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Mass spectrometry labelling technique - acid catalyzed deuterium and oxygen 18 exchange by gas-liquid chromatography
The objective of the Energy Expenditure in Space Flight (ESS) experiment is to demonstrate and evaluate the doubly labeled water method of measuring the energy expended by crew members during approximately 7 days in microgravity. The doubly labeled water technique determines carbon dioxide production which is then used to calculate energy expenditure. The method relies on the equilibrium between oxygen in respiratory carbon dioxide and oxygen in body water. Because of this equilibrium, the kinetic of water turnover and respiration are interdependent. Under normal conditions, man contains small but significant amounts of deuterium and oxygen 18. Deuterium is eliminated from the body as water while oxygen 18 is eliminated as water and carbon dioxide. The difference in the turnover rates in the two isotopes is proportional to the carbon dioxide production. Deliberately enriching the total body water with both of these isotopes allows the isotope turnovers to be accurately measured in urine, plasma, or saliva samples. The samples are taken to the laboratory for analysis using an ion-ratio spectrometer.
Other than Earth, Mars is the planet generating the greatest interest among those researching and contemplating the origin and distribution of life throughout the universe. The similarity of the early environments of Earth and Mars, and the biological evolution on early Earth provides the motivation to seriously consider the possibility of a primordial Martian biosphere. In 1975 the Viking project launched two unmanned spacecraft to Mars with the intent of finding evidence of the existence of present or past life on this planet. Three Viking Biology experiments were employed: the Labeled Release experiment, the Gas Exchange Experiment, and the Pyrolytic Release experiment. Each of these three experiments tested for microbial existence and utilization of a substrate by examining the gases evolved from specific chemical reactions. Although the results of these experiments were inconclusive, they inferred that there are no traces of extant life on Mars. However, the experiments did not specifically look for indication of extinct life. Therefore, most of the exobiologic strategies and experiments suggested for the Mars Rover Sample Return Mission involve searching for signature of extinct life. The most significant biological signatures and chemical traces to detect include: isotopic and chemical signatures of metabolic activity, anomalous concentrations of certain metals, trace and microfossils, organically preserved materials, carbonates, nitrates, and evaporites.
A novel approach to the radioactive labeling of peptides and PNA oligomers is described. It is based on the conjugation of a deoxynucleoside 3'-phosphate with the terminal amine of the substrate, followed by phosphorylation of the 5'-hydroxyl group of the nucleotide using T4 polynucleotide kinase and [gamma-32P]ATP.
Introduction: Micrometer-scale chemical analyses of chondritic meteorites and mission-returned asteroid samples can reveal details of the physical and chemical processes operating in the early solar system, including processes that gave rise to planets, moons, and minor bodies. These primitive astromaterials are comprised of chondrules, calcium- and aluminum-rich inclusions (CAI), and many other silicates, oxides, metals, sulfides, and fine-grained materials. The chemical and mineralogical complexity of these samples, vast populations of different components, and heterogeneity across mm to km scales, all limit our understanding of the origin and evolution of these materials. Here, we describe recent efforts to use machine learning techniques to automate the segmentation of chemical maps of chondritic meteorites, designed to aid studies of asteroid samples returned by spacecraft. By automating the task of segmentation it will become possible to rapidly analyze and interpret the sizes, shapes, mineralogy, chemistry, and other properties of every chondrule, calcium- and aluminum-rich inclusion (CAI) and other clast within and between asteroid samples. Sample return missions significantly accelerate and heighten the need to develop such new data analysis techniques, and associated data repositories. Techniques: Neural networks require abundant training data, i.e. images which have been segmented by a human user. We have manually segmented data available from previous petrologic and chemical work at NASA Johnson Space Center and the American Museum of Natural History [1-4]. These data were derived from energy- and wavelength-dispersive X-ray spectroscopy (EDS, WDS) mapping of samples from many chondrite groups. The Deeplabv3+ [5] neural network architecture was trained on human-labeled masks and used to create