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PRESIDENT & DIRECTOR MADRAS DIABETES RESEARCH
FOUNDATION,SIRUSERI, CHENNAI
CHAIRMANDR.MOHAN’S DIABETES SPECIALITIES CENTRE,
GOPALAPURAM, CHENNAI
WHO COLLABORATING CENTRE FOR NONCOMMUNICABLE DISEASES
Dr.V.Mohan., MD., Ph.D., D.Sc., D.Sc (Hon. Causa), FRCP (London, Edinburgh, Glasgow & Ireland), FNASc., FASc., FNA, FACE, FTWAS, MACP
MICROBIOTA AND DIABETES
ICMR CENTRE FOR ADVANCED RESEARCH ON DIABETES
Functions of gut microbiota
Gut microbiota and pathophysiology of
diabetes
Metagenomics
Prebiotics and probiotics
FLOW OF MY PRESENTATION
GUT MICROBIOTA Human gut hosts 100 trillion microorganisms!
Thousands of species!!
Weighing an average around 1.5 kg!!!
Microbiota changes from infancy to adulthood
Bacteria from 3 major groups represent ~ 95% of the total microbiota
Firmicutes Bacteroidetes Actinobacteria
Burcelin R et al. Acta Diabetol. 2011
Multiple site impact of gut microbiota on whole host metabolism
Functions of gut microbiota
Gut microbiota & pathophysiology of
diabetes
Metagenomics
Prebiotics and probiotics
FLOW OF MY PRESENTATION
‘GUT CONNECTION’ TO DIABETES
Type 1 diabetes
Type 2 diabetes
‘GUT CONNECTION’ IN TYPE 1 DIABETES
Gut microflora - Bacteroides thetaiotaomicron
Secretion of antimicrobial molecules defensin / angiogenin
Secreted by intestinal Paneth cells – into gut– fight intestinal microbes
Deficiency of Bacteroides thetaiotaomicron – Type 1 diabetes
‘Altered aggressiveness’ - Type 1 diabetes
Oxidative STRESS & pro-inflammation in type 2 diabetes Several studies from the Madras Diabetes Research Foundation (MDRF),
Chennai have demonstrated the association of oxidative stress and pro-inflammation with type 2 diabetes
Increased Oxidative STRESS in patients with Type 2 diabetes and its vascular complications
Molecular & Cellular Biochemistry, 2006
Int. J. Biochem. Cell Biology, 2007
Diabetic Medicine, 2006
Molecular & Cellular Biochemistry, 2009
Increased inflammatory STRESS in patients with Type 2 diabetes and its vascular complications
‘GUT CONNECTION’ TO TYPE 2 DIABETES
Intricate relationship between intestinal microbiota and development of metabolic diseases like type 2 diabetes.
The ‘storage’ hypothesis.
The ‘inflammatory’hypothesis.
High-fat diet modulates the composition of gut microbiota, promotes metabolic endotoxemia and triggers the development of metabolic disorders
Cani PD et al. Diabetologia, 2007 ; Cani PD et al, Diabetes. 2008
Lipopolysaccharide (LPS)
LPS transport in circulation is possible by two ways
a) facilitated by chylomicrons and b) by loss of intestinal tight junction
Pussinen PJ et al Diabetes Care. 2011;34:392-7
Mea
n LP
S le
vels
[EU
/ml]
Control Subjects(n=45)
Patients with T2DM(n=45)
*
* p<0.05 compared to control subjects
0
0.2
0.4
0.6
0.8
Circulatory levels of LPS from control subjects and patients with type 2 diabetes
Jayashree B, Mohan V ,Balasubramanyam M, et al, Mol Cell Biochem. 2014 ;388:203-10
Mean LPS/HDL Ratio (LPS activity) from control subjects and patients with type 2 diabetes
*
Mea
n LP
S/H
DL
ratio
Since HDL cholesterol is the main factor involved in neutralization of endotoxemia, we used the LPS/HDL ratio as a functional measure of the LPS activity
Control Subjects(n=45)
Patients with T2DM(n=45)
* p<0.05 compared to control subjects
0
0.01
0.02
Jayashree B, Mohan V ,Balasubramanyam M, et al, Mol Cell Biochem. 2014 ;388:203-10
Functions of gut microbiota
Gut microbiota and pathophysiology of
diabetes
Metagenomics
Prebiotics and probiotics
FLOW OF MY PRESENTATION
METAGENOMICSNew understanding of GI microbiota came from culture
free-molecular analysis based on 16S rDNA analysis
Methods: The study included 36 male Swedish adults, among which 18 subjects were diagnosed with type 2 diabetes.
