Proteomic analysis of synaptosomes using isotope-coded affinity tags and mass spectrometry

Synaptosomes are isolated synapses produced by subcellular fractionation of brain tissue. They contain the complete presynaptic terminal, including mitochondria and synaptic vesicles, and portions of the postsynaptic side, including the postsynaptic membrane and the postsynaptic density (PSyD). A proteomic characterisation of synaptosomes isolated from mouse brain was performed employing the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS/MS). After isotopic labelling and tryptic digestion, peptides were fractionated by cation exchange chromatography and cysteine-containing peptides were isolated by affinity chromatography. The peptides were identified by microcapillary liquid chromatography-electrospray ionisation MS/MS (muLC-ESI MS/MS). In two experiments, peptides representing a total of 1131 database entries were identified. They are involved in different presynaptic and postsynaptic functions, including synaptic vesicle exocytosis for neurotransmitter release, vesicle endocytosis for synaptic vesicle recycling, as well as postsynaptic receptors and proteins constituting the PSyD. Moreover, a large number of soluble and membrane-bound molecules serving functions in synaptic signal transduction and metabolism were detected. The results provide an inventory of the synaptic proteome and confirm the suitability of the ICAT method for the assessment of synaptic structure, function and plasticity.     

Quantitative profiling of differentiation-induced microsomal proteins using isotope-coded affinity tags and mass spectrometry

An approach to the systematic identification and quantification of the proteins contained in the microsomal fraction of cells is described. It consists of three steps: (1) preparation of microsomal fractions from cells or tissues representing different states; (2) covalent tagging of the proteins with isotope-coded affinity tag (ICAT) reagents followed by proteolysis of the combined labeled protein samples; and (3) isolation, identification, and quantification of the tagged peptides by multidimensional chromatography, automated tandem mass spectrometry, and computational analysis of the obtained data. The method was used to identify and determine the ratios of abundance of each of 491 proteins contained in the microsomal fractions of na?ve and in vitro- differentiated human myeloid leukemia (HL-60) cells. The method and the new software tools to support it are well suited to the large-scale, quantitative analysis of membrane proteins and other classes of proteins that have been refractory to standard proteomics technology.     

Protein N-terminal analysis using fast atom bombardment mass spectrometry

An immunoassay is described that discriminates between monomers and oligomers of human leukocyte interferon. The assay in principle can be used to distinguish between monomers and oligomers of any substance.     

Lectin affinity capture,isotope-coded tagging and mass spectrometry to identify N-linked glycoproteins

We describe here a strategy for the large-scale identification of N-glycosylated proteins from a complex biological sample. The approach, termed isotope-coded glycosylation-site-specific tagging (IGOT), is based on the lectin column-mediated affinity capture of a set of glycopeptides generated by tryptic digestion of protein mixtures, followed by peptide-N-glycosidase-mediated incorporation of a stable isotope tag, 18O, specifically into the N-glycosylation site. The 18O-tagged peptides are then identified by multi-dimensional liquid chromatography-mass spectrometry (LC-MS)-based technology. The application of this method to the characterization of N-linked high-mannose and/or hybrid-type glycoproteins from an extract of Caenorhabditis elegans proteins allowed the identification of 250 glycoproteins, including 83 putative transmembrane proteins, with the simultaneous determination of 400 unique N-glycosylation sites. Because the method is applicable to the systematic identification of a wide range of glycoproteins, it should facilitate basic glycobiology research and may be useful for diagnostic applications, such as genome-wide screening for disease-related glycoproteins.     

Protein stoichiometry of a multiprotein complex, the human spliceosomal U1 small nuclear ribonucleoprotein: absolute quantification using isotope-coded tags and mass spectrometry

The human U1 snRNP (small nuclear ribonucleoprotein), which is a part of the spliceosome, consists of U1 snRNA and ten different proteins: seven Sm proteins B/B', D1, D2, D3, E, F, and G and the three U1-specific proteins U1-70 K, U1-A, U1-C. To determine the stoichiometry of all ten proteins, the complex was denatured, digested completely with an endoproteinase and labeled with an amine-specific tag. Corresponding peptides were synthesized and labeled with the same tag containing heavier isotopes. The digest was then spiked with defined amounts of the synthetic peptides, and the resulting isotopic peptide pairs were analyzed quantitatively by mass spectrometry. The mass spectra provided information about the absolute amount of each component in the starting protein mixture. The use of the isotope-coded, amine-specific reagents propionyl-N-oxysuccinimide and nicotinoyl-N-oxysuccinimide was evaluated for stoichiometry determination; the nicotinoyl reagent was found to be advantageous because of its greater mass spectrometric sensitivity. Absolute quantities of all ten proteins were measured, showing equal numbers of all ten proteins in the U1 spliceosomal snRNP. These data demonstrate that quantitative mass spectrometry has great potential for the determination of the stoichiometry of multiprotein complexes.     

