To ensure consistency in the data generated for this study, particularly that of microbiota profiles which are highly variable in phylogenetic composition across individuals, we will centralize all bacterial community profiling pertormed for this Program Project Grant application in Core D. To further standardize microbiome profiling efforts, analyses will be performed using the recently developed G3 16S rRNA PhyloChip, a phylogenetic microarray capable of detecting -60,000 bacterial taxa (defined as groups of organisms that share at least 99% 16S rRNA sequence homology) in a single assay. This approach provides a highresolution profile of the microbiota present, which due to the semi-quantitative data generated, is ideal for both comparative analyses across treatment groups and correlative analyses using measured immunological or environmental variables. The Core will be responsible for extraction of nucleic acids from house dust and stool samples using methods optimized for efficient extraction of both gram positive and negative organisms and for profiling the microbiota present in these samples. Personnel in the Core have extensive expertise in using this technology and in performing microbial ecology studies;these individuals will calculate gross bacterial community composition (BCC) indices (richness, Pielou's evenness and Inverse Simpson's diversity). In addition, Core personnel will generate datasets containing taxonomic relative abundance (based on normalized fluorescence intensity reported by the array) for each sample analyzed. All of this data will be transferred to the Biostatistics Core (Core B) for subsequent large-scale analyses. Use of Core D specifically for microbiome profiling for all Projects in this application ensures standardization of the approach used for microbiome profiling. It also permits data reduction by individuals with extensive expertise in microbiome data analyses using an established analysis pipeline. Finally, this level of consistency in microbiota profiling across all studies proposed in this application will permit cross comparisons between individual studies which is key to ensuring synergism between projects.

Public Health Relevance

Finding discrete differences in microbiota profiles across exposure groups or in association with specific measured variables necessitates a highly standardized approach. The methods proposed in Core D will provide standardized sample handling and processing for bacterial community analysis in environmental and baby stool and, using an economical assay, determine the relative abundance of -60,000 bacterial groups in a single assay, providing a high-resolution profile of community composition for every sample analyzed in this study.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program Projects (P01)
Project #
5P01AI089473-02
Application #
8567843
Study Section
Special Emphasis Panel (ZAI1-JRR-I)
Project Start
Project End
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
2
Fiscal Year
2013
Total Cost
$287,649
Indirect Cost
$52,552
Name
Henry Ford Health System
Department
Type
DUNS #
073134603
City
Detroit
State
MI
Country
United States
Zip Code
48202
Cassidy-Bushrow, Andrea E; Wegienka, Ganesa; Havstad, Suzanne et al. (2016) Race-specific Association of Caesarean-Section Delivery with Body Size at Age 2 Years. Ethn Dis 26:61-8
Cassidy-Bushrow, Andrea E; Havstad, Suzanne; Basu, Niladri et al. (2016) Detectable Blood Lead Level and Body Size in Early Childhood. Biol Trace Elem Res 171:41-7
Mar, Jordan S; LaMere, Brandon J; Lin, Din L et al. (2016) Disease Severity and Immune Activity Relate to Distinct Interkingdom Gut Microbiome States in Ethnically Distinct Ulcerative Colitis Patients. MBio 7:
Johnson, Christine C; Ownby, Dennis R (2016) Allergies and Asthma: Do Atopic Disorders Result from Inadequate Immune Homeostasis arising from Infant Gut Dysbiosis? Expert Rev Clin Immunol 12:379-88
Ownby, Dennis; Johnson, Christine Cole (2016) Recent Understandings of Pet Allergies. F1000Res 5:
Cassidy-Bushrow, A E; Sitarik, A; Levin, A M et al. (2016) Maternal group B Streptococcus and the infant gut microbiota. J Dev Orig Health Dis 7:45-53
Levin, Albert M; Sitarik, Alexandra R; Havstad, Suzanne L et al. (2016) Joint effects of pregnancy, sociocultural, and environmental factors on early life gut microbiome structure and diversity. Sci Rep 6:31775
Lynch, Susan V; Boushey, Homer A (2016) The microbiome and development of allergic disease. Curr Opin Allergy Clin Immunol 16:165-71
Joseph, Christine L M; Zoratti, Edward M; Ownby, Dennis R et al. (2016) Exploring racial differences in IgE-mediated food allergy in the WHEALS birth cohort. Ann Allergy Asthma Immunol 116:219-224.e1
Fujimura, Kei E; Sitarik, Alexandra R; Havstad, Suzanne et al. (2016) Neonatal gut microbiota associates with childhood multisensitized atopy and T cell differentiation. Nat Med 22:1187-1191

Showing the most recent 10 out of 34 publications