{"doi":"10.14814/phy2.14610","title":"Resistant starch slows the progression of CKD in the 5/6 nephrectomy mouse model","abstract":"BACKGROUND: Resistant Starch (RS) improves CKD outcomes. In this report, we study how RS modulates host-microbiome interactions in CKD by measuring changes in the abundance of proteins and bacteria in the gut. In addition, we demonstrate RS-mediated reduction in CKD-induced kidney damage. METHODS: Eight mice underwent 5/6 nephrectomy to induce CKD and eight served as healthy controls. CKD and Healthy (H) groups were further split into those receiving RS (CKDRS, n = 4; HRS, n = 4) and those on normal diet (CKD, n = 4, H, n = 4). Kidney injury was evaluated by measuring BUN/creatinine and by histopathological evaluation. Cecal contents were analyzed using mass spectrometry-based metaproteomics and de novo sequencing using PEAKS. All the data were analyzed using R/Bioconductor packages. RESULTS: The 5/6 nephrectomy compromised kidney function as seen by an increase in BUN/creatinine compared to healthy groups. Histopathology of kidney sections showed reduced tubulointerstitial injury in the CKDRS versus CKD group; while no significant difference in BUN/creatinine was observed between the two CKD groups. Identified proteins point toward a higher population of butyrate-producing bacteria, reduced abundance of mucin-degrading bacteria in the RS fed groups, and to the downregulation of indole metabolism in CKD groups. CONCLUSION: RS slows the progression of chronic kidney disease. Resistant starch supplementation leads to active bacterial proliferation and the reduction of harmful bacterial metabolites.","journal":"Physiological Reports","year":2020,"id":105772,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":23,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9568,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":511515,"name":"Galina Glazko","orcid":"0000-0002-0570-5304","position":1,"is_corresponding":false},{"id":248440,"name":"Zeljko Dvanajscak","orcid":null,"position":2,"is_corresponding":false},{"id":245938,"name":"John M. Arthur","orcid":"0000-0003-4342-4762","position":3,"is_corresponding":false},{"id":342237,"name":"Samuel G. Mackintosh","orcid":"0000-0002-5530-8403","position":4,"is_corresponding":false},{"id":489433,"name":"Lisa Orr","orcid":null,"position":5,"is_corresponding":false},{"id":511516,"name":"Yasir Rahmatallah","orcid":"0000-0002-8176-6328","position":6,"is_corresponding":false},{"id":273747,"name":"Laxmi Yeruva","orcid":"0000-0003-4289-9109","position":7,"is_corresponding":false},{"id":379499,"name":"Alan J. Tackett","orcid":"0000-0002-3672-4460","position":8,"is_corresponding":false},{"id":511517,"name":"Boris Zybailov","orcid":"0000-0003-2432-9145","position":9,"is_corresponding":false},{"id":511514,"name":"Oleg Karaduta","orcid":"0000-0003-3873-052X","position":0,"is_corresponding":true}],"reference_count":38,"raw_metadata":null,"created_at":"2026-07-18T23:12:21.275494Z","pmid":"33038060","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}