Brigitte Gallot and Luiza Ghila- Cell Plasticity in Homeostasis and Regeneration
Using nutrigenomics to study ranges and plasticity in homeostasis
-
Upload
systems-nutrition -
Category
Health & Medicine
-
view
10 -
download
3
description
Transcript of Using nutrigenomics to study ranges and plasticity in homeostasis
Using nutrigenomics to study ranges and plasticity in homeostasis
Michael MüllerNetherlands Nutrigenomics Centre
& Nutrition, Metabolism and Genomics GroupDivision of Human Nutrition, Wageningen University
http://twitter.com/nutrigenomics
Our scientific challenge: What's healthy?
Metabobolic homeostasis & syndrome
Metabolic health = plasticity / flexibility
• The personal genome is the starting point & we can get comprehensive information about it but we should not underestimate the challenges of “bioinformatics & databasing”
• Health is dynamic: The property to adapt to metabolic perturbations / challenges
• Feeding / fasting => autophagy => cellular homeostasis & “exercise”
• Caloric restriction => chromatin “exercise”• Food bioactives that modulate transcription (e.g. via
nuclear receptors) or chromatin activity (nutriepigenome) => cell & organ “exercise”
4
Phenotype plasticityPhenotypic plasticity is the ability of an organism to change its phenotype in response to changes in the environment => nutrition, lifestyle
Duality of biological information:Epigenetic & Genetic
Modern Nutritional Science with Nutrigenomics Quantification of the nutritional phenotype
Phenotype
Metabolome
Proteome
Transcriptome
Epigenome
Genotype
Lifestyle
NutritionFoods
Microbiota
Environment
Timely relatively modest interventions in early life can have a large effect on disease
risk later
Nutrigenomics – molecular nutrition and genomics
90,000 (?)proteins
20,210 genes
100,000 (?) transcripts
5 -10,000 (?)metabolites
Müller & KerstenNature Reviews Genetics 2003
Understanding NutritionHow nutrients regulate our genes: via sensing molecular
switches
Changed organ
metabolic capacity
J Clin Invest. 2004;114:94-103J Biol Chem. 2006;28:934-44 Endocrinology. 2006;147:1508-16Physiol Genomics. 2007;30:192-204Endocrinology. 2007;148:2753-63 BMC Genomics 2007; 8:267 Arterioscler Thromb Vasc Biol. 2007;27:2420-7
Am J Clin Nutr. 2007;86(5):1515-23PLOS ONE 2008;3(2):e1681 BMC Genomics 2008; 9:231BMC Genomics 2008; 9:262J Biol Chem. 2008;283:22620-7Arterioscler Thromb Vasc Biol. 2009;29:969-74.Plos One 2009;4(8):e6796HEPATOLOGY 2010;51:511-522
Am J Clin Nutr. 2009; 90:415-24Am J Clin Nutr. 2009;90:1656-64Mol Cell Biology 2009;29:6257-67Am J Clin Nutr. 2010;91:208-17BMC Genomics 2009Physiol. Genomics 2009Circulation 2010Diabetes 2010Cell Metabolism 2010Nature 2011
Dose-dependent effects of dietary fat on development of obesity in relation to intestinal differential gene expression in C57BL/6J
mice
PLOS one 2011
0
200
400
600
800
1000
1200
1400
1600
1800
20-1
0E%
30-1
0E%
45-1
0E%
20-1
0E%
30-1
0E%
45-1
0E%
20-1
0E%
30-1
0E%
45-1
0E%
proximal middle distal
Num
ber o
f diff
eren
tially
exp
ress
ed g
enes
w
ith
non-Dose-dependentDose-dependent (%)
Robust & concentration dependent effects in small intestine
Differentially regulated intestinal genes by high fat diet
PLOS one 2011
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10
Cellular localization and specific lipid metabolism-related function of fat-dose dependently regulated
genes
PLOS one 2011
Intestinal capacity for lipid absorption
45% FAT
10% FAT
Microbiota
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10
40 cm
4 cm
Dangerous interaction - The two hitsStress from Metabolism & Inflammation
Liver, FAT & NASH/NAFLD Nonalcoholic Fatty Liver Diseases (NAFLD):
Liver component of Metabolic Syndrome
Different stages in NAFLD progression:
Molecular events involved in NASH pathogenesis: Role of PPARa (Endocrinology 2008 & Hepatology 2010) Role Kupffer cells (Hepatology 2010)
Role of macrophages in lipid metabolism (JBC 2008; Cell Metabolism 2010)
hepatic steatosis steatohepatitis (NASH) & fibrosis cirrhosis
Experimental Design
• stratificatio
n on body weight
• liver• plasma collection multiple protein assays
RNA extraction: Affx microarrays
tissue collectionrun-in diet 20 weeks diet intervention
frozen sections: histological feat.
