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South African Journal of Science
versión On-line ISSN 1996-7489
versión impresa ISSN 0038-2353
S. Afr. j. sci. vol.109 no.5-6 Pretoria ene. 2013
Plant metabolomics: A new frontier in phytochemical analysis
Fidele Tugizimana; Lizelle Piater; Ian Dubery
Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa
The primary and secondary metabolites found in plant cells are the final recipients of biological information flow. In turn, their levels can influence gene expression and protein stability. Qualitative and quantitative measurements of these metabolites reflect the cellular state under defined conditions, and yield critical insights into the cellular processes that control the biochemical phenotype of the cell, tissue or whole organism. Metabolomics differs from traditional targeted phytochemical analysis in various fundamental aspects; for example, it is a data-driven approach with predictive power that aims to assess all measurable metabolites without any pre-conception or pre-selection. As such, metabolomics is providing new dimensions in the study of systems biology, enabling the in-depth understanding of the intra- and extracellular interactions of plant cells. Metabolomics is also developing into a valuable tool that can be used to monitor and assess gene function, and to characterise post-genomic processes from a broad perspective. Here, we give an overview of the fundamental analytical technologies and subsequent multivariate data analyses involved in plant metabolomics as a research tool to study various aspects of plant biology.
Keywords: chromatography; mass spectrometry; metabolite profiling; multivariate data analysis; nuclear magnetic resonance
An organism is an expression of its underlying molecular composition that reacts and responds to a variety of intra-, inter- and extracellular stimuli. Whereas genes and proteins are mostly involved in storing and unfolding information needed for actualisation of cellular functional processes, metabolite patterns reveal the actual dynamic cellular environment.1 In plants, the metabolome is a compilation of all primary and secondary metabolites, and can be regarded as the final recipient of genetic information (Figure 1) where levels of individual metabolites can influence gene expression, protein stability and metabolic fluxes.2-5 These constituents of the metabolome have a wide range of physiological roles in plants such as participating in basic functions of the living cell, contributing to cellular structural integrity, acting as mobile inter- and intracellular signals, and being involved in passive and active defence responses in plant cells.2,6,7 Hence, qualitative and quantitative measurements of intracellular metabolites yield critical insights into the cellular processes that control the biochemical phenotype of the cell, tissue or whole organism.1,8,9
Metabolomics and systems biology
Metabolomics developed from metabolic profiling and is the most recent of the '-omics' approaches to emerge. The word 'metabolome' was first suggested in 1998 by Stephen Oliver (University of Manchester, UK) to designate the set of all low molecular mass compounds synthesised by an organism. In 2002, Oliver Fiehn (Max Plank Institute, Golm, Germany) introduced the word 'metabolomics' to designate a comprehensive analysis in which all the metabolites of an organism were supposed to be identified and quantified.4 Metabolomics is generally defined as a holistic qualitative and quantitative analysis of all metabolites present within a biological system under specific conditions.1,3,8,9 It differs from the classical or traditional targeted phytochemical analysis in various fundamental aspects, such as being a data-driven approach with predictive power that aims to assess all measurable metabolites without any pre-conception or pre-selection. In order to attain this goal, advanced analytical tools that provide high degrees of sensitivity, selectivity and reproducibility are required.5,9-11
Metabolomics has become a valuable tool for advancing our understanding of primary and secondary metabolism in plants and is revolutionising the field of plant biology.12 It is viewed as a complementary technique to other functional genomics approaches such as transcriptomics and proteomics. Furthermore, metabolomics is a cornerstone in the integration of the '-omics' technologies that contribute to a systems biology overview.13 As such, it assists in providing a holistic understanding of the organisation principle of cellular functions at different levels, and in providing ways of monitoring all biological processes operating as an integrated system.1,4,6,14 Moreover, metabolomics as a post-genomics tool is often regarded as offering distinct advantages when compared to other '-omics' technologies. This point of view is based on the fact that changes in the transcriptome or proteome do not always correlate to biochemical phenotypes.1,11,15,16
Metabolomic approaches, on the other hand, monitor the ultimate products of gene expression - the metabolites - thus providing a phenotypic assessment of a biological system. Metabolites are organic compounds that may not be directly encoded in the genome, and their biosynthesis often involves a diversity of enzymes. Furthermore, metabolites are stoichiometrically interrelated, which results in more complex metabolic networks that do not exist in the case of transcripts or proteins. Thus, metabolomic strategies may actually offer the most valuable and functional information that is crucial in systems biology studies.1,4,6,13,17
All metabolomic analyses are a snapshot (or a point-in-time chemistry) of a biological system (cell, tissue or whole organism), showing which metabolites are present and their levels at a given time point and under specific physiological conditions.3,9,11,14,18 Different metabolomic strategies have thus been developed for different applications, and are presented in Table 1.9,18-20
The workflow for plant metabolomic analysis
Plant metabolomes can be very diverse. Because of the complexity and divergent physicochemical properties of the cellular metabolome, a combination of two or more metabolomic strategies (outlined in Table 1) may be considered to achieve a comprehensive coverage of the plant metabolome. Furthermore, in any metabolomic approach, a broad metabolic picture is achieved through the combination of multiparallel- and complementary analytical systems, including the use of various extraction protocols.5'6'9'1821
A metabolomic analysis comprises three main experimental stages: (1) preparation of the sample, (2) acquisition of the data using analytical methods and (3) data mining using chemometric methods followed by compound identification. These steps are crucially interrelated' and as illustrated in Figure 2, may each consist of a series of sub-steps. The resulting analysed data from the various experimental phases form the basis for meaningful biochemical interpretation.15,22
Sample preparation is a critical step in transforming the sample into a solution that can be analysed to make a vital contribution in defining the array of metabolite classes to be covered. This step involves a series of different experimental stages: selection and harvesting of samples, drying or enzyme quenching procedures, extraction of metabolites and preparation of the samples for analysis. The selection of plant material depends mainly on the biological question that the researcher seeks to investigate.22,23 Throughout this step, care must be taken to avoid the introduction of any form of unwanted variability that would significantly affect the outcome of the analysis. Sample degradation (thermal, oxidative or enzymological) and contamination are major factors leading to variations during this step.8,10,24 Various enzyme quenching methods include drying, treatment with acid, use of enzyme inhibitors or high concentrations of organic solvents.4,22
Plant metabolites are structurally diverse, forming a highly complex spectrum of compounds of different size, solubility, volatility, polarity, quantity and stability.1,19,25-27 Any extraction method would certainly produce an inherently multidimensional sample arising from the chemical and physical differences of the constituents.28,29 Several methods may be employed to extract metabolites; the choice of method depends on a variety of factors, such as the physicochemical properties of the target metabolites, the biochemical composition of the system under investigation and the properties of the solvent to be used. Some of the common extraction methods include solvent extraction, supercritical fluid extraction, sonication and solid phase extraction. However, no comprehensive extraction technique exists for the recovery of all classes of compounds with high reproducibility and robustness. Thus, for a comprehensive coverage of different classes of metabolites, extraction methods may be used in combination.5,10,18,19,22
Data acquisition (sample analysis) follows the sample preparation step and requires advanced analytical techniques as the ultracomplexity of samples for metabolomic analysis makes it impossible to technologically separate, quantify and identify every metabolite within a biological sample.1,9 A range of analytical platforms are employed in metabolomic studies (separately or in combination), and each platform has its own advantages and limitations, either in selectivity or sensitivity (Table 2). The choice of the analytical platform depends mainly on the- study at hand, taking into consideration the class of compounds, their chemical and physical properties, and their concentration levels. As such, the techniques most often used are nuclear magnetic resonance spectroscopy3,5,30 and chromatography coupled to MS.9,31
Analytical platforms employed in metabolomics
A range of analytical technologies may be used in metabolomics, including gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry (CE-MS), liquid chromatography-mass spectrometry (LC-MS), liquid chromatography-electrochemistry-mass spectrometry (LC-EC-MS), nuclear magnetic resonance (NMR) spectroscopy, LC-NmR, direct infusion mass spectrometry (DIMS), and Fourier-transform infrared (FT-IR)- and Raman spectroscopies.8,10,14,31,32 Of these, chromatography-mass spectrometry (GC-MS and LC-MS) and NMR are the most widely applied.4,5,30,31