Five bacterial phyla including Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria and Verrumicrobia, were sequenced.
The proportions of phylum Firmicutes and class Clostridia were significantly reduced in the diabetic group compared to the control group.
Furthermore, the ratios of Bacteroidetes to Firmicutes as well as the Bacteroides-Prevotella group to Clostridium coccoides - Eubacteria rectale group correlated positively and significantly with plasma glucose concentrations.
Similarly, class Lactobacilli species was highly enriched in diabetic compared to non-diabetic persons and positively correlated with plasma glucose.
Chinese patients with type 2 diabetes were characterized
1. by a moderate degree of gut microbial dysbiosis,
2. a decrease in the abundance of some universal butyrate-producing bacteria and
3. increase in Clostridium.
Qin et al. Nature. 2012
Consistency Depletion of butyrate producing gut commensals in type 2 diabetes
Based upon metagenomic clusters both studies reported that type 2 diabetes patients and controls can be distinguished with high accuracy although with very different microbial entities
Divergence Chinese study reported an enrichment of several Clostridium species in type 2 diabetes
Swedish study reported an enrichment of several Lactobacilli species in type 2 diabetes
CONSISTENCY AND DIVERGENCE IN REPORTED OUTCOMES OF TYPE 2 DIABETES GUT MICROBIOME ANALYSES
The metformin-associated gut microbiome was more similar to the healthy gut microbiome than
the microbiome of T2D metformin-naïve patients – especially with
respect to abundances of Subdoligranulum and Akkermansia
Nature 528, 262-266, 2015
Are these changes due to T2DM or due to Metformin effect ?
As Gut Microbiota seem to be
ethnic specific, there is a need
for Indian studies ……….
MicroDiab - Studies of interactions between the gut Microbiome and the human host biology to elucidate novel aspects of the pathophysiology and
pathogenesis of type 2 Diabetes
Indo-Danish Collaborative Research Grant
Supported by DBT
Madras Diabetes Research Foundation, Chennai
Translational Health Science and Technological Institute, Delhi
TCS Innovation Labs, Tata Consultancy Services,
Pune
The Novo Nordisk Foundation Center for Basic Metabolic
Research, Copenhagen
COLLABORATORS
Investigators from Indian SideDr. V. Mohan, MDRF, (PI)
Dr. G. Balakrish Nair, THSTI Dr. Sharmila Mande, TCS Dr. Bhabatosh Das, THSTI
Dr. M. Balasubramanyam, MDRF Dr. Radha Venkatesan, MDRF
Dr. R. M Anjana, MDRF
Investigators from Danish SideProf. Oluf B Pedersen, (PI)
Prof. Torben HansenDr. Henrik Vestergaard
To identify gut microbiome signatures in Indian subjects associated with pre-diabetes and type 2 diabetes thereby enabling development of novel biomarkers for early diagnosis of people at high risk of progression to overt type 2 diabetes and compare this with the Danish results.
Looking at trans ethnic differences in gut microbial signatures (Indians/Danes)
OBJECTIVE OF THE STUDY
DENMARKINDIA
NGT
n= 150
PRE DIABETES
n=150
DIABETES
n=150
NGT
n= 150
PRE DIABETES
n= 150
DIABETES
n= 150
Total Individuals
n= 900
SAMPLING
Fecal Samples collected and stored by MDRF, Chennai.
Extraction of bacterial Genomic DNA from Feces using INRA method at MDRF.
Quality checking done performed by spectrophotometric analysis and Gel electrophoresis at MDRF.
16S rDNA seqeuncing: V1-V5 regions sequenced at THSTI, Gurgaon.
Semi-blinded analyses to identify diabetic subject group by TCS R&D, Pune
Diabetes microbiomes from Indian subjectsSTRATEGY EMPLOYED
EXTRACTION OF BACTERIAL DNA FROM EXTRACTION OF BACTERIAL DNA FROM FECES (INRA METHOD)FECES (INRA METHOD)
The 16s rDNA sequence has hypervariable regions, where sequences have
diverged over evolutionary time. Strongly conserved regions often flank these hypervariable regions. Primers are designed to bind to conserved regions and amplify variable regions. By comparing the inferred rRNA sequences, it is possible to estimate the historical
branching order of the species, and also the total amount of sequence
change and also capable of reclassifying bacteria in to completely new species or
even genera (which have never been successfully cultured in laboratories).
