Overexpression of the transmembrane mucin MUC13, as seen in inflammatory bowel diseases (IBD), could potentially impact barrier function. This study aimed to explore how inflammation-induced MUC13 disrupts epithelial barrier integrity by affecting junctional protein expression in IBD, thereby also considering the involvement of MUC1. RNA sequencing and permeability assays were performed using LS513 cells transfected with MUC1 and MUC13 siRNA and subsequently stimulated with IL-22. In vivo intestinal permeability and MUC13-related signaling pathways affecting barrier function were investigated in acute and chronic DSS-induced colitis wildtype and Muc13^−/− mice. Finally, the expression of MUC13, its regulators and other barrier mediators were studied in IBD and control patients. Mucin knockdown in intestinal epithelial cells affected gene expression of several barrier mediators in the presence/absence of inflammation. IL-22-induced MUC13 expression impacted barrier function by modulating the JAK1/STAT3, SNAI1/ZEB1 and ROCK2/MAPK signaling pathways, with a cooperating role for MUC1. In response to DSS, MUC13 was protective during the acute phase whereas it caused more harm upon chronic colitis. The pathways accounting for the MUC13-mediated barrier dysfunction were also altered upon inflammation in IBD patients. These novel findings indicate an active role for aberrant MUC13 signaling inducing intestinal barrier dysfunction upon inflammation with MUC1 as collaborating partner.

Microbiome analysis has become a crucial tool for basic and translational research due to its potential for translation into clinical practice. However, there is ongoing controversy regarding the comparability of different bioinformatic analysis platforms and a lack of recognized standards, which might have an impact on the translational potential of results. This study investigates how the performance of different microbiome analysis platforms impacts the final results of mucosal microbiome signatures. Across five independent research groups, we compared three distinct and frequently used microbiome analysis bioinformatic packages (DADA2, MOTHUR, and QIIME2) on the same subset of fastQ files. The source data set encompassed 16S rRNA gene raw sequencing data (V1–V2) from gastric biopsy samples of clinically well-defined gastric cancer (GC) patients ( n = 40; with and without Helicobacter pylori [ H. pylori ] infection) and controls ( n = 39, with and without H. pylori infection). Independent of the applied protocol, H. pylori status, microbial diversity and relative bacterial abundance were reproducible across all platforms, although differences in performance were detected. Furthermore, alignment of the filtered sequences to the old and new taxonomic databases (i.e., Ribosomal Database Project, Greengenes, and SILVA) had only a limited impact on the taxonomic assignment and thus on global analytical outcomes. Taken together, our results clearly demonstrate that different microbiome analysis approaches from independent expert groups generate comparable results when applied to the same data set. This is crucial for interpreting respective studies and underscores the broader applicability of microbiome analysis in clinical research, provided that robust pipelines are utilized and thoroughly documented to ensure reproducibility. IMPORTANCE: Microbiome analysis is one of the most important tools for basic and translational research due to its potential for translation into clinical practice. However, there is an ongoing controversy about the comparability of different bioinformatic analysis platforms and a lack of recognized standards. In this study, we investigate how the performance of different microbiome analysis platforms affects the final results of mucosal microbiome signatures. Five independent research groups used three different and commonly used bioinformatics packages for microbiome analysis on the same data set and compared the results. This data set included microbiome sequencing data from gastric biopsy samples of GC patients. Regardless of the protocol used, Helicobacter pylori status, microbial diversity, and relative bacterial abundance were reproducible across all platforms. The results show that different microbiome analysis approaches provide comparable results. This is crucial for the interpretation of corresponding studies and underlines the broader applicability of microbiome analysis.

Background: The intestinal mucosal barrier plays an important role in the pathophysiology of inflammatory bowel disease (IBD), with mucins being key components of this barrier. Classified as either transmembrane or secreted, these highly glycosylated proteins protect the mucosal barrier while also influencing barrier integrity. Given their indispensable role in maintaining the intestinal mucosal barrier, mucins are compelling candidates for the evaluation of barrier dysfunction. Numerous studies have investigated mucins in the context of IBD, but a clear consensus regarding their expression, polymorphisms, and post-translational modifications is missing. This systematic review summarizes mucin alterations at the transcriptional, translational, and post-translational levels in the presence/absence of intestinal inflammation in IBD patients. Methods: To this end, PubMed, Scopus, and Web of Science were searched for studies published between February 1993 and January 2025, yielding 69 articles eligible for inclusion. Results: The expression of MUC1, MUC5AC, and MUC6 was reported to be upregulated at both RNA (isoform) and protein level, in contrast to MUC12, which exhibited reduced expression in inflamed mucosa only at RNA isoform level. MUC2 was the only mucin consistently downregulated at the protein level, despite unchanged mRNA expression, whereas polymorphisms of MUC2, MUC3A, MUC4, MUC13, MUC19, MUC21, and MUC22 were associated with susceptibility to Crohn’s disease, ulcerative colitis, or IBD in general. Post-translational modifications, such as hypoglycosylation of MUC1 and MUC2, as well as a reduction of mucin sulphation of MUC2 were reported. Conclusion: Together, these findings underscore the involvement of mucins in IBD and point to their potential as biomarkers for barrier dysfunction.