A novel sec7 domain containing protein BIG3 and its role in regulated secretory pathway

1.1 General Secretory Pathway 1.1.1 ER, the entry station of secretory pathway 1.1.2 Golgi, the sorting station of secretory pathway 1.1.2.1 Golgi structure and function 1.1.2.2 Golg

THE FUNCTIONAL ROLE OF BIG3

IN THE REGULATED SECRETORY PATHWAY

THE FUNCTIONAL ROLE OF BIG3

IN THE REGULATED SECRETORY PATHWAY

LI HONGYU B.Sc

Acknowledgements

I would like to express my gratitude to my supervisor, Professor Hong Wan Jin for his supervision, guidance and support to my work; and to my supervisory committee members: Dr Cai Ming Jie and Dr Walter Hunziker, for their invaluable comments and advices on my work I am grateful to Dr Jill Mae Lan Tham for her constant guidance and advices I would like to thank Dr Vadim Atlachkine and Miss Huang Cai Xia for their great contributions on generating the BIG3 knockout mice I would also like to thank Dr Wang Cheng Chun for the help on mouse work, to Ng Chee Peng for the help

on electron microscopy work, to Dr Wei Shun Hui for the help on capacitance measurement assay, and to Dr Guo Ke for the help on histological work My appreciation also goes to Dr Tran Thi Ton Hoai and Dr Ong Yan Shan for their criticisms and advices on my work I would like to thank my present and past colleagues for their help and advices, Dr Chan Siew Wee, Dr Loo Li Shen, Dr Liu Ning Sheng, Dr Zhang Xiao Qian, Dr Paramjeet Singh, Dr Wang Tuan Lao, Dr Cai Lei, Dr Lu Lei, Dr Lim Koh Pang, Dr Tai Gui Hua, Miss Tan Yik Loo, Mr Lim Chun Jye and Miss Chong Yaan fun

My appreciation also goes to the DNA sequencing unit and histology facility of IMCB, the animal facility of Biological Resource Centre, and the Flow Cytometry Facility of Biopolis Shared Facilities, for their excellent services

I specially thank my family for their constant care and support, patience and understanding

