Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Obesity is reaching epidemic proportions worldwide. This excessive increase of adipose tissue is a risk factor for the development of multiple diseases and premature death. Amongst associated diseases, metabolic syndrome is one of the main comorbidities of obesity. In this context, the gut microbiota has been recognized as both shaping and responding to host energy metabolism. Recently metabolomics has emerged as a powerful tool to capture a snapshot of the metabolites present in a specific tissue, providing new insights into host-microbiota interactions. Integrating metabolomics with gut microbiota studies could help us better understand how specific species impact on host metabolomic profile. Dysosmobacter welbionis has been identified as a promising next generation beneficial bacteria with potential effects on fat mass and glucose metabolism in mice, and fecal Dysosmobacter spp. concentration was inversely correlated to body mass index fasting glucose and plasmatic HbA1c in humans.
Methods: Concentration of Dysosmobacter spp. was quantified by qPCR in the stools of insulin resistant overweight/obese participants with a metabolic syndrome and plasma metabolites were analyzed using untargeted metabolomics. Correlations between Dysosmobacter spp. fecal abundance and the 1169 identified plasma metabolites were uncovered using Spearman correlations followed by a false discovery rate correction.
Results: Interestingly, among the detected metabolites, Dysosmobacter spp. was exclusively associated with lipid molecules. Fecal concentration of Dysosmobacter spp. was positively associated with plasmatic levels of five phosphatidylcholines, arachidonate, two monoacylglycerols, twelve diacylglycerols, three lysophosphatidylethanolamines, one phosphatidylinositol and three lysophosphatidylinositols, as well as glycerophosphoethanolamines, glycerophosphatidylcholine and PC(P-16:0). The correlation was particularly interesting with acylcholine and lysophosphatidylcholine metabolites as, respectively, 6/8 and 8/10 detected molecules were positively associated with Dysosmobacter spp.
Conclusion: These results suggest that Dysosmobacter spp. plays a specific role in host lipid metabolism. This finding aligns with previous in vivo studies highlighting lipid profile alterations in multiple tissues of mice treated with this bacterium. Further studies are needed to elucidate the underlying mechanisms and assess its potential therapeutic applications.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12142885 | PMC |
http://dx.doi.org/10.1186/s12944-025-02629-z | DOI Listing |