Metagenomic Analysis of the Healthy Human Gut Microbiome

Understanding the composition of microbial communities in the human gut, demonstrated to have a significant impact in health and disease, could lead to the discovery of novel medical treatments, improved outcomes from dietary interventions, and more individualized drug therapies. To address this, we aim to characterize patterns of the healthy human gut microbiome, using a cohort of 52 healthy individuals recruited from the GW university community. Each subject donated three fecal samples over the course of the study period, which was between 1 and 3 weeks, depending on the specific protocol in which they were enrolled. We have validated our workflow for collection of fecal samples, assessment of dietary intake, and metagenomics sequencing of healthy young adults. Generation of FASTQ data files containing raw short read sequences with positional quality scores, metadata, and nutritional analysis have been assessed for 16 study participants so far, with 16 more in progress. Using Nutrition Data System for Research (NDSR) software, we calculated nutrient intakes for each participant over the study period, which allowed us to correlate microbial populations with the foods and nutrients consumed. Using the George Washington University’s High-performance Integrated Virtual Environment (HIVE) we conducted bioinformatic analysis on these data and generated a curated database for human gut microbiome analysis. This DB consists of 172 reference sequences from 164 organisms.With our results, we then created a knowledge base, GutFeeling KnowledgeBase, which can generate and export figures or export tables used to create the figures at various taxonomic levels, and summarizing the data by metadata categories. The outputs from the GFKB to tables can be used in other analysis tools that are commonly used for metagenomic analysis. We include here results using some of the more common tools and analysis.

Author

• King IV, Charles Hadley S.

Language

• en

Date created

• 2017

Type of Work

• Master's Thesis

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Molecular Biochemistry & Bioinformatics

Degree

• M.S.

Advisor

• Mazumder, Raja

Committee Member(s)

• Meni, Allison

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/1z40ks94b