Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.
Background: Wheat allergy is not an uncommon event among Thai children. Despite strict avoidance, some patients developed reactions after accidental exposure to minute amount of wheat and thus disturbed their quality of life. Wheat oral immunotherapy (OIT) has been reported to be an alternative treatment for such patients. Objective: We designed a new 3-step wheat OIT protocol for treatment of severe wheat allergy in Thai patients. The feasibility of the protocol is evaluated and is reported here in this paper. Methods: We retrospectively reviewed medical records of 26 patients who had undergone wheat OIT during a 30-month period. The 3-step protocol consisted of an initial phase of double-blind, placebo-controlled food challenge (DBPCFC) and initiation of OIT, a build-up phase, and a maintenance phase. Patient retention in the protocol was the main outcome for this feasibility study. Adverse effects during OIT were recorded. Correlation between serum specific IgE (SpIgE) to wheat and eliciting dose in phase I was determined. Results: Fourteen females and 12 males with a median age of 6 years were studied. Their median age when wheat allergy began was 8 months. Median SpIgE to wheat was high (198 kU A /L). All patients developed reactions during DBPCFC with 17 of 26 patients had moderate to severe reactions required adrenaline injections. Median of eliciting dose of wheat was exceedingly low, i.e., 20 mg of wheat protein. At the end of the study, 23 of 26 patients (88%) were still in the study. Adverse reactions during the build-up phase was frequent (13 patients, 50%), with adrenaline required in 6 occasions. Six patients reached maintenance phase. Conclusion: The new 3-step wheat OIT protocol was feasible in these highly wheat-sensitized patients. Despite a high retention rate, a high rate of adverse effects was observed both during DBPCFC and build-up phases.
The interaction between gut microbiota and host immunity shapes the immune development and microbial functions. Dysbiosis is known to relate to allergy. However, whether alteration of gut microbiota is different among distinct allergic phenotypes has never been elucidated. Our study aimed to determine the difference between gut microbiota and microbial products among infants with different allergic phenotypes from a longitudinal birth cohort in Bangkok, Thailand. METHODS: Gut microbiome of 26 allergic infants and 26 matchedhealthy controls at aged 9-12 months were analyzed using 16s amplicon sequencing. Proteomics analysis was performed using LC-MS. RESULTS: Subjects with atopic manifestation were grouped into 3 phenotypes; atopic dermatitis(AD)61.6%, food allergy(FA)19.2% and subjects with both AD and FA(AD/FA)19.2%. While subjects with only AD had normal microbial diversity, ones with FA and AD/FA showed lowdiversity microbial communities. Erysipelotrichaceae was the most significant abundance in AD. It expressed proteins related to cell replication such as DNA polymerase-I, suggesting its high activity. Bifidobacteriaceae was less abundance in allergic populations and also showed decreased production of glycosyltransferase, which stimulates intestinal mucus synthesis and decreased proteins involving in bacterial cellular energy production/ nutrition uptake such as ATP synthase. Altogether suggested the inactivity and malfunction of Bifidobacteriaceae in allergic subjects. CONCLUSIONS: Different microbial patterns were demonstrated in subjects with distinct allergic phenotypes. Less diversity was found in FA while specific strains of microbiota predominated in AD. Understanding the dynamics of microbial colonization patterns and their activities provides insight into the pathophysiology of allergic diseases as well as the potential target for allergy prevention and treatment.
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