Dysfunction of rat INS-1E pancreatic ß-cells induced by chronic high glucose stimuli

Thesis

Reference

Dysfunction of rat INS-1E pancreatic ß-cells induced by chronic high glucose stimuli

SCHVARTZ, Domitille

Abstract

Type 2 diabetes is a metabolic disorder characterized by a defect in insulin secretion and a decrease of peripheral insulin sensitivity. Glucotoxicity, the detrimental effect of glucose, is involved in this disease progression, and has been shown to exert deleterious effects on various organs and cells, notably leading to impairment of insulin secretion by pancreatic β-cells. Mechanisms of glucose-induced β-cell failure are not entirely described and are fundamental to figure out how β-cells respond to increased glucose stimulation and finally undergo apoptosis. Therefore, the overall goal of this study was to monitor the early molecular mechanisms underlying β-cell dysfunction in conditions of chronic high glucose exposition.

SCHVARTZ, Domitille. Dysfunction of rat INS-1E pancreatic ß-cells induced by chronic high glucose stimuli. Thèse de doctorat : Univ. Genève, 2012, no. Sc. 4446

URN : urn:nbn:ch:unige-258576

DOI : 10.13097/archive-ouverte/unige:25857

Available at:

http://archive-ouverte.unige.ch/unige:25857

Disclaimer: layout of this document may differ from the published version.

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Dysfunction of rat INS-1E pancreatic β-cells induced by chronic high glucose stimuli

THÈSE

présentée à la Faculté des sciences de l'Université de Genève pour obtenir le grade de Docteur ès sciences, mention biologie

par

Domitille S CHVARTZ

Reims (FRANCE)

Thèse n°4446

Genève 2012 Humaines

Biomedical Proteomics Research Group

F

S

Dysfunction of rat INS-1E pancreatic β-cells induced by chronic high glucose stimuli

THÈSE

présentée à la Faculté des sciences de l'Université de Genève pour obtenir le grade de Docteur ès sciences, mention biologie

par

Domitille S CHVARTZ

Reims (FRANCE)

Thèse n°4446

Genève 2012 Humaines

Biomedical Proteomics Research Group Humaines

Biomedical Proteomics Research Group

F

S

Je souhaite adresser mes remerciements à toutes les personnes qui m’ont soutenue et encouragée pendant ces années de thèse, et qui m’ont apportée de l’aide, chacune à leur façon.

En particulier, je remercie :

Jean-Charles Sanchez, pour ton soutien, ton écoute et ta disponibilité. Ton enthousiasme est un moteur et tu as su me donner la motivation nécessaire pour aller toujours plus loin et me dépasser. Tu as rendu mes 4 ans et demi de thèse au BPRG très agréables, grâce à ta bonne humeur et ton entrain quotidien. Je garde de très bons souvenirs des discussions scientifiques, comme des sorties de groupe, et des congrès (avec un goût particulier pour mon premier congrès de Sienne!).

Robbie Loewith, Manfredo Quadroni et Romano Regazzi, qui ont accepté de constituer mon jury de thèse, respectivement en tant que répondant à la faculté des Sciences et experts externes à l’Université de Genève.

Yohann Couté et Yannick Brunner, mes « grands-frères » de la cellule bêta. Merci les garçons de m’avoir mise sur les rails du projet, et d’avoir continué à me donner des coups de pouce quand c’était nécessaire.

Natalia pour ton soutien. Nos nombreuses pauses café m’ont permis de décrocher dans nos journées de fous. Merci de m’avoir écoutée et soutenue toutes ces années, et d’avoir partagé tant de bons (et de mauvais) moments avec moi. On gardera de très bons souvenirs des congrès partagés ensemble! Stockholm, Estoril, la SPS et surtout HuPO ! Merci pour les retours en voiture à Ambilly !

Vanessa qui a fait ses premiers pas au BPRG en même temps que moi. Merci pour ton support, et pour ton aide. J’adore cohabiter avec toi au 9028 depuis 5 ans maintenant, ce qui nous a permis de lier une belle amitié. On a beaucoup partagé, personnellement et professionnellement, et j’espère que cela va continuer encore longtemps ! Merci aussi pour les retours en voiture !

L’équipe de « thésards & Co ! ». Merci à Xavier, Didia, Anne, Virginie, Francesco, HuiSong, Florent et Natalia (+ Vanessa et Alex ?!!) pour l’ambiance de groupe, et pour les soirées passées ensemble. De très beaux fous-rires, et des chouettes moments ! Merci pour vos

encouragements, votre aide et votre soutien. Je garde un souvenir particulier de notre week-end à Londres, un grand moment dans notre vie de thésards ! Merci aux habitants du 9028 d’avoir supporté mes craquages de fin de journée (bon, d’accord…parfois de début et de milieu de journée !). Merci à Didia de nous nourrir, et pour toutes tes petites histoires de pharmacienne ! Merci à Anne pour nos grandes discussions scientifiques, et pour le partage de nos aventures (et mésaventures) de granules ! Un merci spécial à Alex pour tes conseils éclairés et judicieux sur mon avenir… et ne t’en fais pas, je ne lâche pas !

Tous les membres du BPRG pour votre aide et votre sympathie. Merci pour les conversations scientifiques, les petits tuyaux mais aussi toutes les petites discussions de couloir qui rendent les journées agréables. Un merci particulier à Paola, pour ton écoute et ta gentillesse.

Marielle pour ton sourire et ta bonne humeur. Merci d’être là pour nous au quotidien, merci pour toutes les petites attentions que tu as pour moi.

Fanny et Vincent (et la petite Margot) qui veillent sur moi. Merci ma choupinette pour tes mails quasi-quotidiens et pour nos « repas de choups », qui m’ont aidée à avancer. Merci à vous deux d’être toujours là pour moi, quoi qu’il arrive. Merci pour votre amitié.

Caro, Aurélie, Sophie, Jean, Vex, et toute la bande de Lille-Paris. Soirée au calme, cinéma, WE à la vignette, au ski, ou à Paris m’ont aidée à décompresser, et m’ont permis de revivre pour quelques heures nos folles années d’étude !

Brice, pour tes textos plein d’humour, et qui me font oublier qu’on est loin.

