Thesis
Reference
Study of the circadian rhythm in healthy volunteers, obese and type 2 diabetic patients
MAKHLOUF, Anne-Marie
Abstract
Notre rythme circadien régule l'expression de gènes impliqués dans les métabolismes des lipides et du glucose. Notre objectif est de comparer l'expression des gènes circadiens dans la peau de patients obèses et diabétiques de type 2 (DT2), comparé aux sujets sains. Des sujets sains, obèses, et DT2 étaient recrutés. Une biopsie de la peau et une prise de sang étaient réalisées. Les gènes rapporteurs de la luciférase sous contrôle de promoteurs circadiens étaient introduits dans les fibroblasts de la peau et les profils de bioluminescence enregistrés. La durée de la période n'était pas différente entre les sujets sains et les patients DT2. La valeur de l'HbA1c était inversement corrélée à la durée de la période chez les patients DT2. Un grand nombre de gènes différentiellement exprimés en fonction du chronotype a été détecté. Il existe une interaction entre le rythme circadien et le métabolisme du glucose chez l'humain.
MAKHLOUF, Anne-Marie. Study of the circadian rhythm in healthy volunteers, obese and type 2 diabetic patients. Thèse de doctorat : Univ. Genève, 2016, no. Sc. 5026
URN : urn:nbn:ch:unige-909673
DOI : 10.13097/archive-ouverte/unige:90967
Available at:
http://archive-ouverte.unige.ch/unige:90967
Disclaimer: layout of this document may differ from the published version.
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1 UNIVERSITE DE GENEVE
Département de génétique et évolution FACULTE DES SCIENCES Professeure Emi Nagoshi HÔPITAUX UNIVERSITAIRES DE GENEVE
Département des spécialités de médecine FACULTE DE MEDECINE Professeur Claude Pichard Docteure Charna Dibner
Study Of The Circadian Rhythm In Healthy Volunteers, Obese And Type 2 Diabetic Patients
THÈSE
présentée à la Faculté des sciences de l’Université de Genève pour obtenir le grade de Docteur ès sciences, mention biologie
par
Anne-Marie MAKHLOUF de
Ferney-Voltaire (France)
Thèse n° 5026 Genève 04 janvier 2017
2
3 AKNOWLEDGEMENTS
I sincerely thank Pr. Claude Pichard for giving me the opportunity to do my PhD under his supervision and for all the knowledge he has transmitted to me over the years.
I would also like to express my gratitude to Dr. Charna Dibner who welcomed me in her lab, proposed me to do my PhD, supervised me and taught me all the techniques of molecular biology.
My research was much improved thanks to the supervision and precious advices of Pr.
Jacques Philippe, Pr. Françoise Rohner-Jeanrenaud and Pr. Michelangelo Foti. I gratefully thank Dr. Patrick Meyer and Dr. Zoltan Pataky for helping in human subject recruitment and enrolment in my research project, the team of Pr. Emmanouil Dermitzakis for performing RNA sequencing, in particular Cedric Howald for conducting the RNA sequencing analysis.
Besides my advisors, I would like to thank the rest of my thesis committee: Pr. Emi Nagoshi and Pr. Steven Brown.
It was a real pleasure to work together with Laurent Perrin, and share with him highs and lows of this enriching experience.
A special thanks goes to my lab members and lab neighbours, particularly Mounia and Ingrid for their help in performing many experiments, but also Tiphaine, Pamela, Camille, Svetlana, Volodymyr, Laurianne, Ursula, Flore, Miguel, Marie-Claude, Florian, Yvan, Rodolphe, Jonas, Nicolette, Xénia, Silvana, Sandra and Sarah for their enthusiasms and all the great moments we spent together.
My PhD thesis would have been incomplete without the Nutrition Unit team with whom it has been a pleasure to work; I particularly thank Séverine Graf for her support every day, and
4 also Marinette Chikhi, Marina Schütz and Ronan Thibault. I deeply thank Laurence Genton-Graf who both offered me a first job and my first paper.
Last but surely not least, many thanks to my family, Thomas and my friends who supported my ups and downs during these years.
In memory of my grand-mother and Ludo, who encouraged me to do the PhD.
5 ABBREVIATIONS
AMPK 5' adenosine monophosphate-activated protein kinase ARNT Aryl hydrocarbon receptor nuclear translocator protein bHLH-PAS Basic helix-loop-helix Per Arnt Sim domain
BMAL1 Brain-Muscle ARNT-Like 1
BMI Body Mass Index
BRIP1 BRCA1 interacting protein C-terminal helicase1 BSA Bovine serum albumin
CCG Clock-controlled gene
CK1 Casein Kinase 1
CLOCK Circadian locomotor output cycles kaput COL18A1 Collagen, Type XVIII, alpha 1
CREBP C-AMP response element-binding protein
CRY Cryptochrome
CT Circadian time
CYP19A1 Cytochrome P450, family 19, subfamily A, polypeptide 1 DAB1 Dab, reelin signal transducer, homolog 1
DBP Albumin D-box binding protein DHA Docosahexaenoic acid
DIO2 Deiodinase, iodothyronine type II DMEM Dubelcco’s modified Eagle medium
dNTP Deoxynucleotide
DTT Dithiothreitol
EDTA Ethylene diamine tetraacetic acid EGTA Ethylene glycol tetraacetic acid EPA Eicosapentaenoic acid
EPAS1 Endothelial PAS domain protein 1 FACS Fluorescence-activated cell sorting FASPS Familial advanced sleep phase syndrome FCS Fetal calf serum
FFA Free fatty acid
FGF21 Fibroblast growth factor 21 GDF15 Growth differentiation factor 15 GFP Green fluorescent protein
GO Gene ontology
GPCR G protein-coupled receptor HbA1c Glycated hemoglobin A1c HEK293T Human embryonic kidney HEK293T Human embryonic kidney cells
HFD High fat diet
HPRT Hypoxanthine guanine phosphoribosyl transferase
6 HRP Horseradish peroxidase
HT1080 Human fibrosarcoma cells
ICAM1 Intercellular adhesion molecule 1
ipRGC Intrinsically photosensitive retinal ganglion cells
ITIH5 Inter-alpha-trypsin inhibitor heavy chain family, member 5 KEGG Kyoto encyclopedia of genes and genomes
KO Knock-out
LA Linoleic acid
LB Lysogeny broth
LYPD6 LY6/PLAUR domain containing 6 MCTQ Munich chronotype questionnaire MGP Matrix gla protein
MOI Multiplicity of infection MSF Mid-sleep on free days
NAD Nicotinamide adenine dinucleotide NAMPT Nicotinamide phosphoribosyltransferase NPAS2 Neuronal PAS domain protein 2
NUAK1 NUAK family, SNF1-like kinase, 1
OA Oleic acid
