Craig D. Wenger

Human embryonic stem cell phosphoproteome revealed by electron transfer dissociation tandem mass spectrometry.

Protein phosphorylation is central to the understanding of cellular signaling, and cellular signaling is suggested to play a major role in the regulation of human embryonic stem (ES) cell pluripotency. Here, we describe the use of conventional tandem mass spectrometry-based sequencing technology—collision-activated dissociation (CAD)—and the more recently developed method electron transfer dissociation (ETD) to characterize the human ES cell phosphoproteome. In total, these experiments resulted in the identification of 11,995 unique phosphopeptides, corresponding to 10,844 nonredundant phosphorylation sites, at a 1% false discovery rate (FDR). Among these phosphorylation sites are 5 localized to 2 pluripotency critical transcription factors—OCT4 and SOX2. From these experiments, we conclude that ETD identifies a larger number of unique phosphopeptides than CAD (8,087 to 3,868), more frequently localizes the phosphorylation site to a specific residue (49.8% compared with 29.6%), and sequences whole classes of phosphopeptides previously unobserved.

Phosphoproteomics for the masses.

Protein phosphorylation serves as a primary mechanism of signal transduction in the cells of biological organisms. Technical advancements over the last several years in mass spectrometry now allow for the large-scale identification and quantitation of in vivo phosphorylation at unprecedented levels. These developments have occurred in the areas of sample preparation, instrumentation, quantitative methodology, and informatics so that today, 10 000-20 000 phosphorylation sites can be identified and quantified within a few weeks. With the rapid development and widespread availability of such data, its translation into biological insight and knowledge is a current obstacle. Here we present an overview of how this technology came to be and is currently applied, as well as future challenges for the field.

A Proteomics Search Algorithm Specifically Designed for High- Resolution Tandem Mass Spectra

The acquisition of high-resolution tandem mass spectra (MS/MS) is becoming more prevalent in proteomics, but most researchers employ peptide identification algorithms that were designed prior to this development. Here, we demonstrate new software, Morpheus, designed specifically for high-mass accuracy data, based on a simple score that is little more than the number of matching products. For a diverse collection of data sets from a variety of organisms (E. coli, yeast, human) acquired on a variety of instruments (quadrupole-time-of-flight, ion trap-orbitrap, and quadrupole-orbitrap) in different laboratories, Morpheus gives more spectrum, peptide, and protein identifications at a 1% false discovery rate (FDR) than Mascot, Open Mass Spectrometry Search Algorithm (OMSSA), and Sequest. Additionally, Morpheus is 1.5 to 4.6 times faster, depending on the data set, than the next fastest algorithm, OMSSA. Morpheus was developed in C# .NET and is available free and open source under a permissive license.

Post-acquisition ETD spectral processing for increased peptide identifications

Tandem mass spectra (MS/MS) produced using electron transfer dissociation (ETD) differ from those derived from collision-activated dissociation (CAD) in several important ways. Foremost, the predominant fragment ion series are different: c- and z·-type ions are favored in ETD spectra while b- and y-type ions comprise the bulk of the fragments in CAD spectra. Additionally, ETD spectra possess charge-reduced precursors and unique neutral losses. Most database search algorithms were designed to analyze CAD spectra, and have only recently been adapted to accommodate c- and z·-type ions; therefore, inclusion of these additional spectral features can hinder identification, leading to lower confidence scores and decreased sensitivity. Because of this, it is important to pre-process spectral data before submission to a database search to remove those features that cause complications. Here, we demonstrate the effects of removing these features on the number of unique peptide identifications at a 1% false discovery rate (FDR) using the open mass spectrometry search algorithm (OMSSA). When analyzing two biologic replicates of a yeast protein extract in three total analyses, the number of unique identifications with a ∼1% FDR increased from 4611 to 5931 upon spectral pre-processing—an increase of ∼28. 6%. We outline the most effective pre-processing methods, and provide free software containing these algorithms.

Amine-reactive neutron-encoded labels for highly plexed proteomic quantitation.

We describe a novel amine-reactive chemical label that exploits differential neutron-binding energy between 13C and 15N isotopes. These neutron-encoded (NeuCode) chemical labels enable up to 12-plex MS1-based protein quantification. Each structurally identical, but isotopically unique, tag is encoded with a 12.6-mDa mass difference—relative to its nearest neighbor—so that peptides bearing these NeuCode signatures do not increase spectral complexity and are detected only upon analysis with very high mass-resolving powers. We demonstrate that the method provides quantitative performance that is comparable to both metabolic labeling and isobaric tagging while combining the benefits of both strategies. Finally, we employ the tags to characterize the proteome of Saccharomyces cerevisiae during the diauxic shift, a metabolic transition from fermentation to aerobic respiration.

