Project description:Elysia crispata is a tropical sea slug Sacoglossa is a superorder of marine sea slugs, of which a few speciesthat can retain intracellular functional chloroplasts from their its algae prey, a mechanism termed kleptoplasty. Elysia crispata is a tropical species of Sacoglossa that can feed through this mechanism on and acquire chloroplasts from a variety of macroalgae. Thisese sea slugs, as other gastropods, produce mucus, a viscous secretion with multiple functions, such as lubrication, protection, and locomotion. This study presents the first comprehensive analysis of the mucus proteome of the sea slug E. crispata using gel electrophoresis and HPLC-MS/MS. We identified 306 proteins in the mucus secretions of this animal, despite the limited entries for E. crispata in the Uniprot database. The reproducibility of the mucus sampling technique was evaluated revealing no significant differences in protein abundance across samples. The functional annotation of the mucus proteome using Gene Ontology identified proteins involved in different functions such as hydrolase activity (molecular function), carbohydrate-derived metabolic processes (biological processes) and cytoskeletal organization (cell component). Moreover, a high proportion of proteins with enzymatic activity in the mucus of E. crispata suggests potential biotechnological applications including antimicrobial and antitumor activities. Putative antimicrobial properties are reinforced by the high abundance of hydrolases. This study also identified proteins common in mucus samples from various species, supporting a common mechanism of mucus in protecting cells and tissues while facilitating animal movement. This study highlights the need for further research to fully understand the roles of these proteins in mucus, their potential impact on animal physiology, and the influence of genetics, and environmental factors, including the type of mucus, on protein composition and relative abundance.
Project description:Purpose: Build genesets using text mining and validate the geneset with data from public repository and a dataset generated in house using in vitro models and RNA-seq Methods: Mucus hypersecretion and mucociliary dysfucntion adverse outcome pathways (AOPs) genesets were build using the text mining method described by Rani et al., 2015. Validation was performed using RNA expression data from cigarette and e-cigarette aerosol treated cells, IL-13 treated airway cells, and COPD-lung biopsies. The cigarette and e-cigarette aerosol RNA-samples from airway cells were generated and sequenced in house. The other dataset were publically available. Results: Using unsupervised clustering, the mucus hypersecretion and mucociliary dysfunction genesets were able to discriminate the cigartte treated cells from the e-cigarettes and the air control. The e-cigarette and the air control clustered together. Clustering was also observed with IL-13 treated cells. IL-13 is an induced of mucus hypersecretion. Clustering was not observed when COPD RNA-seq samples were used. PCA analysis revealed some degree of grouping based on disease status, but this was also heavily confounded by other parameters. Conclusions: Our study described the first application of text mining to build genesets relevant to AOPs. In vitro validation confirmed the genesets could discriminates between treatment that induce mucus hypersecretion phenotypes, however this could not be confirmed with COPD biopsy samples. This could be due to a series of technical confouding factors and the heterogeneity of the COPD disease.
Project description:The aim of the study is to assess the feasibility of genomic and epigenetic analysis of rectal mucus to detect non-colorectal cancers of the aero- digestive tract using samples collected by the OriCol Sampling Device.
The primary objective of the study is to assess whether significant changes in DNA mutation and methylation associated with Non-colorectal cancers of the Aero- digestive Tract (NCRCADT) can be detected in rectal mucus as shed cells and cell-free DNA (cfDNA) pass through the gut and theoretically can be collected from rectal mucus.
Secondary objectives will assess the participant acceptability of the OriCol Sampling Device for Upper GI and Lung Pathology as well as contributing to a genomic library collating information about rectal mucus.
Project description:In a healthy colon, the stratified mucus layer serves as a crucial innate immune barrier to protect the epithelium from microbes. Mucins are complex glycoproteins that serve as a nutrient source for resident microflora but can be exploited by pathogens. We aimed to understand how the intestinal pathogen, Clostridioides diffiicile, independently uses or manipulates mucus to its benefit. Using a 2-D primary human intestinal epithelial cell model to generate physiologic mucus, we assessed C. difficile-mucus interactions through growth assays, RNA-Seq, biophysical characterization of mucus, and contextualization of an established genome-scale metabolic network reconstruction (GENRE). We found that host-derived mucus promotes C. difficile growth both in vitro and in an infection model. RNA-Seq revealed significant upregulation of genes related to metabolism in response to mucus, including genes involved in sugar uptake, the Wood-Ljungdahl pathway, and the glycine cleavage system. In addition, we identified differential expression of genes related to sensing and transcriptional control. Analysis of mutants with deletions in highly upregulated genes reflected the complexity of C. difficile-mucus interactions, with potential interplay between sensing and growth. Mucus also stimulated biofilm formation in vitro, which may in turn alter viscoelastic properties of mucus. Context-specific metabolic modeling confirmed differential metabolism and predicted importance of enzymes related to serine and glycine catabolism with mucus. Subsequent growth experiments supported these findings, indicating mucus is an important source of serine. Our results better define responses of C. difficile to human gastrointestinal mucus and highlight a flexibility in metabolism that may influence pathogenesis.
