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Using Bioinformatics Tools to Evaluate Potential Risks of Food Allergy and to Predict Microbiome Functionality
Abstract
Novel foods and Genetically Engineered (GE) organisms are being developed for nutritional, industrial, and environmental applications. Dietary interventions have been used recently to mitigate methane emissions in ruminants. In this project, bioinformatics tools have been used to answer two main questions. The first question is the potential allergy risks for consumption of novel foods and GE organisms. The second question is the effects of dietary interventions on microbiome functionality related to methane production in ruminants. To answer the first question, regulatory authorities in the United States and Europe now expect an evaluation of new proteins in novel foods or genetically engineered organisms to be evaluated for possible allergy and Celiac disease (CeD) risk. Two microalgal species, a fungus, House Cricket, and GE Canola have been tested to evaluate potential IgE cross-reactivity. Whole genome sequencing, genomic, transcriptomic, proteomic, and immunoinformatics techniques have been used to predict potential cross-reactivity. Bioinformatics tools helped us to characterize their proteomes and critically evaluate matches to putative or proven allergens. The two microalgal species and Fusarium sp. had matches to putative allergens, which are extensively conserved in allergenic, and non-allergenic species, leading to the need for critical evaluation of the CODEX guidelines. Shrimp allergic patients may experience cross-reactions if they consume crickets. There is no reason to suspect that the GE canola would elicit allergic reactions or would induce toxic responses. In addition, we developed a sequence searchable celiac database to identify peptides and proteins for risk assessment of novel food proteins. Concerning the second question, we studied the effect of dietary nitrate and sulfate on finishing cattle performance and methane emissions. To address to question, 16S sequencing and metagenomics were used for better understanding of rumen microbiome composition and functionality. Sulfate and nitrate combination helped to reduce methane emissions, with a reduction in average daily gain, dry matter intake and gain:feed. Ruminal bacterial composition illustrated high abundance of phyla with less hydrogen production, and genera with high H2 utilization capability in fatty acids’ formation, sulfate and nitrate reduction instead of methane production. Metagenomics demonstrated a significant decrease in enzymes linked to methanogenesis in COMBO diet.
Subject Area
Bioinformatics|Microbiology|Immunology
Recommended Citation
Abdelmoteleb, Mohamed, "Using Bioinformatics Tools to Evaluate Potential Risks of Food Allergy and to Predict Microbiome Functionality" (2020). ETD collection for University of Nebraska-Lincoln. AAI27955787.
https://digitalcommons.unl.edu/dissertations/AAI27955787