Claire E. Eyers

The power of ion mobility-mass spectrometry for structural characterization and the study of conformational dynamics

Mass spectrometry is a vital tool for molecular characterization, and the allied technique of ion mobility is enhancing many areas of (bio)chemical analysis. Strong synergy arises between these two techniques because of their ability to ascertain complementary information about gas-phase ions. Ion mobility separates ions (from small molecules up to megadalton protein complexes) based on their differential mobility through a buffer gas. Ion mobility-mass spectrometry (IM-MS) can thus act as a tool to separate complex mixtures, to resolve ions that may be indistinguishable by mass spectrometry alone, or to determine structural information (for example rotationally averaged cross-sectional area), complementary to more traditional structural approaches. Finally, IM-MS can be used to gain insights into the conformational dynamics of a system, offering a unique means of characterizing flexibility and folding mechanisms. This Review critically describes how IM-MS has been used to enhance various areas of chemical and biophysical analysis.

Discrimination of epimeric glycans and glycopeptides using IM-MS and its potential for carbohydrate sequencing

Mass spectrometry is the primary analytical technique used to characterize the complex oligosaccharides that decorate cell surfaces. Monosaccharide building blocks are often simple epimers, which when combined produce diastereomeric glycoconjugates indistinguishable by mass spectrometry. Structure elucidation frequently relies on assumptions that biosynthetic pathways are highly conserved. Here, we show that biosynthetic enzymes can display unexpected promiscuity, with human glycosyltransferase pp-α-GanT2 able to utilize both uridine diphosphate N-acetylglucosamine and uridine diphosphate N-acetylgalactosamine, leading to the synthesis of epimeric glycopeptides in vitro. Ion-mobility mass spectrometry (IM-MS) was used to separate these structures and, significantly, enabled characterization of the attached glycan based on the drift times of the monosaccharide product ions generated following collision-induced dissociation. Finally, ion-mobility mass spectrometry following fragmentation was used to determine the nature of both the reducing and non-reducing glycans of a series of epimeric disaccharides and the branched pentasaccharide Man3 glycan, demonstrating that this technique may prove useful for the sequencing of complex oligosaccharides. Identification of glycosylation patterns is complicated by the lack of sensitive analytical techniques that can distinguish between epimeric carbohydrates. It has now been shown that ion-mobility tandem mass spectrometry of ions derived from glycopeptides and oligosaccharides enables glycan stereochemistry to be determined, highlighting the potential of this technique for sequencing complex carbohydrates on cell surfaces.

CONSeQuence: Prediction of Reference Peptides for Absolute Quantitative Proteomics Using Consensus Machine Learning Approaches

Mass spectrometric based methods for absolute quantification of proteins, such as QconCAT, rely on internal standards of stable-isotope labeled reference peptides, or “Q-peptides,” to act as surrogates. Key to the success of this and related methods for absolute protein quantification (such as AQUA) is selection of the Q-peptide. Here we describe a novel method, CONSeQuence (consensus predictor for Q-peptide sequence), based on four different machine learning approaches for Q-peptide selection. CONSeQuence demonstrates improved performance over existing methods for optimal Q-peptide selection in the absence of prior experimental information, as validated using two independent test sets derived from yeast. Furthermore, we examine the physicochemical parameters associated with good peptide surrogates, and demonstrate that in addition to charge and hydrophobicity, peptide secondary structure plays a significant role in determining peptide “detectability” in liquid chromatography-electrospray ionization experiments. We relate peptide properties to protein tertiary structure, demonstrating a counterintuitive preference for buried status for frequently detected peptides. Finally, we demonstrate the improved efficacy of the general approach by applying a predictor trained on yeast data to sets of proteotypic peptides from two additional species taken from an existing peptide identification repository.

Enzymatic reactions on immobilised substrates

This review gives an overview of enzymatic reactions that have been conducted on substrates attached to solid surfaces. Such biochemical reactions have become more important with the drive to miniaturisation and automation in chemistry, biology and medicine. Technical aspects such as choice of solid surface and analytical methods are discussed and examples of enzyme reactions that have been successful on these surfaces are provided.

Absolute Quantification of the Glycolytic Pathway in Yeast: DEPLOYMENT OF A COMPLETE QconCAT APPROACH

The availability of label-free data derived from yeast cells (based on the summed intensity of the three strongest, isoform-specific peptides) permitted a preliminary assessment of protein abundances for glycolytic proteins. Following this analysis, we demonstrate successful application of the QconCAT technology, which uses recombinant DNA techniques to generate artificial concatamers of large numbers of internal standard peptides, to the quantification of enzymes of the glycolysis pathway in the yeast Saccharomyces cerevisiae. A QconCAT of 88 kDa (59 tryptic peptides) corresponding to 27 isoenzymes was designed and built to encode two or three analyte peptides per protein, and after stable isotope labeling of the standard in vivo, protein levels were determined by LC-MS, using ultra high performance liquid chromatography-coupled mass spectrometry. We were able to determine absolute protein concentrations between 14,000 and 10 million molecules/cell. Issues such as efficiency of extraction and completeness of proteolysis are addressed, as well as generic factors such as optimal quantotypic peptide selection and expression. In addition, the same proteins were quantified by intensity-based label-free analysis, and both sets of data were compared with other quantification methods.

