OptiMS: An Accessible Program for Automating Mass Spectrometry Parameter Optimization and Configuration

Mass spectrometers have an enormous number of user-changeable parameters that drastically affect the observed mass spectrum. Using optimal parameters can significantly improve mass spectrometric data by increasing signal stability and signal-to-noise ratio, which decreases the limit of detection, thus revealing previously unobservable species. However, ascertaining optimal parameters is time-consuming, tedious, and made further challenging by the fact that parameters can act dependently on each other. Consequently, suboptimal parameters are frequently used during characterization, reducing the quality of results. OptiMS, an open-source, cross-platform program, was developed to simplify, accelerate, and more accurately determine optimal mass spectrometer parameters for a given system. It addresses common difficulties associated with existing software such as slow performance, high costs, and limited functionality. OptiMS efficacy was demonstrated through its application to multiple systems, quickly and successfully optimizing instrument parameters unassisted to maximize a user-defined metric, such as the intensity of a particular analyte. Additionally, among other features, OptiMS allows running of a sequence of predefined parameter configurations, reducing the workload of users wishing to obtain mass spectra under multiple sets of conditions.

Insight on physicochemical properties governing peptide MS1 response in HPLC-ESI-MS/MS: A deep learning approach

Accurate and absolute quantification of peptides in complex mixtures using quantitative mass spectrometry (MS)-based methods requires foreground knowledge and isotopically labeled standards, thereby increasing analytical expenses, time consumption, and labor, thus limiting the number of peptides that can be accurately quantified. This originates from differential ionization efficiency between peptides and thus, understanding the physicochemical properties that influence the ionization and response in MS analysis is essential for developing less restrictive label-free quantitative methods. Here, we used equimolar peptide pool repository data to develop a deep learning model capable of identifying amino acids influencing the MS1 response. By using an encoder-decoder with an attention mechanism and correlating attention weights with amino acid physicochemical properties, we obtain insight on properties governing the peptide-level MS1 response within the datasets. While the problem cannot be described by one single set of amino acids and properties, distinct patterns were reproducibly obtained. Properties are grouped in three main categories related to peptide hydrophobicity, charge, and structural propensities. Moreover, our model can predict MS1 intensity output under defined conditions based solely on peptide sequence input. Using a refined training dataset, the model predicted log-transformed peptide MS1 intensities with an average error of 9.7 ± 0.5% based on 5-fold cross validation, and outperformed random forest and ridge regression models on both log-transformed and real scale data. This work demonstrates how deep learning can facilitate identification of physicochemical properties influencing peptide MS1 responses, but also illustrates how sequence-based response prediction and label-free peptide-level quantification may impact future workflows within quantitative proteomics.

Formation of Gaseous Peptide Ions from Electrospray Droplets: Competition between the Ion Evaporation Mechanism and Charged Residue Mechanism

The transfer of peptide ions from solution into the gas phase by electrospray ionization (ESI) is an integral component of mass spectrometry (MS)-based proteomics. The mechanisms whereby gaseous peptide ions are released from charged ESI nanodroplets remain unclear. This is in contrast to intact protein ESI, which has been the focus of detailed investigations using molecular dynamics (MD) simulations and other methods. Under acidic liquid chromatography/MS conditions, many peptides carry a solution charge of 3+ or 2+. Because of this pre-existing charge and their relatively small size, prevailing views suggest that peptides follow the ion evaporation mechanism (IEM). The IEM entails analyte ejection from ESI droplets, driven by electrostatic repulsion between the analyte and droplet. Surprisingly, recent peptide MD investigations reported a different behavior, that is, the release of peptide ions via droplet evaporation to dryness which represents the hallmark of the charged residue mechanism (CRM). Here, we resolved this conundrum by performing MD simulations on a common model peptide (bradykinin) in Rayleigh-charged aqueous droplets. The primary focus was on pH 2 conditions (bradykinin solution charge = 3+), but we also verified that our MD strategy captured pH-dependent charge state shifts seen in ESI-MS experiments. In agreement with earlier simulations, we found that droplets with initial radii of 1.5-3 nm predominantly release peptide ions via the CRM. In contrast, somewhat larger radii (4-5 nm) favor IEM behavior. It appears that these are the first MD data to unequivocally demonstrate the viability of peptide IEM events. Electrostatic arguments can account for the observed droplet size dependence. In summary, both CRM and IEM can be operative in peptide ESI-MS. The prevalence of one over the other mechanism depends on the droplet size distribution in the ESI plume.

