Amyloid-beta42 signals tau hyperphosphorylation and compromises neuronal viability by disrupting alkylacylglycerophosphocholine metabolism.

Perturbation of lipid second messenger networks is associated with the impairment of synaptic function in Alzheimer disease. Underlying molecular mechanisms are unclear. Here, we used an unbiased lipidomic approach to profile alkylacylglycerophosphocholine second messengers in diseased tissue. We found that specific isoforms defined by a palmitic acid (16:0) at the sn-1 position, namely 1-O-hexadecyl-2-acetyl-sn-glycero-3-phosphocholine (C16:0 PAF) and 1-O-hexadecyl-sn-glycero-3-phosphocholine (C16:0 lyso-PAF), were elevated in the temporal cortex of Alzheimer disease patients, transgenic mice expressing human familial disease-mutant amyloid precursor protein, and human neurons directly exposed to amyloid-beta(42) oligomers. Acute intraneuronal accumulation of C16:0 PAF but not C16:0 lyso-PAF initiated cyclin-dependent kinase 5-mediated hyperphosphorylation of tau on Alzheimer disease-specific epitopes. Chronic elevation caused a caspase 2 and 3/7-dependent cascade resulting in neuronal death. Pharmacological inhibition of C16:0 PAF signaling, or molecular strategies increasing hydrolysis of C16:0 PAF to C16:0 lyso-PAF, protected human neurons from amyloid-beta(42) toxicity. Together, these data provide mechanistic insight into how disruptions in lipid metabolism can determine neuronal response to accumulating oligomeric amyloid-beta(42).

Identification of lysophosphatidylcholine (LPC) and platelet activating factor (PAF) from PC12 cells and mouse cortex using liquid chromatography/multi-stage mass spectrometry (LC/MS3).

Lipids play essential roles in cellular structural support, energy storage and signal transduction. Recently, mass spectrometry (MS) has been used to produce three-dimensional maps that elucidate the lipid composition of complex cellular lysates. The identification of individual lipids within these maps is slow and requires the synthesis and spiking of each candidate lipid. We present a novel MS-based technique that rapidly elucidates the atomic connectivity of the fatty acid/alcohol substituent on the sn-1 position of several different families of glycerophosphocholine-containing lipids within the confines of a chromatographic separation. Sodiated lipid species were fragmented to produce radical cations which lost successive methylene groups upon further collisional activation to reveal the identity of the parent molecule. This approach was demonstrated to be effective on isobaric members of the lysophosphatidylcholine (LPC) and platelet activating factor (PAF) families of glycerophospholipids. We demonstrate the application of this technique to unambiguously identify these species within complex cellular lysates and tissue extracts.

Identification and quantitation of changes in the platelet activating factor family of glycerophospholipids over the course of neuronal differentiation by high-performance liquid chromatography electrospray ionization tandem mass spectrometry.

Glycerophospholipids are important structural lipids in membranes with changes associated with progressive neurodegenerative disorders such as Alzheimer disease. Synthesis of the platelet activating factor (PAF) glycerophospholipid subclass is implicated in the control of neuronal differentiation and death. In this article, we combine nanoflow HPLC and mass spectrometry to screen, identify, and quantitate changes in glycerophospholipid subspecies, specifically PAF family members, over the course of neuronal differentiation. Furthermore, precursor ion scans for fragments characteristic of PAF phosphocholine family members and the standard additions of PAF subspecies were combined to perform absolute quantitation of PAF lipids in undifferentiated and differentiated PC12 cells. Surprisingly, a marked asymmetry was detected in the two predominant PAF species (C16:0, C18:0) over the course of differentiation. These results describe a new technique for the sensitive analysis of lipids combining nanoflow HPLC, ESI-MS, and precursor ion scan. Limits of detection of as little as 2 pg of PAF and LPC were obtained, and analysis of the lipidome of as little as 70,000 cells was performed on this system. Furthermore, application to the PC12 model identified a quantifiable difference between PAF molecular species produced over the course of neuronal differentiation.

A differential phosphoproteomic analysis of retinoic acid-treated P19 cells.

External stimuli trigger internal signaling events within a cell that may represent either a temporary or permanent shift in the phosphorylation state of its proteome. Numerous reports have elucidated phosphorylation sites from a variety of biological samples and more recent studies have monitored the temporal dynamics of protein phosphorylation as a given system is perturbed. Understanding which proteins are phosphorylated as well as when they are phosphorylated may indicate novel functional roles within a system and allow new therapeutic avenues to be explored. To elucidate the dynamics of protein phosphorylation within differentiating murine P19 embryonal carcinoma cells, we induced P19 cells to differentiate using all-trans-retinoic acid and developed a strategy that combines isotopically labeled methyl esterification, immobilized metal affinity chromatography, mass spectrometric analysis, and a rigorous and unique data evaluation approach. We present the largest differential phosphoproteomic analysis using isotopically labeled methyl esterification to date, identifying a total of 472 phosphorylation sites on 151 proteins; 56 of these proteins had altered abundances following treatment with retinoic acid and approximately one-third of these have been previously associated with cellular differentiation. A series of bioinformatic tools were used to extract information from the data and explore the implications of our findings. This study represents the first global gel-free analysis that elucidates protein phosphorylation dynamics during cellular differentiation.

