CHAPTER I INTRODUCTION - Vanderbilt...

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CHAPTER I

INTRODUCTION

Glucagon is a 29-amino acid peptide hormone secreted by the alpha cells of the

pancreas, which was originally identified as a hyperglycemic hormone in pancreatic

extracts in 1923 by Kimball and Murlin. The regulation of glucagon secretion is

complex; it involves the effects of several metabolic substrates, hormones and

neurotransmitters. The main physiological role of glucagon is the maintenance of hepatic

glucose production during fasting, hypoglycemia, exercise and infection/trauma.

The goal of this dissertation is to describe the acute in vivo regulation of hepatic

glucose production by glucagon during insulin-induced hypoglycemia in the overnight-

fasted conscious dog. This chapter will provide an introduction to the following: 1)

Counterregulatory response to hypoglycemia, 2) Glucagon action and signaling, 3)

Insulin action and signaling, 4) Insulin and glucagon interaction.

Counterregulatory response to hypoglycemia Under physiological conditions glucose is metabolized by all tissues throughout

the body, but is a critical metabolic fuel for the nervous system. The reason for this is

that the brain can not synthesize glucose or store more than a small amount of glycogen;

it relies mainly on the continuous uptake of glucose from the circulation to supply its

metabolic needs (1). As a result, hypoglycemia is a dangerous condition that can lead to

brain damage, coma and even death. Therefore, maintenance of the plasma glucose

concentration is critical for survival and it is normally tightly regulated by various control

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mechanisms. These counterregulatory signals are so efficient that hypoglycemia is a rare

clinical condition in normal individuals. Clinical conditions most commonly associated

with hypoglycemia are: ethanol-consumption, certain drugs, insulin-secreting islet cell

tumors, pituitary or adrenal insufficiency, hepatic and renal failure, sepsis and ectopic

production of an insulin-like growth factor (2). However, hypoglycemia is the most

frequent complication experienced by insulin-requiring individuals with diabetes. It is

also the principal factor limiting the glycemic control in people with type 1 diabetes and

late stage type 2 diabetes (1).

For many years investigators performed studies to understand hypoglycemia by

using an acute intravenous bolus of insulin, which resulted in a rapid increase in insulin

concentration followed by a short term hypoglycemia. Garber et al. (3) conducted studies

in healthy humans using insulin injections (0.15 U/kg). The insulin injection resulted in a

rapid fall in glucose production (~30%) followed by a doubling of glucose production by

40 minutes due to an increase in glucagon secretion. The increase in glucose production

was attributable mainly to glucagon’s effects on glycogenolysis (3). This model doesn’t

represent a common clinical condition seen in patients with Type 1 Diabetes in which

hypoglycemia develops gradually and can be present for several hours (4). To

understand better the mechanisms involved in the increase in glucose production during

prolonged hypoglycemia, Lecavalier et al. (5) and Caprio et al. (6) in the human and

Frizzell et al. (7) in the dog, studied the contribution of glycogenolysis and

gluconeogenesis to the regulation of hepatic production during prolonged hypoglycemia.

Frizzell infused a high dose of insulin (5mU/kg/min) intraportally for 3 hours into

overnight fasted conscious dogs. Glucose production fell initially and then doubled by 60

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minutes. They found that glycogenolysis accounted for ~79% of glucose production

during the first hour of hypoglycemia and gluconeogenesis played a major role by the

third hour of hypoglycemia (~68%). Studies in humans have also concluded that

glycogenolysis accounted for the increase in glucose production in the first hour

following establishment of hypoglycemia while gluconeogenesis played a mayor role

during the subsequent hours of prolonged hypoglycemia (5; 6).

Defense against hypoglycemia

The fall in arterial plasma glucose is sensed in widespread regions of the brain,

portal vein, carotid body and pancreas. When arterial plasma glucose decreases (~80-85

mg/dl) in response to an increase in insulin, there is a reduction of insulin secretion and

enhancement of hepatic glucose production (8; 9). It has been suggested that

glucokinase-mediated sensing in the pancreatic beta cells is involved in this response

(10). As the arterial plasma glucose concentration decreases to ~65-70 mg/dl the

secretion of glucagon and epinephrine increases (8; 9). Under physiological conditions

this response can restore euglycemia without the development of hypoglycemic

symptoms. Glucagon secretion from α cells is regulated by many factors, including

plasma insulin levels, blood substrate concentrations and the autonomic nervous system

(10). Under the control of the CNS, epinephrine is secreted from the adrenal medullae

during hypoglycemia (1). In patients with type 1 diabetes the counterregulatory

mechanisms mentioned above are impaired (8). When plasma glucose decreases to ~60

mg/dl it results in the secretion of norepinephrine, cortisol and growth hormone and to

the development of symptoms (8; 9). Like the epinephrine response, increases in

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circulating levels of norepinephrine, cortisol and growth hormone are mediated through

the CNS (1).

The glycemic thresholds for the counterregulatory responses described above

apply to insulin induced hypoglycemia. Most studies in vivo used insulin as a

pharmacologic agent to induce hypoglycemia. A study conducted by Flattem et al. (11)

used a glycogen phosphorylase inhibitor to induce hypoglycemia in conscious dogs.

They found that during non insulin-induced hypoglycemia the glycemic threshold for the

increase in glucagon secretion was ~94 mg/dl, which is much higher than the threshold

during insulin-induced hypoglycemia. Therefore, there seems to be a difference in the

glycemic threshold required for the counterregulatory response of the α cell when

hypoglycemia is accompanied by hyperinsulinemia. The mechanism for this increase in

the sensitivity of the α cell to insulin remains unclear but recent studies have shown that

perhaps is attributable to a loss of the fall in intraislet insulin that normally triggers an

increase in glucagon secretion as glucose levels fall (12). For the purpose of our studies

we are going to focus on insulin-induced hypoglycemia.

Hormone Action

The counterregulatory response to hypoglycemia involves the release of glucagon,

epinephrine, norepinephrine, cortisol and growth hormone (1; 4; 13). Studies in humans

and dogs have demonstrated the primary role of glucagon during insulin induced

hypoglycemia (14-17). Studies performed by Gerich et al. (15) in normal and

adrenalectomized humans showed the primary role of glucagon and the secondary role of

epinephrine during insulin-induced hypoglycemia. Dobbins et al. (18) performed studies

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in overnight fasted conscious dogs to characterize the role of the hormone during insulin-

induced hypoglycemia. A 6 fold rise in glucagon (Δ140 pg/ml) significantly increased

glucose production (Δ 4.5 mg/kg/min) in the presence of hypoglycemia despite an arterial

insulin level that was increased 20 fold (Δ328 µU/ml). The effect of the increment of

glucagon on hepatic glucose production was primarily due to a rapid, time dependent

effect on glycogenolysis and a modest, prolonged effect on gluconeogenesis.

Epinephrine, like glucagon, has been shown to increase production in a rapid,

time-and dose-dependent manner in response to a fall in glucose (19; 20). Studies

performed by Cherrington et al. (21) in overnight fasted conscious dogs showed that an

acute physiological rise in plasma epinephrine was associated with a initial increase in

glucose production due to a glycogenolytic response followed later by a gluconeogenic

response. The effect of epinephrine on glycogenolysis wanes with time like glucagon

(21; 22). This similarity may be explained by the fact that epinephrine exerts its effect by

binding to the β-adrenergic receptors on the liver (23; 24). In addition, Chu et al. (25)

demonstrated that effects of epinephrine on glycogenolysis are the result of a direct effect

of the hormone on the liver. On the other hand, the effects of epinephrine on

gluconeogenesis are the result of its action on peripheral tissues (22; 26-28), specifically

an increase in muscle glycogenolysis and adipose tissue lipolysis.

Norepinephrine is also involved in the counterregulatory response. Circulating

norepinephrine reflects release of the catecholamine from the adrenal medullae but more

importantly its release from sympathetic postganglionic neurons (1; 29). The ability of

norepinephrine to restrain a fall in plasma glucose, while not as potent as epinephrine’s,

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involves a stimulatory effect on gluconeogenesis which results from a glycogenolytic

effect in muscle and a lipolytic effect in fat (30-32).

Cortisol and growth hormone are referred as “slow acting” hormones because

their effects are seen a few hours after their increase in plasma. Boyle et al. (33)

conducted studies in humans that provide evidence that cortisol and growth hormone are

involved in the defense against hypoglycemia but they are not critical for recovery from a

low blood sugar. Additionally, the authors suggested that the roles of these hormones in

the defense of hypoglycemia are permissive rather than direct. Further, De Feo et al.

(34) have reported that growth hormone effects were evident after 3 hours of insulin-

induced hypoglycemia at which time it enhanced glucose production and decreased

glucose utilization. Goldstein et al. (35; 36) also showed that acute increases in cortisol

have minimal effects on hepatic glucose production whereas chronic infusion of cortisol

(5 days) increased glucose production by maintaining substrate availability to support

gluconeogenesis and by maintaining hepatic glycogen availability. It also had effects in

peripheral tissues where it decreased glucose utilization in muscle and enhanced lipolysis

in adipose tissue.

Autoregulation and other factors

It has been suggested that the liver is capable of adjusting its glucose output in

response to changes in the plasma glucose concentration per se, independent of changes

in the hormones that normally control glucose homeostasis (37; 38). In vitro studies in

perfused rat liver have reported that hepatic glucose production can vary inversely with

the perfusate glucose levels (39). In vivo studies have shown that the hormonal changes

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are not the only means by which counterrregulation is brought about. Frizzell et al. (40)

performed studies in overnight-fasted conscious dogs to assess the role of the

counterregulatory hormones per se in the response to insulin-induced hypoglycemia. In

one group the counterregulatory hormone response was simulated in the presence of

euglycemia to separate the effects of hypoglycemia per se from those associated with the

counterregulatory hormones. The other groups included a control for the previous group

(insulin + euglycemia) and a group in which insulin was infused alone. They concluded

that the counterregulatory hormones alone accounted for 50% of the response, while the

other 50% resulted from some aspect of hypoglycemia per se. In addition, Bolli et al.

(41) demonstrated the contribution of hepatic autoregulation to hypoglycemic

counterregulation in humans. They assessed the role of hepatic autoregulation during

moderate (~50mg/dl) and severe (~30 mg/dl) hypoglycemia by using somatostatin and

pharmacologic agents to inhibit the secretion of glucagon, growth hormone, cortisol and

to block the action of epinephrine and norepinephrine. Glucagon and growth hormone

were fixed at basal levels while insulin was infused. During moderate hypoglycemia

insulin infusion resulted in complete inhibition of glucose production whereas during

severe hypoglycemia there was an initial suppression of glucose production followed by

an increased in glucose production two times higher than the moderate hypoglycemic

group. Therefore, the authors concluded that hepatic autoregulation is a component of

the counterregulatory response during severe hypoglycemia. Further, Connolly et al. (42)

conducted studies in adrenalectomized overnight-fasted conscious dogs to control for

epinephrine and cortisol release and used somatostatin to clamp insulin and glucagon.

During the euglycemic-hyperinsulinemic control period the liver displayed net hepatic

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glucose uptake, but as the plasma glucose levels dropped there was a stepwise increase in

net hepatic glucose output despite the absence of counterregulatory hormones. The

authors, therefore, concluded that non-hormonal mechanisms including autoregulation

and direct neural input to the liver can stimulate glucose production in response to

insulin-induced hypoglycemia.

The brain is known to be responsible for most of the rise in the counterregulatory

hormones during hypoglycemia but it also affects glucose production directly (43). It

has been reported that stimulation of the VMH results in an increase in hepatic glucose

production (44) and that electrical stimulation of hepatic nerves results in hyperglycemia

(45). Furthermore, Borg et al. (46) have reported that the VMH stimulates the

counterregulatory response during hypoglycemia in rats. In addition, Connolly et al.

(47) conducted studies to determine if the increase in glucose production seen in the

absence of the counterregulatory hormones is either initiated by liver (autoregulation) or

the brain (neural input) in overnight-fasted conscious dogs. They observed that in the

absence of counterregulatory hormones, hypoglycemia sensed at the liver results in an

increase of hepatic glucose production whereas hypoglycemia sensed at the brain

stimulates the lipolytic and ketogenic responses. Taken together, these studies clearly

indicate that non hormonal mechanisms (autoregulation and neural input to the liver) also

play a role in the metabolic response to hypoglycemia.

Although much about the counterregulatory response during hypoglycemia is

known a controversy still remains regarding the site at which the change in the plasma

glucose level is sensed. The brain and the hepato-portal region have both been postulated

to contain glucose sensing neurons that are responsible for triggering the

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counterregulatory response. Biggers et al. (43) performed studies in which euglycemia

was maintained in the brain but hypoglycemia was allowed to occur elsewhere. Under

these circumstances, the plasma glucagon levels decreased, the sympathetic nervous

system response to hypoglycemia was blunted and a rise in glucose production was

attenuated by 75%. On the other hand, Donovan et al. (48) has shown that when

glucose was infused into the hepato-portal region during insulin-induced hypoglycemia

there was an inhibition of the sympathetic response to hypoglycemia. Therefore, the

authors suggested that glucose sensing neurons in the hepato-portal region are important

in the response of the sympathetic nervous system to hypoglycemia, supporting the view

that hypoglycemic sensing occurs at peripheral sites. On the other hand, Jackson et al.

(49; 50) have conducted vagal blockade and liver denervation studies resulting in no

prevention of the counterregulatory response to hypoglycemia. More recently, Saberi et

al. (51) conducted studies in chronically cannulated rats that underwent afferent ablation

of spinal afferent nerve endings in the portal vein (PV) or portal and superior mesenteric

veins (PMV) nerve endings to determine if the rate by which glucose falls determines the

primacy of the hypoglycemic sensing. Their data showed that when PV and PMV were

ablated using capsaicin, the sympathetic response was suppressed when hypoglycemia

developed slowly (~80 min). However, when hypoglycemia was reached quickly (~ 20

min) the responses were minimally decreased (15-30 %). Therefore, it seems that low

blood glucose levels are sensed by central and peripheral mechanisms and the

predominance between them is rate sensitive. It should be noted however that glucagon

secretion is solely under the control of central rather than peripheral glucose sensors.

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Glucagon action and signaling The main physiological role of glucagon is to stimulate hepatic glucose

production. Studies in humans and dogs have established the dose response relationship

between plasma glucagon levels and hepatic glucose production (52; 53). Stevenson at

al. (20) showed using overnight fasted conscious dogs that a selective rise in glucagon (2-

,4-,8-, and 12-fold) for 3 hours resulted in a sensitive dose-dependent increase in glucose

production. In addition, studies in our laboratory have demonstrated that in the presence

of basal insulin a fourfold rise of the hormone produces a half-maximal activation of

hepatic glucose production (~Δ 5.0 mg/kg/min) despite mild hyperglycemia (52).

Additionally, a small change (<10 pg/ml) in arterial plasma glucagon results in an

increase in glucose production of ~ 0.5 mg/kg/min (52; 53). Not only are glucagon’s

effects on hepatic glucose production potent, they also have been shown to be rapid since

it takes ~4.5 minutes for the hormone to half-maximally activate the liver (54). All

together glucagon is a potent and rapid stimulator of hepatic glucose production, and a

small change of the hormone can result in significant changes in hepatic glucose output.

Glucose production by the liver is the result of either glycogen breakdown

(glycogenolysis) or de novo synthesis of glucose from gluconeogenic precursors

(gluconeogenesis). In the dog and the human, the effect of an increment in glucagon on

hepatic glucose production has been shown to be primarily due to a rapid, time dependent

stimulation of glycogenolysis and a modest more prolonged effect on gluconeogenesis

(55-57). The time dependence of glucagon’s effect on glycogenolysis is in part related to

the progressive inhibitory effect of hyperglycemia that occurs in response to the hormone

and in part to factors endogenous to the liver that limit the action of the hormone (58; 59).

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Glucagon’s effects on gluconeogenesis are more modest. Studies have shown that the

hormone regulates amino acid transport into liver via the transcriptional expression of the

hepatic Na+-dependent amino acid transport system A (60). In addition the hormone is

known to stimulate transcription of gluconeogenic enzymes like PEPCK and G-6-Pase

(61-65). It also enhances the phosphorylation of pyruvate kinase, and

phosphofructokinase and decreases intracellular levels of fructose-2, 6-P2, resulting in

inhibition of glycolysis and stimulation of gluconeogenesis (61). The reason for the

limited effect of glucagon on gluconeogenesis, despite its hepatic effects, lies in its

inability to increase gluconeogenic substrate mobilization from the peripheral tissues

such as muscle and fat (66). In fact there are no glucagon receptors in muscle and there

are very few in adipose tissue (67). As one would predict from this observation

glucagon does not have effects on glucose utilization by adipose tissue or skeletal muscle

(20; 68; 69). Likewise it has minimal effects on lipolysis and protein metabolism.

