Journal of the American Society for Mass Spectrometry最新文献

Top-down mass spectrometry (MS) enables comprehensive characterization of modified proteins and nucleic acids and, when native electrospray ionization (ESI) is used, binding site mapping of their complexes with native or therapeutic ligands. However, the high complexity of top-down MS spectra poses a serious challenge to both manual and automated data interpretation, even when the protein, RNA, or DNA sequence and the type of modification or the ligand are known. Here, we introduce FAST MS, a user-friendly software that identifies, assigns and relatively quantifies signals of molecular and fragment ions in MS and MS/MS spectra of biopolymers with known sequence and provides a toolbox for statistical analysis. FAST MS searches mass spectra for ion signals by comparing all signals in the spectrum with isotopic profiles calculated from known sequences, resulting in superior sensitivity and an increased number of assigned fragment ions compared to algorithms that rely on artificial monomer units while maintaining the false positive rate on a moderate level (<5%). FAST MS is an open-source, cross-platform software for the accurate identification, localization and relative quantification of modifications, even in complex mixtures of positional isomers of proteins, oligonucleotides, or any other user-defined linear polymer.

In this study, the formation and emission of alkali halide cluster ions in charged droplets generated by electrospray ionization (ESI) was investigated using mass spectrometry (MS). We focus on ion emission at the air–solution interface of charged droplets, distinguishing between two mechanisms: the ion evaporation model (IEM), where ions are released directly from the interface, and the charge residue model (CRM), where ions are generated after complete solvent evaporation. Using an iodide/chloride mixture, we analyzed how interfacial affinity influences the composition of the generated alkali halide cluster cations and anions. With the knowledge that iodides have much higher interfacial affinities than chlorides, a relative faction of iodide in the cluster ion enables us to distinguish between IEM and CRM. Small cluster anions and cations exclusively containing iodides are suggested to be from IEM, while the larger cluster ions containing more chlorides are expected to be from CRM. This work clarifies the distinctions between IEM and CRM in alkali halide cluster ion formation and also establishes a robust analytical approach for assessing interfacial affinities of ions using ESI-MS, which may potentially enhance our understanding of interfacial chemistry and its implications in atmospheric and analytical sciences.

Cyclic ion mobility-mass spectrometry (cIM-MS) is a powerful technique for separating and identifying isomeric mixtures of compounds. When coupled with chromatography, cIM-MS creates a multidimensional separation system, with high resolving power and peak capacity. In this study, we report the cyclic ion mobility separation and high-resolution mass spectrometry identification of four regioisomers of a Sugammadex-related impurity, abbreviated as Di-OH-SGM. Separation using multipass cyclic ion mobility was achieved by selecting the [M + 2Na]²⁺ ion, while other adducts, such as [M + Na]⁺, [M + 2H]²⁺, [M + H + Na]²⁺, and [M - 2H]^2- did not yield isomer separation. Two methods were developed for ion mobility separation of the isomers: a conventional multipass method and a slicing method. Isomer assignment was based on the characteristic fragment ions. The collision cross section values (^cTWCCS_N2) of the resolved cyclodextrin isomers were also determined. Ion mobility separation of structurally different fragment ions was demonstrated. Additionally, by coupling cIM-MS with reversed-phase liquid chromatography (HPLC-cIM-MS), two-dimensional separation of the isomers was achieved. The isomers, separated using HPLC-cIM-MS, were identified with the same approach as with cIM-MS alone, and their elution order provided insights into their relative hydrophobicity.

While gas chromatography mass spectrometry (GC-MS) has long been used to identify compounds in complex mixtures, this process is often subjective and time-consuming and leaves a large fraction of seemingly good-quality spectra unidentified. In this work, we describe a set of new mass spectral library-based methods to assist compound identification in complex mixtures. These methods employ mass spectral uniqueness and compound ubiquity of library entries alongside noise reduction and automated comparison of retention indices to library compounds. As a test data set, we used a publicly available electron ionization mass spectrometry data set consisting of 4833 spectra of particulate organic compounds emitted by combustion of wildland fuels. In the present work, spectra in this data set were first identified using the NIST 2023 EI-MS Library and associated batch process identification software (NIST MS PepSearch) using retention-index corrected Identity Search scoring. Resulting identifications and related information were then employed to parametrize other factors that correlate with identification. A method for identifying compounds absent from but related to those present in mass spectral libraries using the Hybrid Similarity Search is illustrated. Nevertheless, some 90% of the spectra remain unidentified. Through comparison of unidentified to identified mass spectra in this data set, a new simple measure, namely median relative abundance, was developed for evaluating the likelihood of identification.

Fluorescence labeled glycan homologous mixtures were quantified using fluorescence and then used to evaluate ionization performances in electrospray ionization at micro, nano, and femto flow modes. nanoESI produced higher (2+ and 3+) charged ions adducted with sodium and calcium. In comparison, femtoESI was found to favor the generation of [M + H]⁺ ions against metal adducts, even with nonvolatile salts up to 1 mM for NaCl and 100 μM for CaCl₂. For labeled glucose homopolymer (GHP) glycans, nanoESI and femtoESI had 0.81 and 3 nM detection limits, respectively. With LC separation and a much higher flow rate, conventional microflow ESI detected all glycans with 10-fold lower concentrations. Overall, nanoESI had the optimum uniformity in the relative ionization efficiency (RIE). When summing up intensities of analyte ions formed with all charge carriers, the RIE of the midsized glycans (10 to 16 glucose units) appear to be uniform (RIE 95%-105%). For the smaller (1-5 glucose units) glycan components, femtoESI provided better uniformity than nanoESI and conventional ESI. For the labeled IgG N-glycans, the impact of chemical structure on the ionization efficiency was revealed by the strong correlation between their RIE trends in different ionization modes.