Large-scale mapping of human protein-protein interactions by mass spectrometry.

Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24,540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.

The proteomic reactor facilitates the analysis of affinity-purified proteins by mass spectrometry: application for identifying ubiquitinated proteins in human cells.

Mass spectrometry (MS) coupled to affinity purification is a powerful approach for identifying protein-protein interactions and for mapping post-translational modifications. Prior to MS analysis, affinity-purified proteins are typically separated by gel electrophoresis, visualized with a protein stain, excised, and subjected to in-gel digestion. An inherent limitation of this series of steps is the loss of protein sample that occurs during gel processing. Although methods employing in-solution digestion have been reported, they generally suffer from poor reaction kinetics. In the present study, we demonstrate an application of a microfluidic processing device, termed the Proteomic Reactor, for enzymatic digestion of affinity-purified proteins for liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Use of the Proteomic Reactor enabled the identification of numerous ubiquitinated proteins in a human cell line expressing reduced amounts of the ubiquitin-dependent chaperone, valosin-containing protein (VCP). The Proteomic Reactor is a novel technology that facilitates the analysis of affinity-purified proteins and has the potential to aid future biological studies.

Multiplexed proteomic reactor for the processing of proteomic samples.

We report the development of a 96-well plate proteomic reactor for gel-free processing of minute amounts of complex proteomic samples. The device performs multiplexed trapping, enrichment, and biochemical processing of proteins, resulting in concentrated peptide solutions ready for mass spectrometric analysis. Individual wells on the reactor can process up to 2 microg of protein. We also report the coupling of the plate proteomic reactor with protein fractionation using size-exclusion chromatography for large-scale identification of proteins. To illustrate the potential of this approach, we separated 400 microg of MCF7 cell lysate using size-exclusion chromatography and processed 35 protein fractions on the reactor plate. Using stringent criteria when searching the data, a total of 875 unique proteins were identified. More relaxed searching conditions associated with a 1% false positive rate led to the identification of 2683 unique proteins, meaning that one protein was identified per 3-10 ng of total protein lysate loaded on the reactor plate.

The proteomic reactor: a microfluidic device for processing minute amounts of protein prior to mass spectrometry analysis.

Gel-free proteomics has emerged as a complement to conventional gel-based proteomics. Gel-free approaches focus on peptide or protein fractionation, but they do not address the efficiency of protein processing. We report the development of a microfluidic proteomic reactor that greatly simplifies the processing of complex proteomic samples by combining multiple proteomic steps. Rapid extraction and enrichment of proteins from complex proteomic samples or directly from cells are readily performed on the reactor. Furthermore, chemical and enzymatic treatments of proteins are performed in 50 nL effective volume, which results in an increased number of generated peptides. The products are compatible with mass spectrometry. We demonstrated that the proteomic reactor is at least 10 times more sensitive than current gel-free methodologies with one protein identified per 440 pg of protein lysate injected on the reactor. Furthermore, as little as 300 cells can be directly introduced on the proteomic reactor and analyzed by mass spectrometry.

N-glycosylation analysis using the StrOligo algorithm.

N-glycosylation of proteins is the predominant glycosylation in mammals and confers specific conformations, localization, and functions to proteins. High-throughput proteomics techniques have focused on the identification of proteins through amino acid sequence determination, with little attention paid to their post-translational modification, in particular, glycosylation. High-throughput mass spectrometric data often contain information about glycosylation, but this is systematically discarded by proteomic search engines. We have developed an algorithm, StrOligo (for STRucture of OLIGOsaccharides), capable of automated analysis of oligosaccharide composition and possible structures by mass spectrometry. The algorithm analyzes tandem mass spectrometry (MS/MS) data in an automated three-step process and provides possible structures and a discrimination score. In the first step, the algorithm constructs a relationship tree of the monosaccharide moiety losses observed in the MS/MS spectrum. In the second step, the algorithm uses the tree to propose possible compositions and structures from combinations of adduct and fragment ions as well as a discrimination score, which reflects the fit with the experimental results. Finally, an interface is available to visualize the proposed structures and their scores. As well, the MS/MS spectrum is displayed with relevant peaks labeled for the proposed structure with the highest discrimination score, using a modified nomenclature.

