Can We Boost N-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine.

High confidence and reproducibility are still challenges in bottom-up mass spectrometric N-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of N-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of N-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centric, which manifests itself already in the dependence of optimal collision energy on m/z. Using classical statistical and machine learning methods, we revealed that peptide hydrophobicity, glycan and peptide masses, and the number of mobile protons also have significant and search-engine-dependent influence, as opposed to a series of other parameters we probed. We envisioned an MS/MS workflow making a smart collision energy choice based on online available features such as the hydrophobicity (described by retention time) and glycan mass (potentially available from a scout MS/MS). Our assessment suggests that this workflow can lead to a significant gain (up to 100%) in the identification confidence, particularly for low-scoring hits close to the filtering limit, which has the potential to enhance reproducibility of N-glycopeptide analyses. Data are available via MassIVE (MSV000093110).

Optimum collision energies for proteomics: The impact of ion mobility separation.

Ion mobility spectrometry (IMS) is a widespread separation technique used in various research fields. It can be coupled to liquid chromatography-mass spectrometry (LC-MS/MS) methods providing an additional separation dimension. During IMS, ions are subjected to multiple collisions with buffer gas, which may cause significant ion heating. The present project addresses this phenomenon from the bottom-up proteomics point of view. We performed LC-MS/MS measurements on a cyclic ion mobility mass spectrometer with varied collision energy (CE) settings both with and without IMS. We investigated the CE dependence of identification score, using Byonic search engine, for more than 1000 tryptic peptides from HeLa digest standard. We determined the optimal CE values-giving the highest identification score-for both setups (i.e., with and without IMS). Results show that lower CE is advantageous when IMS separation is applied, by 6.3 V on average. This value belongs to the one-cycle separation configuration, and multiple cycles may supposedly have even larger impact. The effect of IMS is also reflected in the trends of optimal CE values versus m/z functions. The parameters suggested by the manufacturer were found to be almost optimal for the setup without IMS; on the other hand, they are obviously too high with IMS. Practical consideration on setting up a mass spectrometric platform hyphenated to IMS is also presented. Furthermore, the two CID (collision induced dissociation) fragmentation cells of the instrument-located before and after the IMS cell-were also compared, and we found that CE adjustment is needed when the trap cell is used for activation instead of the transfer cell. Data have been deposited in the MassIVE repository (MSV000090944).

Diversity Matters: Optimal Collision Energies for Tandem Mass Spectrometric Analysis of a Large Set of N-Glycopeptides.

Identification and characterization of N-glycopeptides from complex samples are usually based on tandem mass spectrometric measurements. Experimental settings, especially the collision energy selection method, fundamentally influence the obtained fragmentation pattern and hence the confidence of the database search results ("score"). Using standards of naturally occurring glycoproteins, we mapped the Byonic and pGlyco search engine scores of almost 200 individual N-glycopeptides as a function of collision energy settings on a quadrupole time of flight instrument. The resulting unprecedented amount of peptide-level information on such a large and diverse set of N-glycopeptides revealed that the peptide sequence heavily influences the energy for the highest score on top of an expected general linear trend with m/z. Search engine dependence may also be noteworthy. Based on the trends, we designed an experimental method and tested it on HeLa, blood plasma, and monoclonal antibody samples. As compared to the literature, these notably lower collision energies in our workflow led to 10-50% more identified N-glycopeptides, with higher scores. We recommend a simple approach based on a small set of reference N-glycopeptides easily accessible from glycoprotein standards to ease the precise determination of optimal methods on other instruments. Data sets can be accessed via the MassIVE repository (MSV000089657 and MSV000090218).

Stepwise Collision Energy-Resolved Tandem Mass Spectrometric Experiments for the Improved Identification of Citrullinated Peptides.

The use of tandem mass spectrometry (MS/MS) is a fundamental prerequisite of reliable protein identification and quantification in mass-spectrometry-based proteomics. In bottom-up and middle-down proteomics, proteins are identified by the characteristic fragments of their constituting peptides. Post-translational modifications (PTMs) often further complicate proteome analyses. Citrullination is an increasingly studied PTM converting arginines to citrullines (Cit, X) and is implicated in several autoimmune and neurological diseases as well as different types of cancer. Confirmation of citrullination is known to be very challenging since it results in the same molecular mass change as Asn/Gln deamidation. In this study, we explore which MS/MS characteristics can be used for the reliable identification of citrullination. We synthesized several peptides incorporating Cit residues that model enzymatic cleavages of different proteins with verified or putative citrullination. Collision-induced dissociation was used to investigate the energy dependence of Byonic and Mascot scores and confirmed sequence coverage (CSC) along with the neutral loss of HNCO characteristic to citrulline side chains. We found that although the recommended values (19-45 V) for ramped collision energy settings cover the optimal Mascot, Byonic, or %CSC scores effectively, the diagnostic HNCO loss from precursors and fragments may reach their maximum intensities at lower and higher collision energies, respectively. Therefore, we suggest broadening the ramp range to ∼5-60 V to obtain more favorable identification rates for citrullinated peptides. We also found that Byonic was more successful in correctly identifying citrullinated peptides with deamidated residues than Mascot.

