Published in Volume
117, Issue 9 (September 4, 2007)
J Clin Invest. 2007;117(9):2621–2637.
doi:10.1172/JCI31021.
Copyright © 2007, American Society for Clinical
Investigation
Research Article
Obesity-associated improvements in metabolic profile through expansion of
adipose tissue
Ja-Young Kim1, Esther van de Wall2, Mathieu Laplante3, Anthony Azzara2, Maria E. Trujillo1, Susanna M. Hofmann4, Todd Schraw1, Jorge L. Durand5, Hua Li5, Guangyu Li6, Linda A. Jelicks5, Mark F. Mehler6, David Y. Hui4, Yves Deshaies3, Gerald I. Shulman7, Gary J. Schwartz2,6,8,9 and Philipp E. Scherer10
1Department of Cell Biology and
2Department of Medicine,
Albert Einstein College of Medicine, New York, New York, USA.
3Department
of Anatomy and Physiology, Laval University Hospital Centre Research Centre, Laval
University School of Medicine, Quebec City, Quebec, Canada.
4Department
of Pathology, Genome Research Institute, University of Cincinnati, Cincinnati, Ohio,
USA.
5Department of Physiology and Biophysics and
6Department of Neuroscience, Albert Einstein College of Medicine, New
York, New York, USA.
7Department of Internal Medicine and Department of
Cellular and Molecular Physiology, Yale University School of Medicine, and Howard Hughes
Medical Institute, New Haven, Connecticut, USA.
8Department of Molecular
Pharmacology and
9Diabetes Research and Training Center, Albert Einstein
College of Medicine, New York, New York, USA.
10Touchstone Diabetes
Center, Department of Internal Medicine, University of Texas Southwestern Medical
Center, Dallas, Texas, USA.
Address correspondence to: Philipp E. Scherer, Touchstone Diabetes Center,
Department of Internal Medicine, University of Texas Southwestern Medical Center,
5323 Harry Hines Blvd., Dallas, Texas 75390-9077, USA. Phone: (214) 648-8715; Fax:
(214) 648-8720; E-mail: philipp.scherer@utsouthwestern.edu.
First published August 23, 2007
Received for publication November 21,
2006, and accepted in revised form May 31,
2007.
Excess caloric intake can lead to insulin resistance. The underlying reasons are
complex but likely related to ectopic lipid deposition in nonadipose tissue. We
hypothesized that the inability to appropriately expand subcutaneous adipose tissue
may be an underlying reason for insulin resistance and β cell failure.
Mice lacking leptin while overexpressing adiponectin showed normalized glucose and
insulin levels and dramatically improved glucose as well as positively affected
serum triglyceride levels. Therefore, modestly increasing the levels of circulating
full-length adiponectin completely rescued the diabetic phenotype in
ob/ob mice. They displayed increased expression of
PPARγ target genes and a reduction in macrophage infiltration in adipose
tissue and systemic inflammation. As a result, the transgenic mice were morbidly
obese, with significantly higher levels of adipose tissue than their
ob/ob littermates, leading to an interesting dichotomy of
increased fat mass associated with improvement in insulin sensitivity. Based on
these data, we propose that adiponectin acts as a peripheral
“starvation” signal promoting the storage of triglycerides
preferentially in adipose tissue. As a consequence, reduced triglyceride levels in
the liver and muscle convey improved systemic insulin sensitivity. These mice
therefore represent what we believe is a novel model of morbid obesity associated
with an improved metabolic profile.
Introduction
Adipose tissue plays a central role in the management of systemic energy stores as
well as in many other processes (1). This is
in part due to its capacity to store triglycerides but is also a function of its
ability to secrete many proteins that have a major impact on energy homeostasis. A
dysregulation of both processes leads to profound changes in insulin sensitivity at
the level of the whole organism. Mice lacking specific adipocyte-derived secretory
proteins, such as leptin, adiponectin, and resistin have metabolic phenotypes. On
the other hand, mice lacking adipocytes altogether also display profound changes.
Studies of several lipoatrophic models have been published (2–4). A
common observation regarding many of these lipoatrophic or lipodystrophic models is
that in the absence of functional adipocytes, triglycerides tend to be stored
ectopically in liver and muscle. These lipids, particularly as they relate to lipids
in the liver, have been closely linked to insulin resistance (5).
This raises an interesting question. If accumulation of lipids in the liver and
muscle were a “spillover” effect from adipose tissue, would
it be possible to prevent this ectopic lipid accumulation if we enabled adipose
tissue to expand beyond the limits observed under normal physiological conditions?
We tested this in the context of ob/ob mice. The absence of leptin
induced a massive hyperphagia and reduced energy expenditure, which are associated
with a decrease in circulating adiponectin, a phenomenon shared by most obese,
insulin-resistant models. The mice displayed dyslipidemia, hyperglycemia, and
hyperinsulinemia. They accumulated large amounts of triglycerides in adipose tissue
and are as a result among the most obese mouse models available to date. Despite
massive obesity, the mice displayed a significant accumulation of hepatic
triglycerides relatively early in life. This was an ideal setting to establish
conditions that would allow adipose tissue to expand further. We found that
overexpression of a mutated version of the adipokine adiponectin led to a
significant increase in circulating levels of WT adiponectin protein as well as to
an increase in adipocyte cell number and hence to an overall expansion of adipose
tissue mass. Surprisingly, the uninhibited expansion of adipose tissue led to a
complete normalization of all metabolic parameters tested despite the morbid
obesity.
While many mouse models with defects in proper adipose tissue development have been
described, we believe this is the first genetically engineered model that directly
highlights that fat mass expansion has potent antidiabetic effects. These
observations fully support the data obtained in pharmacological models in which an
effective expansion of fat mass can be encountered, such as in the context of the
PPARγ agonists, the thiazolidinediones. They suggest that one of the key
factors that link excess caloric intake and a positive energy balance with insulin
resistance and type 2 diabetes is the inability to appropriately expand the
(subcutaneous) adipose tissue. With respect to adiponectin physiology, they suggest
that adiponectin serves as a starvation signal released by the adipocyte, indicating
a local need to further expand triglyceride stores in adipose tissue. As a result,
triglycerides were effectively redistributed from hepatocytes and muscle cells to
subcutaneous adipose tissue. This redistribution coupled to increased adipogenesis
resulted in the expected improvements in all the metabolic parameters, including a
reduction in a number of proinflammatory factors.
Results
Transgenic ob/ob mice overexpress adiponectin at levels comparable to those
obtained by PPARγ agonist treatment. To determine the consequences of a moderate overexpression of full-length
adiponectin in ob/ob mice, we used a transgenic cassette that
we have previously described (6). This
triggered an effective increase of steady state concentrations of adiponectin in
plasma about 2- to 3-fold above baseline. This increase was comparable to the
levels that can be obtained in ob/ob mice upon exposure to
PPARγ agonists (Figure 1A).
Similarly, tissue-associated adiponectin levels were also increased at a
comparable degree in a number of different fat pads, except in brown adipose
tissue (Figure 1B). This represented a
relatively modest overexpression of adiponectin, well within the physiological
range (7). Since adiponectin circulates in
several different forms in plasma, we measured the relative abundance of the
different complexes by gel filtration analysis, a method that efficiently
separates high molecular weight, hexameric, and trimeric complexes. The
transgenic mice carried all 3 complexes in circulation, albeit with a slight
bias toward higher HMW forms compared with ob/ob mice (Figure
1C). We conclude therefore that this is
a model of modest overexpression of adiponectin with properly assembled
complexes in circulation.
Modest adiponectin overproduction results in dramatic improvements in the
baseline values of metabolic parameters of ob/ob mice. To determine whether this modest overexpression of adiponectin has an impact on
any of the metabolic parameters dysregulated in ob/ob mice, we
determined fasting glucose, insulin, triglyceride, and FFA levels (Table 1). All parameters measured showed dramatic
improvements, with glucose levels reaching near hypoglycemic levels, insulin
levels significantly lowered, and a highly significant lowering of triglycerides
and FFAs.