Glucagon exerts its effects by binding to the glucagon receptor (Figure 1.1). The

glucagon receptor belongs to the superfamily of heptahelical transmembrane G protein-

coupled receptors, which is divided into subfamilies based on amino acid sequence. A

large number of G proteins have been identified: Gs, Gi and Gq and subsets of these

proteins. Each G protein consists of three subunits, α, β and γ (70-74). The binding of

glucagon to the receptor results in conformational changes of the latter, leading to

subsequent activation of the coupled G proteins. Upon G protein-coupled receptor

activation, guanosine diphosphate (GDP) is exchanged for guanosine triphosphate (GTP),

which dissociates the G protein complex into 2 units: the Gα and Gβγ subunits. These

subunits in turn activate or inhibit enzymes. Activation of Gq results in the activation of

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phospholipase C (PLC) which causes the production of inositol 1,4,5-triphosphate and

subsequent release of intracellular calcium (70; 75). The extent to which this pathway

contributes to glucose production remains unclear. There are in fact inconsistencies in

the data; some investigators have found that in the presence of a physiological increment

of glucagon there is an increase in intracellular calcium (76), while others have found that

calcium only increases in response to a supra-physiological increment in glucagon (77).

A study performed by Yamatani et al. (78) showed that glucagon increased glucose

production mainly through the cAMP pathway and that Ca2+ dependency was only

observed when the cAMP pathway was inhibited and when supra-physiological levels of

glucagon were present (78).

On the other hand, activation of Gs leads to the activation of adenyl cyclase, and

elevation of cAMP (61; 67; 70; 79). The rise in cAMP causes the activation of c-AMP-

dependent protein kinase or PKA (80), leading to the phosphorylation of a number of

cellular proteins involved in glycogenolysis, gluconeogenesis, glycolysis and glycogen

synthesis (67; 70; 79).

Glucagon stimulates glycogenolysis through the activation of PKA. PKA

catalyzes the phosphorylation of a single serine residue in each subunit of glycogen

phosphorylase. The phosphorylation of the serine-14 residue leads to major changes in

the catalytic and physical properties of the enzyme (81). This in turn increases glycogen

breakdown and net hepatic glucose output. Another effect of glucagon is inhibition of

glycogenesis. Glucagon controls glycogenesis by inducing the phosphorylation and

inactivation of glycogen synthase. Studies have shown that the enzyme is subject to

multi-site phosphorylation, some of which results in the inactivation of the enzyme.

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Recent studies have suggested that PKA activation by cAMP leads to the

phosphorylation of cAMP response element-binding protein (CREB). PKA

phosphorylates CREB at serine 133 leading to its activation (82). CREB is a

transcription factor that induces the expression of key genes involved in the

gluconeogenic pathway such as PEPCK and G-6-Pase (83). PGC-1 (Peroxisome

proliferator-activated receptor- coactivator) is a transcriptional target of CREB and its

expression is triggered by elevated cAMP levels (84). Studies performed by Yoon et al.

(85) showed that overexpression of PGC-1 in liver increased glucose production and the

transcription of genes encoding gluconeogenic enzymes. In addition Heizig et al. (86)

provided evidence that the metabolic effects of cAMP in the liver may be mediated

through PGC-1. Furthermore studies have shown that the nuclear transcription factor

hepatocyte nuclear factor-4 (HNF-4) acts together with PGC-1 to increase the

transcription of PEPCK (85). Transcription factors function through the docking of

specific coactivitors or corepressors proteins. Recently Koo et al. (87) identified the

transcriptional regulator TORC2 (Transducer of regulated CREB activity 2) as an

important component of the gluconeogenic gene regulation (87; 88). Furthermore,

glucagon has been shown to activate glucose-6-phosphatase activity (89). Hornbuckle et

al. (90) have shown that glucagon increased the G-6-Pase activity by selectively

stimulating the transcription of the G-6-Pase catalytic subunit but not the G-6-Pase

transporter and they found that the effect is cAMP dependent (90).

In addition glucagon via cAMP and PKA enhances the phosphorylation of

pyruvate kinase and phosphofructokinase and decreases intracellular levels of fructose-2,

6-P2, resulting in the inhibition of glycolysis (61; 91). Fructose-1, 6-P2ase catalyzes the

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hydrolysis of the C-1 phosphate in fructose 1, 6-P2 into fructose 6-P. Fructose-1, 6-P2ase

is allosterically inhibited by fructose 2, 6-P2. The levels of fructose 2, 6-P2 are regulated

by the hepatic bifunctional enzyme, 6PF-2-K/Fru-2, 6-P2ase. Studies have shown that

upon glucagon stimulation, activated PKA phosphorylates, 6PF-2-K/Fru-2, 6-P2ase in the

liver at serine-32, leading to the inhibition of the kinase and activation of the

phosphatase. This in turn reduces the intracellular levels of the fructose-2, 6-P2, thereby

relieving the inhibition of fructose-1, 6-P2ase and stimulating gluconeogenesis (91-93).

Phosphofructokinase is allosterically activated by fru-2,6-P2ase therefore the

activated PKA by reducing the levels of the biphosphate also causes the inhibition of the

phosphofructokinase (92; 94). In addition, glucagon inhibits pyruvate kinase due to the

PKA phosphorylation and it also inhibits transcription of the pyruvate kinase gene and

increases the degradation of pyruvate kinase mRNA (92; 95).

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Figure 1.1: Glucagon receptor-signaling pathway

(cAMP) Adenosine 3’,5’-cyclic monophosphate; (PKA) protein kinase A; (GS) Glycogen Synthase; (GPK) Glycogen Phosphorylase Kinase; (GP) Glycogen Phosphorylase; (I-1) Inhibitor 1; (PP1) Protein Phosphatase 1; (PGC-1) Peroxisome Proliferator-Activated Receptor-γcoactivator; (PEPCK) Phosphoenolpyruvate Carboxykinase; (G-6-Pase) Glucose-6-Phosphatase; (PFK-2/F2,6P2ase) 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase; (PK) L-type pyruvate kinase; (PLC) Phospholipase C; (PIP2) Phosphatidylinositol 4,5-biphosphate; (PIP3) Posphatidylinositol 3,4,5 trisphosphate; (CREB) cAMP Responsive element binding protein; (TORC2) Transducer of regulated CREB activity 2. From reference (70).

CREB TORC2CREB TORC2CREB TORC2

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Insulin action and signaling

Insulin has a wide variety of physiologic effects in different tissues. Insulin

stimulates cell growth and differentiation and promotes the storage of substrates in fat,

liver and muscle by stimulating lipogenesis, glycogen synthesis and protein synthesis and

by inhibiting lipolysis, glycogenolysis, gluconeogenesis and protein breakdown (96). It

has been known for many years that increasing plasma insulin levels results in an

inhibition of glucose production. In addition, there was a dose-dependent relationship

between hepatic sinusoidal insulin levels and glucose production (52; 53).

Insulin rapidly inhibits hepatic glucose production, but it requires several hours

(~3 hours) to reach its steady state effect (97). A number of investigators have studied

the ability of insulin to inhibit glycogenolysis and gluconeogenesis. In vitro studies have

shown that insulin represses gluconeogenesis by inhibiting PEPCK and G-6-Pase gene

transcription (61; 98) More recently Hall et al. (99) found that addition of insulin to

dexamethasone-treated cells results in a rapid dissociation of the glucocorticoid receptor,

polymerase II, and other transcriptional regulators from the PEPCK and G-6-Pase gene

promoter. They suggested that insulin caused the demethylation of arginine-17 on

histone H3 of both genes, leading to the reduction in gene transcription of both genes.

On the other hand in vivo studies performed in humans and dogs have shown that the

effect of insulin in gluconeogenesis is minimal and that its main effect comes about

through an inhibition of glycogenolysis (100; 101). Edgerton et al. (101) conducted

studies in overnight fasted conscious dogs in which they used three different methods to

determine gluconeogenesis and glycogenolysis. They found that the liver glycogenolysis

is markedly sensitive to small changes in insulin whereas the gluconeogenic flux is not.

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For many years insulin was thought to decrease hepatic glucose production by a

direct interaction with its hepatic receptor. That was until in 1987 when Prager et al.

(102) suggested that the hormone can suppress glucose production through indirect

actions. In these studies carried out using insulin-resistant obese subjects insulin was

infused peripherally in the presence of euglycemia and hepatic glucose production was

suppressed by 82%. There was a decrease in endogenous insulin secretion in response to

peripheral insulin infusion such that portal insulin levels were calculated to have changed

minimally. Thus the authors concluded that indirect effects of the hormone caused the

inhibition of glucose production since the insulin level at the liver did not change

appreciably (102). This concept has subsequently been supported by others (103; 104)

but the indirect mechanisms by which insulin suppresses hepatic glucose production was

probably best demonstrated in a study performed by Sindelar et al (105). The authors

used overnight fasted conscious dogs to investigate the mechanism of a selective increase

in either peripheral or portal insulin in changing hepatic glucose production. A selective

rise of 14µU/ml in either the arterial insulin or portal insulin was associated with a

decrease in NHGO of ~ 50%. Even though the extent to which insulin inhibited hepatic

glucose production was similar in both groups, the time required for the inhibition and

the mechanism for the inhibition was markedly different. The response of the liver to a

selective increase in portal insulin (direct action) was observed at 15 minutes and it was

attributable to an inhibition in glycogenolysis. On the other hand, the response of the

liver to a selective rise in arterial insulin (indirect action) occured slowly (~ 1 hour) and

resulted from the suppression of hepatic gluconeogenic precursor uptake secondary to a

reduction in gluconeogenic amino acid flux from muscle and glycerol from adipose tissue

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and from the redirection of glycogenolytic carbon to lactate due to a decrease in NEFA

levels (105; 106). Therefore, insulin inhibits hepatic glucose production by directly

inhibiting glycogenolysis and indirectly by inhibiting net gluconeogenic flux and

lipolysis.

In addition to insulin’s indirect effects in the muscle and fat, it has been reported

that insulin can inhibit the alpha cell leading to inhibition of glucagon secretion. In

unpublished data from our laboratory a rise of insulin of ~ 20µU/ml resulted in a decrease

in glucagon to ~15pg/ml. In addition, in perfused pancreas from rats a retrograde

infusion of ~0.3mU/ml of insulin significantly inhibit glucagon secretion (107). Recent

investigations have provided some insight into the possible mechanisms by which insulin

inhibits glucagon secretion. It appears that insulin increases α-cell KATP channel activity

in PI-3K dependent manner thus resulting in hyperpolarization of the membrane and

inhibition of α-cell electrical activity and glucagon secretion (108; 109). Another

mechanism proposed recently, involves the GABA-GABAA receptor system. Insulin has

been reported to activate GABAA receptors in the α-cells through receptor translocation

via an AKT kinase-dependent pathway, leading to hyperpolarization and ultimately

inhibition of glucagon secretion (110). In any event any insulin induced decrease in

glucagon levels would reduce glucose production by the liver.

Furthermore, it has been suggested that insulin’s action in the brain may explain

part of insulin’s indirect actions in the liver. Studies performed by Davis et al. have

shown that the brain can sense circulating insulin levels (111). It is also known that the

brain provides neural drive to the liver (112). Most recently, Obici et al. (113) showed

that infusion of insulin into the third ventricle in six hour fasted conscious rats resulted in

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suppression of glucose production. They also showed that blockade of the insulin

receptor using an antisense oligonucleotide injection into the hypothalamus impaired the

ability of a rise in plasma insulin to inhibit hepatic glucose production. Thus they

concluded that hypothalamic insulin signaling could be important to the action of insulin

on the liver. On the other hand, Edgerton et al. (114) carried out a study to determine the

effect of a 4-fold rise in the head insulin on hepatic glucose production during peripheral

hyperinsulinemia and hepatic insulin deficiency in overnight fasted conscious dogs.

They found that an acute 4-fold rise of insulin in the head did not reduce hepatic glucose

production. Furthermore, they demonstrated that the direct effects of insulin on hepatic

glucose production are dominant. The different results obtained in these studies might be

explained by the differences between the animal model used (rodents and dogs) and acute

effects vs. chronic effects of insulin. The glucose production rate is much greater in the

rodents compared to the dog or human. The hepatic glucose production rate of a rat or

mouse is ~12 and 20 mg/kg/min, respectively, whereas in the dog or human it is ~2-

3mg/kg/min. . It is conceivable that this might result in the existence of higher neural

drive to the liver in the rodent than in the dog or human (115; 116). Furthermore, it is

possible that an acute increment in insulin is not able to acutely regulate hepatic glucose

production via an action on the brain whereas a chronic rise in insulin might be able to

(115; 116).

Insulin exerts its effect by binding to the insulin receptor. The insulin receptor

(IR) is a tetrameric protein that consists of two extracellular α-subunits and two

intracellular β-subunits linked together by disulfide bonds. It belongs to a subfamily of

receptor tyrosine kinases which also includes the insulin growth factor-1 receptor

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(IGF1R) and IR-related receptor (IRR) (117). Binding of insulin to the α-subunit induces

a conformational change resulting in the autophosphorylation of several tyrosine residues

present in the β-subunit (96; 118). These residues are recognized by phosphotyrosine-

binding (PTB) domains of adaptor proteins such as members of the insulin receptor

substrate family (IRS), Gab-1, Shc and Cbl. (96; 118; 119). Upon tyrosine

phosphorylation, these proteins interact with signaling molecules through their SH2

domains. This results in the activation of PI 3-Kinase and downstream PtdIns(3,4,5)P3,

ras, MAP kinase cascade, Cbl/CAP and TC10 (96). Cbl/CAP and TC 10 are involved in

stimulation of glucose uptake and GLUT4 translocation. The MAPK pathway regulates

the expression of some genes and cooperates with the PI3K pathway to control cell

growth and differentiation. The PI 3-kinase pathway is responsible for the metabolic

aspects of insulin action. For the purpose of this thesis we will focus on the PI-3K

pathway.

The metabolic effects of insulin are mediated through downstream effectors of

Phosphoinositide 3-kinase (PI3K), atypical protein kinase (aPKC) and Protein Kinase B

(PKB) or Akt. Previous studies have reported that the increase in plasma insulin that

follows a carbohydrate meal results in a decreased transcription and translation of

PEPCK in vitro (61; 120). In addition, studies have shown that insulin represses G-6-

Pase gene expression in vitro and in vivo (121; 122). Furthermore, overexpression of the

catalytic subunit of PI 3-kinase is sufficient to markedly inhibit PEPCK and G-6-Pase

gene expression (123). In addition more recently studies conducted by Dentin et al. (124)

have reported that insulin inhibits the gluconeogenic gene expression during re-feeding

by promoting the phosphorylation and degradation of TORC2, a cAMP-responsive

21

CREB coactivator. All together these effects of insulin on gluconeogenic gene

expression contribute to the reduction in gluconeogenesis seen after the ingestion of a

carbohydrate meal.

After a carbohydrate meal, insulin stimulates glycogen synthesis and inhibits

glycogen breakdown. Glycogen synthase, an enzyme that catalyzes the rate-determining

step in glycogen synthase, is regulated by insulin through changes in phosphorylation.

Insulin activates glycogen synthase by promoting its dephosphorylation via the inhibition

of GSK-3 (96). This results in the inactivation of GSK-3 and in the disinhibition of

glycogen synthase, leading to an increase in glycogen synthesis. In addition, PP1 also

reduces GSK-3 activity and inhibits glycogen phosphorylase, a key enzyme in glycogen

breakdown (96). In addition, insulin stimulates PDE3B which promotes the degradation

of cAMP in the liver. The reduction in cAMP results in decreased activation of PKA and

a subsequent decrease in glycogenolysis in the liver (91; 125-127).

In addition, PI3K is an upstream regulator of mTOR (mammalian target of

rapamysin) which is a central regulator of ribosome biogenesis, protein synthesis, cell

growth. mTOR controls the translation machinery, in response to aminos acids and

growth factors via activation of p70 ribosomal S6 Kinase and inhibition of eIF-4E

binding protein (128). Therefore, insulin effects on GSK-3, PP1, mTOR and PDE inhibit

glucose production, promote glycogen, FFA, protein and triglycerides synthesis, all

together, opposing glucagon’s action.

22

Figure 1.2. Insulin-receptor signaling pathway Insulin receptor substrate family (IRS), Gab-1, Shc and Cbl. Phosphoinositide 3-kinase (PI3K); atypical protein kinase (aPKC); Protein Kinase B (PKB) or Akt; mammalian target of rapamysin (mTOR); Protein Phosphatase 1 (PP1); Glycogen Synthase Kinase 3 (GSK-3). From reference (96).

cAMP5’-AMP PDE3

mTORcAMP5’-AMP PDE3

mTOR

23

Insulin and glucagon interaction

Insulin and glucagon are potent regulators of carbohydrate metabolism and their

interaction is usually the main determinant of gluconeogenic and glycogenolytic flux in

the liver. After an overnight fast, glucagon plays a major role in stimulating hepatic

glucose production while insulin acts as a potent inhibitor of the process. Glucagon can

be considered to provide the positive drive to the liver which allows insulin to exert its

controlling effects on glucose production.

In response to carbohydrate ingestion, insulin secretion increases whereas

glucagon secretion decreases (52; 53). These changes in hormone secretion, along with

the hyperglycemia that results from the glucose load and the portal glucose signal, inhibit

hepatic glucose production and convert the liver to net glucose consumtion (53; 129).