OGA β-N-acetylglucosaminidase O-GlcNAc β-linked N-acetylglucosamine OGT β-N-acetylglucosaminyltransferase P/S Penicillin/streptomycin
PA Palmitic acid
PAPPA Pregnancy-associated plasma protein A, pappalysin 1 PAR bZIP Proline and acid-rich basic leucine zipper domain PBS Phosphate balanced saline
PEI Polyethylenimine
PER Period
PGC1 Peroxisome proliferator-activated receptor gamma coactivator-1-alpha PI3K Phosphatidylinositol-4,5-bisphosphate 3-kinase
PKA Protein kinase A
PUGNAc O-(2-acetamido-2-deoxy-d-glucopyranosylidene)-amino-N- phenylcarbamate
PVDF Polyvinylidene difluoride REV-ERB Reverse-erb
RIN RNA integrity number
RIPA Radioimmunoprecipitation assay ROR Retinoid-related orphan receptors
RORE Retinoic acid-related orphan receptor response element RPKM Reads per kilobase per million mapped reads
RPP25 Ribonuclease P/MRP 25kDa subunit RXR Retinoid X receptor
SCN Suprachiasmic nucleus
7
SD Standard deviation
SDS Sodium dodecyl sulfate SERTAD4 SERTA domain containing 4 SEM Standard error of the mean SIM Single-minded protein SIRT1 Sirtuin 1
SNP Single-nucleotide-polymorphism
SREBP Sterol regulatory element-binding proteins SUMO Small ubiquitin-like modifier
T2D Type 2 Diabetes
TBS Tris-buffered saline
TTFL Transcriptional-translational feedback loop TUFT1 Tuftelin 1
VNTR Variable number tandem repeat
WT Wild-type
ZT Zeitgeber time
8
9 CONTENTS
1. ABSTRACT 13
2. RESUME DE THESE 17
3. INTRODUCTION 21
3.1. HISTORY AND CONCEPT 21
3.2. CENTRAL AND THE PERIPHERAL CLOCKS 22
3.3. ENTRAINMENT OF THE CIRCADIAN RHYTHM 25
3.4. THE MOLECULAR MAKEUP OF MAMMALIAN CLOCK 26
3.4.1. THE CORE CLOCK GENES: DESCRIPTION OF THE TRANSCRIPTIONAL-TRANSLATIONAL
FEEDBACK LOOP MODEL (TTFL) 26
3.4.2. THE CLOCK-CONTROLLED GENES, PROTEINS AND METABOLITES 27 3.4.3. ROLE OF THE POST-TRANSLATIONAL MODIFICATIONS IN SUSTAINING THE MOLECULAR
CLOCK 29
3.5. CIRCADIAN RHYTHM PARAMETERS 32
3.6. CIRCADIAN RHYTHM AND METABOLIC DISORDERS 33
3.6.1. RECIPROCALLY CONNECTIONS BETWEEN THE CIRCADIAN CLOCK AND METABOLISM 33
3.6.2. INTERCONNECTION BETWEEN OBESITY AND THE CIRCADIAN CLOCK 33
3.6.2.1. STUDY OF OBESITY AND CLOCK IN MICE MODELS 33
3.6.2.2. EVIDENCE OF CONNECTIONS BETWEEN OBESITY AND CIRCADIAN CLOCK IN HUMANS 35 3.6.3. ROLE OF THE CIRCADIAN CLOCK IN THE PATHOLOGY OF TYPE 2 DIABETES (T2D) 36 3.6.3.1. MICE STUDIES ON THE CONNECTION BETWEEN T2D AND CLOCK 36
3.6.3.2. EXPLORATIONS IN HUMANS 38
3.7. STUDY OF CIRCADIAN RHYTHM IN HUMANS 40
3.7.1. CHRONOTYPE: DEFINITION AND APPROACHES FOR HUMAN CHRONOTYPE ASSESSEMENT 40
3.7.2. ANALYSIS OF MELATONIN SECRETION 41
3.7.3. MOLECULAR CLOCK ASSESSMENT IN DIFFERENT HUMAN CELL TYPES 42
4. HYPOTHESIS 47
5. OBJECTIVE 49
6. MATERIALS AND METHODS 51
6.1. STUDY DESIGN 51
6.2. PATIENT RECRUITMENT 52
6.3. SKIN BIOPSY AND BLOOD COLLECTION 54
6.4. PRIMARY SKIN FIBROBLAST CULTURE 55
6.5. LENTIVIRAL PLASMID PREPARATION 56
6.5.1. BMAL1-LUCIFERASE (BMAL1-LUC) AND PER2-LUCIFERASE (PER2-LUC) PLASMIDS 56
6.5.2. PLASMID PURIFICATION 56
6.6. LENTIVIRUS PRODUCTION AND TITRATION 58
6.7. LENTIVIRAL TRANSDUCTION AND SELECTION 62
10 6.8. IN VITRO SYNCHRONIZATION OF THE CULTURED HUMAN SKIN FIBROBLASTS 62
6.9. REAL-TIME BIOLUMINESCENCE RECORDING 63
6.10. CROSS-SERUM EXPERIMENT 63
6.11. GLUCOTOXICITY AND LIPOTOXICITY ASSAYS 64
6.12. ANALYSIS OF CELL VIABILITY BY TRYPAN BLUE STAINING METHOD 65
6.13. DNA AND RNA EXTRACTIONS 65
6.14. REVERSE TRANSCRIPTION AND QUANTITATIVE PCR(RT-QPCR) 66
6.15. PROTEIN EXTRACTION AND WESTERN BLOT 68
6.16. RNA SEQUENCING: LIBRARY PREPARATION, MAPPING AND ANALYSIS 69
6.17. STATISTICAL ANALYSES 70
7. RESULTS 73
7.1. PATIENT CHARACTERISTICS 73
7.2. OPTIMIZING EXPERIMENTAL CONDITIONS FOR STUDYING CIRCADIAN RHYTHM IN CULTURED
PRIMARY HUMAN SKIN FIBROBLASTS 79
7.2.1. EFFECT OF HUMAN SERUM CONCENTRATION AND CELLULAR OSCILLATION PERIOD LENGTH 79 7.2.2. IMPACT OF DEXAMETHASONE AND FORSKOLIN SYNCHRONIZATION ON THE HUMAN
FIBROBLAST OSCILLATORY PROFILE. 80
7.3. IMPACT OF THE HUMAN SERUM ON THE SKIN FIBROBLAST CIRCADIAN RHYTHM 82 7.4. OSCILLATION PROFILES AND CIRCADIAN CHARACTERISTICS OF THE PRIMARY SKIN
FIBROBLASTS ESTABLISHED FROM HEALTHY, OBESE, T2D OBESE AND T2D NON-OBESE
SUBJECTS 84
7.4.1. RECORDING CIRCADIAN OSCILLATIONS IN THE PRIMARY SKIN FIBROBLASTS FROM HEALTHY,
OBESE AND T2D INDIVIDUALS IN THE PRESENCE OF OWN SERUM. 84 7.4.2. CIRCADIAN PERIOD LENGTH DISTRIBUTION IN HEALTHY, OBESE AND T2D SUBJECTS 87 7.4.3. COMPARISON OF PERIOD LENGTHS OBTAINED FROM PRIMARY SKIN FIBROBLASTS FROM
HEALTHY, OBESE AND T2D INDIVIDUALS IN THE PRESENCE OF OWN SERUM OR FCS. 89
7.4.4. STUDIES OF ENDOGENOUS CORE CLOCK TRANSCRIPTS 92
7.5. HBAC1 VALUE EXHIBITS STRONG INVERSE CORRELATION WITH THE SKIN FIBROBLASTS
OSCILLATION PERIOD IN T2D INDIVIDUALS. 95
7.5.1. EFFECT OF THE OGA INHIBITOR PUGNAC ON THE OSCILLATION PROFILES 97 7.5.2. ANALYSIS OF O-GLYCOSYLATED PROTEINS IN HEALTHY AND T2D SUBJECTS 99 7.6. LARGE SCALE TRANSCRIPTOME ANALYSIS OF SKIN FIBROBLASTS DERIVED FROM T2D
PATIENTS 102
7.6.1. EXPRESSION OF GENES IMPLIED IN GLUCOSE METABOLISM AND CIRCADIAN RHYTHM 103 7.6.2. THE CHRONOTYPE OF T2D PATIENTS INFLUENCE THE GENE EXPRESSION IN FIBROBLASTS 105 7.7. ADDITIONAL CORRELATIONS BETWEEN THE SERUM FACTORS, THE CIRCADIAN PARAMETERS
AND ANTHROPOMETRIC VALUES 109
7.7.1. CORRELATIONS IN THE GROUP OF HEALTHY VOLUNTEERS 109
7.7.2. ABSENCE OF SIGNIFICANT CORRELATIONS BETWEEN GLUCOSE AND LIPID PARAMETERS OF
T2D PATIENTS AND THEIR CIRCADIAN CLOCK PROPERTIES. 110
7.7.3. CORRELATIONS BETWEEN LIPID PROFILES AND THE PERIOD LENGTH IN OBESE PATIENTS 112 7.8. IMPACT OF GLUCOTOXICITY ON THE CELLULAR CIRCADIAN CLOCK PROPERTIES 113
7.9. DISRUPTION OF THE CIRCADIAN OSCILLATIONS BY LIPIDS 116
11 7.9.1. IMPACT OF FFA ON THE CIRCADIAN OSCILLATIONS OF HUMAN FIBROBLASTS 116 7.9.2. LIPID MIXTURES ADDED IN THE RECORDING MEDIUM DO NOT AFFECT THE CIRCADIAN
OSCILLATIONS 119
7.9.3. EFFECT OF GLUCO-LIPOTOXICITY ON CIRCADIAN OSCILLATIONS OF HUMAN SKIN
FIBROBLASTS 120
8. DISCUSSION AND CONCLUSION 123
9. REFERENCES 137
10. APPENDICES 147
12
13 1. ABSTRACT
