1. The document discusses the role of nutrition challenges and sensing mechanisms in adaptation and disease. It summarizes research on how different diets affect gene expression, organ function, and disease development using mouse models. 2. One study found that a weekly alternating diet between calorie restriction and a medium-fat diet in mice protected the liver from fatty liver disease compared to mice fed a constant medium-fat or calorie-restricted diet. 3. The research suggests unsaturated fats may be more efficiently taken up in the small intestine, activating nutrient sensing pathways and preventing organ overload and early disease development, compared to saturated fats.

1. ‘From Molecular to Systems Nutrition
Lessons from mouse to man’
Michael Müller
Professor of Nutrigenomics & Systems Nutrition
Norwich Medical School
@nutrigenomics

2. You are what you eat, have eaten, host & how you lived
2 Meals/day, work as long as possible & embrace challenges
Walter Breuning (1896 – 2011, aged 114 years, 205 days)
(But Breuning was also a lifelong cigar smoker, but quit in 1999 when he was 103 because it became too expensive)

3. 100
50
0
% Energy
Low-fat meat
Chicken
Eggs
Fish
Fruits
Vegetables (carrots)
Nuts
Honey
100
50
0
% Energy
Fruits
Vegetables
Beans
Meat
Chicken
Fish
Grain
Milk/-products
Isolated Carbs
Isolated Fat/Oil
Alcohol
1.200.000 Generations
between feast en famine
Paleolithic era
3-4 Generations
in energy abundance
Modern Times
Our “paleolithic” genes + modern diets
Real Foods with ‘challenges’ “Safe, processed” foods = Less challenges

4. My talk
• Challenges & sensing mechanisms
• Biological Systems Multi-omics - challenges
• From molecular nutrition to the mode of action
• Complex diseases: role of the inter-organ
crosstalk
• The role of organ capacity
• From the liver and adipose tissue back to the gut
• The gut as a gatekeeper
• Opportunities for customized / precision nutrition

5. No pain, no gain
The molecular basis of adaptation to challenges

6. “We are what we eat, have eaten and what we host”
4Rs: Received, Recorded, Remembered & Revealed
Mathers JC (2008) Proc.Nutr.Soc.67,9390-394

7. Biological Systems Multi-omics to elucidate the Role of
Nutrition in the Genotype-Phenotype Relationship
Nature Reviews Genetics | AOP, published online 13 January 2015
Phenome
• Metabolic
Syndrome
CVD
NAFLD
• Inflammatory
Diseases
• Cancer

8. But

9. Genomics Data
Functional
Knowledge Base
Analytical Tools
(Galaxy, R, Bioconductor,
Subio, Ingenuity, Genomatix)
Single
Cell Data
Epigenetic
regulation
Text Mining
Interaction
Networks
KEGG/GO
pathways
Transcriptomics
Metabolomics
“Multi”Omics
Epigenomics
(incl. miRNA)
Microbiome
Genome
analysis
Transcription
factor analysis
New functional knowledge
New physiological understanding
New testable hypothesis
‘Virtual gut model’
Statistical
Analysis
Machine
learning
Visualization
Gut-
Microbe-
Dietome
Integration and Mining
of Big Data from
Omics Applications

10. Expression heatmapping of PPAR target genes & inflammatory
genes in human PBMCs after SFA/MUFA consumption
Esser et al Mol Food Nutr. Res 2015
In a cross-over study, 17 lean and 15 obese men (50-70y) received two 95g fat shakes,
high in SFAs or MUFAs. PBMC gene-expression profiles were assessed fasted and 4h
postprandially. Comparisons were made between groups and shakes.

11. Expression heatmap of significantly changed genes in obese
relative to lean subjects after the MUFA challenge
Esser et al Mol Food Nutr. Res 2015

12. What do we know about the mechanisms?
Healthy food (pattern)s have a large impact on our gene expression & phenotype
• (Micro & Macro) Nutrients
– High in Mono & (N-3) polyunsaturated fatty acids
– Sufficient high-quality protein (optimal macro-nutrient ratio)
– Vitamins (e.g. vitamin A & D) , minerals (e.g. Zn)
• Microbiota (from foods)
– Vegetarians / omnivores / carnivores => different microbiota
– “Raw” or fermented food (e.g. diary, cheese) consumption => food-
borne microbiota
– Dietary diversity => microbiota diversity & genetic richness
• Plant food components
– Fibers or secondary plant metabolites (e.g. resveratrol, glucosinolates)
e.g. bitter => “healthy stressors” & impact on microbiota
• Less foods/calories & diet-related stress (caloric restriction)
– “Chromatin exercise” & other epigenetic mechanisms
– “Cell exercise” (e.g. via autophagy)

