Heat-shock response in Arabidopsis thaliana explored by multiplexed quantitative proteomics using differential metabolic labeling

We have developed a general method for multiplexed quantitative proteomics using differential metabolic stable isotope labeling and mass spectrometry. The method was successfully used to study the dynamics of heat-shock response in Arabidopsis thaliana. A number of known heat-shock proteins were confirmed, and some proteins not previously associated with heat shock were discovered. The method is applicable in stable isotope labeling and allows for high degrees of multiplexing.

Quantitative proteomics using uniform 15N-labeling, mascot and the trans-proteomic pipeline

Stable isotope labeling combined with MS is a powerful method for measuring relative protein abundances, for instance, by differential metabolic labeling of some or all amino acids with 14N and 15N in cell culture or hydroponic media. These and most other types of quantitative proteomics experiments using high-throughput technologies, such as LC-MS/MS, generate large amounts of raw MS data. This data needs to be processed efficiently and automatically, from the mass spectrometer to statistically evaluated protein identifications and abundance ratios. This paper describes in detail an approach to the automated analysis of uniformly 14N/15N-labeled proteins using MASCOT peptide identification in conjunction with the trans-proteomic pipeline (TPP) and a few scripts to integrate the analysis workflow. Two large proteomic datasets from uniformly labeled Arabidopsis thaliana were used to illustrate the analysis pipeline. The pipeline can be fully automated and uses only common or freely available software.

Quantitative proteomics using uniform N-15-labeling, MASCOT, and the trans-proteomic pipeline

Stable isotope labeling combined with MS is a powerful method for measuring relative protein abundances, for instance, by differential metabolic labeling of some or all amino acids with N-14 and N-15 in cell culture or hydroponic media. These and most other types of quantitative proteomics experiments using high-throughput technologies, such as LC-MS/MS, generate large amounts of raw MS data. This data needs to be processed efficiently and automatically, from the mass spectrometer to statistically evaluated protein identifications and abundance ratios. This paper describes in detail an approach to the automated analysis of Uniformly N-14/N-15-labeled proteins using MASCOT peptide identification in conjunction with the trans-proteomic pipeline (TPP) and a few scripts to integrate the analysis workflow. Two large proteomic datasets from uniformly labeled Arabidopsis thaliana were used to illustrate the analysis pipeline. The pipeline can be fully automated and uses only common or freely available software.

Multiplexed quantitative proteomics using differential metabolic 15N-labeling

There are several advantages of using metabolic labeling in quantitative proteomics. The early pooling of samples compared to post-labeling methods eliminates errors from different sample processing, protein extraction and enzymatic digestion. Metabolic labeling is also highly efficient and relatively inexpensive compared to commercial labeling reagents. However, methods for multiplexed quantitation in the MS-domain (or ‘non-isobaric’ methods), suffer from signal dilution at higher degrees of multiplexing, as the MS/MS signal for peptide identification is lower given the same amount of peptide loaded onto the column or injected into the mass spectrometer. This may partly be overcome by mixing the samples at non-uniform ratios, for instance by increasing the fraction of unlabeled proteins. We have developed an algorithm for arbitrary degrees of nonisobaric multiplexing for relative protein abundance measurements. We have used metabolic labeling with different levels of 15N, but the algorithm is in principle applicable to any isotope or combination of isotopes. Ion trap mass spectrometers are fast and suitable for LC-MS/MS and peptide identification. However, they cannot resolve overlapping isotopic envelopes from different peptides, which makes them less suitable for MS-based quantitation. Fourier-transform ion cyclotron resonance (FTICR) mass spectrometry is less suitable for LC-MS/MS, but provides the resolving power required to resolve overlapping isotopic envelopes. We therefore combined ion trap LC-MS/MS for peptide identification with FTICR LC-MS for quantitation using chromatographic alignment. We applied the method in a heat shock study in a plant model system (A. thaliana) and compared the results with gene expression data from similar experiments in literature.

Quantitative plant proteomics

Quantitation is an inherent requirement in comparative proteomics and there is no exception to this for plant proteomics. Quantitative proteomics has high demands on the experimental workflow, requiring a thorough design and often a complex multi-step structure. It has to include sufficient numbers of biological and technical replicates and methods that are able to facilitate a quantitative signal read-out. Quantitative plant proteomics in particular poses many additional challenges but because of the nature of plants it also offers some potential advantages. In general, analysis of plants has been less prominent in proteomics. Low protein concentration, difficulties in protein extraction, genome multiploidy, high Rubisco abundance in green tissue, and an absence of well-annotated and completed genome sequences are some of the main challenges in plant proteomics. However, the latter is now changing with several genomes emerging for model plants and crops such as potato, tomato, soybean, rice, maize and barley. This review discusses the current status in quantitative plant proteomics (MS-based and non-MS-based) and its challenges and potentials. Both relative and absolute quantitation methods in plant proteomics from DIGE to MS-based analysis after isotope labeling and label-free quantitation are described and illustrated by published studies. In particular, we describe plant-specific quantitative methods such as metabolic labeling methods that can take full advantage of plant metabolism and culture practices, and discuss other potential advantages and challenges that may arise from the unique properties of plants.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes. Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes, Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

Difference gel electrophoresis

DIGE is a protein labelling and separation technique allowing quantitative proteomics of two or more samples by optical fluorescence detection of differentially labelled proteins that are electrophoretically separated on the same gel. DIGE is an alternative to quantitation by MS-based methodologies and can circumvent their analytical limitations in areas such as intact protein analysis, (linear) detection over a wide range of protein abundances and, theoretically, applications where extreme sensitivity is needed. Thus, in quantitative proteomics DIGE is usually complementary to MS-based quantitation and has some distinct advantages. This review describes the basics of DIGE and its unique properties and compares it to MS-based methods in quantitative protein expression analysis.