The use of NMR-based fingerprinting marked the beginning of metabolomics as a tool in biochemistry and phytochemical analysis.19 It is an unbiased, rapid, non-destructive technique that requires little sample preparation and thus lessens the chance of sample loss or the introduction of variability into the preparation.30 In an NMR analysis, there is no analyte separation process involved (as is the case in chromatographic analyses); NMR can thus provide selectivity without separation, is independent of analyte polarity, and does not require sample derivatisation prior to analysis. The magnetic properties of paramagnetic (e.g. 1H and 13C) nuclei allow for a powerful tool for observing the environments of such nuclei bonded all over a molecular skeleton. When samples in a deuterated solvent are placed in a strong magnetic field and irradiated with a radio frequency, the absorption of energy allows the nuclei to be promoted from low-energy to high-energy- spin states. The subsequent emission of radiation during the relaxation process generates the resonances or signals recorded on an NMR spectrum as 'chemical shifts', representing frequencies from all NMR-visible nuclei in the sample, relative to that of a reference proton present in a reference compound. Thus, an NMR spectrum of a multicomponent extract is the result of the superposition of the collective spectra of all NMR-visible individual compounds present in the sample under study. Hence, an NMR analysis would generally give a global view of all the metabolites (primary and secondary) in a sample, provided that they are NMR detectable.5,30 In NMR spectroscopy, the signal intensity for all compounds is dependent on the molar concentrations and reproducibility is high, even though the sensitivity is relatively low (micromolar range) and more sample is required.3,5 Following data acquisition, it is necessary to apply solvent suppression techniques, baseline or background correction, and integration and data normalisation methods.30
Although NMR spectroscopy can yield detailed information on the quantities and identities of metabolites present in extracts, the chemical elucidation of NMR-detected compounds can be highly complex as a result of overlapping signals and shielding effects by neighbouring electrons. Moreover, the inherent low sensitivity of NMR, its sensitivity to the chemical environment (pH, ionic strength, temperature, etc.) of the sample and the differential sensitivity of metabolites to the chemical environment, hamper the quality of NMR analyses of complex samples.30,33 However, the disadvantages of low sensitivity and resolution are addressed by the development of cryogenic probes, higher strength superconducting magnets, miniaturised radio frequency coils and multidimensional (e.g. 2D-J-resolved and heteronuclear single quantum coherence) techniques.5,30,34 By using 2D-NMR that spreads the spectral content over a two-dimensional plane, the identification of compounds can be facilitated and minor compounds can be better observed, even allowing for structural elucidation in crude extracts.3,5,30
Column chromatographic techniques (GC/LC), on the other hand, have medium and high sensitivity, and provide separation of the sample components based on the partitioning of an analyte between stationary and mobile phases, according to its physicochemical properties. A better chromatographic separation of an inherently multidimensional sample can significantly enhance the quality of MS analysis and subsequent- compound identification by reducing the complexity of the mass spectra and the matrix effect. To optimise chromatographic separation of such complex samples, factors including column chemistry, the elution method for LC (gradient or isocratic) and the programmed-temperature method for GC are to be considered. Recent developments in enhancing chromatographic separation of complex samples include the use of multidimensional separation systems such as two-dimensional gas chromatography (GCxGC) and two-dimensional liquid chromatography (LCxLC). Separation involved in these techniques is based on the orthogonality of the two columns (of different chemistries) used. These techniques thus permit an improved chromatographic separation of complex samples by providing an expanded separation space, thereby minimising possible co-elution of an analyte or one-dimensional peak overlap.35-38
Coupled to MS detection, these chromatographic techniques are more sensitive and capable of detecting metabolites in low abundance. GC-MS is a versatile, robust, technically reproducible and sensitive technique in the nano- to picomolar range. It is well suited to non-targeted metabolite profiling of volatile and thermally stable non-polar or derivatised polar metabolites or the targeted analysis of derivatised primary metabolites.39 LC-MS, on the other hand, is technically more demanding, but caters well for metabolites that are non-volatile, polar or thermally labile. In plant metabolomics, LC-MS is frequently used to profile secondary metabolites. As chromatographic separation is based on the chemical nature of the analytes and that of the stationary and mobile phases of the column, more than one type of column chemistry might be needed to cover a wide range of analyte classes, especially for secondary metabolites. In combination with EsI-MS (electron spray ionisation-MS) it offers a powerful and sensitive technique in the pico- to femtomolar range.1,31
Here, the detection of the mass-to-charge ratio (m/z) and abundance of the various analytes generated during ionisation is a key aspect of the analysis. The three main components in all types of MS instruments are (1) an ionisation source such as electron impact- (EI), electrospray-(ESI) and atmospheric pressure chemical (API) ionisations, (2) a mass analyser such as time-of-flight, quadrupole mass filters and quadrupole ion traps and (3) a detector such as an electron multiplier-based detector or a micro-channel plate linked to a time-to-digital converter. To optimise the transmission of ions to the analyser and detector, all three MS components are maintained under vacuum. The detected ions are recorded as pairs of m/z and abundance values, processed, and displayed in a mass spectral format.14,31 To enhance detection efficiency, mass resolving power and mass accuracy of MS, various technologies (in ionisation methods, mass analysers and detectors) have been developed for different applications and for use in multi-MS platforms.14,40-43
In plant metabolomic analyses, MS is the key platform for compound identification, an essential step in the workflow of any metabolomic analysis. The mass spectral data provides a pattern that is most often compound specific. However, the degree of certainty in elucidating the structural and chemical identity of an MS-detected analyte relies on the efficiency and accuracy of the three principal processes of the MS (ionisation, m/z analysis/manipulation and ion detection) and on appropriate algorithms. The procedure in metabolite assignments from MS data consists of: (1) acquisition of sufficient and accurate structural information (such as accurate mass measurement and fragmentation patterns), (2) calculation of chemical combinations that fit the measured accurate mass (elemental composition formula), (3) spectral comparison (mostly for GC-MS instruments) or a database search and verification of the fragmentation pattern (for LC-MS instruments), (4) the use of other MS information available such as MSn and MSE data (the latter is a form of non-selective MSn where E is collision energy) and (5) the use of authentic pure standards (when commercially available) or 13C materials as internal standards.14,15,44,45
The usage of parallel analytical platforms can provide additional information or confirmation for a putatively identified metabolite. For example, EI ionisation is the most commonly used GC-MS ionisation technique that generates informative and characteristic mass spectra resulting from the relative high degree of fragmentation which aids in- compound identification. In contrast, ESI-MS, used in LC-MS, usually generates [M+H] + and [M-H]- ions as the main signals, and these ions are useful for reducing the candidate structures of detected compounds. GC-EI-MS is thus a good approach for targeted analysis of known primary metabolites, whereas LC-ESI-MS is good for untargeted analysis of secondary metabolites.14,15,34,44,45
Data mining and data processing
High-performance instrumentation as described generates extremely large volumes of data. In order to handle these large data sets and to comprehend the metabolome data, automated software is needed that can identify peaks from raw data, align the peaks among different samples and replicates, and identify and quantify each metabolite. Informatics and statistics are therefore essential tools for processing metabolomic data sets.33,46,47 Data mining comprises data pre-processing, data pre-treatment and statistical modelling of the primary data (Figure 2). The statistical modelling (which is essential and central in data analysis) is briefly explained below and the reader is referred to more advanced discussions of the topic.46,47
Because metabolomic analyses reflect the cellular state under defined conditions, metabolomic experiments are designed in such a way as to measure the biological variation in the metabolome.5,18 However, the total variation in the metabolomic data is actually the sum of the pre-defined or induced biological variation and all other variations (non-induced biological, technical and analytical variation). Hence, in the data mining step the procedures of data pre-processing and data pre-treatment aid in 'cleaning' the data to focus on the biologically relevant information. Various software packages (which depend on the analytical technique employed for data acquisition) have been developed to aid with data mining in an automated manner.9,48
Some of the data pre-treatment methods include centring, scaling and transformation. The centring procedure enables the conversion of all concentrations to fluctuate around the zero value of coordinates, by calculating the average of each variable and subtracting it from each observation. This process adjusts differences in the offset between high and low levels of compounds in samples. It thus simplifies the estimation of regression coefficients. Scaling, on the other hand, involves dividing each variable by a function related to its standard deviation (scaling factor) to adjust for the variation in fold differences between detected metabolites. Lastly, mathematical transformation processes are performed on the raw data because of the possibility of non-linearity in variables from a biological system. These methods transform the data into data matrices suitable for linear modelling techniques by converting multiplicative relations into additive relations, and correcting for heteroscedasticity (random variables with different variability).47-49 The cleaned data are then subjected to statistical analysis which provides model-based descriptions of the biological variation in the system under study. These statistical models specifically single out representatives of metabolites of interest (annotated peaks), which can further be chemically or structurally identified in a definitive manner.
