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At least 109 records · Page 6

Transgenics in crops

With rapid world population growth and declining availability of fresh water and arable land, a new technology is urgently needed to enhance agricultural productivity. Recent discoveries in the field of crop transgenics clearly demonstrate the great potential of this technology for increasing food production and improving food quality while preserving the environment for future generations. In this review, we briefly discuss some of the recent achievements in crop improvement that have been made using gene transfer technology.

Review↗

A low molecular weight artificial RNA of unique size with multiple probe target regions

Artificial RNAs (aRNAs) containing novel sequence segments embedded in a deletion mutant of Vibrio proteolyticus 5S rRNA have previously been shown to be expressed from a plasmid borne growth rate regulated promoter in E. coli. These aRNAs accumulate to high levels and their detection is a promising tool for studies in molecular microbial ecology and in environmental monitoring. Herein a new construct is described which illustrates the versatility of detection that is possible with aRNAs. This 3xPen aRNA construct carries a 72 nucleotide insert with three copies of a unique 17 base probe target sequence. This aRNA is 160 nucleotides in length and again accumulates to high levels in the E. coli cytoplasm without incorporating into ribosomes. The 3xPen aRNA illustrates two improvements in detection. First, by appropriate selection of insert size, we obtained an aRNA which provides a unique and hence, easily quantifiable peak, on a high resolution gel profile of low molecular weight RNAs. Second, the existence of multiple probe targets results in a nearly commensurate increase in signal when detection is by hybridization. These aRNAs are naturally amplified and carry sequence segments that are not found in known rRNA sequences. It thus may be possible to detect them directly. An experimental step involving RT-PCR or PCR amplification of the gene could therefore be avoided.

Non-NASA Center↗

Tissue-engineered human bioartificial muscles expressing a foreign recombinant protein for gene therapy

Murine skeletal muscle cells transduced with foreign genes and tissue engineered in vitro into bioartificial muscles (BAMs) are capable of long-term delivery of soluble growth factors when implanted into syngeneic mice (Vandenburgh et al., 1996b). With the goal of developing a therapeutic cell-based protein delivery system for humans, similar genetic tissue-engineering techniques were designed for human skeletal muscle stem cells. Stem cell myoblasts were isolated, cloned, and expanded in vitro from biopsied healthy adult (mean age, 42 +/- 2 years), and elderly congestive heart failure patient (mean age, 76 +/- 1 years) skeletal muscle. Total cell yield varied widely between biopsies (50 to 672 per 100 mg of tissue, N = 10), but was not significantly different between the two patient groups. Percent myoblasts per biopsy (73 +/- 6%), number of myoblast doublings prior to senescence in vitro (37 +/- 2), and myoblast doubling time (27 +/- 1 hr) were also not significantly different between the two patient groups. Fusion kinetics of the myoblasts were similar for the two groups after 20-22 doublings (74 +/- 2% myoblast fusion) when the biopsy samples had been expanded to 1 to 2 billion muscle cells, a number acceptable for human gene therapy use. The myoblasts from the two groups could be equally transduced ex vivo with replication-deficient retroviral expression vectors to secrete 0.5 to 2 microg of a foreign protein (recombinant human growth hormone, rhGH)/10(6) cells/day, and tissue engineered into human BAMs containing parallel arrays of differentiated, postmitotic myofibers. This work suggests that autologous human skeletal myoblasts from a potential patient population can be isolated, genetically modified to secrete foreign proteins, and tissue engineered into implantable living protein secretory devices for therapeutic use.

Non-NASA Center↗

The M2 Proton Channel of Influenza Virus: How Does It Work?

