第 15 回腸内細菌学会

87

シンポジウム基調講演
Justin L. Sonnenburg
Department of Microbiology and Immunology
Stanford University School of Medicine
Positions
1995–1996
1996–2003
2003–2006
2006–2008
2008–pres

Undergraduate Research (DJ Klionsky, Advisor), University of California—Davis
PhD Student in Biomedical Sciences Graduate Program (A Varki, Advisor),
University of California—San Diego
Research Associate, Department of Molecular Biology & Pharmacology and Center for GenomeSciences (JI Gordon, Mentor), Washington University School of Medicine, St. Louis, Missouri
Instructor, Department of Molecular Biology & Pharmacology and Center for Genome Sciences (JIGordon, Mentor), Washington University School of Medicine, St. Louis, Missouri
Assistant Professor, Department of Microbiology and Immunology, Stanford University School ofMedicine, Stanford, CaliforniaHonors
1995
1996
2004–2006
2008
2008
2009

Presidential Undergraduate Fellowship
Lucille P. Markey Fellowship in Biomedical Sciences
W.M. Keck Fellowship
Stanford Digestive Disease Center (DDC), Named Investigator
Beckman Center for Molecular and Genetic Medicine, Start-up award
NIH Director’s New Innovator Award

Selected Peer-reviewed Publications
1. Tomashek JJ, Sonnenburg JL, Artimovich JM, Klionsky DJ. Resolution of subunit interactions and cytoplasmic subcomplexes ofthe yeast vacuolar proton-translocating ATPase. J. Biol. Chem. 1996; 271(17) : 10397–404.
2. Chammas R, Sonnenburg JL, Watson NE, Tai T, Farquhar MG, Varki NM, Varki A. De-N-acetyl-gangliosides in humans: unusual subcellular distribution of a tumor antigen. Cancer Res. 1999; 59(6) : 1337–46.
3. Brinkman-Van der Linden ECM, Sonnenburg JL, Varki A. Effects of sialic acid substitutions on recognition by sambucus nigra
agglutinin and maackia amurensis hemagglutinin. Analytical Biochem. 2002; 303(1) : 98–104.
4. Sonnenburg JL, Van Halbeek H, Varki A. Characterization of the acid stability of glycosidically-linked neuraminic acid: use indetecting De-N-acetyl-gangliosides in human melanoma. J. Biol. Chem. 2002; 277(20) : 17502–10.
5. Sonnenburg JL, Altheide TK, Varki A. A uniquely human consequence of domain-specific functional adaptation in a sialic acidbinding receptor. Glycobiology. 2004; 14(4) : 339–46.
6. Sonnenburg JL, Angenent LT, Gordon JI. Getting a grip on things: how do communities of bacterial symbionts become established in our intestine? Nat Immunol. 2004; 5(6) : 569–73.
7. Westover BP, Buhler JD, Sonnenburg JL, Gordon JI. Operon prediction without a training set. Bioinformatics. 2005 Apr 1; 21(7) : 880–8.
8. Sonnenburg JL, Xu J, Leip DD, Chen CH, Westover BP, Weatherford J, Buhler JD, Gordon JI. Glycan foraging in vivo by anintestine-adapted bacterial symbiont. Science. 2005; 307(5717) : 1955–9.
9. Sonnenburg ED, Sonnenburg JL, Manchester J, Hansen E, Chiang H, Gordon JI. A hybrid two-component system protein of aprominent human gut symbiont couples glycan sensing in vivo to carbohydrate metabolism. PNAS. 2006; 103(23) : 8834–9.
PMC1472243.
10. Sonnenburg JL, Chen CTL, Gordon JI. Genomic and metabolic studies of the impact of probiotics on a model gut symbiont
and host. PLoS Biol. 2006; 4(12) : e413. PMC1661682.
11. Lecuit M, Sonnenburg JL, Cossart P, Gordon JI. Functional genomic studies of the intestinal response to a foodborne
enteropathogen in a humanized gnotobiotic mouse model. J. Biol. Chem. 2007; 282(20) : 15065–72.
12. Moon K, Sonnenburg JL, Salyers AA. Unexpected effect of a Bacteroides conjugative transposon, CTnDOT, on chromosomal
gene expression in its bacterial host. Mol. Micro. 2007; 64(6) : 1562–1571. PMC1976400.
13. Marco ML, Peters THF, Bongers RS, Molenaar D, van Hemert S, Sonnenburg JL, Gordon JI, Kleerebezem M. Lifestyle ofLactobacillus plantarum in the mouse caecum. Environ. Micro. 2009; 11(10) : 2747–57. PMCID: not applicable.
14. Sonnenburg ED, Zheng H, Joglekar P, Higginbottom SK, Firbank SJ, Bolam DN, Sonnenburg JL. Specificity of polysaccharide
use in intestinal bacteroides species determines diet-induced microbiota alterations. Cell. 141(7) pp. 1241–1252, June 25, 2010.
PMCID: PMC2900928.