Insulin is an anabolic hormone that promotes storage of substrates in fat, liver and

skeletal muscle by stimulating triglyceride, glycogen and protein synthesis, and inhibiting

lipolysis, and glycogen and protein breakdown (130)

Furthermore, Steiner at al. (131) has previously examined the interaction between

insulin and glucagon in controlling glucose production using a pancreatic clamp in the

conscious dog. A constant replacement of basal amounts of insulin and glucagon did not

change glucose production. A selective four-fold rise in glucagon resulted in an

increment in glucose production of ~4.5 mg/kg/min at 30 minutes. In contrast, a

selective four-fold rise in insulin resulted in a decrement in glucose production of ~1.3

mg/kg/min at 30 minutes. When both hormones were simultaneously increased fourfold,

the decrement in glucose production at 30 minutes was only ~0.6 mg/kg/min. Therefore,

glucagon’s effect was 4.5 mg/kg/min in the presence of basal insulin despite a developing

24

hyperglycemia and only 0.7 mg/kg/min in the presence of high insulin, a reduction of

almost 85%. Consequently, insulin dominates glucagon’s action on the liver even if the

increments are equimolar (131). This was not the case in the presence of hypoglycemia

as seen in another previous study (18). A 6 fold rise in glucagon (Δ140 pg/ml)

significantly increased glucose production (Δ 4.5 mg/kg/min) in the presence of

hypoglycemia despite an arterial insulin level that was increased 20 fold (Δ328 µU/ml).

Therefore, glucagon appears to be more effective during hypoglycemia than during

euglycemia, despite dramatically increased insulin levels.

Despite the fact that previous studies have suggested that the liver is more

sensitive to glucagon during hypoglycemia, a direct comparison of the effects of a

controlled rise in glucagon on glucose production in the presence of euglycemia versus

hypoglycemia has never been carried out. Therefore, the aim of this work was to

examine the interaction of a selective rise in insulin and glucagon in controlling hepatic

glucose production under euglycemic and hypoglycemic conditions.

25

CHAPTER II

MATERIALS AND METHODS

Animal Care

Studies were conducted on twenty-four 18 h fasted conscious mongrel dogs (18-

25 kg) of either sex that had been fed a standard diet of meat (Kal Kan, Vernon, CA) and

chow (Purina Lab Canine Diet No. 5006; Purina Mills, St. Louis, MO) composed of 34%

protein, 14.5% fat, 46% carbohydrate, and 5.5% fiber based on dry weight (1500

kilocalories). Water was available at all times. Only dogs that had good appetite, a

leukocyte count < 18,000/mm3, a hematocrit >35%, and normal stools were used for

studies. The animals were housed in a facility which met the American Association for

Accreditation of Laboratory Animal Care guidelines, and the protocol was approved by

the Vanderbilt University Medical Center Animal Care Committee.

Surgical Procedures

Approximately 16 days prior to the metabolic study, surgery was performed on

each dog while it was under general anesthesia. Anesthesia was induced with propofol

(given until induction) preceded by buprenorphine HCl (0.02 mg/kg, presurgery) 30 min

earlier. Anesthesia was maintained by isoflurane (1.5-2.0% with oxygen) inhalation. The

dog was placed in a supine position on a surgical table with an 8.5 mm inner diameter

(ID) endotracheal tube (Concord/Protex, Kenee, NH), and ventilated with a tidal volume

of 400 ml at 14 breaths per minute.

26

A laparotomy was performed by making a midline incision 1.5 cm caudal to the

xyphoid process through the skin, subcutaneous layers and linea alba, and extending

caudally 15-20 cm. Silastic catheters (0.03 in ID; HelixMedical, Carpintera, CA) were

placed in the following manner: A portion of the jejunum was exposed and a branch of a

jejunal vein was selected for cannulation. A small section of the vessel was exposed by

blunt dissection and ligated with 4-0 silk (Ethicon, Inc, Sommerville, NJ). A silastic

infusion catheter was inserted into the vessel through a small incision and passed

antegrade until the tip of the catheter lay approximately 1 cm proximal to the coalescence

of two jejunal veins. Another silastic catheter was inserted into a distal branch of the

splenic vein and advanced until the tip of the catheter lay 1 cm beyond the bifurcation of

the main splenic vein. The catheters were secured in place with 4-0 silk.

For blood sampling, silastic catheters (0.04 in ID) were placed into the left hepatic

vein, the hepatic portal vein and left femoral artery. The central and left lateral lobes of

the liver were retracted cephalically and caudally, respectively. The left common hepatic

vein and the left branch of the portal vein were exposed. A 14-gauge angiocath (Benton

Dickinson Vascular Access, Sandy, UT) was inserted in the left branch of the portal vein

2 cm from the central liver lobe. A silastic catheter (0.04 in ID) was inserted into the hole

created by the angiocath, advanced retrograde about 4 cm into the portal vein so that the

tip of the catheter lay 1 cm beyond the bifurcation of the main portal vein. It was then

secured with three ties of 4-0 silk through the adventitia of the vessel and around the

catheter. An angiocath was inserted into the left common hepatic vein 2 cm from its exit

from the left lateral lobe. A silastic sampling catheter was inserted into the hole and

passed antegrade 2 cm and secured into place with three ties of 4-0 silk suture.

27

For sampling of arterial blood, a catheter was inserted into the left femoral artery

following a cut-down in the left inguinal region. A 2 cm incision was made parallel to

the vessel. The femoral artery was isolated and ligated distally. A silastic catheter (0.04

in ID) was inserted and advanced 16 cm in order to place the tip of the catheter in the

abdominal aorta. It was then secured into place with 4-0 silk suture.

All catheters were filled with normal saline (Baxter Healthcare Corp, Deerfield,

IL) containing 200 U/ml heparin (Abbott Laboratories, North Chicago, IL) and knotted.

Abdominal catheters were secured to the abdominal wall and placed in a subcutaneous

pocket prior to closure of the skin. The arterial sampling catheter was also placed in a

subcutaneous pocket prior to closure of the skin.

Ultrasonic flow probes (Transonic System Inc, Ithaca, NY) were positioned

around the hepatic artery and portal vein, to determine liver blood flow during

experiments. The duodenum was retracted laterally to expose a section of the hepatic

artery and portal vein. A small section of the portal vein was exposed by blunt dissection,

taking care not to disturb the nerve bundle located on the vessel. A 6 or 8 mm ID

ultrasonic flow probe (Transonic Systems Inc, Ithaca, NY) was placed around the vessel.

A small portion of the common hepatic artery was also carefully exposed and a 3 mm ID

ultrasonic flow probe was secured around the vessel. To prevent blood from entering the

portal vein beyond the site of the flow probe, the gastroduodenal vein was isolated and

ligated. Blood that would normally flow through the gastroduodenal vein was shunted

through the caudal pancreatoduodenal vein draining the tail of the pancreas. The

ultrasonic flow probe leads were positioned in the abdominal cavity and secured with the

ends of the catheters to the abdominal wall.

28

After all abdominal surgeries, the subcutaneous layer was closed with a

continuous suture of 2-0 chromic gut (Ethicon, Inc.). The skin was closed with

horizontal mattress sutures of 3-0 Dermalon (Ethicon, Inc.). Immediately following

surgery, the dogs received an intramuscular injection of penicillin G (106 U, Procaine;

Anthony Products, Irwindale, CA) to minimize the possibility of infection. In addition,

Flunixin (Meglumine 50mg/ml; Phoenix Scientific, Inc., St. Joseph, MO) was injected

intramuscularly (1 mg/kg body weight) after wound closure for acute pain relief.

Animals awoke from surgery within 2 h, were active, and ate normally approximately 8 h

after surgery. Post-operatively, each dog also received 500 mg ampicillin (Principen;

Bristol-Myers Squibb, Princeton, NJ) orally twice a day for 3 days.

Experimental Procedure

On the day of the experiment following an 18h fast, the free ends of the catheters

and ultrasonic leads were removed from their subcutaneous pockets under local

anesthesia (2% lidocaine; Abbott Laboratories, North Chicago, IL). The contents of each

catheter were aspirated, and they were flushed with saline. Blunt needles (18 gauge;

Monoject, St. Louis, MO) were inserted into the catheter ends and stopcocks (Medex,

Inc, Hilliard, OH) were attached to prevent the backflow of blood between sampling

times.

Twenty gauge Angiocaths (Beckton Dickson) were inserted percutaneously into

the left and right cephalic veins and into a saphenous vein for the infusion of

somatostatin, tracers, dye and glucose. A continuous infusion of heparinized (1U/ml;

Abbott Laboratories, North Chicago,IL) normal saline was started via the femoral artery

29

at a rate to prevent any clotting in the line. Animals were allowed to rest quietly in a

Pavlov harness for at least 100 min before the start of the experiment.

Experimental Design

The study included four groups of animals: saline-euglycemia (SE), saline-

hypoglycemia (SH), glucagon-euglycemia (GE) and glucagon-hypoglycemia (GH). Each

experiment consisted of equilibration (-140 to -40 min), basal (-40 to 0 min) and

experimental (0 to 180 min) periods (Figure 2.1). At -140 min a priming dose of [3-3H]

glucose (33 µCi) was given, followed by a constant infusion of [3-3H] glucose

(0.35µCi/min) and indocyanine green (0.08 mg/min). The equilibration period was

followed by a control period and an experimental period which was divided into period 1

(0-60 min) and period 2 (60-180 min). In period 1, somatostatin (0.8µg/kg/min) and

intraportal insulin (5.0 mU/kg/min) were infused and glucose was monitored every five

minutes in order to maintain euglycemia using glucose infusion through the saphenous

vein as required (20% Dextrose). In period 2, the somatostatin and insulin infusions were

continued and in addition either glucagon (2.3ng/kg/min) or saline were infused

intraportally. Glucose was infused as required to bring about euglycemia (~100 mg/dl) or

hypoglycemia (~50 mg/dl).

30

Figure 2.1: Experimental Design

Po Glucagon (2.3 ng/kg/min) or Saline

Euglycemia

Hypoglycemia


180-40 min 0 60CP P2P1

Pe Somatostatin (0.8 g/kg/min) + Po Insulin (5.0 mU/kg/min)

Pe Glucose(Euglycemia)

[3-3H]-Glucose (0.35µCi/min) + Indocyanine Green (0.08 mg/min)

SAL + EU (n=6)

GGN + EU (n=6)

SAL + HYPO (n=6)

GGN + HYPO (n=6)

Pe - Peripheral; Po - PortalCP - Control Period P1 - Period 1; P2 - Period 2


Euglycemia

Hypoglycemia


180-40 min 0 60CP P2P1

Pe Somatostatin (0.8 g/kg/min) + Po Insulin (5.0 mU/kg/min)

Pe Glucose(Euglycemia)

[3-3H]-Glucose (0.35µCi/min) + Indocyanine Green (0.08 mg/min)

SAL + EU (n=6)

GGN + EU (n=6)

SAL + HYPO (n=6)

GGN + HYPO (n=6)

Pe - Peripheral; Po - PortalCP - Control Period P1 - Period 1; P2 - Period 2 Pe - Peripheral; Po - PortalCP - Control Period P1 - Period 1; P2 - Period 2

31

Collection and Processing of Samples

Blood samples were drawn from the femoral artery and portal and hepatic veins at

the predetermined time points. Additionally, whenever the experimental design required

a glucose clamp, small (~0.5 ml) arterial samples were drawn every 5 min to facilitate

maintenance of the plasma glucose concentration. Before samples were taken, the

sampling catheter was cleared by withdrawing 5 ml of blood into a syringe. After

sampling, this blood was re-infused and the catheter was flushed with heparinized saline

(1 U/ml; Abbott Laboratories, North Chicago, IL). The total volume of blood withdrawn

did not exceed 20% of the animal’s blood volume, and two volumes of normal saline

(0.9% sodium chloride; Baxter Healthcare Co., Deerfield, Il) were given for each volume

of blood withdrawn. No significant decrease in hematocrit occurred throughout duration

of study.

Before the experiment started, an arterial blood sample was drawn and

centrifuged (3000 rpm for 7 min). The plasma from this blood sample was used to

prepare hormone infusates and the indocyanine green standard curve. When samples

were taken from all vessels, the arterial and portal blood samples were collected

simultaneously ~30 s before the collection of the hepatic vein samples in an attempt to

compensate for the transit time through the liver, and thus allow for the most accurate

estimates of net hepatic substrate balance (132).

Immediately following each sample collection, the blood was processed. A 20 l

aliquot of arterial whole blood was used for the immediate duplicate measurement of

hematocrit using capillary tubes (0.4 mm ID; Drummond Scientific Co., Broomall, PA).

One ml of the collected blood was placed in a tube containing 20µl of 0.2M glutathione

32

(Sigma Chemical Co.) and 1.8mg EGTA (Sigma Chemical Co.) for catecholamine

measurements. This tube was vortexed, centrifuged at 3000 rpm for 7 minutes, and the

supernatant was stored in a separate tube for later analysis. The remaining blood was

placed into tubes containing potassium ethylenediaminetetraacetate (EDTA, 1.6 mg/ml;

Sarsdedt, Newton, NC), inverted and gently mixed. One ml aliquot of whole blood was

lysed with 3 ml of 4% perchloric acid (PCA; Fisher Scientific, Fair Lawn, New Jersey),

centrifuged and the supernatant was stored for later analysis of metabolites levels (lactate,

alanine, -hydroxybutyrate and glycerol). The remainder of the whole blood was

centrifuged at 3000 rpm at 4º C to obtain plasma.

The plasma samples were used for all other measurements. Glucose

concentrations were immediately determined from four 10 l aliquots of plasma using the

glucose oxidase method with a glucose analyzer (Beckman Instruments, Fullerton, CA).

A 1 ml aliquot of plasma received 50 l of 10,000 KIU/ml Trasylol (FBA

Pharmaceuticals, New York, NY) and was stored for analysis of glucagon. Insulin, [3H]-

glucose, free fatty acids and cortisol were measured from aliquots of plasma (1.0, 1.0, 0.5

and 0.5 ml respectively) The arterial and hepatic insulin samples were used for

measurement of indocyanine green, as will be described later, and then frozen at -70ºC

until insulin was measured. After each sample was processed, it remained on wet ice for

the remainder of the experiment and was then stored at -70º C until analysis was

performed.

Following the study, the plasma samples for [3H]-glucose measurement were

deproteinized by stepwise addition of 5 ml of 0.067 N Ba(OH)2 and 5 ml 0.067 N ZnSO4

33

(Sigma Chemical Co.). These samples were then stored at 4ºC for 1-3 days and then

processed.

Sample Analysis

Plasma Glucose

Plasma glucose concentrations were determined during the experiment using the

glucose oxidase method (133) with a Beckman glucose analyzer (Beckman Instruments,

Fullerton, CA). The reaction sequence was as follows:

Glucose Oxidase ß-D-glucose + O2 ---------------------------► gluconic acid and H2O2 (1) Catalase H2O2 + ethanol ---------------------------► acetaldehyde + H2O (2) Molybdate H2O2 + 2H+ +2I- ---------------------------► I2 + H2O (3)

The glucose concentration is proportional to the rate of oxygen consumption. The

plasma glucose concentration in a sample (10 l) is determined by comparison of the

oxygen consumption in the samples with the rate of oxygen consumption by a standard

solution (150 mg/dl). There is no end-product inhibition of the process, as reactions 2 &

3 remove all of the hydrogen peroxide. Thus virtually all of the glucose in the sample is

consumed. Glucose was measured 4 times at each sampling time point for each vessel

and a minimum of 2 times for samples drawn to clamp glucose. The glucose analyzer is

accurate to 450 mg/dl.

34

Plasma [3-3H] glucose

Plasma [3-3H] glucose was measured from the samples deproteinized according to

the method of Somogyi-Nelson (134-136) involving addition of Ba(OH)2 and ZnSO4 as

described under Collection and Processing of Samples. After incubation of 1-3 days, the

samples were centrifuged at 3000 rpm for 20 min. A 5 ml aliquot of the supernatant was

pipetted into a glass scintillation vial and placed in a heated vacuum oven to evaporate all

water (hence removing 3H2O). The residue was reconstituted in 1 ml of deionized water

and 10 ml liquid scintillation fluid (EcoLite (+); Research Product Division, Costa Mesa,

CA), and placed in Beckman LS 9000 Liquid Scintillation Counter (Beckman

Instruments Inc, Irvine, CA) for counting. The scintillation counter was programmed so

that the processor corrected the counts per minute (cpm) for quenching of the

radioactivity in the sample and presented the results as disintegrations per minute (dpm).

To assess the loss of radioactive glucose during the deproteinization process, a

recovery standard was prepared. The [3-3H]glucose infusate was diluted 1:250 (vol:vol)

with saturated benzoic acid containing 1 mg/ml cold glucose. Six 1 ml aliquots of this

diluted 3H infusate were placed into 2 sets of glass scintillation vials labeled as chemical

standard evaporated (CSE) or chemical standard (CS); therefore CSE and CS were

measured in triplicate. The diluted infusate aliquots in the CSE vials were evaporated to

dryness (with plasma samples) in a heated vacuum oven and reconstituted with 1 ml

deionized water. The diluted infusate aliquots in the CS were not evaporated.

Scintillation fluid (10 ml) was added to all standard vials and the standards were counted.

Three additional 1 ml aliquots of diluted 3H infusate were treated identical to the plasma

samples and labeled chemical recovery standard (CRS). Comparison of the CS and CSE

35

provided an evaluation of the loss of 3H counts in the evaporation process. The final

amount of radioactivity per sample was determined by generating a recovery factor (ratio

of radioactivity in the CSE compared to CRS) which accounted for the radioactivity lost

during sample processing.