13. Ronald M. Evans , David J. Mangelsdorf Nuclear Receptors, RXR, and the Big Bang Cell, Volume 157, Issue 1, 2014, 255 - 266
Metabolic homeostasis is regulated by nutrient sensors

14. Zooming in – zooming out
Expression atlas
http://www.ebi.ac.uk/gxa/home

15. Understanding Nutrition: Identifying the mechanisms involved in the
regulation of chromatin activity and gene transcription
Impact on
metabolic capacity
& health of organs
& the epigenetic
memory
Transgenic mice
(e.g. NRF2, SIRT1
HIF1, AHR, PPARs etc)

16. Nuclear receptors are linking
cellular biology to systems biology
PPAR
Liver
Heart
Intestine
0 25 50 75 100
placenta
trachea
thymus
bladder
prostate
testes
cervix
thyroid
adipose
lung
esophagus
colon
spleen
ovary
brain
skeletal muscle
kidney
liver
heart
small intestine
%%%%
Apolipoproteins & related
TAG (re)-synthesis
Pnliprp2 ,Pnliprp1, Mgll,
Lipe,Lipa,Pla2g6,
Pnpla2,Pnpla8, Daglb,
Ces1,Ces3
Chylomicron assembly
& secretion
Ketone body synthesis
Intestinal lipases &
phospholipases
Fat/Cd36,Slc27a2,
Slc27a4,Acsl1,Acsl3,
Acsl5,Fabp2,Fabp1,
Scarb2,Scarb1
Gpat1, Mogat2,
Dgat1,Dgat2,
Gpat3,Agpat3
Mttp, Stx5a,Vti1a,
Bet1,Sar1a
Apob,Apoa1 ,Apoa2,Angptl4,
Apoa4,Apoc2,Vldlr,Apoc3,
Apoe,Apol3,Apool
Acaa2,Acad10,Acad8,Acad9,
Acadl,Acadm,Acads,Acadsb,
Acadvl,Acot10,Acot2,Acot9,
Aldh9a1,Cpt1a,Cpt2,Crat,Dci,
Decr1,Hadha,Hadhb,Hibch,
Slc22a5,Slc25a20,Aldh3a2,
Cyp4a10,Abcd3,Acaa1a,
Acaa1b,Acot3,Acot4,Acot5,
Acot8,Acox1,Acox2,Crot,
Decr2,Ech1,Ehhadh,
Hsd17b4,Peci,Pecr,
Ppara
Acat1, Hmgcl,Hmgcs2
Mitochondrial,
microsomal, peroxisomal
fatty acid oxidation
Fatty acid
transport &
binding
P
P
A
R
α
PPARa

17. Context-dependent gene regulation by the
nutrient-sensing transcription factor PPARa
WY
Fibrate
“Drug”
DHA
PUFA
“Food”
Liver Intestine

18. Non-communicable diseases are complex
“Too much non-resolving metabolic & pro-inflammatory stress”
Non-communicable diseases are caused by chronic organ overload & dysregulation

19. LOCAL effects/inflammation) (first!)
Systemic effects/inflammation (second)
Br J Nutr. 2013 Jan;109 Suppl 1:S1-34.

20. de Wit NJ, Afman LA, Mensink M, Müller M
Phenotyping the effect of diet on non-alcoholic
fatty liver disease J Hepatol 2012
.
A systems nutrition view of health & disease

21. Interaction between WAT and liver tissue
essential for NASH/NAFLD in C57Bl/6 mice
• stratification
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
pipeline
Mouse
genome
430 2.0
0 2 4 8 12 16 20 weeks-3

22. High fat diet-induced obesity
0
5
10
15
20
25
0 2 4 8 12 16 20
weeks under diet intervention
BWgain(g)
*
*
*
**
* *
* *
LFL
LFH
HFL
HFH
**
*
***
Liver TG content
0
40
80
120
160
200
mgTG/gliver
ALTactivity(UI)
ALT plasma activity
RatioLW/BW(%)
Hepatomegaly
**
0
2
4
6
8
10
***
0
20
40
60
80
100
* *
LFL LFH HFL HFH

23. A subpopulation of mice fed HFD develops NASH

24. Immunohistochemical staining confirms enhanced liver
inflammation and early fibrosis in HFH mice
Macrophage CD68
Collagen
Stellate cell GFAP
HFL HFH

