Intestinal Organoids: A Tool for Modelling Diet–Microbiome–Host Interactions

Dietary patterns, microbiome dysbiosis, and gut microbial metabolites (GMMs) have a pivotal role in the homeostasis of intestinal epithelial cells and in disease progression, such as that of colorectal cancer (CRC). Although GMMs and microorganisms have crucial roles in many biological activities, m...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Trends in endocrinology and metabolism 2020-11, Vol.31 (11), p.848-858
Hauptverfasser: Rubert, Josep, Schweiger, Pawel J., Mattivi, Fulvio, Tuohy, Kieran, Jensen, Kim B., Lunardi, Andrea
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 858
container_issue 11
container_start_page 848
container_title Trends in endocrinology and metabolism
container_volume 31
creator Rubert, Josep
Schweiger, Pawel J.
Mattivi, Fulvio
Tuohy, Kieran
Jensen, Kim B.
Lunardi, Andrea
description Dietary patterns, microbiome dysbiosis, and gut microbial metabolites (GMMs) have a pivotal role in the homeostasis of intestinal epithelial cells and in disease progression, such as that of colorectal cancer (CRC). Although GMMs and microorganisms have crucial roles in many biological activities, models for deciphering diet–microbiome–host relationships are largely limited to animal models. Thus, intestinal organoids (IOs) have provided unprecedented opportunities for the generation of in vitro platforms with the sufficient level of complexity to model physiological and pathological diet–microbiome–host conditions. Overall, IO responses to GMM metabolites and microorganisms can provide new insights into the mechanisms by which those agents may prevent or trigger diseases, significantly extending our knowledge of diet–microbiome–host interactions. Dietary patterns modulate the gut microbiota and alter its functions by modulating the production of GMMs, which are capable of regulating homeostasis and the risk of disease.Complex interkingdom regulatory networks and crosstalk occur between the host, its gut microbiota, and its diet.Immortalized cancer cell lines grown in 2D monolayers differ genetically, metabolically, and phenotypically from in vivo cells. However, 3D IOs can mirror structural alterations, mutational signatures, and gene expression changes between patient and patient-derived organoids.IOs provide new opportunities to study how the gut microbiota , or its products, interact with intestinal epithelial cells. In this review, we discuss recent publications using IOs to study the nutrient–microbiome axis in gastrointestinal homeostasis and disease. We also highlight an array of novel approaches by which the nutrient–microbiota–gut epithelium triangle can be further understood and mechanisms governing gastrointestinal diseases better deciphered.
doi_str_mv 10.1016/j.tem.2020.02.004
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2453686307</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1043276020300461</els_id><sourcerecordid>2453686307</sourcerecordid><originalsourceid>FETCH-LOGICAL-c396t-50f66b3002f2d6d28b5beab00601d92c0b039948eaf617c856f95e1f1ceb93a63</originalsourceid><addsrcrecordid>eNp9kE1OwzAQhS0EglI4ABuUJZuEsZ04Cayq8lOkIliUteU4E-QqiYudIrHjDtyQk-CqhSWrmZHee5r3EXJGIaFAxeUyGbBLGDBIgCUA6R4Z0SIvYw6C7ocdUh6zXMAROfZ-CUDTgmaH5IhzKATk-Yg8P_QD-sH0qo2e3Kvqran9VTSJFta2UWNd9GhrbFvTv0Y3Bofvz69Ho52tjO0wHDPrh2iT4ZQejO39CTloVOvxdDfH5OXudjGdxfOn-4fpZB5rXoohzqARouIArGG1qFlRZRWqCkAArUumoQJelmmBqhE010UmmjJD2lCNVcmV4GNysc1dOfu2DhVkZ7wOn6oe7dpLlmZcFIJDHqR0Kw1_e--wkStnOuU-JAW5ASmXMoCUG5ASmAwgg-d8F7-uOqz_HL_kguB6K8BQ8t2gk14b7DXWxqEeZG3NP_E_l4WFAg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2453686307</pqid></control><display><type>article</type><title>Intestinal Organoids: A Tool for Modelling Diet–Microbiome–Host Interactions</title><source>Elsevier ScienceDirect Journals</source><creator>Rubert, Josep ; Schweiger, Pawel J. ; Mattivi, Fulvio ; Tuohy, Kieran ; Jensen, Kim B. ; Lunardi, Andrea</creator><creatorcontrib>Rubert, Josep ; Schweiger, Pawel J. ; Mattivi, Fulvio ; Tuohy, Kieran ; Jensen, Kim B. ; Lunardi, Andrea</creatorcontrib><description>Dietary patterns, microbiome dysbiosis, and gut microbial metabolites (GMMs) have a pivotal role in the homeostasis of intestinal epithelial cells and in disease progression, such as that of colorectal cancer (CRC). Although GMMs and microorganisms have crucial roles in many biological activities, models for deciphering diet–microbiome–host relationships are largely limited to animal models. Thus, intestinal organoids (IOs) have provided unprecedented opportunities for the generation of in vitro platforms with the sufficient level of complexity to model physiological and pathological diet–microbiome–host conditions. Overall, IO responses to GMM metabolites and microorganisms can provide new insights into the mechanisms by which those agents may prevent or trigger diseases, significantly extending our knowledge of diet–microbiome–host interactions. Dietary patterns modulate