| Literature DB >> 22730468 |
Magnus Simrén1, Giovanni Barbara, Harry J Flint, Brennan M R Spiegel, Robin C Spiller, Stephen Vanner, Elena F Verdu, Peter J Whorwell, Erwin G Zoetendal.
Abstract
It is increasingly perceived that gut host-microbial interactions are important elements in the pathogenesis of functional gastrointestinal disorders (FGID). The most convincing evidence to date is the finding that functional dyspepsia and irritable bowel syndrome (IBS) may develop in predisposed individuals following a bout of infectious gastroenteritis. There has been a great deal of interest in the potential clinical and therapeutic implications of small intestinal bacterial overgrowth in IBS. However, this theory has generated much debate because the evidence is largely based on breath tests which have not been validated. The introduction of culture-independent molecular techniques provides a major advancement in our understanding of the microbial community in FGID. Results from 16S rRNA-based microbiota profiling approaches demonstrate both quantitative and qualitative changes of mucosal and faecal gut microbiota, particularly in IBS. Investigators are also starting to measure host-microbial interactions in IBS. The current working hypothesis is that abnormal microbiota activate mucosal innate immune responses which increase epithelial permeability, activate nociceptive sensory pathways and dysregulate the enteric nervous system. While we await important insights in this field, the microbiota is already a therapeutic target. Existing controlled trials of dietary manipulation, prebiotics, probiotics, synbiotics and non-absorbable antibiotics are promising, although most are limited by suboptimal design and small sample size. In this article, the authors provide a critical review of current hypotheses regarding the pathogenetic involvement of microbiota in FGID and evaluate the results of microbiota-directed interventions. The authors also provide clinical guidance on modulation of gut microbiota in IBS.Entities:
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Year: 2012 PMID: 22730468 PMCID: PMC3551212 DOI: 10.1136/gutjnl-2012-302167
Source DB: PubMed Journal: Gut ISSN: 0017-5749 Impact factor: 23.059
Figure 1Gut microbiota and the intrinsic and extrinsic factors that can affect its distribution and composition. A number of host mechanisms participate in gut microbiota modulation, including gastric acid secretion, fluid, anticommensal sIgA and antimicrobial peptide production, and gastrointestinal (GI) motility. Drugs that block acid secretion and affect GI motility can indirectly alter the microbiota. Antibiotics, depending on spectrum and dosage, will directly affect microbiota composition. Dietary modifications, including probiotic and fibre supplements, will also affect microbiota composition. MMC, migrating motor complexes; H+ hydrogen ions; O2, partial oxygen tension; sIgA, secretory immunoglobulin A; PPI, proton pump inhibitor; NSAID, non-steroidal anti-inflammatory drug.
Figure 2Gut microbiota composition in African children living in rural areas with a polysaccharide-rich diet when compared with Italian city children.35 (Reprinted with permission from Proc Natl Acad Sci USA).
Main features of culture-independent detection methods of gut microbiota
| Question | Target | Approach | Data generated | Can microbes be identified directly? | Main benefit | Main limitation |
| Which microbes are present in the GI tract? | Isolates | Cultivation | Phenotypic characterisation | Yes | Accurate species identification | Not representative |
| 16S rRNA gene | Cloning and sanger sequencing | Phylogenetic identification | Yes | Complete 16S rRNA gene sequence data | Cloning bias | |
| 16S rRNA gene | High-throughput sequencing | Phylogenetic identification | Yes | High-throughput data generation | Short reads | |
| 16S rRNA gene | Fingerpinting | Community profile | No | Fast comparison between communities | No direct link with phylogeny | |
| 16S rRNA | FISH | Cell numbers | Yes | Accurate enumeration | Dependent on 16S rRNA databases | |
| 16S rRNA gene | qPCR | 16S rRNA gene abundances | Yes | Wide dynamic range | Dependent on 16S rRNA databases | |
| 16S rRNA gene | Phylogenetic microarray | Phylogenetic identification | Yes | High-throughput phylogenetic profiling | Dependent on 16S rRNA databases | |
| What microbial genes are present in the GI tract? | Community DNA | Sequence-based metagenomics | Gene sequences | Not always | High-throughput data generation | Function mainly based on predictions |
| Community DNA | Function-based metagenomics | Functional properties encoded on DNA fragment | Not always | Functional properties linked to DNA sequences | Suitable cloning host/system and screening assays needed | |
| What are GI tract microbes doing? | mRNA | Metatranscriptomics | Community gene expression | Not always | Direct information about microbial activity | Community RNA extraction challenging |
| Proteins | Metaproteomics | Community protein production | Not always | Direct information about microbial activity | No uniform protocol for all cell fractions | |
| Metabonomics | Metabonomics/metabolomics | Community metabolity profiles | No | Microbiota activity representation | No link with microbes or its function | |
| Lactulose hydrogen breath test | Measuring GI tract gas production | Hydrogen and methane breath content | No | Unclear, simple test but not validated for diagnosing SIBO | May simply measure small intestinal transit time to caecum | |
| Glucose hydrogen breath test | Measuring GI tract gas production | Hydrogen breath content | No | Same as above | Poor sensitivity; misses distal SIBO |
FISH, fluorescent in situ hybridisation; GI, gastrointestinal; qPCR, quantitative PCR; SIBO, small intestinal bacterial overgrowth.