25. Upregulation of inflammatory and fibrotic
gene expression in HFH responder mice

26. Adipose dysfunction in HFH mice

27. Change in adipose gene expression
indicate adipose tissue dysfunction

28. Conclusions
• The data support the existence of a tight
relationship between adipose tissue dysfunction
(because of chronic organ overload & unbalanced
expansion) and NASH pathogenesis.
• It also demonstrates the time-dependent
progression of local (organ) towards systemic
inflammation.
Duval et al. Diabetes 2010

29. Mice are not Humans?
No, they are Models for Systems Responses to Food Patterns
Natural Variation in Gene-by-Diet Interactions

30. A weekly alternating diet between caloric restriction
and medium-fat protects the liver from fatty liver
development in middle-aged C57BL/6J mice
• Can a novel dietary intervention consisting of an every-
other-week calorie-restricted diet prevent nonalcoholic
fatty liver disease (NAFLD) development induced by a
medium-fat (MF) diet?
• 9-week-old male C57BL/6J mice received either
– a control (C), 30E% calorie restricted (CR), MF (25E% fat), an
intermittent (INT) diet, a diet alternating weekly between 40E%
CR and an ad libitum MF diet until the age of 12 months.
• The metabolic, morphological, and molecular features of
NAFLD were examined.
Rusli F, Boekschoten MV, Zubia AA, Lute C, Müller M, Steegenga WT.. Mol Nutr Food Res. 2014 Dec 15

31. A B
C
***
***
***
ED F
***
***
*
*** *
*
r = 0.83
P-value < 0.0001
**
***
Body w eight (g)
Liverweight(g)
20 30 40 50
0.5
1.0
1.5
2.0
2.5
C
CR
MF
ID
r = 0.82
P-value < 0.0001
***
***
***
***
Age (w eeks)
Bodyweight(g)
10 20 30 40 50
10
20
30
40
50 C
CR
MF
INT
WATweight(g)
C CR MF INT
0.0
0.5
1.0
1.5
2.0
RelativeWATweight(%)
C CR MF INT
0
1
2
3
4
5
Liverweight(g)
C CR MF INT
0.0
0.5
1.0
1.5
2.0
2.5
Relativeliverweight(%)
C CR MF INT
0
1
2
3
4
5
6
WAT w eight (g)
Liverweight(g)
0.0 0.5 1.0 1.5 2.0
0.5
1.0
1.5
2.0
2.5
C
CR
MF
INT
kcal/day/mouse
D
ay
1
D
ay
2
D
ay
3
D
ay
4D
ay
5-7
0
2
4
6
8
10
C
CR
MF
INT-CR w eek
INT-MF w eek
kcal/week/mouse
C CR MF INT
0
20
40
60
80
100
120
Carbohydrate
Protein
Fat
Time (min)
Bloodglucoselevel(mmol/L)
0 50 100 150
5
10
15
20
25
30 C
CR
MF
INT
Plasmainsulinlevel(ng/ml)
C CR MF INT
0
1
2
3
Beneficial effects of an INT diet regimen on body, WAT, and liver
weight, food intake, and glucose tolerance
Rusli F, Boekschoten MV, Zubia AA, Lute C, Müller M, Steegenga WT.. Mol Nutr Food Res. 2014

32. F C CR MF INT
LowBWHighBWHighBW
E C CR MF INT
LowBW
NAFLD development in C- and MF-fed mice, but not in
mice exposed to the CR and INT diet
Rusli F, Boekschoten MV, Zubia AA, Lute C, Müller M, Steegenga WT.. Mol Nutr Food Res. 2014 Dec 15

33. Conclusions
• Our study reveals that the INT diet maintains metabolic
health and reverses the adverse effects of the MF diet,
thus effectively prevents the development of NAFLD in
12-month-old male C57BL/6J mice.
Age (weeks)
Survival(%)
52 65 78 91 104
50
75
100
C
CR
MF
INT
*
*
**
Rusli F, Boekschoten MV, Zubia AA, Lute C, Müller M, Steegenga WT.. Mol Nutr Food Res. 2014 Dec 15

34. From local problems to systemic
diseases – the contribution of the gut

35. Robust & concentration dependent effects in small intestine
Differentially regulated intestinal genes by high fat diet
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10
De Wit et al Plos ONE 2011

36. Chronic overload of organs => NCDs
• Saturated fat (but not or to a less extent unsaturated fat)
stimulates obesity and the development of fatty liver disease
and affects gut microbiota composition & diversity by an
enhanced overflow of dietary fat to the distal intestine.
• Unsaturated fats are more effectively taken up by the small
intestine, likely by more efficiently activating nutrient sensing
systems (PPARs) and thereby contributing to the prevention of
organ overload & the development of early pathology (e.g.
NASH).
Food Colon