The effect of dissolved oxygen on the production and the glycosylation profile of recombinant human erythropoietin produced from CHO cells.

Human recombinant erythropoietin (rHuEPO) was produced from Chinese hamster ovary (CHO) cells transfected with the human EPO gene. The cells were grown in batch cultures in controlled bioreactors in which the set-points for dissolved oxygen varied between 3% and 200%. The cell-specific growth rate and final cell yield was significantly lower under hyperoxic conditions (200% DO). However, there was no significant difference in growth rates at other oxygen levels compared to control cultures run under a normoxic condition (50% DO). The specific productivity of EPO was significantly lower at a DO set-point of 3% and 200% but maintained a consistently high value between 10% to 100% DO. The EPO produced under all conditions as analyzed by two-dimensional electrophoresis showed a molecular weight range of 33 to 37 kDa and a low isoelectric point range of 3.5 to 5.0. This corresponds to a highly glycosylated and sialylated protein with a profile showing at least seven distinct isoforms. The glycan pattern of isolated samples of EPO was analyzed by weak anion exchange (WAX) HPLC and by normal-phase HPLC incorporating sequential digestion with exoglycosidase arrays. Assigned structures were confirmed by mass spectrometry (MALDI-MS). The most prominent glycan structures were core fucosylated tetranntenary with variable sialylation. However, significant biantennary, triantennary, and non-fucosylated glycans were also identified. Detailed analysis of these glycan structures produced under variable dissolved oxygen levels did not show consistently significant variations except for the ratio of fucosylated to non-fucosylated isoforms. Maximum core fucosylation (80%) was observed at 50% and 100% DO, whereas higher or lower DO levels resulted in reduced fucosylation. This observation of lower fucosylation at high or low DO levels is consistent with previous data reported for glycoprotein production in insect cells.

Analysis of protein interaction networks using mass spectrometry compatible techniques.

The ability to map protein-protein interactions has grown tremendously over the last few years, making it possible to envision the mapping of whole or targeted protein interaction networks and to elucidate their temporal dynamics. The use of mass spectrometry for the study of protein complexes has proven to be an invaluable tool due to its ability to unambiguously identify proteins from a variety of biological samples. Furthermore, when affinity purification is combined with mass spectrometry analysis, the identification of multimeric protein complexes is greatly facilitated. Here, we review recent developments for the analysis of protein interaction networks by mass spectrometry and discuss the integration of different bioinformatic tools for predicting, validating, and managing interaction datasets.

Proteomic analysis of ubiquitinated proteins from human MCF-7 breast cancer cells by immunoaffinity purification and mass spectrometry.

Post-translational modification of proteins via the covalent attachment of Ubiquitin (Ub) plays an important role in the regulation of protein stability and function in eukaryotic cells. In the present study, we describe a novel method for identifying ubiquitinated proteins from a complex biological sample, such as a whole cell lysate, using a combination of immunoaffinity purification and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. We have demonstrated the applicability of this approach by identifying 70 ubiquitinated proteins from the human MCF-7 breast cancer cell line after treatment with the proteasome inhibitor MG132. This method will aid the study of protein ubiquitination and may be used as a tool for the discovery of novel biomarkers that are associated with disease progression.

Strategy to design improved proteomic experiments based on statistical analyses of the chemical properties of identified peptides.

Proteomics is an emerging field that uses many types of proteomic platforms however has few standardized procedures. Deciding which platform to use to perform large-scale proteomic studies is either based on personal preference or on so-called "figures of merit" such as dynamic range, resolution, and the limit of detection; these factors are often insufficient to predict the outcome of the experiment as the detection of peptides correlates to the chemical properties of each peptide. There is a need for a novel figure of merit that describes the overall performance of a platform based on measured output, which in proteomics is often a list of identified peptides. We report the development of such a figure of merit based on a predictive genetic algorithm. This algorithm takes into account the properties of the observed peptides such as length, hydrophobicity, and pI. Several large-scale studies that differed in sample type or platform were used to demonstrate the usefulness of the algorithm for improved experimental design. The figures that were obtained were clustered to find platforms that were biased in similar ways. Even though some platforms are different, they lead to the identification of similar peptide types and are thus redundant. The algorithm can thus be used as an exploratory tool to suggest a minimal number of complementary experiments in order to maximize experimental efficiency.

Global and site-specific detection of human integrin alpha 5 beta 1 glycosylation using tandem mass spectrometry and the StrOligo algorithm.