Statistical modelling and multivariate data analysis
Metabolomic studies generally generate high-dimensional and complex data sets that are difficult to analyse and interpret by visual inspection or any traditional univariate statistical analyses. Multivariate data analysis (MVDA) methods - mathematical modelling approaches - are therefore used to extract meaningful information from these large empirical data sets.4,49-51 These chemometric techniques provide models that are well suited to handle confounding and covariance patterns (both within and between variables) - analyses that are normally beyond the capacity of traditional univariate statistical methods.52-54 Table 3 lists a number of chemometric methods that are used for MVDA. Depending on the research objectives, the most appropriate method should be exploited. Detailed explanations of the mathematical algorithms on which these chemometric models are based, can be found in the cited literature. It may suffice to underline that most of these MVDA models are projection-based methods and apply, in an expanded manner, the- eigenvector/eigenvalues and kernel algebraic notions. Furthermore, these methods are based on the notion of latent variables (assuming that the system under consideration is driven by a definable number of latent variables) that assume a linear (or non-linear) relationship between the descriptor and response variables (see Figure 3: X and Y matrices: observed variables and pre-defined response outputs).53-55
The high-dimensional and complex metabolomic data can be chemometrically analysed in unsupervised and supervised ways (Table 3 and Figure 3). The unsupervised modelling of the data focuses on the intrinsic structure, relations and interconnectedness of the data and is sometimes referred to as descriptive models. Supervised modelling, on the other hand, seeks to transform the multivariate data from metabolite profiles into a representation of biological interest under the guidance of a 'supervisor'. These models are often called predictive models. The basis of supervised modelling is that there are some patterns (such as metabolic fingerprints) in data that have predefined responses (such as effects of a treatment or condition), and the goal of supervised methods is to find a model or mapping that will correctly associate the inputs with the responses.54 The data is thus algebraically represented in two types of matrices - the descriptor- matrix X (observed variables) and the response matrix Y (the pre-defined traits). Geometrically, a multivariate modelling process defines a point in K-dimensional space with the descriptor values as coordinates.53,54,56 The unsupervised methods are non-parametric analyses and generate models that are independent of the user. The input data, the descriptor matrix X, is presented into the system, which then simplifies and reduces the dimensionality of the data sets, grouping metabolites into different clusters with no loss of information. The supervised models, on the other hand, are mathematical transformations that correctly relate the descriptor matrix X with the response matrix γ.46,53,54,56
In many metabolomic studies, principal component analysis (PCA) - an unsupervised multivariate linear model - and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) - a supervised model - are often used for data analysis. In all unsupervised chemometric methods, PCA remains the workhorse and gold standard model to deal with high-dimensional and complex data sets.46,53 PCA is a projection-based method and a mathematically rigorous process that provides a global and qualitative visual representation of similarity or dissimilarity between and within samples (without using class information; e.g. treatment vs. control).46
In PCA modelling, the variance in a data set is algebraically described in terms of underlying orthogonal variables, also called principal components (PCs). The original variables are thus expressed as linear combinations of these PCs (latent variables), each consisting of two parts - a score (ti) and loading (pi). All PCs are mutually linearly orthogonal to each other and each PC counts for a portion of the total variance in the data set, the first two or three PCs accounting for the largest part of the total variance. The descriptor matrix X is thus mathematically projected into a low-dimensional space, providing interpretable visualisation of the original complex data set thereby highlighting similarities or differences. The score plot gives information about relationships between objects (e.g. trends, groupings and outliers). The Y- and X-axes (e.g. PC1 vs. PC2) of a score plot illustrate the variation within and between groups, respectively. The loading plot illustrates the putative discriminating variables responsible for sample clustering and also explains the variation in scores.46,53,54 Figure 4a and 4b illustrate typical PCA-derived score and loading plots, respectively.
OPLS-DA is a linear regression method, which has been successfully used for prediction modelling in metabolomics and biochemical applications.52,53,55 It is a supervised classification model that differs from PCA by the addition of grouping variables that indicate in which class the samples belong. Where PCA modelling is a descriptive method, OPLS-DA method is an explicative or predictive analysis. The latter facilitates the identification of the metabolite ions responsible for the discrimination between groups.57,58
OPLS-DA is a modification of the PLS-DA (projection to latent structures-discriminant analysis) method, with an integral orthogonal signal correction filter. The OPLS-DA modelling aims at finding predictive components that simultaneously maximise the covariance and correlation between X and Y matrices.57 Algebraically, the model uses information in the response matrix Y to decompose the descriptor matrix X into correlated, orthogonal and residual structures of information, respectively. The power of this regression model lies in its ability to separate modelling of Y-predictive (response-related)- and systematic Y-orthogonal (response-orthogonal) variations in data, while simultaneously maximising the covariance between X and Y. The Y-orthogonal variation can be described as systematic effects needed to characterise the system but are unrelated to the model predictions.52,55,57
OPLS-DA methods therefore model data according to a priori class information (such as treated vs. non-treated) assigned to samples before the analysis. This separation of Y-predictive (discriminating) variation and Y-orthogonal variation (that which does not contribute to the class separation) greatly facilitates the data interpretation. As such, the OPLS-DA model is a suitable tool to extract information on changes or differences in the molecular composition of samples (Figure 4c). While the OPLS-DA loading S-plot (Figure 4d) enables the extraction of statistically and potentially biochemically significant metabolites or biomarkers in the samples, the more advanced shared-and-unique-structures plot (not shown) enables the identification of metabolites that are shared between groups or that are unique to a group.53,57,59
Compound identification
Compound identification, the last step in metabolomic analyses, is of great importance because biochemical interpretation of metabolomic data relies heavily on the availability of well-structured databases for the identification of metabolites. In putative identification some molecular properties (such as experimentally determined accurate mass) and mass spectral patterns are used to define molecular and empirical formulae from which metabolites can be derived or identified by comparative searches of available spectral, compound and metabolic pathway databases.15,34 In such identification procedures, chemical standards are normally not used and the putatively identified metabolites are usually reported with a defined degree of certainty.14,15,57 Definitive identification, on the other hand, involves the use of more than two molecular properties (retention time, retention index, mass spectral fragmentation, NMR-spectral shifts), comparative searches of libraries (mass spectral, NMR-spectral, retention index), confirmation with authentic chemical standards and the use of in vivo labelling methods.15,18,60 In some instances, analytically detected entities of biological significance are reported as unknown with no structural identification.10,15,18,31 Figure 5 schematically illustrates typical information generated from different analytical methods, aiding the identification of compounds in a metabolomic analysis.