Nearline acquisition and processing of liquid chromatography-tandem mass spectrometry data

Liquid chromatography–mass spectrometry (LC–MS) is a commonly used analytical platform for non-targeted metabolite profiling experiments. Although data acquisition, processing and statistical analyses are almost routine in such experiments, further annotation and subsequent identification of chemical compounds are not. For identification, tandem mass spectra provide valuable information towards the structure of chemical compounds. These are typically acquired online, in data-dependent mode, or offline, using handcrafted acquisition methods and manually extracted from raw data. Here, we present several methods to fast-track and improve both the acquisition and processing of LC–MS/MS data. Our nearly online (nearline) data-dependent tandem MS strategy creates a minimal set of LC–MS/MS acquisition methods for relevant features revealed by a preceding non-targeted profiling experiment. Using different filtering criteria, such as intensity or ion type, the acquisition of irrelevant spectra is minimized. Afterwards, LC–MS/MS raw data are processed with feature detection and grouping algorithms. The extracted tandem mass spectra can be used for both library search and de-novo identification methods. The algorithms are implemented in the R package MetShot and support the export to Bruker, Agilent or Waters QTOF instruments and the vendor-independent TraML standard. We evaluate the performance of our workflow on a Bruker micrOTOF-Q by comparison of automatically acquired and extracted tandem mass spectra obtained from a mixture of natural product standards against manually extracted reference spectra. Using Arabidopsis thaliana wild-type and biosynthetic gene knockout plants, we characterize the metabolic products of a biosynthetic pathway and demonstrate the integration of our approach into a typical non-targeted metabolite profiling workflow.     

Protein analysis by electrospray ionization mass spectrometry

The applicability of electrospray ionization (ESI) mass spectrometry to protein analyses has been studied. The molecular weight of hen egg lysozyme (HEL) was determined with an accuracy of +/- 2 u. The choice of solvents and additives in sample preparations was important to achieve high sensitivity as well as high precision of molecular weight measurements.     

Clustering mass spectrometry data using order statistics

Mass spectrometry data is inherently uncertain. Rather than compare peak heights across samples, a comparison can be made of the relative ordering of the peak height across samples. Order statistics are used to provide a distance metric between each ordered list of peak heights from the samples. A principal component analysis is performed on the set of distance vectors to highlight to important components.     

Classification and identification of bacteria by mass spectrometry and computational analysis

Background

In general, the definite determination of bacterial species is a tedious process and requires extensive manual labour. Novel technologies for bacterial detection and analysis can therefore help microbiologists in minimising their efforts in developing a number of microbiological applications.

Methodology

We present a robust, standardized procedure for automated bacterial analysis that is based on the detection of patterns of protein masses by MALDI mass spectrometry. We particularly applied the approach for classifying and identifying strains in species of the genus Erwinia. Many species of this genus are associated with disastrous plant diseases such as fire blight. Using our experimental procedure, we created a general bacterial mass spectra database that currently contains 2800 entries of bacteria of different genera. This database will be steadily expanded. To support users with a feasible analytical method, we developed and tested comprehensive software tools that are demonstrated herein. Furthermore, to gain additional analytical accuracy and reliability in the analysis we used genotyping of single nucleotide polymorphisms by mass spectrometry to unambiguously determine closely related strains that are difficult to distinguish by only relying on protein mass pattern detection.

Conclusions

With the method for bacterial analysis, we could identify fire blight pathogens from a variety of biological sources. The method can be used for a number of additional bacterial genera. Moreover, the mass spectrometry approach presented allows the integration of data from different biological levels such as the genome and the proteome.     

