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Drought stress at the reproductive stage causes severe damage to productivity of wheat. However, little is known about the metabolites associated with drought tolerance. The objectives of this study were to elucidate changes in metabolite levels in wheat under drought, and to identify potential metabolites associated with drought stress through untargeted metabolomic profiling using a liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based technique called Isotopic Ratio Outlier Analysis. Metabolomic analysis was performed on flag leaves of drought-stressed and control (well-watered) plants after 18 days of post-anthesis drought stress at three-hour intervals over a 24-hour period. Out of 723 peaks detected in leaves, 221 were identified as known metabolites. Sixty known metabolites were identified as important metabolites by 3 different methods, PLS-DA, RF and SAM. The most pronounced accumulation due to drought stress was demonstrated by tryptophan, proline, pipecolate and linamarin, whereas the most pronounced decrease was demonstrated by serine, trehalose, N-acetyl-glutamic acid, DIBOA-glucoside etc. Three different patterns of metabolite accumulation were observed over 24-hour period. The increased accumulated metabolites remained higher during all 8 time points in drought stressed leaves. On the contrary, metabolites that showed decreased level remained significantly lower during all or the most time points. However, the levels of some decreased metabolites were lower during the day, but higher during night in drought stressed leaves. Both univariate and multivariate analyses predicted that N-acetyl-glutamic acid, proline, pipecolate, linamarin, tryptophan, and DIBOA-glucoside could be potential metabolite biomarkers, and their levels could serve as indicators of drought tolerance in wheat.

Various research strategies involving biomarker discovery and mechanistic studies in system biology depend on reproducible and reliable quantification of all metabolites from tissue(s) of interest. Contemporary analytical methods rely on mass spectrometry-based targeted and/or untargeted metabolomics platforms. The robustness of these analyses depends on the cleanliness of the samples, accuracy of the database, resolution of the instrument, and, the most variable of the list, the personal preferences of the researcher and the instrument operator. In this chapter, we introduce a simple method to prepare murine liver samples and carry it through the Isotope Ratio Outlier Analysis (IROA

There is always a tension within the omics sciences between trying to measure biological molecules rapidly and measuring accurately. Metabolomics as an omics science tries to measure the small biochemicals rapidly, in a single pass, but the current state of the art cannot provide the reproducibility or accuracy needed for clinical use or even daily reproducibility for larger experiments. The IROA TruQuant measurement system uses a daily "Long-Term Reference Standard (LTRS)" and a chemically identical Internal Standard (IS) to provide validated chemical identity, daily QA/QC on instrument and sample preparation, and accurate reproducible quantitation that is comparable across days, instruments, and even, for most compounds, chromatographic methods. The LTRS is, as the name implies, a Long-Term Reference Standard that is always the same and should therefore provide very similar results on a large but finite collection of compounds. All of the compounds in the LTRS are isotopically signed with formula indicating IROA patterns so they cannot be mistaken for one another. Because of the precise IROA patterns, a software-driven analysis of the compounds seen daily can determine the performance of the instrument in terms of sensitivity, in-source fragmentation, and chromatographic and injection stability and provide completely reproducible quantitation.

Various research strategies involving biomarker discovery and mechanistic studies in system biology depend on reproducible and reliable quantification of all metabolites from tissue(s) of interest. Contemporary analytical methods rely on mass spectrometry-based targeted and/or untargeted metabolomics platforms. The robustness of these analyses depends on the cleanliness of the samples, accuracy of the database, resolution of the instrument, and, the most variable of the list, the personal preferences of the researcher and the instrument operator. In this chapter, we introduce a simple method to prepare murine liver samples and carry it through the Isotope Ratio Outlier Analysis (IROA®) pipeline. This pipeline encompasses sample preparation, LC-MS-based peak acquisition, proprietary software-based library creation, normalization, and quantification of metabolites. IROA® offers a unique platform to create and normalize a local library and account for run-to-run variability over years of acquisition using the internal standards (IROA®-IS) and long-term reference standards (IROA®-LTRS).