Applications of metabolomics in plant research
Despite present limitations, metabolomics has proved to be an indispensable tool for characterisation of post-genomic processes in plants with a broader perspective. The uniqueness of metabolomics, firstly, is that it is a data-driven approach with mathematically rigorous data analysis methods and, secondly, is that it has the ability to provide a (relatively) holistic analysis of the actual cellular dynamisms of a biological system under consideration. Metabolomic analyses offer ways of elucidating relationships that occur primarily through regulation at the metabolic level and reveal a direct link between a gene sequence and the function of the metabolic network.1,6,8,54,61
Plant metabolomics is still a relatively young field. Figure 6 shows the increase in publications in plant metabolomics relative to those related to genomics and proteomics. Metabolomic strategies have much to offer and are increasingly being applied in various areas of the plant sciences.62 This increase in publications is the result of a divergence in the use of the new technology where different metabolomic approaches (Table 1) is combined with one or more analytical platforms (Table 2).
Broad research areas where metabolomics are applied include the interpretation of metabolic pathways and networks, biomarker discovery that can assist in the identification of novel molecular targets and bioactive metabolites,59,63-65 genotyping,1,8,16 gene function elucidation,66-68 plant breeding and crop quality assessment,18,20,69-71 the discovery of metabolites involved in environmental adaptations, abiotic and biotic stress responses, host-pathogen interactions,72-79 molecular biotechnology, and recombinant DNA technology, including risk assessment of genetically modified crops.34
Metabolomics can be an effective approach for the comprehensive evaluation of the qualities of medicinal plants.80 The combination of NMR spectroscopy and MVDA was used in a chemotaxonomic study of Ilex paraguariensis (a tonic and medicinal plant) and other Ilex species.81 Distinct discrimination of species was observed, based on a large number of metabolites present in organic and aqueous fractions. The major metabolites that contributed to the discrimination were identified as arbutin, caffeine, phenylpropanoids and theobromine. Among those metabolites, arbutin, which had not been reported as a constituent of Ilex species, was found to be a biomarker in 8 of the 11 species investigated. With regards to the mining of medicinal plants for the discovery of bioactive metabolites, metabolomics has so far been a valuable tool for high-throughput screening of bioactive substances in order to discover new phytotherapeutic agents with high selectivity, unique modes of action and acceptable toxicological profiles.80
In the development of novel herbicides and pesticides, metabolomics is an invaluable tool because of its non-targeted nature. Modes of action of herbicides determine how plants respond to these chemicals and can be used to predict the suitability of new lead compounds. Here, applications of metabolomics in agroecosystems also include the investigation of ecotoxicological risk assessment of these bioactive compounds.82,83
Ecometabolomic studies were the subject of a recent review 83 concerning investigation into the responses of some metabolic pathways in plants to changes in abiotic factors (such as temperature, water, nutrient availability and pollution) and the biotic interactions between two or more species, which provided new biochemical insights that can be useful for systems biology and metabolic or genetic engineering.
NMR-based and MS-based metabolic fingerprints allowed the investigation of a range of chemistries, adding insight into the metabolic changes associated with establishment of disease in Arabidopsis thaliana leaves infected with Pseudomonas syringaeJ6 Significant alterations in the levels of amino acids and other nitrogenous compounds, as well as specific classes of glucosinolates, disaccharides and molecules that influence the prevalence of reactive oxygen species involved in defence signalling were identified. The findings suggest that, superimposed on defence suppression, pathogens reconfigure host metabolism to provide the sustenance required to support exponentially growing populations of apoplastically localised bacteria.
To obtain further insight into the interaction between plants and herbivores, the interaction between cabbage (Brassica oleracea) and small cabbage white caterpillars (Pieris rapae) was analysed by LC-MS.69 This study revealed a high correlation in levels of three structurally related coumaroylquinic acids in both plants and caterpillars, which suggests that these compounds represent a 'metabolic interface' in the interaction between the plant and the caterpillars.
Another NMR-based metabolomic analysis of the metabolome of tobacco plants treated with salt contributed to the understanding of the dosage and duration dependence of salinity effects on plant metabolism.73 The results showed that salinity causes alterations in widespread metabolic networks involving, inter alia, transamination, the tricarboxylic acid cycle, glutamate-mediated proline biosynthesis and shikimate-mediated secondary metabolism. These results evidenced the valuable insights provided by metabolomic approaches in understanding the osmotic effects on plant biochemistry.
The composition of secondary metabolites greatly influences the quality and health potential of food and food products, in particular, flavonoids as a result of their antioxidant properties. Bovy and co-workers84 highlighted the potential of GC-MS and LC-MS based metabolomics in profiling the metabolic changes in the flavonoid biosynthetic pathway of genetically engineered tomatoes and in monitoring the flux into newly introduced branches of the flavonoid pathway, such as stilbenes, aurones, chalcones, anthocyanins and flavones.
Further selected examples (Table 4) illustrate the wide and divergent range of applications of metabolomics and metabolomic approaches in modern plant sciences.
Current limitations of metabolomics
One of the main challenges of plant metabolomic studies is the enormous complexity and diversity of the plant metabolome and the incomplete knowledge of plant metabolic pathways. Plant primary and secondary metabolites constitute a more heterogeneous group of molecules than the biomacromolecules in terms of physical and chemical properties.1,3,5,9,10,19 An analysis of the metabolome, with its divergent physicochemical properties and wide variation in concentration ranges, would thus require a wide spectrum of chemistries and instrumentation with wide dynamic ranges. Hence, it is currently technologically impossible to extract and analyse all metabolites in a cell or organism in a single analysis, and the currently characterised plant metabolites represent a very small fraction of the- whole metabolome. A second challenging task is the identification and/ or structural elucidation of molecules from analytical detector signals. The lack of universal metabolite-specific libraries and known reference compounds currently represents a major limitation to the definitive identification of metabolites.15,18,60 Fortunately, a number of strategies, such as advancement in and complementary use of technology (LC-NMR-MS, GCxGC-TOF-MS, highly improved MS instrumentation, etc.) and metabolomic databases,12,85 are increasingly being brought forward to assist in metabolite annotations and compound identification.14,15,36
Conclusion and outlook
The combination of the capabilities of different analytical instrumentation for the analyses of multicomplex samples and the integration of metabolomics with other '-omics' approaches in the context of a high-dimensional biological approach, is able to provide new insights into cellular function and regulation of metabolic networks. The ultimate aim of '-omics' technologies is to understand and predict the behaviour of complex systems such as plants, through the use of results obtained from data mining tools for subsequent modelling and simulation. Plant metabolomics has developed to the point where it can be applied alone and/or in combination with other technologies of functional genomics. Even with its current limitations, plant metabolomics is an informative tool that is revolutionising plant biology.