The transport of protons across membranes is an essential process for both bioenergetics of modem cells and the origins of cellular life. All living systems make use of proton gradients across cell walls to convert environmental energy into a high-energy chemical compound, adenosine triphosphate (ATR), synthesized from adenosine diphosphate. ATR, in turn, is used as a source of energy to drive many cellular reactions. The ubiquity of this process in biology suggests that even the earliest cellular systems were relying on proton gradient for harvesting environmental energy needed to support their survival and growth. In contemporary cells, proton transfer is assisted by large, complex proteins embedded in membranes. The issue addressed in this study was: how the same process can be accomplished with the aid of similar, but much simpler molecules that could have existed in the protobiological milieu? The model system used in the study contained a bilayer membrane made of phospholipid, dimyristoylphosphatidylcholine (DMPC), which is a good model of the biological membranes focusing cellular boundaries. Both sides of the bilayer were surrounded by water which simulated the environment inside and outside the cell. Embedded in the membrane was a fragment of the Influenza-A M2 protein and enough sodium counterions to maintain system neutrality. This protein has been shown to exhibit remarkably high rates of proton transport and, therefore, is an excellent model to study the formation of proton gradients across membranes. The Influenza M2 protein is 97 amino acids in length, but a fragment 25 amino acids long, which contains a transmembrane domain of 19 amino acids flanked by 3 amino acids on each side, is sufficient to transport protons. Four identical protein fragments, each folded into a helix, aggregate to form small channels spanning the membrane. Protons are conducted through a narrow pore in the middle of the channel in response to applied voltage. This channel is large enough to contain water molecules, and is normally filled with water. In analogy to the mechanism of proton transfer in some other channels, it has been postulated that protons are translocated along the network of water molecules filling the pore of the channel. This mechanism, however, must involve an additional, important step because the channel contains four histidine amino acid residues, one from each of the helices, which are sufficiently large to occlude the pore and interrupt the water network. The histidine residues ensure channel selectivity by blocking transport of small such as sodium or potassium. They have been also implicated in gating protons due to the ability of each histidine to become positively charged by accepting an additional proton. Two mechanisms of gating have been proposed. In one mechanism, all four histidines acquire an additional proton and, due to repulsion between their positive charges, move away from one another, thus opening the channel. The alternative mechanism relies of the ability of protons to move between different atoms in a molecule (tautomerization). Thus, a proton is captured on one side of the gate while another proton is released from the opposite side, and the molecule returns to the initial state through tautomerization. The simulations were designed to test these two mechanisms. Large-scale, atomic-level molecular dynamics simulations of the channel, in which the histidine residues were in different protonation states revealed that all intermediate states of the system involved in the tautomerization mechanism are structurally stable and the arrangement of water molecules in the channel is conducive to the proton transport. In contrast, in the four-protonated state, postulated to exist in the gate-opening mechanism, the electrostatic repulsion between the histidine residues appears to be so large that the channel looses its structural integrity and one helix moves away from the remaining three. This result indicates that such a mechanism of proton transport is unlikely. The simulations revealed that translocation along a network of water molecules in the channel and tautomerization of the histidine residues in the M2 proteins in the most likely mechanism of proton transport. The results not only explain how a remarkably simple protein system can efficiently aid in the formation of proton gradients across cell walls, but also suggest how this system can be genetically re-engineered to become a directional, reversible proton pump. Such a pump can provide energy to laboratory-built models of simple cellular systems. If they were successfully constructed it would greatly advance our understanding of the beginnings of life and find important applications in medicine and pharmacology.

Pohorille, Andrew↗

BRIC-17 Mapping Spaceflight-Induced Hypoxic Signaling and Response in Plants

Goals of this work are: (1) Define global changes in gene expression patterns in Arabidopsis plants grown in microgravity using whole genome microarrays (2) Compare to mutants resistant to low oxygen challenge using whole genome microarrays Also measuring root and shoot size Outcomes from this research are: (1) Provide fundamental information on plant responses to the stresses inherent in spaceflight (2) Potential for informing on genetic strategies to engineer plants for optimal growth in space

Gilroy, Simon↗

Surface Cancellation in Wideband Ground Penetrating Radar Employing Genetic Algorithm AI for Waveform Synthesis