Je remercie surtout mes frères et sœurs, ainsi que leurs « pièces rapportées ». Merci Thibault &

Pauline, Ségolène & Philippe, et Romary & Emmeline de m’avoir épaulée, d’avoir cru en moi, et de m’avoir soutenue chacun à votre façon. Mes retours à Reims, nos WE à Montpellier, ou les vacances en famille étaient des coupures plus que nécessaires pour continuer et persévérer dans mon travail de thèse. Vous êtes au top ! Merci Ségo pour tous tes appels, tes mails et tes textos qui me rapprochent de toi.

Timéo, Arthur, Elina, Anaëlle, et Laélie pour leurs rires, leurs grains de folie, et leur insouciance ! Les parties de carte, de cache-cache, et les vacances tous ensemble sont des purs moments de bonheur!

Merci à ma super Mamie, toujours à l’écoute. Merci pour tes appels, et merci de réunir toute la famille de temps en temps.

Un grand merci à mes parents, qui croient en moi. Merci de m’avoir permis d’avancer, de me valoriser et d’être fiers de moi. Merci pour tout l’amour que vous me donnez. Vous avez rendu mes WE à Reims très réconfortants, dans mon petit cocon familial !

Je remercie finalement Romain, mon mari et mon plus grand support. Merci pour ton aide scientifique, pour nos discussions SILAC, pour ton regard critique. Mais surtout merci pour ton immense soutien au quotidien et pour tout ce que tu m’apportes. Merci de croire en moi et de m’écouter. Merci pour ton amour.

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Abstract ... p. 17 Résumé ... p. 19 Chapter I : Introduction ... p. 21 I. Glucose Homeostasis ... p. 23 I.1. Generalities ... p. 23 I.2. Glucagon and Insulin... p. 23 I.3. Mechanisms of insulin release ... p. 25 II. Diabetes Mellitus ... p. 26

II.1. Disease generalities ... p. 26 II.2. Type 1 diabetes ... p. 27 II.3. Type 2 diabetes ... p. 27 III. β-cell dysfunction in type II diabetes ... p. 28

III.1. Impairment of insulin secretion ... p. 29 III.2. Glucotoxicity and β-cells ... p. 29 IV. Insulin Secretory Granules ... p. 31

IV.1. Biogenesis of insulin secretory granules ... p. 32 IV.2. ISGs exocytosis ... p. 34 IV.3. ISG proteome ... p. 35 V. Organellar proteomics ... p. 37

V.1. Introduction to organellar proteomics ... p. 37 V.2. Subcellular fractionation methods ... p. 37 V.2.a. Gradients ... p. 37 V.2.b. Immunoaffinity purification ... p. 39 V.2.c. Free flow electrophoresis ... p. 40 V.3. Combination with proteomics tools ... p. 40 V.3.a. Subtractive approach ... p. 40 V.3.b. LOPIT ... p. 41 V.3.c. PCP ... p. 41 V.4. The help of bioinformatics... p. 42 V.5. Verification ... p. 43 VI. Research plan and objectives ... p. 44 References ... p. 47

Chapter II: Glucotoxicity and pancreatic proteomics ... p. 53

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Chapter III: Proteomics of regulated secretory organelles ... p. 71 Chapter IV: Improved characterization of the insulin secretory granule proteomes

... p. 97 Chapter V: Early activation of the fatty acid metabolism pathway by chronic high glucose exposure in rat insulin secretory β-cells ... p. 111 Chapter VI: Modulation if the Neuronal Pentraxin 1 expression in rat pancreatic β-cells submitted to chronic glucotoxic stress ... …..p. 127 Chapter VII: High glucose exposure on INS-1E pancreatic β-cells induces the

overexpression of the MCM2-7 protein complex in the nucleus ... p.141 Chapter VIII: Discussion and perspectives ... p. 161

I. Unravelling ISGs proteomes ... p. 163 II. From compensation to dysfunction ... p. 165 II.1. Glucose induces β-cells proliferation ... p. 165 II.2. Chronic hyperglycemia leads to β-cells dysfunction and apoptosis ... p. 167 III. Perspectives ... p. 171

III.1. Functional analysis of NP1 ... p. 172 III.2. Integrative analysis ... p. 172 III.3. Post-translational modifications ... p. 173 III.4. Study of lipotoxicity on β-cells ... p. 174 Conclusions ... p. 177

15 2-DE: Two-Dimensional gel Electrophoresis Adarb1: Double-stranded RNA-specific editase 1

ADP: Adénosine Diphosphate

AGE: Advanced Glycation Endproduct ATP: Adénosine Triphosphate

CDK: Cyclin Dependant Kinase

DAVID: Database for Annotation, Visualization and Integrated Discovery

ER: Endoplasmic Reticulum FASN: Fatty Acid Synthase FBS: Fetal Bovine Serum FDR: False Discovery Rate FFE: Free Flow Electrophoresis GDH: Glutamate dehydrogenase GLUT: Glucose Transporter

GPI: Glucose-6-Phosphate Isomerase GSK3: Glycogen Synthase Kinase 3 IAA: Iodoacetamide

IRS: Insulin Receptor Substrate ISG: Insulin Secretory Granule

iTRAQ: Isobaric Tag for Relative and Absolute Quantification

JNK: c-Jun N-terminal kinase

Kif20A: Kinesin Family Member 20A protein LOPIT: Localization of Organelle Proteins by Isotope Tagging

MCM: MiniChromosome Maintenance

MS: Mass Spectrometry NP1: Neuronal Pentraxin 1

NSF: N-ethylmaleimide-Sensitive Factor ORC: Origin Recognition Complex PBS: Phosphate buffered saline PC1/2: Prohormone Converstase ½ PCA: Principal Component Analysis PCNA: Proliferating Cell Nuclear Antigen PCP: Protein Correlation Profiling

Pdx1: Pancreatic and duodenal homeobox 1 PTM: Post-translational Modifications ROS: Reactive Oxygen Species

RRP: Readily Releasable Pool

SDS-PAGE: Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis

SILAC: Stable Isotope Labeling with Amino acids in Cell culture

SNAP: Soluble NSF Attachment Protein

SNARE: Soluble NSF attachment protein receptors

STRING: Search Tool for the Retrieval of Interacting Genes

T1D: Type 1 Diabetes T2D: Type 1 Diabetes TGN: Trans Golgi Network Txnrd1: Thioredoxin Reductase 1

VAMP: Vesicle associated membrane protein WHO: World Health Organization

17

Type 2 diabetes is a metabolic disorder characterized by a defect in insulin secretion and a decrease of peripheral insulin sensitivity. Glucotoxicity, the detrimental effect of glucose, is involved in this disease progression, and has been shown to exert deleterious effects on various organs and cells, notably leading to impairment of insulin secretion by pancreatic β-cells.