Hongyu

2010

1.1 General Secretory Pathway

1.1.1 ER, the entry station of secretory pathway

1.1.2 Golgi, the sorting station of secretory pathway

1.1.2.1 Golgi structure and function

1.1.2.2 Golgi biogenesis and intra-Golgi transport

1.1.2.3 TGN, the sorting station

1.1.2.4 Post-TGN carrier formation

1.1.3 Exocytosis

1.2 Regulated Secretory Pathway

1.2.1 Identity of secretory granules

1.2.2 Biogenesis Models of secretory granules from the TGN

1.2.3 ISG Maturation

1.2.4 Secretory Cargo Sorting Mechanisms

1.2.5 Prohormone processing enzymes

1.2.6 Balance of production and demand

1.3 Sec7 proteins

1.3.1 Arf proteins: properties and functions

1.3.2.1 The Sec7 domain of Arf-GEF

1.3.2.2 BFA inhibition

1.3.2.3 Arf-GEF family

1.3.2.4 BIG3, a putative member of Sec7 protein family

4 Aim of the Study

2.4 Coomassie blue staining

2.5 Immunization of rabbits and affinity purification of antibodies

2.6 Antibodies used in the study

2.7 Cell lines used in the study

2.8 Preparation of tissue and cell lysates

2.9 Western blot

2.10 Indirect immunoflurescence microscopy

2.11 Histological analysis and immuno-staining

2.12 Pancreatic islet isolation and primary culture

2.13 K+/Ca++, glucose and cycloheximide treatment

2.14 Construct expression in mammalian cells

2.15 Electron microscopy

2.16 GST-GAT pulldown assay

2.17 Short hairpin RNA-mediated gene silencing

2.18 Lenti-viral infection

2.19 Cell sorting

2.20 Quantitative Real-Time PCR

2.21 Pulse-Chase assay using 35S labeling

2.22 Membrane capacitance measurement

2.23 Animal Welfare and housing

2.24 Generation of the BIG3-/- mice

2.25 DNA extraction and genotyping

2.26 Body fat composition measurement

2.27 Glucose, triglyceride, cholesterol, insulin and testosterone measurement

2.28 Glucose and insulin tolerance tests

2.29 Metabolic Cage Studies

2.30 Statistical Analysis

Chapter 3 Identification, expression and localization of BIG3

3.1 Identification of BIG3

3.2 Generation of rabbit polyclonal antibody against BIG3

3.3 Selective expression of BIG3 protein

3.3.1 Expression of BIG3 in mouse tissues

3.3.2 Expression of BIG3 in cultured cell lines

3.3.3 BIG3 is presented in the endocrine pancreatic islets

3.4 BIG3 is localized to secretory granules in MIN6 cells

3.4.1 BIG3 is partially localized to the insulin and CGA containing vesicles

3.4.2 BIG3 partially co-localized with gamma-adaptin

3.4.3 Minimal co-localization of BIG3 with Golgi or endosomal resident markers

3.4.4 Co-localization of BIG3 and CGA limited to the perinuclear region, and

sensitive to cycloheximide inhibition

3.5 Presence of BIG3 on dense core granules revealed by EM

3.6 Null catalytic function of BIG3 Sec7 on ARF activation

3.7 Discussion

Figures of Chapter 3

Chapter 4 Functional role of BIG3 in the regulated secretory pathway

4.1 Generation of stable BIG3 knockdown MIN6 cells

4.2 Increased secretory protein storage in BIG3-deficient cells

4.3 Elevated secretion in BIG3-deficient cells

4.3.1 Elevated betagranin secretion upon K+/Ca++ stimulation

4.3.2 Elevated total secretion upon K+/Ca++ stimulation

4.3.3 Increased exocytosis events in BIG3-deficient cells

4.4 Elevated betagranin production in BIG3-deficient cells

4.5 Generating BIG3 Knockout mice

4.6 Increased dense core granule number in BIG3-/- beta cells

4.7 Increased insulin secretion in BIG3-/- islets

4.8 Discussion

Figures of Chapter 4

Chapter 5 Metabolic abnormalities in BIG3 knockout mice

5.1 BIG3 knockout mice developed normally

5.2 Histological examination exhibited fatty liver disease in BIG3 knockout mice

5.3 Altered glucose homeostasis and insulin sensitivity in BIG3 knockout mice

5.4 Altered metabolic parameters in BIG3-/- mice on 129/Sv background

5.5 Reduced testosterone level in BIG3-/- male mice

5.6 Discussions

Figures of Chapter 5

Chapter 6 General discussion and future perspectives

References

Summary

The beta cell dysfunction in insulin secretion is one of the key factors in the pathophysiology of diabetes (Bell and Polonsky, 2001) However the mechanisms that underline the development of the beta cell dysfunction in humans still remain elusive Arf-GEFs are a family of Sec7 domain proteins that regulate intracellular vesicle trafficking BIG3 is identified as a putative member of the Sec7 protein family and distantly related to BIG/Sec7p subfamily BIG3 mRNA expression profile shows it is selectively expressed with high levels in the brain and islet This study therefore investigates the function of endogenous BIG3 in islet cells BIG3 protein was found highly expressed in beta cells, and predominantly localized to the secretory granules Investigations on BIG3 knockdown and knockout beta cells demonstrated that the deficiency of BIG3 caused increased amount of secretory granules and secretory proteins

in the cells, and elevated secretion upon stimulation The study on BIG3 knockout mice revealed that in absence of BIG3, the mice exhibited relatively elevated blood insulin level, disturbed glucose homeostasis, impaired glucose tolerance, reduced insulin sensitivity, fatty liver disease, disturbed energy expenditure and activity, and reduced testosterone level Up-regulated insulin storage and secretion in beta cells may account for the elevated blood insulin level The metabolic abnormalities could be in part due to the excessively secreted insulin These data demonstrate for the first time that BIG3 has a functional role in the regulated secretory pathway to modulate the insulin secretion, and therefore to affect the whole body metabolic homeostasis

List of Tables

Table 5.1 Mortality of adult BIG3+/+ and BIG3-/- mice on mixed background

List of Figures

Figure1.1 Simplified illustration of the general secretory pathway

Figure1.2 Simplified illustration of the constitutive and regulated pathways

Figure3.1 Sequence analysis of BIG3 protein

Figure3.2 Characterization of rabbit polyclonal antibody against BIG3

Figure3.3 Selective expression of BIG3 in mouse tissues

Figure3.4 Selectively expression of BIG3 protein in cultured cell lines

Figure3.5 Expression of BIG3 protein in pancreatic islets

Figure3.6 Expression of BIG3 in islet alpha and beta cells

Figure3.7 Partial co-localization of BIG3 with insulin and CGA in MIN6 cells

Figure3.8 Partial co-localization of BIG3 with gamma-adaptin in MIN6 cells

Figure3.9 Minimal co-localization of BIG3 with Vti1a, Vti1b or GS28 on separated

vesicles in MIN6 cells

Figure3.10 Minimal co-localization of BIG3 with Stx6 or GM130 on separated vesicles

Figure3.13 Expression of BIG3 full length construct

Figure3.14 Preferential localization of BIG3 to dense core granules by Immuno-electron

microscopy

Figure3.15 Null catalytic function of BIG3 on Arf activation

Figure4.1 Generation of BIG3 stable knockdown MIN6 cell line

Figure4.2 Increased betagranin storage in BIG3-deficient MIN6 cells

Figure4.3 Increased insulin storage in BIG3-deficient MIN6 cells

Figure4.4 Increased betagranin secretion in BIG3-deficient cells

Figure4.5 Increased total secretion in BIG3-deficient MIN6 cells

Figure4.6 Increased exocytosis events in BIG3-deficient MIN6 cells

Figure4.7 Up-regulated processing of CGA to betagranin in BIG3-deficent MIN6 cells Figure4.8 Generation of BIG3 targeted embryonic stem cells (E-14)

Figure4.9 Generation of BIG3 knockout mice

Figure4.10 Increased granule number in beta cells of BIG3-/- mice

Figure4.11 Increased insulin secretion by BIG3-/- islets

Figure5.1 Body weight of BIG3+/+, BIG3+/- and BIG3-/- mice on mixed background Figure5.2 Body weight of high-fat-diet fed BIG3+/+ and BIG3-/- male mice on mixed

background

Figure5.3 Body weight of BIG3+/+ and BIG3-/- on 129/Sv background

Figure5.4 Survival rate of BIG3+/+ and BIG3-/- adult male mice on mixed background Figure5.5 Normal morphological appearance of pancreatic islets in BIG3-/- mice on both

backgrounds

Figure5.6 Fatty liver in BIG3-/- female mice on both backgrounds

Figure5.7 Progressed fatty liver in a sick BIG3-/- female mice on mixed background Figure5.8 Fatty liver in BIG3-/- male mice on both backgrounds

Figure5.9 Body fat composition of female mice on 129/Sv background at ~4 months old Figure5.10 Blood triglyceride and cholesterol level of BIG3+/+ and BIG3-/- mice on

mixed background at 9 months old

Figure5.11 Blood triglyceride and cholesterol level of BIG3+/+ and BIG3-/- mice on

129/Sv background at 6 months old

Figure5.12 Blood glucose and insulin levels in BIG3+/+ and BIG3-/- female mice on

mixed background at 18-20 weeks old

Figure5.13 Blood glucose and insulin levels in BIG3+/+ and BIG3-/- male mice on

mixed background at 16 weeks old

Figure5.14 Delayed glucose uptake in BIG3-/- male and female mice on 129/Sv

background at 12 weeks old

Figure5.15 Delayed glucose uptake in BIG3-/- male and female mice on 129/Sv

background at 24 weeks old

Figure5.16 Delayed glucose uptake in BIG3-/- female mice on mixed background at 32