machine-labeled masks. Several different algorithms were investigated, with inputs ranging from common RGB image formats through to hyperspectral datasets, with raw data comprising greyscale maps of Mg, Ca, and Al, with or without Si, Fe, Ti for both EDS and WDS data, and extending to other elements in EDS only. Each greyscale image was paired with a binary mask for each labelled particle type. Results: The trained algorithms can segment (Fig 1), classify, and measure the dimensions of thousands of particles in chemical maps of a standard 1-inch round petrographic section in seconds to minutes, rather than many hours needed by a human. Accuracy of the algorithms varied from chondrite to chondrite and across particle types. Further results and details of the algorithms will be presented at the workshop. Future directions: Machine learning has the potential to revolutionize our understanding of complex particle populations contained within primitive astromaterial, with segmentation being a critical first step. Example applications include better understanding of particle transport, nebular reservoirs, parent body accretion, and a deeper understanding of the relationships between particle populations and bulk rock elemental and isotopic compositions. In addition to benefits that machine learning can bring to individual researchers, building a community data repository of thousands to millions of particles across hundreds of samples will open up many other possibilities. For example, with a large enough dataset it will be possible to search for exceptionally closely matching particles across disparate samples. Such a capability would enable a single CAI from OSIRISREx or Hayabusa/II samples to be matched to chondritic CAIs that exhibit near-identical size, texture, and mineralogy, down to the level of similar core phenocrysts, zonation, and rim sequences. Such comparative analyses will help to disentangle precursor chemistry, chronology, gas/dust reservoirs during heating, and accretion. Such an endeavor would be impossible without machine learning and a large community data repository of astromaterial chemical/mineralogic maps.
The doubly labeled water (DLW, 2H(2)18O) method is a highly accurate method for measuring energy expenditure (EE). A possible source of error is bolus fluid intake before body water sampling. If there is bolus fluid intake immediately before body water sampling, the saliva may reflect the ingested water disproportionately, because the ingested water may not have had time to mix fully with the body water pool. To ascertain the magnitude of this problem, EE was measured over a 5-day period by the DLW method. Six subjects were dosed with 2H2(18)O. After the reference salivas for the two-point determination were obtained, subjects drank water (700-1,000 ml), and serial saliva samples were collected for the next 3 h. Expressing the postbolus saliva enrichments as a percentage of the prebolus value, we found 1) a minimum in the saliva isotopic enrichments were reached at approximately 30 min with the minimum for 2H (95.48 +/- 0.43%) being significantly lower than the minimum for 18O (97.55 +/- 0.44, P less than 0.05) and 2) EE values calculated using the postbolus isotopic enrichments are appreciably higher (19.9 +/- 7.5%) than the prebolus reference values. In conclusion, it is not advisable to collect saliva samples for DLW measurements within approximately 1 h of bolus fluid intake.
Recently, evidence has begun to grow supporting the possibility that the Viking GC-MS would not have detected certain carboxylate salts that could have been present as metastable oxidation products of high molecular weight organic species. Additionally, despite the instrument's high sensitivity, the possibility had remained that very low levels of organic matter, below the instrument's detection limit, could have been present. In fact, a recent study indicates that the degradation products of several million microorganisms per gram of soil on Mars would not have been detected by the Viking GC-MS. Since the strength of the GC-MS findings was considered enough to dismiss the biology packet, particularly the LR results, any subsequent evidence suggesting that organic molecules may in fact be present on the Martian surface necessitates a re-evaluation of the Viking LR data. In addition to an advanced mass spectrometer to look for isotopic signatures of biogenic processes, future lander missions will include the ability to detect methane produced by methanogenic bacteria, as well as techniques based on biotechnology. Meanwhile, the identification of Mars samples already present on Earth in the form of the SNC meteorites has provided us with the ability to study samples of the Martian upper crust a decade or more in advance of any planned sample return missions. While contamination issues are of serious concern, the presence of indigenous organic matter