RESUMEN
Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.
Asunto(s)
Trasplante de Microbiota Fecal , Heces , Metaboloma , Metabolómica , Espectrometría de Masas en Tándem , Humanos , Heces/microbiología , Heces/química , Cromatografía Liquida/métodos , Metabolómica/métodos , Espectrometría de Masas en Tándem/métodos , Infecciones por Clostridium/microbiología , Infecciones por Clostridium/metabolismo , Clostridioides difficile/metabolismo , Ácidos y Sales Biliares/metabolismo , Ácidos y Sales Biliares/análisis , Cromatografía Líquida con Espectrometría de MasasRESUMEN
BACKGROUND AND AIMS: Alpha-gal allergy causes a delayed reaction to mammalian meats and has been reported worldwide. Patients with the allergy may present with isolated gastrointestinal (GI) symptoms, but this phenotype is poorly understood. METHODS: We pooled and analyzed symptoms and demographics of patients from two prospective cohorts of patients with a diagnosis of alpha-gal allergy who reacted after eating mammalian meat under observation. We compared the characteristics of patients who demonstrated GI-isolated symptoms on a challenge with those who exhibited symptoms outside the GI tract (skin, respiratory, and circulatory). RESULTS: Among the 91 children and adult alpha-gal allergic patients who exhibited symptoms after oral challenge with mammalian meat, 72.5% experienced GI distress with one or more GI symptoms, which was the most frequent class of symptoms, compared with skin changes in 57.1% and respiratory distress in 5.5%. The most common GI symptoms were abdominal pain (71%) and vomiting (22.0%). GI-isolated symptoms occurred in 37 patients (40.7%) who reacted, and those patients reacted more quickly than patients who exhibited systemic symptoms (median onset of symptoms in GI-isolated group 90 min vs 120 min) and were more likely to be children than adults (relative risk=1.94, 95% CI: 1.04-3.63). CONCLUSIONS: Isolated-GI distress occurred in 4 in every 10 alpha-gal allergic individuals who developed symptoms on oral food challenge with mammalian meat. Alpha-gal allergic patients, particularly children, may exhibit GI distress alone, and adult and pediatric gastroenterologists should be aware of the diagnosis and management of the allergy.
Asunto(s)
Dispepsia , Hipersensibilidad a los Alimentos , Adulto , Niño , Animales , Humanos , Estudios Prospectivos , Inmunoglobulina E , Hipersensibilidad a los Alimentos/diagnóstico , Carne/efectos adversos , MamíferosRESUMEN
Recurrent C. difficile infection (rCDI) is an urgent public health threat for which the last resort and lifesaving treatment is a fecal microbiota transplant (FMT). However, the exact mechanisms which mediate a successful FMT are not well understood. Here we use longitudinal stool samples collected from patients undergoing FMT to evaluate changes in the microbiome, metabolome, and lipidome after successful FMTs. We show changes in the abundance of many lipids, specifically acylcarnitines and bile acids, in response to FMT. These changes correlate with Enterobacteriaceae, which encode carnitine metabolism genes, and Lachnospiraceae, which encode bile salt hydrolases and baiA genes. LC-IMS-MS revealed a shift from microbial conjugation of primary bile acids pre-FMT to secondary bile acids post-FMT. Here we define the structural and functional changes in successful FMTs. This information will help guide targeted Live Biotherapeutic Product development for the treatment of rCDI and other intestinal diseases.
RESUMEN
Background and Aims: Fecal microbiota transplant (FMT) via colonoscopy is highly effective treatment for Clostridioides difficile infection (CDI). We aimed to determine baseline patient characteristics that predict failure to respond to colonoscopy-based FMT. Methods: We evaluated adult patients who received FMT for CDI not responding to standard therapies at a single tertiary center between 2014 and 2018 in this retrospective cohort study. We defined clinical success as formed stool or C difficile-negative diarrhea at 2 months after FMT. If patients required a second FMT, follow-up was extended 2 months after repeat infusion. We performed multivariate logistic regression and a random forest model to identify variables predictive of response to FMT. Results: Clinical success was attained in 87.3% of 103 patients who underwent FMT for CDI. In the multivariate model, the odds of FMT failure for family donation compared with stool bank were odds ratio 4.13 (1.00-7.01 P = .049). Diarrhea while taking anti-CDI antibiotics was common (37.8% of patients) and did not predict failure (odds ratio 0.64, 0.19-2.11 P = .46) in the univariate model. A machine learning model to predict response using clinical factors only achieved a sensitivity of 70%, specificity of 77%, and negative predictive value of 96%. Conclusion: Colonoscopy-based FMT was highly effective for CDI, even in a population where immunosuppression and proton pump inhibitor use were common. Family stool donation was associated with FMT failure, compared with the use of a stool bank. The study suggests that the use of a stool bank may not only improve access to FMT but also its efficacy.