Collision energies on QTof and Orbitrap instruments: How to make proteomics measurements comparable?

Quadrupole time-of-flight (QTof) collision-induced dissociation (CID) and Orbitrap higher-energy collisional dissociation (HCD) are the most commonly used fragmentation techniques in mass spectrometry-based proteomics workflows. The information content of the MS/MS spectra is first and foremost determined by the applied collision energy. How can we set up the two instrument types to achieve maximum transferability? To answer this question, we compared MS/MS spectra obtained on a Bruker QTof CID and a Thermo Q-Exactive Focus Orbitrap HCD instrument as a function of collision energy using the similarity index. Results show that with a few eV lower collision energy setting on HCD (Orbitrap-specific CID) than on QTof CID, nearly identical MS/MS spectra can be obtained for leucine enkephalin pentapeptide standard, for selected +2 and +3 enolase tryptic peptides and for a large number of peptides in a HeLa protein digest. The Bruker QTof was able to produce colder ions, which may be significant to study inherently labile compounds. Further, we examined energy dependence of peptide identification confidence, as characterized by Mascot scores, on the HeLa peptides. In line with earlier QTof results, this dependence shows one or two maxima (unimodal or bimodal behavior) on Orbitrap. The fraction of bimodal peptides is lower on Orbitrap. Optimal energies as a function of m/z show a similar linear trend on both instruments, which suggests that with appropriate collision energy adjustment, matching conditions for proteomics can be achieved. Data have been deposited in the MassIVE repository (MSV000086434).

Optimal Collision Energies and Bioinformatics Tools for Efficient Bottom-up Sequence Validation of Monoclonal Antibodies.

Rigorous validation of amino acid sequence is fundamental in the characterization of original and biosimilar protein biopharmaceuticals. Widely accepted workflows are based on bottom-up mass spectrometry, and they often require multiple techniques and significant manual work. Here, we demonstrate that optimization of a set of tandem mass spectroscopy (MS/MS) collision energies and automated combination of all available information in the measurements can increase the sequence validated by one technique close to the inherent limits. We created a software (called "Serac") that consumes results of the Mascot database search engine and identifies the amino acids validated by bottom-up MS/MS experiments using the most rigorous, industrially acceptable definition of sequence coverage (we term this "confirmed sequence coverage"). The software can combine spectra at the level of amino acids or fragment ions to exploit complementarity, provides full transparency to justify validation, and reduces manual effort. With its help, we investigated collision energy dependence of confirmed sequence coverage of individual peptides and full proteins on trypsin-digested monoclonal antibody samples (rituximab and trastuzumab). We found the energy dependence to be modest, but we demonstrated the benefit of using spectra taken at multiple energies. We describe a workflow based on 2-3 LC-MS/MS runs, carefully selected collision energies, and a fragment ion level combination, which yields ∼85% confirmed sequence coverage, 25%-30% above that from a basic proteomics protocol. Further increase can mainly be expected from alternative digestion enzymes or fragmentation techniques, which can be seamlessly integrated to the processing, thereby allowing effortless validation of full sequences.

High sensitivity proteomics of prostate cancer tissue microarrays to discriminate between healthy and cancerous tissue.