Structure of 16s rRNA geneStructure of 16s rRNA gene
V1 – V3 V1 – V5
Rank Genus Name Median Abundance %
1 Prevotella 25.350
2 Faecalibacterium 7.920
3 Lachnospiracea_incertae_sedis 3.871
4 Blautia 2.930
5 Collinsella 2.450
6 Roseburia 2.410
7 Megasphaera 2.314
8 Dorea 2.216
9 Catenibacterium 2.118
10 Lactobacillus 2.034
11 Dialister 1.665
12 Erysipelotrichaceae_incertae_sedis 1.312
13 Coprococcus 1.191
14 Ruminococcus 0.725
15 Streptococcus 0.606
16 Oscillibacter 0.601
17 Mitsuokella 0.556
18 Butyricicoccus 0.523
19 Bacteroides 0.481
20 Ruminococcus2 0.443
21 Gemmiger 0.407
22 Olsenella 0.406
23 Clostridium XlVa 0.406
24 Clostridium sensu stricto 0.242
25 Anaerostipes 0.241
26 Alloprevotella 0.170
27 Clostridium IV 0.155
28 Clostridium XI 0.128
29 Flavonifractor 0.110
Overall taxonomic distribution (major genera) in Indians & Danish Rank Genus Name Median Abundance %
1 Bacteroides 17.079
2 Faecalibacterium 13.595
3 Oscillibacter 5.022
4 Alistipes 3.298
5 Lachnospiracea_incertae_sedis 3.235
6 Prevotella 2.218
7 Ruminococcus 2.009
8 Roseburia 1.951
9 Parabacteroides 1.879
10 Clostridium XlVa 1.362
11 Coprococcus 1.270
12 Clostridium IV 1.256
13 Blautia 1.136
14 Collinsella 0.781
15 Gemmiger 0.772
16 Barnesiella 0.623
17 Dorea 0.557
18 Erysipelotrichaceae_incertae_sedis 0.486
19 Clostridium XVIII 0.448
20 Ruminococcus2 0.446
21 Butyricicoccus 0.403
22 Clostridium XlVb 0.299
23 Phascolarctobacterium 0.298
24 Flavonifractor 0.253
25 Anaerostipes 0.233
26 Odoribacter 0.214
27 Anaerovorax 0.188
28 Sutterella 0.179
29 Rhodococcus 0.145
30 Butyricimonas 0.135
31 Sporobacter 0.114
32 Streptococcus 0.105
Danish samplesIndian samples
Prominent geography specific taxonomic variations in Indian and Danish Gut microbiome data
PCoA plot with JSD distance based on Taxonomic abundance
Taxonomic distribution of NGT, PD & DM (Indians)
DM DM
DMDM
Taxonomic distribution of NGT, PD & DM (Danes)
Differentially abundant genera in Indian NGT/PD/DM subjects
Kruskal-Wallis P-values computed using R
Genera identified in different subject groups
Median abundancein different glucose tolerance
groups
P value(Kruskal-
Wallis test)Overall median
All Subjects (N=429) NGT (N=134) PD (N=140) DM (N=155)
Clostridium sensu stricto 0.329 0.340 0.124 0.0001 0.242Pseudomonas 0.014 0.082 0.023 0.0000 0.038Clostridium XI 0.200 0.161 0.065 0.0001 0.128Achromobacter 0.000 0.065 0.008 0.0004 0.013Escherichia.Shigella 0.041 0.075 0.098 0.0034 0.075Megasphaera 1.662 3.316 2.194 0.0061 2.314
Erysipelotrichaceae_incertae_sedis 1.913 0.828 1.534 0.0177 1.312
Ruminococcus 1.000 0.700 0.670 0.0302 0.725Olsenella 0.337 0.627 0.372 0.0484 0.406Blautia 2.845 2.692 3.222 0.0664 2.930Anaerostipes 0.334 0.233 0.197 0.0695 0.241Butyricicoccus 0.617 0.502 0.533 0.0862 0.523Megamonas 0.010 0.021 0.054 0.0865 0.019
Differentially abundant genera in Danish NGT/PD/DM subjects
Kruskal-Wallis P-values computed using R
Genera identified in different subject groups
Median abundancein different glucose tolerance groups
P value(Kruskal-
Wallis test)Overall median
All Subjects (N=429) NGT (N=159) PD (N=155) DM (N=112)