The N-methylated peptide SEN304 powerfully inhibits Aβ(1-42) toxicity by perturbing oligomer formation.

Oligomeric forms of β-amyloid (Aβ) have potent neurotoxic activity and are the primary cause of neuronal injury and cell death in Alzheimers disease (AD). Compounds that perturb oligomer formation or structure may therefore be therapeutic for AD. We previously reported that d-[(chGly)-(Tyr)-(chGly)-(chGly)-(mLeu)]-NH(2) (SEN304) is able to inhibit Aβ aggregation and toxicity, shown primarily by thioflavin T fluorescence and MTT (Kokkoni, N. et al. (2006) N-Methylated peptide inhibitors of β-amyloid aggregation and toxicity. Optimisation of inhibitor structure. Biochemistry 45, 9906-9918). Here we extensively characterize how SEN304 affects Aβ(1-42) aggregation and toxicity, using biophysical assays (thioflavin T, circular dichroism, SDS-PAGE, size exclusion chromatography, surface plasmon resonance, traveling wave ion mobility mass spectrometry, electron microscopy, ELISA), toxicity assays in cell culture (MTT and lactate dehydrogenase in human SH-SHY5Y cells, mouse neuronal cell death and synaptophysin) and long-term potentiation in a rat hippocampal brain slice. These data, with dose response curves, show that SEN304 is a powerful inhibitor of Aβ(1-42) toxicity, particularly effective at preventing Aβ inhibition of long-term potentiation. It can bind directly to Aβ(1-42), delay β-sheet formation and promote aggregation of toxic oligomers into a nontoxic form, with a different morphology that cannot bind thioflavin T. SEN304 appears to work by inducing aggregation, and hence removal, of Aβ oligomers. It is therefore a promising lead compound for Alzheimers disease.

Rigorous determination of the stoichiometry of protein phosphorylation using mass spectrometry.

Quantification of the stoichiometry of phosphorylation is usually achieved using a mixture of phosphatase treatment and differential isotopic labeling. Here, we introduce a new approach to the concomitant determination of absolute protein concentration and the stoichiometry of phosphorylation at predefined sites. The method exploits QconCAT to quantify levels of phosphorylated and nonphosphorylated peptide sequences in a phosphoprotein. The nonphosphorylated sequence is used to determine the absolute protein quantity and serves as a reference to calculate the extent of phosphorylation at the second peptide. Thus, the stoichiometry of phosphorylation and the absolute protein concentration can be determined accurately in a single experiment.

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies.

QCAL-a Novel Standard for Assessing Instrument Conditions for Proteome Analysis

If proteome datasets are to be collated, shared, and merged for higher level proteome analyses, there is a need for generally accepted strategies and reagents for optimization and standardization of instrument performance. At present, there is no single protein or peptide standard set that is capable of assessing instrument performance for peptide separation and analysis in this manner. To create such a standard, we have used the recently described QconCAT methodology to generate an artificial protein, QCAL. This protein, a concatenation of tryptic peptides that is expressed in E. coli, provides a stoichiometrically controlled mixture of peptides that are amenable to analysis by all commonly used instrumentation platforms for proteomics.

Eukaryotic Elongation Factor 2 Kinase Activity Is Controlled by Multiple Inputs from Oncogenic Signaling

ABSTRACT Eukaryotic elongation factor 2 kinase (eEF2K), an atypical calmodulin-dependent protein kinase, phosphorylates and inhibits eEF2, slowing down translation elongation. eEF2K contains an N-terminal catalytic domain, a C-terminal α-helical region and a linker containing several regulatory phosphorylation sites. eEF2K is expressed at high levels in certain cancers, where it may act to help cell survival, e.g., during nutrient starvation. However, it is a negative regulator of protein synthesis and thus cell growth, suggesting that cancer cells may possess mechanisms to inhibit eEF2K under good growth conditions, to allow protein synthesis to proceed. We show here that the mTORC1 pathway and the oncogenic Ras/Raf/MEK/extracellular signal-regulated kinase (ERK) pathway cooperate to restrict eEF2K activity. We identify multiple sites in eEF2K whose phosphorylation is regulated by mTORC1 and/or ERK, including new ones in the linker region. We demonstrate that certain sites are phosphorylated directly by mTOR or ERK. Our data reveal that glycogen synthase kinase 3 signaling also regulates eEF2 phosphorylation. In addition, we show that phosphorylation sites remote from the N-terminal calmodulin-binding motif regulate the phosphorylation of N-terminal sites that control CaM binding. Mutations in the former sites, which occur in cancer cells, cause the activation of eEF2K. eEF2K is thus regulated by a network of oncogenic signaling pathways.