Figure 3The lactulose hydrogen breath test (LHBT) predominantly measures small intestinal transit rather than small intestinal bacterial overgrowth (SIBO) in irritable bowel syndrome (IBS) patients. Upper schematic shows ingestion of test meal with subsequent serial measurement of both H2 gas, resulting from fermentation of the lactulose by intestinal bacteria, and Tc99 scanning in the caecum. This latter measurement detects when the test meal has reached the caecum. The stylised drawing below shows a representative result from an IBS patient with serial measurements over time. The Tc99 had already reached the caecum in large quantities before the H2 PPM level has reached the threshold for an abnormal test. This demonstrates that the increased H2 production results from fermentation by colonic bacteria, not by abnormal bacteria small intestine (ie, SIBO).94
Summary of studies culturing small bowel microbiome
| Study | Number of patients | Sample type | Microbiology results | Comments |
| Drasar and Shiner | 13 Diarrhoea, all investigations negative | Jejunal capsule | No difference from controls; no increased numbers of pathogens or non-pathogens | Possible IBS but not defined as IBS |
| Rumessen | 60 Patients suspected of SIBO | Proximal jejunal aspirate | 15 With no predisposing cause had no evidence of SIBO; of 23 with SIBO, 4 had no predisposing cause | Groups poorly defined, 8 IBS identified and all negative for SIBO; 22 cases considered inconclusive |
| Corazza | 31 Chronic diarrhoea, no predisposing cause | Proximal jejunal aspirate | 10 Had SIBO (≥106 cfu/ml or colonic bacteria), 2 IBS, 8 other multiple other diagnoses | IBS not defined, and total IBS not clear |
| Bardhan | 10 Controls; 4 irritable colon; 22 other | Endoscopic aspirates from proximal jejunum | No positive cultures in irritable colon | Positive cultures in 11 cases, many postsurgical |
| Lewis | 23 With functional bowel disorders | Duodenal endoscopic aspirate | Mean control count 3.2×102 cfu/ml, no anaerobes, no sterile samples | No specific IBS, defined as functional bowel disorders |
| Sullivan | 7 IBS; 20 controls | Proximal jejunal biopsy using Watson capsule | No differences, flora similar to normal oropharyngeal flora | Colonic pathogen in 2 healthy subjects |
| Posserud | 162 IBS; 42 controls | Proximal jejunal aspirate | 4%≥105 cfu, same as controls. Subanalysis using ≥5×103, 43% IBS vs 12% controls | No correlation with motor pattern in IBS group |
| Kerckhoffs | 8 IBS; 9 controls | Proximal jejunal aspirate | No different number diagnosed with SIBO using multiple definitions | No differences also using molecular-based counts |
| Choung | 148 IBS; 542 ‘other indications to test for SIBO’ | Duodenal endoscopic aspirate | 2% IBS >105 cfu/ml 10% in ‘other’ indications | Retrospective study 18% IBS >0<105 cfu/ml |
| Pyleris | 85 IBS 150 non-IBS | Duodenal endoscopic aspirate | 37% IBS >103 cfu/ml 15.11% non-IBS | All investigated because of UGI bleed |
IBS, irritable bowel syndrome; SIBO, small intestinal bacterial overgrowth; UGI, upper gastrointestinal.
