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pmid:30699108

Metaproteomics reveals potential mechanisms by which dietary resistant starch supplementation attenuates chronic kidney disease progression in rats.

Boris L Zybailov · Galina V Glazko · Yasir Rahmatallah · Dmitri S Andreyev · Taylor McElroy · Oleg Karaduta · Stephanie D Byrum · Lisa Orr · Alan J Tackett · Samuel G Mackintosh · Ricky D Edmondson · Dorothy A Kieffer · R J Martin · Sean H Adams · Nosratola D Vaziri · John M Arthur

PloS one · 2019 doi:10.1371/journal.pone.0199274

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Experiment

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Data

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title
Metaproteomics reveals potential mechanisms by which dietary resistant starch supplementation attenuates chronic kidney disease progression in rats.
doi
10.1371/journal.pone.0199274
pmid
30699108
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[0]
Boris L Zybailov
[1]
Galina V Glazko
[2]
Yasir Rahmatallah
[3]
Dmitri S Andreyev
[4]
Taylor McElroy
[5]
Oleg Karaduta
[6]
Stephanie D Byrum
[7]
Lisa Orr
[8]
Alan J Tackett
[9]
Samuel G Mackintosh
[10]
Ricky D Edmondson
[11]
Dorothy A Kieffer
[12]
R J Martin
[13]
Sean H Adams
[14]
Nosratola D Vaziri
[15]
John M Arthur
journal
PloS one
year
2019
abstract
BACKGROUND: Resistant starch is a prebiotic metabolized by the gut bacteria. It has been shown to attenuate chronic kidney disease (CKD) progression in rats. Previous studies employed taxonomic analysis using 16S rRNA sequencing and untargeted metabolomics profiling. Here we expand these studies by metaproteomics, gaining new insight into the host-microbiome interaction. METHODS: Differences between cecum contents in CKD rats fed a diet containing resistant starch with those fed a diet containing digestible starch were examined by comparative metaproteomics analysis. Taxonomic information was obtained using unique protein sequences. Our methodology results in quantitative data covering both host and bacterial proteins. RESULTS: 5,834 proteins were quantified, with 947 proteins originating from the host organism. Taxonomic information derived from metaproteomics data surpassed previous 16S RNA analysis, and reached species resolutions for moderately abundant taxonomic groups. In particular, the Ruminococcaceae family becomes well resolved-with butyrate producers and amylolytic species such as R. bromii clearly visible and significantly higher while fibrolytic species such as R. flavefaciens are significantly lower with resistant starch feeding. The observed changes in protein patterns are consistent with fiber-associated improvement in CKD phenotype. Several known host CKD-associated proteins and biomarkers of impaired kidney function were significantly reduced with resistant starch supplementation. Data are available via ProteomeXchange with identifier PXD008845. CONCLUSIONS: Metaproteomics analysis of cecum contents of CKD rats with and without resistant starch supplementation reveals changes within gut microbiota at unprecedented resolution, providing both functional and taxonomic information. Proteins and organisms differentially abundant with RS supplementation point toward a shift from mucin degraders to butyrate producers.
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Metaproteomics of the Resistant Starch-fed Chronic Kidney Disease Rats
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Number of quantified proteins by various methods.For a protein to be quantified, a p-value had to be calculated (requiring at least 3 non-zero quantitative values in either CKD-DS or CKD-RS group). Total number of proteins quantified, and number of significant proteins using either p<0.05 or p<0.01 thresholds after Benjamini-Hochberg correction for multiple testing is reported for each of the quantification methods used.
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Metaproteomics protein signature of cecal contents from rats fed resistant starch or digestible starch diets
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Number of quantified proteins by various methods.For a protein to be quantified, a p-value had to be calculated (requiring at least 3 non-zero quantitative values in either CKD-DS or CKD-RS group). Total number of proteins quantified, and number of significant proteins using either p<0.05 or p<0.01 thresholds after Benjamini-Hochberg correction for multiple testing is reported for each of the quantification methods used.