Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics.

Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.

Improved Peptide Backbone Fragmentation Is the Primary Advantage of MS-Cleavable Crosslinkers.

Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of mass spectrometry (MS)-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently, such studies have also been published with noncleavable crosslinkers, suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the commonly used MS-cleavable crosslinker, disuccinimidyl sulfoxide (DSSO). Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS cleavability of the crosslinker, but improved peptide backbone fragmentation which reduces the ambiguity of peptide identifications. This also holds true for another commonly used MS-cleavable crosslinker, DSBU. We show furthermore that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped higher-energy collisional dissociation (HCD) method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry.

Leveraging Parameter Dependencies in High-Field Asymmetric Waveform Ion-Mobility Spectrometry and Size Exclusion Chromatography for Proteome-wide Cross-Linking Mass Spectrometry.

Ion-mobility spectrometry shows great promise to tackle analytically challenging research questions by adding another separation dimension to liquid chromatography-mass spectrometry. The understanding of how analyte properties influence ion mobility has increased through recent studies, but no clear rationale for the design of customized experimental settings has emerged. Here, we leverage machine learning to deepen our understanding of field asymmetric waveform ion-mobility spectrometry for the analysis of cross-linked peptides. Knowing that predominantly m/z and then the size and charge state of an analyte influence the separation, we found ideal compensation voltages correlating with the size exclusion chromatography fraction number. The effect of this relationship on the analytical depth can be substantial as exploiting it allowed us to almost double unique residue pair detections in a proteome-wide cross-linking experiment. Other applications involving liquid- and gas-phase separation may also benefit from considering such parameter dependencies.

Reliable identification of protein-protein interactions by crosslinking mass spectrometry.

Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.

Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry.

Crosslinking mass spectrometry has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the mass spectra of crosslinked peptides limits the numbers of protein-protein interactions that can be confidently identified. Here, we leverage chromatographic retention time information to aid the identification of crosslinked peptides from mass spectra. Our Siamese machine learning model xiRT achieves highly accurate retention time predictions of crosslinked peptides in a multi-dimensional separation of crosslinked E. coli lysate. Importantly, supplementing the search engine score with retention time features leads to a substantial increase in protein-protein interactions without affecting confidence. This approach is not limited to cell lysates and multi-dimensional separation but also improves considerably the analysis of crosslinked multiprotein complexes with a single chromatographic dimension. Retention times are a powerful complement to mass spectrometric information to increase the sensitivity of crosslinking mass spectrometry analyses.

Cryo-EM structures of holo condensin reveal a subunit flip-flop mechanism.

Complexes containing a pair of structural maintenance of chromosomes (SMC) family proteins are fundamental for the three-dimensional (3D) organization of genomes in all domains of life. The eukaryotic SMC complexes cohesin and condensin are thought to fold interphase and mitotic chromosomes, respectively, into large loop domains, although the underlying molecular mechanisms have remained unknown. We used cryo-EM to investigate the nucleotide-driven reaction cycle of condensin from the budding yeast Saccharomyces cerevisiae. Our structures of the five-subunit condensin holo complex at different functional stages suggest that ATP binding induces the transition of the SMC coiled coils from a folded-rod conformation into a more open architecture. ATP binding simultaneously triggers the exchange of the two HEAT-repeat subunits bound to the SMC ATPase head domains. We propose that these steps result in the interconversion of DNA-binding sites in the catalytic core of condensin, forming the basis of the DNA translocation and loop-extrusion activities.