Escherichia Shigella 0.021 0.023 0.082 0.033 0.0000Clostridium XI 0.093 0.086 0.013 0.070 0.0000Alistipes 4.100 2.868 2.648 3.298 0.0001Catenibacterium 0.000 0.000 0.006 0.000 0.0004Anaerovorax 0.221 0.207 0.135 0.188 0.0014Barnesiella 0.829 0.499 0.492 0.623 0.0022Clostridium.sensu.stricto 0.040 0.035 0.007 0.027 0.0033Pelomonas 0.025 0.023 0.037 0.027 0.0057Coprococcus 1.652 1.283 0.845 1.270 0.0065Flavonifractor 0.208 0.263 0.290 0.253 0.0131Acetivibrio 0.010 0.005 0.000 0.006 0.0585Streptococcus 0.107 0.127 0.069 0.105 0.0587Sporobacter 0.133 0.112 0.102 0.114 0.0604Oxalobacter 0.006 0.000 0.000 0.000 0.0671Ruminococcus 2.014 2.140 1.403 2.009 0.0769
• Functions of gut microbiota
• Gut microbiota and pathophysiology of diabetes
• Metagenomics
• Prebiotics and probiotics
FLOW OF MY PRESENTATION
WHAT ARE PREBIOTICS AND PROBIOTICS?
PROBIOTICS : Live micro-organisms which, when administered in
adequate amounts, confer a health benefit on the host.
Source: Found in foods such as yogurt, other dairy products and also
available as dietary supplements.
PREBIOTICS : Non-digestible substances that provide a beneficial
physiological effect for the host by selectively stimulating the
favorable growth or activity of a limited number of indigenous.
Basically food for probiotics.
Source: Found in whole grains, bananas, onions, garlic, honey and also
available as dietary supplements.
Cani PD et al. Diabetologia, 2007; Cani PD et al, Diabetes, 2008
ROLE OF PREBIOTICS / PROBIOTICS
GLP–1
RESULTS OF THE ORAL GLUCOSE TOLERANCE TEST (OGTT)
Compared to control animals, mice fed with high fat showed increased area under curve (AUC) of the OGTT i.e., impaired glucose tolerance
Probiotic culture MTCC5689 significantly improved the glucose tolerance in HFD mice and this is comparable to the results obtained with positive control (LGG) and anti-diabetic drugs Metformin & Vildagliptin
Balakumar et al 2016, Eur J Nutr, Published online : 18 October 2016
RESULTS OF THE INSULIN TOLERANCE TEST (ITT)
Compared to control animals, mice fed with high fat showed impaired insulin sensitivity as revealed by decrease in % kITT
Probiotic cultures (both MTCC 5690 & MTCC5689) significantly improved the insulin tolerance as evident from the increased kITT value (increased glucose disposal rate) and this is comparable to the results obtained with positive control (LGG) and anti-diabetic drugs metformin and vildagliptin
Balakumar et al 2016, Eur J Nutr, Published online : 18 October 2016
Alterations in microbiota are associated with disease states. This is understood better in type 2 diabetes than type 1 diabetes.
Gut Microbiota in Indian and Danish populations are completely different.
In Indian diabetic patients, Clostridium sensu stricto and Clostridium XI are decreased markedly, whereas pre-diabetes subjects, Megasphaera is increased 3 fold especially in males.
Among Danish diabetic patients, Escherichia Shigella and Clostridium XI are reduced.
Pre/probiotics have a beneficial role, but more studies are
needed !
SUMMARY
Is to apply metagenomic and integrative metabolomic approaches to better understand the underlying causes of metabolic diseases in the context of gut microbiota. Develop novel therapeutic options including targeting drugs to microbial genes or co- regulated host pathways or modifying the gut microbiota through diet, (probiotic and prebiotic interventions), bariatric surgery, fecal transplants, or ecological engineering.
The Challenge………………..
A whole new field is waiting to be explored!