Biology subjects

Lisacek, F.

Publications and source records attributed to Lisacek, F..

7 recordsLinked to original sources

bioRxiv2024

Protein structure, a genetic encoding for glycosylation

Unlike DNA, RNA, and protein biosynthesis, dogma describes glycosylation as primarily determined by intrinsic cellular limitations, such as glycosyltransferase expression and precursor availability. However, this cannot explain the commonly-observed differences between glycans on the same protein. By examining site-specific glycosylation on diverse human proteins, we detected associations between protein structure and glycan structure, broadly generalizable to human-expressed glycoproteins. Through structural analysis of site-specific glycosylation data, we found protein-sequence and structural features consistently correlated with specific glycan features. To quantify these relationships, we present a new amino acid substitution matrix describing "glycoimpact", i.e., the association of primary protein structure and glycosylation. High-glycoimpact amino acids co-evolve with glycosites, and glycoimpact is high when estimates of amino acid conservation and variant pathogenicity diverge. We report thousands of disease variants near glycosites with high-glycoimpact, including several with known links to aberrant glycosylation (e.g., Oculocutaneous Albinism, Jakob-Creutzfeldt disease, Gerstmann-Straussler-Scheinker, and Gauchers Disease). Finally, glycoimpact quantification is validated by studying oligomannose-complex glycan ratios on HIV ENV, differential sialylation on IgG3 Fc, differential glycosylation on SARS-CoV-2 Spike, and fucose-modulated function of a tuberculosis monoclonal antibody. Finally, to test the causality of protein-glycan associations, we created 5 glycoimpact-designed novel Rituximab variants, 4 of which substantially changed glycoprofiles as predicted. In all, we report that site-specific glycan biosynthesis is influenced by underlying protein structure, enabling glycan structure prediction and genetic sequence-guided glycoengineering.

genetics↗

bioRxiv2024

Decoding glycosylation potential from protein structure across human glycoproteins with a multi-view recurrent neural network

Glycosylation is described as a non-templated biosynthesis. Yet, the template-free premise is antithetical to the observation that different N-glycans are consistently placed at specific sites. It has been proposed that glycosite-proximal protein structures could constrain glycosylation and explain the observed microheterogeneity. Using site-specific glycosylation data, we trained a hybrid neural network to parse glycosites (recurrent neural network) and match them to feasible N-glycosylation events (graph neural network). From glycosite-flanking sequences, the algorithm predicts most human N-glycosylation events documented in the GlyConnect database and proposed structures corresponding to observed monosaccharide composition of the glycans at these sites. The algorithm also recapitulated glycosylation in Enhanced Aromatic Sequons, SARS-CoV-2 spike, and IgG3 variants, thus demonstrating the ability of the algorithm to predict both glycan structure and abundance. Thus, protein structure constrains glycosylation, and the neural network enables predictive in silico glycosylation of uncharacterized or novel protein sequences and genetic variants.

bioinformatics↗

bioRxiv2022

A pore-forming β-trefoil lectin with specificity for the tumor-related glycosphingolipid Gb3

Lectins are efficient multivalent glycan receptors, deciphering the glyco-code on cell surfaces. The {beta}-trefoil fold, characterized by three lobe-shaped repeats, is adopted by several classes of lectins, often associated with other domains having enzymatic or toxic activity. Based on the UniLectin3D database classification, the sequence signature of trefoil lobes was defined and used to predict 44714 lectins from 4497 species. Among them, SaroL-1 from the lower eukaryote Salpingoeca rosetta was predicted to contain both {beta}-trefoil and aerolysin-like pore-forming domain. Recombinant SaroL-1 binds to galactose and derivatives, with a stronger affinity for cancer-related -galactosylated epitopes such as glycosphingolipid Gb3 embedded in giant unilamellar vesicles or cell membranes. Crystal structures in complex with Gb3 trisaccharide and GalNAc show similarity with pore-forming toxins. Recognition of the Gal epitope on glycolipids was necessary for hemolysis of rabbit erythrocytes and toxicity on cancer cells through carbohydrate-dependent pore-formation.

biochemistry↗

bioRxiv2022

In silico analysis of the human milk oligosaccharide glycome reveals key enzymes of their biosynthesis