Background: There is an increasing evidence for the critical roles of the circadian clock in the body metabolism orchestration. Disruption of the circadian clock is leading to insulin resistance and diabetes development in rodents. We aimed at studying molecular makeup of circadian oscillations in healthy subjects, obese and type 2 diabetes (T2D) patients, employing primary skin fibroblasts as an experimental system. Moreover, the impact of high concentration of glucose and fatty acids (gluco- and lipotoxicity) on the human fibroblasts circadian clock has been assessed.
Methods: Healthy controls, obese and T2D (non-obese and obese) patients were recruited.
2mm skin biopsy and blood collection were performed at 8 A.M. The subjects were sex and MCTQ (chronotype evaluation) matched between the groups. After establishing primary skin fibroblast culture from each biopsy, circadian luciferase reporters (Bmal1-luciferase, Period2- luciferase) were introduced by lentiviral transduction, cells were synchronized by single dexamethasone pulse, and bioluminescence profiles were recorded using photomultiplier tubes. The recording was performed in the presence of the subject’s own serum. Western- blots were performed to test whether O-GlcNAcylation might impact on the circadian period.
RNA sequencing was used to analyse the level of gene expression in cells from T2D group.
To assess the effect of gluco-and lipotoxicity on the fibroblast circadian rhythm, different concentrations of glucose and fatty acids (Ω3, Ω6, bovine serum albumin (BSA)-coupled palmitate, oleate and linoleate) were added to the cell culture medium with subsequent recording of circadian bioluminescence. Oscillation profiles were analyzed for the period length and compared by Mann-Whitney U test between the groups. Correlation between glycated hemoglobin (HbA1c) and period length was defined by spearman’s rank correlation coefficient.
14 Results: 11 healthy volunteers, 8 obese subjects and 17 T2D patients (8 non-obese and 9 obese) were recruited for this study. No significant differences in circadian period length of the established primary skin fibroblasts have been observed between healthy and T2D groups recorded from the individual primary skin fibroblasts in the presence of own sera (Bmal1-luc:
p=0.119, Per2-luc: p=0.051). Of note, inside T2D group HbA1c value exhibited strong inverse correlation with the oscillation period: (ρ = -0.592 p= 0.012) for obese T2D and (ρ = - 0.802 p= 0.017) for non-obese T2D patients. In obese patients, the period length recorded with Bmal1-luc and Per2-luc reporters in the presence of subject’s own serum was not different from the period length measured in healthy group (Bmal1-luc: p=0.242, Per2-luc:
p=0.911). The phase was advanced of 1h 36 minutes ± 24 minutes for the obese group compared to the healthy volunteers. According to RNAseq analyses, expression levels of ICAM1 transcript were higher in patients with a short circadian period than in those with longer period. Moreover, large number of genes was differentially expressed according to the subject chronotype. The variation of glucose concentration in the medium did not affect the circadian rhythm. Palmitate and oleate exhibited weak effects on the cellular circadian phase.
Conclusion: We assessed the circadian oscillation profiles of human primary fibroblasts established from healthy, T2D and obese patients. The correlation between HbA1c levels and period length in diabetic patients might suggest an interaction between circadian rhythm and glucose metabolism in humans. In cells from T2D patients, the genes were differentially expressed according to the chronotype. Obesity seems to affect the circadian oscillations in humans. The modifications of the concentration of glucose and the addition of lipids to the culture medium of the skin fibroblasts did not significantly affect the circadian oscillations, probably suggesting that longer incubation time might be required to study the effect of glucolipotoxicity on the circadian oscillator. Identifying the molecular pathways involved in
15 circadian disruption in obesity and T2D is important for understanding these disease etiologies and developing new avenues for the treatment.
16
17 2. RESUME DE THESE
Introduction et but de l'étude: Notre rythme circadien régule l’expression de gènes impliqués dans les métabolismes des lipides et du glucose. Chez les rongeurs, une perturbation de l’horloge entraîne une insulino-résistance et l’apparition du diabète. A l’échelle moléculaire, elle peut être étudiée dans les fibroblastes de la peau puisqu’ils reflètent le profil circadien physiologique. Notre objectif est de comparer l’expression des gènes circadiens dans la peau de patients obèses et diabétiques de type 2 (DT2), comparé aux sujets sains. L’effet de différentes concentrations de glucose et d’acides gras sur les profils circadiens a également été étudié.
Matériel et méthodes: Quatre groupes de sujets ont été recrutés : sains, obèses, DT2 obèses et DT2 non obèses. Une biopsie de la peau et une prise de sang (dosage de l’HbA1c et des lipides) ont été réalisées à 08h. Après mise en culture des fibroblastes de la peau, les gènes rapporteurs de la luciférase Bmal1-luciférase (Bmal1-luc) et Per2-luciférase (Per2-luc) ont été introduits par transduction lentivirale et les profils de bioluminescence ont été enregistrés grâce à un tube photomultiplicateur. Les enregistrements ont été effectués avec le propre sérum du patient. L’impact de la O-glycosylation des protéines sur la durée de la période a été étudié par western-blot. L’analyse de l’expression des gènes dans les cellules des patients DT2 a été effectuée par séquençage de l’ARN. Différentes concentrations de glucose ou d’acides gras (Ω3, Ω6, palmitate couplé à la BSA, oléate et l’acide linoléique) ont été pré- incubées avec les cellules ou ajoutés dans le milieu de culture pendant l’enregistrement. Les profils d’oscillation ont été analysés pour la durée de la période et comparés par Mann- Whitney entre les groupes. Les corrélations entre les valeurs d’HbA1c et de périodes ont été analysées par le coefficient de corrélation de Spearman.