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30699108", "kind": "science-record", "revision": 7, "content_hash": "sha256:1c46d14f8222aade61adf0efa3e9bc3532fa24d827475bbe0acf3b03ec1d2792", "created_at": "2026-11-01T15:40:41Z", "updated_at": "2026-11-01T22:00:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Metaproteomics reveals potential mechanisms by which dietary resistant starch supplementation attenuates chronic kidney disease progression in rats.", "doi": "10.1371/journal.pone.0199274", "pmid": "30699108", "authors": ["Boris L Zybailov", "Galina V Glazko", "Yasir Rahmatallah", "Dmitri S Andreyev", "Taylor McElroy", "Oleg Karaduta", "Stephanie D Byrum", "Lisa Orr", "Alan J Tackett", "Samuel G Mackintosh", "Ricky D Edmondson", "Dorothy A Kieffer", "R J Martin", "Sean H Adams", "Nosratola D Vaziri", "John M Arthur"], "journal": "PloS one", "year": 2019, "abstract": "BACKGROUND: Resistant starch is a prebiotic metabolized by the gut bacteria. It has been shown to attenuate chronic kidney disease (CKD) progression in rats. Previous studies employed taxonomic analysis using 16S rRNA sequencing and untargeted metabolomics profiling. Here we expand these studies by metaproteomics, gaining new insight into the host-microbiome interaction.\nMETHODS: Differences between cecum contents in CKD rats fed a diet containing resistant starch with those fed a diet containing digestible starch were examined by comparative metaproteomics analysis. Taxonomic information was obtained using unique protein sequences. Our methodology results in quantitative data covering both host and bacterial proteins.\nRESULTS: 5,834 proteins were quantified, with 947 proteins originating from the host organism. Taxonomic information derived from metaproteomics data surpassed previous 16S RNA analysis, and reached species resolutions for moderately abundant taxonomic groups. In particular, the Ruminococcaceae family becomes well resolved-with butyrate producers and amylolytic species such as R. bromii clearly visible and significantly higher while fibrolytic species such as R. flavefaciens are significantly lower with resistant starch feeding. The observed changes in protein patterns are consistent with fiber-associated improvement in CKD phenotype. Several known host CKD-associated proteins and biomarkers of impaired kidney function were significantly reduced with resistant starch supplementation. Data are available via ProteomeXchange with identifier PXD008845.\nCONCLUSIONS: Metaproteomics analysis of cecum contents of CKD rats with and without resistant starch supplementation reveals changes within gut microbiota at unprecedented resolution, providing both functional and taxonomic information. 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Total number of proteins quantified, and number of significant proteins using either p<0.05 or p<0.01 thresholds after Benjamini-Hochberg correction for multiple testing is reported for each of the quantification methods used.", "structure": {"pmcid": "PMC6353070", "section_index": 14, "section_title": "Metaproteomics protein signature of cecal contents from rats fed resistant starch or digestible starch diets", "row_count": 0, "column_count": 0}, "table": {"label": "Table 1", "caption": "Number of quantified proteins by various methods.For a protein to be quantified, a p-value had to be calculated (requiring at least 3 non-zero quantitative values in either CKD-DS or CKD-RS group). Total number of proteins quantified, and number of significant proteins using either p<0.05 or p<0.01 thresholds after Benjamini-Hochberg correction for multiple testing is reported for each of the quantification methods used.", "rows": [], "row_count": 0, "column_count": 0, "numeric_cells": 0, "header_rows": 0, "locator": "section[14]/table-wrap[1]#pone.0199274.t001"}}, {"id": "asset:table:pmid:30699108:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:80d19ff745c912fe67fd5a63220e50081293d0fbcb57592a0ae74e1e8ba251a9", "bytes": 300, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[2]#pone.0199274.t002", "version": null, "note": "Representative differentially-abundant host proteins in cecal contents from CKD rats fed digestible starch (DS) or resistant starch (RS).", "structure": {"pmcid": "PMC6353070", "section_index": 14, 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"row_count": 0, "column_count": 0}, "table": {"label": "Table 5", "caption": "GO categories under-represented in CKD-RS microbial proteins.", "rows": [], "row_count": 0, "column_count": 0, "numeric_cells": 0, "header_rows": 0, "locator": "section[17]/table-wrap[2]#pone.0199274.t005"}}, {"id": "asset:table:pmid:30699108:6", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:54650462dd105e9eae39c57441e21ef677b5d310b474952ddadce7b926200890", "bytes": 223, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[18]/table-wrap[1]#pone.0199274.t006", "version": null, "note": "GO categories over-represented in CKD-RS microbial proteins.", "structure": {"pmcid": "PMC6353070", "section_index": 18, "section_title": "GO categories over-represented in CKD-RS microbial proteins", "row_count": 0, "column_count": 0}, "table": {"label": "Table 6", "caption": "GO categories over-represented in CKD-RS microbial proteins.", "rows": [], "row_count": 0, "column_count": 0, "numeric_cells": 0, "header_rows": 0, "locator": "section[18]/table-wrap[1]#pone.0199274.t006"}}], "gaps": ["asset:data:geo:PXD008845 not downloaded", "asset:data:geo:PXD008845 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "PCA"}}, {"id": "method-2", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 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