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Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet
An imbalance of energy intake and expenditure is commonly considered as the fundamental cause of obesity. However, individual variations in susceptibility to obesity do indeed exist in both humans and animals, even among those with the same living environments and dietary intakes. To further explore...
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Published in: | Nutrients 2024-05, Vol.16 (11), p.1579 |
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description | An imbalance of energy intake and expenditure is commonly considered as the fundamental cause of obesity. However, individual variations in susceptibility to obesity do indeed exist in both humans and animals, even among those with the same living environments and dietary intakes. To further explore the potential influencing factors of these individual variations, male C57BL/6J mice were used for the development of obesity-prone and obesity-resistant mice models and were fed high-fat diets for 16 weeks. Compared to the obesity-prone mice, the obesity-resistant group showed a lower body weight, liver weight, adipose accumulation and pro-inflammatory cytokine levels. 16S rRNA sequencing, which was conducted for fecal microbiota analysis, found that the fecal microbiome's structural composition and biodiversity had changed in the two groups. The genera
,
,
and
increased in the obesity-prone mice, and the genera
,
and
were enriched in the obesity-resistant mice. Using widely targeted metabolomics analysis, 166 differential metabolites were found, especially those products involved in arachidonic acid (AA) metabolism, which were significantly reduced in the obesity-resistant mice. Moreover, KEGG pathway analysis exhibited that AA metabolism was the most enriched pathway. Significantly altered bacteria and obesity-related parameters, as well as AA metabolites, exhibited strong correlations. Overall, the phenotypes of the obesity-prone and obesity-resistant mice were linked to gut microbiota and AA metabolism, providing new insight for developing an in-depth understanding of the driving force of obesity resistance and a scientific reference for the targeted prevention and treatment of obesity. |
doi_str_mv | 10.3390/nu16111579 |
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,
,
and
increased in the obesity-prone mice, and the genera
,
and
were enriched in the obesity-resistant mice. Using widely targeted metabolomics analysis, 166 differential metabolites were found, especially those products involved in arachidonic acid (AA) metabolism, which were significantly reduced in the obesity-resistant mice. Moreover, KEGG pathway analysis exhibited that AA metabolism was the most enriched pathway. Significantly altered bacteria and obesity-related parameters, as well as AA metabolites, exhibited strong correlations. Overall, the phenotypes of the obesity-prone and obesity-resistant mice were linked to gut microbiota and AA metabolism, providing new insight for developing an in-depth understanding of the driving force of obesity resistance and a scientific reference for the targeted prevention and treatment of obesity.</description><identifier>ISSN: 2072-6643</identifier><identifier>EISSN: 2072-6643</identifier><identifier>DOI: 10.3390/nu16111579</identifier><identifier>PMID: 38892512</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Amino acids ; Animals ; Arachidonic acid ; Arachidonic Acid - metabolism ; Bacteria ; Bacteria - classification ; Body Weight ; Cytokines ; Diet ; Diet, High-Fat - adverse effects ; Disease Models, Animal ; Feces ; Feces - microbiology ; Gastrointestinal Microbiome - physiology ; gut microbiota ; Male ; Metabolism ; Metabolites ; Mice ; Mice, Inbred C57BL ; Microbiota ; Microbiota (Symbiotic organisms) ; Obesity ; Obesity - metabolism ; Obesity - microbiology ; obesity prone ; obesity resistant ; Overweight ; Proteins ; RNA, Ribosomal, 16S - genetics ; Taxonomy ; Tumor necrosis factor-TNF ; Unsaturated fatty acids ; widely targeted metabolomics</subject><ispartof>Nutrients, 2024-05, Vol.16 (11), p.1579</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 by the authors. 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c429t-7c9a39d0b0e5620f230e98566817b2a7d0d94752cbb4792a0ec80f72f35b0cb43</cites><orcidid>0000-0002-0529-0719</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3067501533/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3067501533?