Plasma Fatty Acids (FFAs)

Plasma fatty acids were determined spectrophotometrically using the Packard Multi

Probe Robotic Liquid Handling system (Perkin Elmer;Shelton, CT) and a kit from Wako

Chemicals (Richmond, VA). In the presence of acyl-Coenzyme A (CoA) synthase, CoA

is acylated by the fatty acids within the plasma sample. The acyl-CoA produced is

oxidized by acyl CoA oxidase, resulting in the production of H2O2. The addition of

peroxidase, in the presence of H2O2, subsequently allows for oxidative condensation of 3-

methyl-N-ethyl-N-(β-hydroxyethyl)-aniline with 4-aminoantipyrine (4-AAP) to form a

purple colored adduct. The purple color adduct was measured at an optical density of

550 nm and is proportional to the plasma FFA concentration in the sample. The FFA

concentrations were calculated using a calibration curve of known amounts of oleic acid.

The assay was run at 37ºC. The specific reactions were as follows:

Acyl-CoA Synthetase FFA + ATP + CoA ---------------------------►Acyl-CoA + AMP + Ppi (4)

Acyl-CoA Oxidase Acyl-CoA + O2 ---------------------------► 2,3-trans-enoyl-CoA + H2O2 (5)

2 H2O2 + 3-methyl-N-ethyl-N-(β-hydroxyethyl)-aniline + 4-AAP Peroxidase ---------------------------► Purple colored adduct (6)

36

Metabolites

Whole blood concentrations of lactate, alanine, β-hydroxybutyrate (BOHB) and

glycerol were determined using the methods developed by Lloyd et al. (137) for the

Technicon Autoanalyzer (Tarrytown, NY) and were modified for the Packard Multi

Probe Robotic Liquid Handling System (Perkin Elmer; Shelton, CT). Enzymes and

coenzymes for metabolic analyses were obtained from Boehringer-Mannheim

Biochemicals (Germany) and Sigma Chemicals. The reduced form (NADH) has a native

fluorescence, which is not exhibited in the oxidized form. Excess amounts of NAD and

enzyme/coenzyme are added to the metabolite samples. NAD is reduced to NADH upon

oxidation of the metabolite. A fluorometer incorporated in the system detects changes in

fluorescence resulting from changes in NADH concentration; therefore, the concentration

of the metabolite present is proportional to the NADH produced.

Metabolites were measured in the PCA-treated blood samples as described above.

A standard curve was constructed for each metabolite using known concentrations of the

analyte prepared in 3% PCA. The Packard Multi Probe Robotic Liquid Handling System

pipettes the sample into one well of the 96-well plate. After an initial absorbance is read,

the Packard Multi Probe Robotic Liquid Handling System pipettes enzyme solution into

each well and shakes the plate to mix sample and enzyme. The reaction proceeds and

after an allotted time, the change in absorbance is determined. All assay reactions are

reversible, with the exception of glycerol kinase. The NAD and enzyme are in excess

compared to the substrate, thus the reactions are essentially taken to completion and the

rate-limiting component is the substrate; therefore, all reactions below are written with a

single direction arrow. All reactions are carried out at 23°C.

37

Lactate

The lactate assay involved the following reaction:

Lactate Dehydrogenase Lactate + NAD+ ---------------------------► Pyruvate + NADH + H+

(7)

The enzyme buffer used was 0.24 M glycine and 0.25 M hydrazine dihydrochloride and 7

mM disodium EDTA, pH 9.6. To 10 ml of enzyme buffer, 4.6 mg NAD and 0.1 U lactate

dehydrogenase were added.

Alanine

The alanine assay involved the reaction:

Alanine Dehydrogenase L-alanine + NAD+ + H2O ---------------------------► Pyruvate + NADH + NH4

+ (8)

The enzyme buffer used was 0.05 M trizma base, 2 mM EDTA and 1 mM hydrazine

hydrate, pH 10. To 10 ml of enzyme buffer, 4.6 mg of NAD and 3.4 Units (U) of alanine

dehydrogenase were added.

ß-hydroxybutyrate

The ß-hydroxybutyrate analysis involved the following reaction:

3-hydroxybutyrate dehydrogenase

ß-hydroxybutyrate + NAD+ ---------------------------► Acetoacteate + NADH + H+ (9)

38

The enzyme buffer was 0.2 M monopotassium phosphate, 3 mM EDTA and 1 mM

hydrazine hydrate, pH 8.5. To 10 ml of enzyme buffer, 12 mg NAD and 2.1 U ß-

hydroxybutyrate dehydrogenase were added.

Glycerol

The glycerol assay involved the following reactions:

Glycerokinase Glycerol + ATP ---------------------------► Glycerol-l-phosphate + ADP (10)

Glycerol-3-phosphate dehydrogenase

L-glycerol-l-phosphate + NAD+ ------------------------------------------------► dihydroxyacetone phosphate + NADH + H+

(11)

The enzyme buffer was 0.09 M glycine, 1 mM hydrazine, and 0.01 M MgC12, pH 9.5. To

10 ml of the enzyme buffer, 15.4 g NAD, 15.4 mg ATP, 0.3 U glycerokinase, and 0.6 U

glycerol-3-phosphate dehydrogenase were added.

Hormones

The plasma levels of insulin, glucagon, and C-peptide were measured using

radioimmunoassay (RIA) techniques (138). In general, a sample containing an unknown

amount of hormone was incubated with an antibody specific for that hormone. A known

amount of radiolabeled hormone was added to the mixture to compete with the antibody

binding sites. A double antibody procedure which caused precipitation of the bound

complex was used to separate unbound hormone from the antibody-hormone complexes.

The radioactivity of the precipitate was measured via a Cobra II Gamma Counter

39

(Packard Instrument Co., Meriden, CT). Binding of the radiolabeled hormone is

inversely proportional to the amount of unlabeled hormone present, and a standard curve

was constructed using known concentrations of unlabelled hormone.

Insulin

Immunoreactive plasma insulin was measured using a double-antibody RIA

procedure (139). A 100 µl aliquot of the plasma sample, 200 l of 125I-labeled insulin,

and 100 ml of guinea pig specific antibody to insulin (both from Linco Research, Inc., St.

Charles, MO.) were mixed and incubated for 18 h at 4°C. The sample was then treated

with 100 µl goat anti-guinea pig IgG (2nd antibody) and 100 µl IgG carrier and incubated

for 30 min at 4°C. One ml of a wash buffer was added and the tubes were centrifuged at

3000 rpm. The samples were decanted and the portion of total radioactivity bound to the

antibody (pellet) was counted in a Cobra II Gamma Counter (Packard Instrument Co,

Meriden, CT).

The log of the amount of hormone in the sample was inversely proportional to the

log of bound 125I-labeled insulin to free 125I-labeled insulin. The insulin concentration in

each sample was determined by comparison to a standard curve constructed using known

amounts of unlabeled hormone. The samples were corrected for non-specific binding.

The sample detection range was 1-150 µU/ml. The specificity of the antibody is 100% to

porcine, canine, and human insulin, 90% with bovine insulin, 38% with human

proinsulin, 47 and 72% with the split proinsulin products Des 31,32 and Des 64,65,

respectively. In general, less than 15% of the basal insulin level is due to non-insulin

cross reactivity (mainly the split proinsulin products Des 31,32 and Des 64,65). There is

40

no cross reactivity to glucagon, pancreatic polypeptide, C-peptide, or somatostatin. The

recovery in the assay was between 90-100% based on spiking the sample with known

amounts of insulin, and the interassay CV was approximately 7-8% for the entire range of

the dose response curve.

Glucagon

Immunoreactive plasma glucagon was also measured using a double antibody

RIA (Linco Research, Inc., St. Charles, MO) (140). The protocol utilized primary and

secondary antibodies specific for glucagon (kit with glucagon antibodies and 125I tracers

from Linco). A 100 µl aliquot of the plasma sample and 100 µl of guinea pig specific

antibody to glucagon were mixed and incubated for 24 hours at 4oC. Next, 100 µl of 125I-

labeled glucagon was added and the solution was incubated for an additional 24 h at 4°C.

Samples were then treated with 100 µl goat anti-guinea pig IgG (2nd antibody) and 100

µl IgG carrier and incubated for 2 hours at 4°C. One ml of a wash buffer was added and

the tubes were centrifuged at 3000 rpm. The samples were decanted and the portion of

total radioactivity bound to the antibody (pellet) was counted in a Cobra II Gamma

Counter.


log of bound 125I-labeled glucagon to free 125I-labeled glucagon. Glucagon concentration

in each sample was determined by comparison to a standard curve constructed using

known amounts of unlabeled hormone. The samples were corrected for non-specific

binding, and the sample detection range was 20-400 pg/ml. The antibody is 100%

specific to glucagon with only slight (0.01 %) cross reactivity to oxyntomodulin, and no

41

cross reactivity with human insulin, human proinsulin, human C-peptide, glucagon-like

petide-1, somatostatin, or pancreatic polypeptide. A cross-reacting protein in plasma

reads in this assay and results in a glucagon stripped sample reading 15-20 pg/ml. This

represents a stable, constant background in all samples. The recovery for the assay was

between 80-109% based on spiking the sample with known amounts of glucagon, and the

interassay CV was approximately 6-10% for the entire dose response curve.

Cortisol

Immunoreactive plasma cortisol was measured with a single antibody technique

(141) using a gamma coat RIA from Diagnostics Products Corporation (Los Angeles,

CA). Twenty-five µl aliquot of plasma and 1 ml of 125I-labeled cortisol were pipetted

into a cortisol specific antibody-coated tube with an antibody immobilized on the lower

inner wall of the tube. They were incubated for 2 hours in a 31ºC water bath. Later, the

tubes were decanted and rinsed with dionized water. The tubes were allowed to dry, and

then counted in a Cobra II Gamma Counter for 4 minutes.


log of of bound 125I-labeled cortisol to free 125I-labeled cortisol. The cortisol

concentration in each sample was determined by comparison to a standard curve using

known amounts of unlabeled hormone. The sample detection range was 0.5-50 µg/dl.

The antibody is 100% specific for cortisol with only slight cross-reactivity of 6% with

11-deoxycortisol and 1% with 17-hydroxyprogesterone. In contrast, it has no cross-

reactivity with corticosterone, aldosterone, progesterone, deoxycorticosterone and

42

tetrahydrocortisone. The recovery for the assay was > 90% and the interassay CV was

approximately 8-10% for the entire range of the dose response curve.

Catecholamines

A high performance liquid chromatography (HPLC) method was used to determine

plasma epinephrine and norepinephrine levels as previously described by Goldstein et al.

(142). 400 µl of the plasma samples were partially purified by absorption to 10 mg of

acid-washed alumina (Bioanalytical Systems, West Lafayette, IN) in 600 µl of

Tris/EDTA (ph 8.6) and 50 µl of an internal standard, dihydroxybenzylamine (DHBA,

500pg/ml, Sigma Chemical Co.). Samples were then shaken for 15 minutes, centrifuged

for 4 minutes and aspirated. The alumina pellet was rinsed with 2ml of water, and then

the solution was vortexed, centrifuged and aspirated. This process was repeated 3 times.

Next, the catecholamines were eluted with 200 µl 0.1 M perchloric acid (PCA) according

to Anton and Sayre (143).

Samples were next injected onto a HR-80, reverse phase, 3µm octadecylsilane

column. The mobile phase was composed of 43 ml of methanol, 440 mg of sodium octyl

sulfate, 37 mg of sodium EDTA (ph 3.4) and 14.2 g of disodium phosphate. The system

utilized a Coulochem II Detector, Conditioning Cell (Model 5021) and Analytical Cell

(Model 5011; all obtained from ESA, Bedford, MA). Epinephrine and norepinephrine

concentrations were calculated using a linear calibration curve consisting of 5 standards

(ranging from 50-1000 pg/ml). The standards were prepared from epinephrine bitartrate

and (-)-arterenol bitartrate (norepinephrine) salts (Sigma Chemical Co.). In addition, a

known amount of epinephrine and norepinephrine were added to the sample taken at the

43

start and at the end of each experiment to evaluate recovery and to ensure precise

identification of the peaks.

In order to identify the peaks, data reduction was performed using ESA 500

Chromatograph and data station software. The ratio of the peak height of the internal

standard to the catecholamine was calculated and the concentration of catecholamine was

determined by comparison with the standard curve. The limit of detection of the assay

for epinephrine was 20 pg/ml and for norepinephrine was 5 pg/ml. Recovery of the

hormones was between 80-100%. The interassay CV for epinephrine was 3-11% and 4-

6% for norepinephrine.

Pancreatic Polypeptide

Immunoreactive plasma pancreatic polypeptide was measured using a double antibody

RIA (Linco) (140). The protocol was adapted by using primary and secondary antibodies

specific for pancreatic polypeptide (kit with pancreatic polypeptide antibodies and 125I

tracers from Linco) A 100µl aliquot of the sample was incubated for 72 h at 4ºC with

100µl of rabbit antiserum raised against bovine pancreatic polypeptide. Subsequently,

100µl 125I-labeled pancreatic polypeptide was added and the solution was incubated for

24 h at 4ºC. After 24 h, the sample was incubated with 100µl goat anti-guinea pig IgG

(2nd antibody) and 100µl IgG carrier for 6 h at 4ºC. One ml of wash buffer was added

and the tubes were centrifuged at 3000 rpm. The samples were decanted and the portion

of total radioactivity bound to the antibody (pellet) was counted in a Cobra II Gamma

Counter.

44


log of of bound 125I-labeled pancreatic polypeptide to free 125I-labeled pancreatic

polypeptide. The pancreatic polypeptide concentration in each sample was determined

by comparison to a standard curve using known amounts of unlabeled hormone. Samples

were corrected for non-specific binding, and the sample detection range was 20-1200

pg/ml. The antibody is 100% specific for human and dog pancreatic polypeptide and

there is no detectable cross-reactivity with insulin, glucagon and somatostatin. The

recovery of the assay was between 80-110%, and the interassay CV was approximately

10-15% for the entire range of the dose response curve.

Blood Flow

Blood flow in the hepatic artery and hepatic portal vein were determined using

ultrasonic flow probes implanted during surgery (as described in Surgical Procedures).

Total hepatic blood flow which is defined as the sum of blood flow in the hepatic artery

and the hepatic portal vein was also assessed using the indocyanine green (ICG) dye

method described by Leevy et al. (144). The results presented in this document were

calculated using ultrasonic determined flow. This method allows for the direct

measurement of blood flow in the hepatic artery and hepatic portal vein whereas the ICG

dye method requires an assumption of the percent contribution of each vessel to total

hepatic blood flow. ICG-determined flow was used as a backup measurement in the case

of ultrasonic flow probe failure.

Ultrasonic flow measurements represented instantaneous variations in velocity

and, therefore, provided blood flow in individual vessels of interest. Each probe

45

determined the mean transit time of an ultrasonic signal passed back and forth between

two transducers within a probe which were located upstream and downstream of the

direction of blood flow in the vessel. The transducers are made of piezoelectric material

which is capable of both receiving and transmitting the ultrasonic signal. The

downstream transducer first emits an ultrasonic pulse into the blood vessel that is

received upstream by a second transducer. After the upstream transducer receives the

ultrasonic signal, it re-emits the ultrasonic pulse signal back to the downstream

transducer. The transit time of each ultrasonic beam, as measured by the upstream and

downstream transducers (ΔTup and ΔTdown, respectively), is defined by the following

relationships:

ΔTup = D / (vo - vx ) (12)

ΔTdown = D / (vo + vx ) (13)

where D is the distance traveled by the ultrasonic beam within the acoustic window of the

probe, vo is the phase velocity, or the speed of sound, in blood, and vx is the component

of fluid velocity that is parallel or antiparallel to the phase velocity. The parallel

component augments the phase velocity when the signal is traveling in the same direction

of blood flow, while the antiparallel component is subtracted from phase velocity if the

ultrasonic signal moves against the flow of blood in the vessel. Combining the two

expressions for transit time yields the following equation:

ΔTup - ΔTdown = [D / (vo - vx )] – [D / (vo + vx )] (14)

46

Since the transit times measured by both transducers, the distance traveled by the beam,

and the speed of sound in blood are all known quantities; therefore, this equation can be

used to calculate vx. Once vx is obtained, the transit velocity (V) of blood traveling

through the vessel can be determined according to the following equation:

V cos θ = vx (15)

where θ is the angle between the centerline of the vessel and the ultrasonic beam axis.

Finally, blood flow is the product of the transit velocity and the cross-sectional area of the

vessel. The cross-sectional area of the vessel is pre-determined by the size of the acoustic

window according the probe model. Since transit time is sampled at all points across the

diameter of the vessel, volume flow is independent of the flow velocity profile.

If a flow probe failed during the experiment, the missing values were estimated by

subtracting the values from the functional flow probe from the ICG values.

The ICG method is based on the Fick principle, according to which the net

balance of a substrate across an organ is equal to the concentration difference of the

substrate across the organ multiplied by the blood flow through the organ. The equation

can be rearranged to calculate hepatic blood flow by dividing hepatic ICG balance by the

arteriovenous difference of ICG across the liver. Because the liver is assumed to be the

only site of ICG clearance, hepatic ICG uptake is equal to ICG infusion rate under steady

state conditions. The extraction of ICG across the liver remains constant for brief

infusions. However, if ICG is infused for a longer time (> 4 h), the dye level in plasma

gradually increases, resulting in a 5-10 % overestimation of hepatic blood flow (145).