Förster resonance energy transfer (FRET) is becoming a valuable technique in gas-phase structural biology for identifying local structural motifs and conformations of biological molecules, such as peptides and proteins. This method involves labeling the biomolecule with two dyes, a donor dye and an acceptor dye, that are commonly charged rhodamines. Here we examine how different amino acid (AA) methyl esters linked to the dye via amide linkages can influence the dye transition energy and, consequently, the energy-transfer efficiency, using cryogenic ion fluorescence spectroscopy. Absorption spectra were recorded for rhodamine B⁺-labeled AA esters (RB⁺-AA) through fluorescence-excitation experiments at the LUNA2 setup in Aarhus, which operates at cryogenic temperatures (down to approximately 100 K). The AAs studied include aliphatic ones (alanine (A), leucine (L), tert-leucine (tert-L), and methionine (M)), aromatic ones (phenylalanine (F) and tryptophan (W)), and two with polar side chains (serine (S) and threonine (T)). Results show that the band maximum either remains unchanged compared to RB⁺ or red shifts by over 3 nm in the case of RB⁺-M and RB⁺-F. While the spectra of RB⁺-A and RB⁺-L closely resemble that of RB⁺, RB⁺-tert-L shows a distinct red shift of about 1.4 nm. Spectral variations do not appear to be more influenced by the presence of aromatic AA side chains than other types, as differences observed between aliphatic AAs are comparable to those between the three groups. Instead, these variations appear to arise from differing conformations where the dihedral angle between the xanthene moiety and the pendant phenyl group varies, as influenced by the linked AA side chain. The angle determines the π-overlap between the two aromatic moieties, and according to TD-DFT calculations, an angle larger than 90° can easily account for red shifts due to larger delocalization of the π-electron cloud. Another factor is the polarizability of the side chain that could also contribute to the red shift. RB⁺-F and RB⁺-W spectra exhibit red-shifted, narrower absorption profiles, which is likely associated with the large aromatic side chains that limit the number of contributing structural configurations.

Molecular glues (MGs) and proteolysis-targeting chimeras (PROTACs) are used to modulate protein-protein interactions (PPIs), via induced proximity between compounds that have little or no affinity for each other naturally. They promote either reversible inhibition or selective degradation of a target protein, including ones deemed undruggable by traditional therapeutics. Though native MS (nMS) is capable of analyzing multiprotein complexes, the behavior of these artificially induced compounds in the gas phase is still not fully understood, and the number of publications over the past few years is still rather limited. Here, we studied two MG-induced complexes between mTOR_FRB and FKBP12 as well as a PROTAC-induced complex between FKBP51_FK1 and the von Hippel-Lindau E3 ligase (VHL). Native MS combined with collision-induced dissociation (CID) provided a way of measuring not only the formation of these complexes but also their dissociation pathways. Both protein complexes seem to eject preferably the centrally located small (compared to the mass of the proteins) ligand upon CID, rather than dissociating a peripheral subunit, as is often observed for naturally occurring protein complexes. In contrast, chemically induced dissociation in solution generated complementary data to CID, by disrupting the PPI surface, which resulted in more diverse MS spectra that preserved the stronger interactions in solution.

An inherent strength of hydrogen/deuterium exchange coupled to mass spectrometry (HDX-MS) is its ability to detect the presence of multiple conformational states of a protein, which often manifest as multimodal isotopic envelopes. However, the statistical considerations for accurate analysis of multimodal spectra have yet to be established. Here we outline an unrestrained binomial distribution fitting approach with the corresponding statistical tests to accurately detect and, when possible, deconvolute isotopic distributions that contain multiple subpopulations. The algorithms have been incorporated into an updated version of the freely available software, HX-Express, and validated using known mixtures of peptides deuterated to varying degrees. This approach presents a readily accessible tool to fit and interpret bimodal and trimodal behavior in HDX-MS data for mixed populations, EX1 kinetics, and pulse labeling data.

In recent years, alternative enzymes with varied specificities have gained importance in MS-based bottom-up proteomics, offering orthogonal information about biological samples and advantages in certain applications. However, most mass spectrometric workflows are optimized for tryptic digests. This raises the questions of whether enzyme specificity impacts mass spectrometry and if current methods for nontryptic digests are suboptimal. The success of peptide and protein identifications relies on the information content of MS/MS spectra, influenced by collision energy in collision-induced dissociation. We investigated this by conducting LC-MS/MS measurements with different enzymes, including trypsin, Arg-C, Glu-C, Asp-N, and chymotrypsin, at varying collision energies. We analyzed peptide scores for thousands of peptides and determined optimal collision energy (CE) values. Our results showed a linear m/z dependence for all enzymes, with Glu-C, Asp-N, and chymotrypsin requiring significantly lower energies than trypsin and Arg-C. We proposed a tailored CE selection method for these alternative enzymes, applying ca. 20% lower energy compared to tryptic peptides. This would result in a 10-15 eV decrease on a Bruker QTof instrument and a 5-6 NCE% (normalized collision energy) difference on an Orbitrap. The optimized method improved bottom-up proteomics performance by 8-32%, as measured by peptide identification and sequence coverage. The different trends in fragmentation behavior were linked to the effects of C-terminal basic amino acids for Arg-C and trypsin, stabilizing y fragment ions. This optimized method boosts the performance and provides insight into the impact of enzyme specificity. Data sets are available in the MassIVE repository (MSV000095066).