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38892512$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Huixia</creatorcontrib><creatorcontrib>Chen, Shiqi</creatorcontrib><creatorcontrib>Yang, Liu</creatorcontrib><creatorcontrib>Zhang, Shuai</creatorcontrib><creatorcontrib>Qin, Linqian</creatorcontrib><creatorcontrib>Jiang, Haiyang</creatorcontrib><title>Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet</title><title>Nutrients</title><addtitle>Nutrients</addtitle><description>An imbalance of energy intake and expenditure is commonly considered as the fundamental cause of obesity. However, individual variations in susceptibility to obesity do indeed exist in both humans and animals, even among those with the same living environments and dietary intakes. To further explore the potential influencing factors of these individual variations, male C57BL/6J mice were used for the development of obesity-prone and obesity-resistant mice models and were fed high-fat diets for 16 weeks. Compared to the obesity-prone mice, the obesity-resistant group showed a lower body weight, liver weight, adipose accumulation and pro-inflammatory cytokine levels. 16S rRNA sequencing, which was conducted for fecal microbiota analysis, found that the fecal microbiome's structural composition and biodiversity had changed in the two groups. The genera
,
,
and
increased in the obesity-prone mice, and the genera
,
and
were enriched in the obesity-resistant mice. Using widely targeted metabolomics analysis, 166 differential metabolites were found, especially those products involved in arachidonic acid (AA) metabolism, which were significantly reduced in the obesity-resistant mice. Moreover, KEGG pathway analysis exhibited that AA metabolism was the most enriched pathway. Significantly altered bacteria and obesity-related parameters, as well as AA metabolites, exhibited strong correlations. Overall, the phenotypes of the obesity-prone and obesity-resistant mice were linked to gut microbiota and AA metabolism, providing new insight for developing an in-depth understanding of the driving force of obesity resistance and a scientific reference for the targeted prevention and treatment of obesity.</description><subject>Amino acids</subject><subject>Animals</subject><subject>Arachidonic acid</subject><subject>Arachidonic Acid - metabolism</subject><subject>Bacteria</subject><subject>Bacteria - classification</subject><subject>Body Weight</subject><subject>Cytokines</subject><subject>Diet</subject><subject>Diet, High-Fat - adverse effects</subject><subject>Disease Models, Animal</subject><subject>Feces</subject><subject>Feces - microbiology</subject><subject>Gastrointestinal Microbiome - physiology</subject><subject>gut microbiota</subject><subject>Male</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Mice</subject><subject>Mice, Inbred C57BL</subject><subject>Microbiota</subject><subject>Microbiota (Symbiotic organisms)</subject><subject>Obesity</subject><subject>Obesity - metabolism</subject><subject>Obesity - microbiology</subject><subject>obesity prone</subject><subject>obesity resistant</subject><subject>Overweight</subject><subject>Proteins</subject><subject>RNA, Ribosomal, 16S - genetics</subject><subject>Taxonomy</subject><subject>Tumor necrosis factor-TNF</subject><subject>Unsaturated fatty acids</subject><subject>widely targeted metabolomics</subject><issn>2072-6643</issn><issn>2072-6643</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkltvFCEYhidGY5vaG3-AIfHGmEzlMAPDldn0nLSpMXpNgGF2v80sVGDU_vuyuz2tES4gH-_7kO9QVe8JPmJM4i9-IpwQ0gr5qtqnWNCa84a9fnHfqw5TWuL1Elhw9rbaY10naUvofvX3BFIGbzM6nzK6BhuDgZA10r5Hs6jtAvrgwaKZhR5du6xNGCGtEHh0Y1yCfFd_i8G7jeEx8r0cKWu_ITr0B_ICaXQB80V9pjM6AZffVW8GPSZ3-HAeVD_PTn8cX9RXN-eXx7Or2jZU5lpYqZnsscGu5RQPlGEnu5bzjghDtehxLxvRUmtMIyTV2NkOD4IOrDXYmoYdVJdbbh_0Ut1GWOl4p4IGtQmEOFc6ZrCjU8XEWdNY4jBpLObSYEp7Z4jgVAjKC-vrlnU7mZXrrfM56nEHuvviYaHm4bcqDRJNw0khfHogxPBrcimrFSTrxlF7F6akWGlRhzEjbZF-_Ee6DFP0pVZFxUWLi4Y9q-a6ZAB-COVju4aqmZBC4payNevoP6qye7cCW7o3QInvGD5vDWUeUopueEqSYLWeO_U8d0X84WVZnqSPU8buAd5dz1Y</recordid><startdate>20240523</startdate><enddate>20240523</enddate><creator>Zhang, Huixia</creator><creator>Chen, Shiqi</creator><creator>Yang, Liu</creator><creator>Zhang, Shuai</creator><creator>Qin, Linqian</creator><creator>Jiang, Haiyang</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-0529-0719</orcidid></search><sort><creationdate>20240523</creationdate><title>Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet</title><author>Zhang, Huixia ; Chen, Shiqi ; Yang, Liu ; Zhang, Shuai ; Qin, Linqian ; Jiang, Haiyang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c429t-7c9a39d0b0e5620f230e98566817b2a7d0d94752cbb4792a0ec80f72f35b0cb43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Amino