Mechanisms of glucose-induced β-cell failure are not entirely described and are fundamental to figure out how β-cells respond to increased glucose stimulation and finally undergo apoptosis.

Therefore, the overall goal of this study was to monitor the early molecular mechanisms underlying β-cell dysfunction in conditions of chronic high glucose exposition.

The first study we conducted was focused on the Insulin secretory granule (ISG) proteome. ISGs are β-cell vesicles dedicated to insulin processing, storage and release. It is hence essential to decipher the ISG proteome and its maturation during granule biogenesis to fully understand insulin secretion processes, and better apprehend the associated defects in type 2 diabetes pathology. Sub-cellular fractionation combined to proteomics allowed establishing 3 groups of ISG-associated proteins. These enhanced our knowledge of ISG biogenesis, maturation and exocytosis. We mainly centered our interest on ProSAAS, a protein highly enriched in mature ISGs and described for the first time in ISGs.

In a second part, we monitored glucotoxicity consequences on β-cells, at different levels. We used a quantitative proteomic strategy to find various proteins, which expressions were affected by long term glucose exposure in total cell, ISGs and nuclei. Several results were verified at the cellular level in these 3 different studies, and highlighted proliferation and apoptotic pathways, which were modified when cells are submitted to glucotoxic conditions.

19

d’insuline par les cellules-β, ainsi que par une résistance périphérique à l’insuline. La glucotoxicité désigne les effets négatifs induits par le glucose. Elle est impliquée dans la progression de la maladie, et provoque des effets délétères sur différents organes et cellules, notamment en générant un défaut de sécrétion de l’insuline par les cellules-β. Les mécanismes induisant la défaillance de la cellule-β par le glucose ne sont pas entièrement connus, et sont pourtant essentiels pour comprendre comment la cellule-β répond à la stimulation au glucose, menant finalement à l’apoptose. C’est pourquoi, le but général de cette étude est de suivre les mécanismes moléculaires précoces qui génèrent un dysfonctionnement de la cellule-β lorsqu’elle est confrontée à une exposition chronique de hautes concentrations de glucose.

La première étude que nous avons donc menée était centrée sur le protéome des granules sécrétrices d’insuline (GSI). Les GSI sont des vésicules de la cellule-β qui sont dédiées à la production de l’insuline ainsi qu’à son stockage et à sa sécrétion. Il est donc essentiel de connaitre le protéome de ces granules, ainsi que son évolution pendant la biogenèse, dans le but de comprendre le processus de sécrétion de l’insuline. Cela permettrait aussi d’appréhender les défauts de sécrétion qui sont observés dans le cas du diabète de type 2. Nous avons combiné des techniques de sous-fractionnement cellulaire à des approches de protéomique, ce qui nous a permis de constituer 3 groupes de protéines qui sont associées aux GSIs. Ceci nous a permis d’améliorer notre connaissance sur la biogenèse, la maturation et l’exocytose des granules. Nous avons particulièrement travaillé sur la ProSAAS, une protéine qui est hautement enrichie dans les granules matures, et qui est décrite dans les GSIs pour la première fois.

Dans un deuxième temps, nous avons évalué les conséquences de la glucotoxicité sur la cellule- β, à différents niveaux. Nous avons utilisé une technique de protéomique quantitative dans le

20

but d’identifier des protéines dont les expressions seraient affectées par l’exposition au glucose.

Nous avons travaillé sur les cellules totales, mais aussi sur les noyaux et les GSIs. Plusieurs de nos protéines cibles ont été vérifiées au long de ces 3 études distinctes, et ceci nous a permis d’établir que des voies métaboliques telles que la prolifération et l’apoptose sont modifiées par l’exposition au glucose dans les cellules-β. Nous avons donc pu établir des hypothèses sur les mécanismes précoces qui engendrent le dysfonctionnement des cellules-β dans le cadre du diabète de type 2.

C HAPTER I

I NTRODUCTION

C HAPTER I

I NTRODUCTION

23 I.

G

I.1. Generalities

Glucose is an indispensable nutrient for tissues and cells, and especially for brain. Circulating blood glucose levels are tightly controlled in order to balance glycemia [1-3]. Several parameters lead to changes in blood glucose concentration such as stress, age, gestation, and nutritional state. Normal glycemic values are considered to be comprised between 0.63 and 1.1 g/L (3.5 to 6.1mmol/L). Maximum fasting glycemia value is 1.26 g/L (7mmol/L), corresponding to the proportion which does not cause glucose related-complications. Misbalance of blood glucose levels leads to either hypoglycemia or hyperglycemia, both causing deleterious effects if chronic [4-6].

This balance is mainly dependant of the endocrine pancreas, more specifically of the islets of Langerhans. These regions of the pancreas are composed of 4 distinct hormone producing cell types: Α-cells produce glucagon, β-cells synthesize insulin, delta-cells generate somatostatin and PP cells produce pancreatic polypeptides. Glucagon and insulin both have a crucial role in glucose homeostasis [7]. This event is actually regulated by three linked processes: glucose production in the liver, glucose uptake by peripheral tissues, and action of insulin and glucagon on glucose levels (figure 1) [2, 3].

I.2. Glucacon and insulin

Insulin and glucagon have opposite effects on glucose homeostasis. Glucagon is a 29 amino-acid peptidic hormone, secreted by α-cells of Langerhans islets. During fasting states, glucagon secretion first increases the conversion of glycogen into glucose through hepatic gluconeogenesis, and subsequently induces gluconeogenesis to generate the synthesis of

Chapter I

24

additional glucose molecules. To prevent hypoglycemia, glucagon also regulates lipolysis and decreases glycogen synthesis.

Following a meal, insulin is secreted by pancreatic β-cells in response to elevated blood glucose levels. It generates glucose uptake in tissues, as well as an increase of glycogen synthesis in liver and an increase of lipid synthesis in adipose tissues (Figure 1). A detailed review of glucose homeostasis is depicted in chapter 2 of this manuscript.

Figure 1: Role of the pancreas in glucose homeostasis processes.

