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How gut microbiota might influence fat storage and metabolism
ILSI SEAR Australasia Symposium
Future Directions in Saturated Fats: composition and metabolism
School of Molecular Bioscience Andrew Holmes
Microbes that colonize you as an infant give rise to a stable
community that influences you for the rest of your life. �
2
1. Overview of our gut microbiota?�"How many cells? What kinds of species?�
"How we interact with it �
2. Why microbes matter. �"Microbes influence our gene expression patterns�
"Microbial activity influences our metabolism�
3. Detecting links with our microbiota�"Diversity measurement and scale "�
"An obesity-associated microbiota �
"High-fat diet microbiota �
Flint H et al. (2008) Nature Reviews Microbiology 6, 121-131 Polysaccharide utilization by gut bacteria: potential for new insights from genomic analysis
Total Energy content �
< 104 g-1
103 - 105 108
1011 - 1012
Stomach
Duodenum
Colon Jejunum
Ileum
The available energy is in polysaccharides not degraded by host enzymes or secretions
Absorption of host-accessible sugars, lipids
and amino acids is
‘complete’ by the ileum
The dominant gut-associated bacteria are members of the
Bacteroidetes and Firmicutes.
Specialize in degrading digestion-resistant
carbohydrate.
Host-microbe interaction is greatest in intestines and reflects: �
What microbes are made of (surface components, breakdown products)
What they do (metabolites produced and substrates consumed)
How our tissues sense the gut compartment (dendritic cell projections, PRRs)
What we export to the gut lumen (mucin, sIgA, bile, peptides)
What crosses in from the gut lumen (sugars, lipids, fatty acids, amino acids, microbes)
Over 1000 species, but >90% in just 2 phyla and share many features�Does diversity matter?�
Figure from Flint H et al. (2008)
Main energy source for colonocytes. Net production influences epithelial health
and gut barrier function
Absorbed and transported to liver. Net production has
potential to influence host energy balance.
Different bacteria have different strategies to degrade polysaccharide and use different pathways to extract energy from the solubilized
sugars – giving different end products�
See effect of microbes by comparing germ free with experimentally- or naturally-colonized animals�
Foetus�
Sterile�
Neonate� Child (mini adult)�
Sterile�
Birthday �Inoculation day �
Diverse community�(>1000 “species”)�
Sterile�
Defined community�(1 or more species)�
Natural�
Microbiota �
Germ-free�
Gnotobiont �
(known microbes)�
No community�
Gnotobiont models: Some features of GF animals do not need complex community�
L.V. Hooper and J.I. Gordon (2001) Glycobiology 11: 1R–10R.
Germ free�
Conv colonized�
B. theta. colonized�
Stappenbeck et al., (2002) Proc. Natl. Acad. Sci. U. S. A. 99: 15451–15455.
Conv. colonized Germ free
Epithelial fucosylation �
Intestinal vascularization�
Gnotobionts don’t do everything: microbe community required for normal phenotype�
System � GF phenotype �Nutrition ""vitamins K & B required�
""lower body fat, but eat more! �Metabolism "increased bilirubin �
""increased fecal nitrogen �
"decreased fatty acids�Intestinal "reduced mass�
"increased goblet cells�
"altered lectin composition �
Immune "decreased sIgA �
"low systemic Ig �"GALT undeveloped�
"Altered cytokine profile "�
www.narl.org.tw/en/topic/topic.php?topic_id=1
From Backhed et al. (2004) PNAS 101: 15718
From: Turnbaugh et al. (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 1027-131
Caloric content of feces is lower in obese mice - more energy has been extracted.�
Higher fatty acid concentrations in cecum of obese mice - more food converted to absorbable forms�
Association studies: Some microbiota-influenced properties linked to health issues (obesity, IBD).�
Microbiota: �
association �or�
cause?�
Transplantation experiments show composition of microbiota affects outcome�
Germ free ob/ob mouse
Obesity-associated microbiota (normal
ob/ob mouse)
Lean-associated microbiota (normal
mouse)
ob/ob mice conventionalized with
a LAM have less increase in body fat
From: Turnbaugh et al. (2006) Nature 444, 1027-131
ob/ob mice conventionalized with an OAM have greater increase in body fat
11
Regulatory poise of immune system is influenced by microbiota composition. Inflammatory response contributes pathology
Immune system may influence microbiota composition
Host Factors (Genetic background, immunological state)
Interventions (Diet, pharmaceuticals, exercise)
Gut Microbiota (composition, activity)
Human Health
Microbiota composition influences metabolism and absorption: Diets may not deliver the anticipated calorie deficit
Oral drug delivery may not give the anticipated dose Drug metabolism may modulate the anticipated biological effect
Diet differences may influence microbiota composition Antibiotic may alter microbiota composition
The problem: Interventions give variable and/or transient
outcomes that are not explained by host-intervention
interaction axis
Working hypotheses
What are the implications of gut microbial community structure for human health?�
The emergent properties of the GUT MICROBIOME are such that therapeutic management of many diseases and disorders requires consideration of gut
microbiota - and could also involve management of gut microbiota�
Systemic inflammation,
dyslipidemia and insulin resistance
Systemic inflammation,
dyslipidemia and insulin resistance
Liver
Cytokine - & fat-laden
PortalCirculation
Inflamed & steatotic liver
Diet (caloric overload & pro -inflammatory profile)
Genetics Obesity
Gut Dysfunction
Microb
iota
profile
Impaired barrier
function
Inflamm
ation
Mesenteric fat
Endotoxins
Liver
Leaky gut
Lipid & macrophage accumulation
Systemic inflammation,
dyslipidemia and insulin resistance
Systemic inflammation,
dyslipidemia and insulin resistance
Liver
Cytokine - & fat-laden
PortalCirculation
Inflamed & steatotic liver
Diet (caloric overload & pro -inflammatory profile)
Genetics Obesity
Gut Dysfunction
Microb
iota
profile
Impaired barrier
function
Inflamm
ation
Mesenteric fat
Endotoxins
Liver
Leaky gut
Lipid & macrophage accumulation
Lam et al (2011) Role of the gut in visceral fat inflammation and metabolic disorders Obesity (online early)
Increased fat storage - obesity�
Genetic factors�
Poor diet (excess energy; inappropriate macronutrient ratio)�
Selective pressure on microbial community�
Sampling intensity: At any one point in time
there are an estimated 1014 bacterial cells in the GIT.
