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Abstract
Small intestinal bacterial overgrowth (SIBO) has been implicated in symptoms associated with functional gastrointestinal disorders (FGIDs), though mechanisms remain poorly defined and treatment involves non-specific antibiotics. Here we show that SIBO based on duodenal aspirate culture reflects an overgrowth of anaerobes, does not correspond with patient symptoms, and may be a result of dietary preferences. Small intestinal microbial composition, on the other hand, is significantly altered in symptomatic patients and does not correspond with aspirate culture results. In a pilot interventional study we found that switching from a high fiber diet to a low fiber, high simple sugar diet triggered FGID-related symptoms and decreased small intestinal microbial diversity while increasing small intestinal permeability. Our findings demonstrate that characterizing small intestinal microbiomes in patients with gastrointestinal symptoms may allow a more targeted antibacterial or a diet-based approach to treatment.
Small intestinal bacterial overgrowth (SIBO) has been associated with functional gastrointestinal disorders. Here, the authors show that SIBO may be a result of dietary preferences, and patient symptoms correlate with changes in small intestinal microbial composition but not with SIBO.
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1 Mayo Clinic, Division of Gastroenterology and Hepatology, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X)
2 University of Minnesota, BioTechnology Institute, College of Biological Sciences, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000000419368657); Macalester College, Department of Biology, Saint Paul, USA (GRID:grid.259382.7) (ISNI:0000 0001 1551 4707)
3 Mayo Clinic, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X)
4 Imperial College, Computational and Systems Medicine Section of the Department of Surgery and Cancer, (London), UK (GRID:grid.7445.2) (ISNI:0000 0001 2113 8111)
5 The Ohio State University, Department of Veterinary Preventive Medicine, Columbus, USA (GRID:grid.261331.4) (ISNI:0000 0001 2285 7943)
6 Mayo Clinic, Division of Internal Medicine, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X)
7 Mayo Clinic, Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X)
8 Icahn School of Medicine at Mount Sinai, Department of Genetics and Genomic Sciences, Medicine, and Clinical Immunology, New York, USA (GRID:grid.59734.3c) (ISNI:0000 0001 0670 2351)
9 Mayo Clinic, Division of Gastroenterology and Hepatology, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X); Mayo Clinic, Department of Physiology and Biomedical Engineering, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X)
10 Stanford University, Department of Microbiology and Immunology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
11 Mayo Clinic, Division of Gastroenterology, Jacksonville, USA (GRID:grid.417467.7) (ISNI:0000 0004 0443 9942)
12 University of Minnesota, BioTechnology Institute, College of Biological Sciences, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000000419368657); University of Minnesota, Department of Computer Science and Engineering, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000000419368657)