Figure5.22 Energy Expenditure (heat) and Respiratory parameters of BIG3+/+ and

BIG3-/- male mice on 129/Sv background

Figure5.23 Food, water intake and activity of BIG3+/+ and BIG3-/- male mice on 129/Sv

background

Figure5.24 Energy Expenditure (heat) and Respiratory parameters of BIG3+/+ and

BIG3-/- female mice on 129/Sv background

Figure5.25 Food, water intake and activity of BIG3+/+ and BIG3-/- female mice on

129/Sv background

Figure5.26 Decreased plasma testosterone level in male BIG3-/- mice on mixed

background at 6 months old

Abbreviations

ARF ADP ribosylation factor

DME Dulbecco’s modified Eagles (medium)

GH growth hormone

kDa kilo Dalton

PI3,4,5P3 phosphoinositide-3,4,5-trisphosphate

Chapter 1 Introduction

Balance of energy consumption and storage to adapt to environmental changes is crucial

to the maintainance of metabolic homeostasis in multicellular organisms The ‘thrifty genotype’ hypothesis suggests that humans are genetically adapted to the circle of feed and starvation ( Neel, 1962; Joffe and Zimmet, 1998) However the rapid changes in human behavior and lifestyle have resulted in worldwide epidemic outbreak of type 2

diabetes (Zimmet et al., 2001) It has been well established that this disease is a multifactorial syndrome that shows heterogeneity in many respects (Ayres, 1977; Lisanti

abnormal insulin secretion takes a centre role in this disease, although there are debates

on which one is more predominant ( Reaven, 1993; Ferrannini, 1998; Relimpio, 2003) The balance between insulin action and insulin secretion is coordinated by insulin sensitive tissues and endocrinal beta cells Multiple genes and genetic loci responsible for the genetic susceptibility to type 2 diabetes have been identified to be involved in insulin signaling, insulin secretion, insulin resistance, glucose metabolism, obesity, and the

hormone processing ( Kahn et al., 1996; Bastian, 2002; Florez, 2008a) However the

mechanisms that underline the development of the insulin resistance and beta cell dysfunction in humans still remain elusive

The beta cell dysfunction in insulin secretion is one of the key factors in the pathophysiology of diabetes (Bell and Polonsky, 2001) It is not only the determinant factor of the final failure to compensate the insulin demand, but also a major contributor

to the development of the disease (Weir and Bonner-Weir, 2004) Multiple lines of evidence have demonstrated that the defects in insulin synthesis, processing, and/or

secretion can often give rise to the disease For example, studies on the monogenic diabetes, maturity-onset diabetes of the young (MODY) have discovered a class of genes that are expressed in beta cells and control insulin secretion (Velho and Froguel, 1997; Stride and Hattersley, 2002;) They demonstrate that strong effects of a single gene can lead to diabetes However it is much more difficult to identify genes in polygenic diabetes since their contributions to the diabetic phenotype may be modest, variable among different populations, and dependent on interactions with other genes and the environment Recently genomic-wide association scans (GWAS) have revealed a number

of new genetic loci associated with type 2 diabetes in addition to a few well known genes

(Dupuis et al.; Zeggini et al., 2008) Interestingly, most of them appear to be involved in

insulin secretion rather than insulin resistance (Florez, 2008b) It implies that the genetic control of insulin secretion may be stronger than that of insulin resistance It also suggests the necessity of further efforts to improve our understanding on the detailed mechanisms of insulin secretion in beta cells

Insulin release to the body tissues is modulated in amounts and time-dynamics to maintain plasma glucose within a narrow concentration range (Ferrannini and Mari, 2004) The amount of insulin output must cope with glucose uprise after meals on the one hand, and with target tissue sensitivity on the other The rate of insulin secretion must adapt to stimuli both on a minute basis and in the longer term as well To achieve this complex task, the pancreatic beta cells feature an array of specialised functions, which are finely integrated to respond to highly variable environmental inputs Endocrine cells, including beta cells, usually produce and process protein hormones by a common secretory pathway similar to other secreted proteins in all cells, but they also contain

specialized secretory vesicles capable of additional processing, large amount of storage, and induced release of contents This regulated secretory pathway allows the fine control

of cellular hormone production and secretion to meet the body’s demand

Although specialized, the regulated secretory pathway possesses many common mechanisms of the general secretory pathway, such as the secretory protein production and modification, intracellular transport and exocytosis (Burgess and Kelly, 1987; Bonifacino and Glick, 2004; Morvan and Tooze, 2008) The general secretory pathway starts from the endoplasmic reticulum (ER); goes through Golgi apparatus (GA); then seperates into distinct transport routes at the trans-Golgi network (TGN); and finally targets to the plasma membrane (PM), endosomes and other compartments (Enns, 2001)

A simplified diagram demonstrates this pathway in Figure 1.1

1.1 General Secretory Pathway

Along the secretory pathway, a cell is compartmentalized with a series of subcellular organelles The different compartments are defined by membrane-enclosed structures Maintenance of the characteristic of a compartment as well as the communications

between compartments is largely achieved by vesicular transport (Lee et al., 2004;

Munro, 2004; Bonifacino and Glick, 2004)

1.1.1 ER, the entry station of secretory pathway

The ER is the starting point of the secretory pathway, firstly described by Palade in 1975

It is a large intracellular network consisting of differentiated subdomains Translocan is the gateway of entry to the ER New proteins are translocated across or integrated into

the ER membrane via the translocan complex (Walter and Lingappa, 1986) The

translocation event is coupled with translation (Crowley et al., 1993) A series of

covalent modifications and conformational foldings take place during and after translocation