The National Research Foundation and the University of Johannesburg are acknowledged for support.
Authors' contributions
F.T., L.P. and I.A.D. contributed to and wrote the manuscript. I.A.D. was the project leader.
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Ian Dubery
Department of Biochemistry, University of Johannesburg
PO Box 524, Auckland Park 2006, South Africa
Received: 12 Apr. 2012
Revised: 10 Sep. 2012
Accepted: 01 Nov. 2012


text:
An IRONMAN Rookie Finished What He Started in Lake Tahoe
An IRONMAN rookie enjoys the heart and spirit of the sport, despite a tough day in Tahoe.
by Kevin Mackinnon
It was supposed to be Thomas Stark's 50th birthday present to himself. Just over a year ago Stark was flipping pancakes in his kitchen in Washington, D.C. when his girlfriend, Joanne Hopkins, got word that there would be a new IRONMAN race in Lake Tahoe. A full-distance finisher herself, she and a few friends were texting back and forth, trying to decide if they should enter the new race.
"I'll do that," Stark yelled across the room, getting a laugh from Hopkins, who was fully aware that he couldn't swim.
Stark entered the race and promptly signed himself up for a triathlon swim course at his local YMCA. A few weeks later he entered an open-water swim race, completing the 500 m event just a few seconds ahead of the final finisher - an eight-year-old named Simone.
Over the next year Stark worked really hard on his swim technique. Last August he entered the two-mile event at the same open-water swim race, this time finishing with ease. He was ready to become an IRONMAN.
A month later he got into the chilly waters of Lake Tahoe and loved every minute of the swim, despite the tough conditions.
"I loved everything about it," he says. "The fog, the crowd, the people, the snow, I was smiling while I was swimming. I didn't want it to be over."
The cold conditions, though, would come back to haunt him. As so many did on race day, Stark struggled to warm up during the bike. He barely made the cut off, then started the run. Well, sort of. He was so cold he had to walk the first few miles.
Then, along the way, he stopped at one of the aid stations and began to sweat, which cooled him down even more once he started moving again. When he got to an aid station manned by a bunch of students from UC Davis, his teeth were chattering so much he could barely talk. Realizing he was in trouble, he decided to quit.
"The decision was rational, but the hard part was taking off that timing chip and handing it away," he remembers.
Later that night he returned to the finish line bundled in so many clothes he could barely move to watch Hopkins finish. The next morning the two were having a cup of coffee when she asked him what he wanted to do that day—they weren't leaving until Tuesday.
"I want to finish the race," he said. "I've still got 15 miles to do."
Stark got his running gear back on and headed out to the course.
"As I continued on my run, I met a couple with their children down on the Truckee River trail," Stark wrote in an e-mail. "It turned out they were both finishers from the day before and were pretty shocked I still had my race bib on and was running the final miles by myself the next day."
As he ran towards the finish line Stark was shocked to see more than a dozen people at the line waiting for him. Corey and Patrick, the couple who he had seen on the course, had beelined back to Squaw Valley and rounded up a bunch of their friends to greet Stark across the line.
"As I rounded the final turn into the village, I could hear applause, cow bells and cheers from a dozen people with signs who came out to cheer me home to the finish. One of the guys even put his finisher's medal on my neck for the photos. It was such an act of generosity and acceptance that I am still in awe."
While he didn't make it to the line last month, Stark says he wouldn't change a thing. He's now made some amazing new friends and learned that there's much more to IRONMAN than getting across the line.
"I learned that IRONMAN is not a life-list box to check," he says. "It is a life changer. You can't do it and not have your life changed.
Thomas Stark has some unfinished business to take care of, which he's pretty sure he'll be taking on next year in Tahoe.

subset: commoncrawl


text:
Auto insurance policies: all you need to know
CarInsurance.com gets thousands of questions about auto insurance policies. Here are the top questions our readers ask about what their policies cover.
If you don t see the answer to your question here, search to see if we have already answered your car insurance policy question. If not, you can ask your own question .
What does liability insurance cover? What does 25/50/25 mean?
Liability insurance protects car owners whose vehicle injures others or damages their property. It does not cover the insured vehicle itself. There are two types of liability coverages, bodily injury and property damage.
- Bodily injury coverage pays for medical expenses and lost wages of people you have injured in an auto accident.
- Property damage covers damages you have caused to someone else's property, such as their vehicle, house or fence.
Liability coverages are commonly referred to by their maximum limits in thousands, such as 25/50/25. The first and second numbers stand for your bodily injury liability limits, which here are $25,000 per person and $50,000 per accident. The third number represents your property damage liability limit of $25,000 per accident.
What is full coverage?
There s really no such thing, because no policy can cover every single peril or situation. Most commonly, full coverage is what people label car insurance policies that have liability coverages along with collision and comprehensive physical damage coverages.
- Collision covers damage to your car when it hits, or is hit by, another vehicle, or other object.
- Comprehensive covers your car for those damages from non-collision causes, such as vandalism, hail, animals or theft.
What are the recommended limits for liability?
State liability limits are typically low; a severe accident can easily exceed the limits of minimum auto insurance policies, leaving personal assets of the car owner at risk.
The insurance industry recommends bodily injury liability coverage of $100,000 per person and $300,000 per accident, and property damage liability of $50,000. This is shown as 100/300/50 coverage. If you can afford even more coverage, then the recommendation is limits of 300/500/100.
What is an SR-22?
A SR-22 is a form that is filed with the state verifying that you have a current car insurance policy with the state mandated coverages. The particular limits that are required vary from state to state; some require higher Liability limits.
Often the SR-22 is required after certain convictions, such as a DUI or driving without insurance, or to reinstate your license after a suspension, and in most states it must be maintained for three years.
Who do I have to list as drivers?
You need to list all household members living in your residence when applying for insurance and anyone who frequently operates your vehicle even if they don t live with you.
Most insurers include those listed as drivers on the policy. There are some that allow you to exclude a driver from the policy or not rate a person on the policy (like an unlicensed 15-year-old).
Failure to list all drivers could result in lack of proper coverage, an increase in payment or the denial of a claim.


text:
January 04, 2012
UCLA Anderson Using iPads to Evaluate MBA Applications
New Matchbox application makes admissions process paperless
LOS ANGELES -- The application process for the full-time MBA program at UCLA Anderson School of Management has gone completely paperless. Starting this admissions season, applications are being evaluated on iPads, eliminating the need to print out any documents, such as forms, essays, recommendations or transcripts.
Using a new mobile application provided by Matchbox, a Boston-based software company, the school has streamlined the review and analysis process to focus on finding the most distinctive candidates to admit, notes Rob Weiler, UCLA Anderson assistant dean and director of admissions and financial aid.
"With an iPad stylus, the evaluator can highlight evidence and score each MBA application across several metrics including academics, focus, leadership, interpersonal skills and employability," says Craig Hubbell, UCLA Anderson associate director of MBA admissions.
"Both speed and depth of analysis are enhanced with the Matchbox solution, in a process that is healthier for applicants, admissions officers and trees, too," says Hubbell.
"Matchbox provides a new flexibility for us to read applications in any location," adds Weiler. "Whether in the office, on a plane or in an admissions committee meeting, we can instantly view files to compare and contrast the key points of the candidates under consideration."