Human milk oligosaccharides (HMOs) form the third most abundant component of human milk and are known to convey several benefits to the neonate, including protection from viral and bacterial pathogens, training of the immune system, and influencing the gut microbiome. As HMO production during lactation is driven by enzymes that are common to other glycosylation processes, we adapted a model of mucin-type GalNAc-linked glycosylation enzymes to act on free lactose. We identified a subset of 11 enzyme activities that can account for 206 of 226 distinct HMOs isolated from human milk, and constructed a biosynthetic reaction network that identifies 5 new core HMO structures. A comparison of monosaccharide compositions demonstrated that the model was able to discriminate between two possible groups of intermediates between major subnetworks, and to assign possible structures to several previously uncharacterised HMOs. The effect of enzyme knockouts is presented, identifying {beta}-1,4-galactosyltransferase and {beta}-1,3-N-acetylglucosaminyltransferase as key enzyme activities involved in the generation of the observed HMO glycosylation patterns. The model also provides a synthesis chassis for the most common HMOs found in lactating mothers.

biochemistry↗

bioRxiv2020

Proteome-wide prediction of bacterial carbohydrate-binding proteins as a tool for understanding commensal and pathogen colonisation of the vaginal microbiome

Bacteria use protein receptors called lectins to anchor to specific host surface sugars. The role of lectins in the vaginal microbiome, and their involvement in reproductive tract pathophysiology is poorly defined. Here we establish a classification system based on taxonomy and protein 3D structure to identify 109 lectin classes. Hidden Markov Model (HMM) profiles for each class were used to search bacterial genomes, resulting in the prediction of >100 000 bacterial lectins available at unilectin.eu/bacteria. Genome screening of 90 isolates from 21 vaginal bacterial species showed that potential pathogens produce a larger variety of lectins than commensals indicating increased glycan-binding potential. Both the number of predicted bacterial lectins, and their specificities for carbohydrates correlated with pathogenicity. This study provides new insights into potential mechanisms of commensal and pathogen colonisation of the reproductive tract that underpin health and disease states.

bioinformatics↗

bioRxiv2020

Examining and fine-tuning the selection of glycan compositions with GlyConnect Compozitor

A key point in achieving accurate intact glycopeptide identification is the definition of the glycan composition file that is used to match experimental with theoretical masses by a glycoproteomics search engine. At present, these files are mainly built from searching the literature and/or querying data sources focused on posttranslational modifications. Most glycoproteomics search engines include a default composition file that is readily used when processing mass spectrometry data. We introduce here a glycan composition visualising and comparative tool associated with the GlyConnect database and called GlyConnect Compozitor. It has web interface through which the database can be queried to bring out contextual information relative to a set of glycan compositions. The tool takes advantage of compositions being related to one another through shared monosaccharide counts and outputs interactive graphs summarising information searched in the database. These results provide a guide for selecting or deselecting compositions in a file in order to reflect the context of a study as closely as possible. As part of the tool collection of the Glycomics@ExPASy initiative, Compozitor is hosted at https://glyconnect.expasy.org/compozitor/ where it can be run as a web application. It is also directly accessible from the GlyConnect database.

bioinformatics↗

bioRxiv2018

e-workflow for recording of glycomic mass spectrometric data in compliance with reporting guidelines

Glycomics targets released glycans from proteins, lipids and proteoglycans. High throughput glycomics is based on mass spectrometry (MS) that increasingly depends on exchange of data with databases and the use of software. This requires an agreed format for accurately recording of experiments, developing consistent storage modules and granting public access to glycomic MS data. The introduction of the MIRAGE (Mimimum Requirement for A Glycomics Experiment) reporting standards for glycomics was the first step towards automating glycomic data recording. This report describes a glycomic e-infrastructure utilizing a well established glycomics recording format (GlycoWorkbench), and a dedicated web tool for submitting MIRAGE-compatible MS information into a public experimental repository, UniCarb-DR. The submission of data to UniCarb-DR should be a part of the submission process for publications with glycomics MSn that conform to the MIRAGE guidelines. The structure of this pipeline allows submission of most MS workflows used in glycomics.

bioinformatics↗