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1000 Titel
  • Circulating bacterial signature is linked to metabolic disease and shifts with metabolic alleviation after bariatric surgery
1000 Autor/in
  1. Chakaroun, Rima |
  2. Massier, Lucas |
  3. Heintz-Buschart, Anna |
  4. Said, Nedal |
  5. Fallmann, Joerg |
  6. Crane, Alyce |
  7. Schütz, Tatjana |
  8. Dietrich, Arne |
  9. Blüher, Matthias |
  10. Stumvoll, Michael |
  11. Musat, Niculina |
  12. Kovacs, Peter |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-06-22
1000 Erschienen in
1000 Quellenangabe
  • 13(1):105
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13073-021-00919-6 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218394/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Background!#!The microbiome has emerged as an environmental factor contributing to obesity and type 2 diabetes (T2D). Increasing evidence suggests links between circulating bacterial components (i.e., bacterial DNA), cardiometabolic disease, and blunted response to metabolic interventions. In this aspect, thorough next-generation sequencing-based and contaminant-aware approaches are lacking. To address this, we tested whether bacterial DNA could be amplified in the blood of subjects with obesity and high metabolic risk under strict experimental and analytical control and whether a putative bacterial signature is related to metabolic improvement after bariatric surgery.!##!Methods!#!Subjects undergoing bariatric surgery were recruited into sex- and BMI-matched subgroups with (n = 24) or without T2D (n = 24). Bacterial DNA in the blood was quantified and prokaryotic 16S rRNA gene amplicons were sequenced. A contaminant-aware approach was applied to derive a compositional microbial signature from bacterial sequences in all subjects at baseline and at 3 and 12 months after surgery. We modeled associations between bacterial load and composition with host metabolic and anthropometric markers. We further tested whether compositional shifts were related to weight loss response and T2D remission. Lastly, bacteria were visualized in blood samples using catalyzed reporter deposition (CARD)-fluorescence in situ hybridization (FISH).!##!Results!#!The contaminant-aware blood bacterial signature was associated with metabolic health. Based on bacterial phyla and genera detected in the blood samples, a metabolic syndrome classification index score was derived and shown to robustly classify subjects along their actual clinical group. T2D was characterized by decreased bacterial richness and loss of genera associated with improved metabolic health. Weight loss and metabolic improvement following bariatric surgery were associated with an early and stable increase of these genera in parallel with improvements in key cardiometabolic risk parameters. CARD-FISH allowed the detection of living bacteria in blood samples in obesity.!##!Conclusions!#!We show that the circulating bacterial signature reflects metabolic disease and its improvement after bariatric surgery. Our work provides contaminant-aware evidence for the presence of living bacteria in the blood and suggests a putative crosstalk between components of the blood and metabolism in metabolic health regulation.
1000 Sacherschließung
lokal Type 2 diabetes
lokal Bariatric Surgery/methods [MeSH]
lokal Metagenome [MeSH]
lokal Microbiota [MeSH]
lokal Male [MeSH]
lokal Translating the microbiome in health and disease
lokal Bariatric surgery
lokal DNA Contamination [MeSH]
lokal Metagenomics/methods [MeSH]
lokal Bacteremia/blood [MeSH]
lokal Glucose/metabolism [MeSH]
lokal Metabolic Diseases/blood [MeSH]
lokal Blood bacteria
lokal Obesity
lokal Postoperative Period [MeSH]
lokal Female [MeSH]
lokal Metabolic Diseases/diagnosis [MeSH]
lokal Adult [MeSH]
lokal DNA, Bacterial [MeSH]
lokal Humans [MeSH]
lokal Bariatric Surgery/adverse effects [MeSH]
lokal Middle Aged [MeSH]
lokal Body Weight [MeSH]
lokal Diabetes Mellitus, Type 2/blood [MeSH]
lokal RNA, Ribosomal, 16S [MeSH]
lokal Metabolic Diseases/etiology [MeSH]
lokal Metabolic syndrome
lokal ROC Curve [MeSH]
lokal Research
lokal Biomarkers [MeSH]
lokal In Situ Hybridization, Fluorescence [MeSH]
lokal Computational Biology/methods [MeSH]
lokal High-Throughput Nucleotide Sequencing [MeSH]
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0001-9901-1815|https://frl.publisso.de/adhoc/uri/TWFzc2llciwgTHVjYXM=|https://frl.publisso.de/adhoc/uri/SGVpbnR6LUJ1c2NoYXJ0LCBBbm5h|https://frl.publisso.de/adhoc/uri/U2FpZCwgTmVkYWw=|https://frl.publisso.de/adhoc/uri/RmFsbG1hbm4sIEpvZXJn|https://frl.publisso.de/adhoc/uri/Q3JhbmUsIEFseWNl|https://frl.publisso.de/adhoc/uri/U2Now7x0eiwgVGF0amFuYQ==|https://frl.publisso.de/adhoc/uri/RGlldHJpY2gsIEFybmU=|https://frl.publisso.de/adhoc/uri/QmzDvGhlciwgTWF0dGhpYXM=|https://frl.publisso.de/adhoc/uri/U3R1bXZvbGwsIE1pY2hhZWw=|https://frl.publisso.de/adhoc/uri/TXVzYXQsIE5pY3VsaW5h|https://frl.publisso.de/adhoc/uri/S292YWNzLCBQZXRlcg==
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1000 Erstellt am 2023-11-16T17:31:23.215+0100
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