Glycans are oligosaccharides associated with proteins, and are known to confer specific functions and conformations on glycoproteins. As protein tridimensional structures are related to function, the study of glycans and their impact on protein folding can provide important information to the field of proteomics. The subdiscipline of glycomics (or glycoproteomics) is rapidly growing in importance as glycans in proteins have shown to be involved in protein-protein or protein-(drug, virus, antibody) interactions. Glycomics studies most often aim at identifying glycosylation sites, and thus are performed on deglycosylated proteins resulting in loss of site-specific details concerning the glycosylation. In order to obtain such details by mass spectrometry (MS), either whole glycoproteins must be digested and analyzed as mixtures of peptides and glycopeptides, or glycans must be isolated from glycopeptide fractions and analyzed as pools. This article describes parallel experiments involving both approaches, designed to take advantage of the StrOligo algorithm functionalities with the aim of characterizing glycosylation microheterogeneity on a specific site. A hybrid quadrupole-quadrupole-time-of-flight (QqTOF) instrument equipped with a matrix-assisted laser desorption/ionization (MALDI) source was used. Glycosylation of alpha 5 beta 1 subunits of human integrin was studied to test the methodology. The sample was divided in two aliquots, and glycans from the first aliquot were released enzymatically, labelled with 2-aminobenzamide, and identified using tandem mass spectrometry (MS/MS) and the StrOligo program. The other aliquot was digested with trypsin and the resulting peptides separated by reversed-phase high-performance liquid chromatography (HPLC). A specific collected fraction was then analyzed by MS before and after glycan release. These spectra allowed, by comparison, detection of a glycopeptide (several glycoforms) and elucidation of peptide sequence. Compositions of glycans present were proposed, and identification of possible glycan structures was conducted using MS/MS and StrOligo.

Application of the StrOligo algorithm for the automated structure assignment of complex N-linked glycans from glycoproteins using tandem mass spectrometry.

Oligosaccharides associated with proteins are known to give these molecules specific conformations and functions. Analysis of proteins would not be complete without studying the glycans. However, high-throughput techniques in proteomics will soon overwhelm the current capacity of methods if no automation is incorporated into glycomics. New capabilities of the StrOligo algorithm introduced for this purpose (Ethier et al., Rapid Commun. Mass Spectrom., 2002; 16: 1743) will be discussed here. Experimental tandem mass spectra were acquired to test the algorithm using a hybrid quadrupole-time-of-flight (QqTOF) instrument with a matrix-assisted laser desorption/ionization (MALDI) source. The samples were N-linked oligosaccharides from monoclonal antibody IgG, beta interferon and fetuin, detached by enzymatic deglycosylation and labeled at the reducing end. Improvements to the program were made in order to reduce the need for user intervention. StrOligo strips the spectra down to monoisotopic peaks only. The algorithm first builds a relationship tree, accounting for each observed loss of a monosaccharide moiety, and then analyzes the tree and proposes possible structures from combinations of adducts and fragment ion types. A score, which reflects agreement with experimental results, is then given to each proposed structure. The program then decides which combination is the best one and labels relevant peaks in the experimental mass spectrum using a modified nomenclature. The usefulness of the algorithm has been demonstrated by assigning structures to several glycans released from glycoproteins. The analysis was completed in less than 2 minutes for any glycan, which is a substantial improvement over manual interpretation.

Automated structural assignment of derivatized complex N-linked oligosaccharides from tandem mass spectra.

Glycoprotein function is controlled by several biological factors, one of them being the structure of carbohydrate chains (glycans) attached to specific amino acids of the protein backbone. Changes in glycan structures have been shown to modify the secondary and tertiary conformation of glycoproteins, thus their function. Powerful analytical tools are available for the characterization of sugar structures, and recently mass spectrometry (MS) has been increasingly useful for this purpose. Manual interpretation of tandem mass spectrum is possible but tedious. Automated interpretation should speed the analysis and enhance the results obtained. A new computer program for automated interpretation of tandem MS spectra of complex N-linked glycans oligosaccharides from mammals will be described. N-Linked oligosaccharides standards were derivatized with 1-phenyl-3-methyl-5-pyrazolone (PMP) and analyzed by matrix-assisted laser desorption/ionization (MALDI)-tandem MS. Simulated tandem mass spectra of other common glycans were also generated to test the algorithm. The MALDI-MS/MS spectra featured resolved isotopic distributions for the [M + H](+) and fragment ions of oligosaccharides. These isotopic distributions complicated the automated analysis of the spectra and were removed to leave only monoisotopic peaks. An algorithm was written for this purpose, yielding simplified tandem mass spectra. Another algorithm is then used to determine the structure of the oligosaccharide. A score is then given to each structure, depending on agreement with experimental results. The program successfully assigned the true structure in 24 out of the 28 cases (86%) and the true structure was among the three top scoring structures in all cases.