Going paperless is especially timely given the large increase in applications that the full-time MBA program has received so far this year. Prospective MBA students have responded enthusiastically to innovations in the core curriculum and UCLA Anderson's refocused outreach, driving applications up by more than 20%.
"The ability to readily target candidates who fit with our community will have a profound effect in the classroom and beyond," adds Weiler. "We look forward to seeing the fruits of our efforts in the stellar MBA Class of 2014."
About UCLA Anderson School of Management
Celebrating 75 years of Business Beyond Usual, UCLA Anderson School of Management is among the leading business schools in the world. UCLA Anderson faculty members are globally renowned for their teaching excellence and research in advancing management thinking. Each year, UCLA Anderson provides a distinctive approach to management education to more than 1,800 students enrolled in its MBA, Fully-Employed MBA, Executive MBA, Global Executive MBA for Asia Pacific, Global Executive MBA for the Americas, Master of Financial Engineering, doctoral and executive education programs. Combining selective admissions, varied and innovative learning programs, and a world-wide network of 39,000 alumni, UCLA Anderson develops and prepares global leaders.
Media Relations, (310) 206-7707, firstname.lastname@example.com


text:
The Bureau of Accessibility and Job Accommodation (BAJA) and the Illinois ADA Project host an ADA Distance Learning session on "ADA Update: 19 Years Later." This session will feature representatives from the Federal Agencies discuss an update on their
litigation, technical assistance and enforcement efforts over the past year. In addition, representatives will take questions during the session regarding issues in the workplace or community.
The program is free to those who call and register. You must pre-register prior to the training date in order to receive the dial-in number and pass code.
If you are requesting a reasonable accommodation, please contact BAJA and specify what form of accommodation is needed at least two weeks prior to the training date.
Contact the Bureau of Accessibility and Job Accommodation at one of the following numbers:
No events for August


text:
Group by: Date | Item Type | No Grouping
Number of items: 13.
Lambe, Jacqueline, McNair, Victor and Smith, Ron (2013) Special needs education, e-learning and the reflective e-portfolio: implications for developing and assessing competence in pre-service education. Journal of Education for Teaching: international research and pedaglgy, 39 (2). pp. 181-196. [Journal article]
Jordan, Dervil and Lambe, Jackie (2012) 'It's Easy to See which Side You are on': Northern and Southern Irish Student Teachers' Reflections on Art and Identity. In: Art Education and Contemporary Culture: Irish experiences, international perspectives. (Eds: Granville, Gary), Intellect, The University of Chicago Press, Chicago, IL USA, pp. 89-110. ISBN 978-1-84150-546-6 [Book section]
Lambe, Jackie (2011) Developing pre-service teachers' reflective capacity through engagement with classroom based research. Reflective Practice, 12 (1). pp. 87-100. [Journal article]
Lambe, Jackie (2011) Pre-service education and attitudes towards inclusion: the role of the teacher educator within a permeated teaching model. International Journal of Inclusive Education, 15 (9). pp. 975-999. [Journal article]
Lambe, Jackie and Bones, Robert (2008) The impact of a special school placement on student teachers' beliefs about inclusion in Northern Ireland. British Journal of Special Education, 35 (2). pp. 108-116. [Journal article]
Lambe, Jackie, Muthukrishna, Nithi and Ngcobo, Jabulani (2007) Inclusive Education in Northern Ireland and South Africa: A Conversation. In: Comparative Education and Quality Global Learning: Engaging in Controversial Issues in South Africa and the UK. (Eds: Harber, Clive and Serf, Jeff), TIDE-Global Learning, pp. 43-48. ISBN IBSN 978-0-948838-39-2 [Book section]
Lambe, Jacqueline (2007) Northern Ireland Student Teachers' Changing Attitudes Towards Inclusive Education During Initial Teacher Training. International Journal of Special Education, 22 (1). pp. 59-71. [Journal article]
Lambe, Jacqueline (2007) Student teachers, special educational needs and inclusion education: reviewing the potential forproblem-based, e-learning pedagogy to support practice. Journal of Education for Teaching, International Research and Pedagogy, 33 (3). pp. 359-377. [Journal article]
Lambe, Jacqueline and Bones, Robert (2007) The Effect of School-based Practice on Student Teachers' Attitudes Towards Inclusion in Northern Ireland. Journal of Education for Teaching, International Research and Pedagogy, 33 (1). pp. 99-113. [Journal article]
Gallagher, Eamonn, Bones, Robert and Lambe, Jacqueline (2006) Precision teaching and education: Is fluency the missing link between success and failure? Irish Educational Studies, 25 (1). p. 93. [Journal article]
Lambe, Jacqueline and Bones, Robert (2006) Student Teachers' Perceptions about Inclusive Classroom Teaching in Northern Ireland Prior to Teaching Practice Experience. European Journal of Special Needs Education, 21 (2). pp. 167-186. [Journal article]
Lambe, Jacqueline and Bones, Robert (2006) Student teachers' attitudes to inclusion: implications for Initial Teacher Education in Northern Ireland. International Journal of Inclusive Education, 10 (6). p. 511. [Journal article]
Lambe, Jacqueline and Clarke, Linda (2002) Initial Teacher Education on-line: Factors Influencing the Use of Computer Conferencing by Student Teachers. European Journal of Teacher Education, 26 (3) . pp. 351-363. [Journal article]
This list was generated on Fri Aug 23 01:41:55 2019 BST.


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It is NOT MORAL to use violence (or threats of violence) to change the behavior of peaceful people. This is true no matter what they are doing: whether they are talking to each other, writing to each other, meeting with each other, worshipping with each other, or, yes, trading with each other.
Even if you COULD successfully direct the behavior of other people who have their own plans, IT IS NOT MORAL TO DO SO.


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Just about four months ago my best friend K and her husband J brought a lovely new human into this world. Their new baby is happy, laughing, and good natured...seemingly content with everything going around her and pleased with the attentions of her family (including her big sister, my awesomely terrific godchild!).
How wonderful it must be to be a child...napping and drinking milk, having people bathe you and comb your hair. I sometimes wish I could go back to that time, if only to relish this life of being absolutely care-free. I would store this feeling for stormier times to come, when I can then take it out and rub it against my cheek like a blankie.
Then again, I don't know how long I could be on a diet consisting of milk and milk.
I suppose there is a lot to be said about every stage in life, and the important thing is to make sure we don't forget to savor each one – embracing all the good that comes with the moment you are in. Like being a child (Kids, don't try to grow up too fast! You will miss those carefree days when you have rent to pay!). Like being an adult (Yay! My own kitchen...all the raw cake batter I can eat!).
And for all ages, except the strictly milk-drinking set, there's chocolate cupcakes...
Chocolate and Fig Preserve Cupcakes
(adapted from Nigella Lawson's Chocolate-Cherry Cupcakes in How to Be A Domestic Goddess)
For the cupcakes:
For the icing:
- Place butter in a saucepan and put over low heat to melt. When it is almost completely melted, add chocolate. Once the chocolate has softened a bit, remove the pan from heat and stir until chocolate is completely melted and the mixture is smooth.
- Add the fig preserves, sugar, salt, and eggs to the chocolate mixture, then mix until everything is well incorporated. Stir in the flour, to which you've added the baking powder (do not overmix!).
- Pour into a 12-bun muffin tin lined with papers and bake in an 180C oven for 25-30 minutes, or until toothpick comes out fairly clean.
- Cool in the pan on a rack for 10 minutes before turning out. Wait to cool completely before icing.
- For the icing, melt chocolate and cream in a saucepan over low heat. Remove from heat and whisk until it's smooth and thick. Ice the cupcakes, smoothing it out with the back of a spoon or a spatula. Garnish with a candied nut on each – I used candied pili nuts.
