Stephen W. Holman

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.

Global absolute quantification of a proteome: Challenges in the deployment of a QconCAT strategy

In this paper, we discuss the challenge of large‐scale quantification of a proteome, referring to our programme that aims to define the absolute quantity, in copies per cell, of at least 4000 proteins in the yeast Saccharomyces cerevisiae. We have based our strategy on the well‐established method of stable isotope dilution, generating isotopically labelled peptides using QconCAT technology, in which artificial genes, encoding concatenations of tryptic fragments as surrogate quantification standards, are designed, synthesised de novo and expressed in bacteria using stable isotopically enriched media. A known quantity of QconCAT is then co‐digested with analyte proteins and the heavy:light isotopologues are analysed by mass spectrometry to yield absolute quantification. This workflow brings issues of optimal selection of quantotypic peptides, their assembly into QconCATs, expression, purification and deployment.

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.

Quantitative analysis of chaperone network throughput in budding yeast.

The network of molecular chaperones mediates the folding and translocation of the many proteins encoded in the genome of eukaryotic organisms, as well as a response to stress. It has been particularly well characterised in the budding yeast, Saccharomyces cerevisiae, where 63 known chaperones have been annotated and recent affinity purification and MS/MS experiments have helped characterise the attendant network of chaperone targets to a high degree. In this study, we apply our QconCAT methodology to directly quantify the set of yeast chaperones in absolute terms (copies per cell) via SRM MS. Firstly, we compare these to existing quantitative estimates of these yeast proteins, highlighting differences between approaches. Secondly, we cast the results into the context of the chaperone target network and show a distinct relationship between abundance of individual chaperones and their targets. This allows us to characterise the ‘throughput’ of protein molecules passing through individual chaperones and their groups on a proteome‐wide scale in an unstressed model eukaryote for the first time. The results demonstrate specialisations of the chaperone classes, which display different overall workloads, efficiencies and preference for the sub‐cellular localisation of their targets. The novel integration of the interactome data with quantification supports re‐estimates of the level of protein throughout going through molecular chaperones. Additionally, although chaperones target fewer than 40% of annotated proteins we show that they mediate the folding of the majority of protein molecules (∼62% of the total protein flux in the cell), highlighting their importance.

Absolute protein quantification of the yeast chaperome under conditions of heat shock

Chaperones are fundamental to regulating the heat shock response, mediating protein recovery from thermal‐induced misfolding and aggregation. Using the QconCAT strategy and selected reaction monitoring (SRM) for absolute protein quantification, we have determined copy per cell values for 49 key chaperones in Saccharomyces cerevisiae under conditions of normal growth and heat shock. This work extends a previous chemostat quantification study by including up to five Q‐peptides per protein to improve confidence in protein quantification. In contrast to the global proteome profile of S. cerevisiae in response to heat shock, which remains largely unchanged as determined by label‐free quantification, many of the chaperones are upregulated with an average two‐fold increase in protein abundance. Interestingly, eight of the significantly upregulated chaperones are direct gene targets of heat shock transcription factor‐1. By performing absolute quantification of chaperones under heat stress for the first time, we were able to evaluate the individual protein‐level response. Furthermore, this SRM data was used to calibrate label‐free quantification values for the proteome in absolute terms, thus improving relative quantification between the two conditions. This study significantly enhances the largely transcriptomic data available in the field and illustrates a more nuanced response at the protein level.

RePLiCal: A QconCAT Protein for Retention Time Standardization in Proteomics Studies

This study introduces a new reversed-phase liquid chromatography retention time (RT) standard, RePLiCal (Reversed-phase liquid chromatography calibrant), produced using QconCAT technology. The synthetic protein contains 27 lysine-terminating calibrant peptides, meaning that the same complement of standards can be generated using either Lys-C or trypsin-based digestion protocols. RePLiCal was designed such that each constituent peptide is unique with respect to all eukaryotic proteomes, thereby enabling integration into a wide range of proteomic analyses. RePLiCal has been benchmarked against three commercially available peptide RT standard kits and outperforms all in terms of LC gradient coverage. RePLiCal also provides a higher number of calibrant points for chromatographic retention time standardization and normalization. The standard provides stable RTs over long analysis times and can be readily transferred between different LC gradients and nUHPLC instruments. Moreover, RePLiCal can be used to predict RTs for other peptides in a timely manner. Furthermore, it is shown that RePLiCal can be used effectively to evaluate trapping column performance for nUHPLC instruments using trap-elute configurations, to optimize gradients to maximize peptide and protein identification rates, and to recalibrate the m/z scale of mass spectrometry data post-acquisition.