Biopsies, in the form of tissue microarrays (TMAs) were studied to identify anomalies indicative of prostate cancer at the proteome level. TMAs offer a valuable source of well-characterized biological material. However, because of the small tissue sample size method development was essential to provide the sensitivity and reliability necessary for the analysis. Surface digestion of TMA cores was followed by peptide extraction and shotgun proteomics analysis. About 5 times better sensitivity was achieved by the optimized surface digestion compared to bulk digestion of the same TMA spot and it allowed the identification of over 500 proteins from individual prostate TMA cores. Label-free quantitation showed that biological variability among all samples was about 3 times larger than the technical reproducibility. We have identified 189 proteins which showed statistically significant changes (t-test p-value <.05) in abundance between healthy and cancerous tissue samples. The proteomic profile changed according to cancer grade, but did not show a correlation with cancer stage. Results of this pilot study were further evaluated using bioinformatics tools, identifying various protein pathways affected by prostate cancer progression indicating the usefulness of studying TMA cores to identify quantitative changes in tissue proteomics. SIGNIFICANCE: Detailed proteomics analysis of TMAs presents a good alternative for tissue analysis. Here we present a novel method, based on tissue surface digestion and nano-LC-MS measurements, which is capable of identifying and quantifying over 500 proteins from a 1.5 mm diameter tissue section. We compared healthy and cancerous prostate tissue samples, and tissues with various grades and stages of cancer. Tissue proteomics clearly distinguished healthy and cancerous samples, furthermore the results correlated well with cancer grade, but not with cancer stage. Over 100 proteins showed statistically significant abundance changes (t-test p-value <.05) between various groups. This was sufficient for a meaningful bioinformatics evaluation; showing e.g. increased abundance of proteins in cancer in the KEGG ribosome pathway, GO mRNA splicing via spliceosome, and chromatin assembly biological processes. The results highlight the feasibility of the developed method for future large-scale tissue proteomics studies using commercially available TMAs.

Sensitive method for glycosaminoglycan analysis of tissue sections.

A simple, isocratic HPLC method based on HILIC-WAX separation, has been developed for analyzing sulfated disaccharides of glycosaminoglycans (GAGs). To our best knowledge, this is the first successful attempt using this special phase in nano-HPLC-MS analysis. Mass spectrometry was based on negative ionization, improving both sensitivity and specificity. Detection limit for most sulfated disaccharides were approximately 1 fmol; quantitation limits 10 fmol. The method was applied for glycosaminoglycan profiling of tissue samples, using surface digestion protocols. This novel combination provides sufficient sensitivity for GAG disaccharide analysis, which was first performed using prostate cancer tissue microarrays. Preliminary results show that GAG analysis may be useful for identifying cancer related changes in small amounts of tissue samples (ca. 10 µg).

Stereocontrol in Diphenylprolinol Silyl Ether Catalyzed Michael Additions: Steric Shielding or Curtin-Hammett Scenario?

The enantioselectivity of amine-catalyzed reactions of aldehydes with electrophiles is often explained by simple steric arguments emphasizing the role of the bulky group of the catalyst that prevents the approach of the electrophile from the more hindered side. This standard steric shielding model has recently been challenged by the discovery of stable downstream intermediates, which appear to be involved in the rate-determining step of the catalytic cycle. The alternative model, referred to as the Curtin-Hammett scenario of stereocontrol, assumes that the enantioselectivity is related to the stability and reactivity of downstream intermediates. In our present computational study, we examine the two key processes of the catalytic Michael reaction between propanal and ß-nitrostyrene that are relevant to the proposed stereoselectivity models, namely the C-C bond formation and the protonation steps. The free energy profiles obtained for the pathways leading to the enantiomeric products suggest that the rate- and stereodetermining steps are not identical as implied by the previous models. The stereoselectivity can be primarily controlled by C-C bond formation even though the reaction rate is dictated by the protonation step. This kinetic scheme is consistent with all observations of experimental mechanistic studies including those of mass spectrometric back reaction screening experiments, which reveal a mismatch between the stereoselectivity of the back and the forward reactions.

Anion binding by bambus[6]uril probed in the gas phase and in solution.

Electrospray ionization mass spectrometry (ESI-MS) is used to probe the binding of small anions to the macrocycle of bambus[6]uril. For the halide ions, the experimental patterns suggest F(-) < Cl(-) < Br(-) < I(-), which is consistent with the order of anion binding found in the condensed phase. Parallel equilibrium studies in the condensed phase establish the association constants of halide anions and bambus[6]uril in mixed solvents. A detailed analysis of the mass spectrometric data is used to shed light on the correlations between the binding constants in the condensed phase and the ion abundances observed using ESI-MS. From the analysis it becomes apparent that ESI-MS can indeed represent the situation in solution to some extent, but the sampling in the gas-phase experiment is not 1:1 compared to that in solution.

Microhydration of the magnesium(II) acetate cation in the gas phase.

Electrospray ionization of aqueous solutions of magnesium(II) acetate leads to microhydrated magnesium acetate cations of the type [(CH(3)COO)(2m-1)Mg(m)(H(2)O)(n)](+) with m = 1-4 and n = 0-4, which are characterized by mass spectrometry and, for the cluster with three water molecules, also by infrared multiphoton dissociation spectroscopy. Density functional theory is used to determine the energies of microhydration for the mononuclear species [(CH(3)COO)Mg(H(2)O)(n)](+) with n = 0-6 and the associated changes in molecular structure. While bidentate coordination of the acetato ligand is generally preferred, at higher values of n, a switch to a monodentate coordination becomes energetically competitive.