ISS), technologies capable of rapid microbial identification and disease diagnostics are not currently available. NASA still relies upon sample return for comprehensive, molecular-based sample characterization. Next-generation DNA sequencing is a powerful approach for identifying microorganisms in air, water, and surfaces onboard spacecraft. The Biomolecule Sequencer payload, manifested to SpaceX-9 and scheduled on the Increment 4748 research plan (June 2016), will assess the functionality of a commercially-available next-generation DNA sequencer in the microgravity environment of ISS. The MinION device from Oxford Nanopore Technologies (Oxford, UK) measures picoamp changes in electrical current dependent on nucleotide sequences of the DNA strand migrating through nanopores in the system. The hardware is exceptionally small (9.5 x 3.2 x 1.6 cm), lightweight (120 grams), and powered only by a USB connection. For the ISS technology demonstration, the Biomolecule Sequencer will be powered by a Microsoft Surface Pro3. Ground-prepared samples containing lambda bacteriophage, Escherichia coli, and mouse genomic DNA, will be launched and stored frozen on the ISS until experiment initiation. Immediately prior to sequencing, a crew member will collect and thaw frozen DNA samples, connect the sequencer to the Surface Pro3, inject thawed samples into a MinION flow cell, and initiate sequencing. At the completion of the sequencing run, data will be downlinked for ground analysis. Identical, synchronous ground controls will be used for data comparisons to determine sequencer functionality, run-time sequence, current dynamics, and overall accuracy. We will present our latest results from the ISS flight experiment the first time DNA has ever been sequenced in space and discuss the many potential applications of the Biomolecule Sequencer for environmental monitoring, medical diagnostics, higher fidelity and more adaptable Space Biology Human Research Program investigations, and even life detection experiments for astrobiology missions.

Sequencer↗
NASA NTRS2002

Biosensors for DNA sequence detection

DNA biosensors are being developed as alternatives to conventional DNA microarrays. These devices couple signal transduction directly to sequence recognition. Some of the most sensitive and functional technologies use fibre optics or electrochemical sensors in combination with DNA hybridization. In a shift from sequence recognition by hybridization, two emerging single-molecule techniques read sequence composition using zero-mode waveguides or electrical impedance in nanoscale pores.

Review↗
NASA NTRS1995

Statistical and linguistic features of DNA sequences

We present evidence supporting the idea that the DNA sequence in genes containing noncoding regions is correlated, and that the correlation is remarkably long range--indeed, base pairs thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationary" feature of the sequence of base pairs by applying a new algorithm called Detrended Fluctuation Analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and noncoding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to all eukaryotic DNA sequences (33 301 coding and 29 453 noncoding) in the entire GenBank database. We describe a simple model to account for the presence of long-range power-law correlations which is based upon a generalization of the classic Levy walk. Finally, we describe briefly some recent work showing that the noncoding sequences have certain statistical features in common with natural languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts, and the Shannon approach to quantifying the "redundancy" of a linguistic text in terms of a measurable entropy function. We suggest that noncoding regions in plants and invertebrates may display a smaller entropy and larger redundancy than coding regions, further supporting the possibility that noncoding regions of DNA may carry biological information.

Non-NASA Center↗
NASA NTRS1995

Statistical properties of DNA sequences

We review evidence supporting the idea that the DNA sequence in genes containing non-coding regions is correlated, and that the correlation is remarkably long range--indeed, nucleotides thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationarity" feature of the sequence of base pairs by applying a new algorithm called detrended fluctuation analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and non-coding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to every DNA sequence (33301 coding and 29453 non-coding) in the entire GenBank database. Finally, we describe briefly some recent work showing that the non-coding sequences have certain statistical features in common with natural and artificial languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts. These statistical properties of non-coding sequences support the possibility that non-coding regions of DNA may carry biological information.

Non-NASA Center↗
NASA NTRS1994

Correlation approach to identify coding regions in DNA sequences

Recently, it was observed that noncoding regions of DNA sequences possess long-range power-law correlations, whereas coding regions typically display only short-range correlations. We develop an algorithm based on this finding that enables investigators to perform a statistical analysis on long DNA sequences to locate possible coding regions. The algorithm is particularly successful in predicting the location of lengthy coding regions. For example, for the complete genome of yeast chromosome III (315,344 nucleotides), at least 82% of the predictions correspond to putative coding regions; the algorithm correctly identified all coding regions larger than 3000 nucleotides, 92% of coding regions between 2000 and 3000 nucleotides long, and 79% of coding regions between 1000 and 2000 nucleotides. The predictive ability of this new algorithm supports the claim that there is a fundamental difference in the correlation property between coding and noncoding sequences. This algorithm, which is not species-dependent, can be implemented with other techniques for rapidly and accurately locating relatively long coding regions in genomic sequences.

