The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Engineering the gut microbiota to treat hyperammonemia
Open accessAbstract
Increasing evidence indicates that the gut microbiota can be altered to ameliorate or prevent disease states, and engineering the gut microbiota to therapeutically modulate host metabolism is an emerging goal of microbiome research. In the intestine, bacterial urease converts host-derived urea to ammonia and carbon dioxide, contributing to hyperammonemia-associated neurotoxicity and encephalopathy in patients with liver disease. Here, we engineered murine gut microbiota to reduce urease activity. Animals were depleted of their preexisting gut microbiota and then inoculated with altered Schaedler flora (ASF), a defined consortium of 8 bacteria with minimal urease gene content. This protocol resulted in establishment of a persistent new community that promoted a long-term reduction in fecal urease activity and ammonia production. Moreover, in a murine model of hepatic injury, ASF transplantation was associated with decreased morbidity and mortality. These results provide proof of concept that inoculation of a prepared host with a defined gut microbiota can lead to durable metabolic changes with therapeutic utility.
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Cites
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Lozupone, C., & Knight, R. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8228-8235.2005 · Cited by 8,227
Duodenal Infusion of Donor Feces for Recurrent Clostridium difficile
van Nood, E., Vrieze, A., Nieuwdorp, M., Fuentes, S., Zoetendal, E. G., de Vos, W. M., Visser, C. E., Kuijper, E. J., Bartelsman, J. F. W. M., Tijssen, J. G. P., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1205037 · Cited by 3,708
High-Fat Diet Determines the Composition of the Murine Gut Microbiome Independently of Obesity
Hildebrandt, M. A., Hoffmann, C., Sherrill–Mix, S. A., Keilbaugh, S. A., Hamady, M., Chen, Y., Knight, R., Ahima, R. S., Bushman, F., & Wu, G. D. (2009) · Gastroenterology · doi:10.1053/j.gastro.2009.08.042 · Cited by 1,576
Self-citationMicrobial co-occurrence relationships in the human microbiome
Faust, K., Sathirapongsasuti, J. F., Izard, J., Segata, N., Gevers, D., Raes, J., & Huttenhower, C. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002606 · Cited by 1,527
Gut Microbiomes of Malawian Twin Pairs Discordant for Kwashiorkor
Smith, M. I., Yatsunenko, T., Manary, M. J., Trehan, I., Mkakosya, R., Cheng, J., Kau, A. L., Rich, S. S., Concannon, P., Mychaleckyj, J. C., et al. (2013) · Science · doi:10.1126/science.1229000 · Cited by 1,173
Correlation between intraluminal oxygen gradient and radial partitioning of intestinal microbiota
Albenberg, L., Esipova, T. V., Judge, C. P., Bittinger, K., Chen, J., Laughlin, A., Grunberg, S., Baldassano, R. N., Lewis, J. D., Li, H., et al. (2014) · Gastroenterology · doi:10.1053/j.gastro.2014.07.020 · Cited by 886
Self-citationHughes, R. N. (2004) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2004.06.006 · Cited by 641 · cited 1×
“Using a lower dose of TAA to reduce mortality, we analyzed memory and spatial learning in a Y maze test (36) comparing prepared/ASF mice with mice transplanted with normal microbiota (referred to herein as prepared/normal microbiota mice; Figure 7 and Supplemental Figure 3, B and C) as a control.”
MethodLawley, T. D., Clare, S., Walker, A. W., Stares, M. D., Connor, T. R., Raisen, C., Goulding, D., Rad, R., Schreiber, F., Brandt, C., et al. (2012) · PLoS Pathogens · doi:10.1371/journal.ppat.1002995 · Cited by 540
Cited by
Current Understanding of Dysbiosis in Disease in Human and Animal Models
DeGruttola, A. K., Low, D., Mizoguchi, A., & Mizoguchi, E. (2016) · Inflammatory Bowel Diseases · doi:10.1097/mib.0000000000000750 · Cited by 1,122
Zarrinpar, A., Chaix, A., Xu, Z. Z., Chang, M. W., Marotz, C. A., Saghatelian, A., Knight, R., & Panda, S. (2018) · Nature Communications · doi:10.1038/s41467-018-05336-9 · Cited by 546
Yehl, K., Lemire, S., Yang, A. C., Ando, H., Mimee, M., Torres, M. D. T., de la Fuente-Nunez, C., & Lu, T. K. (2019) · Cell · doi:10.1016/j.cell.2019.09.015 · Cited by 437
Kurtz, C. B., Millet, Y. A., Puurunen, M. K., Perreault, M., Charbonneau, M. R., Isabella, V. M., Kotula, J. W., Antipov, E., Dagon, Y., Denney, W. S., et al. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aau7975 · Cited by 399
Microbiome therapeutics — Advances and challenges
Mimee, M., Citorik, R. J., & Lu, T. K. (2016) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2016.04.032 · Cited by 317
Metadata
- Authors
- Shen, T.-C. D., Albenberg, L., Bittinger, K., Chehoud, C., Chen, Y.-Y., Judge, C. A., Chau, L., Ni, J., Sheng, M., Lin, A., Wilkins, B. J., Buza, E. L., Lewis, J. D., Daikhin, Y., Nissim, I., Yudkoff, M., Bushman, F. D., & Wu, G. D.
- Venue
- Journal of Clinical Investigation
- Published
- 2015-06-22
- Volume
- 125
- Issue
- 7
- Pages
- 2841-2850
- ISSN
- 0021-9738 (ISSN-L)
- OpenAlex
- W2112931540
- Cited by
- 180
- References
- 8
- FWCI
- 6.82
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Shen, T.-C. D., Albenberg, L., Bittinger, K., Chehoud, C., Chen, Y.-Y., Judge, C. A., Chau, L., Ni, J., Sheng, M., Lin, A., Wilkins, B. J., Buza, E. L., Lewis, J. D., Daikhin, Y., Nissim, I., Yudkoff, M., Bushman, F. D., & Wu, G. D. (2015). Engineering the gut microbiota to treat hyperammonemia. Journal of Clinical Investigation. https://doi.org/10.1172/jci79214
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