in the form of polycyclic aromatic hydrocarbons has been detected in the Martian meteorites ALH84001 and Nakhla, while there is circumstantial evidence for carbonaceous material in Chassigny. The radiochronological ages of these meteorites are 4.5 Ga, 1.3 Ga, and 165 Ma respectively representing a span of time in Earth history from the earliest single-celled organisms to the present day. Given this perspective on organic material, a biological interpretation to the Viking LR results can no longer be ruled out. In the LR experiment, a solution containing C-14 labeled organic compounds was injected into soil samples. The detection of radioactivity in the overhead space would indicate that one or more of the substrates had been chemically converted into a carbon-containing gas. To serve as a control, some samples were heated enough to destroy most known terrestrial microbes so that an indication for life would be a positive response from unheated samples and a negative response from heated samples. On Mars, the LR results had met minimum criteria for a biological interpretation but due to the GC-MS results, the LR responses were later attributed to putative soil inorganic oxidants. Since the time of Viking, studies have been carried out with the objective of determining an oxidant or combination of oxidants that might exist on Mars and have produced the observed kinetics of the LR response. To date, no such agent has been found that produces all aspects of the LR results on Mars. While the above considerations in no way imply the existence of life forms at the two Viking landing sites, inorganic and biological explanations for the Viking LR data should now be considered equally plausible until more complete studies of the Martian surface are carried out. Therefore, in light of the SNC meteorites data and their implications for the possibility of organic matter near or on the Martian surface the Viking biology experiments should thus be seen, not as failures for their inability to provide unambiguous evidence for or against Martian life, but as a foundation for the development of future life-detection instruments. Additional information is contained in the original extended abstract.
The mean daily energy expenditure rates of two rhesus monkeys (Macaca mulatta) were determined during spaceflight on the joint U.S./Russian Bion 11 mission by the doubly labeled water (DLW, 2H218O) method. Control values were obtained from two studies performed under flight-like conditions (n = 4). The mean inflight energy expenditure for the two Bion 11 monkeys was 81.3 kcal/kg/day, which was higher than that seen previously. The average energy expenditure (77.6 +/- 4.4 kcal/kg/day) for the four ground control monkeys was slightly lower than had been measured previously.
The primary metabolic fate of phyenylalanine, following its deamination in plants, is conscription of its carbon skeleton for lignin, suberin, flavonoid, and related metabolite formation. Since this accounts for approximately 30-40% of all organic carbon, an effective means of recycling the liberated ammonium ion must be operative. In order to establish how this occurs, the uptake and metabolism of various 15N-labeled precursors (15N-Phe, 15NH4Cl, 15N-Gln, and 15N-Glu) in lignifying Pinus taeda cell cultures was investigated, using a combination of high performance liquid chromatography, 15N NMR, and gas chromatograph-mass spectrometry analyses. It was found that the ammonium ion released during active phenylpropanoid metabolism was not made available for general amino acid/protein synthesis. Rather it was rapidly recycled back to regenerate phenylalanine, thereby providing an effective means of maintaining active phenylpropanoid metabolism with no additional nitrogen requirement. These results strongly suggest that, in lignifying cells, ammonium ion reassimilation is tightly compartmentalized.
In the first step of the phenylpropanoid metabolic pathway, L-phenylalanine (L-Phe) is deaminated to form E-cinnamate, in a conversion catalyzed by phenylalanine ammonia-lyase (PAL; EC 4.3.1.5). The metabolic fate of the ammonium ion (NH4+) produced in this reaction was investigated in sweet potato (Ipomoea batatas) tuber discs. [15N]-Labeled substrates including L-Phe, in the presence or absence of specific enzyme inhibitors, were administered to sweet potato discs in light under aseptic conditions. 15N-Nuclear magnetic resonance spectroscopic analyses revealed that the 15NH4+ liberated during the PAL reaction is first incorporated into the amide nitrogen of L-glutamine (L-Gln) and then into L-glutamate (L-Glu). These results extend our previous observations in pine and potato that PAL-generated NH4+ is assimilated by the glutamine synthetase (GS; EC 6.3.1.2)/glutamate synthase (GOGAT; EC 1.4.1.13) pathway, with the NH4+ so formed ultimately being recycled back to L-Phe via L-Glu as aminoreceptor and donor.