Normalization of parameters during metabolic challenges. We wanted to know whether these improvements in baseline values also translated
into improvements upon exposing the mice to glucose and lipid challenges. During
an oral glucose tolerance test (OGTT), the transgenic animals displayed a much
more efficient clearance of systemic glucose levels than ob/ob
littermates (Figure 2A). In addition, the
transgenic animals had a much more robust glucose-induced insulin release during
the OGTT compared with the hyperinsulinemic ob/ob littermates,
which showed a much more delayed and less dramatic increase over baseline
(Figure 2A). Upon exposure of the mice to
an oral triglyceride gavage, ob/ob mice showed the expected
high excursion/slow clearance of triglycerides from circulation. The increased
levels of adiponectin levels effectively prevented circulating lipids from ever
rising much above baseline. As there was no evidence for malabsorption of
nutrients from the gut (data not shown), this suggests that the transgenic mice
developed extremely efficient mechanisms for the removal of dietary fat from
circulation (Figure 2B).
To determine whether an induced loss of function of adiponectin in the
transgenics has an impact on the rate of lipid clearance, we treated the mice
for 1 week with either a mixture of 2 monoclonal antibodies raised against
adiponectin that effectively trigger a reduction in circulating adiponectin or
with equal amounts of a nonimmune mouse IgG preparation (Figure 2C). The relatively sudden reduction in adiponectin
levels led to a trend toward reduction in the clearance rate of the ingested
triglycerides, suggesting that both acute and chronic differences mediated the
metabolic differences between these 2 mouse models.
As an additional functional test for both adipocytes and β cells, we
exposed the mice to an injection of the β3 adrenergic agonist
CL-316,243. Exposure to CL-316,243 triggered a response that was critically
dependent on the presence of the β3 adrenergic receptor in white
adipose tissue (WAT) and resulted in a very acute, sharp rise in insulin
secreted from pancreatic β cells (8). The underlying reasons for this phenomenon are not yet known,
but fully functional WAT and functional β cells are required.
CL-316,243 significantly stimulated lipolysis in both mouse models assessed by
increased circulating FFAs after stimulation. While the baseline FFA values had
a tendency to be lower in the transgenic mice, β3
agonist–mediated lipolysis was increased compared with that of
ob/ob mice (Figure 2D). However, more dramatic differences became apparent when looking at
β3 agonist–stimulated insulin release. Mice lacking
leptin were hyperinsulinemic at baseline but failed to further increase the
insulin levels upon stimulation. The transgenic animals, in contrast, showed a
robust increase in insulin release upon stimulation of β3 adrenergic
receptors in WAT, suggesting full reconstitution of this process both at the
level of WAT and at the level of pancreatic β cells (Figure 2D).
Effects on lipoprotein particle distribution. In light of the fairly dramatic effects seen on baseline triglyceride levels and
during the oral triglyceride gavage, we wanted to see whether there were any
changes in lipoprotein particle distribution. To that end, we size fractionated
serum from the 2 strains by conventional size-exclusion chromatography and
measured cholesterol and triglyceride distribution (Figure 2E). In addition to a reduction of total cholesterol
levels in all particle fractions, there were also subtle but reproducible shifts
toward a higher density within the cholesterol containing HDL particles.
Adiponectin-overexpressing mice showed a marked decrease in the main HDL peak
and in the shoulder, where HDL-1 and LDL elute, compared with the plain
ob/ob background. The triglyceride levels associated with
the particle fractions were so low in the transgenic animals that, with the
exception of the VLDL fraction, triglyceride levels were below the detection
limit in all particle fractions. The apoE content of HDL was reduced in
adiponectin-overexpressing ob/ob mice compared with
ob/ob mice, suggesting that adiponectin reduces the levels
of apoE-enriched, cholesterol ester rich HDL-1 (Figure 2F). On the other hand, the apoA1 and A2 content of
HDL were similar in both transgenic and nontransgenic mice (data not shown).
This suggests that the increased levels of adiponectin may effectively overcome
the established impairment in HDL turnover that normal ob/ob
mice display (9).
Transgenic mice are resistant to the deleterious impact of high-fat diets on
insulin sensitivity. Exposure to a high-fat diet for 6 weeks further exacerbated the effects on
glucose and lipids. High-fat diet further impaired the metabolic state of
ob/ob mice, yet adiponectin-overexpressing mice are
resistant to this high-fat diet–induced deterioration of metabolic
parameters. Glucose levels remained unchanged on the high-fat diet (Figure 2G), and OGTT did not show significant change
in glucose clearance (Figure 2G), while
ob/ob mice demonstrated a worsening of the clearance rate.
Insulin levels remained low, and FFA levels did not change significantly either
(Figure 2G).
In addition, we wanted to determine whether the ability to respond to a central
hypoglycemic stimulus was preserved in the transgenic animals compared with
ob/ob animals. We infused a bolus of 2-deoxyglucose (2DG)
centrally i.c.v. This mimicked a systemic hypoglycemic response, prompting
central compensatory mechanisms, triggering a number of peripheral responses and
sending a strong vagal stimulus to the liver to initiate a gluconeogenic
response (10). In WT animals, the
resulting hyperglycemia triggered the expected compensatory reduction of hepatic
glucose output, leading to a rapid normalization of plasma glucose levels. While
ob/ob mice displayed a very significant initial excursion
of glucose levels, they failed to appropriately compensate for hepatic glucose
output and remained hyperglycemic throughout the rest of the time course. The
transgenic animals, however, displayed a response comparable to that of WT mice,
further highlighting the improvements in hepatic carbohydrate metabolism (Figure
2H).
The metabolic improvements are associated with an increase in adipose tissue
mass. A systematic analysis of the age-dependent weight gain revealed that
ob/ob animals with increased adiponectin levels displayed
markedly higher body weights than their ob/ob counterparts, the
current gold standard for obesity in mice (Figure 3A). As these mice aged, the average weight difference was more than
30 grams. A representative example of 2 male siblings, one with, the other one
without transgene is shown.
Body composition analysis performed with an EchoMRI revealed that all of the
extra body weight could be accounted for by an increase in adipose tissue mass
(Figure 3B). Due to the size restrictions
for the conventional EchoMRI machines, only young animals could be measured for
body composition. The absolute weight contributions of the 3 different
compartments that can be distinguished by EchoMRI are indicated, referring to
lean body mass, fat mass that includes adipose tissue, and contributions of
other compartments, such as bone. The weight differences became more extreme
when the mice were exposed to a high-fat diet (Figure 3C). The transgenic mice showed a significant increase
in fat mass while preserving euglycemia (Figure 2G). A histological examination of various adipose tissue pads
revealed remarkable differences with respect to average adipocyte size. The fat
from ob/ob mice displayed the expected enlarged, lipid-engorged
adipocytes. Adipose tissue from transgenic animals, in contrast, displayed a
larger number of adipocytes with much smaller average cell size in gonadal fat
pads (Figure 3D). Similar observations can
be made for other fat pads, such as subcutaneous fat (data not shown). A
representative picture of gonadal adipose tissue is shown in Figure 3E. Quantification of average cell area in a
number of representative histological sections (Figure 3D) further highlighted the significant size
difference. In light of the overall increase in adipose tissue mass, this
suggests that the transgenic mice displayed a significant hyperproliferation of
adipocytes.
Normalization of islet size and reduction of liver triglyceride and
diacylglycerol content. To test whether the improvements in systemic insulin sensitivity are also
associated with improvements at the level of the β cell, we examined
a large number of pancreatic sections histologically. The average islet diameter
was considerably reduced compared with the classical hypertrophic phenotype seen
in the islets of ob/ob mice (judged both histologically and
quantitatively), and the overall integrity of the islets was much better
preserved (Figure 3E).