After proteins are properly processed, they are transported to the Golgi Aparatus via Golgi-intermediate compartment (ERGIC), either by small transport vesicles or by

ER-prolonged tubular structures (Bonifacino and Glick, 2004; Martinez-Menarguez et al.,

1999) There are two major working models that are implicated for protein export from

the ER (Lee et al., 2004) In active transport model, secreted proteins are selectively

enriched at ER exit sites with specific receptors ER export receptors would then interact with coat proteins or their adaptors to trigger the vesicle formation In the bulk flow model, no specific receptor or signal sequence is required By default, the aggregation of proteins at ER exit sites itself triggers spontaneous vesicle formation Thus both ER resident and secreted proteins are transported to Golgi, where ER residents with signal sequences such as KDEL are sorted back to ER (Lewis and Pelham, 1992) At the ERGIC, COPI-coated (Coat Protein complex I) vesicular transport complexes (VTCs) separate from ERGIC and move towards the Golgi (Watson and Stephens, 2005) Parallel

to above pathway, tubular transport intermediates (TTIs) carry cargo that are too large to enter COPII (Coat Protein complex II) vesicles to the Golgi (Fromme and Schekman, 2005)

1.1.2 Golgi, the sorting station of secretory pathway

1.1.2.1 Golgi structure and function

The Golgi was firstly discovered by Camillo Golgi in 1898 Newly synthesized proteins are further modified and sorted in the Golgi The Golgi is a highly organized and polar-distributed complex that consists of membrane-enclosed flat stacked layers of cisternae with distinct resident enzymes (Mellman and Simons, 1992) In yeast, Golgi simply

exists as individual cisternae (Rossanese et al., 1999) In higher organisms like mammals, Golgi is a stack of ordered layers, divided into cis, medial, trans faces and

TGN The distribution pattern of the Golgi depends on cell types In most plant and fungi cells, the Golgi stacks scatter throughout the cell (Wooding and Pelham, 1998); while in

a mammalian cell, Golgi stack mainly clusters at the perinuclear region (Sciaky et al.,

1997)

1.1.2.2 Golgi biogenesis and intra-Golgi transport

The formation and maintenance of the Golgi structure is dynamically balanced, where COPI coated vesicles play important roles in cargo protein sorting and resident protein

retention (Lee et al., 2004) COPI formation is ADP-ribosylation factor (Arf) dependent,

which is a class of small GTPases, and catalyzed by a specific group of

guanine-nucleotide exchange factors (GEFs) and GTPase activatng proteins (GAPs)(Fiedler et al., 1996; Orci et al., 1993; Zhao et al., 1997)

The polarized Golgi is in the order of the entry, maturation and exit sites for secretory proteins There are two major models to explain how the secretory proteins pass through the Golgi In vesicular transport model (Rothman, 1994), secretory cargos are carried by vesicles moving between layers or by bulk flow, while the Golgi cisternae as well as the resident enzymes mainly remain unchanged Cisternal maturation model is more widely

accepted nowadays(Anelli and Sitia, 2008; Bonfanti et al., 1998; Mironov et al., 1997;

Pelham, 1998) In this model, Golgi cisternae themselves gradually move forward, carrying cargo proteins and resident enzymes; and resident components are sorted backwards by tubular-visicular transport The Golgi is continuously balanced by

consumption at trans face into post-Golgi intermediates and replenishment at cis face by

the pre-Golgi intermediates formed by fusion of ER-derived vesicles

1.1.2.3 TGN, the sorting station

The outer phase of trans Golgi cisternae is connected to a scattered tubular-saccular

network as the TGN The most distal layers of TGN are exclusively enriched with

clathrin coats(Ladinsky et al., 1994; Mogelsvang et al., 2004) The TGN is the main

sorting and packing station of newly synthesized protein Cargos leaving the Golgi from TGN are sorted into large tubular segments that are elongated and detached from the

TGN(Hirschberg et al., 1998; Polishchuk et al., 2000), and later packed into different

coated vesicles for constitutive secretion(Kornfeld and Mellman, 1989; Pearse and Robinson, 1990), regulated secretion (Traub and Kornfeld, 1997), endosome pathway,

and others (Rodriguez-Boulan et al., 2005) The morphology and size of the TGN vary in

different cell types according to the amount and type of cargo An example is that there is less tubular TGN structure in the cells with regulated secretion compared to that in cells

without secretory granules (Clermont et al., 1995) The size of the TGN also dramatically

changes depending on cargo flux: it reduces when cargo is released and recovers when

cargo is reloaded (Trucco et al., 2004)

There are complex and sophisticated machineries to control the sorting of the TGN depending on the types of cargo within the cell as well as the cell type In the conventional sorting model, different sorting signals mediate the separation of proteins, and the recognition of the signals occurs at the TGN Alternatively, there are post-TGN

sorting events that take place at the tubular structure (Polishchuk et al., 2000), or at the endosomal route (Futter et al., 1995; Gravotta et al., 2007; Leitinger et al., 1995), or at

the immature granules (Arvan and Castle, 1998) These could be the complementary sorting control for fine regulation

1.1.2.4 Post-TGN carrier formation

Secretory cargos are enriched in tubular TGN subdomains through segregation by either sorting motif recognition or favored affinity to lipid or protein microenvironment During this process, Arf activated by specific GEF promotes the recruitment of the cytosolic protein adaptor complexes that can recognize cargo sorting motifs and bind to clathrin coat proteins simutaneously Arf also activates the phosphatidylinositol 4 kinase (PI4K)

to produce phosphatidylinositol 4-phosphate (PI4P) to further increase the affinity of

cytosolic complex to membrane (De Matteis and Godi, 2004; Shin et al., 2004b; Wang et

al., 2003) The Arf activation together with further lipid composition modifications as well as cytosolic protein recruitment distiguishes the cargo-loaded subdomains from the rest of TGN Curvature-inducing proteins, such as the Bin/amphiphysin/Rvs (BAR) domain family and the GRIP-domain-containing Golgins, and lipid metabolizing enzymes such as phospholipase A, facilitate the subdomain tubulation that is coupled with the cargo segregation (Zimmerberg and Kozlov, 2006)

