Medicina

Background: The pathological mechanism of the gastrointestinal forms of food aller-gies is less understood in comparison to other clinical phenotypes, such as asthmaand anaphylaxis Importantly, high-IgE levels are a poor prognostic factor in gastroin-testinal allergies.Methods: This study investigated how high-IgE levels influence the development ofintestinal inflammation and the metabolome in allergic enteritis (AE), using IgE knock-in (IgEki) mice expressing high levels of IgE. In addition, correlation of the altered me-tabolome with gut microbiome was analysed.Results: Ovalbumin-sensitized and egg-white diet-fed (OVA/EW) BALB/c WT micedeveloped moderate AE, whereas OVA/EW IgEki mice induced more aggravated in-testinal inflammation with enhanced eosinophil accumulation. Untargeted metabo-lomics detected the increased levels of N-tau-methylhistamine and 2,3-butanediol,and reduced levels of butyric acid in faeces and/or sera of OVA/EW IgEki mice, whichwas accompanied with reduced Clostridium and increased Lactobacillus at the genus level. Non-sensitized and egg-white diet-fed (NC/EW) WT mice did not exhibit anysigns of AE, whereas NC/EW IgEki mice developed marginal degrees of AE. Comparedto NC/EW WT mice, enhanced levels of lysophospholipids, sphinganine and sphin-gosine were detected in serum and faecal samples of NC/EW IgEki mice. In addi-tion, several associations of altered metabolome with gut microbiome—for exampleAkkermansia with lysophosphatidylserine—were detected.Conclusions: Our results suggest that high-IgE levels alter intestinal and systemic levelsof endogenous and microbiota-associated metabolites in experimental AE. This studycontributes to deepening the knowledge of molecular mechanisms for the developmentof AE and provides clues to advance diagnostic and therapeutic strategies of allergicdiseases

Omics strategies have triggered a revolution in the understanding of the microorganisms that reside in our body, and their implications in health and disease. For diagnosis and therapeutics, metabolomic fingerprinting is the most powerful approach, since the metabolites represent the actual interplay between humans and microbes. Studying the metabolome requires several new high-throughput analytical techniques and innovative computational methodologies. Herein, we will focus on the metabolomics workflow for gut microbiota analysis, including sampling, laboratory procedures, and available analytical techniques, paying special attention to microbiota isolation and multiplatform complementarity. Finally, we will summarize some applications and implications of gut microbiota metabolites in biomarkers discovery and several therapeutic strategies, such as fecal microbiota transplantation and the usage of prebiotics and probiotics.

GC-MS for untargeted metabolomics is a well-established technique. Small molecules and molecules made volatile by derivatization can be measured and those compounds are key players in main biological pathways. This tutorial provides ready-to-use protocols for GC-MS-based metabolomics, using either the well-known low-resolution approach (GC-Q-MS) with nominal mass or the more recent high-resolution approach (GC-QTOF-MS) with accurate mass, discussing their corresponding strengths and limitations. Analytical procedures are covered for different types of biofluids (plasma/serum, bronchoalveolar lavage, urine, amniotic fluid) tissue samples (brain/hippocampus, optic nerve, lung, kidney, liver, pancreas) and samples obtained from cell cultures (adipocytes, macrophages, Leishmania promastigotes, mitochondria, culture media). Together with the sample preparation and data acquisition, data processing strategies are described specially focused on Agilent equipments, including deconvolution software and database annotation using spectral libraries. Manual curation strategies and quality control are also deemed. Finally, considerations to obtain a semiquantitative value for the metabolites are also described. As a case study, an illustrative example from one of our experiments at CEMBIO Research Centre, is described and findings discussed.

Composition of the gut microbiota changes during ageing, but questions remain about whether age is also associated with deficits in microbiome function and whether these changes occur sharply or progressively. The ability to define these deficits in populations of different ages may help determine a chronological age threshold at which deficits occur and subsequently identify innovative dietary strategies for active and healthy ageing. Here, active gut microbiota and associated metabolic functions were evaluated using shotgun proteomics in three well‐defined age groups consisting of 30 healthy volunteers, namely, ten infants, ten adults and ten elderly individuals. Samples from each volunteer at intervals of up to 6 months (n = 83 samples) were used for validation. Ageing gradually increases the diversity of gut bacteria that actively synthesize proteins, that is by 1.4‐fold from infants to elderly individuals. An analysis of functional deficits consistently identifies a relationship between tryptophan and indole metabolism and ageing (p < 2.8e−8). Indeed, the synthesis of proteins involved in tryptophan and indole production and the faecal concentrations of these metabolites are directly correlated (r2 > .987) and progressively decrease with age (r2 > .948). An age threshold for a 50% decrease is observed ca. 11–31 years old, and a greater than 90% reduction is observed from the ages of 34–54 years. Based on recent investigations linking tryptophan with abundance of indole and other “healthy” longevity molecules and on the results from this small cohort study, dietary interventions aimed at manipulating tryptophan deficits since a relatively “young” age of 34 and, particularly, in the elderly are recommended.

Cow’s milk allergy (CMA) is one of the most prevalent food allergies in children. Several studies have demonstrated that gut microbiota influences the acquisition of oral tolerance to food antigens at initial stages of life. Changes in the gut microbiota composition and/or functionality (i.e., dysbiosis) have been linked to inadequate immune system regulation and the emergence of pathologies. Moreover, omic sciences have become an essential tool for the analysis of the gut microbiota. On the other hand, the use of fecal biomarkers for the diagnosis of CMA has recently been reviewed, with fecal calprotectin, -1 antitrypsin, and lactoferrin being the most relevant. This study aimed at evaluating functional changes in the gut microbiota in the feces of cow’s milk allergic infants (AI) compared to control infants (CI) by metagenomic shotgun sequencing and at correlating these findings with the levels of fecal biomarkers ( -1 antitrypsin, lactoferrin, and calprotectin) by an integrative approach. We have observed differences between AI and CI groups in terms of fecal protein levels and metagenomic analysis. Our findings suggest that AI have altered glycerophospholipid metabolism as well as higher levels of lactoferrin and calprotectin that could be explained by their allergic status.