This paper presents a wideband 600-1200 MHz ground penetrating radar (GPR) system for sub-surface exploration of the moon and other planetary bodies. The presented radar system uses an arbitrary waveform generator (AWG) to directly produce the frequency-modulated continuous wave (FMCW) chirp waveform. To address the key challenges of Tx-to-Rx leakage and surface reflections, the system uses a second AWG channel coupled directly to the receiver that provides a cancellation waveform to mitigate the unwanted signals. The system also uses a genetic algorithm AI engine which assesses the radar IF and iteratively improves the parameters of the cancellation waveform injected at the receiver.

Chang, Frank↗

Tissue-Engineered Skeletal Muscle Organoids for Reversible Gene Therapy

Genetically modified murine skeletal myoblasts were tissue engineered in vitro into organ-like structures (organoids) containing only postmitotic myoribers secreting pharmacological levels of recombinant human growth hormone (rhGH). Subcutaneous organoid implantation under tension led to the rapid and stable appearance of physiological sera levels of rhGH for up to 12 weeks, whereas surgical removal led to its rapid disappearance. Reversible delivery of bioactive compounds from postmitotic cells in tissue engineered organs has several advantages over other forms of muscle gene therapy.

Vandenburgh, Herman↗

Tissue-Engineered Skeletal Muscle Organoids for Reversible Gene Therapy

Genetically modified murine skeletal myoblasts were tissue engineered in vitro into organ-like structures (organoids) containing only postmitotic myofibers secreting pharmacological levels of recombinant human growth hormone (rhGH). Subcutaneous organoid Implantation under tension led to the rapid and stable appearance of physiological sera levels of rhGH for up to 12 weeks, whereas surgical removal led to its rapid disappearance. Reversible delivery of bioactive compounds from postimtotic cells in tissue engineered organs has several advantages over other forms of muscle gene therapy.

Vandenburgh, Herman↗

Engineering plants for spaceflight environments

The conversion efficiency of radiation into biomass and yield has steadily increased for centuries because of continued improvement in both plant genetics and environmental control. Considerable effort has gone into improving the environment for plant growth in space, but work has only begun to engineer plants for spaceflight. Genetic manipulation offers tremendous potential to improve our ability to study gravitational effects. Genetic manipulation will also be necessary to build an efficient regenerative life support system. We cannot fully characterize plant response to the spaceflight environment without understanding and manipulating their genetic composition. Identification and selection of the existing germplasm is the first step. There are thousands of cultivars of each of our major crop plants, each specifically adapted to a unique environment on our planet. Thousands of additional lines are held in national germplasm collections to maintain genetic diversity. Spaceflight imposes the need to tap this diversity. Existing lines need to be evaluated in the environment that is characteristic of closed-system spaceflight conditions. Many of the plant growth challenges we confront in space can be better solved through genetic change than by hardware engineering. Ten thousand years of plant breeding has demonstrated the value of matching genetics with the environment. For example, providing continuous light can increase plant growth in space, but this often induces calcium deficiencies because Ca is not supplied by guttation during a dark period. This deficiency cannot be eliminated through increased root-zone and foliar Ca applications. It can be solved, in wheat, through genetic selection of lines that do not have the deficiency. Subsequent comparison of lines with and without the Ca deficiency has also helped us understand the nature of the problem.

Non-NASA Center↗

Catalysis and biocatalysis program

The annual report presents the fiscal year (FY) 1990 research activities and accomplishments for the Catalysis and Biocatalysis Program of the Advanced Industrial Concepts Division (AICD), Office of Industrial Technologies of the Department of Energy (DOE). The mission of the AICD is to create a balanced program of high risk, long term, directed interdisciplinary research and development that will improve energy efficiency and enhance fuel flexibility in the industrial sector. The Catalysis and Biocatalysis Program's technical activities were organized into five work elements: the Molecular Modeling and Catalysis by Design element; the Applied Microbiology and Genetics element; the Bioprocess Engineering element; the Separations and Novel Chemical Processes element; and the Process Design and Analysis element.

