Cell-specific protein profiling in Arabidopsis thaliana trichomes: identification of trichome-located proteins involved in sulfur metabolism and detoxification.

Metabolite, protein, and transcript analysis at the cellular level gives unparalleled insight into the complex roles tissues play in the plant system. However, while capillary electrophoresis and PCR amplification strategies make the profiling of metabolites and transcripts in specific cell types possible, the profiling of proteins in small samples represents a bottleneck. Here for the first time protein profiling has been achieved in a specific plant cell type: The application of specific cell sampling and shotgun peptide sequencing (nano LC/MS/MS) resulted in the identification of 63 unique proteins from pooled Arabidopsis trichome cells.

Metabolite profiling in plant biology: platforms and destinations.

Optimal use of genome sequences and gene-expression resources requires powerful phenotyping platforms, including those for systematic analysis of metabolite composition. The most used technologies for metabolite profiling, including mass spectral, nuclear magnetic resonance and enzyme-based approaches, have various advantages and disadvantages, and problems can arise with reliability and the interpretation of the huge datasets produced. These techniques will be useful for answering important biological questions in the future.

Differential metabolic networks unravel the effects of silent plant phenotypes.

Current efforts aim to functionally characterize each gene in model plants. Frequently, however, no morphological or biochemical phenotype can be ascribed for antisense or knock-out plant genotypes. This is especially the case when gene suppression or knockout is targeted to isoenzymes or gene families.

Linking protein fractionation with multidimensional monolithic reversed-phase peptide chromatography/mass spectrometry enhances protein identification from complex mixtures even in the presence of abundant proteins.

Recently, multidimensional shotgun proteomics has proven to be an alternative technology able to identify hundreds of proteins from single samples. Two major limitations of the technology are the presence of high abundance proteins (e.g.

Process for the integrated extraction, identification and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks.

A novel extraction protocol is described with which metabolites, proteins and RNA are sequentially extracted from the same sample, thereby providing a convenient procedure for the analysis of replicates as well as exploiting the inherent biological variation of independent samples for multivariate data analysis. A detection of 652 metabolites, 297 proteins and clear RNA bands in a single Arabidopsis thaliana leaf sample was validated by analysis with gas chromatography coupled to a time of flight mass spectrometer for metabolites, two-dimensional liquid chromatography coupled to mass spectrometry for proteins, and Northern blot analysis for RNA. A subset of the most abundant proteins and metabolites from replicate analysis of different Arabidopsis accessions was merged to form an integrative dataset allowing both classification of different genotypes and the unbiased analysis of the hierarchical organization of proteins and metabolites within a real biochemical network.

Interpreting correlations in metabolomic networks.

Correlations, as observed between the concentrations of metabolites in a biological sample, may be used to gain additional information about the physiological state of a given tissue. In this mini-review, we discuss the integration of these observed correlations into metabolomic networks and their relationships with the underlying biochemical pathways.

Immunocytochemical and molecular data guide peptide identification by mass spectrometry: orcokinin and orcomyotropin-related peptides in the stomatogastric nervous system of several crustacean species.

In order to identify new orcokinin and orcomyotropin-related peptides in crustaceans, molecular and immunocytochemical data were combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). In the crayfish Procambarus clarkii, four orcokinins and an orcomyotropin-related peptide are present on the precursor. Because these peptides are highly conserved, we assumed that other species have an identical number of peptides.

Metabolomics in systems biology.

The primary aim of "omic" technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. By their nature, these technologies reveal unexpected properties of biological systems. A second and more challenging aspect of omic technologies is the refined analysis of quantitative dynamics in biological systems.

Scoring and identifying organism-specific functional patterns and putative phosphorylation sites in protein sequences using mutual information.

The co-variance of amino acid positions within a multiple alignment of 294 protein kinases from mammals, plants, and bacteria was studied. Applying mutual information (MI), characteristic amino acid sites have been identified markedly discriminating the different organisms. The relation of surface accessibility of these sites in the 3D structure of a kinase and their MI content is studied.