The changes I made to the recipe were substituting the original cherry jam with fig preserves, and using a mixture of all purpose flour and baking powder instead of self-raising flour (which I didn't have)...and using candied nuts instead of glace cherries for garnish. If you own this book you will notice that the recipe is pretty much the same as her Chocolate Orange Cake a few pages earlier (which I adapted for Yummy Magazine last march), using the cherry jam instead of the orange marmalade. I love both the orange cake and this fig preserve cupcake version – adding the jam/marmalade/preserves to the batter does two things: it yields a moist and rich cake as opposed to a light and spongy one, and it gives another dimension of flavour...the fruit underlying the chocolate. It also makes for a supremely satisfying raw cake batter to lick off everything! I will be experimenting with other fruit preserves soon...
I made these to take to K's house for a small tea party. We sat outdoors and enjoyed K's lovely spread of tea sandwiches (in a proper multi-tiered, afternoon-tea-type tray) and buttermilk scones with cream cheese icing. We chatted and played with the baby and whiled the afternoon away together...enjoying the moment :)
One day we will introduce K's little one to chocolate...and I hope to be present on that special occasion. Until then, she's happy chugging away at her milky sustenance and we are happy just to watch (while having tea and scones and cupcakes) :)


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January 30, 2014
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Our booking engine will search for all available Cargo Van Rentals in Omegna in real time and return results of the best prices for the dates selected. We compare the prices form all major car rental suppliers to offer you a wide range of Cargo Vans. You will find examples of the Cargo Van group range below, but for a full offer and availability please use the Instant Quote form. Please note that availability for Cargo Van in Omegna Via Comoli is limited and we advise booking a few months in advance to reserve the most popular Cargo Van vehicles. You can cancel your reservation free of charge so book now to secure your Cargo Van hire.
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LeTourneau University is pleased to announce Dr. Kelly Liebengood has been appointed to a cabinet-level role as the university's new Chief Global Initiatives Officer. He will be responsible for leading the university's international recruiting and global initiatives programs, including overseeing projects dealing with study abroad and global service learning.
Since the fall of 2009, Kelly has been serving as an associate professor of biblical studies at LETU. In 2012 he also became the university's director of the Center for Global Service Learning.
Liebengood is charged with equipping LETU to be a university of global influence where faculty members prepare students to succeed in the global workplace and excel as transformational leaders and service providers in the world community. Liebengood seeks for LETU to be known widely as a university of choice for international students, actively engaged with global educational partners around the world.
Liebengood earned his doctorate in biblical studies from the University of St. Andrews in Scotland, and holds a Master of Divinity degree from Midwestern Baptist Theological Seminary and a Master of Arts in education from the University of Kansas. His undergraduate degree was from San Jose State University in advertising.
Liebengood has served as a professor, student life director, missionary, elder, university campus director, and pastor in various international settings including: Costa Rica, Cuba, Chile, Egypt, Scotland and Turkey.
Besides English, Liebengood speaks Spanish and reads Italian, French and Portuguese.
"Kelly has a demonstrated passion for Christ and students," said LETU Provost Dr. Philip A. Coyle. "He brings a compelling commitment to the growth and health of LeTourneau University as an institution of global impact."
Major initiatives of LETU's Office of Global Initiatives including creating a more global and international university environment through increasing the number of international students and encouraging students to travel and study abroad. The university seeks to support international student recruitment, retention and alumni service. Other objectives include equipping students with a global understanding and competencies and enhance global competencies of faculty and staff. The university also seeks to become a university without borders with a strong global presence. Liebengood will facilitate opportunities for students and faculty to engage in global service learning opportunities.
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text: Finally finished the 2011 Block of the Month from Bunny Hill Designs web site - this quilt was great fun to do. AND first time ever - I did not buy anything specifically for this quilt - it was all done from what I had on hand. It is hand appliqued and hand quilted.


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Sounds like the ever-overworked HR department over at ESPN has got yet another case on its hands.
Word broke this weekend that Around the Horn contributor (and Fanhouse blogger) Jay Mariotti was arrested on a domestic violence rap after an argument with this girlfriend turned heated and she ended up with scratches and bruises. Mariotti was released on a whopping $50,000 bail.
Unfortunate news, and it sounds like a bit more than a parking ticket.
I'll be honest, I don't read a lot of Mariotti's work and he doesn't seem to have a lot of respect in the sports journalism business. White Sox television voice Hawk Harrelson had it out with him a few years back and obviously Ozzie Guillen is not a great fan of Mariotti's either. Famously, neither is Mariotti's former colleague Roger Ebert. And they are but a few of the many who seem to share Gregg Doyel's overwhelmingly negative opinion about "Jay the Joke".
Unfortunately for ESPN, however, while Mariotti may be unique in the seemingly universal hatred that gets spewed in his direction, he is far from the first member of the Worldwide Leader to get himself into trouble.
One has to start questioning ESPN, which has sure seen enough of its talent land in trouble in recent years. With the army of thousands who work in Bristol, I have no idea if the percentage has reached Cincinnati Bengals levels yet; but here is a rather lengthy list of those who have landed in hot water or been pink-slipped because of something that happened while employed by ESPN:
It was announced recently that the ever-edgy columnist had left his long-time gig with the Kansas City Star after an extended leave of absence.
Whitlock resigned from his online work at ESPN a few years back and later revealed that he was fired from the television side due to comments said to be made towards Mike Lupica and Scoop Jackson.
His Twitter feed says it all – 'Black people think I'm a sellout, white people think I'm racist, I think I'm too honest…'
Whitlock continues to write for Fanhouse as well as Fox Sports, and also does radio and fills in for Jim Rome on occasion, and I have a feeling he has more projects set for the future.
Steve Phillips
Was canned from ESPN last October after reports surfaced about an affair with he and a 22-year old production assistant, which also led to his divorce. It was said that Phillips also took a leave of absence from his GM job with the Mets in 1998, also due to sexual assault allegations. Phillips now does some work for New York radio as well as satellite video and still does commentary on 2KSports MLB video game titles.
Harold Reynolds
Was terminated from ESPN in 2006 following a sexual harassment charge, allegedly for giving a co-worker a hug. Reynolds wound up suing the network and the case was settled in 2008. Reynolds has since resurfaced on the MLB Network after stints with New York Mets television and TBS.
How ESPN did not see this ending in quick disaster is beyond me.
Rush is perhaps the most polarizing figure in talk-radio history, and has brought plenty of controversy along the way, along with one of the most lucrative contracts in the history of radio. The EIB Network is great for Clear Channel affiliates, with local stations surrounding their own personalities around his show. 'This Guy on from 8 AM to Rush' and 'That Guy from Rush till 6 PM.' Limbaugh is more than a show to those stations, he's a time of day.
Describing himself as a life-long football fan, ESPN took a chance on his name recognition, adding him to the network's Sunday NFL pre-game coverage in 2003. That experiment ended in flames after Week 4 when Limbaugh made comments about Donovan McNabb being defended by the media because, in their mind, they collectively wanted to see an African-American succeed as a quarterback. In that pre-Twitter era, it wasn't until 48 hours later that Limbaugh became a hot-button topic and soon after forced to resign.
A bad move from the beginning, asking Limbaugh to refrain from getting on a political soapbox is like asking Tony Siragusa to go on a diet. And McNabb?? His career body of work I say is pretty good.