There is always a tension within the omics sciences between trying to measure biological molecules rapidly and measuring accurately. Metabolomics as an omics science tries to measure the small biochemicals rapidly, in a single pass, but the current state of the art cannot provide the reproducibility or accuracy needed for clinical use or even daily reproducibility for larger experiments. The IROA TruQuant measurement system uses a daily "Long-Term Reference Standard (LTRS)" and a chemically identical Internal Standard (IS) to provide validated chemical identity, daily QA/QC on instrument and sample preparation, and accurate reproducible quantitation that is comparable across days, instruments, and even, for most compounds, chromatographic methods. The LTRS is, as the name implies, a Long-Term Reference Standard that is always the same and should therefore provide very similar results on a large but finite collection of compounds. All of the compounds in the LTRS are isotopically signed with formula indicating IROA patterns so they cannot be mistaken for one another. Because of the precise IROA patterns, a software-driven analysis of the compounds seen daily can determine the performance of the instrument in terms of sensitivity, in-source fragmentation, and chromatographic and injection stability and provide completely reproducible quantitation.

We evaluated Isotope Ratio Outlier Analysis (IROA) as a metabolome-wide internal standard approach to improve the quality of LC/MS data collected from a large-scale greenhouse experiment designed to metric the ability of metabolomics to model quantitatively nitrogen treatments. We further looked at how IROA would be incorporated into a metabolomics workflow. For this we compared IROA processed data with that generated without the benefit of metabolome-wide internal standards using our current tool, Genedata Expressionist, from the same raw LC/MS data files. In our experiment, 367 maize plants were grown from kernel in a greenhouse under controlled conditions. Plants were treated from germination on with varying concentrations of nutrient nitrogen as one (treatment) variable. A second variable was the presence of one of two transgenes. Metabolomics analysis of leaves was performed by LC/MS positive and negative electrospray ionization modes, and raw data were processed with both our routine and IROA protocols. IROA data analysis detected 184 metabolites in each ionization mode. Analysis without IROA yielded 281 metabolites in positive ionization mode and 172 in negative ionization mode. Data from both protocols were normalized for sample dry weight, location in the greenhouse, extraction batch, sample run order, and internal standard. Normalized results were subjected to partial least squares (PLS) analysis to model the relationship between the metabolome and nitrogen treatment. Without IROA, regression coefficients of 0.819 and 0.849 for positive and negative modes, respectively were achieved. The IROA protocol improved on the values, yielding regression coefficients of 0.876 and 0.879 for positive and negative modes, respectively. In addition, IROA corrected for detector saturation for several high abundant peaks. Our experiment demonstrates that incorporating IROA into an LC/MS metabolomics experiment improves data quality and facilitates more precise modeling of a biological response.

Actinomycetes are powerhouses of natural product biosynthesis. Full realization of this biosynthetic potential requires approaches for recognizing novel metabolites and determining mediators of metabolite production. Herein, we develop an isotopic ratio outlier analysis (IROA) ultra-high performance liquid chromatography-mass spectrometry (UHPLC/MS) global metabolomics strategy for actinomycetes that facilitates recognition of novel metabolites and evaluation of production mediators. We demonstrate this approach by determining impacts of the iron chelator 2,2&prime, bipyridyl on the Nocardiopsis dassonvillei metabolome. Experimental and control cultures produced metabolites with isotopic carbon signatures that were distinct from corresponding &ldquo, standard&rdquo, culture metabolites, which were used as internal standards for LC/MS. This provided an isotopic MS peak pair for each metabolite, which revealed the number of carbon atoms and relative concentrations of metabolites and distinguished biosynthetic products from artifacts. Principal component analysis (PCA) and random forest (RF) differentiated bipyridyl-treated samples from controls. RF mean decrease accuracy (MDA) values supported perturbation of metabolites from multiple amino acid pathways and novel natural products. Evaluation of bipyridyl impacts on the nocazine/XR334 diketopiperazine (DKP) pathway revealed upregulation of amino acid precursors and downregulation of late stage intermediates and products. These results establish IROA as a tool in the actinomycete natural product chemistry arsenal and support broad metabolic consequences of bipyridyl.

>Metabolomics or biochemical profiling is a fast emerging science; however, there are still many associated bottlenecks to overcome before measurements will be considered robust. Advances in MS resolution and sensitivity, ultra pressure LC–MS, ESI, and isotopic approaches such as flux analysis and stable-isotope dilution, have made it easier to quantitate biochemicals. The digitization of mass spectrometers has simplified informatic aspects. However, issues of analytical variability, ion suppression and metabolite identification still plague metabolomics investigators. These hurdles need to be overcome for accurate metabolite quantitation not only for in vitro systems, but for complex matrices such as biofluids and tissues, before it is possible to routinely identify biomarkers that are associated with the early prediction and diagnosis of diseases. In this report, we describe a novel isotopic-labeling method that uses the creation of distinct biochemical signatures to eliminate current bottlenecks and enable accurate metabolic profiling