Figure 4Plot chart of currently available strategies for modifying gut microbiota aiming to demonstrate the relationship between the effectiveness and invasiveness/safety of the proposed approach. FODMAP, fermentable oligo-, di- and mono-saccharides and polyols; PPI, proton pump inhibitor.
Summary of culture and molecular studies of colonic microbiome
| Study | Subject | Sample | Method | Patient group | Main finding | Country of study |
| Balsari |
IBS (n=20) Ctrls (n=20) | Faeces | Culture | IBS |
↓ Coliform bacteria ↓ ↓ | Italy |
| Si |
IBS (n=25) Ctrls (n=25) | Faeces | Culture | IBS |
↓ Bifidobacterium ↑ Enterobacteriaceae ↓ | China |
| Malinen |
IBS (n=27) Ctrls (n=22) | Faeces | qPCR | IBS |
↓ ↓ | Finland |
| IBS-D |
↓ | |||||
| IBS-C |
↑ ↑ | |||||
| Mättö |
IBS (n=26) Ctrls (n=25) | Faeces | CulturePCR-DGGE | IBS |
↑ Coliform bacteria ↑ Aerob to anaerob ratio ↓ Temporal stability | Finland |
| Maukonen |
IBS (n=24) Ctrls (n=16) | Faeces |
PCR-DGGE Affinity capture | IBS |
↓ Temporal stability | Finland |
| IBS-C |
↓ | |||||
| Kassinen |
IBS (n=24) Ctrls (n=23) | Faeces |
GC-profiling + sequencing of 16S rRNA genes qPCR | IBS |
↓ ↓ ↓ Subgroup-diff (D, C, M) | Finland |
| Rajilić-Stojanović |
IBS (n=20) Ctrls (n=20) | Faeces | Microarray | IBS |
Proteobacteria and specific Firmicutes↑ Other Firmicutes, Bacteroidetes and bifidobacteria ↓ | Finland |
| Kerckhoffs |
IBS (n=41) Ctrls (n=26) |
Faeces Duodenal mucosa |
FISH qPCR | IBS |
↓ ↓ | The Netherlands |
| Krogius-Kurikka |
IBS-D (n=10) Ctrls (n=23) | Faeces | GC-profiling + sequencing of 16S rRNA genes | IBS-D |
↑ Proteobacteria ↑ Firmicutes ↓ Actinobacteria ↓ Bacteroidetes | Finland |
| Lyra |
IBS (n=20) Ctrls (n=15) | Faeces | qPCR | IBS-D |
↑ ↓ | Finland |
| IBS-C |
↑ | |||||
| IBS-A |
↓ ↑ | |||||
| Tana |
IBS (n=26) Ctrls (n=26) | Faeces |
Culture qPCR | IBS |
↑ ↑ | Japan |
| Codling |
IBS (n=41) Ctrls (n=33) |
Faeces Colonic mucosa | PCR-DGGE | IBS |
↑ Temporal stability No significant difference Faecal/mucosal | Ireland |
| Carroll |
IBS-D (n=10) Ctrls (n=10) |
Faeces Colonic biopsies |
Culture qPCR | IBS-D |
↓ Aerobic bacteria | USA |
| Noor |
IBS (n=11) Ctrls (n=22) UC (n=13) | Faeces | PCR-DGGE + sequencing of 16S rRNA genes | IBS |
↓ Bacterial species ↓ Biodiversity ↑ Biological variability of predominant bacteria | UK |
| Malinen |
IBS (n=44) | Faeces | qPCR |
Other phylotypes neg assoc. | Finland | |
| Ponnusamy |
IBS (n=11) Ctrls (n=8) | Faeces | DGGE + qPCR of 16sRNA genes |
↑ Diversity in Bacteroidetes & Lactobacilli ↑ Alanine & pyroglutamic acid & phenolic compounds | Korea | |
| Rinttila |
IBS (n=96) Ctrls (n=23) | Faeces | qPCR | IBS |
| Finland |
| Saulnier |
IBS (n=22) Ctrls (n=22) (Children) | Faeces | 16s Metagenomic sequencing and DNA microarray | IBS |
↑ γ Proteobacteria Classified IBS subtypes using sets of discriminant bacterial species | USA |
| Rajilic-Stojanovic |
IBS (n=62) Ctrls (n=42) | Faeces | Phylogenetic 16S rRNA microarray and qPCR | IBS |
↑ Proteobacteria and specific Firmicutes ↓ Other Firmicutes, Bacteroidetes and bifidobacteria | Finland |
| Carroll |
IBS-D (n=16) Ctrls (n=21) | FaecesColonic mucosa | T-RFLP fingerprinting of 16S rRNA - PCR | IBS-D | Diminished microbial biodiversity in faecal samples | USA |
| Parkes |
IBS-D (n=27) IBS-C (n=26) Ctrls (n=26) | Colonic mucosa |
FISH Confocal microscopy | IBS | Expansion of mucosa-associated microbiota; mainly bacteroides and clostridia; association with IBS subgroups and symptoms | UK |
| Jeffery |
IBS (n=37) Ctrls (n=20) | Faeces | Pyrosequencing 16SrRNA | Clustering of IBS patients—normal-like versus abnormal microbiota composition (increased ratio of Firmicutes to Bacteroidetes); association with symptom profile | Sweden |
n, number of randomised subjects.