In β-cells, insulin is synthesized in the rough endoplasmic reticulum as pre-proinsulin, the 110 amino-acid translation product of the insulin gene. The protease cleavage of the signal peptide from preproinsulin gives rise to proinsulin, which is in turn incorporated into the Golgi apparatus and later in insulin secretory granules [8, 9]. Proinsulin is processed into insulin during granule maturation through the cytoplasm, by the action of two proteolytic enzymes and one exoprotease removing the C-peptide: the prohormone convertase-1, prohormone convertase-2, and carboxypeptidase E [10]. The remaining 51 amino-acid polypeptide is the result of the covalent binding of A and B chains by disulfide bounds [11].

25 I.3. Mechanisms of insulin release

As described above, β-cells release insulin upon glucose stimulation. Glucose uptake by β-cells is performed via the glucose transporter GLUT2, present at the surface of the cell. Glucose metabolism generates ATP, leading to an increase of ATP/ADP intracellular ratios. It inactivates the ATP-sensitive membrane K⁺ channel, inducing cell membrane depolarization. A consequent extracellular calcium influx through voltage-dependant Ca²⁺ channels induces the release of insulin from insulin secretory granules. Insulin secretion could also be stimulated by other molecules such as leucine or arginine (Figure 2) [12-14].

Figure 2: Mechanism of glucose-induced insulin secretion [15].

Under physiological conditions, glucose uptake causes a biphasic secretion of insulin. During the first minutes, insulin is rapidly secreted, reaching a peak in 5 to 7 minutes. It was estimated that 2-3% of β-cell insulin content is released during this period. This phase is followed by a lower secretion phase lasting several hours, during which approximatively 20% of insulin content is released. Insulin secretion returns to its basal level when there is no more stimuli [16-18].

Chapter I

26

Glucose homeostasis is an essential phenomenon mainly controlled by pancreatic β-cells and α- cells. The disturbance of the glucose balance is associated with diabetes pathologies, where the body has the inability to counteract increased blood glucose levels. It leads to chronic hyperglycemia, which induces cellular defects at many levels.

II.

D

II.1. Disease generalities

Although the first medical description of diabetes pathology arises from the year 120 of the Common Era by the greek physician Aretaeus of Cappodocia, several centuries were necessary to figure out the main dysfunctions associated to this pathology. Notably, the discovery of pancreatic islets of Langerhans in 1869 by Paul Langerhans, followed by their connection in 1901 to the occurrence of diabetes, represented a key progress in the field. Later, insulin was discovered (1920) from dog pancreatic extracts, and extended the general knowledge on diabetes [19-21].

Diabetes mellitus is a group of progressive metabolic diseases characterized by a default of glucose homeostasis, leading to an excessive amount of blood glucose, named hyperglycemia.

The frequency of diabetes occurrence increases worldwide, especially in developing countries.

This increase is linked to excess weight, obesity and sedentarity [22]. The World Health Organization (WHO) estimates that 346 millions of people are diabetic in the world. According to their evaluation, diabetes could become the 7^th death cause by 2030, mostly due to associated long-term complications [23]. Diabetes increases the risk of cardiopathies, strokes, neuropathies leading to member amputations, diabetic retinopathies caused by multiple lesions on blood vessels, as well as kidney failure. It exists several forms of diabetes mellitus, but the two main forms are Type I Diabetes (T1D) and Type 2 Diabetes (T2D).

27 II.2. Type 1 Diabetes

Type 1 Diabetes (T1D) is caused by an absolute deficiency of insulin following an auto-immune destruction of pancreatic β-cells [24]. This form of the disease counts for approximately 10% of diabetic cases. It concerns mainly children and young adults (< 30 years old), who have normal weight. The onset of the disease is sudden, and symptoms comprise increased thirst, frequent urination, fatigue and weight loss.

There is a production of auto-antibodies, mediating selective β-cell destruction through T-cells [25]. Actually, histological examination of endocrine pancreas at the clinical onset of T1D shows a drastic decrease of β-cells, as well as an infiltration of T-lymphocytes, B-lymphocytes and macrophages. It corresponds to the auto-immune reaction against distinct antigens expressed by β-cells. There is obviously a genetic predisposition to T1D, but also associated to environmental factors. Evidences were brought to demonstrate that viruses, but also nutrition, may have an important role in the development of T1D [26]. Β-cell destruction progressively leads to the lack of insulin and therefore a permanent glycemia increase.

II.3. Type 2 Diabetes

Type 2 Diabetes (T2D) represents 80-90% of all diabetes cases [6]. Its prevalence increases and is now between 2 and 5% in Europe (more than 5% in USA). This form of the disease usually affects people above 40 years old, and children with severe obesity. T2D results of two main factors: a genetic predisposition and environmental factors. The transmission mode of the disease is still misunderstood. It is apparently polygenic, leading to insulin production and/or action alteration. The nutritional unbalance and weight excess, which are environmental factors, are also associated to the pathology [27, 28]. There is actually a strict link between excess weight and T2D, as 2/3 of patients are obese. Also, 80% of patients display a distinct phenotype, named metabolic syndrome. This syndrome appears to be present upstream of T2D and

Chapter I

28

encompasses the following criteria: abnormally elevated insulin rate, hypercholesterolemia, high blood pressure, weigh excess, hyperglycemia. The onset of diabetes following the metabolic syndrome is characterized by symptoms such as frequent urination, increased thirst, increased hunger, and weight loss leading to chronic complications [29, 30].

T2D patients have fasting glycemic values above 1.26g/L (7mmol/L) due to the default of insulin secretion combined to the insulin resistance of the peripheric tissues, leading to a default in hyperglycemia prevention. The chronic increase of glycemia is the major hallmark of T2D, however it is still debated whether hyperglycemia is a cause of a consequence of the observed defects of T2D [31-33]. It is more likely that these mechanisms function as a vicious circle, each of them worsening the others.

In summary, T2D is a progressive disease due to the unbalance of glucose homeostasis. It leads to chronic hyperglycemia, which in turn induces many defects on the organism. Notably, β-cells are affected by chonic hypeglycemia, which cause β-cell failure at several levels.

III.