Photo-assisted peptide enrichment in protein complex cross-linking analysis of a model homodimeric protein using mass spectrometry

MS analysis of cross-linked peptides can be used to probe protein contact sites in macromolecular complexes. We have developed a photo-cleavable cross-linker that enhances peptide enrichment, improving the signal-to-noise ratio of the cross-linked peptides in mass spectrometry analysis. This cross-linker utilizes nitro-benzyl alcohol group that can be cleaved by UV irradiation and is stable during the multiple washing steps used for peptide enrichment. The enrichment method utilizes a cross-linker that aids in eliminating contamination resulting from protein-based retrieval systems, and thus, facilitates the identification of cross-linked peptides. Homodimeric pilM protein from Pseudomonas aeruginosa 2192 (pilM) was investigated to test the specificity and experimental conditions. As predicted, the known pair of lysine side chains within 14?? was cross-linked. An unexpected cross-link involving the protein's amino terminus was also detected. This is consistent with the predicted mobility of the amino terminus that may bring the amino groups within 19?? of one another in solution. These technical improvements allow this method to be used for investigating protein-protein interactions in complex biological samples.     

A three-dimensional homology model of lipid-free apolipoprotein A-IV using cross-linking and mass spectrometry

Human apolipoprotein A-IV (apoA-IV) is a 46-kDa exchangeable plasma protein with many proposed functions. It is involved in chylomicron assembly and secretion, protection from atherosclerosis through a variety of mechanisms, and inhibition of food intake. There is little structural basis for these proposed functions due to the lack of a solved three-dimensional structure of the protein by x-ray crystallography or NMR. Based on previous studies, we hypothesized that lipid-free apoA-IV exists in a helical bundle, like other apolipoprotein family members and that regions near the N and C termini may interact. Utilizing a homobifunctional lysine cross-linking agent, we identified 21 intramolecular cross-links by mass spectrometry. These cross-links were used to constrain the building of a sequence threaded homology model using the I-TASSER server. Our results indicate that lipid-free apoA-IV does indeed exist as a complex helical bundle with the N and C termini in close proximity. This first structural model of lipid-free apoA-IV should prove useful for designing studies aimed at understanding how apoA-IV interacts with lipids and possibly with unknown protein partners.     

Comparative analysis of S-fatty acylation of gel-separated proteins by stable isotope-coded fatty acid transmethylation and mass spectrometry

Covalent attachment of palmitic acid or other fatty acids to the thiol groups of cysteine residues of proteins through reversible thioester bonds has an important role in the regulation of diverse biological processes. We describe here the development of a mass spectrometry protocol based on stable isotope-coded fatty acid transmethylation (iFAT) for qualitative and comparative analysis of protein S-fatty acylation under different experimental conditions. In this approach, cellular proteins extracted from different cell states are separated by SDS-PAGE and then the gel is stained with either Coomassie blue or Nile red for improved sensitivity. Protein bands are excised and then an in-gel stable iFAT procedure is performed. The fatty acid methyl esters resulting from derivatization with d0- and d3-methanol are identified by mass spectrometry. By measuring the intensities of labeled and unlabeled fragment ion pairs of fatty acid methyl esters, the levels of S-fatty acylation in different cells or tissues can be compared. This approach has been applied to monitor the changes of S-fatty acylation of zebrafish liver proteome in response to environmental dichlorodiphenyltrichloroethane exposure. Compared with the approach using metabolic incorporation of radioactive fatty acid analogs, it is not only simple and effective but also eliminates the hazards of handling radioactive isotopes.     

Computational and statistical analysis of protein mass spectrometry data

High-throughput proteomics experiments involving tandem mass spectrometry produce large volumes of complex data that require sophisticated computational analyses. As such, the field offers many challenges for computational biologists. In this article, we briefly introduce some of the core computational and statistical problems in the field and then describe a variety of outstanding problems that readers of PLoS Computational Biology might be able to help solve.     

Statistical analysis of relative labeled mass spectrometry data from complex samples using ANOVA

Statistical tools enable unified analysis of data from multiple global proteomic experiments, producing unbiased estimates of normalization terms despite the missing data problem inherent in these studies. The modeling approach, implementation, and useful visualization tools are demonstrated via a case study of complex biological samples assessed using the iTRAQ relative labeling protocol.     

Protein complexes and analysis of their assembly by mass spectrometry

The utility of mass spectrometry for the analysis of proteins has grown enormously in the past decade. Significant advances in detection and ionization techniques are allowing questions about noncovalent assembly to be addressed by the direct observation of gas phase complexes, their assembly in real time and their disassembly by perturbation of solution or instrument conditions. These technological innovations have plainly captured the imagination of biological researchers. Recent and novel developments include the combination of mass spectrometry with isotopic labeling, affinity labeling and genomic information. Collectively, these advances are opening new doors to the isolation of complexes, the identification of their substituents and the characterization of their conformations and assembly.     