Peptide Scrambling During Collision-Induced Dissociation is Influenced by N-terminal Residue Basicity

Abstract‘Bottom up’ proteomic studies typically use tandem mass spectrometry data to infer peptide ion sequence, enabling identification of the protein whence they derive. The majority of such studies employ collision-induced dissociation (CID) to induce fragmentation of the peptide structure giving diagnostic b-, y-, and a- ions. Recently, rearrangement processes that result in scrambling of the original peptide sequence during CID have been reported for these ions. Such processes have the potential to adversely affect ion accounting (and thus scores from automated search algorithms) in tandem mass spectra, and in extreme cases could lead to false peptide identification. Here, analysis of peptide species produced by Lys-N proteolysis of standard proteins is performed and sequences that exhibit such rearrangement processes identified. The effect of increasing the gas-phase basicity of the N-terminal lysine residue through derivatization to homoarginine toward such sequence scrambling is then assessed. The presence of a highly basic homoarginine (or arginine) residue at the N-terminus is found to disfavor/inhibit sequence scrambling with a coincident increase in the formation of b(n-1)+H2O product ions. Finally, further analysis of a sequence produced by Lys-C proteolysis provides evidence toward a potential mechanism for the apparent inhibition of sequence scrambling during resonance excitation CID. Graphical Abstractᅟ

A rapid methodology for the characterization of dialkyl tertiary amine-N-oxide metabolites using structurally dependent dissociation pathways and reconstructed ion current chromatograms.

A high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (HPLC-ESI-MS/MS) approach to the characterization of dialkyl tertiary amine-N-oxides is presented. The methodology is based upon forming reconstructed ion current chromatograms (RICCs) of m/z values of product ions known to form through diagnostic losses from dialkyl tertiary amine-N-oxides. The diagnostic losses of N,N-dimethylhydroxylamine and N,N-diethylhydroxylamine were identified through the analysis of a structurally diverse library of compounds by ESI-low-energy collision-induced dissociation (CID)-MS/MS using quadrupole ion trap-mass spectrometry (QIT-MS) and quadrupole time-of-flight-mass spectrometry (QqTOF-MS). The library consisted of dialkyl tertiary amine-containing commercially available pharmaceuticals, along with a number of model, synthetic N-oxides. The loss of the nitrogen-containing group was observed in 89% of the low-energy CID product ion spectra acquired using various collision energies. Further, the resultant product ions, formed through the loss of the nitrogen-containing group, were shown to be unstable because of the observation of second-generation dissociation. These observations regarding gas-phase ion chemistry could be useful to developers of in silico programs for fragmentation prediction by allowing the creation of improved algorithms and models for predicting dissociation. Using the information derived from the library analysis, the characterization methodology was developed and demonstrated using tetracaine. The approach is rapid, MS/MS platform independent, utilizes existing technology, and could be automated. Further, it is definitive and overcomes the limitations of other tools for N-oxide identification by localizing the site of oxidation. Thus, it provides a useful addition to the existing approaches for metabolite identification.

Representation of selected-reaction monitoring data in the mzQuantML data standard

The mzQuantML data standard was designed to capture the output of quantitative software in proteomics, to support submissions to public repositories, development of visualization software and pipeline/modular approaches. The standard is designed around a common core that can be extended to support particular types of technique through the release of semantic rules that are checked by validation software. The first release of mzQuantML supported four quantitative proteomics techniques via four sets of semantic rules: (i) intensity‐based (MS1) label free, (ii) MS1 label‐based (such as SILAC or N15), (iii) MS2 tag‐based (iTRAQ or tandem mass tags), and (iv) spectral counting. We present an update to mzQuantML for supporting SRM techniques. The update includes representing the quantitative measurements, and associated meta‐data, for SRM transitions, the mechanism for inferring peptide‐level or protein‐level quantitative values, and support for both label‐based or label‐free SRM protocols, through the creation of semantic rules and controlled vocabulary terms. We have updated the specification document for mzQuantML (version 1.0.1) and the mzQuantML validator to ensure that consistent files are produced by different exporters. We also report the capabilities for production of mzQuantML files from popular SRM software packages, such as Skyline and Anubis.

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.