18 Résultats:11 volontaires sains, 8 sujets obèses et 17 patients DT2 (8 non-obèses et 9 obèses) ont été inclus. La durée de la période n’a pas été différente entre les sujets sains et les patients DT2 (Bmal1-luc: p=0.119, Per2-luc: p=0.051), ou DT2 obèses (Bmal1-luc: p=0.583, Per2- luc: p=0.30), ou non obèses (Bmal1-luc: p=0.241, Per2-luc: p=0.111). Une corrélation inverse a été observée entre la valeur de l’HbA1c et la durée de la période chez les patients DT2 (ρ=- 0.592 P=0.012), et les patients DT2 non-obèses. Une corrélation est également obtenue entre les valeurs de triglycérides et la longueur de la période chez les patients obèses non DT2 (ρ=- 0.802 P=0.017).
La durée de la période mesurée dans les cellules des patients obèses ne s’est pas révélée différente de celle des sujets sains (Bmal1-luc: p=0.242, Per2-luc: p=0.911). La phase était avancée de 1h36 minutes ± 24 minutes pour le groupe des patients obèses comparé au groupe contrôle. La durée de la période était corrélée positivement aux valeurs de triglycérides et LDL dans le groupe des patients obèses. Chez les patients DT2, l’expression du gène ICAM1 était plus importante chez les patients ayant une période plus courte comparé aux patients avec une période plus longue. Par ailleurs, un grand nombre de gènes différentiellement exprimés en fonction du chronotype a été détecté. Les différentes concentrations de glucose dans le milieu de culture n’affectaient pas le rythme circadien. L’ajout de palmitate ou d’oléate dans le milieu de culture avait peu d’effet sur la phase cellulaire.
Conclusion: Le rythme circadien a pu être mesuré dans les fibroblastes primaires humains des patients sains, diabétiques de type 2 et obèses. La corrélation entre la durée de la période et l’HbA1c chez les patients DT2 confirme qu’il existe une interaction entre le rythme circadien et le métabolisme du glucose chez l’humain. Dans les cellules des patients DT2, les gènes étaient différemment exprimés en fonction du chronotype. L’obésité semble perturber le rythme circadien de l’Homme. L’ajout de différentes concentrations de glucose ou de lipides dans le milieu de culture des fibroblastes humains ne modifiait pas les profils
19 circadiens. Il est maintenant crucial d’identifier les voies moléculaires impliquées dans la perturbation des rythmes chez les patients obèses et diabétiques de type 2.
20
21 3. INTRODUCTION
3.1. History and concept
Sunlight has always been a life guide, and was the only time marker before the invention of clocks. Sumerians, Incas or any nomad populations used the variation of light along the day and the seasons to guide their activities such as agriculture. All light-sensitive organisms possess an internal clock that follows the 24 hours day/night cycle. This helps the organism to adapt its physiology and behavior depending on the external stimulus.
The first experiment demonstrating the existence of an internal clock was done on plants in 1729. Jean Jacques d’Ortous de Mairan, a French astronomer observed that mimosa leaves were still opened in the forced obscurity [1]. Leaves movements were independent of the presence or absence of light, implying the existence of an internal clock in plants. This hypothesis was verified by Duhamel in 1758 and Candolle in 1799. They did the same experiment than De Mairan but in a condition of controlled temperature and humidity (Candolle), that are dependent on the rotation of the earth [2]. They observed the same phenomenon: The leaf movements persist in the absence of an external cue; they would possess an internal clock.
In animals, the De Mairan’s hypothesis was observed in the late 19th century. The rhythm of pigment in arthropods was described by Kiesel [3] and the body temperature rhythmic variation in squirrel monkeys by Simpson and Galbraith [4]. In mammals, Curt Richter raised the hypothesis of a freerunning rhythm after observing the persistence of the rhythmicity in rats in constant conditions [5]. Later, in the 1950s, Aschoff confirmed the presence of an endogenous clock independent of light-dark cycle and in different animal models (rats, chicken). For example, Aschoff raised the chicken eggs under constant conditions and their daily rhythms remained normal. To study biological rhythms in humans, Aschoff used a
22 bunker without natural daylight. 25 subjects including himself lived in the bunker during 3-4 weeks, and the participants could manage their daily activities whenever they wanted [6].
Despite no sunlight or no time clue, the average days of the subjects were about or longer than 24 hours, but remained constant during the entire experiment. This indicated that the human body possesses an internal clock that is adjusted to the light/dark cycle and that controls daily rhythms. It is now called the circadian rhythm (“circa” means around, “diem” means day in Latin).
The existence of a circadian rhythm and the study of chronobiology has become a field of interest for many scientists.
3.2. Central and the peripheral clocks
In mammals, the circadian rhythm is driven by both a central and a peripheral clock. The central clock is located in the suprachiasmatic nucleus (SCN) of the hypothalamus, and acts as a central pacemaker receiving a direct synchronization signal from the light [7,8]. Figure 1 shows the localization of the SCN in a mouse brain [9].
Figure 1. (Adapted from [9]). Localization of the nuclei in the mammalian brain. AMY, amygdala;
ARC, arcuate nucleus; BNST, bed nucleus of the stria terminalis; CB, cerebellum; CX, cortex; DG,
23 dentate gyrus; DMH, dorsomedial hypothalamus; DRN, dorsal raphe nucleus; HB, habenula; Hip, hippocampus; LH, lateral hypothalamus; ME, median eminence; MRN, median raphe nucleus; NAc, nucleus accumbens; NTS, nucleus of the solitary tract; OB, olfactory bulb; OVLT, vascular organ of the lamina terminalis; Pi, piriform cortex; Pin, pineal gland; Pit, pituitary gland; PVN, paraventricular nucleus of the hypothalamus; PVT, paraventricular nucleus of the thalamus; Ret, retina; RVLM, rostral ventrolateral medulla; SCN, suprachiasmatic nuclei; SON, supraoptic nucleus; VLPO, ventrolateral preoptic area; VTA, ventral tegmental area.
The light is integrated in the retina by the cones and rods that transfer the signals to the horizontal, bipolar and amacrine cells. Then the signal is integrated by the intrinsically photosensitive retinal ganglion cells (ipRGC) expressing the photopigment melanopsin [10].
These cells transfer the information to the SCN using the optic nerve (see Figure 2).
Figure 2. (Adapted from Hatori [10]). Integration of light by the intrinsically photosensitive retinal ganglion cells (ipRGC). H, horizontal cells; B, bipolar cells; A, amacrine; RPE, retinal pigment epithelium; OPL, outer plexiform layer; INL, inner nuclear layer; IPL, inner plexiform layer;
GCL, ganglion cell layer.