Sean Salisbury
He sure had a checkered career in Bristol. He clashed with the respected John Clayton, then there was that little something about sending cell phone pictures of his penis, and a slip of the tongue explaining Peyton's Manning's calm during the Colts comeback against the Patriots in the AFC Championship game a few years back.
Salisbury went on to work for a radio station in Dallas, where he was then canned – leading to a lawsuit by Salisbury in an attempt to clear up the 'carelessness' of media stories which he contends ruined his reputation. Salisbury was last seen doing commentary for the 'Lingerie Football League'
Mike Tirico
Today, he's one of the most visible figures at the network and one of the most respected announcers in all of sports. But in 1992 Tirico found himself in a world of hot water stemming from the aftermath of a company party. A 2000 book chronicling the 'unauthorized history of ESPN' noted 'several' instances of sexual harassment by Tirico. After that early-career suspension, it obviously appears that Tirico has cleaned up his off-mic life.
A staple as a sideline reporter during college football telecasts through the 1990's into the 2000's, the Northwestern graduate seemed to have it all, but then faced federal charges for not reporting his taxes for two years. In addition to losing the ESPN job, the legal rap also cost him his marriage.
In 2005 Karsten was scheduled to report to federal prison but did not show up. He was later found dead in his home garage, having hung himself. Sad story. After a prison stint I thought he would have been able to re-surface in another platform, as he was a talented journalist.
Bob Griese
This one I blame on ESPN, which has gone a little overboard promoting NASCAR since acquiring the property in 2007. In its first year of coverage the network even went to the length of including Brent Musberger and Suzy Kolber on its coverage. As talented as the two are covering ball sports, they were clearly out of their element in NASCAR.
Which leads to the incident in which Bob Griese made an off-color comment towards driver Juan Pablo Montoya during one of the network's frequent on-air promos during college football presentations.
There is no middle ground in NASCAR; one either follows the sport feverishly and knows what Denny Hamlin had for breakfast, or one has zero interest whatsoever. Very few casual viewers are going to be persuaded to NASCAR as they would be by a MNF or NBA promo. All this leads to awkward moments such as the PBP guy reading a script with the graphic noting that Jimmie Johnson has a 98 point lead over Tony Stewart and a 122 point lead over Jeff Gordon with five races to go, at which point the other commentators feel like they need to make some sort of comment to at least pretend they know at least something about the sport.
Griese's infamous reference to Montoya and tacos earned him a one-week suspension. Ironically, Montoya announced on his Twitter feed a few weeks later that he had invited his pit crew for dinner and that they had 'Mexican'. There – Bob Griese, vindicated.
Tony Kornheiser
One of the network's most visible personalities over the years was suspended two weeks earlier this year for comments made about SportsCenter anchor Hannah Storm's wardrobe while doing a local show in the DC market.
Dana Jacobson
The host of First Take found herself quickly in hot water for comments made during a celebrity roast for Mike Greenberg and Mike Golic, apparently with a few beverages in her. In a rant directed towards Golic's alma mater, Jacobson said '(screw) Notre Dame', '(screw) Touchdown Jesus', and finally '(screw) Jesus' himself.
Feel free to take shots at the Golden Dome, but curse Touchdown Jesus, Jesus Jones, or even Jesus himself at you own peril.
Danyelle Sargent
Remember the kid who was pressed into duty doing a sports segment on a Ball State student newscast a few years back, and made the famous 'Boom Goes the Dynamite' line? Well that was a flawless performance next to a couple of Danyelle's greatest hits.
During a segment with ESPNews in 2006, Sargent (thinking she's off-mic) yells 'WHAT THE
(BLEEP) WAS THAT!?!' during a highlights package. Broadcasting rule #1: always assume the mic's live.
That would be enough YouTube infamy for one lifetime, but then came Sargent's interview for FOX Sports with Mike Singletary moments before opening kickoff of his first game coaching the San Francisco 49ers. (This isn't specifically ESPN-related, but is relevant nonetheless.)
Danyelle's first question involved telling Singletary that she heard that one of the first people he called upon getting hired was his 'mentor' Bill Walsh. Only two problems with that: first, Singletary never worked for Walsh; and second, Danyelle never got the news flash that BW had passed on more than a year earlier. Too bad the team had already taken his initials off their helmets by then.
This is a prime example of networks looking more for eye candy than someone who actually has his/her research/facts straight.
Jemele Hill
An ESPN writer, Hill has crossed the line on a few occasions. There is nothing wrong with hating the Boston Celtics; however, saying that cheering for them would be like rooting for Hitler and also including a nuclear war reference a bit much though.
Another one of her columns last fall suggested that Green Bay Packers fans give Brett Favre the 'Duracell Treatment' (sorry, loss of season ticket privileges too heavy a price to throw a D Cell), and yet another likened John Calipari to Charles Manson.
Someone, quick! Stop her – before she goes too far and links Bill Belichick with Jeffrey Dahmer.
Michael Irvin
The controversies that followed Irvin off the field during his playing career continued while being a studio analyst at ESPN. Some off-color comments involving current Cowboys QB Tony Romo, as well as being pulled over with drug paraphernalia in his car, did not help neither. Each year, ESPN has an entire new batch of retired athletes (especially NFL) to audition and put on-air, which made parting ways with Irvin all that much easier.
Trev Alberts
He was actually a pretty good commentator for ESPN's college football platforms from 2002-2004, but was let go for 'breach of contract' after deciding not to show up during the first weekend of the 2005 season. At issue was Alberts apparent dissatisfaction with being on the network's 'B' team of commentators (Mark May/Rece Davis) rather than being in with the Chris Fowler/Kirk Herbstriet/Lee Corso action.
Post-ESPN, Alberts bounced around several assignments and is now the Athletic Director at the University of Nebraska-Omaha.
Jeremy Green
The son of coach Dennis Green was a contributing writer for ESPN's Scouts Inc. before being arrested on several charges earlier this year, including possession of child porn and posession of narcotics and drug paraphernalia. The 38-year old Green was released on $750,000 and soon after a spokesman announced that Green was no longer affiliated with the company
And that's just the best of the ESPN HR blotter. From what I hear there are many foot soldiers who get into trouble and are quietly let go behind the scenes and replaced by other foot soldiers. I wouldn't be surprised if ESPN puts the mute button on Mariotti for good; there are plenty of outspoken reporters (and even bloggers) from throughout America to choose from.
Jerod Morris for Around the Horn?? OK, I'll quit sucking up to the editor.
Although it is impossible to be a sports fan and completely boycott ESPN, this is why I personally tend to migrate towards other sources of sports media when possible, whether it be the Internet or other cable sports channels. Employees go off the wagon everywhere, but it seems more endemic in Bristol.
Count me among those who believe that ESPN far too often becomes the story, rather than a source reporting the story. It would be nice if they took a step back and reverted to the bread-and-butter simple love of sports that helped make the network iconic in the 1980's and 1990's.
Jay Mariotti, and his arrest, are the perfect symbol for how far ESPN has strayed from those humble, but much more endearing, beginnings.


text:
Windows - Sound Editing
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Name:Adobe Audition v3 WinAll Cracked NoPE
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Last Updated: 2009-11-28 11:14:51 (Update Now)
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Audition3_EFGJSI_Trial.exe225.02 MB
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nope.nfo13.13 KB
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text:
The Glorious Twelth!
Yes another opportunity to do pre-show checks before the GnOrfolkers descend on the Dereham Model Railway Show at Dereham's Neatherd High School to display our various layouts and stock on an unsuspecting public.
Meeting at the usual time and place with our excellent hosts Ralph and Janet. That's Janet of the delicious home-made biscuits.