the gut microbiota and alter its functions by modulating the production of GMMs, which are capable of regulating homeostasis and the risk of disease.Complex interkingdom regulatory networks and crosstalk occur between the host, its gut microbiota, and its diet.Immortalized cancer cell lines grown in 2D monolayers differ genetically, metabolically, and phenotypically from in vivo cells. However, 3D IOs can mirror structural alterations, mutational signatures, and gene expression changes between patient and patient-derived organoids.IOs provide new opportunities to study how the gut microbiota , or its products, interact with intestinal epithelial cells. In this review, we discuss recent publications using IOs to study the nutrient–microbiome axis in gastrointestinal homeostasis and disease. We also highlight an array of novel approaches by which the nutrient–microbiota–gut epithelium triangle can be further understood and mechanisms governing gastrointestinal diseases better deciphered.</description><identifier>ISSN: 1043-2760</identifier><identifier>EISSN: 1879-3061</identifier><identifier>DOI: 10.1016/j.tem.2020.02.004</identifier><identifier>PMID: 33086077</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>gut microbial metabolites ; intestinal organoids ; microbiome ; phytochemicals ; single cell analysis</subject><ispartof>Trends in endocrinology and metabolism, 2020-11, Vol.31 (11), p.848-858</ispartof><rights>2020 The Author(s)</rights><rights>Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-50f66b3002f2d6d28b5beab00601d92c0b039948eaf617c856f95e1f1ceb93a63</citedby><cites>FETCH-LOGICAL-c396t-50f66b3002f2d6d28b5beab00601d92c0b039948eaf617c856f95e1f1ceb93a63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1043276020300461$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,65309</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33086077$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rubert, Josep</creatorcontrib><creatorcontrib>Schweiger, Pawel J.</creatorcontrib><creatorcontrib>Mattivi, Fulvio</creatorcontrib><creatorcontrib>Tuohy, Kieran</creatorcontrib><creatorcontrib>Jensen, Kim B.</creatorcontrib><creatorcontrib>Lunardi, Andrea</creatorcontrib><title>Intestinal Organoids: A Tool for Modelling Diet–Microbiome–Host Interactions</title><title>Trends in endocrinology and metabolism</title><addtitle>Trends Endocrinol Metab</addtitle><description>Dietary patterns, microbiome dysbiosis, and gut microbial metabolites (GMMs) have a pivotal role in the homeostasis of intestinal epithelial cells and in disease progression, such as that of colorectal cancer (CRC). Although GMMs and microorganisms have crucial roles in many biological activities, models for deciphering diet–microbiome–host relationships are largely limited to animal models. Thus, intestinal organoids (IOs) have provided unprecedented opportunities for the generation of in vitro platforms with the sufficient level of complexity to model physiological and pathological diet–microbiome–host conditions. Overall, IO responses to GMM metabolites and microorganisms can provide new insights into the mechanisms by which those agents may prevent or trigger diseases, significantly extending our knowledge of diet–microbiome–host interactions. Dietary patterns modulate the gut microbiota and alter its functions by modulating the production of GMMs, which are capable of regulating homeostasis and the risk of disease.Complex interkingdom regulatory networks and crosstalk occur between the host, its gut microbiota, and its diet.Immortalized cancer cell lines grown in 2D monolayers differ genetically, metabolically, and phenotypically from in vivo cells. However, 3D IOs can mirror structural alterations, mutational signatures, and gene expression changes between patient and patient-derived organoids.IOs provide new opportunities to study how the gut microbiota , or its products, interact with intestinal epithelial cells. In this review, we discuss recent publications using IOs to study the nutrient–microbiome axis in gastrointestinal homeostasis and disease. We also highlight an array of novel approaches by which the nutrient–microbiota–gut epithelium triangle can be further understood and mechanisms governing gastrointestinal diseases better deciphered.</description><subject>gut microbial metabolites</subject><subject>intestinal organoids</subject><subject>microbiome</subject><subject>phytochemicals</subject><subject>single cell analysis</subject><issn>1043-2760</issn><issn>1879-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kE1OwzAQhS0EglI4ABuUJZuEsZ04Cayq8lOkIliUteU4E-QqiYudIrHjDtyQk-CqhSWrmZHee5r3EXJGIaFAxeUyGbBLGDBIgCUA6R4Z0SIvYw6C7ocdUh6zXMAROfZ-CUDTgmaH5IhzKATk-Yg8P_QD-sH0qo2e3Kvqran9VTSJFta2UWNd9GhrbFvTv0Y3Bofvz69Ho52tjO0wHDPrh2iT4ZQejO39CTloVOvxdDfH5OXudjGdxfOn-4fpZB5rXoohzqARouIArGG1qFlRZRWqCkAArUumoQJelmmBqhE010UmmjJD2lCNVcmV4GNysc1dOfu2DhVkZ7wOn6oe7dpLlmZcFIJDHqR0Kw1_e--wkStnOuU-JAW5ASmXMoCUG5ASmAwgg-d8F7-uOqz_HL_kguB6K8BQ8t2gk14b7DXWxqEeZG3NP_E_l4WFAg</recordid><startdate>202011</startdate><enddate>202011</enddate><creator>Rubert, Josep</creator><creator>Schweiger, Pawel J.