Core B,the Microbiome Data ManagementCore (MDMC), will serve as a central data repository for Projects 1, 2 and 3 as well as Core A. This facility will be housed at TIGR and directed by Jeremy Selengut of TIGR's Bioinformatics Department. The diverse data types and large amount of data that will be generated by the different components of this program necessitate a central facility for data storage and access. This typeof program, with a distributed sequencing effort, a shared pool of data for collaborative analysis, and a common database to flexibly represent not only the data but the growing conceptual model of the system under study, is likely to be an archetype of future human microbiome and other environmental metagenomics research. The plan we outline utilizes technologies and methods with which we are very experienced and skilled, but are combined and shaped into a new system optimized for this type of programmatic effort. There are 3 aims.
Aim 1 Establish a Core Database. We will establish a database repository to support the sample collection effort and metagenomic/pan-genomic, analyses for the microbiome project. This system will support types of data critical to the success of this program project:e.g., subsets of de-identified patient metadata, 16SrRNA- pan-genomic- and fecal community microbiome gene, transcriptome and metabolite datasets). We will provision for multiple users and institutions to operate on the database, and develop straightforward electronic submission and retrieval mechanisms for the MDMC database.
Aim 2 : Formalize Data Exchange. The core will ensure that all electronic data are robustly encoded in a data exchange file format to effectively support the project. We will supply an Application Programmer Interface (API)that will allow all contributors to deliver data to MDMC over the web. We will support the API with documentation. Open Source code, training support, and validation scripts for all data required by the project.
Aim 3 : Maintain Communication Between the MDMC and Projects 1, 2 and 3. Ensuring mat the data management system meets the needs of the scientists distributed among the other projects in this proposal is paramount. This will be accomplished by development of documentation, a help desk system, direct contacts between key staff, a system of email updates, reports to the project website, and attendance at all regularly scheduled meetings.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Program Projects (P01)
Project #
5P01DK078669-02
Application #
7664574
Study Section
Special Emphasis Panel (ZDK1)
Project Start
Project End
Budget Start
2008-07-01
Budget End
2009-06-30
Support Year
2
Fiscal Year
2008
Total Cost
$98,754
Indirect Cost
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Chondronikola, Maria; Magkos, Faidon; Yoshino, Jun et al. (2018) Effect of Progressive Weight Loss on Lactate Metabolism: A Randomized Controlled Trial. Obesity (Silver Spring) 26:683-688
Hillmann, Benjamin; Al-Ghalith, Gabriel A; Shields-Cutler, Robin R et al. (2018) Evaluating the Information Content of Shallow Shotgun Metagenomics. mSystems 3:
Janssen, Stefan; McDonald, Daniel; Gonzalez, Antonio et al. (2018) Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information. mSystems 3:
An, Jie; Wang, Liping; Patnode, Michael L et al. (2018) Physiological mechanisms of sustained fumagillin-induced weight loss. JCI Insight 3:
Wang, Hanghang; Muehlbauer, Michael J; O'Neal, Sara K et al. (2017) Recommendations for Improving Identification and Quantification in Non-Targeted, GC-MS-Based Metabolomic Profiling of Human Plasma. Metabolites 7:
Jiang, Lingjing; Amir, Amnon; Morton, James T et al. (2017) Discrete False-Discovery Rate Improves Identification of Differentially Abundant Microbes. mSystems 2:
Mark Welch, Jessica L; Hasegawa, Yuko; McNulty, Nathan P et al. (2017) Spatial organization of a model 15-member human gut microbiota established in gnotobiotic mice. Proc Natl Acad Sci U S A 114:E9105-E9114
Newgard, Christopher B (2017) Metabolomics and Metabolic Diseases: Where Do We Stand? Cell Metab 25:43-56
Morton, James T; Sanders, Jon; Quinn, Robert A et al. (2017) Balance Trees Reveal Microbial Niche Differentiation. mSystems 2:
Green, Jonathan M; Barratt, Michael J; Kinch, Michael et al. (2017) Food and microbiota in the FDA regulatory framework. Science 357:39-40

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