The ob/ob mice displayed a propensity to accumulate
triglycerides in the liver, a phenomenon that is likely to contribute to the
reduced systemic insulin sensitivity. Liver sections from ob/ob
animals displayed a clearly visible positive signal for oil red O, a stain
highlighting neutral lipids in tissues (Figure 3F). There was a marked reduction in the lipid stain in the
transgenic animals. Measurements of total liver triglycerides confirmed the
visual impression, highlighting the marked decrease in hepatic steatosis (Figure
3F). This was further corroborated with
measurements of one of the key metabolites, diacylglycerol (DAG), in the liver.
DAG can activate a number of PKC isoforms, some of which have been implicated as
inhibitors of insulin signaling. Specifically, activation of DAG-sensitive PKC
isoforms that include PKC-θ in skeletal muscle (11) and PKC-e in the liver (12–14) downregulates insulin receptor signaling and may represent a
biochemical link between dysregulated lipid metabolism and insulin resistance.
DAG levels were indeed reduced in transgenic animals (Figure 3F), lending further support for the presence of an
excellent hepatic metabolic profile despite a high degree of adiposity.
Subcutaneous, but not intraabdominal, fat pads increase in size. Upon dissection of the animals, it was quite apparent that the visceral fat pads
in the transgenic animals matched more closely those found in WT animals than
those of their obese littermates (Figure 3G) while most other fat pads displayed the expected increase in volume
(data not shown). The increase in overall adiposity was therefore primarily due
to increases in nonvisceral depots, i.e., subcutaneous adipose tissue. One
notable exception was the pericardial fat, which was disproportionately
increased in the transgenic mice as well, leading to a 5-fold increase in total
pericardial fat mass. A representative pair of pericardial fat pads is shown in
a 3D reconstitution (Figure 3H). Of note is
also the observation that the heart volume of the transgenic animals was
significantly larger (>30%) than that of ob/ob mice (not
shown), suggesting that excess adiponectin leads to cardiomyopathy. Whether this
is a specific consequence of excess adiponectin in circulation or the result of
the overall increase in weight is not known to date. No weight differences were
observed for other organs, such as the liver, and the increased heart weights
can be observed even in transgenic animals on a WT background that do not
display such a significant increase in overall fat mass (data not shown).
Significant improvements in hepatic insulin sensitivity. To determine whether hepatic insulin sensitivity improved in the transgenic mice,
we performed an in vivo insulin sensitivity assay. Mice were fasted and injected
with insulin, and livers were then extracted after the indicated time points.
Analysis of the phosphorylation state of the insulin receptor and a number of
downstream targets demonstrated a significant improvement in insulin sensitivity
as judged by the increased phosphorylation state of these proteins upon insulin
exposure (Figure 3I).
Immunohistological analysis of islets and adipose tissue revealed
dramatically improved islet histology. To see whether the normalization of islet size also translated into a
normalization of cell-type distribution, we performed an immunohistochemical
analysis of islets (Figure 4A). Compared
with islets from ob/ob mice, transgenic ob/ob
mice displayed a normalized distribution and staining intensity for
α cells (glucagon) and β cells (insulin). The
immunohistological appearance of these islets was nearly identical to what can
be observed in WT animals.
Macrophage infiltration is not a function of fat mass. It is well established that increased adiposity is associated with increased
infiltration of macrophages into adipose tissue (15, 16). The transgenic model
presented here offers an interesting opportunity to determine whether this is
strictly a function of fat mass. Staining of WAT with antibodies to the
macrophage marker F4/80 showed the expected high frequency of F4/80-positive
cells in the ob/ob mice. Interestingly, despite the massive
obesity in the transgenic ob/ob mice, it was difficult to
detect any F4/80-positive cells in the WAT of these mice (Figure 4B). Due to the nonquantitative nature of
immunohistochemistry, we complemented this data with FACS analysis to quantitate
the number of macrophages in the fat pads isolated from the 2 mouse strains.
This analysis confirmed the immunohistochemical data, as the number of
macrophages was sharply reduced in the fat pad isolated from transgene-positive
mice (Figure 4C). This was further
confirmed by quantitative RT-PCR (qRT-PCR) for the message for the F4/80 surface
marker (Figure 4C). In addition, we aimed
to obtain a quantitative measurement of the degree of inflammation in the
vascular endothelium in adipose tissue of these mice. We used vWF as a marker of
the endothelium, which is relatively constitutively expressed, and VCAM-1 as an
inflammation-sensitive readout. The ratio of VCAM-1 to vWF was therefore a
valuable indicator of the local degree of inflammation in the endothelium.
Figure 4D shows that this ratio between
these 2 markers was significantly smaller in the transgenic animals. Therefore,
a statistically significant decrease was observed in the vasculature of
transgenic adipose tissue with respect to the degree of inflammation. As we and
others have demonstrated a significant impact of adipose tissue on systemic
inflammation with respect to IL-6 levels, we predicted that in light of the
reduced overall inflammation in adipose tissue, the systemic levels of IL-6
should also drop in the transgenic animals. As seen in Figure 4E, the circulating IL-6 levels were significantly
reduced in the animals expressing increased levels of adiponectin. In addition,
we also performed qRT-PCR analysis for TNF-α in adipose tissue,
which was also reduced (Figure 4E).
Changes underlying the altered metabolic phenotype in the transgenic
mice. To gain a better understanding of the underlying molecular changes that led to
the improvements in the metabolic phenotype, we looked at a number of different
parameters in adipose tissue and in plasma. Lipoprotein lipase (LPL) plays a key
role in the clearance of circulating triglycerides and their routing toward
storage or oxidative tissues. LPL activity was elevated in several white fat
pads of transgenic animals (Figure 5A).
When expressed per whole depot, LPL in the expanded subcutaneous fat was
increased more than 2-fold, and it was increased 5-fold in brown adipose tissue
of transgenic compared with ob/ob littermates (not shown).
Concomitantly, there was a marked elevation in heparin-releasable LPL in plasma,
a reflection of the global intravascular availability of the enzyme. An overview
of the expression levels of mRNAs encoding some relevant enzymes in lipid
metabolism demonstrated increases in cytosolic phosphoenolpyruvate carboxykinase
(PEPCK), diacylglycerol acyltransferase (DGAT-1), PPARγ2, and
adipocyte/macrophage fatty-acid–binding protein (aP2) in the adipose
tissue (Figure 5B). LPL, PEPCK, DGAT-1, and
aP2 are all well established PPARγ targets. To obtain a more
comprehensive overview of gene expression in the adipose tissue of transgenic
mice, a series of microarray experiments was performed. This global gene
expression analysis with NimbleGen arrays revealed a large number of
transcriptional changes in adipose tissue of transgenic mice. The general
transcriptional fingerprint of this adipose tissue revealed an increase in
lipogenesis along with an increase in the levels of mitochondrial genes and a
reduction of proinflammatory markers (Supplemental Table 1; available online
with this article; doi:10.1172/JCI31021DS1), consistent with reported changes
upon PPARγ agonist treatment. Indeed, mRNA levels of
PPARγ, PGC1α,β, and RXRα were
also increased. Importantly, the microarray data fully confirmed the data
obtained independently by qPCR for PEPCK, DGAT-1, PPARγ2, and aP2.