基シン
調ポ
講ジウ
演ム

88

腸内細菌学雑誌

25 巻 2 号

2011

Mechanistic Insight into Intestinal Microbiota Function and Manipulation
Justin L. Sonnenburg
Trillions of microbes live in our digestive tract and influence our biology in profound and diverse ways. Several
diseases, including obesity and inflammatory bowel diseases, have been associated with large-scale shifts in microbiota composition. The ability to address basic questions concerning community function and plasticity are fundamental to understanding the extent of causal relationships between host biology and microbiota perturbations, andwhether the microbiota is a viable therapeutic target. One of our long-term goals is to achieve a level of functional understanding that would allow us to accurately predict aspects of a microbial community’s functional adaptation to a specific perturbation (e.g., dietary change).
To investigate how changes in the intestinal environment alter microbiota function, and how these changes, inturn, influence host biology we have characterized responses of simplified microbiotas living within the gut of gnotobiotic mice to changes in host diet, community membership, and host genotype. These studies have revealed theimportance of finely-tuned systems of polysaccharide sensing and utilization in Bacteroides species. We are currently using a single polysaccharide utilization locus (PUL) dedicated to dietary fructan utilization of Bacteroides
as a model to understand mechanisms underlying diet-induced changes in microbiota function and composition.
These data have elucidated how Bacteroides species acquire and process this common class of dietary carbohydrates. Comparative genomic analysis revealed that the fructan PUL is conserved to varying extents among
Bacteroides species, corresponding to a range of fructan utilization capability across the genus. Using model intestinal microbiotas living within gnotobiotic mice, we demonstrate that dietary fructan can have disparate effects oncommunity composition, depending upon the fructan degrading capacity of members of the microbiota.
Analysis of ＞ 10 members of the Bacteroides genus has revealed that each species has specialized in use ofeither β 2-1 (inulin)- or β 2-6 (levan)-linked fructan, but no species is adept at using both linkages. Investigation ofseveral B. thetaiotaomicron isolates has revealed that even closely related strains within the same species havediffering specificities for the fructan linkage. We have set out to understand the genomic and molecular basis forthese differences in fructan-use specificity suspecting that either lateral gene transfer or rapid evolution (i.e., positive selection) could explain the functional differences that we observe. Bi-associated gnotobiotic mice colonizedwith wild-type (wt) Bacteroides species, genetically modified Bacteroides species, and/or Bifidobacterium species
have revealed how genomic sequence information can be translated to understand and predict community dynamics in vivo.
In addition to alterations in diet, differences in host genotype, antibiotics, orally acquired microbes, and numerous other factors can impact the microbiota. Understanding how variability in these environmental factors influence the composition, function, and interaction within the microbiota, and how these changes, in turn, affect ourbiology as hosts, is experimentally challenging due to the complexity of the community. We have used gnotobiotic
mice harboring defined model communities or a completed human microbiota (‘humanized’) to unravel the complexity associated with the ‘universe’ of small molecules associated with microbiota-host interaction. Small molecule metabolites produced by the microbiota are important mediators of microbe-microbe and microbe-host interactions. New technology in mass-spectrometry offers the ability to perform extensive characterization of small molecule metabolites produced by the microbiota or via microbiota-host interaction. We are applying these metabolomic approaches to understand how alterations in the composition of the gut microbiota influence the metabolite profile of urine, blood or feces. Metabolomic analysis of these biofluids allows us to monitor the dynamics of microbialcolonization and provides an instantaneous readout of gut microbiota functionality. We are also defining novel, biologically important compounds produced by members of the microbiota. Together these data set the stage for predicting, based on gene content or metabolite profile, how a microbiota will respond to changes in the nutrient environment and suggest how systems-level data could facilitate both the diagnostic potential and the personalized
therapeutic manipulation of the intestinal microbiota.