Protein-Small Molecule Interactions in Native Mass Spectrometry

Small molecule drug discovery has been propelled by the continual development of novel scientific methodologies to occasion therapeutic advances. Although established biophysical methods can be used to obtain information regarding the molecular mechanisms underlying drug action, these approaches are often inefficient, low throughput, and ineffective in the analysis of heterogeneous systems including dynamic oligomeric assemblies and proteins that have undergone extensive post-translational modification. Native mass spectrometry can be used to probe protein-small molecule interactions with unprecedented speed and sensitivity, providing unique insights into polydisperse biomolecular systems that are commonly encountered during the drug discovery process. In this review, we describe potential and proven applications of native MS in the study of interactions between small, drug-like molecules and proteins, including large multiprotein complexes and membrane proteins. Approaches to quantify the thermodynamic and kinetic properties of ligand binding are discussed, alongside a summary of gas-phase ion activation techniques that have been used to interrogate the structure of protein-small molecule complexes. We additionally highlight some of the key areas in modern drug design for which native mass spectrometry has elicited significant advances. Future developments and applications of native mass spectrometry in drug discovery workflows are identified, including potential pathways toward studying protein-small molecule interactions on a whole-proteome scale.

Protons Are Fast and Smart; Proteins Are Slow and Dumb: On the Relationship of Electrospray Ionization Charge States and Conformations

We present simple considerations of how differences in time scales of motions of protons, the lightest and fastest chemical moiety, and the much longer time scales associated with the dynamics of proteins, among the heaviest and slowest analytes, may allow many protein conformations from solution to be kinetically trapped during the process of electrospraying protein solutions into the gas phase. In solution, the quantum nature of protons leads them to change locations by tunneling, an instantaneous process; moreover, the Grotthuss mechanism suggests that these small particles can respond nearly instantaneously to the dynamic motions of proteins that occur on much longer time scales. A conformational change is accompanied by favorable or unfavorable variations in the free energy of the system, providing the impetus for solvent ↔ protein proton exchange. Thus, as thermal distributions of protein conformations interconvert, protonation states rapidly respond, as specific acidic and basic sites are exposed or protected. In the vacuum of the mass spectrometer, protons become immobilized in locations that are specific to the protein conformations from which they were incorporated. In this way, conformational states from solution are preserved upon electrospraying them into the gas phase. These ideas are consistent with the exquisite sensitivity of electrospray mass spectra to small changes of the local environment that alter protein structure in solution. We might remember this approximation for the protonation of proteins in solution with the colloquial expression-protons are fast and smart; proteins are slow and dumb.

Ion optics simulation of an ion beam setup coupled to an electrospray ionization source, strengths, and limitations

A unified approach to achieve a start-to-end ion optics simulation of an ion beam apparatus coupled to an electrospray ionization source is presented. We demonstrate that simulations enable reliable information on the behavior and operation of the apparatus to be obtained, but due to the collisions with the buffer gas in the initial stages of the setup, the results concerning the kinetic energy of the ion beam must be treated with care.

Olefinic reagents tested for peptide derivatization with switchable properties: Stable upon collision induced dissociation and cleavable by in-source Paternò-Büchi reactions

This contribution is part of our ongoing efforts to develop innovative cross-linking (XL) reagents and protocols for facilitated peptide mixture analysis and efficient assignment of cross-linked peptide products. In this report, we combine in-source Paternò-Büchi (PB) photo-chemistry with a tandem mass spectrometry approach to selectively address the fragmentation of a tailor-made cross-linking reagent. The PB photochemistry, so far exclusively used for the identification of unsaturation sites in lipids and in lipidomics, is now introduced to the field of chemical cross-linking. Based on trans-3-hexenedioic acid, an olefinic homo bifunctional amine reactive XL reagent was designed and synthesized for this proof-of-principle study. Condensation products of the olefinic reagent with a set of exemplary peptides are used to test the feasibility of the concept. Benzophenone is photochemically reacted in the nano-electrospray ion source and forms oxetane PB reaction products. Subsequent CID-MS triggered retro-PB reaction of the respective isobaric oxetane molecular ions and delivers reliably and predictably two sets of characteristic fragment ions of the cross-linker. Based on these signature ion sets, a straightforward identification of covalently interconnected peptides in complex digests is proposed. Furthermore, CID-MSⁿ experiments of the retro-PB reaction products deliver peptide backbone characteristic fragment ions. Additionally, the olefinic XL reagents exhibit a pronounced robustness upon CID-activation, without previous UV-excitation. These experiments document that a complete backbone fragmentation is possible, while the linker-moiety remains intact. This feature renders the new olefinic linkers switchable between a stable, noncleavable cross-linking mode and an in-source PB cleavable mode.

