Integrated gut metabolome and microbiome fingerprinting reveals that dysbiosis precedes allergic inflammation in IgE-mediated pediatric cow's milk allergy.

BACKGROUND: IgE-mediated cow's milk allergy (IgE-CMA) is one of the first allergies to arise in early childhood and may result from exposure to various milk allergens, of which ß-lactoglobulin (BLG) and casein are the most important. Understanding the underlying mechanisms behind IgE-CMA is imperative for the discovery of novel biomarkers and the design of innovative treatment and prevention strategies. METHODS: We report a longitudinal in vivo murine model, in which two mice strains (BALB/c and C57Bl/6) were sensitized to BLG using either cholera toxin or an oil emulsion (n = 6 per group). After sensitization, mice were challenged orally, their clinical signs monitored, antibody (IgE and IgG1) and cytokine levels (IL-4 and IFN-γ) measured, and fecal samples subjected to metabolomics. The results of the murine models were further extrapolated to fecal microbiome-metabolome data from our population of IgE-CMA (n = 22) and healthy (n = 23) children (Trial: NCT04249973), on which polar metabolomics, lipidomics and 16S rRNA metasequencing were performed. In vitro gastrointestinal digestions and multi-omics corroborated the microbial origin of proposed metabolic changes. RESULTS: During mice sensitization, we observed multiple microbially derived metabolic alterations, most importantly bile acid, energy and tryptophan metabolites, that preceded allergic inflammation. We confirmed microbial dysbiosis, and its associated effect on metabolic alterations in our patient cohort, through in vitro digestions and multi-omics, which was accompanied by metabolic signatures of low-grade inflammation. CONCLUSION: Our results indicate that gut dysbiosis precedes allergic inflammation and nurtures a chronic low-grade inflammation in children on elimination diets, opening important new opportunities for future prevention and treatment strategies.

A comprehensive metabolite fingerprint of fibrostenosis in patients with Crohn's disease.

Intestinal fibrostenosis in patients with Crohn's disease (CD) is a common and untreatable comorbidity that is notoriously difficult to monitor. We aimed to find metabolites associated with the presence of fibrostenosis in patients with CD using targeted and untargeted metabolomics analyses of serum and primary cell cultures using hyphenated ultra-high performance liquid chromatography high-resolution mass spectrometry. Targeted metabolomics revealed 11 discriminating metabolites in serum, which were enriched within the arginine and proline metabolism pathway. Based on untargeted metabolomics and discriminant analysis, 166 components showed a high predictive value. In addition, human intestinal fibroblasts isolated from stenotic tissue were characterized by differential levels of medium-chain dicarboxylic acids, which are proposed as an energy source through beta-oxidation, when oxidative phosphorylation is insufficient. Another energy providing pathway in such situations is anaerobic glycolysis, a theory supported by increased expression of hexokinase 2 and solute carrier family 16 member 1 in stenotic fibroblasts. Of interest, four (unannotated) metabolic components showed a negative correlation with hexokinase 2 gene expression. Together, this study provides a discriminative metabolic fingerprint in the serum and in intestinal fibroblasts of stenotic and non-stenotic patients with CD suggestive for increased production of building blocks for collagen synthesis and increased glycolysis.

Point-of-care applicable metabotyping using biofluid-specific electrospun MetaSAMPs directly amenable to ambient LA-REIMS.

In recent years, ambient ionization mass spectrometry (AIMS) including laser ablation rapid evaporation IMS, has enabled direct biofluid metabolome analysis. AIMS procedures are, however, still hampered by both analytical, i.e., matrix effects, and practical, i.e., sample transport stability, drawbacks that impede metabolome coverage. In this study, we aimed at developing biofluid-specific metabolome sampling membranes (MetaSAMPs) that offer a directly applicable and stabilizing substrate for AIMS. Customized rectal, salivary, and urinary MetaSAMPs consisting of electrospun (nano)fibrous membranes of blended hydrophilic (polyvinylpyrrolidone and polyacrylonitrile) and lipophilic (polystyrene) polymers supported metabolite absorption, adsorption, and desorption. Moreover, MetaSAMP demonstrated superior metabolome coverage and transport stability compared to crude biofluid analysis and was successfully validated in two pediatric cohorts (MetaBEAse, n = 234 and OPERA, n = 101). By integrating anthropometric and (patho)physiological with MetaSAMP-AIMS metabolome data, we obtained substantial weight-driven predictions and clinical correlations. In conclusion, MetaSAMP holds great clinical application potential for on-the-spot metabolic health stratification.