Project description:A novel one-dimensional on-line pH gradient-eluted strong cation exchange (SCX)-nano-ESI-MS/MS method was developed for protein identification and tested with mixture of six standard proteins, total lysate of HuH7 and N2a cells, as well as membrane fraction of N2a cells. This method utilized an on-line nano-flow SCX column in a nano-LC system coupled with a nano-electrospray high-resolution mass spectrometer. Protein digests were separated on a nano-flow SCX column with a pH gradient and directly introduced into a mass spectrometer through nano-electrospray ionization. SCXLC-MS/MS showed identification capability for higher proportion of basic peptides compared to RPLC-MS/MS method, especially for histidine-containing peptides. Our SCXLC-MS/MS method is an excellent alternative method to the RPLC-MS/MS method for analysis of standard proteins, total cell and membrane proteomes.
Project description:Mucus is a protein-based gel secreted by specialized epithelial cells that protects the gastrointestinal mucosa from microorganism attack and irritating agents. Experiments in mice have demonstrated that when the mucosa is infected or inflamed, the mucus becomes enriched with broad-spectrum bactericidal compounds known as antimicrobial peptides (AMPs). Although AMP gene expression has been identified in both immune and epithelial cells, how inflammation regulates AMP secretion in the mucus remains unclear, and the efficacy of AMP-enriched mucus in defending against microorganisms has not been assessed. We have developed a “mucosoid” culture model that simulates the healthy human stomach epithelium. In these cultures, epithelial cells form a barrier and can differentiate into mucus-secreting cells. The accumulation of mucus on the apical side facilitates the detection of AMPs and the assessment of their bactericidal properties. We report that cytokines TNFa, IL1b and IFNg enhance the secretion of the AMPs lactotransferrin, lipocalin2, C3A, and CXCL9 into the mucus. The mucus from inflamed cells which contains the aforementioned AMPs partially kills Helicobacter pylori, the sole stomach pathogen. However, H. pylori can inhibit this defence by reducing AMP gene expression in inflamed epithelial cells. These results reveal that secreted mucus is a relevant effector of epithelial immunity but pathogens like H. pylori can subvert these defences to persist in the mucosa.
Project description:Antibiotic use is a risk factor for development of inflammatory bowel diseases (IBDs). IBDs are characterized by a damaged mucus layer, which does not properly separate the host intestinal epithelium from the microbiota. Here, we hypothesized that antibiotics might affect the integrity of the mucus barrier. By systematically determining the effects of different antibiotics on mucus layer penetrability we found that oral antibiotic treatment led to breakdown of the mucus barrier and penetration of bacteria into the mucus layer. Using fecal microbiota transplant, RNA sequencing followed by machine learning and ex vivo mucus secretion measurements, we determined that antibiotic treatment induces ER stress and inhibits colonic mucus secretion in a microbiota-independent manner. This mucus secretion flaw led to penetration of bacteria into the colonic mucus layer, translocation of microbial antigens into circulation and exacerbation of ulcerations in a mouse model of IBD. Thus, antibiotic use might predispose to development of intestinal inflammation by impeding mucus production.
Project description:Antibiotic use is a risk factor for development of inflammatory bowel diseases (IBDs). IBDs are characterized by a damaged mucus layer, which does not properly separate the host intestinal epithelium from the microbiota. Here, we hypothesized that antibiotics might affect the integrity of the mucus barrier. By systematically determining the effects of different antibiotics on mucus layer penetrability we found that oral antibiotic treatment led to breakdown of the mucus barrier and penetration of bacteria into the mucus layer. Using fecal microbiota transplant, RNA sequencing followed by machine learning and ex vivo mucus secretion measurements, we determined that antibiotic treatment induces ER stress and inhibits colonic mucus secretion in a microbiota-independent manner. This mucus secretion flaw led to penetration of bacteria into the colonic mucus layer, translocation of microbial antigens into circulation and exacerbation of ulcerations in a mouse model of IBD. Thus, antibiotic use might predispose to development of intestinal inflammation by impeding mucus production.