β-

II

Although insulin resistance is a fundamental dysfunction in T2D, it is known that it is not sufficient to induce the pathology. Β-cell dysfunction is a very important process in the development of the disease. Both defects are known to increase hyperglycemia, and therefore glucotoxicity [34], causing complications at many levels. Β-cell dysfunction is linked with T2D and its evolution, through several mechanisms. Defaults in insulin secretion are for instance described in T2D, and therefore induce a progressive increase of glycemia, avoiding β-cell to overcome insulin resistance of peripheric tissues. The second concern about β-cells in T2D affects its mass, which is highly decreased in patient pancreas [35-37]. This decrease in β-cell

29

mass is due to a combined effect of the increase of apoptosis with a decrease of replication and neogenesis. β-cell failure is multifactorial, involving many distinct pathways, acting indirectly or directly in concert on insulin secretion and apoptosis.

III.1. Impairment of insulin secretion

Chronic glucose stimulation leads to a decrease of insulin release from β-cells [38, 39]. Insulin secretion is actually implicated at two different levels in β-cell dysfunction: a quantitative and a qualitative failure in insulin release. Firstly, it is known that the first phase of insulin secretion after a glucose stimulation is reduced by glucotoxicity or is even nonexistent [40]. This functional default could be supplemented with a delayed response, and along time, with a reduced insulin release during the second phase. The loss of correct functioning in the biphasic mechanisms of insulin secretion in response to glucose stimulation is determinant for the development and the worsening of the pathology. These defaults are also related to other disruptions. It was pointed out that T2D is associated with default of insulin conversion. In normal conditions, about 2% of proinsulin is release with insulin, resulting from non-cleavage during granule maturation. In diabetic patients, a 4-5 fold increase of proinsulin release was described [6, 41]. Lastly, Machetti et al. [42] shown that there is also a decreased number of mature insulin secretory granules from human β-cells carrying a T2D-related polymorphism, suggesting a default in granule biogenesis.

III.2. Glucotoxicity and β-cells

Chronic hyperglycemia, caused by distinct defaults, exerts with time toxic effects on peripheric tissues, but also on pancreatic β-cells. The toxic effect of glucose, glucotoxicity, is one of the major cause of β-cell dysfunction and apoptosis observed in T2D. Apoptosis leads with time to a decrease of β-cell mass, a phenomenon which is known to contribute to the development of the

Chapter I

30

disease [43-45]. It was described that in normal conditions, only 0.5% of β-cells undergoes apoptosis. This rate is 10 times higher in diabetic patients. Several mechanisms are regulating β- cell mass, such as apoptosis, hyper- and hypoplasia, replication and neogenesis [46-49]. Under normal conditions, β-cell is able to adapt its mass to changes in metabolism. It is known that an increased glucose demand induces β-cell proliferation [50-52], in order to compensate the need in insulin. The regulation of β-cell mass is performed through the balance of cell cycle proteins [47, 53, 54]. Despite the ability of β-cells to redress the need in insulin by increasing its mass, it is known that a chronic increase of glucose stimulation leads, finally, to β-cell dysfunction and apoptosis. Kloppel et al. described that there is a 25-50% reduction of β-cell mass in T2D pancreas, suggesting that it happens at the onset of the disease [55].

Studies on glucotoxicity and β-cells described that several mechanisms are involved in glucose- induced cellular dysfunction, such as ER stress, glycations, and oxidative stress [56, 57]. Indeed, oxidative stress has a central role in β-cell dysfunction, and ROS species are common to various pathways leading to cell dysfunction and/or apoptosis. Hyperglycemia induces ROS generation through mitochondrial dysfunction, glycations and glucose auto-oxidation, leading to the induction of the transcription factor NF-κB pathway [58-60], and to the default of secretion during the first phase of insulin release [61]. It was shown that the activation of NF-κB is an early event in glucotoxicity, mediating immune response and apoptosis. NF-κB role in β-cell dysfunction is well known [62]. Oxidative stress activates also JNK, p38 MAPK and protein kinase C. JNK is known to decrease IRS signaling in pancreatic β-cells, inducing a decrease of Pdx1 activity, which leads to a decrease of insulin gene transcription [63]. In addition to oxidative stress, chronic hyperglycemia also increases ER stress, through the activation of several characteristic proteins [64-67]. This induces an increased intracellular calcium level, leading to cell dysfunction and apoptosis [68, 69]. The various mechanisms of glucose-induced β-cell dysfunctions are complexes, and not fully elucidated.

31

New therapies targeting β-cells are therefore focused on the preservation of β-cell mass, by promoting cellular regeneration or decreasing apoptosis. Promising approaches are targeting the component of the insulin and IGF-1 receptor signaling pathway, such as IRS-2, to successfully induce β-cell proliferation [70]. In contrast, other groups are working on the possibility to decrease GSK3 activity aiming at the decrease of apoptotic processes [71].

In conclusion, β-cells are major actors in type 2 diabetes, therefore it is necessary to cover and understand mechanisms of β-cell dysfunction observed in the pathology. Glucose is the main responsible of β-cell failure, and glucotoxicity-related mechanisms need to be fully unraveled.

IV.

I

S

G

Insulin secretory granules (ISGs) are β-cell vesicles dedicated to insulin release. It was originally estimated that rat β-cells contain 11’000 ISGs per cell, and that each granule measures approximatively 350 nm, containing 2x10⁵ insulin molecules [72]. But a very recent article reported new findings about the description of these vesicles, and decreased these numbers to 5.000 ISGs/cell and a size of 250 nm [73]. They also consider that a single ISG is carrying 4-5x10⁵ insulin molecules. Insulin is the main component of ISGs, and corresponds to 50-60% of the total granule proteins (figure 3) [74]. Granule content is released via exocytosis, either by constitutive or regulated secretion. The constitutive secretion is considered as “the default route” for secreted proteins. These constitutive vesicles directly traffic from the TGN to the plasma membrane where they fused. This allows the renewing of membrane phospholipids, as well as a rapid movement of proteins between the TGN and the plasma membrane [75, 76]. This is the case for insulin, which is constitutively secreted by β-cells to maintain a basal level of insulin secretion. Ninety-nine percent of endogenous insulin is actually released via a tightly regulated

Chapter I

32

pathway [9]. Regulated secretion is triggered by different stimuli, such as glucose, which is the main stimulator of granule exocytosis.

Figure 3: A/ Electron microscopy of a β-cell. B/ Schematic representation of the insulin secretory granule, with their main proteins [77].