Non-NASA Center↗
NASA NTRS2001

A Bioluminometric Method of DNA Sequencing

Pyrosequencing is a bioluminometric single-tube DNA sequencing method that takes advantage of co-operativity between four enzymes to monitor DNA synthesis. In this sequencing-by-synthesis method, a cascade of enzymatic reactions yields detectable light, which is proportional to incorporated nucleotides. Pyrosequencing has the advantages of accuracy, flexibility and parallel processing. It can be easily automated. Furthermore, the technique dispenses with the need for labeled primers, labeled nucleotides and gel-electrophoresis. In this chapter, the use of this technique for different applications is discussed.

Ronaghi, Mostafa↗
NASA NTRS1993

Finite-size effects on long-range correlations: implications for analyzing DNA sequences

We analyze the fluctuations in the correlation exponents obtained for noncoding DNA sequences. We find prominent sample-to-sample variations as well as variations within a single sample in the scaling exponent. To determine if these fluctuations may result from finite system size, we generate correlated random sequences of comparable length and study the fluctuations in this control system. We find that the DNA exponent fluctuations are consistent with those obtained from the control sequences having long-range power-law correlations. Finally, we compare our exponents for the DNA sequences with the exponents obtained from power-spectrum analysis and correlation-function techniques, and demonstrate that the original "DNA-walk" method is intrinsically more accurate due to reduced noise.

NASA Discipline Cardiopulmonary↗
NASA NTRS2017

Beyond DNA Sequencing in Space: Current and Future Omics Capabilities of the Biomolecule Sequencer Payload

Why do we need a DNA sequencer to support the human exploration of space? (A) Operational environmental monitoring; (1) Identification of contaminating microbes, (2) Infectious disease diagnosis, (3) Reduce down mass (sample return for environmental monitoring, crew health, etc.). (B) Research; (1) Human, (2) Animal, (3) Microbes/Cell lines, (4) Plant. (C) Med Ops; (1) Response to countermeasures, (2) Radiation, (3) Real-time analysis can influence medical intervention. (C) Support astrobiology science investigations; (1) Technology superiorly suited to in situ nucleic acid-based life detection, (2) Functional testing for integration into robotics for extraplanetary exploration mission.

Wallace, Sarah↗
NASA NTRS1996

Random-breakage mapping method applied to human DNA sequences

The random-breakage mapping method [Game et al. (1990) Nucleic Acids Res., 18, 4453-4461] was applied to DNA sequences in human fibroblasts. The methodology involves NotI restriction endonuclease digestion of DNA from irradiated calls, followed by pulsed-field gel electrophoresis, Southern blotting and hybridization with DNA probes recognizing the single copy sequences of interest. The Southern blots show a band for the unbroken restriction fragments and a smear below this band due to radiation induced random breaks. This smear pattern contains two discontinuities in intensity at positions that correspond to the distance of the hybridization site to each end of the restriction fragment. By analyzing the positions of those discontinuities we confirmed the previously mapped position of the probe DXS1327 within a NotI fragment on the X chromosome, thus demonstrating the validity of the technique. We were also able to position the probes D21S1 and D21S15 with respect to the ends of their corresponding NotI fragments on chromosome 21. A third chromosome 21 probe, D21S11, has previously been reported to be close to D21S1, although an uncertainty about a second possible location existed. Since both probes D21S1 and D21S11 hybridized to a single NotI fragment and yielded a similar smear pattern, this uncertainty is removed by the random-breakage mapping method.

NASA Discipline Radiation Health↗
NASA NTRS1995

Systematic analysis of coding and noncoding DNA sequences using methods of statistical linguistics

We compare the statistical properties of coding and noncoding regions in eukaryotic and viral DNA sequences by adapting two tests developed for the analysis of natural languages and symbolic sequences. The data set comprises all 30 sequences of length above 50 000 base pairs in GenBank Release No. 81.0, as well as the recently published sequences of C. elegans chromosome III (2.2 Mbp) and yeast chromosome XI (661 Kbp). We find that for the three chromosomes we studied the statistical properties of noncoding regions appear to be closer to those observed in natural languages than those of coding regions. In particular, (i) a n-tuple Zipf analysis of noncoding regions reveals a regime close to power-law behavior while the coding regions show logarithmic behavior over a wide interval, while (ii) an n-gram entropy measurement shows that the noncoding regions have a lower n-gram entropy (and hence a larger "n-gram redundancy") than the coding regions. In contrast to the three chromosomes, we find that for vertebrates such as primates and rodents and for viral DNA, the difference between the statistical properties of coding and noncoding regions is not pronounced and therefore the results of the analyses of the investigated sequences are less conclusive. After noting the intrinsic limitations of the n-gram redundancy analysis, we also briefly discuss the failure of the zeroth- and first-order Markovian models or simple nucleotide repeats to account fully for these "linguistic" features of DNA. Finally, we emphasize that our results by no means prove the existence of a "language" in noncoding DNA.