Sampling pattern 2: Different anatomical regions
of the gut have different functions – and different
microbiota
Sampling pattern 1: There is continual turnover
of the microbiota by ingestion, growth and
defecation
Monitoring and measuring associations between gut microbiota and animal phenotype�
1013 g-‐1
The 16S rRNA gene is sampled by PCR - we count PCR products
No. different sequence types ≈ No. biological types
Abundance of sequence ≈ abundance of cells
Sequence relationships correspond to evolutionary
history.
Cells with different properties have different genomes�
We can isolate cells and measure properties or isolate DNA and
measure sequences�
Cells ‘Isolated’ genes
http
://bi
olog
y.cl
c.uc
.edu
/fank
haus
er/L
abs/
Isolated colonies
Measuring microbial community structure: evol distance and discrete state methods�
‘Populations’: fingerprinting by DGGE�
Zoetendal et al. (1998) Appl. Env. Microbiol. 64:3854-3859 �
‘Clades’: phylogenetic trees�
Ley et al. (2006) Cell 124:837-848 �
Taxonomic resolution, biological relevance and sampling power�
Microbial community varies between
individuals�Sub-Species correlated
with particular metabolites �
From: Li et al. (2008) Proc. Natl. Acad. Sci. USA 105, 2117-2122
Different microbiome properties will show patterns at different
levels of resolution �
Published studies have implicated low ratio of Bacteroidetes:Firmicutes with obesity�
Fig
1. Le
y et
al.
(200
6) N
atur
e 44
4:10
22�
Obesity and community structure outcomes after dietary intervention �
12 individuals, 4 timepoints, ca 400 sequences per sample, (18,348 in total)�
6 individuals on low Carb diet �
6 individuals on low fat diet
The Korean diet study: do gut microbiota influence diet success for weight loss?�
The study� A clinical trial to examine the acceptability and efficacy of a traditional Korean diet for Westerners (PIs Caterson, Kang).�
Project’s microbiology aims� Measure the correlation between gut community differences and weight loss and metabolic health outcomes�
Identify diet-induced changes in key gut microbes �
70 patients
35 Western Diet
35 Korean Diet
12 weeks
Diet-induced changes KD
vs WD cohorts
Microbiota-influenced outcomes low wt loss vs high
wt loss
No significant difference in weight loss outcome or metabolic improvement after 12 weeks between diets�
Calorie-restricted diet (Western) shows trend to shifting Bacteroides:Firmicutes populations but High fibre diet (Korean) did not �
Pre-diet community
Diet exposed community
(n= 9)
(n= 9)
Which aspects of community change reflect diet-selection for ‘better’ microbes�
20
Three closely related
members of the Firmicutes
respond differently to high fat diet
Zhang et al. (2010) The ISME Journal 4:232-241
High fat diet induces obesity and metabolic disease in mice
The change in gut microbiota over time is proportional to weight loss�Te
chni
cal R
eplic
ates
Te
mpo
ral R
eplic
ates
3.9 % change
6.7 % change
-16.2% -11.6%
% change over diet period
222 201
18.8% 21.4%
Subject
Weight loss
▲ Western diet
▲ Korean diet
0 12wk 0 12wk Time
Community change was important – is it: �
What the organisms do?�or�
How the host reacts to them?�
T5KO mice develop obesity and metabolic disease: Mice on the same diet, but differing in ability to perceive microbe-associated molecular patterns.
M Vijay-Kumar et al. Science 2010;328:228-231
Points to consider�
Host Factors (Genetic)
Environment Gut Microbiota
Metabolic Health
QTL mapping in mouse intercross line shows host genetic factors influence
microbiota relative abundance.�
We acquire our microbes from our immediate environment – some times of our life are more
critical than others.�
Ingesta impacts community structure and vice versa�
We require our immune system for stable microbial
community structure�
Ingesta (food and bioactive molecules) impact many
aspects of our health and metabolism�
Acknowledgements �
School of Molecular Bioscience, University of Sydney�Yi Vee Chew – (KD study, mouse nutritional geometry)�Feyza Colakoglu – (mouse nutritional geometry)�Connie Ha – (KD study, HFD and barrier function)�
Korean Diet Study (Funded by Korean Govt) �
Ian Caterson, Nick Fuller (and many more) – Institute for Obesity, Nutrition and Exercise, University of Sydney�
Jae-Heon Kang, Institute for Clinical Nutrition, Inje University, Seoul�
High Fat Diet and Gut Barrier Function �
Len Storlien, Yan Lam - IONE, University of Sydney�
Nutritional Geometry�
Steve Simpson – School of Biological Sciences, University of Sydney �Aisling McMahon, Sam Solon - ANZAC Institute