Preliminary Comparison of Endoscopic Brush and Net Catheters as the Sampling Tool to Analyze the Intestinal Mucus in the Rectum with Ulcerative Colitis Patients

Machine learning-assisted label-free colorectal cancer diagnosis using plasmonic needle-endoscopy system

Early and accurate detection of colorectal cancer (CRC) is critical for improving patient outcomes. Existing diagnostic techniques are often invasive and carry risks of complications. Herein, we introduce a plasmonic gold nanopolyhedron (AuNH)-coated needle-based surface-enhanced Raman scattering (SERS) sensor, integrated with endoscopy, for direct mucus sampling and label-free detection of CRC. The thin and flexible stainless-steel needle is coated with polymerized dopamine, which serves as an adhesive layer and simultaneously initiates the nucleation of gold nanoparticle (AuNP) seeds on the needle surface. The AuNP seeds are further grown through a surface-directed reduction using Au ions-hydroxylamine hydrochloride solution, resulting in the formation of dense AuNHs. The formation mechanism of AuNHs and the layered structure of the plasmonic needle-based SERS (PNS) sensor are thoroughly analyzed. Furthermore, a strong field enhancement of the PNS sensor is observed, amplified around the edges of the polyhedral shapes and at nanogap sites between AuNHs. The feasibility of the PNS sensor combined with endoscopy system is further investigated using mouse models for direct colonic mucus sampling and verifying noninvasive label-free classification of CRC from normal controls. A logistic regression-based machine learning method is employed and successfully differentiates CRC and normal mice, achieving 100% sensitivity, 93.33% specificity, and 96.67% accuracy. Moreover, Raman profiling of metabolites and their correlations with Raman signals of mucus samples are analyzed using the Pearson correlation coefficient, offering insights for identifying potential cancer biomarkers. The developed PNS-assisted endoscopy technology is expected to advance the early screening and diagnosis approach of CRC in the future.

The emerging role of the gut microbiota and its application in inflammatory bowel disease

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is a complex disorder with an unknown cause. However, the dysbiosis of the gut microbiome has been found to play a role in IBD etiology, including exacerbated immune responses and defective intestinal barrier integrity. The gut microbiome can also be a potential biomarker for several diseases, including IBD. Currently, conventional treatments targeting pro-inflammatory cytokines and pathways in IBD-associated dysbiosis do not yield effective results. Other therapies that directly target the dysbiotic microbiome for effective outcomes are emerging. We review the role of the gut microbiome in health and IBD and its potential as a diagnostic, prognostic, and therapeutic target for IBD. This review also explores emerging therapeutic advancements that target gut microbiome-associated alterations in IBD, such as nanoparticle or encapsulation delivery, fecal microbiota transplantation, nutritional therapies, microbiome/probiotic engineering, phage therapy, mesenchymal stem cells (MSCs), gut proteins, and herbal formulas.

Analysis of Neuropeptides in the Intestinal Mucus of Patients with Ulcerative Colitis Using RNA Sequencing

INTRODUCTION

Inflammation in ulcerative colitis (UC) originates in the colorectal mucosa. Transcriptome sequencing analysis of the colorectal mucosa allows the identification of potential neuropeptides related to local neurotransmission. The intestinal mucus lining the surface of the mucosa may harbor biomarkers of mucosal inflammation; however, this has not been sufficiently investigated, given the difficulty in obtaining human samples. We previously reported the feasibility of obtaining mucin samples for proteomic analysis by brushing during colonoscopy. Herein, we aimed to investigate the composition of the intestinal mucus and detect neuropeptides characteristic of UC.

METHODS

Mucus and mucosal samples were collected from patients with UC from the colorectum in areas showing remission or active UC using a brush catheter and biopsy forceps during colonoscopy. RNA sequencing findings of mucus samples of active and remission areas were compared. RNA and protein expression levels of significantly upregulated neuropeptides were analyzed.

RESULTS

Of the neuropeptides associated with UC, somatostatin (SST) was significantly elevated in areas of remission, according to RNA sequencing results of mucus and expression levels in mucus RNA and proteins. Conversely, SST expression in the mucosa was increased in the inflamed areas. Flow cytometry revealed that the fluorescence intensity of SST-positive cells in the remission zone was higher in the mucus than in the mucosa.