Influence of the amino acid composition on the ionization efficiencies of small peptides

Electrospray ionization is widely used to generate gas phase ions from a variety of molecules ranging from small ions to large proteins, while the ionization mechanism is claimed to depend on the size of the molecule. For small molecules, the ionization efficiency, the amount of gas phase ions produced in the electrospray process, depends on the properties of the compound. Here, we show that the amino acid composition also influences the ionization efficiency of the oligopeptide. Additionally, we show that the ionization efficiencies of oligopeptides consisting of more than five amino acid residues are very similar to one another, and assuming equal ionization efficiencies is feasible. Therefore, accurate ionization efficiency predictions are needed mainly for small oligopeptides. For these oligopeptides, the amino acid composition can be used to estimate the ionization efficiency in an easy to use manner.

A systematic approach toward comparing electrospray ionization efficiencies of derivatized and non-derivatized amino acids and biogenic amines

Ionization efficiency (IE) in mass spectrometry (MS) has been studied for many different compounds, and different IE scales have been constructed in order to quantitatively characterize IE. In the case of MS, derivatization has been used to increase the sensitivity of the method and to lower the limits of detection. However, the influence of derivatization on IE across different compounds and different derivatization reagents has not been thoroughly researched, so that practitioners do not have information on the IE-enhancing abilities of different derivatization reagents. Moreover, measuring IE via direct infusion of compounds cannot be considered fully adequate. Since derivatized compounds are in complex mixtures, a chromatographic method is needed to separate these compounds to minimize potential matrix effects. In this work, an IE measurement system with a chromatographic column was developed for mainly amino acids and some biogenic amines. IE measurements with liquid chromatography electrospray ionization mass spectrometry (LC/ESI/MS) were carried out, and IE scales were constructed with a calibration curve for compounds with and without derivatization reagent diethyl ethoxymethylenemalonate. Additionally, eluent composition effects on ionization were investigated. Results showed that derivatization increases IE for most of the compounds (by average 0.9 and up to 2-2.5 logIE units) and derivatized compounds have more similar logIE values than without derivatization. Mobile phase composition effects on ionization efficiencies were negligible. It was also noted that the use of chromatographic separation instead of flow injection mode slightly increases IE. In this work, for the first time, IE enhancement of derivatization reagents was quantified under real LC/ESI/MS conditions and obtained logIE values of derivatized compounds were linked with the existing scale.

Opportunities and challenges for nutritional proteomics in cancer prevention

Knowledge gaps persist about the efficacy of cancer prevention strategies based on dietary food components. Adaptations to nutrient supply are executed through tuning of multiple protein networks that include transcription factors, histones, modifying enzymes, translation factors, membrane and nuclear receptors, and secreted proteins. However, the simultaneous quantitative and qualitative measurement of all proteins that regulate cancer processes is not practical using traditional protein methodologies. Proteomics offers an attractive opportunity to fill this knowledge gap and unravel the effects of dietary components on protein networks that impinge on cancer. The articles presented in this supplement are from talks proffered in the "Nutrition Proteomics and Cancer Prevention" session at the American Institute for Cancer Research Annual Research Conference on Food, Nutrition, Physical Activity and Cancer held in Washington, DC on October 21 and 22, 2010. Recent advances in MS technologies suggest that studies in nutrition and cancer prevention may benefit from the adoption of proteomic tools to elucidate the impact on biological processes that govern the transition from normal to malignant phenotype; to identify protein changes that determine both positive and negative responses to food components; to assess how protein networks mediate dose-, time-, and tissue-dependent responses to food components; and, finally, for predicting responders and nonresponders. However, both the limited accessibility to proteomic technologies and research funding appear to be hampering the routine adoption of proteomic tools in nutrition and cancer prevention research.