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Resistant starch alters gut microbiome and metabolomic profiles concurrent with amelioration of chronic kidney disease in rats
Open accessAbstract
Patients and animals with chronic kidney disease (CKD) exhibit profound alterations in the gut environment including shifts in microbial composition, increased fecal pH, and increased blood levels of gut microbe-derived metabolites (xenometabolites). The fermentable dietary fiber high amylose maize-resistant starch type 2 (HAMRS2) has been shown to alter the gut milieu and in CKD rat models leads to markedly improved kidney function. The aim of the present study was to identify specific cecal bacteria and cecal, blood, and urinary metabolites that associate with changes in kidney function to identify potential mechanisms involved with CKD amelioration in response to dietary resistant starch. Male Sprague-Dawley rats with adenine-induced CKD were fed a semipurified low-fiber diet or a high-fiber diet [59% (wt/wt) HAMRS2] for 3 wk ( n = 9 rats/group). The cecal microbiome was characterized, and cecal contents, serum, and urine metabolites were analyzed. HAMRS2-fed rats displayed decreased cecal pH, decreased microbial diversity, and an increased Bacteroidetes-to-Firmicutes ratio. Several uremic retention solutes were altered in the cecal contents, serum, and urine, many of which had strong correlations with specific gut bacteria abundances, i.e., serum and urine indoxyl sulfate were reduced by 36% and 66%, respectively, in HAMRS2-fed rats and urine p-cresol was reduced by 47% in HAMRS2-fed rats. Outcomes from this study were coincident with improvements in kidney function indexes and amelioration of CKD outcomes previously reported for these rats, suggesting an important role for microbial-derived factors and gut microbe metabolism in regulating host kidney function.
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“A diet with high levels of resistant starch (a prebiotic) favourably altered the gut microbiota and caecal, serum and urine metabolite profiles in rats with adenine-induced CKD217.”
From The gut microbiota and the brain–gut–kidney axis in hypertension and chronic kidney disease (2018) · cites this paper as [217]
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
An obesity-associated gut microbiome with increased capacity for energy harvest
Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006) · Nature · doi:10.1038/nature05414 · Cited by 12,444
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
PLS-regression: a basic tool of chemometrics
Wold, S., Sjöström, M., & Eriksson, L. (2001) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(01)00155-1 · Cited by 10,084
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,944
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
K/DOQI clinical practice guidelines for bone metabolism and disease in chronic kidney disease
Massry, S. G., Coburn, J. W., Chertow, G. M., Hruska, K. A., Langman, C. B., Malluche, H. H., Martin, K. J., McCann, L. M., McCarthy, J. T., Moe, S. M., et al. (2003) · University of Groningen research database (University of Groningen / Centre for Information Technology) · Cited by 2,527
Nasir, O. (2013) · Kidney & Blood Pressure Research · doi:10.1159/000350152 · Cited by 2,331
Research works printed but not linked: 3
- Baker D, 1977, Cereal Chem, 54, 360
- Rampton D, 1984, Clin Nephrol, 21, 159
- Scholz M, 2007, Pac Sympos Biocomput, 2007, 169
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The gut microbiota and the brain–gut–kidney axis in hypertension and chronic kidney disease
Yang, T., Richards, E. M., Pepine, C. J., & Raizada, M. K. (2018) · Nature Reviews Nephrology · doi:10.1038/s41581-018-0018-2 · Cited by 753
Zhang, L., & Davies, S. S. (2016) · Genome Medicine · doi:10.1186/s13073-016-0296-x · Cited by 521
Microbiome–metabolome reveals the contribution of gut–kidney axis on kidney disease
Chen, Y., Chen, D., Chen, L., Liu, J., Vaziri, N. D., Guo, Y. P., & Zhao, Y. (2019) · Journal of Translational Medicine · doi:10.1186/s12967-018-1756-4 · Cited by 430
Self-citationGut Microbiota and Complications of Type-2 Diabetes
Iatcu, O. C., Steen, A., & Covașă, M. (2021) · Nutrients · doi:10.3390/nu14010166 · Cited by 448
Metadata
- Authors
- Kieffer, D. A., Piccolo, B. D., Vaziri, N. D., Liu, S., Lau, W. L., Khazaeli, M., Nazertehrani, S., Moore, M. E., Marco, M. L., Martin, R. J., & Adams, S. H.
- Affiliations
- Agricultural Research Service (US)
- Arkansas Children's Nutrition Center (US)
- University of California, Irvine (US)
- University of California, Davis (US)
- Corresponding author
- Adams, Sean H.
- ORCID
- Venue
- American Journal of Physiology-Renal Physiology
- Publisher
- American Physiological Society
- Published
- 2016-05-01
- Volume
- 310
- Issue
- 9
- Pages
- F857-F871
- ISSN
- 1522-1466 (ISSN-L)
- 1931-857X
- PMC
- PMC4867313
- OpenAlex
- W2262540956
- Cited by
- 308
- References
- 87
- Citations by year
- 2026: 22 · 2025: 46 · 2024: 35 · 2023: 24 · 2022: 32 · 2021: 30 · 2020: 42 · 2019: 34 · 2018: 25 · 2017: 8 · 2016: 9
- FWCI
- 13.17
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Physiology-Renal Physiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- HHS | NIH | National Center for Advancing Translational Sciences (NCATS) (UL1 TR000002 and linked award TL1 TR000133)
- Danish Council for Strategic Research
- USDA-ARS Projects (2032-51530-022-00D and 6026-51000-010-00D)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Nursing › Nutrition and Dietetics › Food composition and properties
- Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
- Keywords
- resistant starch, chronic kidney disease, gut microbiota, metabolomics, dietary fiber, adenine-induced CKD, uremic toxins, indoxyl sulfate, p-cresol, Firmicutes/Bacteroidetes ratio, cecal microbiota, microbial metabolites, renal function
- MeSH terms
- Gastrointestinal Microbiome, Animals, Cecum, Cresols, Diet, Dietary Fiber, Hydrogen-Ion Concentration, Kidney Function Tests, Male, Starch, Uremia, Rats, Sprague-Dawley, Rats, Renal Insufficiency, Chronic, Metabolomics
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