Source record↗

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Zaychik, Kirill B.↗

A Single-Lap Joint Adhesive Bonding Optimization Method Using Gradient and Genetic Algorithms

A natural process for any engineer, scientist, educator, etc. is to seek the most efficient method for accomplishing a given task. In the case of structural design, an area that has a significant impact on the structural efficiency is joint design. Unless the structure is machined from a solid block of material, the individual components which compose the overall structure must be joined together. The method for joining a structure varies depending on the applied loads, material, assembly and disassembly requirements, service life, environment, etc. Using both metallic and fiber reinforced plastic materials limits the user to two methods or a combination of these methods for joining the components into one structure. The first is mechanical fastening and the second is adhesive bonding. Mechanical fastening is by far the most popular joining technique; however, in terms of structural efficiency, adhesive bonding provides a superior joint since the load is distributed uniformly across the joint. The purpose of this paper is to develop a method for optimizing single-lap joint adhesive bonded structures using both gradient and genetic algorithms and comparing the solution process for each method. The goal of the single-lap joint optimization is to find the most efficient structure that meets the imposed requirements while still remaining as lightweight, economical, and reliable as possible. For the single-lap joint, an optimum joint is determined by minimizing the weight of the overall joint based on constraints from adhesive strengths as well as empirically derived rules. The analytical solution of the sin-le-lap joint is determined using the classical Goland-Reissner technique for case 2 type adhesive joints. Joint weight minimization is achieved using a commercially available routine, Design Optimization Tool (DOT), for the gradient solution while an author developed method is used for the genetic algorithm solution. Results illustrate the critical design variables as a function of adhesive properties and convergences of different joints based on the two optimization methods.

Smeltzer, Stanley S., III↗

Life in the Clouds of Venus? An Experimental Synthetic Biology Approach

The surface of Venus constitutes the most hellish and biologically inhospitable planetary surface in our solar system, boasting a pH of 0, blistering winds that can melt lead, and pressures of 60 atm. However, during the earlier years of the solar system, without the runaway greenhouse effect that has plagued the planet, Venus potentially housed oceans and perhaps even life. There is a possibility that microbes could have retreated into hospitable niches in the atmosphere, as suggested by Carl Sagan as early as 1967 [1]. For example, 50 km above the raging hell of the Venusian surface, exists a relatively temperate environment that might serve as reservoir for life. This astrobiology project seeks to explore life at the extremes and to theorize whether microbial communities could not only survive but also reproduce in the Venusian atmosphere. Specifically, we ask: are aerosols viable microbial environments? But before we can test for life in the clouds, we have to develop a proper reporter to visualize cell growth in situ. For this purpose, we aimed to develop cell-growth dependent reporters to serve as remote biosensors for cell growth. We developed two using the polA promoter, a DNA-replication dependent promoter, and nrd operon promoter, a cell-cycle dependent promoter. Using these cell-growth reporters, the next step is to aerosolize microbes expressing these reporters in a suspension chamber adapted from a Millikan Drop Apparatus to assay reproduction in an aerosolized environment. Better yet is to test the reproduction of microbes in a microgravity regime such as on ISS.Approach: We engineered two cell-cycle dependent genetic reporters. One was the polA promoter which codes for DNA Polymerase I, a gene active in DNA replication [2]. The other was the nrdP. The activation of ribonucleotide reductase reduces ribonucleotides into deoxyribonucleotides and is involved in the bacterial cell cycle [3]. This promoter began activation during the initiation of DNA replication and is cell-cycle dependent [4]. These promoters were fused to a GFP reporter, transformed into E. coli. The constructs were deposited in the iGEM registry as K847210: Escherichia coli DNA-replication dependent polA promoter K847211: Escherichia coli cell-division dependent nrd promoter Results: Our constructs displayed fluorescence when transformed into NEB-5alpha competent cells. While nrdP-E0840 displayed sufficient fluorescence as verified by fluorescent microscopy, the original polAP-E0840 construct (which uses mut3b GFP) exhibited low expression; while fluorescence was visible under the microscope, the signal was too weak for the camera to recognize. The polA promoter was therefore digest-ed with EcoRI and SpeI then ligated into plasmid pNCS containing a RBS, Clover, and a terminator. Clover is a highly engineered green fluorescent protein that exhibits extreme brightness [5] Fluoresence time course data demonsrated that the genes were induced in a cell cycle dependant manner [6]. Our assays via microscopy and the bulk assay shows that our promoters are functional as cell cycle reporters.Conclusions: The application of such tools are widespread and not limited to astrobiology; nrdP could be used to determine doubling times empirically and could possibly extrapolate DNA content from intensity of signals expressed by polAP. However, we are pri-marily interested in its use in astrobiology.