acids</topic><topic>Animals</topic><topic>Arachidonic acid</topic><topic>Arachidonic Acid - metabolism</topic><topic>Bacteria</topic><topic>Bacteria - classification</topic><topic>Body Weight</topic><topic>Cytokines</topic><topic>Diet</topic><topic>Diet, High-Fat - adverse effects</topic><topic>Disease Models, Animal</topic><topic>Feces</topic><topic>Feces - microbiology</topic><topic>Gastrointestinal Microbiome - physiology</topic><topic>gut microbiota</topic><topic>Male</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Mice</topic><topic>Mice, Inbred C57BL</topic><topic>Microbiota</topic><topic>Microbiota (Symbiotic organisms)</topic><topic>Obesity</topic><topic>Obesity - metabolism</topic><topic>Obesity - microbiology</topic><topic>obesity prone</topic><topic>obesity resistant</topic><topic>Overweight</topic><topic>Proteins</topic><topic>RNA, Ribosomal, 16S - genetics</topic><topic>Taxonomy</topic><topic>Tumor necrosis factor-TNF</topic><topic>Unsaturated fatty acids</topic><topic>widely targeted metabolomics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Huixia</creatorcontrib><creatorcontrib>Chen, Shiqi</creatorcontrib><creatorcontrib>Yang, Liu</creatorcontrib><creatorcontrib>Zhang, Shuai</creatorcontrib><creatorcontrib>Qin, Linqian</creatorcontrib><creatorcontrib>Jiang, Haiyang</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Physical Education Index</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Nutrients</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Huixia</au><au>Chen, Shiqi</au><au>Yang, Liu</au><au>Zhang, Shuai</au><au>Qin, Linqian</au><au>Jiang, Haiyang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet</atitle><jtitle>Nutrients</jtitle><addtitle>Nutrients</addtitle><date>2024-05-23</date><risdate>2024</risdate><volume>16</volume><issue>11</issue><spage>1579</spage><pages>1579-</pages><issn>2072-6643</issn><eissn>2072-6643</eissn><abstract>An imbalance of energy intake and expenditure is commonly considered as the fundamental cause of obesity. However, individual variations in susceptibility to obesity do indeed exist in both humans and animals, even among those with the same living environments and dietary intakes. To further explore the potential influencing factors of these individual variations, male C57BL/6J mice were used for the development of obesity-prone and obesity-resistant mice models and were fed high-fat diets for 16 weeks. Compared to the obesity-prone mice, the obesity-resistant group showed a lower body weight, liver weight, adipose accumulation and pro-inflammatory cytokine levels. 16S rRNA sequencing, which was conducted for fecal microbiota analysis, found that the fecal microbiome's structural composition and biodiversity had changed in the two groups. The genera
,
,
and
increased in the obesity-prone mice, and the genera
,
and
were enriched in the obesity-resistant mice. Using widely targeted metabolomics analysis, 166 differential metabolites were found, especially those products involved in arachidonic acid (AA) metabolism, which were significantly reduced in the obesity-resistant mice. Moreover, KEGG pathway analysis exhibited that AA metabolism was the most enriched pathway. Significantly altered bacteria and obesity-related parameters, as well as AA metabolites, exhibited strong correlations. Overall, the phenotypes of the obesity-prone and obesity-resistant mice were linked to gut microbiota and AA metabolism, providing new insight for developing an in-depth understanding of the driving force of obesity resistance and a scientific reference for the targeted prevention and treatment of obesity.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>38892512</pmid><doi>10.3390/nu16111579</doi><orcidid>https://orcid.org/0000-0002-0529-0719</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Amino acids Animals Arachidonic acid Arachidonic Acid - metabolism Bacteria Bacteria - classification Body Weight Cytokines Diet Diet, High-Fat - adverse effects Disease Models, Animal Feces Feces - microbiology Gastrointestinal Microbiome - physiology gut microbiota Male Metabolism Metabolites Mice Mice, Inbred C57BL Microbiota Microbiota (Symbiotic organisms) Obesity Obesity - metabolism Obesity - microbiology obesity prone obesity resistant Overweight Proteins RNA, Ribosomal, 16S - genetics Taxonomy Tumor necrosis factor-TNF Unsaturated fatty acids widely targeted metabolomics |
title | Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet |
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