47

The arterial and the corresponding hepatic vein plasma samples were centrifuged

at 3000 rpm for 30 min without the brake to pellet the residue. The absorbance was then

measured on a Spectronic spectrophotometer at 810 nm. The procedure was then

repeated, and the values obtained for each sample were averaged. A standard curve was

constructed by adding successive 5 µl aliquots of diluted dye (1:10 dilution) to 1 ml of

plasma drawn from the animal before the dye infusion was started. The standard curve

mean difference per incremental changes was then used to calculate hepatic plasma flow

(HPF) as follows:

HPF = [IR x 10 x SCMD] / [dog weight in kg x (0.005) x (A-H)] (16)

where IR is ICG infusion rate (ml/min), SCMD is the standard curve mean difference per

5 µl increments, and A-H is the difference in absorbance between the arterial and the

hepatic venous sample. The value of 10 was used to correct for the dilution of the ICG

used in the standard curve, and 0.005 was the volume in ml used as increments in the

standard curve. Hepatic blood flow (HBF) was derived from HPF:

HBF=HPF/(1-hematocrit) (17)

Hematocrit was measured at every time point of each in which samples were taken from

the hepatic artery and portal and hepatic veins. This technique only determines total

blood flow; therefore, an assumption was made regarding the contribution of blood flow

in the vessels supplying the liver. The normal distribution of flow was assumed to be

28% artery and 72% hepatic portal vein at baseline.

48

Tissue Analysis

Real time PCR and Western blot analysis

Within 2 min of the final sampling time point, each animal was anesthetized with

pentobarbital (390mg/ml Fatal-Plus; vortech Pharmaceutical Inc., Dearborn,MI) at

1ml/kg. The animal was then removed from the Pavlov harness while the tracers and

hormones continued to infuse. A midline laparotomy incision was made, the liver

exposed and clamps cooled in liquid nitrogen were used to simultaneously freeze sections

of the hepatic lobes 2, 3 and 7 in situ. The frozen liver samples (~5g liver lobes) were

stored at -70°C until subsequent analysis of test proteins (via Western blotting) and

mRNA levels (via Real Time PCR).

Real Time PCR analysis of mRNA levels was performed using the BioRad iQ

iCycler Detection System, iQ Supermix, and canine liver cDNA preparations as template.

Test genes were normalized to the housekeeping gene hypoxanthine phosphoribosyl

transferase 1 (HPRT1), using the Livak method (146). Total RNA was extracted by

homogenizing 50 mg of frozen canine liver in Tri-reagent (Sigma, St. Louis, MO)

following the manufacturer’s instructions and RNA was further purified using the Qiagen

RNEasy kit (Qiagen, Valencia, CA). First strand cDNA was synthesized from total RNA

using the High Capacity reverse transcription kit (Applied Biosystems, Foster City, CA)

as per manufacturer’s directions. Primers were designed using the Primer3 program and

possible primer secondary structure was analyzed using the Mfold program, according to

parameters outlined in the BioRad iCycler manual. Primer pairs were as follows: PEPCK

5'-AGCTTTCAATGCCCGATTTCCAGG and 5'-

TCAGCTCGATGCCGATCTTTGACA; G6Pase 5'-TGAAACTTTCAGCCACATCCG

49

and 5'-GCAGGTAAAATCCAAGTGCGAA; HPRT1 5'-

AGCTTGCTGGTGAAAAGGAC and 5'-TTATAGTCAAGGGCATATCC. Primer

efficiencies were validated to be between 91 and 95% for each primer pair using a

dilution series of cDNA, and primer specificity was confirmed by both melt curve

analysis and 1% agarose gel electrophoresis (each of which revealed one product), and

optimal annealing temperature was determined to be 55oC for each primer set. Samples

were run in duplicate, and a negative control (no cDNA template) was included for every

primer pair.

For Western blotting, sample preparation, electrophoretic separation, blotting, and

immunodetection of proteins was performed essentially as described previously

(Ramnanan and Storey, 2006). Antibodies specific for total and phosphorylated Akt,

GSK3β, FOXO1, and CREB proteins were purchased from Cell Signaling (Danvers,

MA), while the PGC1α antibody was purchased from Santa Cruz Biotechnology (Santa

Cruz, CA). The PEPCK antibody was a generous gift from Dr. D.K. Granner. Briefly,

frozen canine liver was homogenized 1:10 w:v in cold (4oC) buffer that was designed to

inhibit endogenous protein phosphatase, protein kinase and protease activities: 50 mM

Tris-HCl pH 7.0, 100 mM sucrose, 10% v:v glycerol, 2 mM EDTA, 2 mM EGTA, and 25

mM NaF; 10 µL/mL homogenization buffer of Sigma Phosphatase Inhibitor Cocktail 1,

Phosphatase Inhibitor Cocktail 2, and Sigma Protease Inhibitor Cocktail were added at

the time of homogenization. Homogenates were centrifuged at 10,000 x g for 20 min,

supernatants were removed and soluble protein concentration was determined using the

Biorad protein assay. Aliquots of supernatant were mixed 1:1 v:v with freshly prepared

2X SDS-PAGE loading buffer (100 mM Tris-HCl, pH. 6.8, 4% w:v SDS, 20% v:v

50

glycerol, 0.2% w:v bromophenol blue, 10% v:v 2-mercaptoethanol) and boiled for 5 min.

Samples were immediately frozen with liquid nitrogen and stored at –20oC. Aliquots

containing 20 µg soluble protein were subjected to SDS-PAGE (12% resolving gel) and

proteins were subsequently wet-transferred to nitrocellulose membranes using the

Invitrogen XCell Blot II apparatus. Blocking conditions and antibody incubation

conditions were optimized for specific proteins. Generally, membranes were blocked

with 5% (wt/v) bovine serum albumin in Tris-buffered saline containing Tween-20

(TBST: 10 mM Tris-base, pH 7.0, 150 mM NaCl, 0.5% v:v Tween 20) for 1 h at room

temperature and then probed with primary antibodies diluted 1:1000 v:v in TBST for 2 h.

After 3 x 5 min washes with TBST, membranes were then incubated with the appropriate

HRP-conjugated secondary antibody (Promega; Madison, WI) diluted 1:2000 v:v in

TBST for 1 h at room temperature, followed by 3 x 5 min washes in TBST. Proteins were

visualized using ECL Plus Western detection reagents (GE Healthcare, Piscataway, NJ)

following manufacturer’s protocols and the ECL signal was detected after exposure to

BioMax Light X-ray film (Kodak, Chalon-sur-Saone, France).

Test protein bands were quantified using ImageJ software

(http://rsb.info.nih.gov/ij/). After immunodetection, blots were normalized for loading as

previously described (147). Bio-Rad Kaleidoscope pre-stained markers were run in one

lane of each gel to verify the subunit molecular mass of target proteins. Membranes were

stripped using Restore reagent from Pierce (Rockford, IL) and reprobed according to

manufacturer’s directions.

51

Calculations

Net Hepatic Substrate Balance and Fractional Extraction

The net hepatic balances and net hepatic fractional extractions of blood glucose,

lactate, alanine, glycerol, BOHB and plasma FFA were calculated using both ultrasonic-

determined and ICG-determined flow. As previously mentioned, the data shown are

those calculated using ultrasonic-determined flow because this flow does not require an

assumption about the distribution of arterial versus portal flow. ICG-determined flows

were used to calculate the data only to verify that conclusions drawn using the flow probe

data were independent of the method used to determine flow.

The net balance of a substrate across an organ was determined using the

arteriovenous (A-V) difference technique. This employed the Fick principle as described

for the ICG-determination of blood flow (as described in Sample Analysis under Blood

Flow)

The net balance of a substrate (NSB) was calculated as:

NHSB = Loadout - Loadin (19)

The Loadout was calculated according to the equation:

Loadout = [S]HV x HBF (20)

52

where [S]HV is the substrate concentration in the hepatic vein blood, and HBF is the total

hepatic blood flow.

The Loadin was calculated according to the equation:

Loadin = ([S]A x HABF) + ([S]PV x PVBF) (21)

where [S]A and [S]PV are the arterial and portal venous blood substrate concentrations,

respectively, and HABD, PVBF are the hepatic artery and the portal vein blood flows,

respectively. For all glucose balance calculations, plasma glucose concentrations were

converted to whole blood values using a previously determined correction factor (148)

which assumes blood glucose to be 73 % of the plasma glucose values. Blood flows

were used for all substrate balance calculations with the exception of FFA balances. FFa

balances were calculated by using plasma flow and plasma substrate concentrations.

Plasma flow was determined by multiplying blood flow by (1-hematocrit). A positive

value for NHSB indicates net substrate production by the liver, whereas a negative value

represents net hepatic substrate uptake. When the data were plotted as net hepatic uptake,

positive values were used.

Net fractional extraction (FE) was also calculated using ultrasonic-determined

blood flow according to the following equation:

FE = NHSU/Loadin (22)

53

where NHSU is net hepatic substrate uptake.

The arterio-venous difference technique has some limitations that must be

taken into account such as: 1) variability of vascular anatomy and heterogeneity of tissue

structure and function, 2) imprecision in measurement of local blood flow, 3)

measurement of net rather than absolute flux across the organ, and 4) access to the portal

vein is required, making this procedure only useful in animals. Furthermore, transit time

through the organ must be taken into account. Glucose transit time through the liver it is

very short (<1 min) making the measurement robust nevertheless the arterio-venous

difference represents net flux across an organ, it is most valid during steady-state

conditions.

Glucose Turnover

Glucose turnover is the rate at which old glucose is replaced with new glucose.

Glucose production (Ra) and glucose utilization (Rd) were determined using an isotope

dilution method described by Wall (149), as simplified by DeBodo (150) and using a

two-compartmental model (151) with canine parameters (152). The glucose pool was

initially primed with an injection of [3-3H]glucose followed by a constant infusion of the

tracer. By the beginning of the control period, the tracer ([3-3H]glucose) and tracee (cold

glucose) were in equilibrium so that the specific activity of glucose (SA = dpm

glucose/mg glucose) was in a steady state. Ra and Rd were calculated according to the

following equations:

Ra = [I - N (dSA/dt)]/SA, and (23)

54

Rd = Ra – (dN/dt) (24)

where I is infusion rate of tracer (dpm/min), N is the size of the glucose pool (mg) and t is

time (min) (153). In a steady state, when dSA/dt = 0, the Ra equation is simplified to:

Ra = I/SA (25)

This method utilizes a one-compartment model of glucose kinetics as described

by Steele (154). Assumptions of the model are that one compartment of glucose consists

of both rapidly mixing and slowly mixing glucose pools; therefore, when a rapid change

in the cold glucose concentration is induced in the system, the consequent changes in

glucose specific activity would be unevenly distributed throughout the entire glucose

compartment. To compensate for this problem, the pool size is calculated as:

N = pVC (26)

where p is the pool fraction, V is the volume of distribution of glucose (ml) and C is

concentration of cold glucose (mg/dl). The pool fraction (the rapidly mixing component

of the glucose compartment) was estimated to be 0.65, or 65 % of the total system (155),

while V was assumed to be the extracellular volume, which is approximately 22% of the

dog weight (156).

The major limitation of the one-compartment model is that a rapid change in SA

invalidates the method, so that a fall in SA, which occurs either by endogenous glucose

55

production or exogenous glucose infusion in the presence of a constant [3-3H] glucose

infusion, the change in SA would cause an error in the estimation of Ra (underestimation

if SA drops, overestimation if SA increases) (157). In order to overcome this problem, in

the present studies, the data were calculated using a two-compartment model (151). This

model describes the glucose system more accurately under non-steady-state conditions.

Ra was calculated as the sum of three terms: a steady-state term, a term for the first

compartment, and the term for the second compartment. The principle equations are as

follows, where the expression of Ra, calculated at the equally spaced time instants t0,

t1,…, tk, tk+1, is determined from the following formulas:

Ra(tk) = (R*inf)(tk)/SA(tk) – V1[C(tk)dSA(tk)/dt] / SA(tk) – V2k22[SA(tk)G(tk) –

G*(tk)]/SA(tk) (27)

G(tk+1) = b1G(tk) + b2C(tk) + b3C(tk+l) (28)

G*(tk+l) = blG*(tk) + b2C*(tk) + b3C*(tk+l) (29)

V2= V1k12k21/k222 (30)

where tk and tk+l are time parameters, respectively; Ra(tk) and R*inf(tk) are the rate of

appearance calculated with a two-compartment model (mg/kg/min) and tracer infusion

rate (dpm/kg/min), respectively; SA(tk) and dSA(tk) are specific activity (dpm/mg) and

derivative of specific activity (dpm/mg/min), respectively. V1 and V2 (ml/kg) are the

volumes of the first and second compartments, respectively; C*(tk) and C(tk) are tracer

and tracee concentrations, respectively; k12, k21, and k22 are constant rate parameters of

the first and second compartments, respectively; G(tk) and G*(tk) are variables calculated

56

recursively from tracee and tracer concentrations, respectively; bl, b2, and b3 are

coefficients of recursive equations for calculating G(tk) and G*(tk). Canine parameters

used for Vl, V2, and k22 in the present studies were those determined by Dobbins et al.

(152). It has been reported (152) that under non-steady state conditions where specific

activity changes dramatically, glucose appearance determined using the two-

compartment model is more accurate than the Steele equation (one-compartment model.)

When glucose was infused, endogenous glucose production (endo Ra) was

determined by subtracting the glucose infusion rate (GIR), from total glucose production

(Ra).

Of note, there are two major assumptions that are made when using the particular

isotope dilution method to determine glucose kinetics. First, the labeled and unlabeled

glucose molecules are assumed to be metabolized in the same manner. Secondly, the

label is assumed to be irreversibly lost (158).

It should also be noted, however, that since both the liver and the kidneys produce

glucose, whole body tracer-determined glucose production is slightly higher than the rate

of hepatic glucose production. Although net kidney glucose balance in the postabsorptive

state is near zero, the kidneys have been estimated to contribute 5-15% to whole body

glucose production. Metanalysis suggests that the kidneys are only a minor contributor to

total glucose production (159).

Hepatic Gluconeogenesis and Glycogenolysis

Gluconeogenesis is the synthesis and release of glucose formed from non-

carbohydrate precursors. Glucose-6-phosphate produced from flux through the

57

gluconeogenic pathway is not only released as glucose; it can also be stored as glycogen,

oxidized or released as lactate. Therefore, there is a distinction between gluconeogenic

flux to glucose-6-phosphate, which is the conversion of precursors to glucose-6-

phosphate, and gluconeogenesis per se, which is the release of glucose derived from

gluconeogenic flux into the blood. In the present studies, we estimated hepatic

gluconeogenic (GNG) flux to glucose-6-phosphate and net hepatic glycogenolytic

(NHGLY) flux.

The net hepatic uptakes of the gluconeogenic precursors alanine, lactate and

glycerol were measured using the arterio-venous difference method (as described in

Calculations under Net Hepatic Substrate Balance and Fractional Extraction). This

method assumes that there is 100% conversion of gluconeogenic precursors taken up by

the liver into G-6-P and that intrahepatic GNG precursors do not contribute significantly

to GNG flux. The net hepatic balance of pyruvate was assumed to be 10% of the net

hepatic lactate balance (160). In these studies certain gluconeogenic precursors were not

measured (e.g. pyruvate, glycine, threonine, serine, glutamine, glutamate). To the extent

that they contributed to gluconeogenic flux, it will be underestimated. To correct for this

error and assuming, based on previous studies (161) that net hepatic alanine uptake

represents a reasonable approximation of the uptake of the unmeasured gluconeogenic

precursors, net hepatic alanine uptake was multiplied by 2. Hepatic gluconeogenic flux

to glucose-6-phosphate was estimated by summing gluconeogenic precursor uptake and

dividing by two to account for the incorporation of the three-carbon precursors into the

six-carbon glucose molecule (to convert the data into glucose equivalents). When net

58

hepatic output of any precursor occurred, rather than uptake, the precursor was

considered to be a product of the liver, and thus uptake was set to zero.

Net hepatic gluconeogenic flux was determined by subtracting the sum of net

hepatic output rates (when such occurred) of gluconeogenic precursors (in glucose

equivalents) and hepatic glucose oxidation from the gluconeogenic flux to G-6-P. A

positive number represents net gluconeogenic flux to G-6-P whereas a negative number

indicates net glycolytic flux from G-6-P or net flux to pyruvate. In the present studies,

glucose oxidation was assumed to be 0.2 mg/kg/min in all groups (162). This parameter

was not directly measured because it is difficult to differentiate between the small signal

and the high inherent noise in the measurement. On the other hand, our laboratory has

reported that glucose oxidation after an overnight fast ranges from 0.1 to 0.2 mg/kg/min.

Although by using this value may slightly overestimate or underestimate the absolute rate

of glucose oxidation; it is unlikely to differ by more than 0.1 mg/kg/min from the true

value. In addition, previous studies have shown that in the presence

euglycemic/hyperinsulinemic states hepatic glucose oxidation did not change

significantly (162). Glucagon has been reported to inhibit pyruvate dehydrogenase and

as a result pyruvate oxidation (163; 164) but the basal oxidation rate is so low that the

noise of the measurement would be greater than the magnitude of the potential fall.

Net hepatic glycogenolytic flux was estimated by subtracting net hepatic

gluconeogenic flux from net hepatic glucose balance. A positive value indicates net

glycogen breakdown whereas a negative value represents net glycogen synthesis.