Elevation of peripheral adiponectin reduces food intake and energy
expenditure. An important question is whether the massive accumulation of adipose tissue is
the result of increased caloric intake or reduced energy expenditure or a
combination of the two. Mice lacking leptin and their transgenic littermates ate
approximately the same amount of food per gram of lean body mass when they were
young or old (Figure 6A). Since the
transgenic littermates were much heavier at a later age, this translates into a
very significantly reduced amount of food intake per gram of body weight in the
presence of the transgene (Figure 6A). In
light of the net increase of body fat, this suggests that the transgenic mice
were metabolically much more efficient. Consistent with that, the body core
temperature was significantly lower in the transgenic animals at all ages,
particularly during the dark cycle (Figure 6B). The essential finding is therefore that the transgenic mice had
a food intake comparable to that of their ob/ob littermates.
While we expected a higher energy expenditure in these heavier animals, the
exact opposite occurred. This suggests that adiponectin overexpression results
in a negative regulation of energy expenditure.
Unlike ob/ob animals, transgenic animals showed reductions in
multiple behavioral and physiological measures relevant for determining overall
energy balance, including body temperature, locomotor activity, and oxygen
consumption. These reductions were characterized by a relative absence of
typical diurnal rhythms. While lateral ambulatory and vertical rearing movement
were not significantly different in younger animals (data not shown), older
transgenic animals were significantly less active than age-matched
ob/ob mice, again particularly during the dark cycle
(Figure 6C). In light of the reduced
caloric intake and increased fat mass, an overall improvement in metabolic
efficiency would be expected. Energy expenditure was indeed reduced in the
transgenic mice, accounting at least in part for the increased ability to store
triglycerides in the context of reduced caloric intake. Oxygen consumption was
reduced in the transgenic animals, as assessed by reduced oxygen volume per time
(VO2), particularly during the dark cycle. (Figure 6D). No significant differences were seen between the
2 models at the level of the respiratory exchange ratio (RER) during free access
to food (Figure 6E).
Increasing adiponectin levels in the absence of leptin leads to starvation
intolerance. The very high tendency to store triglycerides in adipose tissue raises the
question of whether these lipid stores can appropriately be activated in times
of need. In principle, the β3 adrenergic axis was intact in both
mouse models with respect to induction of lipolysis (Figure 2D). However, it was not clear whether this translates
into an equally efficient response to starvation. Preliminary experiments in the
context of caloric restriction had demonstrated that the increased levels of
adiponectin resulted in a decreased weight loss during caloric restriction (data
not shown), suggesting that it may be more difficult for the transgenic mice to
tap into lipid stores during times of reduced exogenous caloric intake.
RER values were not significantly different between the 2 mouse lines during free
access to food. However, during an acute fast, RER dropped significantly faster
in the transgenic mice, suggesting an increased dependence on fatty acid
oxidation early on in the fast (Figure 6F).
Nevertheless, both strains reached asymptotic respiratory quotient values
characteristic of fat mobilization within 12 hours. Activity increased in both
groups in response to fasting, but activity levels were lower overall in
transgenic mice (Figure 6G). Furthermore,
increases in circulating adiponectin seen in the transgenic mice cause the
complete absence of any diurnal variability of glucose and FFAs, while
ob/ob mice maintained a clear diurnal pattern (Figure 6H). Unlike fasted controls, fasted
transgenic mice showed no diurnal variation in plasma glucose and FFA and
overall had markedly reduced levels of these fuels relative to controls.
However, the transgenic animals managed to sustain reasonable glucose and FFA
levels at all times. Fasting VO2 and core temperature did not differ
significantly between strains (Figure 7A),
and fasting restored the diurnal fluctuations in both VO2 and core
temperature in transgenic mice. In a separate experiment, we subjected cohorts
of male and female mice to a 36-hour fast. We noticed that the fasted transgenic
mice lost less weight than fasted ob/ob controls. This was a
phenomenon seen in both females (Figure 7B)
and males (data not shown), but the females showed a more pronounced difference.
Similarly, the females had a more severe trend toward hypoglycemia during the
fast (Figure 7C). In light of the lower
plasma glucose levels in the transgenic animals throughout the fast, we wanted
to test whether the livers from these animals displayed a reduced ability to
induce gluconeogenesis. To do that, we looked at the message levels of PEPCK and
glucose-6-phosphate (G-6-P). Changes in the message levels for these 2 enzymes
are suggestive of changes in the gluconeogenic pathway. While the males did not
display a significant difference, the transgenic females had a significantly
impaired ability of liver to mount a gluconeogenic response, consistent with the
hypoglycemia observed throughout the fasting experiment (Figure 7D). The more striking effects in the females were
consistent with the considerably higher adiponectin levels that could be
achieved in females in this model (6).
Discussion
To our knowledge, this is the first detailed analysis of a mouse model that directly
supports the hypothesis that enabling a massive expansion of the subcutaneous
adipose tissue mass potently counteracts the strong trends toward the development of
insulin resistance associated with excess caloric intake. We have chosen to address
this issue in the ob/ob mouse model. These mice displayed
hyperphagia and early onset obesity, resulting in hyperglycemia, hyperinsulinemia,
and dyslipidemia. We achieved a normalization of all metabolic parameters through a
modest overexpression of adiponectin. We were employing a transgene under the
control of the fat cell–specific aP2 promoter that we previously
characterized in the background of WT mice. This transgene encodes a version of
adiponectin that carries a deletion within the collagenous domain of the protein,
leading to the formation of a subset of mixed WT/mutant complexes. The detailed
mechanism of action of these mutant protein complexes is currently under study in
our laboratory. The net effect is an improved efficacy of the secretory pathway with
respect to adiponectin assembly and release, leading to a 2- to 3-fold elevation of
steady state levels of WT adiponectin complexes in plasma.
We challenged these mice metabolically by breeding them into the ob/ob
background. The leptin deficiency induced hyperphagia. This resulted in a
gradual increase in adipose tissue mass. Under these conditions, this expansion of
the fat mass was associated with a reduction of circulating adiponectin levels.
However, in the transgenic mice, this obesity-induced downregulation did not occur,
but instead, there was a constitutive elevation of both intracellular and plasma
adiponectin levels despite a continued increase in fat mass. The end result of this
chronic elevation of adiponectin in transgenic ob/ob mice was a
very significant expansion of the fat mass.
Phenotypically, this resulted in improvements in all metabolic parameters examined as
they relate to glucose and lipid metabolism. Concomitant with the metabolic
improvements, there was a positive impact on the inflammatory profile. The
underlying mechanisms for these improvements are complex, but are likely related to
the general increase in the local activity of PPARγ in adipocytes.
Ultimately, this increased PPARγ activity in adipocytes resulted in a
redistribution of lipids from ectopic deposits in liver and muscle to the
subcutaneous adipose depots. As a result, hepatic insulin sensitivity increased,
translating into systemic improvements in insulin sensitivity and preservation of
β cell mass.
This suggests a role for adiponectin as a “starvation signal”
released by the adipocytes, providing a systemic indication that the average
adipocyte size is small and that adipose tissue is in need of accumulating higher
levels of triglyceride. We have previously examined seasonal variations of
adiponectin levels in yellow-bellied marmots and found that adiponectin levels are
highest during the summer and fall months, a time when the marmots massively
increase their fat stores (17). In addition,
Froguel and colleagues recently identified a nucleotide polymorphism in the gene
encoding adiponectin that is associated with severe forms of childhood obesity and,
importantly, increased levels of adiponectin in the plasma of these children (18).
Adiponectin is consistently upregulated in the lean state with further elevation in
anorexic states (19, 20) and correspondingly downregulated in overweight and
obese states (21, 22). This type of regulation is a fundamentally different
from the regulatory mechanism in place for leptin. Leptin levels tend to be directly
proportional to fat mass and do not display the inverse relationship that
adiponectin displays with adipose tissue mass (23). Generally, adiponectin and leptin are regulated in an opposite
fashion under many different physiological states (24). Hence, elevated adiponectin levels go hand in hand with low leptin
levels and may send comparable systemic signals. As an example, we have previously
reported that transgenic overexpression of adiponectin in WT mice (under normal
conditions a reflection of limited systemic energy stores) causes infertility in
females, a phenomenon that can also be triggered with low leptin levels (25).
