2006-2007 - Kennedy Space Center Technology Transfer Office

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Focused Metabolite Profiling for Dissecting Cellular and MolecularProcesses of Living Organisms in Space Environments2006 Center Director’s Discretionary Fund ProjectRegulatory control in biological systems is exerted at all levels within the central dogmaWater andAir Recovery/ of biology: DNA→mRNA→Enzyme inactive→Enzyme active→Metabolites (Figure 1).Purification Metabolites are the end products of all cellular regulatory processes and reflect the ultimateoutcome of potential changes suggested by genomics and proteomics caused by anenvironmental stimulus or genetic modification. Following on the heels of genomics, transcriptomics,and proteomics, metabolomics has become an inevitable part of complete-system biology becausenone of the lower “-omics” alone provide direct information about how changes in mRNA or proteinare coupled to changes in biological function. Analogous to the precedent “omics,” metabolomicsis the systematic study of collections of small molecules (i.e., metabolites) in a biological system(a cell, organ, or organism). In contrast to the traditional biochemistry approach in which specificmetabolites and enzymes are studied, metabolomics takes a holistic view of the entire suite ofmetabolites (the metabolome) in an organism to capture the coordinated regulation of biologicalsystems. Thus, metabolomics, coupled with other “omics” such as transcriptomics and proteomics,holds great promise for deciphering the functions of genes, predicting novel metabolic pathways, andproviding insights to the regulation of a biological event, as well as for directing metabolic engineeringof plants for human benefit. However, the challenges are much greater than those encountered ingenomics because of the greater number of metabolites and the greater diversity of their chemicalstructures and properties. To meet these challenges, much developmental work is needed, including(1) methodologies for unbiased extraction of metabolites and subsequent quantification,(2) algorithms for systematic identification of metabolites, (3) expertise and competency in handlinga large amount of information (data set), and (4) integration of metabolomics with other “omics” anddata mining (implication of the information).Parallel Gene and Metabolite Expression AnalysesBiological SpecimenSamplingSample PreservationGeneExpressionMicroarrayAnalysisRNA IsolationRNA CleanupMetaboliteProfilingFigure 1. The central dogma of biology and the “omics”revolution.GC/MS ProfilingDerivatizationMetabolite ExtractionFigure 2. Analytical platform for metabolite profiling.92 Biological Sciences
Project accomplishments include the following:• A gas chromatography/mass spectrometry (GC/MS)-based analytical platform was developed and optimized(encompassing essential hardware [Figure 2]) for profiling small polar molecules. Procedures, software, andtechnical competency in metabolite profiling were also developed (also see “Development and Couplingof Metabolomics Capability With Transcriptomics To Dissect Cellular and Molecular Processes of LivingOrganisms” in KSC Technology Development and Application 2005 Annual Report).• Metabolite profiling was completed for 54 samples generated in FY 2005 experiments.• Microarray analysis for gene expression (about 22,000 transcripts) and data processing platform was completed.• The Automated Mass Spectral Deconvolution and Identification System (AMDIS) was implemented andenabled to analyze the GC/MS raw data files for the purification of mixed spectra and the identification andquantification of target components (Figure 3). With the help of Bionetics, an Excel macro was developed toextract and format AMDIS outputs.• A targeted mass spectra and retention index library was constructed for Arabidopsis metabolome and quantitativeand qualitative information was extracted from the GC/MS metabolite profiles (70 unique mass tags arestatistically responsive to carbon dioxide [CO 2] treatment).• Competency was increased in statistics and bioinformatics to extract biological meaning from transcriptionaland metabolite profiles, and work to interpret data continued in an effort to understand the differential effect ofnormally elevated CO 2and superelevated CO 2on plant growth and stomatal function.• Four additional elevated-CO 2experiments were conducted to obtain complementary information ontranspiration (indicative of stomatal function), growth, and morphology.• The occurrence in this plant model of previousobservations from other plant species wasconfirmed, thus offering opportunities touse molecular tools to reveal the mechanismunderlying the biphasic response of growth andstomatal function to increasing atmospheric CO 2concentration.• A manuscript focusing on stomatal function undernormally elevated CO 2and superelevated CO 2wasinitiated.Contact: Dr. Raymond M. Wheeler,NASA-KSC, (321) 861-2950Participating Organizations: Dynamac Corporation(Dr. Lanfang H. Levine and Jeffrey T. Richards), University ofFlorida (Dr. Charles Guy), and Bionetics Corporation(Kevin A. Burtness)GC/MS ProfilingRelative Abundance5045403530252015105013.7621.4724.61 30.95MS Spectrum Deconvolution & AlignmentMetabolite Identification & QuantificationMultivariate Statistic Analysis32.4324.9037.1225.26 44.93 49.2917.59 35.3120.2727.2710 15 20 25 30 35 40 45 50 5537.6742.8341.1947.5350.9353.14TreatmentsABCDEF2001000–100YZ–1000–5010050150–200–1000X100200–200Figure 3. Data analysis and information extractionframework.KSC Technology Development and Application 2006-200793/94