Chemical cross-linking and mass spectrometry for protein structural modeling

The growth of gene and protein sequence information is currently so rapid that three-dimensional structural information is lacking for the overwhelming majority of known proteins. In this review, efforts towards rapid and sensitive methods for protein structural characterization are described, complementing existing technologies. Based on chemical cross-linking and offering the analytical speed and sensitivity of mass spectrometry these methodologies are thought to contribute valuable tools towards future high throughput protein structure elucidation.     

Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry

The combined method of LC-MS/MS is increasingly being used to explore differences in the proteomic composition of complex biological systems. The reliability and utility of such comparative protein expression profiling studies is critically dependent on an accurate and rigorous assessment of quantitative changes in the relative abundance of the myriad of proteins typically present in a biological sample such as blood or tissue. In this review, we provide an overview of key statistical and computational issues relevant to bottom-up shotgun global proteomic analysis, with an emphasis on methods that can be applied to improve the dependability of biological inferences drawn from large proteomic datasets. Focusing on a start-to-finish approach, we address the following topics: 1) low-level data processing steps, such as formation of a data matrix, filtering, and baseline subtraction to minimize noise, 2) mid-level processing steps, such as data normalization, alignment in time, peak detection, peak quantification, peak matching, and error models, to facilitate profile comparisons; and, 3) high-level processing steps such as sample classification and biomarker discovery, and related topics such as significance testing, multiple testing, and choice of feature space. We report on approaches that have recently been developed for these steps, discussing their merits and limitations, and propose areas deserving of further research.     

imzML--a common data format for the flexible exchange and processing of mass spectrometry imaging data

The application of mass spectrometry imaging (MS imaging) is rapidly growing with a constantly increasing number of different instrumental systems and software tools. The data format imzML was developed to allow the flexible and efficient exchange of MS imaging data between different instruments and data analysis software. imzML data is divided in two files which are linked by a universally unique identifier (UUID). Experimental details are stored in an XML file which is based on the HUPO-PSI format mzML. Information is provided in the form of a 'controlled vocabulary' (CV) in order to unequivocally describe the parameters and to avoid redundancy in nomenclature. Mass spectral data are stored in a binary file in order to allow efficient storage. imzML is supported by a growing number of software tools. Users will be no longer limited to proprietary software, but are able to use the processing software best suited for a specific question or application. MS imaging data from different instruments can be converted to imzML and displayed with identical parameters in one software package for easier comparison. All technical details necessary to implement imzML and additional background information is available at www.imzml.org.     

Phosphoproteomics toolbox: computational biology, protein chemistry and mass spectrometry

Protein phosphorylation is important for regulation of most biological functions and up to 50% of all proteins are thought to be modified by protein kinases. Increased knowledge about potential phosphorylation of a protein may increase our understanding of the molecular processes in which it takes part. Despite the importance of protein phosphorylation, identification of phosphoproteins and localization of phosphorylation sites is still a major challenge in proteomics. However, high-throughput methods for identification of phosphoproteins are being developed, in particular within the fields of bioinformatics and mass spectrometry. In this review, we present a toolbox of current technology applied in phosphoproteomics including computational prediction, chemical approaches and mass spectrometry-based analysis, and propose an integrated strategy for experimental phosphoproteomics.     

CDtool-an integrated software package for circular dichroism spectroscopic data processing, analysis, and archiving

CDtool is a software package written to facilitate circular dichroism (CD) spectroscopic studies on both conventional lab-based instruments and synchrotron beamlines. It takes format-independent input data from any type of CD instrument, enables a wide range of standard and advanced processing methods, and, in a single user-friendly graphics-based package, takes raw data through the entire processing procedure and, importantly, uses data-mining techniques to retain in the final output all the information associated with the processing. It permits the facile comparison of data obtained from different instruments without the need for reformatting and displays it in graphical formats suitable for publication. It also includes the ability to automatically archive the processed data. This latter feature may be especially useful in light of recent funding institution directives with regard to data sharing and archiving and requirements for "good practice" and "traceability" within the pharmaceutical industry. In addition, CDtool includes a means of interfacing with protein data bank coordinate files and calculating secondary structures from them using alternate definitions and algorithms. This feature, along with a function that permits the facile production of new reference databases, enables the creation of specialized databases for secondary structural analyses of specific types of proteins. Thus the CDtool software not only enables rapid data processing and analyses but also includes many enhanced features not available in other CD data processing/analysis packages.