A circadian system is organized in a hierarchical manner, so that most organs possess internal clocks, called the peripheral clocks [11-13]. These peripheral oscillators can be synchronized either directly or indirectly. The direct pathway comes from the SCN that projects its output neurons through the sympathetic nervous system or by sending humoral signals. The indirect
24 pathway implied the feeding/fasting cycle. Metabolites and feeding-related hormones released participate at modulating the peripheral clock (Figure 3) [14]. Rats with SCN lesions showed a periodicity (assessed using wheel-running activity) of 24 hours under restricted feeding of 24 hours while the periodicity was desynchronized when rats were on ad libitum condition [15]. This underlines the presence of peripheral clock sensitive to external clue such as food availability. The peripheral clock can function independently of the SCN, such as the clock liver that can be entirely impaired from the SCN phase by the food entrainment [16].
Figure 3. (Adapted from [9]). Interplay between central and peripheral clocks. The central clock located in the SCN controls the whole body circadian rhythms by direct or indirect pathways.
25 3.3. Entrainment of the circadian rhythm
The generation of a circadian rhythm is based on the notion of synchronization, also called
“Zeitgeber” (German word for “time giver”). The light is the major Zeitgeber, since its presence or absence determines the day/night cycle. Food intake, neural and hormonal signals, temperature and exercise are all synchronizers acting directly on the peripheral organs. The circadian rhythm can be shifted due to an external cue (e.g. jet lag caused by different time zones). A new external stimulus is necessary to adjust the circadian clock. This capacity of alignment of the circadian rhythm is called the entrainment, and it represents a main characteristic of the circadian clock.
The effectiveness of the light entrainment to the day/night cycle was studied in humans by exposure to different light intensity and time exposures. For example, the circadian rhythm was disrupted for several hours when the volunteers were subjected to only 5 min of bright light (10 000 lux) during a 5 hour-interval on 3 consecutive days [17].
The temperature showed circadian variations across the day but also acts as a synchronizer [18]. It resets the mammalian peripheral oscillator and small variations of temperature (one to three degree difference) could synchronize the fibroblast clock [19,20].
The ability of food to entrain the peripheral clock in mammal has been first demonstrated by Stokkan et al. in 2001. In mice, restricted feeding entrained the clock liver independently of SCN, suggesting that food could synchronize peripheral oscillators [16].
26 3.4. The molecular makeup of mammalian clock
The molecular mechanism underlying the circadian rhythm is determined by the group of genes called the “core clock genes”. These core clock genes control the expression of additional genes named the clock-controlled genes (CCG) that participate in the regulation of the circadian physiology.
3.4.1. The core clock genes: Description of the transcriptional-translational feedback loop model (TTFL)
The clock model in mammals was first described in 1994 with the discovery of the Clock gene in mice by Takahashi et al [21]. More clock genes have been discovered allowing a comprehensive overview of the TTFL model.
Brain-Muscle ARNT-Like 1 (BMAL1) and Circadian Locomotor Output Cycles Kaput (CLOCK) belong to the superfamily of the basic helix-loop-helix PAS domain (bHLH-PAS) transcription factors.
BMAL1 and CLOCK heterodimerize to bind on cis-regulatory element E-box (5’-CACGTG- 3’) or E’-box (5’-CACGTT-3’) of Period (Per1, Per2, Per3) and Cryptochrome (Cry1, Cry2) genes, thus initiating their transcription. When the PERIOD and CRYPTOCROME protein levels reach a certain threshold, PER and CRY translocate into the nucleus and form a multiprotein complex which will inhibit their own transcription. BMAL1:CLOCK complex constitutes the positive limb (or activator), whereas CRY:PER complex represents the negative limb (repressor) of TTFL. In parallel to this main feedback loop, a secondary (auxiliary) loop comprising the ROR/REV-ERB orphan nuclear receptors, modulates the main one. Specifically, REV-ERBα inhibits the expression of BMAL1 whereas RORα enhances it by competitively binding to retinoic acid-related orphan receptor response elements (ROREs)
27 present on Bmal1 promoter [22]. The expression levels of core clock genes are thus oscillating with the period length of nearly 24 hours (Figure 4).
Figure 4. (Adapted from [23]). The simplified model of the mammalian circadian molecular oscillator. BMAL1:CLOCK complex represents the negative arm of the feedback loop model and CRY:PER heterodimer is the positive arm. CCG; Clock-controlled genes.
3.4.2. The clock-controlled genes, proteins and metabolites
Clock-controlled genes (CCG) are genes whose expressions are regulated by the circadian oscillator. CCG possess three different response elements. E-box element allows the binding of the BMAL1:CLOCK complex, RORE motifs bind ROR and REV-ERB family members, and D-elements are binding sites for PAR bZIP factors [24,25]. For instance, the transcription of albumin promoter (albumin D-box) binding protein (Dbp) gene is activated by BMAL1:CLOCK heterodimer, and is repressed by PER and CRY. Dbp is not simply a CCG, since it regulates Per1 transcription indirectly by binding on its D-box element [26].
Large scale transcriptome studies estimate the proportion of cyclic transcripts for each organ in mice by collecting the tissues around the clock. In the liver, 16% of protein-coding genes were rhythmic. In the brown fat and skeletal muscle, the proportions of rhythmically
28 expressed transcripts were 8% and 4% respectively [27]. Atger et al recently showed that rhythmic expression leads to rhythmic mRNA accumulation and rhythmic translation for 72%
of genes [28]. Beyond the transcriptional levels, large scale circadian proteomics analyses were performed to explore the rhythmic accumulation of proteins [29]. The study of proteomic in mouse liver by Mauvoisin et al demonstrated that 50% of proteins displayed a rhythmic oscillation whereas their mRNA expressions were non rhythmics. They also defined the peak phases of protein rhythms at ZT5 and ZT18 [30].
Circadian lipidome and metabolome analyses have been undertaken to explore the oscillatory levels of the lipids and other metabolites [31]. Aviram et al deciphered the oscillations patterns of the different classes of lipids in mouse mitochondria and nucleus. They showed distinct oscillations profiles of lipids between these two organelles [32].
Among those, human plasma and saliva metabolomics by using gas and liquid chromatography coupled to mass spectrometry revealed that around 15% of all identified metabolites in plasma and saliva were controlled by the circadian clock [31].
Clock-controlled proteins and metabolites are involved in regulating a number of key physiological processes, such as glucose or lipid metabolism [33], inflammation [34], and immune functions [35] (Figure 5). The disruption of core clock genes or clock-controlled genes has been related to many pathophysiological processes like modifications of bone homeostasis [36], epileptic seizure [37] or perturbations in xenobiotic metabolism [38]. For instance, PAR bZIP proteins, like DBP, are expressed rhythmically in liver and kidney.
Studies in mice bearing mutations for these proteins revealed a role for PAR bZIP proteins in controlling the expression of key enzymes implied in detoxification, such as cytochrome P450 enzymes [38].
29 Figure 5. (Adapted from [39]). Synchronization of metabolic processes by direct and indirect outputs of core clock genes and CCGs. Metabolism processes like gluconeogenesis and bile acid synthesis are controlled by the molecular clock through oscillating transcriptional factors.
Reciprocally, nutrients variations modulate the circadian clock.