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ForewordSuccessful technology devel
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ContentsSpaceport Structures and Ma
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Contents (continued)Process and Hum
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IntroductionJohn F. Kennedy Space C
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Constellation SystemsSurfaceSystems
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Spaceport Structures and MaterialsK
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20181614∆ E1210Modified Sensor Be
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Initial results of the EDEM model o
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Contacts: Dr. Carlos I. Calle ,NASA
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Close examination of the corrosions
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Adhesion at Failure (psi)2500200015
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Figure 1. After 500 hours of salt f
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Contacts: Dr. Paul E. Hintze , NASA
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Figure 2. Repairs to various types
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on top of the cuvette contains the
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Figure 2. A corrugated NiTi sheet e
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The PLTD can be used to (1) calibra
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SEM images of neat MWNT fibers: (a)
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Contacts: Trent M. Smith
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Figure 1. An isometric cutaway view
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Figure 2. Quartz sand flowing in th
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Figure 2. Top images show how the e
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Sand volume fraction contour at t =
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Integrated LWRD/RVC engineering bre
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Mean relative percentage change in
Page 55 and 56: We compared the model’s predictio
Page 57 and 58: Figure 2. Three-dimensional simulat
Page 59 and 60: Figure 3. Camera calibration model.
Page 61 and 62: The sketch in Figure 2 shows alaunc
Page 63: Figure 2. Signal generator (right)
Page 66 and 67: Hail Size Distribution MappingA 3-D
Page 68 and 69: Launch Pad 39 Hail Monitor Array Sy
Page 70 and 71: Autonomous Flight Safety System - P
Page 72 and 73: The Photogrammetry CubeSpaceport/Ra
Page 74 and 75: Bird Vision SystemThe Bird Vision s
Page 76 and 77: Automating Range Surveillance Throu
Page 78 and 79: Next-Generation Telemetry Workstati
Page 80 and 81: GPS Metric Tracking UnitAs Global P
Page 82 and 83: Space-Based RangeSpace-Based Range
Page 85 and 86: Fluid System TechnologiesKSC Techno
Page 87 and 88: 0.900.850.80Discharge Coefficient,
Page 89 and 90: Composite seals for performance eva
Page 91 and 92: 140000120000100000Signal80000600004
Page 93 and 94: Contacts: Dr. Barry J. Meneghelli ,
Page 95 and 96: 60555045Comparative k-value (mW/m-K
Page 97 and 98: a compatible spacecraft model where
Page 99 and 100: In an ongoing effort for improvemen
Page 101: Low-gravity probe prototype test.th
Page 104 and 105: Countermeasure for Radiation Protec
Page 109 and 110: Process and Human FactorsEngineerin
Page 111 and 112: DON uses game technology to enable
Page 113 and 114: Type of mobile crane that impacted
Page 115 and 116: SALT proof-of-concept communication
Page 117 and 118: SSLM CAD model.Our design offers th
Page 119 and 120: Variables that can be integrated by
Page 121: Exploration Supply Chain Simulation
Page 124 and 125: Nanosensors for Evaluating Hazardou
Page 126 and 127: Sixty-four-Channel Inline Cable Tes
Page 128 and 129: Wireless Inclinometer Calibration S
Page 130 and 131: Generating Safety-Critical PLC Code
Page 132 and 133: Spacecraft Electrostatic Radiation
Page 134 and 135: Ion Beam Propulsion StudySpacecraft
Page 136 and 137: RT-MATRIX: Measuring Total Organic
Page 139 and 140: Appendix AKSC High-Priority Technol
Page 141 and 142: Risk Assessment ToolMission Data Fe
Page 143 and 144: Appendix BInnovative Partnership Pr
Page 145 and 146: system for the Government, using th
Page 147: tracking objects after launch, and
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2006-2007 - Kennedy Space Center Technology Transfer Office

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