Dataset Information

Comprehensive detection of isopeptides between human tissue transglutaminase and gluten peptides using a reciprocal proteomic approach

ABSTRACT: Celiac disease (CD) is a chronic inflammation of the small intestine triggered by the ingestion of gluten in genetically predisposed individuals. Tissue transglutaminase (TG2) is a key factor in the pathogenesis of CD, because it catalyzes both the deamidation of specific glutamine residues and the formation of covalent Nε-(γ-glutamyl)-lysine isopeptide crosslinks resulting in TG2-gluten peptide complexes. These complexes are thought to activate B cells causing the secretion of anti-TG2 autoantibodies that serve as diagnostic markers for CD, although their pathogenic role remains unclear. To gain more insight into the molecular structures of TG2-gluten peptide complexes, we developed a reciprocal proteomic analysis strategy, which facilitates the comprehensive identification of isopeptides in a complex protein hydrolysate. The workflow consists of four steps: (1) performance of the model reaction between TG2 and gluten peptide(s) followed by tryptic hydrolysis, clean-up and untargeted nLC-MS/MS analysis (2), prediction of tryptic TG2-derived lysine peptides that serve as potential isopeptide modifications (3) the search for isopeptides by configuring the TG2-modifications in MaxQuant and search against the α-gliadin fasta file and (4) the reciprocal search for isopeptides by configuring the gluten peptide(s) as modification in MaxQuant and search against the TG2 fasta file. After verification by manual data curation and visualization, this strategy enabled the identification of 26 different isopeptides involving 19 TG2 lysine residues, only six of which were known previously. Experiments with different TG2-gluten peptide molar ratios revealed that K-425, K-590, K-600 and K-649 were the most preferred lysine residues involved in isopeptide crosslinking. Further, expanding the model system to three gluten peptides allowed the localization of the preferred glutamine crosslinking sites. The described strategy is generally applicable to any hydrolysate containing isopeptides and these new insights into the structure of TG2-gluten peptide complexes may help clarify the role of extracellular TG2 in CD autoimmunity and in other inflammatory diseases.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human) Triticum Aestivum (wheat)

DISEASE(S): Celiac Disease

SUBMITTER: Christina Ludwig

LAB HEAD: Christina Ludwig

PROVIDER: PXD014067 | Pride | 2019-09-27

REPOSITORIES: Pride

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Publications

Comprehensive Detection of Isopeptides between Human Tissue Transglutaminase and Gluten Peptides.

Lexhaller Barbara B Ludwig Christina C Scherf Katharina A KA

Nutrients 20190920 10

Celiac disease (CD) is a chronic inflammation of the small intestine triggered by the ingestion of gluten in genetically predisposed individuals. Tissue transglutaminase (TG2) is a key factor in CD pathogenesis, because it catalyzes both the deamidation of specific glutamine residues and the formation of covalent Nε-(γ-glutamyl)-lysine isopeptide crosslinks resulting in TG2-gluten peptide complexes. These complexes are thought to activate B cells causing the secretion of anti-TG2 autoantibodies ...[more]

PMID: 31547042

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Project description:Background & Aims: Traditional celiac disease diagnostics based on histomorphometric evaluations are liable to misinterpretations due to the common technical flaws e.g. wrong orientation of the biopsy and subjective errors are relatively common e.g. interobserver errors. We envisioned that there is a need for molecular histomorphometric tool that obviates these error sources yielding an objective ratio instead. Gene expression determine the state of a tissue, so the changes in expression may be associated with the severity of lesions during CD and can be used to classify it. Methods: 15 CD patients, who have been at least one year on gluten-free diet, were enrolled. All participants were biopsied before and after the gluten challenge (10 weeks, 4 grams of gluten daily). 6 healthy non-CD individuals were included as controls. Biopsies were taken on PAXgene biological fixative and embedded in paraffin and Vh/Cd ratio was assessed. RNA was extracted from the same sections and subjected to genome-wide 3’RNA-sequencing. Sequencing data was used to determine differentially expressed genes and regression model, that successfully describes the mucosal damage, was created and tested in independent material. Results: 167 differentially expressed genes were identified in healthy vs. treated CD comparisons with 117 genes downregulated and 50 genes upregulated. 415 differentially expressed genes were identified in Post gluten challenge to Treated CD comparisons with 195 genes downregulated and 220 genes upregulated. 119 genes whose expression highly correlates to Vh/Cd ratio (Spearman’s rank correlation coefficient, |rho|>0.7) were identified. Gene ontology analyses show that genes involved in cellular response to cytokines, including interferons, were over-represented. Stepwise regression allowed us computationally cut down the number of genes, that describe Vh/Cd ratio changes, to 7 and IELs number to 5. Created models describe 98.9% of observed Vh/Cd and 97.5% of IELs number variabilities; there is a strong correlation between the model’s predicted and observed ratios. Conclusions: Adoption of molecular histomorphometry, with our selected set of target genes, is quantitative and reliable way of estimating gluten-induced mucosal injury and inflammation. By including this technology one can overcome the typical shortcomings common in celiac disease diagnostics based on traditional histomorphometry analyses alone. Likewise, molecular histomorphometry is a promising instrument when incorporated in clinical trials where assessing drug efficacy on mucosal health is paramount. In addition, despite deemed healthy, based on traditional histomorphometric analyses, celiac patients on gluten free diet have significantly distinctive molecular histomorphometric pattern when compared to healthy controls.

Dataset Information

Comprehensive detection of isopeptides between human tissue transglutaminase and gluten peptides using a reciprocal proteomic approach

Publications

Comprehensive Detection of Isopeptides between Human Tissue Transglutaminase and Gluten Peptides.

Similar Datasets

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