It is necessary to consider the limitations of the arterio-venous difference

technique to estimate the net hepatic gluconeogenic and glycogenolytic fluxes. There is

59

little or no hepatic production of gluconeogenic amino acids or glycerol whereas that is

not the case for lactate. Our estimate of the rate of gluconeogenic flux to G-6-P will be

quantitatively accurate only if we assume that lactate flux is unidirectional at a given

moment (i.e. either in or out of the liver). Jungermann and Katz (165; 166) have reported

that there is a spatial separation of metabolic pathways, such that gluconeogenic

periportal hepatocytes synthesize glucose and glycogen primarily from lactate and other

non-carbohydrate precursors whereas glycolytic perivenous hepatocytes consume glucose

which is mainly oxidized or released as lactate. Therefore, in a net sense it is possible

that hepatic gluconeogenic and glycolytic flux occur simultaneously, with lactate output

and uptake occurring in different cells. To the extent that flux occurs in both directions

simultaneously the net hepatic balance method will result in an underestimation of the

absolute rate of gluconeogenic flux to G-6-P. Of note, net hepatic gluconeogenic and net

hepatic glycogenolytic fluxes can be calculated accurately without concern for the

assumptions related to whether or not simultaneous gluconeogenic and glycolytic

substrate flux occur. Ideally the gluconeogenic flux rate would be calculated using

unidirectional hepatic uptake and output rates for each substrate, but this would be

difficult, as it would require the simultaneous use of multiple stable isotopes which could

themselves induce a mild perturbation of the metabolic state.

Statistical Analysis

Data are expressed as means ± standard error (SE). The data were analyzed for

differences between saline-euglycemic vs. glucagon-euglycemic and saline-

hypoglycemic vs. glucagon-hypoglycemic. Statistical comparisons were carried out using

60

two-way repeated measures ANOVA and two-way ANOVA with post hoc data analysis

determined by Student-Newman-Kuels Method (Sigma Stat, SPSS Inc.). Significance

was established when P < 0.05.

61

CHAPTER III

THE SENSITIVITY OF THE LIVER TO GLUCAGON IS INCREASED DURING INSULIN-INDUCED HYPOGLYCEMIA

Aim

In the presence of insulin-induced hypoglycemia glucagon is the most important

stimulator of glucose production. In contrast under euglycemic conditions insulin is a

potent inhibitor of glucagon’s effect on the liver. The results of previous studies suggest

that the liver is more sensitive to glucagon during hypoglycemia. A comparison of the

effects of a controlled rise in glucagon on hepatic glucose production in the presence of

euglycemia or hypoglycemia has never been made. For this reason, the aim of the

present study was to examine the ability of a physiologic increase in glucagon to

overcome the inhibitory effect of insulin on glucose production under euglycemic or

hypoglycemic conditions.

Results

Hormone Concentrations

Arterial plasma insulin rose from baseline to between 230 and 300 U/ml in

response to insulin infusion (Figure 3.1A). Arterial plasma glucagon levels were similar

in all groups during the control period (39±1 pg/ml) and they fell during the first

experimental period to between 25±2 and 30±2 pg/ml. They remained low in

experimental period two in the SE and SH groups (26±5 and 23±6 pg/ml respectively)

but rose to ~ 100 pg/ml in response to intraportal glucagon infusion in the GE and GH

groups (Figure 3.1B). Arterial plasma cortisol was ~3.5±0.3 µg/dl in all groups

62

respectively during the control period and experimental period one (Figure 3.2A). It

remained unchanged in the SE and GE groups (3.7±0.8 and 4.8±2.0 µg/dl respectively)

during experimental period two. On the other hand, in response to insulin-induced

hypoglycemia it increased markedly (15±1 and 17±3 µg/dl, in SH and GH respectively;

P<0.05 vs. euglycemic groups). Arterial plasma epinephrine was basal (~130±2 pg/ml)

during the control period and experimental period one in all groups (Figure 3.2B).

During experimental period two, it was ~137±62 and 126±53 pg/ml in the SE and GE

groups respectively, but rose to 1917±376 and 1755±326 pg/ml, in the SH and GH

groups respectively (P<0.05 vs. euglycemic groups). Arterial plasma norepinephrine

levels remained basal and similar between the groups (161±15 pg/ml) during the control

period and experimental period one (Figure 3.2C). During experimental period two it

remained unchanged in the SE and GE groups (209±33 and 162±30 pg/ml), but increased

to 403±83 and 350±86 pg/ml (P<0.05) in the SH and GH groups. The arterial plasma

polypeptide level averaged ~ 181±37 pg/ml in all groups during the control period. It fell

during experimental period one to 101±19, 82±18, 149±44 and 173±59 pg/ml in the SE,

GE, SH and GH, respectively, in response to the intraportal somatostatin infusion and

remained low in period two in all groups (98±21, 129±65, 162±40 and 174±52 pg/ml in

the SE, GE, SH and GH groups, respectively) (Table 3.1)

Blood glucose levels and hepatic glucose balance

Euglycemia was maintained during experimental period one in each group and

during experimental period two in the SE and GE groups (Figure 3.3A). In the latter

groups glucose infusion rates were 14.7±2.6 and 13.1±2.4 mg/kg/min, respectively

63

(Figure 3.3B). On the other hand, hypoglycemia was allowed to occur in the SH and GH

groups (49±1 mg/dl). The glucose infusion rates required to maintain hypoglycemia of

50 mg/dl were 5.9±1.4 and 4.6±1.7 mg/kg/min respectively. NHGO was ~1.6±0.1

mg/kg/min in all groups in the control period. In response to intraportal insulin infusion

in the presence of euglycemia the liver switched to slight net hepatic glucose uptake in all

groups (~ 0.4±1.2 mg/kg/min; Figure 3.4A). During the second experimental period,

NHGU increased slightly over time (to ~1.5±0.4 mg/kg/min) in the SE group while in the

GE group the liver temporarily switched to net output (~0.4±0.6 mg/kg/min) after which

it switched back to net uptake (~0.9±0.7 mg/kg/min). In the SH and GH groups the liver

quickly switched to net glucose output and remained in a production mode until the end

of the study (1.3±0.2 and 3.1±0.5 mg/kg/min, respectively; P<0.05). The increase in net

hepatic glucose balance (60 to 180 minutes) caused by glucagon was significantly greater

in the presence of hypoglycemia (239 mg/kg/120 min; difference in NHGB between SH-

GH) than in the presence of euglycemia (106 mg/kg/120 min; difference in NHGB

between SE-GE) (Figure 3.4B). Changes in tracer-determined endogenous glucose

production (Ra) paralleled the changes in NHGO (Table 3.2)

Tracer determined glucose utilization (Rd) was between 2.2 and 2.8 mg/kg/min

during the control period. Intraportal infusion of insulin increased Rd in all groups (to

11.9±1.8, 10.6±1.3, 11.6±1.7 and 9.2±1.7 mg/kg/min; Table 3.2) during experimental

period one. Rd continued to increase over time in the SE and GE groups (reaching

19.6±2.2 and 18.6±1.3 mg/kg/min, respectively by the end of the study) but it decreased

in the SH and GH groups (6.2±0.9 and 5.3±0.7 mg/kg/min, respectively; P<0.05).

Glucose clearance increased in all groups during experimental period one (Table 3.2) and

64

it rose to a greater extent during experimental period two in the euglycemic groups than

in the hypoglycemic groups.

Metabolites

Arterial blood alanine had decreased in response to the rise in insulin in all groups

by the end of the study. There was no significant change in net hepatic alanine balance

over time and no difference between groups (Table 3.3). On the other hand, the

fractional extraction of alanine by the liver doubled in all groups although this change

was not significant in any individual group. Arterial blood lactate levels were basal

during control period and rose minimally in experimental period one in all groups (Table

3.3). During experimental period two they remained unchanged in both euglycemic

groups but increased markedly in the hypoglycemic groups (Table 3.3). The liver was

producing lactate in all groups during period one. By the end of the study all groups had

switched to net hepatic lactate uptake but the hypoglycemic groups were taking up almost

6 times as much lactate as the euglycemic groups. The presence of glucagon had no

effect in lactate metabolism in the euglycemic or hypoglycemic settings.

Arterial plasma glycerol levels fell in all groups when insulin rose (Table 3.4).

They remained suppressed during experimental period two in both euglycemic groups but

increased markedly in response to hypoglycemia. Net hepatic glycerol uptake followed

the changes in glycerol levels and was more than 10 fold greater in the presence of

hypoglycemia than in the presence of euglycemia. The addition of glucagon in the

presence of euglycemia or hypoglycemia had no effect in glycerol metabolism.

65

Arterial Plasma Free Fatty Acids and BOHB

Arterial plasma free fatty acid levels were basal in all groups during the control

period and fell markedly in response to insulin in experimental period one (Table 3.5).

They fell to less than 50 µmol/L during experimental period two in both euglycemic

groups whereas they increased markedly in the SH and GH groups (to 547±76 and

376±115 µmol/L, respectively). Net hepatic free fatty acid uptake paralleled the changes

in plasma free fatty acid levels (Table 3.5). Arterial blood BOHB levels and net hepatic

BOHB output tended to fall in response to elevated insulin. The decline was slightly less

in the presence of hypoglycemia. The presence of glucagon had no discernable effect in

FFA or BOHB metabolism (Table 3.4).

Net hepatic glycogenolytic and gluconeogenic flux

Net hepatic gluconeogenic(NHGNG) flux was ~ 0.1±0.1 mg/kg/min during the

control period (Figure 3.5A) and decreased to ~ -0.5±0.1 mg/kg/min in all groups during

experimental period one. It remained close to zero in the SE and GE groups during

experimental period two but increased significantly (~1.8 mg/kg/min) in the SH and GH

groups in response to hypoglycemia. Since the increase was virtually identical (1.7±0.4

and 1.8±0.4 mg/kg/min, respectively (P<0.05). it is clear that the drive for

gluconeogenesis was not attributable to glucagon. Net hepatic glycogenolytic (NHGLY)

flux was ~1.5±0.1 mg/kg/min in all groups at the end of the control period (Figure 3.5B)

and it decreased during experimental period one (to -0.5±0.6, -0.5±0.2, 0.0±0.4 and -

0.6±0.3 mg/kg/min in the SE, SH,GE and GH groups, respectively). During

experimental period two the SE group continued to exhibit net glycogen synthesis (-

66

1.3±0.7 mg/kg/min). Addition of glucagon (GE) caused a small glycogenolytic response

followed by a return to net glycogen synthesis. In the SH group net glycogen synthesis

remained near zero during experimental period two. On the other hand, in the GH group

NHGLY flux increased to ~2.9±1 mg/kg/min at 75 minutes and remained elevated

throughout the study. The increase in NHGLY flux between 60 to 180 minutes caused

by glucagon was much greater in the presence of hypoglycemia (279 mg/kg/120 min)

than in the presence of euglycemia (106 mg/kg/120 min) (P<0.05). Hypoglycemia thus

caused a 2.7 fold increase in the glycogenolytic response to glucagon (Figure 3.5C).

Molecular changes

Molecular indices from the last two dogs studied in each group were analyzed and

compared to control values in liver taken from 18 h, fasted dogs in which basal levels of

insulin, glucagon and glucose were maintained. These animals were part of another

study and were included for references purposes. Levels of phosphorylated (Ser473) Akt

were assayed as an index of activation of the insulin signaling pathway, as were the levels

of phosphorylated (Ser256) FOXO1 and (Ser9) GSK3-β, two downstream targets of Akt

that are relevant to hepatic glucose metabolism. Total protein levels of Akt, FOXO1, and

GSK3-β did not change with treatment, and were used to normalize quantification of the

respective phospho-proteins. (Figure 3.6A). Animals in the euglycemic (SE and GE)

groups featured similar 4.8-fold increases in P-Ser473 Akt relative to the control animals.

However, animals in both hypoglycemic groups had partially blunted Akt activation, with

only 2.1- and 1.5-fold increases in P-Ser473 Akt being observed in the SH and GH

groups, respectively. Relative to control animals, P-Ser9 GSK3-β was increased

67

substantially (7.0-fold increase) in SE animals, while progressively smaller increases

(5.7-, 4.4-, and 1.4-fold) were observed in the GE, SH, and GH groups, respectively.

FOXO1 (Ser256) phosphorylation was markedly increased (5.5-fold) in the SE group

relative to control animals, but only a 1.9-fold rise was observed in the GE group and

there was no increase apparent in either hypoglycemic test condition.

To assess glucagon signaling, we assayed levels of phosphorylated (Ser133)

cAMP-response element-binding protein (CREB), PPAR gamma coactivator-1α (PGC1α)

and PEPCK protein levels. Total levels of CREB protein did not vary between groups,

while P-Ser133 CREB was strongly suppressed in the SE group relative to control

animals, but this suppression was equivalently blocked by the presence of hypoglycemia

and/or glucagon in the other groups. Levels of PGC1α were depressed in the SE group to

~60% of that observed in control animals, but the presence of glucagon and/or

hypoglycemia (GE, SH, GH) led to 2.5-fold increases in PGC1α in these groups.

Likewise, the PEPCK protein level in the SE animals was reduced to ~60% of that in

control animals, but were unchanged from basal in the other three groups. Analysis of

gene transcription revealed that PEPCK mRNA levels were decreased by 89% in the SE

group relative to that in the control animals and this strong repression was decreased by

hypoglycemia and/or glucagon, leading to a doubling of PEPCK mRNA relative to that

evident in the SE animals (Figure 3.6B). Similarly, G6Pase mRNA expression was

reduced in the SE group by 87%. Both GE and SH groups exhibited a doubling in

G6Pase mRNA relative to the SE group, and the combination of glucagon and

hypoglycemia (GH) led to an even more substantial (3-fold) increase.

68

Art

eria

lPl

asm

a In

sulin

( U

/ml)

0

150

300

450

SAL + EUGGN + EUSAL + HYPOGGN + HYPO

Time (min)

-40 0 60 120 180

Art

eria

lPl

asm

a G

luca

gon

(pg/

ml)

0

50

100

150

A

B

Figure 3.1 - (A) Arterial plasma insulin (U/ml) and (B) glucagon (pg/ml) during basal(-40 to 0 min) and experimental periods (0 to 180 min) in 18h fasted conscious dogs exposed to a controlled rise of glucagon in the presence of euglycemia and hypoglycemia. Values are means ± SEM; n=6 groups. *P<0.05 vs. euglycemic group; †P<0.05 vs. saline group.

Pe SRIF + Po INS (5.0 mU/kg/min)EU EU or HYPO

Po GGN (2.3 ng/kg/min)

69

A

B

C

Art

eria

l Pl

asm

aEp

inep

hrin

e(p

g/m

l)

0

1000

2000

3000

4000 SAL + EUGGN + EUSAL + HYPOGGN + HYPO

Time (min)

-40 0 60 120 180

Art

eria

l Pl

asm

aN

orep

inep

hrin

e(p

g/m

l)

0

200

400

600

Figure 3.2 - (A) Arterial plasma cortisol, (B) epinephrine and (C) norepinephrine (pg/ml) during basal (-40 to 0 min) and experimental periods (0 to 180 min) in 18h fasted conscious dogs exposed to a controlled rise of glucagon in the presence of euglycemia and hypoglycemia. Values are means ± SEM; n=6 groups. *P<0.05 vs. euglycemic group; †P<0.05 vs. saline group.

**

** *

**

** *

*

**

**

*

**

**

*

** *

***

*

*



Art

eria

lPl

asm

a C

ortis

ol(

g/dl

)

0

5

10

15

20

25

70

Art

eria

lPl

asm

a G

luco

se(m

g/dl

)

0

406080

100120A

B

Time (min)

-40 0 60 120 180

Glu

cose

Infu

sion

Rat

e(m

g/kg

/min

)

0

5

10

15

20




Figure 3.3 - (A) Arterial plasma glucose (mg/kg/min) and glucose infusion rate (mg/kg/min) between 60 to 180 caused by glucagon (mg/kg/min2) during basal (-40 to 0 min) and experimental periods (0 to 180 min) in 18h fastedconscious dogs exposed to a controlled rise of glucagon in the presence of euglycemia and hypoglycemia. Values are means ± SEM; n=6 groups. *P<0.05 vs. euglycemic group; †P<0.05 vs. saline group.

71

GGN-SALHYPO

GGN-SALEU

Time (min)-40 0 60 120 180

-2

0

2

4

SAL+EUGGN+EU SAL+HYPO GGN+HYPO

Net

Hep

atic

G

luco

se B

alan

ce(m

g/kg

/min

)A

B

NHGU

NHGO

** *

*†*† *†*†

*† *†

Figure 3.4 - (A) Net Hepatic Glucose Balance (mg/kg/min) and the Delta AUC: for the increase in NHGO between 60 to 180 caused by glucagon (mg/kg/min2) during basal (-40 to 0 min) and experimental periods (0 to 180 min) in 18h fasted conscious dogs exposed to a controlled rise of glucagon in the presence of euglycemia and hypoglycemia. Values are means ± SEM; n=6 groups. *P<0.05 vs. euglycemic group; †P<0.05 vs. saline group.

***



Del

ta A

UC

: Fo

r the

incr

ease

in N

HG

O

from

the

last

2 h

ours

ca

used

by

gluc

agon

(mg/

kg/1

20m

in)

0

50

100

150

200

250

300

72

Del

ta A

UC

: Fo

r the

incr

ease

in G

LY fr

om th

e la

st 2

hou

rs

caus

ed b

y gl

ucag

on(m

g/kg

bw

/120

min

)

0

100

200

300



Figure 3.5 - (A) Net hepatic gluconeogenic and (B) glycogenolytic flux (mg/kg/min) during basal (-40 to 0 min)and experimental periods (0 to 180 min) in 18h fasted conscious dogs exposed to a controlled rise of glucagon in the presence of euglycemia and hypoglycemia. Values are means ± SEM; n=6 groups. *P<0.05 vs. euglycemic group; †P<0.05 vs. saline group.