The “pull and cut” model describes the elongation and fission of the TGN subdomains (Bard and Malhotra, 2006) The subdomains interact with microtubule-based motors, and are elongated by the pulling force of microtubules The interaction of TGN subdomain and motor is selective It can be a direct binding of a cargo protein with a motor protein

dynein (Tai et al., 1999); or mediated via adaptor proteins (Nakagawa et al., 2000), or binding to a lipid domain (Noda et al., 2001) Protein kinase D (PKD)(Liljedahl et al.,

2001) and dynamin (Conner and Schmid, 2003) are important players involved in the

“cut” machinery to control the fission site Cargo loading may also regulate the fission site determination (Bard and Malhotra, 2006) Activative Arf and subsequent events also

contribute to the final fission (Godi et al., 2004) The size of the post Golgi carrier may

vary greatly according to the fission site The fission site can be either at the tip of the tubular TGN to produce a small vesicle, or at the bottom of the tubule resulting in a much

bigger chunk of the carrier (Polishchuk et al., 2006) When these carriers are separated

from the TGN, they are driven to their destined sites by the different motors that they were bound to

1.1.3 Exocytosis

Secretory pathway ends with the fusion of secretory vesicles to the plasma membrane The vesicle must target to its proper fusion site, and the fusion event requires energy to

pull, deform and fuse two lipid bilayers together (Borgonovo et al., 2002; Sugita, 2008)

A lot of molecular components from both membranes and cystosol facilitate this fusion event In the constitutive pathway, vesicles fuse immediately upon arrival the PM, while

in the regulated pathway, a portion of vesicles accumulate along the PM awaiting signals

to trigger the fusion (Burgess and Kelly, 1987) In the latter pathway, more complicated

machinery exists to ensure rapid and efficient response to stimulus when in need, such as that of synaptic vesicle exocytosis in neurons (Sudhof, 2004) However, the basic principle is similar, which consists of several common steps: tethering, docking, priming, and fusion For regulated exocytosis, there is a step of triggering before fusion After fusion, vesicle membranes are retrieved from PM to be recycled (Jahn and Scheller, 2006; Sudhof, 2004; Sugita, 2008)

1.2 Regulated Secretory Pathway

Unlike constitutive secretion pathway which exists in all cells, the regulated secretory pathway (RSP) is unique to speciallized cell types such as endocrine, exocrine, neuronal and other cells (Burgess and Kelly, 1987) The hallmark of regulated secretory pathway,

which differs from constitutive secretion, is the regulated exocytosis (Borgonovo et al.,

2002) Generally, in endocrine and exocrine cells, regulated exocytosis refers to the stimulation-induced release of molecules, which are pre-stored in the secretory granules,

or dense core granules according to the appearance under electron microscopy (EM) Depending on cell type, secretory granules contain different types of peptides hormones,

transmitters, and usually co-stored proteins from granin family (Malosio et al., 2004)

Synaptic vesicles with small molecular neurotransmitters in neurons also release the content in a regulated fashion Moreover, lysosomes in blood leukocytes and a few other cell types are found to undergo Ca2+-regulated exocytosis(Jaiswal et al., 2002) Recent

studies suggest a specific group of vesicles displaying calcium-induced exocytosis with a

role in PM enlargement during differentiation and membrane repair (Borgonovo et al.,

2002) Moreover, insulin induces the translocation of the GLUT4 glucose transporter from intracellular storage compartments to the plasma membrane via Glut4 vesicles

(Kanzaki and Pessin, 2003) Thus, the regulated secretory pathway exists in diverse cell types with various machineries and cargos The RSP is under layers of regulation in quantitative and qualitative, spatial and timely manner This section focuses on two aspects of the classical regulated secretory pathway in endocrine cells: the biogenesis and maturation of secretory granules, and the sorting and processing of hormone cargos A simplified diagram of the constitutive and regulated secretory pathways is demonstrated

in figure 1.2

1.2.1 Identity of secretory granules

Secretory granules are membrane-enclosed exocytic organelles derived from the TGN They are also called: secretory vesicles，dense core granules, dense core secretory granules, or large dense core vesicles Secretory granule (SG) buds from the TGN as immature SG (ISG), then undergo homotypic fusion and/or membrane remodeling to become mature SG (MSG), coupled with microtubule dependent transport to the cell periphery, awaiting for stimulation to release The whole process is coupled with sorting, packing, processing and storage of cargo proteins (Arvan and Castle, 1998)

Although SGs are heterogeneous across cell types and even within a single cell, they are

distinguishable by multiple criteria(Malosio et al., 2004; Meldolesi et al., 2004) The

common criteria to identify SGs are: morphological appearance of round dense cores wrapped by a single membrane with size of 60-300 nm; and enriched in cell type specific contents including peptide hormones, granins (chromogranins and secretogranins) (Tony, 2003) and prohormone processing enzymes (PC1/3, PC2, CPE) (Steiner, 1998) Additional criteria include specific SNARE proteins presented on membrane; prolonged

storage in unstimulated state, no markers of other organelles such as TGN endosomes or lysosomes; regulated exocytosis blockable by tetanus and botulinum B toxins Those strict criteria may be applicable to MSGs, but not suitable for the intermediate form ISG ISGs may appear less dense, larger in size, short-lived, and colabeled with proteins of

other organelles such as lysosomal proteins(Kuliawat et al., 1997) and clathrin coat proteins (Orci et al., 1987), which are absent on MSG