37. Gene expression intensity Differential gene expression
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
Triglyceride/FFA metabolism
Transport
12491_at Cd36
26458_at Slc27a2
26569_at Slc27a4
14080_at Fabp1
14079_at Fabp2
Oxidation .
omega
13117_at Cyp4a10
11522_at Adh1
26876_at Adh4
11668_at Aldh1a1
beta
11363_at Acadl
11370_at Acadvl
14081_at Acsl1
12894_at Cpt1a
12896_at Cpt2
51798_at Ech1
97212_at Hadha
57279_at Slc25a20
TG/Chylomicron synthesis
110446_at Acat1
238055_at Apob
11813_at Apoc2
13350_at Dgat1
67800_at Dgat2
17777_at Mttp
FA synthesis
104112_at Acly
14104_at Fasn
20249_at Scd1
20250_at Scd2
Transcription regulation
19013_at Ppara
19015_at Ppard
19016_at Pparg
19017_at Ppargc1a
Cholesterol/oxysterol metabolism
Transport
11303_at Abca1
27409_at Abcg5
67470_at Abcg8
237636_at Npc1l1
Cholesterol synthesis
74754_at Dhcr24
15357_at Hmgcr
Transcription regulation
22260_at Nr1h2/Lxrb
22259_at Nr1h3/Lxra
20787_at Srebf1
20788_at Srebf2
Bile acid metabolism
Transport
16204_at Fabp6
106407_at Osta
330962_at Ostb
20494_at Slc10a2
Transcription regulation
23957_at Nr0b2/Shp
20186_at Nr1h4/Fxr
Chow LF HF
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
Triglyceride/FFA metabolism
Transport
12491_at Cd36
26458_at Slc27a2
26569_at Slc27a4
14080_at Fabp1
14079_at Fabp2
Oxidation
omega
13117_at Cyp4a10
11522_at Adh1
26876_at Adh4
11668_at Aldh1a1
beta
11363_at Acadl
11370_at Acadvl
14081_at Acsl1
12894_at Cpt1a
12896_at Cpt2
51798_at Ech1
97212_at Hadha
57279_at Slc25a20
TG/Chylomicron synthesis
110446_at Acat1
238055_at Apob
11813_at Apoc2
13350_at Dgat1
67800_at Dgat2
17777_at Mttp
FA synthesis
104112_at Acly
14104_at Fasn
20249_at Scd1
20250_at Scd2
Transcription regulation
19013_at Ppara
19015_at Ppard
19016_at Pparg
19017_at Ppargc1a
Cholesterol/oxysterol metabolism
Transport
11303_at Abca1
27409_at Abcg5
67470_at Abcg8
237636_at Npc1l1
Cholesterol synthesis
74754_at Dhcr24
15357_at Hmgcr
Transcription regulation
22260_at Nr1h2/Lxrb
22259_at Nr1h3/Lxra
20787_at Srebf1
20788_at Srebf2
Bile acid metabolism
Transport
16204_at Fabp6
106407_at Osta
330962_at Ostb
20494_at Slc10a2
Transcription regulation
23957_at Nr0b2/Shp
20186_at Nr1h4/Fxr
HF-Chow HF-LF Chow-LF
Dietary impact of on intestinal gene expression involved in lipid metabolism

38. 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
AHR activation
11622_at Ahr
Detoxification
13076_at Cyp1a1
14858_at Gsta2
14859_at Gsta3
14862_at Gstm1
18104_at Nqo1
Inflammation (ILCs and IELs)
19885_at Rorc (ILC)
12501_at Cd3e (IEL)
12502_at Cd3g (IEL)
12525_at Cd8a (IEL)
20302_at Ccl3 (IEL)
20304_at Ccl5 (IEL)
432729_at Tcrg-C (IEL)
17067_at Ly6c1 (IEL, type a)
16636_at Klra5 (IEL, type b)
12504_at Cd4 (T helper)
12475_at Cd14 (Monocytes)
12478_at Cd19 (B cells)
HF-Chow HF-LF Chow-LF
Role of 3 diets on gut phenotypes
Dietary impact on the activation of the AhR essential for the gut immune system
3 Diets =
3 functional states
of the gut

39. Role of dietary fibres on gut function
SCFA
INULIN, FOS, GuarGum, NAXUS (Arabinoxylan), Resistant Starch, Ctrl (Starch)
microbiota
10 days
Lange K, Hugenholtz F, Jonathan MC, Schols HA, Kleerebezem M, Smidt H, Müller M, Hooiveld GJ. Mol Nutr Food Res. 2015 Apr 25.