Escherichia↗

Developing a Genetic Variant Calling Pipeline for Quantifying the Complex Mutagenic Load Accumulated in BioNutrients-1 Production Pack Samples

Microorganisms hold great promise for on demand production of labile nutrients and pharmaceuticals as well recycling and in situ resource utilization. The utilization of microorganisms for such tasks on space missions is hindered by the limited data on how microbes respond to spaceflight. For example, the genetic stability of microorganisms, and the genomic engineered traits added to deliver desired functions, over long-term storage in the spacecraft environment is poorly understood. The BioNutrients-1 (BN-1) mission conducted a 5-year study of desiccated storage in Low Earth Orbit (LEO) to evaluate the suitability of eight synthetic biology chassis organisms for long-duration space missions. We are employing high-depth, whole genome sequencing (WGS) to determine the mutagenic load that accumulated during long-term storage. Mutation analysis pipelines are well established for homogenous culture grown from a single colony, but the mutational landscape of the BN-1 samples present a unique analysis challenge, as every cell in the BN-1 samples had a unique genetic journey of DNA damage and repair. Consequently, sequence variants are expected at low allele frequency within samples. To address this genetic complexity, we apply two distinct computational approaches to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO. For reference genome free mutation detection, we utilized DiscoSNP++, which is a de Bruijn graph approach. For reference genome-based mutation detection we utilize GATK for Microbes, which is a Bayesian probabilistic approach. We will benchmark these approaches against the mutations originally identified using CRISP, a method optimized for pooled samples. Ultimately, quantifying the mutation load imposed by storage or growth on the ISS will help identify chassis organisms with both high levels of genome stability and viability, which are desirable traits for implementation of bioproduction in long-duration missions.

SNP↗

Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems

A technique based on Evolutionary Computational Methods (ECMs) was developed that allows for the automated optimization of complex computationally modeled systems, such as autonomous systems. The primary technology, which enables the ECM to find optimal solutions in complex search spaces, derives from evolutionary algorithms such as the genetic algorithm and differential evolution. These methods are based on biological processes, particularly genetics, and define an iterative process that evolves parameter sets into an optimum. Evolutionary computation is a method that operates on a population of existing computational-based engineering models (or simulators) and competes them using biologically inspired genetic operators on large parallel cluster computers. The result is the ability to automatically find design optimizations and trades, and thereby greatly amplify the role of the system engineer.

Terrile, Richard J.↗

Remote Raman measurement techniques

The use of laser Raman measurement techniques in remote sensing applications is surveyed. A feasibility index is defined as a means to characterize the practicality of a given remote Raman measurement application. Specific applications of Raman scattering to the measurement of atmospheric water vapor profiles, methane plumes from liquid natural gas spills, and subsurface ocean temperature profiles are described. This paper will survey the use of laser Raman measurement techniques in remote sensing applications using as examples specific systems that the Computer Genetics Corporation (CGC) group has developed and engineered.

Leonard, D. A.↗

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

Baskaran, Subbiah↗