1.2.2 Biogenesis Models of secretory granules from the TGN

So far it has not been well addressed how the secretory granules are produced from the TGN Two possible models of SG formation are suggested: discontinued step-maturation model or continued quantitative removal model (Dannies, 1999, 2002) In the step-maturation model, secretory proteins are selectively concentrated, usually by aggregation

to specific areas of trans-Golgi lumen with facilitation of local microenvironment factors such as pH, divalent cations, lipids and proteins; and membrane proteins accumulate at those sites, or condensing vacuoles Granules then bud off from the TGN by the same machinery that applies for other type of vesicles budded from the TGN, but the size of granules is much bigger The newly formed granules may still contain TGN proteins such

as lysosomal proteins and clathrin coat proteins and thus are considered as immature SG ISG may fuse with each other, followed by further removal of non-MSG proteins by small clathrin-coated vesicles Another quantitative removal model is suggested for

aggregated secretory proteins such as Prolactin (PRL) (Rambourg et al., 1992) In this

model the entire TGN is consumed by vesicle budding And aggregation of secretory proteins would be too big to be packed into small vesicles, and thus it is left behind with remaining TGN membrane to form tubular-vesicular progranules, or ISGs Thus ISG

clusters may not be result of homotypic fusion, and no separate budding mechanism is necessary for SG formation Further removal of excessive membrane and contents from pro-granules and poly-granules leads to MSG Both models may work together, however one or the other may look more morphologically dominant depending on cell or cargo types

1.2.3 ISG Maturation

ISG undergoes morphological and biochemical procession after biogenesis, mainly including prohormone processing and removal of excessive content, membrane, and membrane proteins via clathrin coated vesicles Maturation usually leads to smaller and more condensed MSGs However MSG could also be larger than ISG via ISG homotypic

fusion (Urbe et al., 1998) By cell-free reconstitution assay, it has been found that NSF,

SNAP and SNAREs are required in ISG fusion, the same as other membrane fusion

events in cells (Urbe et al., 1998) It has been suggested that Syntaxin6 is required in this fusion step in a t-t-SNARE interaction (Wendler et al., 2001) Synaptotagmin IV is also found to interact with Syntaxin6, and is required for ISG fusion (Ahras et al., 2006)

Syntaxin6 and Synaptotagmin IV, as well as SNARE protein VAMP4, are localized to

ISG but not MSG (Eaton et al., 2000) Removal of those membrane proteins, as well as

soluble lumen content such as unprocessed prohormones, is through ISG-derived CCVs,

which is a BFA sensitive step involving interaction of GTP-Arf and AP-1 (Austin et al.,

2000) More recently, it is reported that another clathrin adaptor, GGA is also required

for maturation of ISG (Kakhlon et al., 2006)

1.2.4 Secretory Cargo Sorting Mechanisms

The enrichment of specific cargos in SGs suggests the existence of sorting machinery Two major sorting machineries, ‘Sorting by entry’ and ‘Sorting by retention’, have been suggested (Arvan and Castle, 1998; Arvan and Halban, 2004; Kuliawat and Arvan, 1994) Each one could be the complementary regulation for another depending on the cell type ‘Sorting by entry’ model proposes that there are positive signals of SG proteins presented to specialized subregion of the TGN It could be a sorting sequence or property (such as aggregation) recognized by an ISG specific membrane receptor, thus SG proteins could be concentrated The sorting event starts in the TGN and ends by ISG formation ‘Sorting by retention’ model proposes that no specific sorting signal is needed for SG protein, instead all secretory proteins not destined for regulated secretion are actively removed via small clathrin coated vesicles, and SG proteins are left behind and condensed In this model the sorting event takes place in the TGN and ends by MSG formation, and ISGs serve as the 2nd sorting station after TGN

For “Sorting by entry” model, the key is to identify a sorting signal recognized by a spefic receptor A precise pH gradient along the secretory pathway, from 7.4 in the ER,

to 6.2 in the trans-Golgi, and 5.5 in SGs is required for sorting and processing of hormones (Demaurex et al., 1998; Seksek et al., 1995; Wu et al., 2001) If a receptor can

bind to a SG protein at neutral pH condition, it will provide one way to concentrate SG proteins in the Golgi, but such a receptor has not been found so far It may indicate that

SG proteins are only separated from other secretory proteins at later stage of the TGN There are at least two proteins proposed to be receptors at acidic pH condition One is the inositol 1,4,5-triphosphate receptor which binds to chromogranin A (CGA) (Yoo, 1994) But the lack of its presence in many endocrine cells indicates it could not be a general

player (Ravazzola et al., 1996) Another candidate is CPE which is suggested to be

responsible for sorting Proopiomelanocortin Precursor (POMC), proinsulin and growth

hormone (GH) to SG (Cool et al., 1997; Normant and Loh, 1998; Shen and Loh, 1997)

There is interaction between C-terminus of CPE and N-terminus of POMC But it has been argued that neither the signal sequence nor the receptor sequence is necessary for

proper sorting by deletion mutant study (Roy et al., 1991; Varlamov and Fricker, 1996) Moreover, CPE knockout does not affect the proinsulin targeting to SG (Irminger et al.,

1997) So far, no general signal sequence or general receptor has been identified, which suggests the active sorting of SG proteins may be different from classical sorting model

‘Sorting by retention’ is a passive sorting model: other proteins are actively sorted away and/or SG protein aggregates are too big to be removed(Arvan and Castle, 1998; Arvan and Halban, 2004) In cells that produce more than one SG proteins, the behavior of each

SG protein may be different For the cells to preferentially retain SGs with one type of cargo but not another, there must be a mechanism to recognize the content of a SG, which may be the result of preferential aggregation or preferential retaining of aggregates It has been found that while salivary amylase and proline-rich protein expressed in AtT-20 cells are stored with endogenous adrenocorticotropic hormone