B, Bifidobacterium; C, constipation; C, Clostridium; Cl, Clostridium; ctrls, controls; D, diarrhoea; DGGE, denaturing gradient gel electrophoresis; FISH, fluorescent in situ hybridisation; IBS, irritable bowel syndrome; L, Lactobacillus; qPCR, quantitative PCR;R, Ruminococcus; S, Staphylococcus; T-RFLP, terminal restriction fragment length polymorphism.
Placebo controlled clinical trials of single or mixed probiotic preparations in IBS
| Organism | n | Outcome | Reference |
| Studies in adult patients | |||
| | 54 | ↓ Global score | Gade |
| | 18 | ↓ Global score | Halpern |
| | 60 | ↓ Flatulence | Nobaek |
| | 20 | ↓ Pain, ‘all IBS symptoms’ | Niedzielin |
| | 12 | Negative | Sen |
| | 16 | Deterioration of symptoms | Ligaarden |
| | 25 | Negative | O'Sullivan |
| | 54 | Negative | Niv |
| | 75 | Negative | O'Mahony |
| | 75 | ↓ Pain and composite score | O'Mahony |
| | 362 | ↓ Pain and composite score | Whorwell |
| | 274 | ↓ Digestive discomfort | Guyonnet |
| | 34 | ↓ Maximum distension & pain | Agrawal |
| | 122 | ↓ Global score | Guglielmetti |
| | 52 | ↓ Bowel movements | Dolin |
| | 120 | ↑ Treatment satisfaction | Kruis |
| VSL#3® (x8)* | 25 | ↓ Bloating | Kim |
| VSL#3® (x8)* | 48 | ↓ Flatulence | Kim |
| Medilac DS® (x2)* | 40 | ↓ Pain | Kim |
| Mixture (x4)* | 103 | ↓ Global score | Kajander |
| Mixture (x4)* | 86 | ↓ Global score | Kajander |
| LAB4 (x4)* | 52 | ↓ Global score | Williams |
| Mixture (x4)* | 106 | Negative | Drouault-Holowacz |
| Mixture (x2)* | 40 | ↓ Pain | Sinn |
| ProSymbioFlor® (x2)* | 297 | ↓ Global score | Enck |
| Cultura® (x3)* | 74 | Negative | Simrén |
| Cultura® (x3)* | 52 | Negative | Sondergaard |
| Mixture (x4)* | 70 | ↓ Pain | Hong |
| Studies in paediatric patients | |||
| | 50 | ↓ Abdominal distension | Bausserman and Michail |
| | 104 | ↓ Pain | Gawronska |
| | 141 | ↓ Pain | Francavilla |
| VSL#3® (x8)* | 59 | ↓ Global score | Guandalini |
*Number of organisms in a mixture.
n, number of randomised subjects.
IBS, irritable bowel syndrome; L ramnosus, Lactobacillus ramnosus; L reuterii, Lactobacillus reuterii; L salivarius, Lactobacillus salivarius; S faecium, Streptococcus faecium.