Much excitement has been created by the original observation that obesity is
associated with increased infiltration of macrophages into the growing fat pads.
Several different models have been proposed to mechanistically explain why
macrophages infiltrate obese fat pads with higher frequency. Monocyte
chemoattractant protein–1 (MCP-1) and its receptor C-C motif chemokine
receptor-2 (CCR2) have recently been implicated in this process (26, 27). MCP-1 is
produced at higher levels in obese fat pads and hence attracts a higher number of
macrophages (28). An alternative model has
recently been proposed by Cinti and colleagues (29). These authors suggest that adipocytes that reach a maximal size
upon lipid loading spontaneously undergo necrosis, which is associated with
increased infiltration of macrophages around the dying adipocyte. Our massively
obese mice do not allow us to differentiate between these 2 models. We report a
reduction in both average adipocyte size and local inflammation. However, our
transgenic line supports strongly the hypothesis that macrophage infiltration is not
a function of absolute adipose tissue mass but rather relates to the
“quality” of the individual fat cell in the adipose pad.
Transgenic overexpression of adiponectin led to a massive expansion of adipose
tissue mass, yet the level of macrophage infiltration was quite minimal, likely due
to the fact that these mice showed hyperplasia but not hypertrophy. We conclude that
macrophage infiltration is clearly not a function of adipose tissue quantity alone
but rather a reflection of the quality of the individual adipocyte.
Adiponectin overexpression also has an impact on lipid levels. This is of interest in
the context of ob/ob mice. In contrast with humans, HDL cholesterol
levels are increased in genetic mouse models of obesity (ob/ob and
db/db) (9, 30, 31)
due to their decreased clearance rates (9,
32). The appearance of large apoE-rich
HDL-1 particles in these animals suggested a normal lipidation process, thus
implying that the decreased clearance can account for the increase in total HDL
levels in ob/ob mice compared with WT mice (31). In the present study, adiponectin-overexpressing
ob/ob mice exhibited significantly lower total plasma
cholesterol levels than the ob/ob controls (data not shown). Gel
filtration analysis of lipoprotein profiles show markedly decreased HDL-1 and HDL
peaks. More importantly, the lipoprotein profiles of adiponectin-overexpressing
ob/ob mice closely resemble the profiles of WT mice, suggesting
that adiponectin normalizes HDL concentration and HDL particle size in ob/ob
mice. The adiponectin-related effects on HDL levels are consistent with a
general improvement seen for the lipid profiles in the context of rodent obesity.
This is not a peculiarity of adiponectin overexpression in the ob/ob
background, since we found that adiponectin overexpression also further
reduces HDL-1 and HDL peaks in WT mice (our unpublished observations). This finding
constitutes a novel observation that is consistent with the increased activity of
LPL in adipose tissue of adiponectin-overexpressing mice. This is likely to be
responsible for increased triglyceride clearance from circulation after an oral
lipid challenge. Correspondingly, we demonstrate that triglyceride concentrations
were decreased in the VLDL fractions in the presence of excess adiponectin.
The differences in HDL size and plasma concentrations also suggest a role for
adiponectin in HDL metabolism. Although the detailed molecular mechanisms for the
decrease in HDL cholesterol of adiponectin-overexpressing mice are not known, it is
likely that HDL turnover is accelerated in adiponectin-overexpressing mice. Factors
known to affect HDL turnover are under current investigation. Important differences
in lipoprotein metabolism between humans and mice have to be taken into account
though. Epidemiological data suggest a strong correlation between HDL levels and
adiponectin levels (33, 34). In light of this, the relationship of adiponectin
overexpression to HDL-cholesterol levels and atherosclerosis in mice is paradoxical.
While we see a marked reduction of HDL-cholesterol levels in this model of
adipocyte-derived overexpression of adiponectin, hepatic overexpression of globular
adiponectin reduces atherosclerosis and neointima formation after arterial injury
(35, 36). These apparently contrasting findings may be due to the ability of
adiponectin to facilitate reverse cholesterol transport. Previous studies with mice
overexpressing scavenger receptor class B type 1 (SR-B1) in liver demonstrated
marked increases in reverse cholesterol transport and significantly reduced HDL
cholesterol levels (37) but resulted in
reduction of atherosclerosis (38). Hence,
this leads to a model of adiponectin action that promotes reverse cholesterol
transport triggering beneficial effects on atherogenesis without raising HDL
cholesterol levels. Furthermore, recent clinical studies also supported a strong
correlation of plasma adiponectin levels with plasma LPL activity and an inverse
correlation with hepatic lipase activity independent of insulin resistance or
inflammation (39, 40). Combined, our findings strongly support an integral
role of adiponectin in lipoprotein metabolism beyond its well-known role in insulin
sensitization (6, 41, 42).
To study the metabolic phenotype of the transgenic animals in more detail, we used
calorimetric cages. Metabolic cage studies revealed that transgenic ob/ob
mice were not hyperphagic compared with their ob/ob
controls. In fact they ate much less when adjusted for total body weight.
This is in contrast to what one would expect considering their obese phenotype and
considering the fact that they lack leptin. The massive obesity may be unleashed
because leptin and adiponectin exert antagonistic effects. Lack of one of these
adipokines combined with overexpression of the other leads to the phenotype
described here. We have previously shown that mice lacking functional leptin are
hyperresponsive to an injection of recombinant adiponectin (41). Even though food intake was similar between both
groups, there are clear metabolic differences. Core temperature as well as activity
levels were considerably lower in transgenic ob/ob mice. The
reduced activity levels could be explained in part by the massive obesity.
Consistent with these observations, oxygen consumption was also decreased compared
with controls. RER levels were similar overall. However, at the beginning of the
dark period, RER levels were increased in transgenic mice, which may reflect
increased carbohydrate utilization, which spared triglyceride oxidation and
stimulated the accumulation of adipose tissue. To investigate whether the animals
had problems switching from carbohydrate to fat utilization as a main source of
energy, the animals underwent a longer-term and short-term metabolic challenge by
fasting and by administration of central 2DG, respectively. In general, the
transgenic animals showed an altered response to fasting, switching more rapidly to
FFA-based metabolism. The transgenic mice lost considerably less weight upon food
deprivation, an indication that they had difficulty dipping into their triglyceride
stores during caloric deprivation. This was particularly apparent in female mice,
which developed a more severe form of hypoglycemia than males. Consistent with that,
mRNA levels encoding gluconeogenic enzymes such as PEPCK and G-6-P were reduced in
the females, which displayed a significantly higher degree of adiponectin
overexpression than the males (6).
Nevertheless, the reduced body core temperature and reduced motility enabled both
males and females to sustain glucose levels allowing them to survive the fast,
despite the strong trend toward a metabolically inappropriate preservation of fat
mass during times of starvation.
An additional striking observation was the total lack of diurnal rhythmicity of
several metabolic parameters in the transgenic animals, which was restored to the
level of ob/ob mice during an acute fast. These changes suggest
that adiponectin interacts in an inhibitory fashion with circadian oscillators in
multiple central and peripheral tissues involved in maintaining energy homeostasis
(43).
While factors such as the maintenance of body core temperature, oxygen consumption,
and locomotor activity are centrally regulated and were clearly altered in the
transgenic mice, other aspects of central regulation of glucose homeostasis were
normalized. Recent data has demonstrated the powerful effects of central
hypothalamic regulation on hepatic glucose homeostasis (44–46). In the transgenic mice, these central regulatory mechanisms were
restored to the level of WT controls. Central infusion of minute amounts of 2DG
offered a powerful challenge, effectively mimicking acute peripheral hypoglycemia.
When performed in WT animals, this triggered release of glucose from the liver, a
process which was effectively restored in the transgenic animals, while
ob/ob animals failed to respond peripherally to this central
starvation signal.
