In this work, the enzyme aldehyde reductase, also known as aldose reductase, was synthesized and cloned from a human gene. Spectrophotometric measurements show that in presence of the nicotinamide adenine dinucleotide phosphate cofactor (NADPH), the aldehyde reductase catalyzed the reduction of glucose to sorbitol. Electrochemical measurements performed on an electrodeposited poly(methylene green)-modified gold electrode showed that in the presence of the enzyme aldehyde reductase, the electrocatalytic oxidation current of NADPH decreased drastically after the addition of glucose. These results demonstrate that aldehyde reductase is an enzyme that allows the construction of an efficient electrochemical glucose biosensor based on glucose reduction.

Because accessing the small intestine is technically challenging, studies of the small intestinal microbiome are predominantly conducted in patients rather than in healthy individuals. Invasive clinical procedures, such as endoscopy or surgery, usually performed for therapeutic purposes, are typically required for sample collection. Although stomas offer a less invasive means for repeated sampling, their use remains restricted to patient populations. As a result, the small intestinal microbiome of healthy individuals remains largely understudied. This study evaluated a novel ingestible medical device for collecting luminal samples from the small intestine. A monocentric interventional trial (NCT05477069) was conducted on 15 healthy subjects. Metagenomics, metabolomics, and culturomics were used to assess the effectiveness of the medical device in characterizing the healthy small intestinal microbiome and identifying potential biomarkers. The small intestinal microbiota differed significantly from the fecal microbiota, displaying high inter-individual variability, lower species richness and reduced alpha diversity. A combined untargeted and semi-targeted LC–MS/MS metabolomics approach identified a distinct small intestinal metabolic footprint, with bile acids and amino acids being the most abundant metabolite classes. Host- and host/microbe-derived bile acids were particularly abundant in small intestinal samples. Using a fast culturomics approach on two small intestinal samples, we achieved species-level characterization and identified 90 bacterial species, including five potentially novel ones. This study demonstrates the efficacy of our novel sampling device in enabling comprehensive small intestinal microbiome analysis through an integrative, multi-omics approach. This approach allows distinct microbiome signatures to be identified between small intestinal and fecal samples.

The connection between imbalances in the human gut microbiota, known as dysbiosis, and various diseases has been well established. Current techniques for sampling the small intestine are both invasive for patients and costly for healthcare facilities. Most studies on human gut microbiome are conducted using faecal samples, which do not accurately represent the microbiome in the upper intestinal tract. A pilot clinical investigation, registered as NCT05477069 and sponsored by the Grenoble Alpes University Hospital, is currently underway to evaluate a novel ingestible medical device (MD) designed for collecting small intestinal liquids by Pelican Health. This study is interventional and monocentric, involving 15 healthy volunteers. The primary objective of the study is to establish the safety and the performance of the MD when used on healthy volunteers. Secondary objectives include assessing the device’s performance and demonstrating the difference between the retrieved sample from the MD and the corresponding faecal sample. Multi-omics analysis will be performed, including metagenomics, metabolomics, and culturomics. We anticipate that the MD will prove to be safe without any reported adverse effects, and we collected samples suitable for the proposed omics analyses in order to demonstrate the functionality of the MD and the clinical potential of the intestinal content.

Bile acids are essential steroids regulating immunity, nutrient absorption, insulin, appetite, and body temperature. Their structural diversity is vast, but due to spectral similarities, MS/MS spectral matching often fails to resolve isomers. This study introduces a proof-of-concept workflow using a mass spectrometry query language filtering tree that distinguishes isomeric bile acids in untargeted LC-MS/MS data. Its application revealed a deoxycholyl-2-aminophenol amidate linked to whole grain consumption.

The gut microbiome is a complex ecosystem varying along different gut sections, consisting of metabolites from food, host, and microbes. Microbially-derived metabolites like bile acids and short-chain fatty acids interact with host physiology. Current studies often use fecal samples, which don’t fully represent the upper gut due to stratification. To sample the proximal gut microbiome, endoscopic methods or new non-invasive devices are used. We developed an approach combining untargeted and semi-targeted metabolomics using a Q-Exactive Plus Orbitrap mass spectrometer to profile gut metabolites. We initially selected 49 key metabolites based on specific criteria, validated them through repeatability tests, and created a compound database with TraceFinder software. Our workflow enables molecule annotation in untargeted studies while validating 37 metabolites in semitargeted analyses. This method, applied to clinical trial samples ( NCT05477069 ), shows promise in discovering new gut metabolites. Highlights: Innovative Combined Metabolomics Workflow: The study introduces a combined approach that integrates semi-targeted and untargeted metabolomics analyses to characterized small intestinal and fecal metabolomes. This method allows for the relative quantification of carefully selected metabolites and the reanalysis of these metabolites using evolving curated databases, enhancing the understanding of the gut microbiome-health axis. Untargeted Metabolomics Strategy: The untargeted approach aims to determine the global metabolic profile of samples and discover new metabolites. This involves processing data through a detailed pipeline, statistical analysis, and feature annotation using tools like MZmine, MetaboAnalyst, and the GNPS platform. Proof of Concept on Clinical Samples: The combined approach was tested on clinical samples from a participant in a clinical trial, revealing distinct metabolomes between small intestinal content and fecal samples. This proof of concept demonstrated the method’s ability to identify and quantify metabolites, showing significant differences in metabolite abundance between the two sample types and highlighting the potential for discovering new bile acids through molecular networking.