IV.1. Biogenesis of insulin secretory granules

ISGs are dedicated to insulin packing and release under glucose stimulation. Insulin is a hormone, which is synthesized in the rough endoplasmic reticulum, as preproinsulin. The conversion of preproinsulin into insulin occurs rapidly, within seconds [8]. Proinsulin as well as other secretory proteins, has a signal sequence for secretion, and moves along the trans-golgi network, to be packed into budding ISGs. During the last decades, two mains models were debated to explain how secretory proteins are sorted into their dedicated vesicles. The first one is called “sorting for entry”. According to this model, the sorting of proteins happens at the TGN, through interactions with specific receptors. For instance, lysosomal proteins interact with the mannose-6-phosphate receptor, whereas secretory proteins bind specific receptors for their direct sorting into the dense core granules. Thus, the constitutive vesicles correspond to a random packing of proteins containing a secretion signal. The second hypothesis is named

33

“sorting by retention”. In this model, secretory proteins are all packed first in immature-clathrin coated granules, and the sorting happens along the process of maturation. Via interactions with receptors, or aggregation processes, proteins are progressively sorted into specific vesicles (figure 4) [78-80].

Figure 4: Hypotheses of protein sorting at the TGN. A/ Sorting for entry. B/ Sorting by retention [75].

This model seems to be the most plausible in the case of β-cells as it is well described now that the conversion of proinsulin into insulin occurs in immature granules, where all the conditions of pH are adapted, rather than in the TGN [9, 81]. Indeed, after immature ISGs budding at the TGN, granules undergo maturation. The maturation process comprises a progressive acidification of

Chapter I

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the granule lumen through ATP dependant proton pumps, allowing the proteolytic cleavage leading to the conversion of proinsulin into insulin, and finally the loss of the clathrin coat [82, 83]. At the end of the process, insulin molecules crystallized with zinc and calcium, and therefore form dense core granules. The transport of granules from the TGN to the plasma membrane occurs via the interaction of ISGs with microtubules, followed by the interaction with microfilament networks of the cytoskeleton, with the help of phosphorylations [84-86].

IV.2. ISGs exocytosis

Once ISG maturation is completed, glucose stimulation precedes insulin release from these specialized vesicles. ISGs are in fact divided into 2 groups, in charge of the biphasic insulin secretion:

The Readily Releasable Pool (RRP), corresponding to plasma membrane-associated ISGs, and the reserved pool. RPR is responsible of the first phase of insulin secretion and its exocytosis is calcium-dependant. The reserved pool is dedicated to the second phase of insulin secretion, and its exocytosis is ATP and calcium dependant. When necessary, ISGs have to be first recruited from the reserved pool and then starts the exocytosis process [87].

The exocytosis process takes place at the plasma membrane, and involves several steps. The two pre-fusion steps are the docking and ATP-dependant priming of the vesicles, allowing SNARE proteins to be organized [88, 89]. SNAREs are associating together to form the binding site for 2 factors, necessary for the fusion: NSF (N-ethylmaleimide-sensitive factor) and α-SNAP (soluble NSF-attachment factor) [90]. The complex for docking is also constituted of v-SNAREs (vesicule- SNARE), such as VAMP2 or cellubrevin, and t-SNARE (at the plasma membrane), such as SNAP-25 and syntaxin I (figure 5) [88, 91-93]. The mechanism of ISG fusion at the plasma membrane is highly debated. It actually exists 3 different fusion models. Some studies demonstrated that this event may occur as a total fusion of the granule membrane with the plasma membrane, allowing

35

the complete release of granule content as well as a mixing of both membranes [94, 95].

However, it appeared that fusion mechanisms more likely take place through a transient fusion pore that opens during exocytosis, followed by a release of granule content, a model named

“kiss and run” [96-99].

Figure 5: Mechanism of β-cell granule exocytosis [88].

IV.3. ISG proteome

Despite the efforts made to improve our knowledge on β-cell function and more specifically on ISGs, the precise molecular mechanisms leading to β-cell dysfunction are still debated. There are now evidences for a central role of insulin secretion and therefore ISGs in the development of the pathology. That is the reason why researchers tried to decipher the ISG proteome, to obtain some additional hints about their biogenesis and maturation, as well as information on secretion mechanisms. The first study was conducted in 1991, by Hutton and co-workers. They purified insulin granules from mammalian pancreatic islets using a Percoll density gradient. The 2-DE analysis allowed detecting more than 150 ISGs associated polypeptides [100]. Brunner and co- worker did the first mass spectometry analysis on ISGs purified from rat INS-1E cells, in 2007.

Chapter I

36

They prepared ISGs through a 2 step fractionation process, and analyzed their ISG-enriched fraction using a liquid chromatography separation followed by MALDI-TOF/TOF. They identified 130 proteins associated to ISGs. They pointed out that a large part of these proteins were secreted proteins, and suggested also that their results give prominence to the “sorting by retention” hypothesis, as they could identified hydrolases and lysosomal proteins in the pool.

They also confirmed the presence of Rab37 and Vamp8 [101]. In 2009, another group worked on the ISG proteome, using a different approach for its purification. Indeed, Hickey et al. described the use of density gradient centrifugation followed by immunoaffinity purification through magnetic beads to purify ISGs from INS-1E cells. They used VAMP2 as a protein specific for ISGs to perform their affinity purification. Once prepared, ISGs were analyzed by MS on a Q-TOF instrument. They could identify 51 ISG-related proteins, comprising well-known ISGs proteins.

However, they failed to detect docking proteins assuming that they remained attached to affinity beads [102].

Although these three proteomics-based studies allowed mapping the main ISG proteins, it was pointed up by Suckale et al. that these lists contain some co-purifying contaminants, such as mitochondria or lysosomes. Moreover, they underlined that these first studies are probably incomplete, as some major ISG proteins failed to be identified [77]. Therefore, the next challenge is to improve ISG enrichment techniques, in combination with novel proteomics approaches, to reach the next step in the ISG proteome coverage.

In summary, considering their essential role in insulin transport and secretion, ISGs are the central organelles of pancreatic β-cells. Although ISG-related knowledge is still incomplete, it is essential to perfectly understand ISG biogenesis, maturation and exocytosis mechanisms. It will bring fundamental evidences for the molecular comprehension of β-cell insulin secretion impairment in glucotoxicity conditions.

