Biology subjects

Reiding, K. R.

Publications and source records attributed to Reiding, K. R..

5 recordsLinked to original sources

bioRxiv2026

Expanding Glycopeptide Identification with Match-Between-Glycans in FragPipe

Glycosylation is one of the most important, but also most complex, post-translational modifications of proteins, playing a pivotal role in various pathological processes. Mass spectrometry-based large-scale glycoproteomics analysis offers a powerful approach to explore the fundamental roles of glycosylation in both physiological and pathological contexts. Traditionally, DDA glycopeptide assignment relies on information-dense MS2 spectra, containing sufficient fragmentation information to identify both the peptide and glycan moieties. Achieving this fragmentation can be difficult, especially for low-abundant glycopeptides and/or large, complex glycans. These glycopeptides are often not assigned using current data analysis software, yet they can be of biological relevance. Here, we introduce a method called match-between-glycans (MBG), which expands glycopeptide identification while maintaining the existing glycoproteome analysis workflow. MBG enables expanding the set of identified glycopeptides to include those without MS2 spectra, or with lower quality MS2 spectra, by looking for MS1 signals displaced from other identified glycopeptides by one or multiple monosaccharide unit(s). MBG can also identify glycans not included in the glycan database, such as those containing adducts or modifications, allowing these glycans to be recovered without a drastic expansion of the search space. Combined with target-decoy FDR control, we show this method is capable of accurately expanding glycopeptide identifications and providing a more complete quantitative profile of glycosylation at each glycosite. MBG is fully integrated into the glycoproteomics workflows in FragPipe, allowing seamless, one-click operation.

bioinformatics↗

bioRxiv2025

Overglycosylation introduces local changes in triple helix alignment in collagen type I fibril structure

Collagen fibrils constitute the structural scaffold of bone, and their hierarchical organization is central to biomineralization. While hydroxylation and glycosylation of lysine residues are well-known collagen post-translational modifications, their structural consequences remain poorly understood. Here we show that excess of glycosylation of hydroxylysine residues leads to significant alterations in the local packing of collagen molecules within the fibrils. By prolonging the enzymatic modification window during helix folding through the use of cyclosporin A, an increase in double glycosylation was observed at specific sites. These overglycosylated residues were pinpointed by mass spectrometry, while cryogenic TEM revealed fibrils with reduced diameters and distinct displacements of defined sub-bands within the D-period, without altering the overall periodicity. By mapping the modified residues onto the quarter-staggered model, we have been able to correlate site-specific glycosylation with sub-band shifts, linking chemical modification to supramolecular order. These results provide molecular-level evidence that collagen glycosylation is an active determinant of fibril structure. Such insights not only advance fundamental understanding of collagen assembly but could also illuminate mechanisms underlying bone fragility disorders, including osteogenesis imperfecta, that feature altered glycosylation.

biochemistry↗

bioRxiv2023

H7 influenza A viruses bind sialyl-LewisX, a potential intermediate receptor between species

Influenza A viruses (IAVs) can overcome species barriers by adaptation of the receptor binding site of the hemagglutinin (HA). To initiate infection, HAs bind to glycan receptors with terminal sialic acids, which are either N-acetylneuraminic acid (NeuAc) or N-glycolylneuraminic acid (NeuGc), the latter is mainly found in horses and pigs but not in birds and humans. We investigated the influence of previously identified equine NeuGc-adapting mutations (S128T, I130V, A135E, T189A, and K193R) in avian H7 IAVs in vitro and in vivo. We observed that these mutations negatively affected viral replication in chicken cells, but not in duck cells, and positively affected replication in horse cells. In vivo, the mutations reduced virus virulence and mortality in chickens. Ducks excreted high viral loads for a longer time than chickens, although they appeared clinically healthy. To elucidate why chickens and ducks were infected by these viruses despite the absence of NeuGc, we re-evaluated the receptor binding of H7 HAs using glycan microarray and flow cytometry studies. This revealed that mutated avian H7 HAs also bound to 2,3-linked NeuAc and sialyl-LewisX, which have an additional fucose moiety in their terminal epitope, explaining why infection of ducks and chickens was possible. Interestingly, the 2,3-linked NeuAc and sialyl-LewisX epitopes were only bound when presented on tri-antennary N-glycans, emphasizing the importance of investigating the fine receptor specificities of IAVs. In conclusion, the binding of NeuGc-adapted H7 IAV to sialyl-LewisX enables viral replication and shedding by chickens and ducks, potentially facilitating interspecies transmission of equine-adapted H7 IAVs. (249 words) ImportanceInfluenza A viruses cause millions of deaths and illness in birds and mammals each year. The viral surface protein hemagglutinin initiates infection by binding to host cell terminal sialic acids. Hemagglutinin adaptations affect the binding affinity to these sialic acids and therefore the potential host species targeted. While avian and human IAVs tend to bind N-acetylneuraminic acid (a form of sialic acid), equine H7 viruses prefer binding to N-glycolylneuraminic acid (NeuGc). To better understand the function of NeuGc-specific adaptations in hemagglutinin and to elucidate interspecies transmission potential NeuGc-adapted viruses, we evaluated the effects of NeuGc-specific mutations in avian H7 viruses in chickens and ducks, important economic hosts and reservoir birds, respectively. We also examined the impact on viral replication and found a binding affinity to sialyl-LewisX, another terminal epitope. These findings are important as they contribute to the understanding of the role of sialyl-LewisX in avian influenza infection. (148 words)

molecular biology↗

bioRxiv2023

Glycoproteomics-compatible MS/MS-based quantification of glycopeptide isomers

Glycosylation is an essential protein modification occurring on the majority of extracellular human proteins, mass spectrometry (MS) being an indispensable tool for its analysis. Not only can MS determine glycan compositions, but also position the glycan at specific sites via glycoproteomics. However, glycans are complex branching structures with monosaccharides interconnected in a variety of biologically relevant linkages - isomeric properties which are invisible when the readout is mass alone. Here, we developed an LC-MS/MS-based workflow for determining glycopeptide isomer ratios. Making use of isomerically-defined glyco(peptide) standards, we observed marked differences in fragmentation behavior between isomer pairs when subjected to collision energy gradients, specifically in terms of galactosylation/sialylation branching and linkage. These behaviors were developed into component variables that allowed relative quantification of isomerism within mixtures. Importantly, at least for small peptides, the isomer quantification appeared largely independent from the peptide portion of the conjugate, allowing broad application of the method.

biochemistry↗

bioRxiv2019

Systematic evaluation of normalization methods for glycomics data based on performance of network inference

Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, we here quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms (LC-ESI-MS, UHPLC-FLD and MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the Probabilistic Quotient method followed by log-transformation, irrespective of the measurement platform.

bioinformatics↗