Project 2 represents a complementary approach to the one presented in Project 1 for examining genetic diversity in the microbiomes of obese and lean twin pairs. Whereas Project 1 investigates genomic and metabolomic properties of the whole gut microbial community, Project 2focuses on the gene complement of two prominent members of the gut microbiota, offering a genome-anchored view of the microbiome. The fermentative bacterium B. thetatiotaomicron and the methanogenic archaeon M. smithii have been shown in gnotobiotic mouse models to have a synergistic effect on energy harvest from the diet. Project 2 explores the genomic content of populations of these two microbial species obtained from lean and obese monozygotic twins. Our central hypothesis is that the microbiome of obese individuals has a greater capacity for energy harvest: thus, we postulate that there may be an enhancement of energy-acquisition functions in the genomes of these two microbial species obtained from obese individuals. The microbial genome is a dynamic entity, shaped by multiple forces that include gene loss and gain via lateral gene transfer (LGT). One implication of LGT is that no single genome sequence can describe a 'species'. To understand the nature of a microbial species we therefore must focus on the """"""""pan-genome"""""""", the sum of core, vertically inherited genes and the variable, strain-specific genes. Pan-genome size can be vastly larger than the genome of any single isolate, increasing with every isolate sequenced. Wewill determine the extent of variability in the pan-genomes, both in terms of functional gene content and the discovery rate of new genes/isolate, of strains isolated from MZ twin pairs and their mothers and selected based on their core gene phylogenetic (tree-based) relationships. In this Project, we will use a combination of methods including culturing of isolates, comparative genome hybridization, genome amplification and large-scale DNA sequencing. Using data analysis methods outlined in Projects 1 and 3, we will assess the functional consequences of obesity- related pan-genome differences in terms of overall microbial gut metabolism, including inter-species synergisms. In addition, the data generated in Project 2will be used as a starting point for the investigations by the Knightlaboratory in Project 3 to trace the flow of genes in the gut microbiome.
| 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: |
| 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 |
| Amir, Amnon; McDonald, Daniel; Navas-Molina, Jose A et al. (2017) Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns. mSystems 2: |
| Barratt, Michael J; Lebrilla, Carlito; Shapiro, Howard-Yana et al. (2017) The Gut Microbiota, Food Science, and Human Nutrition: A Timely Marriage. Cell Host Microbe 22:134-141 |
Showing the most recent 10 out of 90 publications