Stable isotope labeling of phosphopeptides for multiparallel kinase target analysis and identification of phosphorylation sites.

An approach for multiparallel target identification and relative quantification of in vitro kinase activities in two different biological samples, using liquid chromatography/mass spectrometry (LC/MS), is described. Synthetic target peptides, containing the putative regulatory phosphorylation sites of sucrose-phosphate synthase (SPS) isoenzymes from Arabidopsis thaliana, were simultaneously in vitro phosphorylated and their phosphorylation states determined. Quantification was achieved by stable isotope labeling of the phosphoserine moiety with ethanethiol and [(2)D(5)]-ethanethiol.

Observing and interpreting correlations in metabolomic networks.

Motivation: Metabolite profiling aims at an unbiased identification and quantification of all the metabolites present in a biological sample. Based on their pair-wise correlations, the data obtained from metabolomic experiments are organized into metabolic correlation networks and the key challenge is to deduce unknown pathways based on the observed correlations. However, the data generated is fundamentally different from traditional biological measurements and thus the analysis is often restricted to rather pragmatic approaches, such as data mining tools, to discriminate between different metabolic phenotypes.

Deciphering metabolic networks.

All higher organisms divide major biochemical steps into different cellular compartments and often use tissue-specific division of metabolism for the same purpose. Such spatial resolution is accompanied with temporal changes of metabolite synthesis in response to environmental stimuli or developmental needs. Although analyses of primary and secondary gene products, i.

Can we discover novel pathways using metabolomic analysis?

Metabolomic analysis aims at the identification and quantitation of all metabolites in a given biological sample. Current data acquisition and network analysis strategies are classified on the basis of pathway elucidation and characteristics of theoretical networks. The development of metabolomic methods and tools is progressing rapidly, but an understanding of the resulting data is limited owing to a fundamental lack of biochemical and physiological knowledge about network organization in plants.

Visualizing plant metabolomic correlation networks using clique-metabolite matrices.

Motivation: Today, metabolite levels in biological samples can be determined using multiparallel, fast, and precise metabolomic approaches. Correlations between the levels of various metabolites can be searched to gain information about metabolic links. Such correlations are the net result of direct enzymatic conversions and of indirect cellular regulation over transcriptional or biochemical processes.

Comparative quantification and identification of phosphoproteins using stable isotope labeling and liquid chromatography/mass spectrometry.

A new liquid chromatography/mass spectrometry (LC/MS) method is described for relative quantification of phosphoproteins to simultaneously compare the phosphorylation status of proteins under two different conditions. Quantification was achieved by beta-elimination of phosphate from phospho-Ser/Thr followed by Micheal addition of ethanethiol and/or ethane-d(5)-thiol selectively at the vinyl moiety of dehydroalanine and dehydroamino-2-butyric acid. The method was evaluated using the model phosphoprotein alpha(S1)-casein, for which three phosphopeptides were found after tryptic digestion.

Biosynthesis of PF1022A and related cyclooctadepsipeptides.

PF1022A belongs to a recently identified class of N-methylated cyclooctadepsipeptides (CODPs) with strong anthelmintic properties. Described here is the cell-free synthesis of this CODP and related structures, as well as the purification and enzymatic characterization of the responsible synthetase. For PF1022A synthesis extracts of Mycelia sterilia were incubated with the precursors L-leucine, D-lactate, D-phenyllactate, and S-adenosyl-L-methionine in the presence of ATP and MgCl(2).

Biosynthesis of taxol: enzymatic acetylation of 10-deacetylbaccatin-III to baccatin-III in crude extracts from roots of Taxus baccata.

The biosynthesis of taxol is a multistep process. One intermediate reaction is the acetylation of 10-deacetylbaccatin-III (10-DAB) to baccatin-III, an assumed precursor of taxol. Here we describe the cell free acetylation of 10-DAB in crude extracts from roots of Taxus baccata saplings using 14C-or 3H-labeled acetyl-coenzyme A as the acetyl donor.