(ACTH) in SGs, they are sorted differently (Castle et al., 1997) They are progressively

removed from the granule pool via basal secretion so that only small portions remain in MSGs with endogenous ACTH or separately stored It indicates that retention sorting machinery may exist for different SG proteins that have entered SGs There should be mechanisms for specifically preventing aggregation or retaining aggregates for different

SG cargos Moreover, different endogenous hormones may be treated differently within

one cell In rat gonadotrophs, Luteinizing hormone (LH) and Follicle stimulating hormone (FSH) are produced in the same cells, but are stored in different granules More FSH than LH is released basally, while upon stimulation more LH is released than

FSH(Thomas and Clarke, 1997; Watanabe et al., 1993) It indicates retention sorting

machinery may exist for different SGs, as well How the cells achieve these kinds of regulation still remains elusive

It has been suggested that structurally similar sorting signals may utilize different sorting mechanisms; and a single SG protein may contain multiple sorting signals using different

sorting mechanisms (Gorr et al., 2001) Moreover, one cell may contain multiple sorting

mechanisms; and these mechanisms may be under regulation of various physiological

conditions (Gorr et al., 2001) The existence of all these possibilities makes a universal

sorting model less likely

1.2.5 Prohormone processing enzymes

Many peptide hormones arise from larger precursors Those precursors undergo proteolytic processing by proprotein convertases and carboxypeptidases in secretory

granules(Hook et al., 2008; Rholam and Fahy, 2009) The cleavage sites of PCs are

usually dibasic residues, Lys-Arg, Lys-Lys, or Arg-Arg; sometimes Arg-Lys or single Arg with the resulting basic amino acids to be removed by carboxypeptidase One prohormone may contain more than one cutting site to produce multiple peptides in

different sets depending on the cell type (Hook et al., 2008; Rholam and Fahy, 2009)

1.2.6 Balance of production and demand

How secretory cells control the size and number of SGs in order to balance SG

production with demand remains elusive (Borgonovo et al., 2006) For example, GH4C1

cells produce both PRL and GH Treatment with insulin and EGF increases the storage of

PRL by ~ 50 folds but not GH (Gorr, 1996; Scammell et al., 1986) Similar result was observed when the cells were transfected with proinsulin (Reaves et al., 1990)

Expression of human PRL could block rat PRL storage at as low as 1:40 ratio (Arrandale and Dannies, 1994) How the cells achieve such differentiated control remains largely unknown Moreover, hormone storage in a cell is not a purely passive process but actively controlled For example, in AtT-20 cells, over 50% of newly synthesized hormones are constitutively secreted, and majority of them targeted to SG then released

in a constitutive-like manner While in islets cells, less than 5% hormones is released

from ISGs in an unregulated manner (Moore et al., 2002) Comparing normal and tumor

tissues, it also shows that the cells may have regulatory mechanisms to control different

amount of SG proteins in different physiological conditions (Moore et al., 2002) These

findings indicate that there are multiple layers of control in RSP which have not been clearly addressed to date

1.3 Sec7 domain proteins

As motioned in previous sections, Arf proteins play key roles in the secretory pathway They cycle between inactive GDP-bound and active GTP-bound forms The activation of Arf GTPases requires Arf-GEFs, which belong to the Sec7 protein family The GTPase activity of Arf proteins is catalyzed by Arf-GAPs

1.3.1 Arf proteins: properties and functions

Arf proteins belong to the Ras small GTP-binding protein superfamily (Takai et al.,

2001) The Ras superfamily members have common conserved motifs for GDP and GTP binding, and for GTPase activity The GDP/GTP binding conformations of all the members are topologically similar with mobile switch I and switch II regions; and GDP-bound form is inactive form while GTP-bound form is active in engaging downstream

effectors (Takai et al., 2001) The exchange of GDP to GTP is catalyzed by GEF

(Casanova, 2007), while the intrinsic GTPase activity usually requires GTPase Activation Proteins to promote the hydrolysis of the bound GTP (Nie and Randazzo, 2006)

insertion of N-terminus into the membrane (Pasqualato et al., 2002) Thus the

GTP-bound form is tightly coupled with the membrane association with effectors, and GTP hydrolysis leads to the disassociation of Arf from the membrane Furthermore, the active GTP-bound form of Arf can bind to specific effectors, such as previously mentioned coat proteins and lipid-modifuing enzymes The binding region is close to the N-terminal anchor; therefore most of Arf effectors are membrane associated (Gillingham and Munro, 2007), as such, Arf proteins act to mediate membrane targeting of the effectors to facilitate the biological events

1.3.2 Activating Arf proteins by Sec7-family GEFs

Inactive Arf is GDP-bound and cytosolic It requires GEF to catalyze the displacement of GDP for GTP binding and the displacement of N-terminal amphipathic helix for membrane association Arf-GEFs determine the amount and location of activated Arfs (Donaldson and Jackson, 2000)

1.3.2.1 The Sec7 domain of Arf-GEFs

A 200-residue domain was found in the first few identified Arf-GEFs(Chardin et al., 1996; Peyroche et al., 1996) It was named Sec7 domain after the first protein found to contain such a region, the yeast Sec7p (Achstetter et al., 1988) All Arf-GEFs identified

are found to contain such a highly conserved Sec7 domain (Casanova, 2007) Therefore, several other Sec7 domain containing proteins are predicted to be Arf-GEFs based on

sequence analysis (Cox et al., 2004) Moreover, the Sec7 domain of Arf-GEF alone is sufficient for the exchange activity of GDP to GTP (Jones et al., 1999)

The crystal structural studies have revealed that two conserved regions composed of 10 α-helices in the Sec7 domain form a major deep hydrophobic groove and a minor hydrophilic groove The hydrophobic groove favors the insertion of Arf switch I and II regions and leads to substantial conformational changes to expose the nucleotide-binding

site (Cherfils et al., 1998; Goldberg, 1998; Mossessova et al., 1998; Renault et al., 2003)