Rapid ex vivo molecular fingerprinting of biofluids using laser-assisted rapid evaporative ionization mass spectrometry.

Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO2 laser) and with automation for high-throughput analysis. Laser-induced sample evaporation occurs within seconds through radiative heating with the plume guided to the MS instrument. The presented procedure includes (i) laser setup with automation, (ii) analysis of biofluids (blood/urine/stool/saliva/sputum/breast milk) and (iii) data analysis. We provide the optimal settings for biofluid analysis and quality control, enabling sensitive, precise and robust analysis. Using the automated setup, 96 samples can be analyzed in ~35-40 min per ionization mode, with no intervention required. Metabolic fingerprints are made up of 2,000-4,000 features, for which relative quantification can be achieved at high repeatability when total ion current normalization is applied. With saliva and feces as example matrices, >70% of features had a coefficient of variance ≤30%. However, to achieve acceptable long-term reproducibility, additional normalizations by, e.g., LOESS are recommended, especially for positive ionization.

Disparities in the gut metabolome of post-operative Hirschsprung's disease patients.

Hirschsprung's disease (HD) is a congenital structural abnormality of the colon seen in approximately 1 to 5000 live births. Despite surgical correction shortly after presentation, up to 60% of patients will express long-term gastrointestinal complaints, including potentially life-threatening Hirschsprung-associated enterocolitis (HAEC). In this study fecal samples from postoperative HD patients (n = 38) and their healthy siblings (n = 21) were analysed using high-resolution liquid chromatography-mass spectrometry aiming to further unravel the nature of the chronic gastrointestinal disturbances. Furthermore, within the patient group, we compared the faecal metabolome between patients with and without a history of HAEC as well as those diagnosed with short or long aganglionic segment. Targeted analysis identified several individual metabolites characteristic for all HD patients as well as those with a history of HAEC and long segment HD. Moreover, multivariate models based on untargeted data established statistically significant (p < 0.05) differences in comprehensive faecal metabolome in the patients' cohort as a whole and in patients with a history of HAEC. Pathway analysis revealed the most impact on amino sugar, lysine, sialic acid, hyaluronan and heparan sulphate metabolism in HD, as well as impaired tyrosine metabolism in HAEC group. Those changes imply disruption of intestinal mucosal barrier due to glycosaminoglycan breakdown and dysbiosis as major metabolic changes in patients' group and should be further explored for potential diagnostic or treatment targets.

Rapid LA-REIMS and comprehensive UHPLC-HRMS for metabolic phenotyping of feces.

Ambient ionization-based techniques hold great potential for rapid point-of-care applicable metabolic fingerprinting of tissue and fluids. Hereby, feces represents a unique biospecimen as it integrates the complex interactions between the diet, gut microbiome and host, and is therefore ideally suited to study the involvement of the diet-gut microbiome axis in metabolic diseases and their treatments at a molecular level. We present a new method for rapid (<10 s) metabolic fingerprinting of feces, i.e. laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) with an Nd:YAG laser (2940 nm) and quadrupole Time-of-Flight mass spectrometer as main components. The LA-REIMS method was implemented on mimicked crude feces samples from individuals that were assigned a state of type 2 diabetes or euglycaemia. Based on the generated fingerprints, enclosing 4923 feature ions, significant segregation according to disease classification was achieved through orthogonal partial least squares discriminant analysis (Q2(Y) of 0.734 and p-value of 1.93e-17) and endorsed by a general classification accuracy of 90.5%. A comparison between the discriminative performance of the novel LA-REIMS and our established ultra-high performance liquid-chromatography high-resolution MS (UHPLC-HRMS) metabolomics and lipidomics methodologies for fingerprinting of stool was performed. Based on the supervised modelling results upon UHPLC-HRMS (Q2(Y) ≥ 0.655 and p-value ≤ 4.11 e-5), equivalent or better discriminative performance of LA-REIMS fingerprinting was concluded. Eventually, comprehensive UHPLC-HRMS was employed to assess metabolic alterations as observed for the defined classes, whereby metformin treatment of the type 2 diabetes patients was considered a relevant study factor to acquire new mechanistic insights. More specifically, ten metabolization products of metformin were identified, with (hydroxylated) triazepinone and metformin-cholesterol reported for the first time in vivo.In conclusion, LA-REIMS was established as an expedient strategy for rapid metabolic fingerprinting of feces, whereby potential implementations may relate, but are not limited to differential diagnosis and treatment efficacy evaluation of metabolic diseases. Yet, LC-HRMS remains essential for in-depth biological interpretation.