1. R4 이은우 / Pf. 김나영

2. INTRODUCTION
The human microbiome has evolved to be a remarkably diverse, finely balanced, and highly environment-specific ecosystem.
The role of the gut microbiota in health and disease

3. Irritable bowel syndrome(IBS) is the most prevalent functional gastrointestinal disorder(FGID) in Western societies but the etiology of it remains poorly understood.
It is now well accepted that IBS is a disorder involving multiple pathophysiological mechanisms in which composition of gut microbiota has been proposed as one of the potentially important factors.

4. Explore the fecal and mucosa-associated microbiota of IBS patients
Thus, there is currently a need for an improved understanding of gut microbiota composition in IBS patients and for the potential role played by the gut microbiota in the generation of IBS symptoms.
Explore the fecal and mucosa-associated microbiota of IBS patients
and Evaluate whether these were associated with symptoms
Characterize the fecal microbiota alterations in IBS-D patients
and to Explore the effect of rifaximin on gut microbiota

6. MATERIALS Study population Apr 2010 - Nov 2013
Secondary/tertiary care outpatient clinics in Sweden
(Sahlgrenska University Hospital, Gothenburg, Sweden)
Aged years
IBS patients for Rome III criteria and healthy adults
Exclusion criteria
the use of probiotics or antibiotics during the study period or within 1 month before inclusion
another diagnosis that could explain the GI symptoms
severe psychiatric disease as the dominant clinical problem
other severe diseases, and a history of drug or alcohol abuse
Exploratory set(149) ; Apr 2010 – May 2012
Fecal samples(232) : IBS(110), healthy(39)
Mucosal biopsy samples(59) : IBS(39), healthy(20)
Validation set(46) : Jun 2012 – Nov 2013
Fecal samples(46) : IBS(29), healthy(17)

7. METHODS Assessment Statistical analysis Fecal and mucosal samples
Severity of psychological and gastrointestinal symptoms
The IBS Severity Scoring System (IBS-SSS)
the Hospital Anxiety and Depression (HAD) scale
a 4-day food diary
a 2-week stool diary based on the Bristol stool form scale.
Exhaled H2 and CH4 after an overnight fast
Detection of Methanobacteriales : quantitative PCR
Oro-anal transit time(OATT)
Statistical analysis
16S ribosomal RNA targeted pyrosequencing
α-Diversity, β-Diversity (classic approaches)
Machine learning procedure
Co-inertia analysis

8. RESULTS
Patient characteristics

9. Diversity analysis of fecal vs. mucosal microbiota
Fecal and mucosal microbiota are structurally distinct
but highly correlated

10. Diversity analysis of fecal/mucosal microbiota between groups (healthy, IBS patients, IBS Rome III subtypes, or IBS severity)
Neither microbiota richness nor variability differed between groups
in the exploratory set using classic ecologic descriptive approaches

11. Enterotype richness and distribution in healthy subjects and IBS patients
70%
16%
14%

12. Association of methanobacteriales with enterotype and IBS subtype/severity
Correlation !

13. Microbial signature for IBS symptom severity
A machine learning procedure allowed to reduce the 16S rRNA data complexity into a microbial signature for severe IBS. The signature was able to discriminate between patients with severe symptoms.

14. Taxonomic assessment of this microbial signature for IBS severity

15. Relationship to clinical parameters with this microbial signature for IBS severity

16. CONCLUSION By using classic approaches,
no differences in fecal microbiota abundance or composition between patients with IBS vs healthy patients.
A machine learning procedure allowed to reduce the 16S ribosomal RNA data complexity into a microbial signature for severe IBS, consisting of 90 bacterial operational taxonomic units.
The signature was able to discriminate between patients with severe symptoms, patients with mild/moderate symptoms, and healthy subjects.
By using this intestinal microbiota signature, they found IBS symptom severity to be associated negatively with microbial richness, exhaled CH4, presence of methanogens, and enterotypes enriched with Clostridiales or Prevotella species.

18. MATERIAL Study population Sep 2015 – Dec 2016
The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
Aged years
IBS-D patients(30) for Rome III criteria
→ → 10 weeks F/U
age- and gender matched healthy adults(13)
Exclusion criteria
the use of pro/prebiotics, corticosteroids, PPI, IBS prescription or antibiotics during the study period or within 4 weeks before inclusion
another diagnosis that could explain the GI symptoms
severe disease as the dominant clinical problem
PO Rifaximin 400mg bid for 2 weeks

19. METHODS Assessment Statistical analysis Fecal samples ; T0, T28
Lactulose hydrogen breath test (LHBT) → SIBO ; T0, T28
GI symptoms questionnaire 7-point ; T0, T14, T28, T56, T84
(abdominal pain, discomfort, distension, diarrhea,
defecatory urgency, incomplete evacuation)
Statistical analysis
PCR amplification of 16S rRNA gene, Miseq sequencing
SPSS version 23.0, Graph Prism version 7.0
Student’s t-test or Mann–Whitney U-test when appropriate
Chi-square test

20. RESULTS Patient characteristics
30 patients with IBS-D (M/F = 21/9, year)
13 Healthy controls (M/F = 8/5, year)
There were no significant difference in gender, age and body mass index between IBS-D patients and HCs.
Characterization of fecal microbiota in IBS-D patients
community richness parameters
community diversity parameters

21. Lactic acid-producing bacteria

22. Difference of abundant taxons between IBS-D patients and HCs
Butyrate-producing bacteria
Bacteroidetes
Collectively, these characteristic alterations in the fecal microbiota revealed that intestinal dysbiosis is associated with IBS-D.

23. Clinical improvement after Rifaximin intervention to IBS-D patients

24. Fecal microbiota in IBS-D patients before and after treatment
community richness parameters
community diversity parameters

25. Functions and metabolism of gut microbiome before and after treatment
SCFA-producing bacteria ↓
(short-chain fatty acid; butyrate, lactic acid, etc.)
activating the mucosal immune system, increasing intestinal permeability, activating sensory pathways
and modulating the enteric motility.

26. CONCLUSION
There were alterations of gut microbiota in Chinese IBS-D patients as compared to those in HC.
Rifaximin could relieve GI symptoms in IBS-D patients and normalize SIBO in 64.29% of IBS-D patients with SIBO and could induce alterations of some special bacteria rather than dramatic shifts in overall composition of gut microbiota.
Alterations of butyrate-producing and lactic acid-producing bacteria might contribute to the symptoms of IBS-D.
Altered gut microbiota might be associated with the pathogenesis of IBS-D
A possible therapeutic mechanism of rifaximin

27. DISCUSSION Limitations
Small sample size
Different results according to method of approach
SIBO eradication and GI symptom relief ?
The pathophysiology on metabolite level (microbiota & rifaximin)
lack of a mechanistic approach in studying the microbiome and its effects on the host
Some functions in the microbiome can also be highly specialized, limiting them to certain members of the microbial community
non-bacterial organisms such as viruses and fungi
Further studies are necessary to elucidate the mechanism.

28. 하지만 그럼에도 불구하고 Microbiota가 아주 많은 질환의 발생과 연관이 있고, 특히 그 원인에 대해 알게 되면 질병의 근본이나 초기단계부터 치료와 예방이 가능할 것이라는 기대를 갖고 있다는 점 등에서 앞으로 그 연구는 지속되어야 하겠습니다.

29. Thank you for listening