{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T02:03:26Z","timestamp":1781921006727,"version":"3.54.5"},"reference-count":56,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,3,17]],"date-time":"2023-03-17T00:00:00Z","timestamp":1679011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Cardiac surgery-associated acute kidney injury (CSA-AKI) is a common hospital-acquired AKI that carries a grave disease burden. Recently, gut-kidney crosstalk has greatly changed our understanding of the pathogenesis of kidney diseases. However, the relationship between gut microbial dysbiosis and CSA-AKI remains unclear. The purpose of this study was to investigate the possible contributions of gut microbiota alterations in CSA-AKI patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Patients undergoing cardiac surgery were enrolled and divided into acute kidney injury (AKI) and Non_AKI groups. Faecal samples were collected before the operation. Shotgun metagenomic sequencing was performed to identify the taxonomic composition of the intestinal microbiome. All groups were statistically compared with alpha- and beta-diversity analysis, and linear discriminant analysis effect size (LEfSe) analysis was performed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 70 individuals comprising 35 AKI and 35 Non_AKI were enrolled in the study. There was no significant difference between the AKI and Non_AKI groups with respect to the alpha-and beta-diversity of the Shannon index, Simpson or Chao1 index values except with respect to functional pathways (<jats:italic>p<\/jats:italic>\u2009&amp;lt;\u20090.05). However, the relative abundance of top 10 gut microbiota in CSA-AKI was different from the Non_AKI group. Interestingly, both LEfSe and multivariate analysis confirmed that the species <jats:italic>Escherichia coli<\/jats:italic>, <jats:italic>Rothia mucilaginosa<\/jats:italic>, and <jats:italic>Clostridium innocuum<\/jats:italic> were associated with CSA-AKI. Moreover, correlation heat map indicated that altered pathways and disrupted function could be attributed to disturbances of gut microbiota involving <jats:italic>Escherichia coli<\/jats:italic>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Dysbiosis of the intestinal microbiota in preoperative stool affects susceptibility to CSA-AKI, indicating the crucial role of key microbial players in the development of CSA-AKI. This work provides valuable knowledge for further study of the contribution of gut microbiota in CSA-AKI.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmicb.2023.1119959","type":"journal-article","created":{"date-parts":[[2023,3,17]],"date-time":"2023-03-17T04:26:23Z","timestamp":1679027183000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Evaluation of the contribution of gut microbiome dysbiosis to cardiac surgery-associated acute kidney injury by comparative metagenome analysis"],"prefix":"10.3389","volume":"14","author":[{"given":"Ying","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyi","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingchun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yali","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunpeng","family":"Bai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linling","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yirong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunbo","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jimei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,3,17]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.1038\/ki.2012.440","article-title":"The intestinal microbiota, a leaky gut, and abnormal immunity in kidney disease","volume":"83","author":"Anders","year":"2013","journal-title":"Kidney Int."},{"key":"ref2","doi-asserted-by":"publisher","first-page":"142","DOI":"10.3390\/metabo10040142","article-title":"Microbiome-metabolome signature of acute kidney injury","volume":"10","author":"Andrianova","year":"2020","journal-title":"Metabolites"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1038\/nature09944","article-title":"Enterotypes of the human gut microbiome","volume":"473","author":"Arumugam","year":"2011","journal-title":"Nature"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"9234","DOI":"10.3390\/ijms21239234","article-title":"Bacterial metabolites of human gut microbiota correlating with depression","volume":"21","author":"Averina","year":"2020","journal-title":"Int. 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