In summary, we have described a model of chronic overexpression of adiponectin that
leads to a massive increase in subcutaneous fat mass and protection against
diet-induced insulin resistance. We believe that this mouse model is an excellent
preclinical model to study the effects of adipose tissue expansion in the
subcutaneous region in patients as well. There is the well-appreciated fact that not
all obese patients are insulin resistant. Even more dramatically, not all morbidly
obese patients display insulin resistance, and an elevation of adiponectin levels is
frequently associated with improved metabolic profiles (47). Hepatic steatosis is often associated with systemic
insulin resistance (5). The mechanism of
action of antidiabetic compounds such as PPARγ agonists heavily relies
on the ability of these ligands to reduce hepatic lipid content associated with a
concomitant increase in subcutaneous fat mass. In the context of PPARγ
agonists, this effect critically depends on their ability to induce adiponectin
(48, 49). Independently, Cooper and colleagues have demonstrated the potent
antisteatotic effects of adiponectin in the liver (50). Furthermore, our analysis here demonstrates the closely linked gene
expression pattern in white adipocytes from adiponectin-overexpressing adipocytes
with the transcriptional hallmarks seen for PPARγ agonist treatment in
the same cells. This parallel between adiponectin overexpression and
PPARγ agonist action warrants further study. There is a striking overlap
between the 2 conditions. PPARγ activity is increased by adiponectin,
and adiponectin increases PPARγ activity. This demonstrates for what we
believe is the first time a remarkable feed-forward loop between adiponectin and
PPARγ, which appears to be functional only when one or the other is
constitutively stimulated (transgenic adiponectin overexpression or pharmacological
PPARγ activation). Under more physiological conditions (e.g., intact
ob/ob mice), this loop appears to be interrupted by unknown
mechanisms.
All of these observations strongly suggest that adiponectin is a central player
antagonizing the metabolic axis of evil involving obesity, hepatic lipid deposition,
and local inflammation, leading ultimately to systemic insulin resistance.
Therefore, the inability to sustain elevated adiponectin levels during times of
excess caloric intake leads to reduced lipid deposition in the subcutaneous region,
causing ectopic fat accumulation in liver and associated insulin resistance. Type 2
diabetes could therefore be viewed as a failure to appropriately expand fat mass in
the context of a positive energy balance (51).
Methods
Animals. All animal experimental protocols were approved by the Institute for Animal
Studies of the Albert Einstein College of Medicine. Adiponectin transgenic
ob/ob mice were generated by mating heterozygous
leptin-deficient (ob/+) mice with adiponectin transgenic mice
(6). Mice were housed in groups of
2–5 in filter-top cages. The colony was maintained in a
pathogen-free Assessment and Accreditation of Laboratory Animal
Care–accredited facility at the Albert Einstein College of Medicine
under controlled environment settings (22–25°C,
40%–50% humidity). Mice were maintained on 12-hour light and dark
cycles with ad libitum access to water and standard chow diet (5058; LabDiet) or
high-fat diet (D12492; Research Diets Inc.) as indicated. All experiments
presented were littermate controlled and were performed on a mixed C57BL/6 and
FVB background. Many experiments were repeated on a purer C57BL/6 background
(backcross 6 and higher) with identical results. Results reported were generally
seen in male and female mice unless specifically indicated.
MRI and 3D reconstruction. Frozen hearts with attached pericardial fat pads were transferred after thawing
to a 16.6-mm diameter tube with agarose to prevent dehydration of the tissue.
This tube was placed in a custom-built 38-mm inner diameter radio frequency (RF)
coil (RF Sensors LLC Inc.). MRI images were acquired in 3 planes (transversal,
coronal, and sagittal) with spin echo sequence at 11°C in a GE Omega
9.4T vertical bore nuclear magnetic resonance (NMR) system (Fremont Inc.). Echo
and repetition time values were 18 ms and 300 ms, respectively. After
acquisition, images were exported and transformed to jpg format images in a
custom-designed software that runs in the MATLAB (MathWorks Inc.). The images
then were loaded into Amira (Mercury Computer Systems Inc.) sequentially as a
single entity keeping the proper order, slice separation, field of view, and
slice thickness. After this, the region of interest was selected and defined
using label field function in Amira in the 3 planes. Finally, labeling of heart
and pericardial fat tissues was performed, leading to the their 3D
reconstruction.
Assay protocols. Serum values for glucose were measured by FastBlue B glucose assay
(Sigma-Aldrich) and adiponectin with a mouse adiponectin RIA kit (Linco;
Millipore). Insulin was measured with a mouse insulin RIA kit (Linco;
Millipore). OGTTs were performed in animals without access to food for 2 hours
prior to administration of 2.5 g/kg body weight glucose load by oral gavage and
during the course of the study. Fasting glucose, insulin, triglycerides, and FFA
levels were measured at 3 hours after mice were denied access to food. For
fasting studies, blood was collected every 4 hours during 36 hours and used for
glucose and FFA (NEFA C; Wako) measurements. For triglyceride clearance, mice
were fasted for 3 hours and then weighed at 10 am and given 15 μl of
olive oil/g body weight by gastric gavage. Approximately 20 μl of
blood was collected at 0, 2, 4, 6, and 8 hours and assayed for triglyceride
(Infinity Triglyceride Kit; Thermo Scientific). Mice were denied access to food
during the course of the study.
PPARγ agonist gavage and tissue collection. The PPARγ agonist
2-(2-(4-phenoxy-2-propylphenoxy)ethyl)indole-5-acetic acid (COOH) was a kind
gift from Merck (52). The COOH and
vehicle were gavaged daily at 12 noon for 10 days at 10 mg/kg body weight. Mice
were subjected to tail bleeding 4 hours after the last gavage, and 30
μl serum was collected. Mice were then sacrificed within 6 hours
after the last gavage, and adipose tissues were collected.
Immunoblot analysis. Protein extraction and Western blot from fat tissues were performed as previously
described (6). For adipose tissues,
materials were first put into TNET buffer (150 mM NaCl, 5 mM EDTA, 50 mM
Tris-HCl, pH 7.5) without Triton X-100 and homogenized. After low-speed
centrifugation (2,600 g at 4°C), the fat cake was
removed from the top of the tube, and Triton X-100 was added to a final
concentration of 1%. After incubating at 4°C for 30 minutes, the
extract was cleared at 20,000 g for 15 minutes at
4°C and mixed with 2× Laemmli sample buffer. Protein
samples were loaded on 10% Bis-Tris NuPAGE gels (1.5 mm; Invitrogen) for
analysis with indicated antibodies. We analyzed 30 μg of protein
extract for adiponectin or guanosine diphosphate (GDP) dissociation inhibitor
(GDI). The antibody against GDI was kindly provided by Perry Bickel (Washington
University, St. Louis, Missouri, USA). Each band was detected and quantitated by
the Odyssey Infrared Imaging System (LI-COR Biosciences).
Immunohistochemistry for F4/80 marker. Freshly isolated tissues were fixed with phosphate-buffered formalin overnight,
then paraffin wax embedded and subsequently deparaffinized. Sections of 5
μm were incubated overnight with a monoclonal anti-F4/80 antibody.
After washing in PBS, slides were incubated with biotinylated goat anti-rat or
anti-rat IgG at 5 μg/ml (Vector Laboratories) for 1 hour at room
temperature. Slides were developed using a peroxidase detection kit (Vector
Laboratories) and counterstained with hematoxylin (Sigma-Aldrich).
Immunofluorescence staining for insulin and glucagon. Pancreas tissue was fixed in Bouin fixative (saturated picric acid: formaldehyde:
glacial acetic acid at a ratio of 15:5:1) for 5 hours. Paraffin sections (5
μm) were incubated with control donkey IgG (1:500; Jackson
ImmunoResearch Laboratories Inc.) for 1 hour to block nonspecific binding.
