Abstract The diversity of anthropogenic organic substances in aquatic environments creates a need for analytical workflows that combine chemical coverage with reliable quantification, in order to assess global chemical pollution. Here, we present an integrated workflow that combines non-targeted and targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) for the analysis of xenobiotics in river and coastal environments. We developed a web-based application, GNPS2-Quant, to convert data-dependent acquisition (DDA) results into scheduled inclusion lists for parallel reaction monitoring (PRM), using precursor m/z values and retention times, thereby accelerating the transfer from non-targeted discovery to targeted quantification within the same instrument platform. Using a quadrupole orbitrap (Exploris 480) instrument and a panel of 142 xenobiotics, we compared the quantification performance of full-scan DDA-MS1 data vs PRM. While PRM provides greater selectivity, DDA-MS1 generally provided greater sensitivity, yielding lower limits of detection for 61 compounds and lower limits of quantification for 61 compounds. Despite these differences, both methods showed comparable quantitative accuracy, with approximately 75% of quality control measurements meeting our precision criteria, which was in a similar range to measurements using multiple reaction monitoring (MRM) on a triple quadrupole mass spectrometer. Application to Southern California river and estuary samples enabled the quantification of 57 xenobiotics, with strong agreement between methods across sites. While our results highlight the utility of PRM generation from non-targeted LC-MS/MS data, our data also demonstrate that DDA-MS1 alone can provide scalable quantitative performance, avoiding costly and time-consuming reanalysis.
Abstract A mechanistic understanding of collision induced dissociation is well established for fragmentation propensities of peptides in unmodified and modified forms. Major limitations in the characterization of unmodified peptides and peptides with labile posttranslational modifications (PTMs) include preferential cleavage N-terminal to proline, C-terminal to acidic residues as well as loss of PTMs, such as phosphorylation and glycosylation. However, the relative contributions of certain fragmentation pathways are not completely understood at the intact protein level. Here, we evaluated the top-down fragmentation propensities of α-casein, β-casein, ribonuclease B, and ovalbumin under denatured and native conditions using energy resolved higher energy collisional dissociation (HCD). Relative product ion abundance, residue fragmentation propensity, and sequence coverage were used to compare cleavages N-terminal to Pro and C-terminal to Asp/Glu, phosphoric acid neutral loss, and glycan dissociation. Pro-directed cleavage dominated α- and β-casein under both conditions, with limited phosphoric acid loss. Glycoproteins exhibited condition and energy dependent redistribution. Denatured RNase B shifted from Pro directed cleavage toward oxonium ion formation, whereas native RNase B shifted from sequential mannose loss toward Pro directed cleavage. Native ovalbumin shifted from Pro directed to acidic residue directed fragmentation. High relative abundance reflects fragmentation at fewer sites, supporting complementary measurements of ion abundance and fragmentation propensity. These results demonstrate that top-down proteoform characterization is not significantly limited by the neutral loss of labile PTMs as would be predicted by peptide fragmentation. Rather, sequence coverage and thus proteoform characterization are largely limited by sequence specific preferential cleavages, nevertheless highlighting the need for alternative electron and photon-based ion activation methods.
Organoids are in vitro-generated three-dimensional multicell aggregates that are designed to mimic the structural and functional features of their corresponding organ. The field of organoids has attracted significant attention in recent years, particularly in the context of disease research, drug screening, and most notably personalized medicine. Mass spectrometry imaging (MSI), a technique yet to be fully incorporated within organoid research, facilitates the potential for nontargeted broadband molecular analysis at the single-cell level. Due to the small size and fragility of organoids, it is imperative that meticulous sample preparation be undertaken for high-resolution MSI experiments. In this study, we propose a series of methodologies for the preparation of samples, encompassing the processes of embedding and cutting, the selection of a suitable matrix, and the deposition of matrices. Additionally, we explore the acquisition of data through a range of methods, with the objective of generating sufficient MSI data at the single-cell level. These experiments, which employ high-mass-resolution, high-spatial-resolution AP-SMALDI MSI, demonstrate its potential in advancing research into cell-type-specific metabolites in organoids.
The fragmentation of protonated N-phenylphthalimide (C6H4(CO)2NC6H5) in electrospray ionization generates an unexpected cation (C6H4COCN+) at m/z 130.029 as the most abundant ion by the loss of a neutral phenol molecule. One of the oxygen atoms in the two carbonyl groups is transferred to the phenyl ring by replacing the nitrogen atom. To confirm the oxygen migration to the benzene ring, mono-18O–N-phenylphthalimide was synthesized and subjected to collisional activation, resulting in two similarly abundant ions at m/z 130.029 and m/z 132.033 that corresponded to the 18O cation (C6H4C18OCN+). To confirm that one hydrogen atom on the phenyl ring may mediate the reaction to eliminate a water molecule, deuterated N-phenylphthalimide (C6H4(CO)2NC6D5) was prepared, and its MS/MS spectrum shows a peak at m/z 210.0848, corresponding to a neutral loss of HOD. Moreover, when the phenyl group is replaced by a pentafluorobenzene group (i.e., C6H4(CO)2NC6F5), HF loss is observed but without water loss. A nitrogen–oxygen rearrangement mechanism was proposed, in which the carbonyl oxygen atom mediates nucleophilic substitution of the nitrogen atom of the N-phenyl ring, leading to the loss of neutral phenol. The nitrogen–oxygen rearrangement can be extended to various substituted N-phenylphthalimide compounds, including heterocyclic rings such as triazole, most of which yield nitrogen–oxygen rearrangement ions as major peaks in MS/MS spectra.
Tandem mass tag (TMT)-based quantitative proteomics is a leading approach for multiplexed protein quantification, with synchronous precursor selection (SPS)-MS3 as the state-of-the-art strategy to mitigate ratio compression caused by precursor coisolation. Because TMT reporter signal in SPS-MS3 is directly proportional to the abundance of SPS ions selected from the preceding MS2 scan, maximizing SPS ion production should improve quantification. However, current data acquisition strategies apply a universal MS2 fragmentation setting to all peptide precursors, even though peptides possess distinct physicochemical properties that govern SPS ion production and, consequently, quantitative TMT reporter ion signal. While various fragmentation strategies have been explored to maximize peptide identification in label-free MS2 contexts, how to maximize quantitative signal in SPS-MS3-TMT remains underexplored. Inspired by recent advances in intelligent, real-time data acquisition, we hypothesize that adaptive fragmentation tuned per precursor could improve SPS-MS3-based TMT quantification. Here, we present a systematic evaluation using a TMTpro-labeled human data set of 51,064 unique tryptic peptide precursors, each acquired under ten fragmentation conditions (CID and HCD across a range of normalized collision energies). From each MS2 spectrum, we then computationally selected up to ten fragment ions ranked by intensity as pseudo-SPS (p-SPS) ions and used their summed intensity as a proxy for reporter ion signal. We find that CID NCE25, rather than the widely used CID NCE34, maintains identification efficiency and serves as the single best default setting, optimal for p-SPS ion production in more precursors (24%) than any other individual setting. In addition, per-precursor fragmentation optimization increases p-SPS ion signal by ≥25% for 36% of precursors and, more strikingly, ≥50% for 13% of precursors. To enable practical implementation, we developed FragWise, an XGBoost multiclass classifier that predicts the optimal fragmentation setting from precursor features, achieving 91.6% of the maximum achievable p-SPS ion signal. Together, these findings demonstrate the potential of differential fragmentation and lay the groundwork for real-time adaptive fragmentation to maximize quantitative information in TMT-based proteomics.