RNA–protein analysis using a conditional CRISPR nuclease

RNA-binding proteins control the fate and function of the transcriptome in all cells. Here we present technology for isolating RNA–protein partners efficiently and accurately using an engineered clustered regularly interspaced short palindromic repeats (CRISPR) endoribonuclease. An inactive version of the Csy4 nuclease binds irreversibly to transcripts engineered with a 16-nt hairpin sequence at their 5′ ends. Once immobilized by Csy4 on a solid support, contaminating proteins and other molecules can be removed by extensive washing. Upon addition of imidazole, Csy4 is activated to cleave the RNA, removing the hairpin tag and releasing the native transcript along with its specifically bound protein partners. This conditional Csy4 enzyme enables recovery of specific RNA-binding partners with minimal false-positive contamination. We use this method, coupled with quantitative MS, to identify cell type-specific human pre-microRNA-binding proteins. We also show that this technology is suitable for analyzing diverse size transcripts, and that it is suitable for adaptation to a high-throughput discovery format.

Instant spectral assignment for advanced decision tree-driven mass spectrometry

We have developed and implemented a sequence identification algorithm (inSeq) that processes tandem mass spectra in real-time using the mass spectrometer’s (MS) onboard processors. The inSeq algorithm relies on accurate mass tandem MS data for swift spectral matching with high accuracy. The instant spectral processing technology takes ∼16 ms to execute and provides information to enable autonomous, real-time decision making by the MS system. Using inSeq and its advanced decision tree logic, we demonstrate (i) real-time prediction of peptide elution windows en masse (∼3 min width, 3,000 targets), (ii) significant improvement of quantitative precision and accuracy (~3x boost in detected protein differences), and (iii) boosted rates of posttranslation modification site localization (90% agreement in real-time vs. offline localization rate and an approximate 25% gain in localized sites). The decision tree logic enabled by inSeq promises to circumvent problems with the conventional data-dependent acquisition paradigm and provides a direct route to streamlined and expedient targeted protein analysis.

Characterizing Peptide Neutral Losses Induced by Negative Electron-Transfer Dissociation (NETD)

We implemented negative electron-transfer dissociation (NETD) on a hybrid ion trap/Orbitrap mass spectrometer to conduct ion/ion reactions using peptide anions and radical reagent cations. In addition to sequence-informative ladders of a•- and x-type fragment ions, NETD generated intense neutral loss peaks corresponding to the entire or partial side-chain cleavage from amino acids constituting a given peptide. Thus, a critical step towards the characterization of this recently introduced fragmentation technique is a systematic study of synthetic peptides to identify common neutral losses and preferential fragmentation pathways. Examining 46 synthetic peptides with high mass accuracy and high resolution analysis permitted facile determination of the chemical composition of each neutral loss. We identified 19 unique neutral losses from 14 amino acids and three modified amino acids, and assessed the specificity and sensitivity of each neutral loss using a database of 1542 confidently identified peptides generated from NETD shotgun experiments employing high-pH separations and negative electrospray ionization. As residue-specific neutral losses indicate the presence of certain amino acids, we determined that many neutral losses have potential diagnostic utility. We envision this catalogue of neutral losses being incorporated into database search algorithms to improve peptide identification specificity and to further advance characterization of the acidic proteome.

Global Identification of Protein Post-translational Modifications in a Single-Pass Database Search.

Bottom-up proteomics database search algorithms used for peptide identification cannot comprehensively identify post-translational modifications (PTMs) in a single-pass because of high false discovery rates (FDRs). A new approach to database searching enables global PTM (G-PTM) identification by exclusively looking for curated PTMs, thereby avoiding the FDR penalty experienced during conventional variable modification searches. We identified over 2200 unique, high-confidence modified peptides comprising 26 different PTM types in a single-pass database search.

Global Post-Translational Modification Discovery

A new global post-translational modification (PTM) discovery strategy, G-PTM-D, is described. A proteomics database containing UniProt-curated PTM information is supplemented with potential new modification types and sites discovered from a first-round search of mass spectrometry data with ultrawide precursor mass tolerance. A second-round search employing the supplemented database conducted with standard narrow mass tolerances yields deep coverage and a rich variety of peptide modifications with high confidence in complex unenriched samples. The G-PTM-D strategy represents a major advance to the previously reported G-PTM strategy and provides a powerful new capability to the proteomics research community.