40. Integration of epithelial cell gene expression
with luminal microbiota composition
Bacterial groups within
Clostridium cluster XIVa
positively correlated
with genes involved in
energy metabolism (1)
Lange K, Hugenholtz F, Jonathan MC, Schols HA, Kleerebezem M, Smidt H, Müller M, Hooiveld GJ. Mol Nutr Food Res. 2015 Apr 25.

41. PPARg targetsUpstream regulator
Role of Pparg in fibre-dependent gene regulation
1
Activation score per dietary fiber
RS FOS AX IN GG
PPARG 2.83 2.01 4.23 3.07
HNF4A 2.58 3.50
TP53 2.36 2.82
ATF4 2.61 2.43
PPARGC1A 2.39 2.08
XBP1 2.93
NR5A2 2.61
SREBF1 2.58
FOXC2 2.43
SREBF2 2.22
PTTG1 2.21
NR1I2 2.09
CEBPB 2.02
KDM5B 2.00
NCOA2 2.00
TP63 -2.15
STAT5B -2.16
MBD2 -2.23
STAT5A -2.36
MYC -2.63
Lange K, Hugenholtz F, Jonathan MC, Schols HA, Kleerebezem M, Smidt H, Müller M, Hooiveld GJ. Mol Nutr Food Res. 2015 Apr 25.

42. Role of dietary fibres in the colon
• Differential regulation of genes involved in
metabolic, energy-generating and oxidative
processes & those involved in adhesion dynamics
and signalling by dietary fibres.
• Strongly linked to Clostridium cluster XIVa bacteria
(butyrate producers) & likely governed by the
transcription factor PPARg (MCB 2013; & recent
data with organoids from gut-specific Pparg-k.o..
mice).
• Because of different fermentation behaviour fibres
will have a diverse location-specific impact on the
microbiome and the host immune-metabolic
responses.
• Not ‘one fibre fits all’: Diverse food patterns are
recommended to keep our guts ‘flexible and
healthy’!
Lange K, Hugenholtz F, Jonathan MC, Schols HA, Kleerebezem M, Smidt H, Müller M, Hooiveld GJ. Mol Nutr Food Res. 2015 Apr 25.

43. We are what we fed them…?
How strong is the science yet?
‘our gastrointestinal tract is not only the body's most under-appreciated organ,
but "the brain's most important adviser”’.

44. Back to Humans: Identification and Personalized
Treatments of Patients at Risk for Developing NCD
(e.g.T2D) Based on the Microbiota
Microbial Modulation of Insulin Sensitivity
Khan, Muhammad Tanweer et al.
Cell Metabolism , Volume 20 , Issue 5 , 753 - 760

45. The Norwich Centre for Food and Health (2017)

46. Plant and Crop
Science for Health
(JIC/IFR/UEA/TGAC) Human Nutrition
With Controlled
Interventions to
Evidence for
Prevention of NCDs
(UEA/IFR/NNUH)
Molecular Nutrition
From Association to
Causality
(UEA/IFR/
JIC/TGAC)
Liver-Gut
Crosstalk in
Health & Disease
(IFR/UEA/NNUH)
Gut-Food-Microbe
Interactions in Health
& Disease
(IFR/UEA/JIC/TGAC)Food-borne
Pathogens
Food Safety
(IFR/UEA)
Gut Mucosal Immunity
& Inflammatory
Diseases
(IFR/UEA/NNUH)
Impact of
Gut & Liver for
Systemic Diseases
(UEA/NNUH/IFR)
Nutrition &
Organ Memory
Stem cells
From Health to
Disease
(UEA/IFR/NNUH)
Big Data
Network analysis &
Systems integration
(TGAG/UEA/IFR)
Food and Immuno-Metabolic Health Alliance
Opportunities for an Integrated Approach

47. Take home messages
• A systems nutrition approach (not correlation science) is necessary to
understand causal relationships between our food(s) patterns & organ
and systemic health => next-generation nutritional sciences.
– Challenges & sensing mechanisms
– From molecular nutrition to mode of action
– Complex diseases: The role of interorgan crosstalk & of organ capacity
– Opportunities for customized / precision nutrition
– Biological Systems Multi-omics to elucidate the Role of Nutrition in
the Genotype-Phenotype Relationship
A healthy gut is an essential gatekeeper for a human health => we
need a comprehensive understanding of the host-microbe-food
interaction for more healthy modern (reformulated) foods and improved
(customized) therapies.
"Eat food, not too much, mostly plants”