Sections were then incubated with guinea pig anti-mouse insulin antibody (1:500;
a kind gift from Regina Kuliawat, Albert Einstein College of Medicine, New York,
New York, USA) and rabbit anti-human glucagon antibody (1:500; Invitrogen)
overnight at 4°C. After washing with PBS 3 times, sections were
incubated with FITC-conjugated donkey anti-guinea pig antibody and Texas
red–conjugated donkey anti-rabbit antibody (1:250; Jackson
ImmunoResearch Laboratories Inc.) for 1 hour at room temperature. Sections were
analyzed with an Olympus IX81 microscope.
Treatment of mice with monoclonal antibodies. Mice were treated for 1 week with a mixture of monoclonal antibodies. Antibodies
were previously described (53). We
injected 50 μg of a 1:1 mixture of the 2 monoclonal antibodies (or
an equivalent amount of nonimmune mouse antibodies) i.p. on days 1, 4, and 7 of
the experiment.
In vivo insulin signaling. Mice were food deprived for 6 hours and subjected to an i.p. injection of human
recombinant insulin at 1 mU/g body weight. Mice were then sacrificed at various
times; livers were isolated and snap frozen. Subsequently, liver tissues were
lysed in radioimmunoprecipitation assay (RIPA) buffer (54), and immunoprecipitations were performed with
anti-insulin receptor antibodies (Insulin Rβ, sc-711; Santa Cruz
Biotechnology Inc.) and analyzed by Western blot analysis, decorated with
anti-phosphotyrosine clone 4G10 (Millipore). Alternatively, extracts were
directly analyzed by Western blots using phospho-AKT (9271; Cell Signaling
Technology Inc.), phospho-GSK3β (9336; Cell Signaling Technology
Inc.), Akt-1 (c-20; Santa Cruz Biotechnology Inc.), and GSK3β
(sc-7291; Santa Cruz Biotechnology Inc.). Results were analyzed by the Odyssey
Infrared Imaging System (LI-COR Biosciences).
Assessment of macrophage prevalence in adipose tissue stromal vascular
fractions. Adipose tissue from transgenic and ob/ob mice was subjected to
collagenase digestion (1 mg collagenase/g adipose tissue) in Krebs-Ringer
bicarbonate buffer (KRB) containing 4% fatty-acid–poor BSA and 1
μM adenosine at 37°C for 1 hour. Cell digestion was
strained using a 200-μm mesh filter, and the resulting free
adipocytes and stromal vascular cells (SVCs) were subjected to brief
centrifugation at 500 g for 1 minute. The infranatant
containing the SVCs was removed and centrifuged for 5 minutes at 500
g. The SVC pellet was washed 2 times in KRB, then incubated
in erythrocyte lysis buffer, pH 7.3, for 10 minutes at room temperature.
Remaining SVCs were washed 2 times in ice-cold FACS buffer (PBS containing 5 mM
EDTA and 0.2% fatty-acid–poor BSA). Cells were counted using a
hemocytometer, and aliquots of 106 cells were prepared for analysis.
Cells were incubated for 30 minutes in 1 ml FACS buffer containing FcBlock (20
μg/ml; BD), then with FITC-conjugated anti-F4/80 IgG (5
μg/ml) for 1 hour at 4°C. F4/80 positive cells were
detected using FACScan (BD), and analysis was performed using CellQuest software
(BD).
Analysis of adiponectin complex distribution. The complex distribution of adiponectin was determined by separating 15
μl of mouse serum over a Superdex 200 10/300 GL column (GE
Healthcare) using a BioLogic Workstation fast-performance liquid chromatography
(FPLC) system (Bio-Rad). The column was equilibrated in column buffer (25 mM
HEPES, pH 8.0, 150 mM NaCl, 1 mM CaCl2), and 0.22 ml fractions were
collected. Samples (40 μl) were collected over the entire elution of
adiponectin and incubated with 10 μl of 5× Laemmli
sample buffer followed by boiling for 5 minutes. Samples were loaded on a
Criterion precast 26-well gel (Bio-Rad) and subjected to immunoblotting using
1:500 polyclonal anti-adiponectin antibody followed by incubation with IRDye
800–coupled goat anti-rabbit secondary antibody (Rockland
Immunochemicals). The fluorescence signal obtained at 30 kDa was quantitated by
the Odyssey Infrared Imaging System (LI-COR Biosciences).
RNA isolation and analysis. RNA was isolated from frozen fat tissue by using QIAGEN RNeasy tissue kit
following the manufacturer’s protocol. cDNA was synthesized from
isolated RNA using SuperScript II and oligo dT (Invitrogen). Quantitative PCR
was performed with the LightCycler-fast start master SYBER green (Roche
Diagnostics) with the following primer sets: GAPDH (forward:
5′-AACTTTGGCATTGTGGAAGG-3′, reverse:
5′-ACACATTGGGGGTAGGAACA-3′); F4/80 (forward:
5′-CTTTGGCTATGGGCTTCCAGTC-3′, reverse:
5′-GCAAGGAGGACAGAGTTTATCGTG-3′); VCAM (forward:
5′-ATTTTCTGGGGCAGGAAGTT-3′, reverse:
5′-ACGTCAGAACAACCGAATCC-3′); vWF (forward:
5′-TGCTTCTTACGCCCATCTCT-3′, reverse:
5′-CAGCTGCCTTCCAGAAAAAC-3′); PEPCK (2 primer sets were
used interchangeably) (forward:
5′-AGCCTCGACAGCCTGCCCCAGG-3′, reverse:
5′-CCAGTTGTTGACCAAAGGCTTTT-3′); (forward:
5′-CGATGACATCGCCTGGATGA-3′, reverse
5′-TCTTGCCCTTGTGTTCTGCA-3′); G-6-P (forward:
5′-GAAGGCCAAGAGATGGTGTGA-3′, reverse:
5′-TGCAGCTCTTGCGGTACATG-3′); aP2 (forward:
5′-GACGACAGGAAGGTGAAGAG-3′, reverse:
5′-ACATTCCACCACCAGCTTGT-3′); DGAT-1 (forward:
5′-GGCCTGCCCCATGCGTGATTAT-3′, reverse:
(5′-CCCCACTGACCTTCTTCCCTGTAGA-3′); PPARγ2
(forward: 5′-ACTGCCTATGAGCACTTCAC-3′, reverse
5′-CAATCGGATGGTTCTTCGGA-3′); TNF-α (forward:
5′-GAGAAAGTCAACCTCCTCTCTG-3′, reverse:
5′-GAAGACTCCTCCCAGGTATATG-3′). Each PCR reaction was
normalized to β-actin (forward:
5′-TACCACAGGCATTGTGATGG-3′, reverse:
5′-TTTGATGTCACGCACGATTT-3′).
IL-6 measurements. The serum IL-6 levels were determined by a mouse IL-6 immunoassay (Quantikine;
R&D systems). The assay was performed according to the
manufacturer’s protocol.
Body composition analysis. Body composition was measured by MRI using an EchoMRI (Echo Medical Systems).
Oil red O staining. Frozen liver tissue sections were rinsed in water and placed in absolute
propylene glycol for 2 minutes, then in oil red O solution. After 2 days, slides
were transferred to an 85% propylene glycol solution for 1 minute for
differentiation and counterstained with hematoxylin.
Liver triglyceride and DAG measurements. Frozen liver tissues (200 mg) were pulverized and transferred into 30 ml of
chloroform/methanol solution (2:1). Samples were set at room temperature for 20
minutes and 6 ml of 0.05% H2SO4 was added, followed by
centrifugation at 2,000 g for 10 minutes at 4κC.