The levels of mRNA for plasma proteins and for metallothionein in rat liver during the acute-phase response were studied by hybridization to specific cDNA probes. The mRNA for alpha 2-macroglobulin, the beta-chain of fibrinogen, alpha 1-acid glycoprotein (so-called acute-phase reactants) reached a maximum level between 18 and 36 h after inducing an acute inflammation. The level of mRNA for metallothionein-I peaked earlier, after 12 h. The mRNA for transferrin showed a delayed increase with a broad maximum for its relative level after 36-60 h. The mRNA levels for albumin and alpha 2u-globulin (so-called negative acute-phase reactants) decreased, reaching a minimum of 25% of the normal level after 36 h (albumin) and after 72 h (alpha 2u-globulin). The ratios of the rates of incorporation of leucine into the proteins over the levels of their mRNA in liver changed only a little, indicating that the rates of synthesis of plasma proteins in the liver are regulated at the mRNA level during the acute-phase response to inflammation.

1. The effect of fasting on hepatic mRNA levels of seven plasma proteins was examined in the rat.2. The levels of mRNA were measured directly in cytoplasmic extracts by hybridization to specific32P-labelled cDNA probes.3. Following a 48 h period of fasting, the mRNA levels of apolipoprotein E, apolipoprotein A-IV, albumin, transferrin, and transthyretin decreased by 15–30%, while apolipoprotein A-II decreased by 78% compared with non-fasted control rats. The mRNA for apolipoprotein A-I increased by 33%.4. These findings suggest that mRNA levels in the liver following fasting are regulated independently and variations in these levels may be due to differences in transcription rates or mRNA stability.

A cDNA library was constructed from rat liver polyadenylated RNA using the expression vector lambda gt11-Amp3. Several clones expressing antigenic determinants for rat apolipoprotein E were identified. The cDNA insert in one clone was further characterized and found to have a sufficient length (1120 base pairs) to code for full length apolipoprotein E. Restriction mapping and nucleotide sequencing showed the clone to contain the coding region for apolipoprotein E flanked by about 120 nucleotides at the 3'-side and by about 64 nucleotides on the 5'-side. One of the proteins produced by the clone was found to be a prokaryotic/eukaryotic hybrid protein reacting with antibodies to both bacterial beta-galactosidase and rat apolipoprotein E.

In the rodent, the general response to acute inflammation and tissue damage is characterized by a complex rearrangement in the pattern of concentrations of proteins in the plasma leading to an increase in the sedimentation rate of erythrocytes, an increase in leukocyte concentration in the bloodstream, and a decrease in the hematocrit. Body temperature changes only slightly or not at all. The reasons for the change in plasma concentrations of proteins are changes in their rates of synthesis in the liver. Degradation of plasma proteins is not affected. The details of the acute phase response evolved in the interaction of species with their environment. Therefore, it is not surprising to find differences in the details of the acute phase response among species. For example, alpha 2-macroglobulin is a strongly positive acute phase reactant in the rat, but not in the mouse; C-reactive protein is a strongly positive acute phase protein in the mouse, but is not found in the rat. An inducible acute phase cysteine proteinase inhibitor system, which has evolved from a primordial kininogen gene, has been observed so far only in the rat. The changes in the synthesis rates of acute phase proteins during inflammation are closely reflected by corresponding changes in intracellular mRNA levels. In the liver, the capacity to induce the acute phase pattern of synthesis and secretion of plasma proteins probably develops around birth. Changes in mRNA levels are brought about by changes in transcription rates or by changes in mRNA stability. Kinetics of mRNA changes during the acute phase response differ for individual proteins. The main signal compound for eliciting the acute phase response in liver seems to be interleukin-6/interferon-beta 2/hepatocyte stimulating factor, whereas interleukin-1 leads to typical acute phase changes in mRNA levels only for alpha 1-acid glycoprotein, albumin, and transthyretin. Plasma protein genes are expressed in various extrahepatic tissues, such as the choroid plexus, the yolk sac, the placenta, the seminal vesicles, and other sites. All these tissues are involved in maintaining protein homeostasis in associated extracellular compartments by synthesis and secretion of proteins. Synthesis and secretion of plasma proteins in paracompartmental organs other than the liver is not influenced by the acute phase stimuli.