</creator><creator>Mattivi, Fulvio</creator><creator>Tuohy, Kieran</creator><creator>Jensen, Kim B.</creator><creator>Lunardi, Andrea</creator><general>Elsevier Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202011</creationdate><title>Intestinal Organoids: A Tool for Modelling Diet–Microbiome–Host Interactions</title><author>Rubert, Josep ; Schweiger, Pawel J. ; Mattivi, Fulvio ; Tuohy, Kieran ; Jensen, Kim B. ; Lunardi, Andrea</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-50f66b3002f2d6d28b5beab00601d92c0b039948eaf617c856f95e1f1ceb93a63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>gut microbial metabolites</topic><topic>intestinal organoids</topic><topic>microbiome</topic><topic>phytochemicals</topic><topic>single cell analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rubert, Josep</creatorcontrib><creatorcontrib>Schweiger, Pawel J.</creatorcontrib><creatorcontrib>Mattivi, Fulvio</creatorcontrib><creatorcontrib>Tuohy, Kieran</creatorcontrib><creatorcontrib>Jensen, Kim B.</creatorcontrib><creatorcontrib>Lunardi, Andrea</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Trends in endocrinology and metabolism</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rubert, Josep</au><au>Schweiger, Pawel J.</au><au>Mattivi, Fulvio</au><au>Tuohy, Kieran</au><au>Jensen, Kim B.</au><au>Lunardi, Andrea</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Intestinal Organoids: A Tool for Modelling Diet–Microbiome–Host Interactions</atitle><jtitle>Trends in endocrinology and metabolism</jtitle><addtitle>Trends Endocrinol Metab</addtitle><date>2020-11</date><risdate>2020</risdate><volume>31</volume><issue>11</issue><spage>848</spage><epage>858</epage><pages>848-858</pages><issn>1043-2760</issn><eissn>1879-3061</eissn><abstract>Dietary patterns, microbiome dysbiosis, and gut microbial metabolites (GMMs) have a pivotal role in the homeostasis of intestinal epithelial cells and in disease progression, such as that of colorectal cancer (CRC). Although GMMs and microorganisms have crucial roles in many biological activities, models for deciphering diet–microbiome–host relationships are largely limited to animal models. Thus, intestinal organoids (IOs) have provided unprecedented opportunities for the generation of in vitro platforms with the sufficient level of complexity to model physiological and pathological diet–microbiome–host conditions. Overall, IO responses to GMM metabolites and microorganisms can provide new insights into the mechanisms by which those agents may prevent or trigger diseases, significantly extending our knowledge of diet–microbiome–host interactions. Dietary patterns modulate the gut microbiota and alter its functions by modulating the production of GMMs, which are capable of regulating homeostasis and the risk of disease.Complex interkingdom regulatory networks and crosstalk occur between the host, its gut microbiota, and its diet.Immortalized cancer cell lines grown in 2D monolayers differ genetically, metabolically, and phenotypically from in vivo cells. However, 3D IOs can mirror structural alterations, mutational signatures, and gene expression changes between patient and patient-derived organoids.IOs provide new opportunities to study how the gut microbiota , or its products, interact with intestinal epithelial cells. In this review, we discuss recent publications using IOs to study the nutrient–microbiome axis in gastrointestinal homeostasis and disease. We also highlight an array of novel approaches by which the nutrient–microbiota–gut epithelium triangle can be further understood and mechanisms governing gastrointestinal diseases better deciphered.</abstract><cop>United States</cop><pub>Elsevier Ltd</pub><pmid>33086077</pmid><doi>10.1016/j.tem.2020.02.004</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1043-2760
ispartof Trends in endocrinology and metabolism, 2020-11, Vol.31 (11), p.848-858
issn 1043-2760
1879-3061
language eng
recordid cdi_proquest_miscellaneous_2453686307
source Elsevier ScienceDirect Journals
subjects gut microbial metabolites
intestinal organoids
microbiome
phytochemicals
single cell analysis
title Intestinal Organoids: A Tool for Modelling Diet–Microbiome–Host Interactions
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-24T19%3A57%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Intestinal%20Organoids:%20A%20Tool%20for%20Modelling%20Diet%E2%80%93Microbiome%E2%80%93Host%20Interactions&rft.jtitle=Trends%20in%20endocrinology%20and%20metabolism&rft.au=Rubert,%20Josep&rft.date=2020-11&rft.volume=31&rft.issue=11&rft.spage=848&rft.epage=858&rft.pages=848-858&rft.issn=1043-2760&rft.eissn=1879-3061&rft_id=info:doi/10.1016/j.tem.2020.02.004&rft_dat=%3Cproquest_cross%3E2453686307%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2453686307&rft_id=info:pmid/33086077&rft_els_id=S1043276020300461&rfr_iscdi=true