3.4.3. Role of the post-translational modifications in sustaining the molecular clock
Post-translational modifications of the core-clock proteins, such as phosphorylation, acetylation, sumoylation, ubiquitination, glycosylation and others, play a critical role in setting the clock speed in light-sensitive organisms [40].
Nicotinamide adenine dinucletotide (NAD+) is a key factor involved in redox reactions. Its levels are oscillating in liver and adipose tissue, and become lower when Clock and Bmal1 are mutated but higher in the case of Cry1/2 mutations [41]. This indicates a strong association between redox homeostasis and molecular clock. Sirtuin1 (SIRT1) belongs to the sirtuin family of NAD+-dependent acetylase. SIRT1 promotes the degradation and deacetylation of
30 PER2 by binding on CLOCK:BMAL1 rhythmically [42]. SIRT1 acts as a regulator of gluconeogenesis, lipid metabolism and insulin sensitivity [43-46]. A cross talk between SIRT1, NAD+-mediated activity and clock genes has been demonstrated, revealing an interaction between circadian rhythm and nutrient-sensing pathways.
AMPK activity increased in response to stress or prolonged fasting in the liver. CRY1/2 possessed serines that could be phosphorylated by AMPK. Consequently, their interactions and their degradations were stimulated [47].
Casein Kinase 1 (CK1) has been demonstrated as a key regulator of the clock pacing [48].
Knockout mice for CK1δ had perturbation of their circadian rhythms, implying that this kinase is essential for proper function of the clock machinery [49]. PER proteins are phosphorylated by CK1 kinases thereby translocating PER in the nucleus and triggering PER proteins to proteasome degradation [50]. In a pathology called the Familial Advanced Sleep Phase Syndrome (FASPS), mutation of CKIε phosphorylation site of PER2 leads to phase advance of 4h in sleep-wake cycle [51].
Proteins can be O-Glycosylated by an addition of a β-N-acetylglucosamine moiety (O- GlcNAc) on serine/threonine residues. The addition and the removal of O-GlcNAc are modulated by β-N-acetylglucosaminyltransferase (O-GlcNAc transferase; OGT) and β-N- acetylglucosaminidase (O-GlcNAcase; OGA) respectively. O-GlcNAcylated proteins interact with the E-box element present on Dbp promoter, suggesting that clock proteins could be O- GlcNAcylated [25]. In 2012, new evidence came out for a relationship between clock proteins and glycosylation. Kim et al demonstrated in drosophila that dPER is O-GlcNAcylated, and that the timing of dPER nuclear translocation is advanced in OGT knockdown flies, and delayed in OGT overexpressing flies [52]. This means that O-GlcNAcylation stabilizes dPER and thus affects the core clock machinery in the fly. In line with this study, Durgan et al has
31 showed in mammal model (mouse cardiomyocytes) that total protein O-GlcNAc level displayed a rhythmic pattern with a peak during the active (awake) period. Indeed, specific ablation of clock in cardiomyocytes disrupted diurnal variation of O-GlcNAcylated protein level. Moreover, in cardiomyocytes, only BMAL1 and PER1 were O-GlcNAcylated and modifications of the level of protein O-GlcNAcylated modified the abundance of PER2, suggesting interplay between circadian clock and glycosylation in cardiomyocytes [53]. More recently, Kaasik et al demonstrated that O-GlcNAcylation and phosphorylation competed on the same serine residue of PER2 in mouse fibroblasts. These post-translational modifications adjust the stability and ability of PER2 to translocate into the nucleus [54]. Phosphorylation of PER2 on serine 662 by CK1 increases the stability of PER2 in the nucleus, whereas the O- GlcNAcylation by OGT on the same site decreases PER2 stability [54]. Therefore, phosphorylation and glycosylation of clock proteins were intimately connected to regulate their functions. It has been shown in HEK293T cells that O-GlcNAcylation of BMAL1 and CLOCK prevented the clock protein from ubiquitination with subsequent degradation [55].
BMAL1 has been shown to undergo SUMOylation [56]. Removal of SUMO2/3 by specific protease suppressed ubiquitination of BMAL1 whereas absence of ubiquitination induced by an ubiquitin protease led to an accumulation of polysumoylated BMAL1 [56]. These post- translational modifications act together to orchestrate the stability and function of clock proteins.
32 Period
Phase
Amplitude 3.5. Circadian rhythm parameters
The period, the amplitude, the phase and the magnitude constitute the parameters that characterize the rhythmic oscillations (Figure 6).
The period corresponds to the time after which a defined phase of the oscillation occurs again.
When talking about circadian oscillations, the period length is around 24 hours, corresponding to the day/night cycle established by Earth rotation. The amplitude represents the difference between the peaks in a sinusoidal oscillation. The magnitude is the absolute value of the amplitude and is therefore always positive. The phase corresponds to an instantaneous state of an oscillation within a period. A phase shift is a displacement of the oscillation along the time-axis.
The sinusoidal model is determined by this function:
μ(t) = C + A [1 + sin(2π t
T+ θ)] e−Tt
Figure 6. Characteristics of an oscillation profile. The period, the phase and the amplitude define the circadian profile of an oscillation.
33 3.6. Circadian rhythm and metabolic disorders
3.6.1. Reciprocally connections between the circadian clock and metabolism
In peripheral tissues, the molecular clock interacts in a feedback loop with nutrient sensors such as NAD+, NAMPT or SIRT1 as previously described [41,42,57]. REV-ERBα, RORs and PPARs are co-activators of the core clock genes and regulate metabolic processes including adipocyte differentiation and hepatic gluconeogenesis [58-60]. In addition, the secretion of hormones such as glucocorticoides is rhythmic and has the potential to entrain the peripheral clock [61]. These elements underline the strong connection between molecular clock and metabolism.
3.6.2. Interconnection between obesity and the circadian clock
Considering that feeding-fasting cycle is a synchronizer of the peripheral clocks, the temporal food processing may be driven by the circadian clock. The evidence of an interconnection between the obesity and the clock machinery have been demonstrated in mice and humans employing different approaches ranging from transcriptomic to knock-out mice models [62].
3.6.2.1. Study of obesity and clock in mice models
Wild-type (WT) mice fed with high fat diet during one week had a longer period length than mice fed with regular chow [63]. Body weight was comparable between the groups, demonstrating an independency between the period length and the body weight. Mice fed with high fat diet presented higher food intake during the light phase, when they usually eat a little. The expression of genes implied in lipid metabolism was different between these mice in the fat and in the liver. For example, Srebp-1c expression level was diminished in the fat of mice fed with high fat diet. The 24 hour oscillations of RORα and RXRα, two nuclear receptors interacting with Bmal1, observed in regular chow fed mice were reduced in fat of mice fed with high fat diet [63].
34 WT and Clock mutant mice were fed with either regular or high fat chow over 10 weeks.
Energy intake and body weight were higher in Clock mutant mice compared to the control group. Histological analyses revealed that these mice fed with high fat chow presented adipocyte hypertrophy and glycogen accumulation in hepatocytes. Clock mutant mice fed with regular chow had hypercholesterolemia, hypertriglyceridemia and hypoinsulinemia that are metabolic markers of diet-induced obesity [64]. Bmal1 over-expression in 3T3-L1 adipocytes increased lipid synthesis, demonstrating a strong relation between clock genes and lipid metabolism [65].