NASA Discipline Number 14-10↗
NASA NTRS1992

Numerical classification of coding sequences

DNA sequences coding for protein may be represented by counts of nucleotides or codons. A complete reading frame may be abbreviated by its base count, e.g. A76C158G121T74, or with the corresponding codon table, e.g. (AAA)0(AAC)1(AAG)9 ... (TTT)0. We propose that these numerical designations be used to augment current methods of sequence annotation. Because base counts and codon tables do not require revision as knowledge of function evolves, they are well-suited to act as cross-references, for example to identify redundant GenBank entries. These descriptors may be compared, in place of DNA sequences, to extract homologous genes from large databases. This approach permits rapid searching with good selectivity.

Non-NASA Center↗
NASA NTRS1992

Long-range correlations in nucleotide sequences

DNA sequences have been analysed using models, such as an n-step Markov chain, that incorporate the possibility of short-range nucleotide correlations. We propose here a method for studying the stochastic properties of nucleotide sequences by constructing a 1:1 map of the nucleotide sequence onto a walk, which we term a 'DNA walk'. We then use the mapping to provide a quantitative measure of the correlation between nucleotides over long distances along the DNA chain. Thus we uncover in the nucleotide sequence a remarkably long-range power law correlation that implies a new scale-invariant property of DNA. We find such long-range correlations in intron-containing genes and in nontranscribed regulatory DNA sequences, but not in complementary DNA sequences or intron-less genes.

NASA Discipline Cardiopulmonary↗
NASA NTRS2001

Homology and the optimization of DNA sequence data

Three methods of nucleotide character analysis are discussed. Their implications for molecular sequence homology and phylogenetic analysis are compared. The criterion of inter-data set congruence, both character based and topological, are applied to two data sets to elucidate and potentially discriminate among these parsimony-based ideas. c2001 The Willi Hennig Society.

Non-NASA Center↗
DOE OSTI2023

Bubble Relaxation Dynamics in Homopolymer DNA Sequences

Understanding the inherent timescales of large bubbles in DNA is critical to a thorough comprehension of its physicochemical characteristics, as well as their potential role on helix opening and biological function. In this work, we employ the coarse-grained Peyrard–Bishop–Dauxois model of DNA to study relaxation dynamics of large bubbles in homopolymer DNA, using simulations up to the microsecond time scale. By studying energy autocorrelation functions of relatively large bubbles inserted into thermalised DNA molecules, we extract characteristic relaxation times from the equilibration process for both adenine–thymine (AT) and guanine–cytosine (GC) homopolymers. Bubbles of different amplitudes and widths are investigated through extensive statistics and appropriate fittings of their relaxation. Characteristic relaxation times increase with bubble amplitude and width. We show that, within the model, relaxation times are two orders of magnitude longer in GC sequences than in AT sequences. Overall, our results confirm that large bubbles leave a lasting impact on the molecule’s dynamics, for times between 0.5–500 ns depending on the homopolymer type and bubble shape, thus clearly affecting long-time evolutions of the molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

Non-NASA Center↗
NASA NTRS2022

Tracing the Path of Carbon Export in the Ocean though DNA Sequencing of Individual Sinking Particles

Surface phytoplankton communities were linked with the carbon they export into the deep ocean by comparing 18 S rRNA gene sequence communities from surface seawater and individually isolated sinking particles. Particles were collected in sediment traps deployed at locations in the North Pacific subtropical gyre and the California Current. DNA was isolated from individual particles, bulk-collected trap particles, and the surface seawater. The relative sequence abundance of exported phytoplankton taxa in the surface water varied across functional groups and ecosystems. Of the sequences detected in sinking particles, about half were present in large (>300 μm), individually isolated particles and primarily belonged to taxa with small cell sizes (<50 μm). Exported phytoplankton taxa detected only in bulk trap samples, and thus presumably packaged in the smaller sinking size fraction, contained taxa that typically have large cell sizes (>500 m). The effect of particle degradation on the detectable 18 S rRNA gene community differed across taxa, and differences in community composition among individual particles from the same location largely reflected differences in relative degradation state. Using these data and particle imaging, we present an approach that incorporates genetic diversity into mechanistic models of the ocean's biological carbon pump, which will lead to better quantification of the ocean’s carbon cycle.

Carbon Expert↗