• ep. white adipose tissue
10% low fat diet
(palm oil)
10 LFD
10 HFD
45% high fat diet
(palm oil)
20 LFD
RNA extraction: real-time PCR
paraffin sections: histological feat.
lipid content
quality control & data analysis
pipelineMouse
genome 430 2.0
0 2 4 8 12 16 20 weeks-3
High fat diet-induced obesity
0
5
10
15
20
25
0 2 4 8 12 16 20
weeks under diet intervention
BW
gai
n (g
)
**
*
**
* *
* *
LFLLFH
HFLHFH
** *
***
Liver TG content
0
40
80
120
160
200
mg
TG/g
live
r
ALT
act
ivity
(UI)
ALT plasma activity
Rat
io L
W/B
W (%
)
Hepatomegaly
**
0
2
4
6
8
10***
0
20
40
60
80
100
* *
LFL LFH HFL HFH
The HFH mice develops NASH
Immunohistochemical staining confirms enhanced liver inflammation and early fibrosis in HFH mice
Macrophage CD68
Collagen
Stellate cell GFAP
Upregulation of inflammatory and fibrotic gene expression in HFH
responder mice
Adipose dysfunction in HFH mice
Change in adipose gene expression indicate adipose tissue
dysfunction
Plasma proteins as early predictive biomarker for NASH in C57Bl/6
mice
Plasma proteins as early predictive biomarker for NASH in C57Bl/6
mice
Multivariate analysis of association of protein plasma concentrations with final liver triglyceride content
Conclusions
• Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis.
• It points to several novel potential predictive biomarkers for NASH.
Duval C, Thissen U, Keshtkar S, Accart B, Stienstra R, Boekschoten MV, Roskams T, Kersten S, Müller M.
Adipose tissue dysfunction signals progression of hepatic steatosis towards nonalcoholic steatohepatitis in C57BL/6
mice. Diabetes. 2010;59:3181-91.
Plasma Protein Profiling Reveals Protein Clusters Related to BMI and Insulin Levels in Middle-Aged Overweight Subjects
AIM• Associate plasma protein profiles with BMI• Identify potential marker profile of early
disease state
. PLoS One. 2010 Dec 23;5(12):e14422
Measurements
• Rules Based Medicine (Austin, USA)• Multiplex immunoassay• In total 124 proteins measured
– Involved in diseases, inflammation, endothelial function and metabolism
. PLoS One. 2010 Dec 23;5(12):e14422
We are different: improved phenotyping necessary to reveal phenotype clusters
. PLoS One. 2010 Dec 23;5(12):e14422
Fish-oil supplementation induces anti-inflammatory gene expression profiles in human blood
mononuclear cells
Less inflammation & decreased pro-arteriosclerosis markers= Anti-immuno-senescence
Bouwens et al. Am J Clin Nutr. 2009
Very personal conclusionsHow to keep our metabolic plasticity/health
• Identify chronic (non-resolving) stress using systems “perturbation” tests & deep genomics-based phenotyping
• Solve it!– Less Inflammation– Less Metabolic Stress (sat. fat, lipogenic foods)– More Exercise (muscle & other organs) with a
“challenging” lifestyle & food pattern– Eat less from time to time
32
2 Meals a day, work as long as possible & embrace challenge
Walter Breuning (1896 - 2011)
Sander KerstenLinda SandersonNatasha GeorgiadiMark BouwensLydia AfmanGuido HooiveldMeike BungerPhilip de GrootMark BoekschotenNicole de WitMohammad Ohid Ullah
Christian TrautweinFolkert KuipersBen van OmmenHannelore DanielBart StaelsEdith Feskens…..