A Workflow for Improved Analysis of Cross-Linking Mass Spectrometry Data Integrating Parallel Accumulation-Serial Fragmentation with MeroX and Skyline

Cross-linking mass spectrometry (XL-MS) has evolved into a pivotal technique for probing protein interactions. This study describes the implementation of Parallel Accumulation-Serial Fragmentation (PASEF) on timsTOF instruments, enhancing the detection and analysis of protein interactions by XL-MS. Addressing the challenges in XL-MS, such as the interpretation of complex spectra, low abundant cross-linked peptides, and a data acquisition bias, our current study integrates a peptide-centric approach for the analysis of XL-MS data and presents the foundation for integrating data-independent acquisition (DIA) in XL-MS with a vendor-neutral and open-source platform. A novel workflow is described for processing data-dependent acquisition (DDA) of PASEF-derived information. For this, software by Bruker Daltonics is used, enabling the conversion of these data into a format that is compatible with MeroX and Skyline software tools. Our approach significantly improves the identification of cross-linked products from complex mixtures, allowing the XL-MS community to overcome current analytical limitations.

Influence of Mutations and N-Glycosylation Sites in the Receptor-Binding Domain (RBD) and the Membrane Protein of SARS-CoV-2 Variants of Concern on Antibody Binding in ELISA

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect human cells by first attaching to the ACE-2 receptor via its receptor-binding domain (RBD) in the spike protein. Here, we report the influence of N-glycosylation sites of the RBD and the membrane (M) protein on IgG antibody binding in serum samples from patients infected with the original SARS-CoV-2 strain in Germany. The RBDs of the wildtype, alpha, beta, gamma, and kappa variants expressed in HEK293S GnTI- cells were all N-glycosylated at Asn331, Asn334, Asn343, and Asn360 or Asn370, whereas the M-protein was glycosylated at Asn5. An ELISA using a coated RBD and probed with anti-RBD IgG antibodies gave a sensitivity of 96.3% and a specificity of 100% for the wildtype RBD, while the sensitivity decreased by 5% to 10% for the variants of concern, essentially in the order of appearance. Deglycosylation of the wildtype RBD strongly reduced antibody recognition by ~20%, considering the mean of the absorbances recorded for the ELISA. This effect was even stronger for the unglycosylated RBD expressed in Escherichia coli, suggesting structural changes affecting epitope recognition. Interestingly, the N-glycosylated M-protein expressed in HEK293S GnTI- cells gave good sensitivity (95%), which also decreased to 65% after deglycosylation, and selectivity (100%). In conclusion, N-glycosylation of the M-protein, the RBD, and most likely the spike protein are important for proper antibody binding and immunological assays, whereas the type of N-glycosylation is less relevant.

Evaluating Peptide Fragment Ion Detection Using Traveling Wave Ion Mobility Spectrometry with Signal-Enhanced MSE (SEMSE)

The inherent poor sampling of fragment ions in time-of-flight mass analyzers was recently improved for data-dependent acquisition (DDA) by considering their drift times in traveling wave ion mobility spectrometry (TWIMS). Here, we extend this TWIMS-DDA approach to the data-independent acquisition (DIA) mode MS^E to improve the signal intensities of fragment ions by providing improved ion beam sampling efficiency, which we termed therefore signal-enhanced MS^E (SEMS^E). The theoretical expectation that SEMS^E improves the number of identified peptides, the number of quantifiable peptides, and the lower limit of quantitation in wideband DIA was evaluated on an electrospray ionisation-ion mobility spectrometry-quadrupole-time-of-flight-MS (ESI-IMS-Q-TOF-MS) (Synapt G2-Si) in comparison to five established TWIMS-DDA and TWIMS-MS^E methods with respect to the number of peptide identifications, the spectral quality of supporting peptide spectra matches, and (most importantly) fragment ion signal sensitivity. A comparison of the fragment signals clearly indicated that SEMS^E provides 6.8- to 11.5-fold larger peak areas than established MS^E techniques. While this clearly shows the advantages of SEMS^E, the inherent limitations of the current software tools do not allow using all benefits in routine analyses. As the simultaneous fragmentation of co-eluting peptides limited peptide identification, DDA and MS^E data sets were integrated using Skyline.