CONCLUSION

SST expression in the mucus is considered to be an important factor associated with UC activity.

Hydrogel-Integrated Millifluidic Systems: Advancing the Fabrication of Mucus-Producing Human Intestinal Models

The luminal surface of the intestinal epithelium is protected by a vital mucus layer, which is essential for lubrication, hydration, and fostering symbiotic bacterial relationships. Replicating and studying this complex mucus structure in vitro presents considerable challenges. To address this, we developed a hydrogel-integrated millifluidic tissue chamber capable of applying precise apical shear stress to intestinal models cultured on flat or 3D structured hydrogel scaffolds with adjustable stiffness. The chamber is designed to accommodate nine hydrogel scaffolds, 3D-printed as flat disks with a storage modulus matching the physiological range of intestinal tissue stiffness (~3.7 kPa) from bioactive decellularized and methacrylated small intestinal submucosa (dSIS-MA). Computational fluid dynamics simulations were conducted to confirm a laminar flow profile for both flat and 3D villi-comprising scaffolds in the physiologically relevant regime. The system was initially validated with HT29-MTX seeded hydrogel scaffolds, demonstrating accelerated differentiation, increased mucus production, and enhanced 3D organization under shear stress. These characteristic intestinal tissue features are essential for advanced in vitro models as they critically contribute to a functional barrier. Subsequently, the chamber was challenged with human intestinal stem cells (ISCs) from the terminal ileum. Our findings indicate that biomimicking hydrogel scaffolds, in combination with physiological shear stress, promote multi-lineage differentiation, as evidenced by a gene and protein expression analysis of basic markers and the 3D structural organization of ISCs in the absence of chemical differentiation triggers. The quantitative analysis of the alkaline phosphatase (ALP) activity and secreted mucus demonstrates the functional differentiation of the cells into enterocyte and goblet cell lineages. The millifluidic system, which has been developed and optimized for performance and cost efficiency, enables the creation and modulation of advanced intestinal models under biomimicking conditions, including tunable matrix stiffness and varying fluid shear stresses. Moreover, the readily accessible and scalable mucus-producing cellular tissue models permit comprehensive mucus analysis and the investigation of pathogen interactions and penetration, thereby offering the potential to advance our understanding of intestinal mucus in health and disease.

Composition and diverse differences of intestinal microbiota in ulcerative colitis patients

Objective

To explore the composition of the intestinal microbiota in ulcerative colitis (UC) patients and to identify differences in the microbiota between patients with active disease and those in remission.

Methods

Between September 2020 and June 2021, we enrolled into our study, and collected stool samples from, patients with active UC or in remission and healthy control subjects. The diagnosis of UC was based on clinical, endoscopic, radiological, and histological findings. The composition of the intestinal microbiota was determined by sequencing of the 16S rRNA V3–V4 region and by bioinformatic methods. The functional composition of the intestinal microbiota was predicted using PICRUSt 2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) software.

Results

We found that the intestinal flora was significantly less rich and diverse in UC patients than in healthy control subjects. Beta diversity analysis revealed notable differences in the intestinal flora compositions among the three groups, but there was no statistical difference in alpha diversity between UC patients with active disease and those in remission. At the phylum level, the relative abundances of Proteobacteria and Patescibacteria were significantly higher, and the relative abundances of Desulfobacterota and Verrucomicrobiota were lower, in UC patients with active disease than in the healthy control group. Higher levels of potential pathogens and lower levels of butyrate-producing bacteria were also detected in UC patients with active disease. Linear discriminant analysis Effect Size (LefSe) revealed that 71 bacterial taxa could serve as biomarkers, with 26 biomarkers at the genus level. In addition, network analysis showed that there was a positive correlation between Roseburia and Lachnospira. Functional predictions indicated that gene functions involving the metabolism of some substances, such as methane, lipopolysaccharide, geraniol, and ansamycins, were significantly different among the three groups.

Conclusion

The richness and diversity of the intestinal microbiota differed significantly among the three groups. Richness describes the state of being rich in number of intestinal bacteria, whereas diversity is the number of different species of intestinal bacteria. Different bacterial taxa could be used as biomarkers, expanding our understanding of the relationship between the intestinal microbiota microenvironment and UC in the future.