The implication of Bmal1 in obesity remains controversial since KO mice for Bmal1 displayed different phenotypes according to different studies. Hemmeryckx et al observed a reduction of weight in Bmal1-/- mice compared to WT mice but this difference was attributed to premature aging [66]. In the paper from Shi et al fat accumulation and low body weight were shown in Bmal1-knockout mice, suggesting they are obesity-prone [67]. At the molecular level, Bmal1-knockout mice model showed that a deletion of this core clock gene could impact the transcriptional, posttranscriptional and translational processes in the liver.
The feeding rhythm of these mice would increase the translation efficiency of genes with specific sequences (5’-TOP and TISU motif) [28].
In obese mice, 80% of core clock gene expression was suppressed in mesenteric arteries compared to lean mice, highlighting the importance of clock function in the cardiovascular system [68].
Food represents a strong resetting stimulus for the peripheral clocks. Thus inversed day- feeding schedule has been demonstrated to entirely uncouple liver clock from the SCN clock [69]. A short feeding stimulus of 30 minutes in rats leaded to down-regulation of clock genes in the heart with phase shift of 30 minutes, supporting the idea that even a short food stimulus
35 could synchronize the clock [70]. A long-term high fat diet in mice induced over-expression of circadian clock-controlled genes in the liver and kidneys [71].
High fat diet is known to disrupt circadian clock therefore metabolic pathways like glucose and lipid metabolism. When mice were fed a high fat diet during a defined time (Timed HF), they gained less weight than mice fed with high fat diet ad libitum and daily rhythms of glucose and triglycerides were not different between the groups. Cholesterol level was lower in timed HF group and this diet could prevent and delay the development of insulin resistance.
In ad libitum high fat mice, Clock and Per1 expression in the liver were phase advanced and Cry1 and Rorα were phase delayed, whereas in timed HF mice, the phase of Clock and Per1 were restored and the other genes were phase advanced [72].
3.6.2.2. Evidence of connections between obesity and circadian clock in humans
In humans, the relationship between obesity and disruption of circadian rhythm has emerged in 1950’s. Stunkard et al reported that night-eating syndrome was related to the pathology of obesity and life stress [73]. The link between obesity and molecular clock became evident with studies demonstrating the circadian pattern in circulating serum of enzyme (i.e lipoprotein lipase) and adipokines (adiponectin, leptin) implied in lipid metabolism [74-77].
mRNA expression of clock genes (BMAL1, CRY1/2 and PER2) in peripheral blood mononuclear cells of obese patients was higher than in healthy subjects, whereas Glucose level was not different around the clock between these two groups [78].
The study of single-nucleotide-polymorphism (SNP) showed that overweight women with SNP in the CLOCK gene locus (3111T/C) had disturbed circadian rhythm and altered sleep [79]. It was also demonstrated that overweight or obese patients displaying this SNP had more
36 difficulties to lose weight and presented higher plasma ghrelin concentration as well as alterations of eating behaviour [80].
REV-ERBα became a new lead to follow in the understanding of obesity mechanisms.
Indeed, two studies have established a relationship between SNP of REV-ERBα and obesity in two independent populations (Mediterranean and North American) [81,82]. In obese women with metabolic syndrome, the expression of REV-ERBα in adipocytes was positively correlated with waist circumference and Body Mass Index (BMI) [83]. Therefore, REV-ERBα plays an important role in the pathology of obesity and metabolic syndrome.
3.6.3. Role of the circadian clock in the pathology of Type 2 diabetes (T2D)
In physiological conditions, food-induced hyperglycemia induces insulin secretion by beta cells via the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) pathway, leading to increased glucose uptake by skeletal muscle and adipose tissues, and to a reduction in hepatic glucose production. In case of hypoglycemia, glucagon is secreted to increase glycemia level by stimulating liver neoglucogenesis and glycogenolysis through the protein kinase A pathway (PKA) [84,85]. In case of T2D, the chronic exposure to glucose combined with sedentary life style alters beta cell function and reduced insulin sensitivity. This leads to impaired insulin secretion and consequently hyperglycemia, a hallmark of T2D [86].
3.6.3.1. Mice studies on the connection between T2D and clock
The existence of an autonomous molecular clock in the endocrine pancreas was described in mouse and rat pancreas [87,88] but also in mouse islets [89] and in pancreatic cell lines like MIN6, INS-1 and αTC1-9 cells [90-92].
The essential study that highlighted the relationship between clock disruption and T2D in mouse model came out in 2010 by Joseph Bass and colleagues [89]. The researchers have
37 found that ClockΔ19/ Δ19 mutant mice had defect in islet proliferation and reduced islet size and function, resulting in reduced insulin release. Moreover, specific Bmal1-knockout mice in the pancreatic islet displayed impaired glucose tolerance, insulin secretion, and additional features of T2D phenotype [89]. These observations were confirmed in pancreas explants and beta cells in 2011 by Sadacca et al. They showed that Bmal1 pancreas-specific knock-out mice exhibited glucose intolerance and impairment of insulin production. Isolated islets from these mutant mice had normal insulin content but defect in glucose-stimulated insulin secretion [93]. The exocytosis of insulin granules was blocked in beta cells of these mice [94,95].
Supporting this idea, Shi and al demonstrated in 2013 that wild type mice showed a circadian rhythm of insulin action with a more pronounced insulin resistance at Zeitgeber Time (ZT) 7.
The Bmal1-knockout mice were insensitive to insulin and the circadian phase of insulin action and glucose metabolism was comparable to the inactive daily cycle of WT mice [96]. Insulin resistance induced by HFD was associated with the disruption of the circadian expression of clock and lipogenic genes in mice liver [97]. Liu and al recently showed that CLOCK and BMAL1 activate SIRT1 to improve muscle insulin sensitivity in mice [98].
The implication of REV-ERBα in glucose homeostasis has been recently demonstrated.
Knockdown of Rev-erbα in alpha cells inhibited low-glucose induced glucagon secretion while agonist of Rev-erbα increased glucagon secretion. The effect on glucagon secretion was mediated by the AMPK/Nampt/SIRT1 pathway since inhibition of Nampt decreased Sirt1, Pgc1 and Rev-erbα expression [92]. In mouse pancreatic islets, inhibition of Rev-erbα impaired glucose-induced insulin secretion and beta cell proliferation [91]. In mouse white adipose tissue, Rev-erbα modulates the activity of FGF21 by binding to its co-receptor βKlotho [99]. FGF21 is known to increase insulin sensitivity and to prevent hepatitis steatosis [100].
38 Cryptochrome proteins were also related to glucose metabolism. Over-expression of Cry1 in liver of diabetic mice (db/db) improved insulin tolerance and decreased glycemia [101]. In addition, Cry1 and Cry2 inhibited C-AMP response element-binding protein (CREBP) phosphorylation by blocking G protein-coupled receptor (GPCR)-mediated increase in cAMP signaling during fasting in the liver. This resulted in the inhibition of gluconeogenesis, therefore a decrease in glycemia [101].