A Workflow towards the Reproducible Identification and Quantitation of Protein Carbonylation Sites in Human Plasma

Protein carbonylation, a marker of excessive oxidative stress, has been studied in the context of multiple human diseases related to oxidative stress. The variety of post-translational carbonyl modifications (carbonyl PTMs) and their low concentrations in plasma challenge their reproducible identification and quantitation. However, carbonyl-specific biotinylated derivatization tags (e.g., aldehyde reactive probe, ARP) allow for targeting carbonyl PTMs by enriching proteins and peptides carrying these modifications. In this study, an oxidized human serum albumin protein model (OxHSA) and plasma from a healthy donor were derivatized with ARP, digested with trypsin, and enriched using biotin-avidin affinity chromatography prior to nano reversed-phase chromatography coupled online to electrospray ionization tandem mass spectrometry with travelling wave ion mobility spectrometry (nRPC-ESI-MS/MS-TWIMS). The presented workflow addresses several analytical challenges by using ARP-specific fragment ions to reliably identify ARP peptides. Furthermore, the reproducible recovery and relative quantitation of ARP peptides were validated. Human serum albumin (HSA) in plasma was heavily modified by a variety of direct amino acid oxidation products and adducts from reactive carbonyl species (RCS), with most RCS modifications being detected in six hotspots, i.e., Lys10, Lys190, Lys199, Lys281, Lys432, and Lys525 of mature HSA.

A comparison of inducible, ontogenetic, and interspecific sources of variation in the foliar metabolome in tropical trees

Plant interactions with other organisms are mediated by chemistry, yet chemistry varies among conspecific and within individual plants. The foliar metabolome—the suite of small-molecule metabolites found in the leaf—changes during leaf ontogeny and is influenced by the signaling molecule jasmonic acid. Species differences in secondary metabolites are thought to play an important ecological role by limiting the host ranges of herbivores and pathogens, and hence facilitating competitive coexistence among plant species in species-rich plant communities such as tropical forests. Yet it remains unclear how inducible and ontogenetic variation compare with interspecific variation, particularly in tropical trees. Here, we take advantage of novel methods to assemble mass spectra of all compounds in leaf extracts into molecular networks that quantify their chemical structural similarity in order to compare inducible and ontogenetic chemical variation to among-species variation in species-rich tropical tree genera. We ask (i) whether young and mature leaves differ chemically, (ii) whether jasmonic acid-inducible chemical variation differs between young and mature leaves, and (iii) whether interspecific exceeds intraspecific chemical variation for four species from four hyperdiverse tropical tree genera. We observed significant effects of the jasmonic acid treatment for three of eight combinations of species and ontogenetic stage evaluated. Three of the four species also exhibited large metabolomic differences with leaf ontogenetic stage. The profound effect of leaf ontogenetic stage on the foliar metabolome suggests a qualitative turnover in secondary chemistry with leaf ontogeny. We also quantified foliar metabolomes for 45 congeners of the four focal species. Chemical similarity was much greater within than between species for all four genera, even when within-species comparisons included leaves that differed in age and jasmonic acid treatment. Despite ontogenetic and inducible variation within species, chemical differences among congeneric species may be sufficient to partition niche space with respect to chemical defense.

A protocol for high-throughput, untargeted forest community metabolomics using mass spectrometry molecular networks

PREMISE OF THE STUDY

We describe a field collection, sample processing, and ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) instrumental and bioinformatics method developed for untargeted metabolomics of plant tissue and suitable for molecular networking applications.

METHODS AND RESULTS

A total of 613 leaf samples from 204 tree species was collected in the field and analyzed using UHPLC-MS/MS. Matching of molecular fragmentation spectra generated over 125,000 consensus spectra representing unique molecular structures, 26,410 of which were linked to at least one structurally similar compound.

CONCLUSIONS

Our workflow is able to generate molecular networks of hundreds of thousands of compounds representing broad classes of plant secondary chemistry and a wide range of molecular masses, from 100 to 2500 daltons, making possible large-scale comparative metabolomics, as well as studies of chemical community ecology and macroevolution in plants.