Isotopologue pattern based data mining for selenium species from HILIC-ESI-Orbitrap-MS-derived spectra

Automated and specific picking of selenium-containing molecular entities has not been an obvious option for software tools associated with electrospray high-resolution mass spectrometry (MS). In our study, a comprehensive pattern matching approach based on intra-isotopologue distance and isotopologue ratio data was critically evaluated in terms of reproducibility and selenium isotope selection on three samples, including selenized Torula yeast and the selenium hyperaccumulator plant Cardamine violifolia. Hydrophilic interaction liquid chromatography was applied to provide a one-step separation for water soluble metabolites to put an end to the need for either orthogonal setups or poor retention on reversed phase chromatography. Assistance from inductively coupled plasma-MS was taken only for chromatographic verification purposes, and the involvement of absolute mass defect (MD) data in selenometabolite-specific screening was assessed by multivariate statistical tools. High focus was placed on screening efficiency and on the validation of discovered selenized molecules to avoid reporting of artefacts. From the >1000 molecular entries detected, selenium-containing molecules were picked up with a recovery rate of >88% and a false positive rate of <10%. Isotop(ologu)e pairs of 78Se-80Se and 80Se-82Se proved to be the most performant in the detection. On the basis of accurate mass information and hypothetical deamination processes, elemental composition could be proposed for 72 species out of the 75 selenium species encountered without taking into account selenocompound databases. Absolute MD data were used to significantly differentiate a potentially sample-specific subgroup of false positive molecular entities from non-selenized and selenized entities.

Uncovering PFAS and Other Xenobiotics in the Dark Metabolome Using Ion Mobility Spectrometry, Mass Defect Analysis, and Machine Learning

The identification of xenobiotics in nontargeted metabolomic analyses is a vital step in understanding human exposure. Xenobiotic metabolism, transformation, excretion, and coexistence with other endogenous molecules, however, greatly complicate the interpretation of features detected in nontargeted studies. While mass spectrometry (MS)-based platforms are commonly used in metabolomic measurements, deconvoluting endogenous metabolites from xenobiotics is also often challenged by the lack of xenobiotic parent and metabolite standards as well as the numerous isomers possible for each small molecule m/z feature. Here, we evaluate a xenobiotic structural annotation workflow using ion mobility spectrometry coupled with MS (IMS-MS), mass defect filtering, and machine learning to uncover potential xenobiotic classes and species in large metabolomic feature lists. Xenobiotic classes examined included those of known high toxicities, including per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and pesticides. Specifically, when the workflow was applied to identify PFAS in the NIST SRM 1957 and 909c human serum samples, it greatly reduced the hundreds of detected liquid chromatography (LC)-IMS-MS features by utilizing both mass defect filtering and m/z versus IMS collision cross sections relationships. These potential PFAS features were then compared to the EPA CompTox entries, and while some matched within specific m/z tolerances, there were still many unknowns illustrating the importance of nontargeted studies for detecting new molecules with known chemical characteristics. Additionally, this workflow can also be utilized to evaluate other xenobiotics and enable more confident annotations from nontargeted studies.

A small azide-modified thiazole-based reporter molecule for fluorescence and mass spectrometric detection

Molecular probes are widely used tools in chemical biology that allow tracing of bioactive metabolites and selective labeling of proteins and other biomacromolecules. A common structural motif for such probes consists of a reporter that can be attached by copper(I)-catalyzed 1,2,3-triazole formation between terminal alkynes and azides to a reactive headgroup. Here we introduce the synthesis and application of the new thiazole-based, azide-tagged reporter 4-(3-azidopropoxy)-5-(4-bromophenyl)-2-(pyridin-2-yl)thiazole for fluorescence, UV and mass spectrometry (MS) detection. This small fluorescent reporter bears a bromine functionalization facilitating the automated data mining of electrospray ionization MS runs by monitoring for its characteristic isotope signature. We demonstrate the universal utility of the reporter for the detection of an alkyne-modified small molecule by LC–MS and for the visualization of a model protein by in-gel fluorescence. The novel probe advantageously compares with commercially available azide-modified fluorophores and a brominated one. The ease of synthesis, small size, stability, and the universal detection possibilities make it an ideal reporter for activity-based protein profiling and functional metabolic profiling.

Using mass defect plots as a discovery tool to identify novel fluoropolymer thermal decomposition products

Fire events involving halogenated materials, such as plastics and electronics, produce complex mixtures that include unidentified toxic and environmentally persistent contaminants. Ultrahigh-resolution mass spectrometry and mass defect filtering can facilitate compound identification within these complex mixtures. In this study, thermal decomposition products of polychlorotrifluoroethylene (PCTFE, [-CClF-CF2 -]n), a common commercial polymer, were analyzed by Fourier transform ion cyclotron resonance mass spectrometry. Using the mass defect plot as a guide, novel PCTFE thermal decomposition products were identified, including 29 perhalogenated carboxylic acid (PXCA, X = Cl,F) congener classes and 21 chlorine/fluorine substituted polycyclic aromatic hydrocarbon (X-PAH, X = Cl,F) congener classes. This study showcases the complexity of fluoropolymer thermal decomposition and the potential of mass defect filtering to characterize complex environmental samples.

Identification of Phosphorylated Human Peptides by Accurate Mass Measurement Alone

At sufficiently high mass accuracy, it is possible to distinguish phosphorylated from unmodified peptides by mass measurement alone. We examine the feasibility of that idea, tested against a library of all possible in silico tryptic digest peptides from the human proteome database. The overlaps between in silico tryptic digest phosphopeptides generated from known phosphorylated proteins (1-12 sites) and all possible unmodified human peptides are considered for assumed mass error ranges of ±10, ±50, ±100, ±1,000, and ±10,000 ppb. We find that for mass error ±50 ppb, 95% of all phosphorylated human tryptic peptides can be distinguished from nonmodified peptides by accurate mass alone through the entire nominal mass range. We discuss the prospect of on-line LC MS/MS to identify phosphopeptide precursor ions in MS1 for selected dissociation in MS2 to identify the peptide and site(s) of phosphorylation.

Application of fractional mass for the identification of peptide-oligonucleotide cross-links by mass spectrometry

A method has been developed to identify oligonucleotide-peptide heteroconjugates by accurate mass measurements using MS. The fractional mass (the decimal fraction mass value following the monoisotopic nominal mass) for peptides and oligonucleotides is different due to their differing molecular compositions. This property has been used to develop the general conditions necessary to differentiate peptides and oligonucleotides from oligonucleotide-peptide heteroconjugates. Peptides and oligonucleotides generated by the theoretical digestion of various proteins and nucleic acids were plotted as nominal mass versus fractional mass. Such plots reveal that three nucleotides cross-linked to a peptide produce enough change in the fractional mass to be recognized from non-cross-linked peptides at the same nominal mass. Experimentally, a Cytochrome c digest was spiked with an oligonucleotide-peptide heteroconjugate and conditions for analyzing the sample using liquid chromatography (LC)-MS were optimized. Upon analysis of this mixture, all detected masses were plotted on a fractional mass plot and the heteroconjugate could be readily distinguished from non-cross-linked peptides. The method developed here can be incorporated into a general proteomics-like scheme for identifying protein-nucleic acid cross-links, and this method is equally applicable to characterizing cross-links generated from protein-DNA and protein-RNA complexes.