A

Net GLY syn

Net GLY prod

Time (min)-40 0 60 120 180

Net

Hep

atic

G

lyco

geno

lytic

Flu

x(m

g/kg

/min

)

-2

0

2

4


B*†

*†

*†*†

*†*†

GGN-SALHYPO

Net GNG

Net Gycolysis-1

0

1

2N

et H

epat

icG

NG

Flu

x(m

g/kg

/min

)

* * * *

* **

C

GGN-SALEU

73

A

B

Figure 3.6 - (A) Phosphorylation of Akt (Ser 473), GSK3- (Ser 9), FOXO1 (Ser 256), CREB(Ser 133) and PGC-1 and (B) relative gene expression of PEPCK and G-6-Pase of liver samples taken from 18h fasted conscious dogs exposed to a controlled rise of glucagon in the presence of euglycemia and hypoglycemia.

74

TABLE 3.1Pancreatic Polypeptide (pg/ml) during control (-40 to 0 min) and experimental periods (0-180 min) of studies conductedon 18h fasted conscious dogs exposed to a controlled rise in glucagon in the presence of euglycemia and hypoglycemia.

Pancreatic PolypeptideArterial plasma levels (pg/ml)

SAL-EU 148 ± 36 101 ± 19 82 ± 23 103 ± 20 101 ± 23 101 ± 25 103 ± 22GGN-EU 115 ± 33 82 ± 18 97 ± 27 130 ± 62 140 ± 84 118 ± 55 153 ± 96

SAL-HYPO 197 ± 64 149 ± 44 144 ± 40 155 ± 37 161 ± 48 169 ± 47 161 ± 43GGN-HYPO 227 ± 75 172 ± 59 175 ± 62 170 ± 53 190 ± 59 170 ± 54 170 ± 55

Mean ± SEM; n=6; *P < 0.05 vs. euglycemic group; †P<0.05 vs saline group.

P1 P2Experimental Period

180ControlPeriod 30-60 75 90 120 150

75

TABLE 3.2Tracer determined endogenous glucose production, utilization (mg/kg/min) and glucose clearance (ml/kg/min) during control (-40 to 0 min) and experimental periods (0-180 min) of studies conducted on 18h fasted conscious dogs exposed to a controlled rise in glucagon in the presence of euglycemia and hypoglycemia.

Tracer Determined Glucose Production Ra, mg/kg/min

SAL-EU 2.9 ± 0.3 0.7 ± 0.5 -0.7 ± 0.9 -0.1 ± 0.7 0.4 ± 0.6 0.1 ± 0.9 1.0 ± 0.3GGN-EU 2.2 ± 0.2 0.6 ± 0.9 0.6 ± 0.8 -1.1 ± 0.6 0.1 ± 1.0 -0.5 ± 1.1 0.8 ± 1.0

SAL-HYPO 2.5 ± 0.2 0.9 ± 0.8 -0.6 ± 1.4 -0.1 ± 0.9 1.9 ± 0.6 * 1.8 ± 0.6 * 1.8 ± 0.6GGN-HYPO 2.4 ± 0.1 0.6 ± 0.9 2.3 ± 0.4 2.0 ± 0.5* † 3.5 ± 0.6 * 3.3 ± 0.5 * 3.3 ± 0.5

Rd, mg/kg/minSAL-EU 2.8 ± 0.3 11.9 ± 1.8 15.0 ± 1.8 16.5 ± 1.9 18.2 ± 2.0 18.6 ± 2.1 19.6 ± 2.2GGN-EU 2.2 ± 0.2 11.6 ± 1.7 13.2 ± 0.5 14.2 ± 0.6 15.8 ± 0.8 16.9 ± 0.9 18.6 ± 1.3

SAL-HYPO 2.5 ± 0.2 10.6 ± 1.3 8.2 ± 1.5 7.3 ± 1.1 * 6.3 ± 0.8 * 6.1 ± 0.8 * 6.2 ± 0.9 *GGN-HYPO 2.4 ± 0.2 9.2 ± 1.7 8.1 ± 1.1 * 7.0 ± 1.0 * 5.8 ± 0.9 * 5.4 ± 0.7 * 5.3 ± 0.7 *

Glucose Clearance (ml/kg/min)SAL-EU 2.5 ± 0.3 11.4 ± 1.7 14.2 ± 1.8 15.4 ± 1.7 16.8 ± 1.8 17.2 ± 2.0 18.3 ± 2.3GGN-EU 2.0 ± 0.2 11.1 ± 1.6 12.7 ± 0.7 13.9 ± 0.9 15.7 ± 1.3 16.6 ± 1.2 18.2 ± 1.2

SAL-HYPO 2.2 ± 0.2 11.0 ± 1.4 12.7 ± 2.0 13.1 ± 1.9 13.4 ± 1.6 13.3 ± 1.6 13.6 ± 1.8 *GGN-HYPO 2.2 ± 0.1 9.3 ± 1.8 13.1 ± 2.0 13.2 ± 2.0 12.6 ± 2.0 12.0 ± 1.7 * 11.8 ± 1.6 *


Experimental Period

30-60 75 90 120 150PeriodP1 P2Control

180

76

TABLE 3.3Lactate and alanine arterial blood levels and net hepatic balance during control (-40 to 0 min) and experimental periods (0-180 min) of studies conducted on 18h fasted conscious dogs exposed to a controlled rise in glucagon in the presence of euglycemia and hypoglycemia.

LACTATEArterial Blood Levels (µmol/ml)

SAL-EU 694 ± 130 836 ± 74 795 ± 118 796 ± 107 731 ± 103 633 ± 86 671 ± 102GGN-EU 486 ± 116 660 ± 71 728 ± 100 790 ± 92 769 ± 96 759 ± 122 793 ± 90

SAL-HYPO 758 ± 161 850 ± 92 603 ± 98 553 ± 108 1326 ± 369 1721 ± 416 * 1707 ± 380 *GGN-HYPO 563 ± 117 637 ± 105 659 ± 117 830 ± 251 1384 ± 394 1499 ± 351 * 1670 ± 340 *

Net Hepatic Lactate Balance (µmol/kg/min)SAL-EU 3.8 ± 4.8 8.0 ± 1.9 3.4 ± 2.4 0.7 ± 2.0 -1.8 ± 2.3 -1.9 ± 1.9 -2.9 ± 1.2GGN-EU 0.2 ± 3.1 6.1 ± 2.2 6.1 ± 2.1 4.7 ± 2.0 1.5 ± 1.3 0.7 ± 1.7 -2.1 ± 3.2

SAL-HYPO 4.5 ± 2.7 9.1 ± 2.7 -0.8 ± 1.7 -5.2 ± 1.3 -11.1 ± 2.1 * -12.4 ± 2.5 * -13.4 ± 2.5 *GGN-HYPO 2.2 ± 3.6 8.3 ± 2.2 5.7 ± 2.8 3.1 ± 3.6 † -6.1 ± 1.6 -9.2 ± 2.3 * -14.1 ± 3.3 *

Lactate Fractional ExtractionSAL-EU 0.1 ± 0.22 0.5 ± 0.12 0.2 ± 0.10 0.1 ± 0.12 -0.1 ± 0.11 -0.1 ± 0.11 -0.2 ± 0.09GGN-EU -0.1 ± 0.17 0.4 ± 0.17 0.3 ± 0.10 0.2 ± 0.06 0.1 ± 0.07 0.0 ± 0.08 -0.1 ± 0.11

SAL-HYPO 0.2 ± 0.08 0.5 ± 0.10 -0.1 ± 0.10 -0.4 ± 0.10* -0.4 ± 0.11 -0.3 ± 0.08 -0.2 ± 0.04GGN-HYPO 0.0 ± 0.16 0.5 ± 0.10 0.4 ± 0.20 0.2 ± 0.19 † -0.2 ± 0.05 -0.2 ± 0.03 -0.2 ± 0.04

ALANINEArterial Blood Levels (µmol/ml)

SAL-EU 385 ± 33 326 ± 33 255 ± 17 221 ± 17 190 ± 15 161 ± 16 151 ± 15GGN-EU 314 ± 41 255 ± 27 207 ± 21 192 ± 22 176 ± 21 159 ± 20 148 ± 18

SAL-HYPO 356 ± 30 298 ± 31 223 ± 21 192 ± 11 184 ± 17 180 ± 18 171 ± 14GGN-HYPO 331 ± 56 324 ± 42 226 ± 25 198 ± 20 190 ± 24 172 ± 20 167 ± 21

Net Hepatic Alanine Uptake (µmol/kg/min)SAL-EU 2.4 ± 0.4 2.6 ± 0.2 2.8 ± 0.6 2.5 ± 0.4 2.7 ± 0.2 2.4 ± 0.2 2.4 ± 0.2GGN-EU 2.3 ± 0.4 2.1 ± 0.4 2.4 ± 0.4 2.1 ± 0.4 2.3 ± 0.4 2.3 ± 0.5 2.6 ± 0.5

SAL-HYPO 2.5 ± 0.4 2.5 ± 0.6 2.2 ± 0.5 2.2 ± 0.3 2.4 ± 0.3 2.7 ± 0.2 3.1 ± 0.2GGN-HYPO 2.5 ± 0.6 2.1 ± 0.3 2.7 ± 0.5 2.1 ± 0.4 2.2 ± 0.4 2.6 ± 0.5 3.1 ± 0.5

Alanine Fractional ExtractionSAL-EU 1.2 ± 0.02 0.3 ± 0.02 0.4 ± 0.05 0.4 ± 0.04 0.4 ± 0.03 0.5 ± 0.01 0.5 ± 0.01GGN-EU 0.2 ± 0.03 0.3 ± 0.03 0.3 ± 0.02 0.3 ± 0.02 0.4 ± 0.03 0.4 ± 0.04 0.4 ± 0.04

SAL-HYPO 0.2 ± 0.03 0.3 ± 0.10 0.3 ± 0.10 0.3 ± 0.03 0.4 ± 0.04 0.4 ± 0.03 0.4 ± 0.03GGN-HYPO 0.2 ± 0.06 0.3 ± 0.10 0.4 ± 0.10 0.3 ± 0.06 0.3 ± 0.05 0.4 ± 0.05 0.4 ± 0.05


PeriodP1 P2Control

180

Experimental Period

30-60 75 90 120 150

77

TABLE 3.4Glycerol and BOHB arterial blood levels and net hepatic balance during control (-40 to 0 min) and experimental periods (0-180 min) of studies conducted on 18h fasted conscious dogs exposed to a controlled rise in glucagon in the presence of euglycemia and hypoglycemia.

GLYCEROLArterial Blood Levels (µmol/ml)

SAL-EU 86 ± 18 38 ± 13 29 ± 7 25 ± 9 25 ± 9 27 ± 9 26 ± 5GGN-EU 77 ± 14 36 ± 12 24 ± 7 24 ± 6 21 ± 4 30 ± 11 27 ± 7

SAL-HYPO 78 ± 12 34 ± 8 68 ± 34 163 ± 31 * 253 ± 34 * 265 ± 43 * 269 ± 41 *GGN-HYPO 84 ± 17 42 ± 15 107 ± 54 139 ± 27 * 223 ± 29 * 212 ± 31 * 212 ± 27* †

Net Hepatic Glycerol Balance (µmol/kg/min)SAL-EU -1.7 ± 0.4 -0.6 ± 0.2 -0.5 ± 0.1 -0.5 ± 0.1 -0.5 ± 0.1 -0.4 ± 0.1 -0.5 ± 0.2GGN-EU -1.5 ± 0.3 -0.8 ± 0.3 -0.8 ± 0.4 -0.5 ± 0.2 -0.4 ± 0.1 -0.7 ± 0.3 -0.7 ± 0.2

SAL-HYPO -1.8 ± 0.3 -0.8 ± 0.3 -2.1 ± 1.2 -4.1 ± 0.9 * -6.0 ± 1.3 * -6.9 ± 1.5 * -7.9 ± 1.5 *GGN-HYPO -2.2 ± 0.6 -1.1 ± 0.4 -2.9 ± 1.3 -3.4 ± 0.5 * -5.2 ± 0.8 * -5.7 ± 0.9 * -5.9 ± 0.6* †

Glycerol Fractional ExtractionSAL-EU -0.7 ± 0.1 -0.5 ± 0.1 -0.6 ± 0.1 -0.7 ± 0.1 -0.6 ± 0.1 -0.5 ± 0.1 -0.7 ± 0.1GGN-EU -0.6 ± 0.1 -0.7 ± 0.1 -0.6 ± 0.2 -0.6 ± 0.1 -0.6 ± 0.1 -0.6 ± 0.1 -0.7 ± 0.1

SAL-HYPO -0.7 ± 0.0 -0.7 ± 0.1 -0.7 ± 0.0 -0.7 ± 0.0 -0.7 ± 0.0 -0.7 ± 0.0 -0.7 ± 0.0GGN-HYPO -0.7 ± 0.0 -0.7 ± 0.1 -0.7 ± 0.1 -0.7 ± 0.0 -0.7 ± 0.0 -0.7 ± 0.0 -0.7 ± 0.0

BOHBArterial Blood Levels (µmol/ml)

SAL-EU 30 ± 6 22 ± 5 22 ± 7 18 ± 5 18 ± 6 20 ± 6 20 ± 6GGN-EU 40 ± 11 12 ± 2 10 ± 1 10 ± 2 9 ± 1 10 ± 1 10 ± 2

SAL-HYPO 27 ± 3 20 ± 7 16 ± 6 31 ± 6 35 ± 11 37 ± 15 * 32 ± 15GGN-HYPO 32 ± 7 13 ± 1 13 ± 3 14 ± 1 19 ± 3 15 ± 1 † 18 ± 1

Net Hepatic BOHB Balance (µmol/kg/min)SAL-EU 0.5 ± 0.1 0.2 ± 0.1 0.1 ± 0.0 0.1 ± 0.0 0.0 ± 0.1 0.0 ± 0.1 0.0 ± 0.0GGN-EU 1.1 ± 0.4 0.1 ± 0.0 0.1 ± 0.0 0.1 ± 0.1 0.1 ± 0.0 0.1 ± 0.0 0.1 ± 0.0

SAL-HYPO 0.5 ± 0.2 0.3 ± 0.1 0.3 ± 0.1 0.9 ± 0.4 0.3 ± 0.2 0.2 ± 0.2 0.3 ± 0.2GGN-HYPO 0.9 ± 0.3 0.2 ± 0.1 0.3 ± 0.1 0.3 ± 0.1 † 0.3 ± 0.1 0.2 ± 0.1 0.3 ± 0.1


Experimental PeriodP1 P2

180ControlPeriod 30-60 75 90 120 150

78

TABLE 3.5Arterial plasma free fatty acids levels and net hepatic FFA balance during control (-40 to 0 min) and experimental periods (0-180 min) of studies conducted on 18h fasted conscious dogs exposed to a controlled rise in glucagon in the presence of euglycemia and hypoglycemia.

Free Fatty AcidsArterial plasma levels (µmol/l)

SAL-EU 819 ± 126 136 ± 23 83 ± 9 68 ± 7 57 ± 6 47 ± 4 43 ± 2GGN-EU 835 ± 129 105 ± 26 91 ± 25 68 ± 19 52 ± 15 53 ± 15 45 ± 13

SAL-HYPO 838 ± 87 122 ± 17 249 ± 157 * 617 ± 190 * 676 ± 101 * 600 ± 103 * 547 ± 76 *GGN-HYPO 849 ± 131 96 ± 33 163 ± 51 303 ± 37* † 593 ± 147 * 416 ± 101 * 376 ± 115 *

Net Hepatic FFA Balance (µmol/kg/min)SAL-EU -2.9 ± 0.7 -0.1 ± 0.2 0.0 ± 0.1 0.0 ± 0.1 -0.1 ± 0.1 -0.1 ± 0.2 0.0 ± 0.1GGN-EU -2.7 ± 0.5 -0.3 ± 0.1 -0.2 ± 0.1 -0.2 ± 0.1 0.0 ± 0.1 -0.1 ± 0.1 -0.2 ± 0.1

SAL-HYPO -2.7 ± 0.5 0.1 ± 0.1 -0.6 ± 0.6 -2.4 ± 0.9* -2.9 ± 0.4 * -3.0 ± 1.2 * -2.2 ± 0.6 *GGN-HYPO -3.0 ± 0.7 0.0 ± 0.1 -0.1 ± 0.2 -0.7 ± 0.2 † -2.0 ± 0.8 * -1.4 ± 0.7 † -1.5 ± 0.6 *


Experimental Period

180ControlPeriod 30-60 75 90 120 150

P1 P2

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Discussion

Previous studies have shown that the response of the alpha cell is critical for a

normal counterregulatory response to insulin-induced hypoglycemia (15; 18; 167-169).

In fact glucagon is widely thought to provide the primary defense against a low blood

glucose level. On the other hand, insulin is known to exert a powerful restraining effect

on glucagon’s action (131). This raises the question of how glucagon can have such a

prominent role in counterregulation if it is so easily subject to insulin’s inhibitory action.