The connection between circadian clock and glucose metabolism is reciprocal. As stated above, functional circadian clock is indispensable for regulating glucose metabolism. On the other hand, the concentration of glucose is feeding back on the clock machinery. For instance, the effect of glucose concentration on the modulation of the clock machinery was described by Li and al in 2013. The expression of BMAL1 in U2OS cells was higher when the cells were subjected to a high concentration of glucose (25 mM) compared to the cells submitted to a low glucose concentration (5 mM). The authors demonstrated that the hexosamine / O- GlcNAc pathway modulated the circadian clock since OGT over-expression modified the phase of BMAL1 and CLOCK expression. The manipulation of hepatic OGT expression in mice resulted in aberrant rhythm of glucose homeostasis [55].
Metformin is an oral anti-diabetic drug commonly used to treat T2D patients, and is a modulator of the molecular clock. In mice, metformin has been shown to advance the phases of Clock, Bmal1 and Rorα in the liver by activating the AMPK pathway [102].
3.6.3.2. Explorations in humans
In humans, the impact of sleep-deprivation on metabolic dysregulations has been clearly established. Shift-working accelerates the development of metabolic syndrome and increases the risk of cardiovascular diseases [103-105]. A large population-based study including men and women shift workers demonstrated that men shift-workers had higher BMI and waist
39 circumference whereas women shift-workers increased their glycemia and HbA1c levels [106]. Long term shift-working has also been associated with increased risk of breast cancer, and its morbidity [107,108].
It prompted the researchers to take a close look at possible interactions between the circadian clock and the metabolism in humans.
The analysis of SNP from core clock genes and CCGs revealed a strong correlation between NPAS2 (Neuronal Clock) and hypertension, and PER2 was associated with high fasting glycemia [109]. In T2D patients, a Clock SNP was associated with an increased risk of stroke, suggesting a contribution of clock genes into cardiovascular risk in T2D patients [110].The existence of cell-autonomous circadian oscillator in human islets has been demonstrated for whole pancreatic islets and dispersed islet cells. Indeed, clock transcript expressions were following circadian pattern in human pancreatic islets and dispersed cells synchronized in vitro [111]. Furthermore, it has been shown that functional clock is indispensable for proper insulin secretion by human beta cells [112].
With respect to connection between circadian clock and T2D, the expression levels of PER2, PER3 and CRY2 transcripts in human islets isolated from T2D donors were lower if compared to healthy counterparts [113]. Of note, the mRNA levels of these genes were positively correlated to the insulin content, while PER3 and CRY2 transcript levels were negatively correlated with glycated hemoglobin level (HbA1c). In line with these findings, the mRNA expression levels of BMAL1, PER1 and PER3 were lower in leucocytes of T2D patients.
Moreover, HbA1c levels were inversely correlated with transcript expression in the same subjects [114].
The following study by Pivovarova and colleagues has established a clear relation between dietary change and clock machinery. The researchers induced a switch of diet in healthy
40 subjects from 6-weeks high carbohydrates-low fat diet to 6-weeks low carbohydrate-high fat diet. After the switch, the oscillations of period genes in monocytes of the subjects were altered, as well as the genes involved in inflammation and fat metabolism [115]. The same group studied the relationship of weight loss and gene expression in subcutaneous adipose tissue applying similar experimental design. Increase of PER2 and NR1D1 expression has been detected following the weight loss. Moreover, a correlation between the expression levels of core clock genes and those implied in fat metabolism, autophagy and inflammation has been reported [116].
To conclude, there is a reciprocal connection between circadian clock and metabolism.
Mutations of clock genes might have a negative impact on glucose and lipid metabolism, but the reverse might be also true. Diet enriched with fat and carbohydrates altered the cellular clock and a change of diet influence the expression of clock genes.
3.7. Study of circadian rhythm in humans
3.7.1. Chronotype: definition and approaches for human chronotype assessement
The internal clock modulates the day/night cycle. The timing of sleep and wakefulness is a pertinent way to study the circadian rhythm in humans at a behavioural level. The term
“chronotype” refers to the phase of entrainment specific to each person [117]. For example, an early chronotype subject would go to bed and wake up earlier than the average population.
These “early” subjects would be more productive on morning and have difficulties to stay awake at night. On the contrary, the “late chronotype” persons would go to bed and wake up later than the majority of people and are more productive during the evening.
41 To assess the chronotype of a subject, two questionnaires have been developed. The first one was described in 1976 by Horne and Ostberg and was called the “morningness - eveningness questionnaire”. The questions were related to the sleep length and sleep habits [118]. The second questionnaire is the Munich chronotype questionnaire (MCTQ) and was developed in 2003 by Till Roenneberg and colleagues [119]. The MCTQ integrated questions about timing of sleep during the work days and the free days, as well as the consumption of stimulants, caffeine, tea, and cigarettes. The exposure time to sunlight and the duration of transport from home to work were recorded (Appendix A). The analysis of the chronotype using the MCTQ required calculating the mid-sleep on free days (MSF). The MSFsc corresponds to the MSF corrected for sleep-debt accumulated during the work days that are caught up on the free days.
Early chronotype corresponds to MSF-sc ≤ 2.17, the MSF-sc for normal chronotype is between 2.17 and 7.25, and MSF-sc for late chronotype is superior to 7.25.
3.7.2. Analysis of melatonin secretion
The melatonin is a hormone secreted by the pineal gland and the retina in a strongly circadian manner. Its plasma concentration is the highest at night (80-100 pg/ml) and the lowest during the day (10-20 pg/ml). Melatonin is a Zeitgeber since its effects modulate the circadian rhythm through its receptors in the SCN [120]. In mammals, Mtnr1a gene encodes MT1 receptor and Mtnr1b gene encodes MT2 receptor.
The ability of melatonin to synchronize the clock has been used in pharmacology in order to treat insomnia and moderate jet lag [121,122]. Several studies have suggested a role of melatonin in the T2D. Melatonin receptors have been identified in beta cells, with the signal transduction implying the PKA pathway resulting in decrease of insulin secretion [123]. The presence of variant of the melatonin receptor 2 gene MTNR1B was associated with reduced
42 insulin secretion, altered glucose homeostasis, and thus higher risk of T2D development [124,125].
3.7.3. Molecular clock assessment in different human cell types
Exploring molecular clock in human peripheral organs represents a very non-trivial technical challenge due to the obvious reasons [126].
The use of blood cells could assess the human physiological clock. Determining human internal body time could provide breakthroughs in the field of chronopharmacology, since it’s crucial to administrate a medication at a proper time to enhance its efficiency. Minami et al have developed a new method to evaluate internal body time using different mass- spectrometry: gas chromatography mass spectrometry, liquid chromatography mass spectrometry and capillary electrophoresis mass spectrometry in mice. By combining these three methods, they were able to establish a molecular timetable based on blood metabolome analysis [127]. The same group applied this method to human blood sample analyses to estimate the internal body time and the delay caused by enforced sleep-wake cycle of each individual. The oscillating metabolites were identified [128]. Human transcriptome has been performed under forced-desynchrony protocol by Archer et al. They found that central clock remained rhythmic while blood peripheral transcriptome became arrhythmic [129].
In 1998, Balsalobre et al established that cultured rat fibroblasts possessed an internal clock that could be assessed in cells following in vitro synchronization by high concentration of horse serum [130]. E. Nagoshi et al demonstrated that NIH3T3 fibroblasts had a self- sustained and cell-autonomous circadian rhythm and could be synchronized by adding serum [131].
The use of fibroblasts from humans then appeared as an easy model to assess peripheral circadian rhythm.