37 V.

O

V.1. Introduction to organellar proteomics

The study of subcellular proteomes is one way to investigate deeper cell biology, in order to obtain information which are inaccessible at the cellular level. Organelles have pivotal roles in cell, and are therefore essential in the understanding of cellular processes. These compartments were also progressively associated to pathologies [103, 104], and there are therefore an increasing number of studies targeting distinct organelles [105, 106]. The first applications studying organelles were targeted approaches, focusing on some proteins of interest in a particular organelle. The great expansion of proteomics in the last two decades coupled with efficient separation techniques (such as liquid chromatography or off-gel electrophoresis), progressively lead to the description of entire organelle proteomes, facing also the main issue derived from purification techniques, which is the contamination of the enriched fractions by other organelles. However, working with organelles allows the reduction of sample complexity [107, 108], and also to keep protein complexes intact.

Considerable progresses were performed in the field of organellar proteomics, and the next challenge is the integration of the concept of dynamic in these compartments, meaning that their protein content is not constant. This implies that organelles interact together, fuse, evolve according to metabolic conditions and sometimes maturate. It was actually described that 40%

of organellar proteins have several localizations, confirming this notion [109].

V.2. Subcellular fractionation methods V.2.a. Gradients

The method of choice for sub-cellular fractionation is the gradient purification. Cells or tissues are usually resuspended in a buffer and disrupted using ultrasounds, homogenizers or by

Chapter I

38

applying high pressure through needles. Another possibility is the use of hypotonic solutions, in which the cells are swelling and then disrupted, or hypertonic solution to provoke the shrinking of the cells. A low speed centrifugation allows next the removing of cell debris and nucleus, and subsequently to obtain the “post-nuclear supernatant”, composed of cytoplasm and organelles.

The separation of distinct organelles could be achieved by differential centrifugation, using various time and speed, as the sedimentation rates and masses of each organelle differ. But this approach is usually not efficient enough for high purity preparations. An alternative approach for sub-cellular fractionation from PNS is the density-gradient centrifugation. Because of organelle density, they behave differently in the various liquids used for this kind of separations. PNS is layered on the top of the gradient, which could be continuous or discontinuous. Gradients are centrifuged for several hours using high speeds, and their sedimentation in the tube stops at their isopycnic point, meaning that the density of the surrounding solution is equal to the density of the organelle. Continuous gradients offer a better separation resolution, but need specific material for their preparation. This preparation is time consuming. In contrast, discontinuous gradients, which are the superposition of several layers of decreased concentrations, are less resolutive but easier to prepare.

Such gradients could be prepared with various solutions. Each of them have particularities, as organelle densities are not constants and depend from their surrounding media. The main one is the sucrose, an inexpensive solution, very soluble and that can be used readily to prepare solutions that span the range of densities of most biological organelles [110]. However, some organelles have membranes permeable to sucrose, increasing their density, and leading to organelle weakness. That is the reason why other media were recently highlighted such as Ficoll, a high molecular weight polymer of sucrose and epichlorhydrin, which is non permeant and exerts very low osmotic pressure, Percoll, a high molecular weight media of colloidal silica, which cannot enters into the organelles and exerting no osmotic pressure, and Metrizamide or

39

Nycodenz, iodinated media unable to penetrate the membranes but exerting a low osmotic pressure. Nycodenz has the great advantage to be low viscous, therefore requiring shorter centrifugation times in comparison with sucrose [111, 112]. These approaches were succefully used by Brunner et al. to purify ISGs from INS-1E rat β-cell. They could identify 130 ISGs-related proteins using a 2-step gradient purification [101].

V.2.b. Immunoaffinity purification

Increased knowledge about organelle composition allowed the development of techniques such as affinity chromatography. This approach is based on the binding of ligands (antibodies, chemical ligands, aptamers…) on a solid support to capture organelles. This method is extremely selective for compartments or membrane containing a highly specific epitope at their surface, and is especially suitable for the isolation of intact organelles. Further, it allows repeated purification, increasing the yield of recovery. However, this approach may need an extended optimization to find the best conditions for antibodies, and is not fully adapted to large-scale preparations. The preparation is dependant of the antibody specificity, and tight controls have to be done to verify the non-specific interactions. Finally, the main drawback is the epitope accessibility, which is the major limitation of this technique.

Affinity purification was successfully used by Morciano and co-workers [113], who used an antibody raised against the synaptic vesicle protein SV2 in order to immuno-purify two different populations of synaptic vesicles from rat brains, after a continuous gradient purification. This methods was coupled with MALDI-TOF/TOF analysis and allowed identifying 72 proteins in the first population (free synaptic vesicles) and 81 proteins in the second population (plasma membrane-associated synaptic vesicles), which was a higher protein number than previously estimated.

Chapter I

40 V.2.c. Free flow electrophoresis

Free flow electrophoresis (FFE) is another alternative used for organelle purification. Described in the 1960’s, FFE performs a liquid separation of cells, organelles, complex mixtures, or proteins usually according to their net isoelectric charge. The continuous fractionation makes it especially suitable for organelle purification, allowing high sample recovery. FFE is composed of two parallel plates between which is flowing a carrier buffer. Samples and electrolytes are injected continuously by one extremity of the plates, and an electric field is applied perpendicularly to the laminar flow [114]. The separation of the organelles occurs along the flow. Fractionated samples are then collected by the other extremity, usually in a 96 wells plate [115]. The different modes of FFE allow applying the separation according to three parameters: the charge-to-size ratio, the descending mobility, or the isoelectric point. This method was used in combination with a MS analysis by Jethwaney et al. [116], to separate plasma membrane vesicles from secretory vesicles of polymorphonuclear neutrophils (PMN), recovered after a Percoll gradient.

They could identify many novel proteins of these vesicles, and pointed out a high capacity of reorganization of PMN plasma membrane after proinflammatory stimuli, through this approach.

V.3. Combination with proteomics tools

The combination of organelle purification methods with proteomics and bioinformatics tools allows performing large-scale proteomics analysis of entire organelles, unraveling their proteome. Notably, it permits to avoid the large amount of identifications arising from co- purifying contaminants.

V.3.a. Subtractive approach

The first approach to reduce the number of identifications from contaminants was named

“subtractive approach”. Subsequent to gradient separation, fractions are tested for the

41

enrichment of the organelle of interest, as well as major contaminants, using known markers.