The aim of the present study therefore was to determine the extent to which

hypoglycemia enhances glucagon’s ability to overcome insulin’s inhibitory effect on the

liver, and to shed some light on the mechanism by which this comes about. The present

results indicate that hypoglycemia increases glucagon’s ability to increase glucose

production by 2.3 fold even in the presence of extremely high insulin levels. Further,

they also show that this reflects a marked 2.7 fold increase in glycogenolysis which was

associated with a reduction in insulin’s phosphorylation of Akt and enhanced ability of

glucagon to activate GSK-3β.

In the current study, in the presence of hyperinsulinemia and euglycemia a

physiologic rise in glucagon mimicking that seen in response to insulin induced

hypoglycemia caused an increase in net hepatic glucose output that had an AUC of 106

mg/kg bw/120min. On the other hand, when the same rise in glucagon was brought

about under hypoglycemic conditions it produced a 2.3 fold greater increase (239

mg/kg/120min) in NHGO. The rise of glucagon had no effect on net hepatic

gluconeogenic flux under euglycemic or hypoglycemic conditions. In contrast, it had an

almost 3 fold greater effect on glycogenolysis in the presence of hypoglycemia than it did

80

in the presence of euglycemia. It should be noted that the changes in plasma epinephrine,

norepinephrine and cortisol which occurs in response to hypoglycemia were the same

whether glucagon was increased or not and thus a differential response in their secretion

cannot explain any of the differences in glucose production in the two hypoglycemic

groups.

It is possible to estimate how much of glucagon’s full effect is restored in the

presence of hypoglycemia. To do this one needs to determine the effect of an increment

in glucagon of the magnitude used in the present study in the presence of basal insulin

levels. In addition, because under such conditions glucagon would result in

hyperglycemia, one has to take into account the suppression of net hepatic glucose output

that would occur in response to the accompanying increase in glucose. We were able to

do this by analyzing data from earlier studies carried out in our laboratory (26; 131). It

was evident that the full response to a four fold rise in glucagon had an AUC of 423

mg/kg bw/120min. Therefore under euglycemic conditions the rise in insulin which we

employed resulted in a 75% inhibition of glucagon’s action. In the presence of

hypoglycemia, on the other hand, the rise in insulin was only able to reduce glucagon’s

action by slightly more than 40%.

The question then arises as to the mechanism by which the liver’s responsiveness

to glucagon is enhanced by hypoglycemia. It is unclear which physiologic signal,

increased cortisol, increased epinephrine, increased norepinephrine, increased neural

input to the liver, hypoglycemia per se or some combination of these, explains this

important adaptive response. It is certainly possible that hypoglycemia per se brings

about the effect. Previous studies have shown that hyperglycemia per se can inhibit

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hepatic glucose production (170). The biochemical explanation for this effect is that

glucose binds to phosphorylase in the allosteric site of the phosphorylated form of the

enzyme, causing a conformational change that makes phosphorylase a better substrate for

dephosphorylation by protein phosphatase 1 (PP1) (170). This leads to an inactivation of

the enzyme (170). The fact changes in glycogen metabolism provided the explanation for

the augmented response of the liver to glucagon supports this possibility. On the other

hand, Shiota et al. (171) have performed studies using the perfused rat liver to determine

the ability of hyperglycemia to inhibit the response of the liver to glucagon. In their

study they found that the hyperglycemia reduced basal net hepatic glucose output but not

the response of the liver to glucagon.

Another possibility is that the enhanced response to glucagon during insulin-

induced hypoglycemia is related to the interaction of glucagon with one or other of the

counterregulatory hormones. The effects of these hormones in a hypoglycemic setting by

themselves are well established. Epinephrine restrains the fall in glucose by stimulating

hepatic glucose production, limiting glucose utilization and augmenting muscle

glycogenolysis and adipose tissue lipolysis (19; 26; 28; 31). The ability of

norepinephrine to restrain the fall in glucose, while not as potent as epinephrine’s,

involves a stimulatory effect on gluconeogenesis which results from a glycogenolytic

effect in muscle and lipolytic effect in fat (26; 30; 32). Cortisol restrains the fall in

glucose by maintaining substrate availability to support gluconeogenesis (35; 36; 172).

Several studies have looked at the acute interaction of the counterregulatory

hormones. Eigler et al. (173) in the dog and Shamoon et al. (174) in the human studied

the interaction of epinephrine, glucagon and cortisol. In their studies the infusion of the

82

hormones individually resulted in a transient increase in glucose production, but the

effect of glucagon and epinephrine together resulted in additive effects on glucose

production whereas addition of cortisol resulted in a synergistic effect on glucose

production. However, since neither the insulin and/or glucose levels were controlled in

these studies any interpretation of the data is difficult. Lecavalier et al. (175) performed

studies in humans to assess the interaction between glucagon and cortisol on

gluconeogenesis from 14C lactate in a more controlled way. In these studies, glucose was

clamped and they used a pancreatic pituitary clamp to control for changes in insulin,

glucagon and growth hormone. They found that cortisol enhanced glucagon-stimulated

gluconeogenesis in an additive manner. However, the increment in glucagon used in

these studies was very high so it is conceivable that a synergistic effect of the hormones

could have been missed. Gustavson et al. (176) studied the interaction of epinephrine

and glucagon in the regulation of hepatic glucose production at a time when plasma

insulin and hyperglycemia were fixed in overnight fasted conscious dogs. In their studies

the area under the curve for the increase in net hepatic glucose output in the groups was

661±185, 424±158 and 1,178±57 mg/kg in the glucagon, epinephrine and glucagon +

epinephrine groups respectively. This led to the conclusion that the effects of glucagon

and epinephrine on hepatic glucose production are additive but not synergistic.

Therefore, it seems unlikely that the interaction of glucagon with the other

counterregulatory hormones contributes to the increased sensitivity of the liver to the

hormone during insulin-induced hypoglycemia.

It is also interesting to consider the enhancement of glucagon action in the

presence of hypoglycemia at a cellular level. To do so we analyzed key markers in both

83

the insulin and glucagon signaling pathways. Insulin exerts its effect by phosphorylating

Akt, which in turn phosphorylates and inactivates GSK-3β, preventing the

phosphorylation and inactivation of glycogen synthase (177). Thus, phosphorylated

GSK-3β is an indirect marker of increased glycogen synthesis, it can also be indicative of

decreased glycogenolysis, since glycogen synthesis and breakdown are tightly

coordinated. In addition, Akt phosphorylates the transcription factor FOXO1.

Phosphorylated FOXO1 accumulates in the cytosol, decreasing the expression of the

gluconeogenic genes PEPCK and G6Pase, thereby potentially decreasing hepatic glucose

production(178; 179). Conversely, glucagon action leads to the phosphorylation of

CREB which enhances PGC1α transcription (86); PGC1α synergistically acts with

FOXO1 to promote the transcription of both PEPCK and G6Pase, increasing

gluconeogenesis and as a result hepatic glucose production (180-182)

In the present studies the insulin signaling pathway was strongly activated in the

SE group, as evidenced by marked increases in phosphorylated Akt, GSK-3β, and

FOXO1. The addition of glucagon in the presence of euglycemia (GE) did not alter Akt

activation, but led to a partial blunting of GSK-3β, and FOXO1 phosphorylation,

indicating that part of glucagon’s ability to overcome insulin’s inhibition of hepatic

glucose production was related to an impairment in insulin signaling downstream of Akt.

Phosphorylation of Akt was blunted during both hypoglycemic conditions (SH and GH)

suggesting that hypoglycemia or some change associated with it, blunts that ability of

insulin to activate its signaling cascade. Hypoglycemia (in the absence of glucagon; SH)

decreased phosphorylated GSK-3β but the combination of hypoglycemia and glucagon

produced an even more substantial (95%) decrease in GSK-3β phosphorylation relative to

84

that seen in the SE group. In fact the ability of the increase in glucagon to decrease

phosphorylated GSK-3β (SE vs. GE relative to SH vs. GH) was increased 2.3 fold by

hypoglycemia. This correlates well with the 3 fold increase in glycogenolysis caused by

the hormone in the presence of hypoglycemia.

At the same time markers of glucagon signaling indicated that phosphorylated

CREB, as well as PGC1α and PEPCK protein levels were decreased when insulin was

increased (SE). It should be remembered that basal glucagon secretion was inhibited by

somatostatin with the resulting hypoglucagonemia in the SE and SH groups. As such

changes in the SE protocol can be a function of the rise of insulin and/or the fall in

glucagon. Phosphorylated CREB and PEPCK levels were restored to control values by

glucagon (GE). PGC1α, on the other hand, was increased above the control value by

glucagon. Hypoglycemia (in the absence of glucagon; SH) caused similar changes. The

addition of glucagon to hypoglycemia did little to magnify these changes.

Gene expression data confirmed that PEPCK and G6Pase mRNA levels were

substantially reduced by the rise in insulin (SE) and the fall in glucagon. Addition of the

increase in glucagon or hypoglycemia (in the absence of glucagon) doubled the mRNA

expression of both enzymes. Addition of an increase in glucagon to hypoglycemia did

not increase the expression of PEPCK mRNA further but it did increase the expression of

G-6-Pase mRNA by twofold over what it did under euglycemic conditions. Taken

together the molecular data support a reduction in insulin signaling in the presence of

hypoglycemia combined with an enhanced ability of the increase in glucagon to decrease

the phosphorylation of GSK-3β and to increase G-6-Pase gene expression.

85

It is worth noting that 90% fall in mRNA for PEPCK was associated with only a

40% fall in PEPCK protein and little or no change in net hepatic gluconeogenic flux (SE).

These data are consistent with those from Burgess et al. (183) in which isolated perfused

livers with a 90% reduction of PEPCK content showed only a 40% reduction in

gluconeogenic flux, indicating that PEPCK content has limited control strength over the

gluconeogenic process. Hypoglycemia markedly increased NHGNG flux despite PEPCK

mRNA still being reduced by almost 80% and PEPCK protein being unchanged from

control values. The question thus arises as to how the increase in gluconeogenesis comes

about. The answer lies in the large increases in the delivery of gluconeogenic precursors

to the liver during hypoglycemia.

In muscle, in the presence of hyperinsulinemic hypoglycemia (SH, GH) there

was a marked increase in the arterial blood lactate level and as a resulting in net hepatic

lactate uptake. This indicates that production of lactate by muscle increased dramatically

as a result of the rise in catecholamines (31; 32), neural input to muscle and/or

hypoglycemia per se. The increase in glucagon had no impact on the rise in blood lactate

or net hepatic lactate uptake.

Lipolysis is best estimated from the glycerol data since glycerol must be released

from the fat cell and can not be used for re-esterification. In the presence of

hyperinsulinemic euglycemia (SE) there was a marked inhibition of lipolysis as indicated

by a fall in blood glycerol levels. In the presence of the same conditions a physiologic

rise in glucagon had no effect on lipolysis. During insulin-induced hypoglycemia (SH,

GH), there was a marked increase in arterial blood glycerol and net hepatic glycerol

uptake indicating a dramatic rise in lipolysis. This was the result of the lipolytic effect of

86

catecholamines, hypoglycemia per se and/or neural input to fat (31; 32) Once again the

rise in glucagon had no effect on the response. Thus the marked increase in the net

hepatic gluconeogenesis in response to hypoglycemia was a function of increased

substrate delivery to the liver rather than a stimulation of the hepatic gluconeogenic

pathway per se. Addition of a physiologic rise in glucagon to hypoglycemia and its

various effects doubled the magnitude of the increase in glucose production which

occurred. This underscores the importance of glucagon to the increase in hepatic glucose

production seen during insulin-induced hypoglycemia. For this to be relevant to the

normal response to insulin-induced hypoglycemia it is important to point out that the

magnitude of the increment in glucagon which we used in the study represents the normal

physiologic response of glucagon to hypoglycemia of 50 mg/dl caused by insulin infusion

at 5.0 mU/kg/min and plasma glucose decrease to 50 mg/dl. Frizzell et al. (7) showed

that when insulin was infused at 5mU/kg/min, the increment in glucagon levels over 2

hours was Δ 9510 pg/kg bw/120 min. The increment in glucagon in our studies was Δ

8276 pg/kg bw/120 min. Therefore, the rise in glucagon which we used in our studies

represents a normal response of the hormone to hypoglycemia. It should be noted,

however, that we used a square wave elevation of glucagon to simplify the experimental

design whereas under normal circumstances the response would have had a spike decline

pattern.

In summary, hypoglycemia increased glucagon’s ability to overcome insulin’s

inhibitory effect on hepatic glucose production. This effect was attributable to a marked

(almost 3-fold) enhancement of net glycogen breakdown. It paralleled an increase in the

ability of glucagon to reduce the phosphorylation of GSK-3β in the presence of

87

hypoglycemia as opposed to euglycemia. At the same time hypoglycemia decreased

insulin’s activation of its signaling cascade. Proof that it is hypoglycemia per se, rather

than an increase neural input to the liver, or increases in some other component of the

counterregulatory response remains to be obtained.

Summary and Conclusions

In the United States, approximately 23.2 million people have diabetes (~8% of

population). Of those 18.6 million have been diagnosed and 4.6 million do not yet know

they have the disease. There are three types of diabetes: type1 diabetes, type 2 diabetes

and gestational diabetes. Type 1 diabetes is an autoimmune disease in which the immune

system destroys the insulin-producing β cells in the pancreas. Type 1 diabetes accounts

for about 5 to 10 percent of diagnosed diabetes. On the other hand, Type 2 diabetes

which is the most common form of diabetes accounts for ~ 90-95% of people with the

disease. Type 2 diabetes is characterized by insulin resistance and hyperglycemia.

Gestational diabetes is a type of diabetes that occurs only during pregnancy. Although

this form of diabetes usually disappears after birth of the baby, women who have had

gestational diabetes have a 20% to 50% chance of developing Type 2 diabetes within 5-

10 years.

Glycemic control is fundamental for the management of the disease. Reduction

of glucose levels prevents macrovascular and microvascular complications such as heart

disease, retinopathy, nephropathy and neuropathy in both type 1 and type 2 diabetes.

Another complication that is a limiting factor in the management of diabetes is

hypoglycemia. Hypoglycemia is the most frequent complication of insulin-requiring

diabetes and the principal factor limiting optimization of glycemic control. Is typically

88

the result of the interplay of insulin excess and compromised glucose counterregulation in

individuals with type 1 diabetes. In addition, it may contribute to recurrent morbidity in

patients with type 1 diabetes and may sometimes be fatal in patients with advanced,

insulin-requiring type 2 diabetes.

Hypoglycemia triggers the activation of a counterregulatory response to increase

glucose production. The counterregulatory response to hypoglycemia involves the

release of glucagon, epinephrine, norepinephrine and cortisol. Glucagon increases

glucose production by activating glycogenolysis and gluconeogenesis; however, its effect

on gluconeogenesis is limited by its inability to increase gluconeogenic substrate delivery

to the liver. Epinephrine stimulates hepatic glucose production through activation of

gluconeogenesis and glycogenolysis. Norepinephrine increases hepatic glucose

production by increasing gluconeogenesis which results from a glycogenolytic effect in

muscle and a lipolytic effect in fat. Cortisol stimulates hepatic glucose production by

maintaining substrate availability to support gluconeogenesis and limits glucose

utilization.

Glucagon is the primary hormone involved in the regulation of glucose

production. In addition, previous studies have shown glucagon remains the most

important regulator of glucose production even in the presence of very high insulin levels

(18). In contrast, under euglycemic conditions Steiner et al. (131) have shown that

insulin is a potent inhibitor of glucagon’s effect on the liver. Therefore, our aim was to

determine the extent to which hypoglycemia augments glucagon’s ability to increase

glucose production and at a molecular level, how it does so.

89

In the studies described in this dissertation, hypoglycemia increased glucagon’s

ability to overcome insulin’s inhibitory effect on hepatic glucose production 2.3 fold.

This effect was attributable to a marked (almost 3-fold) enhancement of net glycogen

breakdown which was associated with a 2.3 fold increase in the ability of glucagon to

reduce the phosphorylation of GSK3β caused by insulin.

It remains unclear which physiologic signal (increased cortisol, epinephrine,

norepinephrine, neural input to the liver or hypoglycemia per se) explains this adaptive

response. Therefore future studies should be conducted to determine which of these

physiological signals is responsible for the enhancement of glucagon action. It would be

of interest therefore to determine the effects of these other counterregulatory hormones

on glucagon’s action. One could conduct studies to assess the physiologic effects of

elevated cortisol, epinephrine and norepinephrine with or without a rise in glucagon in

the presence of euglycemia and hyperinsulinemia. The counterregulatory hormones

would be selectively increased to the levels seen during hypoglycemia and euglycemia

would be maintained in order discriminate between the effects of the counterregulatory

hormones and hypoglycemia per se. To assess the role of hypoglycemia per se in

overriding insulin’s inhibitory effect on glucagon action one could conduct studies in

adrenalectomized dogs. Using this approach we could eliminate the effects of

epinephrine and cortisol by removing the adrenal glands and because most of the

norepinephrine involve in the counterregulation process is released from sympathetic

postganglionic neurons one could use a α1-adrenergic blocker to inhibit norepinephrine

effects on the liver (24). Glucagon would be selectively increased and its physiologic

effect in overriding insulin’s inhibitory effect would be determined in the presence of

90

hyperinsulinemic-euglycemic or hyperinsulinemic-hypoglycemic conditions. These

studies would therefore determine if hypoglycemia itself is making glucagon more

effective during insulin-induced hypoglycemia.

91

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