Hydroponic isotope labelling of entire plants (HILEP) for quantitative plant proteomics; an oxidative stress case study

Hydroponic isotope labelling of entire plants (HILEP) is a cost-effective method enabling metabolic labelling of whole and mature plants with a stable isotope such as N-15. By utilising hydroponic media that contain N-15 inorganic salts as the sole nitrogen source, near to 100% N-15-labelling of proteins can be achieved. In this study, it is shown that HILEP, in combination with mass spectrometry, is suitable for relative protein quantitation of seven week-old Arabidopsis plants submitted to oxidative stress. Protein extracts from pooled N-14- and N-15-hydroponically grown plants were fractionated by SDS-PAGE, digested and analysed by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). Proteins were identified and the spectra of N-14/N-15 peptide pairs were extracted using their m/z chromatographic retention time, isotopic distributions, and the m/z difference between the N-14 and N-15 peptides. Relative amounts were calculated as the ratio of the sum of the peak areas of the two distinct N-14 and N-15 peptide isotope envelopes. Using Mascot and the open source trans-proteomic pipeline (TPP), the data processing was automated for global proteome quantitation down to the isoform level by extracting isoform specific peptides. With this combination of metabolic labelling and mass spectrometry it was possible to show differential protein expression in the apoplast of plants submitted to oxidative stress. Moreover, it was possible to discriminate between differentially expressed isoforms belonging to the same protein family, such as isoforms of xylanases and pathogen-related glucanases (PR 2). (C) 2008 Elsevier Ltd. All rights reserved.

Hydroponic isotope labeling of entire plants (HILEP) for quantitative plant proteomics

Quantitative analysis by mass spectrometry (MS) is a major challenge in proteomics as the correlation between analyte concentration and signal intensity is often poor due to varying ionisation efficiencies in the presence of molecular competitors. However, relative quantitation methods that utilise differential stable isotope labelling and mass spectrometric detection are available. Many drawbacks inherent to chemical labelling methods (ICAT, iTRAQ) can be overcome by metabolic labelling with amino acids containing stable isotopes (e.g. 13C and/or 15N) in methods such as Stable Isotope Labelling with Amino acids in Cell culture (SILAC). SILAC has also been used for labelling of proteins in plant cell cultures (1) but is not suitable for whole plant labelling. Plants are usually autotrophic (fixing carbon from atmospheric CO2) and, thus, labelling with carbon isotopes becomes impractical. In addition, SILAC is expensive. Recently, Arabidopsis cell cultures were labelled with 15N in a medium containing nitrate as sole nitrogen source. This was shown to be suitable for quantifying proteins and nitrogen-containing metabolites from this cell culture (2,3). Labelling whole plants, however, offers the advantage of studying quantitatively the response to stimulation or disease of a whole multicellular organism or multi-organism systems at the molecular level. Furthermore, plant metabolism enables the use of inexpensive labelling media without introducing additional stress to the organism. And finally, hydroponics is ideal to undertake metabolic labelling under extremely well-controlled conditions. We demonstrate the suitability of metabolic 15N hydroponic isotope labelling of entire plants (HILEP) for relative quantitative proteomic analysis by mass spectrometry. To evaluate this methodology, Arabidopsis plants were grown hydroponically in 14N and 15N media and subjected to oxidative stress.

Application of semiquantitative proteomics techniques to the Maillard reaction

Proteomic tools-in particular, mass spectrometry (MS)-have advanced significantly in recent years, and the identification of proteins within complex mixtures is now a routine procedure. Quantitative methods of analysis are less well advanced and continue to develop. These include the use of stable isotope ratio approaches, isotopically labeled peptide standards, and nonlabeling methods. This paper summarizes the use of MS as a proteomics tool to identify and semiquantify proteins and their modified forms by using examples of relevance to the Maillard reaction. Finally, some challenges for the future are presented.

Investigation of liquid MALDI and optimization for instrument tuning and quantitative measurements

The success of Matrix-assisted laser desorption / ionisation (MALDI) in fields such as proteomics has partially but not exclusively been due to the development of improved data acquisition and sample preparation techniques. This has been required to overcome some of the short comings of the commonly used solid-state MALDI matrices such as - cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB). Solid state matrices form crystalline samples with highly inhomogeneous topography and morphology which results in large fluctuations in analyte signal intensity from spot to spot and positions within the spot. This means that efficient tuning of the mass spectrometer can be impeded and the use of MALDI MS for quantitative measurements is severely impeded. Recently new MALDI liquid matrices have been introduced which promise to be an effective alternative to crystalline matrices. Generally the liquid matrices comprise either ionic liquid matrices (ILMs) or a usually viscous liquid matrix which is doped with a UV lightabsorbing chromophore [1-3]. The advantages are that the droplet surface is smooth and relatively uniform with the analyte homogeneously distributed within. They have the ability to replenish a sampling position between shots negating the need to search for sample hot-spots. Also the liquid nature of the matrix allows for the use of additional additives to change the environment to which the analyte is added.