The method proposed the comparison of protein list from the fraction containing the organelle of interest and the contaminant, with protein list from any other adjacent fraction containing the contaminant and other compartments, but not the organelle of interest. The subtraction of both proteomes allows identifying a list of proteins, which is specific to the organelle of interest [117, 118].

V.3.b. Localization of Organelle Proteins by Isotope Tagging

The development of quantitative proteomics and bioinformatics provides new strategies for the prediction and attribution of organelle proteins and the discrimination of proteins from co- purifying contaminants. One of these methods is named LOPIT (Localization of Organelle Proteins by Isotope Tagging). The method is based on a differential gradient purification, in which known markers for specific organelles are assessed by western blots. Proteins from fractions of interest as well as adjacent fractions are labeled with isobaric tagging, such as iTRAQ or TMT, pooled together and analyzed by mass spectrometry. Finally, a Principal Component Analysis (PCA) is applied on the obtained ratios in order to distribute each protein in the different compartments, compared with the ratios of the well-known organelle proteins. For proteins with unknown distributions, a partial least-squares discriminant analysis (PLS-DA) is used to predict their belonging to a particular group [119-121].

V.3.c. Protein Correlation Profiling

Another method was established for a better localization of the proteins to distinct organelles.

This approach is the PCP: Protein Correlation Profiling. This is of interest to discriminate bona- fide organellar proteins from contaminants, in a density gradient purification. MS analysis of each fraction of the gradient allows calculating the peptide abundance per fraction. This

Chapter I

42

abundance is then normalized and correlated with elution time. As a result, it is possible to establish abundance curves for each protein in the different fractions. Profiles from undefined proteins are compared with the ones from well-known proteins of the different compartments.

Proteins following the same repartition as marker proteins could therefore be attributed to the same organelle (figure 6) [109, 122, 123].

Figure 6: Principle of the Protein Correlation Profiling [124].

V.4. The help of bioinformatics

Bioinformatics tools appeared to be a great help in organellar proteomics, with the occurrence of predicting tools, as well as databases. Annotation tools are based on two different methods.

They could be sequence-based predictor or annotation-based predictor. The first one relies on the amino-acid sequence of the protein, looking for known signal peptides, addressing the proteins to some particular compartments. The second one relies mainly on the annotations found in databases, homologies with other known proteins, or functional domains and motifs.

New tools are now incorporating both approaches, such as RSLpred, which also integrates evolutionary information, or Sherloc2, and appear to be powerful predictors [125, 126].

43

The increasing number of studies focusing on organelle mapping finally results in the creation of databases containing proteome profiles of specific organelles. This is for instance the case with the Nuclear Protein Database (http://npd.hgu.mrc.ac.uk), bringing together the results of several studies on nuclear proteomes. There is a real need for such databases, which constitute a precious help in the field of subcellular proteomics.

V.5. Verification

Purification processes as well as MS results need to be verified in order to confirm the protein localization in a specific organelle. The basic method for verification is to monitor by western blot the repartition of a given protein into the gradient, using a known organelle marker as a reference. Although western blot is widely used to confirm the partitioning of a distinct organelle across the different fractions, it is also necessary to test the presence of potential contaminants in the same fractions. However, the sensitivity of western blot sometimes does not allow discriminating low abundant contaminations, which are identified by MS. Multiple Reaction Monitoring could thus be an alternative method for validation of qualitative and quantitative data obtained by organellar proteomics. Others techniques such as electron microscopy, and immunofluorescence are widely used to confirm the colocalization with known organelle markers.

In conclusion, organellar proteomics allowed going one step further in cellular knowledge. It enables to gain new insights into molecular mechanisms associated to specific organelles, and therefore improved the general understanding of cellular function. It is however essential to go beyond the limits and overcome the new challenges in this field, such as organelle dynamics and the management of contaminants.

Chapter I

44 VI.

R

Pancreatic β-cells are prominent for their role in glucose homeostasis. A failure in this process during T2D leads to chronic hyperglycemia, and induces defects at many levels. Glucotoxicity is known to affect β-cell function, notably leading to a decrease of insulin release in response to glucose, and causes apoptosis via several pathways. The precise early mechanisms of β-cell dysfunction induced by chronic hyperglycemia are not fully understood, and are essential to apprehend new β-cell-targeted therapies under pathological conditions.

Insulin secretory granules are organelles dedicated to insulin secretion in β-cells, and therefore are essential for β-cell to function properly. A few studies described insulin secretory granules content and modulation under chronic high glucose exposure.

This thesis project was therefore divided into 2 main objectives:

Aim 1: Increase our knowledge on ISGs protein content to obtain a comprehensive view of its composition and its dynamic along ISG biogenesis, maturation and exocytosis.

Aim 2: Understand the early molecular events underlying β-cell dysfunction under high glucose concentration. To extend our understanding about these mechanisms, we focused on the modulation of distinct subproteomes such as ISGs and nuclei, but also on total cells.

• Chapter 2 is a review, published in Journal of Proteomics, focusing on glucose homeostasis as well as the different defects associated with glucotoxicity. It gives an overview of the diverse hypothesis proposed to explain β-cell dysfunction induced by high glucose exposure. This review also presents proteomics studies published on glucotoxicity and pancreatic islets.

45

• Chapter 3 is a review published in Mass Spectrometry Reviews centered on secretory mechanisms and the related organelles. It is also dedicated to studies targeting secretion mechanisms by proteomics approaches.

• We conducted a study aiming to characterize ISGs proteomes, in order to complete our knowledge on granules biogenesis and maturation. The results constitute the 4^th chapter and were published in Journal of Proteomics in 2012.

• The 5^th chapter corresponds to a study aiming to monitor changes induced at the proteome level by chronic hyperglycemia on whole INS-1E cells. We validated the modulation of some proteins of interest, and the results were published in Proteomics in 2010.

• Regarding to their fundamental role in insulin secretion, we payed special attention to ISGs. The 6^th part is formed with a paper published in Molecular and Cellular Proteomics in 2012, focusing on the variation of ISGs proteome in cell submitted to glucotoxic stress.

• The 7^th chapter encompasses results from a proteomics analysis aiming to compare the nuclei proteome of cell submitted or not to glucotoxic conditions. Results are centered on a particular complex of proteins called MiniChromosome Maintenance complex.

• The last part is the discussion grouping the results of the different sections. A portion is dedicated to future perspectives for the project.

47

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