Between helix 6 and 7 in the hydrophilic groove, there is an invariant ‘glutamic finger’ which inserts into the Arf GDP-binding site and displace the bound GDP by charge

repulsion (Renault et al., 2003) Mutagenesis studies have shown that the Sec7 domain loses its GEF activity once its glutamic finger is abolished (Beraud-Dufour et al., 1998)

At the same time, the conformation change also leads to the exposure of the N-terminal

myrisoylated α-helix and its insertion into the membrane (Pasqualato et al., 2002)

Although the Sec7 domain facilitates Arf binding, it is not responsible for the substrate Arf specificity (Casanova, 2007)

1.3.2.2 BFA inhibition

Brefeldin A (BFA) is a fungal metabolite that is found to block secretion (Misumi et al.,

1986) Later it has been found that the action of a subset of Arf-GEFs to catalyze Arf activation is inhibited by BFA which leads to the blocked secretion due to defective activation of Arf proteins BFA stabilizes an abortive Arf-GDP-Sec7 domain protein complex Such inhibition requires specific residues from both the Sec7 domain of Arf-

GEF and Class I and II Arf proteins (Peyroche et al., 1999; Robert et al., 2004) It is

noticable that only a subset of Arf-GEFs, GBF1 and BIG1/2 are sensitive to BFA inhibition Moreover, the specificity of BFA sensitivity depends on the properties of both

Arf and Sec7 domain of correspondent GEF (Zeeh et al., 2006)

1.3.2.3 Arf-GEF family

An overview of Sec7-domain-containing proteins was carried in a phylogenetic study

(Cox et al., 2004) In this study, 49 Sec7 proteins were identified in 7 eukaryotic model

systems and classified into 8 subfamilies There are 15 mammalian containing proteins assigned into two major classes and further 6 subclasses based on sequence similarities and functional differences, two subclasses of the large Arf-GEFs (>100kD) and four subclasses of the small Arf GEFs Among them, the large Arf-GEFs are the only group that is conserved in all eukaryotes from yeasts, plants, worms to

Sec7-domain-mammalians, and are BFA sensitive While the small ones are only presented in metazoans and BFA resistant Accumulating evidence indicates that each ArfGEF functions in a specific subcellular compartment or subcompartment, and is subjected to different kinds of upstream regulation (Casanova, 2007)

Large Arf-GEFs

GBF1 (Golgi-specific BFA resistance factor 1) is a well conserved large Arf-GEF Gea1

and 2 are the orthologues of GBF1 in yeast Deletion of both of them is lethal(Peyroche

intermediate compartments, and recruit COPI-coated vesicles in an Arf-dependent

manner (Claude et al., 1999; Franzusoff et al., 1992; Peyroche et al., 1996) It has been

reported that Rab1b interacts with GBF1 and modulates both Arf1 dynamics and COPI

association (Monetta et al., 2007) Arf5 is the preferential substrate in vitro (Claude et

al , 1999), while Class I and II Arfs are possible substrates in vivo (Zhao et al., 2006)

There are two BIGs (Brefeldin A-inhibited guanine nucleotide-exchange protein), BIG1 and BIG2 The yeast orthologue of BIG1 and BIG2, Sec7p, is the founding member of

Arf-GEFs originally identified in a yeast mutagenesis screening (Achstetter et al., 1988) Sec7p is localized to the Golgi (Franzusoff et al., 1991) and plays a key role in ER–Golgi and intra-Golgi transport (Franzusoff et al., 1992) Mammalian BIG1 and BIG2 are mainly localized to the trans face of Golgi apararus They catalyze nucleotide exchange most efficiently on class I Arfs in vitro and are also active on Arf 5 but do not use Arf 6

as a substrate(Mansour et al., 1999; Morinaga et al., 1999) For BIG1, both Sec7 domain and an upstream region ~100 amino acids domain are required for the in vitro GEF

activity (Morinaga et al., 1999) The N-terminal region upstream of Sec7 domain of BIG1 is sufficient for Golgi targeting (Zhao et al., 2002) Different from GBF1, BIG1 as

well as BIG2 recruites adaptor protein AP1 and GGA1 onto the Golgi membrane to

facilitate clathrin coated vesicle formation (Shinotsuka et al., 2002) BIG2 is also present

on endosome compartment (Shen et al., 2006; Shin et al., 2004a) Loss of function

mutations in BIG2 cause an autosomal recessive periventricular heterotopia in human

(Sheen et al., 2004)

The three large Arf-GEFs are evolutionally close-related and mainly localized to the

Golgi complex They display functional diversity and redundancy (Ishizaki et al., 2008; Manolea et al., 2008; Richter et al., 2007) Other than the central Sec7 domain, there are

also other conserved domains among these large Arf-GEFs: the N-terminal Dimerisation and Cyclophilin Binding (DCB) domain, the Homology Upstream of Sec7 domain

(HUS), and three Homology Downstream of Sec7 (HDS) domains (Mouratou et al.,

2005) The function of those domains is not very well defined so far It is supposed to be related to subcellular localization and membrane association, interaction with upstream and downstream factors to finetune the Arf activation There are a number of proteins found to interact with large GEFs, while the specific functions remain to be elucidated The DCB domains can interact with each other and with HUS domains to form

homodimer or heterodimer (Ramaen et al., 2007) Rab1b-GTP interacts with the DCB

domain of GBF1, and induces GBF1 recruitment at the ER exit sites and at the Golgi

complex (Monetta et al., 2007) DCB-HUS domain of BIGs interacts with protein kinase

A (PKA) and protein phosphotase 1γ (PP1γ) The GEF activity of BIGs is decreased upon phosphorylation by PKA, and is recovered through dephosphorylation by PP1γ