Meanwhile, standards were prepared by serial dilution from 200 μg
Wesson oil (ConAgra Foods)/ml chloroform. For each standard and sample, 2 ml was
transferred into glass tubes and mixed with 2 ml of 1% Triton X-100/chloroform.
Samples were dried under nitrogen gas and reconstituted with water.
Concentration of triglycerides of final samples were determined by Trig/GB
(Roche Diagnostics) (55).
DAGs and ceramides were extracted from frozen tissue (~100 mg) with
chloroform/methanol (2:1, v/v) containing 0.01% butylated hydroxytoluene. Prior
to the extraction, known amounts of 1,3-dipentadecanoin, triheptadecanoin, and
hexanoylsphingosine were added as internal standards. Extracted samples were
evaporated to dryness and redissolved in 1 ml of hexane–methylene
chloride–ethyl ether (95:5:0.5, v/v/v). DAGs were isolated from
triglycerides by use of a diol-bonded phase SPE column (Waters) under vacuum, as
described previously (56). In brief, the
SPE column was preconditioned with 4 ml of hexane. Lipid extract was then placed
on the column, and triglycerides were eluted with 8 ml of
hexane–methylene chloride–ethyl ether (89:10:1, v/v/v).
DAGs were eluted with 8 ml of hexane–ethyl acetate (85:15, v/v) into
a second set of collection tubes. Solvent was evaporated to dryness under vacuum
and redissolved in 0.5 ml of hexane–ethyl acetate (85:15, v/v) for
liquid chromatography/tandem mass spectrometry (LC/MS/MS) analysis. Monitoring
for the presence of triheptadecanoin in the DAG fraction assessed the separation
of triglycerides from DAGs.
Lipoprotein analysis. For lipoprotein separation, samples were pooled (0.2 ml) from 5 mice per group.
The pooled plasma from each group was subjected to FPLC gel filtration on 2
Superose 6 columns (GE Healthcare) in series. The eluate was collected in 0.5 ml
fractions at a flow rate of 0.5 ml/minute. Forty-seven fractions were collected,
and total triglycerides and cholesterol levels of each fraction were determined
using the Infinity Triglyceride and Cholesterol Kit (Thermo Electron Corp). For
apo determination, same volumes of fractions 19 to 36 were used to perform
immunoblot analysis with anti-apoE, -apoA1, and -apoA2 antibodies (Santa Cruz
Biotechnology Inc.) using the Odyssey Infrared Imaging System (LI-COR
Biosciences).
Measurement of tissue LPL activity. LPL enzyme activity assays in adipose tissue were performed as previously
described (57). In brief, tissue
homogenates were incubated with a substrate mixture containing
[carboxyl-14C] triolein, and NEFAs released by LPL were separated
and counted. LPL activity was expressed as microunits (1 μU = 1
μmol NEFA released per hour of incubation at 28°C). To
account for genotype-related differences in tissue triglyceride content, data
are expressed as LPL activity per gram of total tissue protein. Postheparin LPL
activity was measured in plasma obtained 10 minutes after heparin injection (60
IU/kg) under conditions that inhibit hepatic lipase activity (58).
Indirect calorimetry. Prior to data collection, animals were implanted with E-mitters (Mini Mitter)
under ketamine/xylazine anesthesia for temperature measurements and allowed 4
days for recovery. Animals were individually housed in metabolic chambers
maintained at 20–22°C on a 12-hour light/12 dark cycle
with lights on at 7 am. Metabolic measurements (oxygen consumption, food intake,
locomotor activity, and core temperature) were obtained continuously using a
CLAMS (Columbus Instruments) open-circuit indirect calorimetry system. Mice were
provided with 35% fat nutritionally complete powdered diet (Research Diets Inc.)
and tap water ad libitum, unless mentioned otherwise. Presented results contain
data collected over at least 7 days following at least 2–4 days of
adaptation to the metabolic cages.
2DG infusions. Response to brain injections of the acute metabolic stressor 2DG was studied in
order to investigate how mice respond to an acute interruption of central
glucose availability. To this end, all animals were implanted with a 23-gauge
stainless steel cannula aimed at the third cerebral ventricle (i.c.v.; 0.3 mm
posterior to bregma, 3 mm ventral to skull surface) under ketamine/xylazine
anesthesia. After 4 days recovery, animals were injected with 0.1 mg in 1
μl 2DG (Sigma-Aldrich) dissolved in artificial cerebrospinal fluid
(Harvard Apparatus). Tail blood samples were taken at 0, 15, 30, 60, 90, and 120
minutes for the measurement of glucose levels.
NimbleGen expression arrays: RNA purification and cRNA probe
labeling. Gonadal fat samples were frozen immediately in liquid nitrogen and transferred to
a –80κC freezer until further processing. Total RNA was
isolated using TRIzol reagent (Invitrogen). Additional purification of
total RNA was achieved with an RNeasy Mini kit (QIAGEN). Total RNA samples had
an absorbance ratio (A260/280) of 1.97–2.00. The integrity of
extracted RNAs was checked on denaturing agarose gels. From each sample, 10
μg of total RNA was utilized to synthesize double-stranded cDNA
using a SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen) and an oligo
dT primer containing a T7 RNA polymerase promoter sequence
(5′-GGCCAGTGAATTGTAATACGACTCACTATAGGGAGGGAGGCGGTTTTTTTTTTTTTTTTTTTTTTTT-3′;
Invitrogen). The double-stranded cDNA samples were sent to NimbleGen Systems
Inc. for cRNA synthesis, probe labeling, and microarray hybridization, as
previously described (59).
NimbleGen expression arrays: microarray hybridization and data
collection. We used a mouse gene expression array manufactured by NimbleGen Systems Inc. A
dual-color hybridization strategy was used in this study, i.e., cRNA probes from
both control and transgene samples were labeled with either fluorescent cyanine
3 (Cy3) or cyanine 5 (Cy5), then both the Cy3- and Cy5-labeled probes were mixed
and applied to 1 array slide. The hybridizations were performed on 3 independent
microarrays. Microarray slides were scanned, and raw data and normalized gene
cells were analyzed by NimbleGen NimbleGen Systems Inc. The ratio of Cy3 to Cy5
for each feature was calculated from all normalized data. Final values were
taken from the average of 3 slides and were log transformed for statistical
analysis.
Statistics. Results are shown as mean ± SEM. For studies shown in Figure 3, comparisons between genotypes for body
weight and body weight gain were performed by 2-way (body weight) or 3-way (body
weight gain) repeated measures ANOVA, with genotype, time, and (for body weight
gain) diet as factors. For studies shown in Figures 6 and 7,
including core temperature, indirect calorimetry, food intake, FFA, and glucose,
comparisons between groups were performed by 2-way repeated measures ANOVA, with
genotype and time as factors. For each dependent measure from the metabolic cage
(RER, VO2, temperature, and food intake), primary data were
considered as the average for each animal for each time point over 3 consecutive
days, beginning after a 2- to 3-day adaptation period to the metabolic chambers.
Post hoc comparisons were made using Neuman-Keuls tests. For all 24-hour time
point comparisons in Figures 6 and 7, unpaired Student’s
t tests were performed. Differences were deemed significant
at P ≤ 0.05.
Statistical analysis was performed by Student’s t
test with SigmaPlot 9.0 and ANOVA analysis with SigmaStat 2.0 (Systat).
Significance was accepted at P < 0.05.
Acknowledgments
We thank members of the Scherer laboratory for helpful comments, in particular Zhao
V. Wang for technical advice for immunofluorescence staining and Nils Hallberg for
help in statistical analysis. Furthermore, we would like to thank our Albert
Einstein College of Medicine (AECOM) Diabetes Research and Training Center (DRTC)
Radioimmunoprecipitation Assay (RIA) Core Facility (Manju Surana) and the AECOM
Cancer Center Hybridoma Facility (Susan Buhl) for their help as well as the AECOM
Institute for Animal Studies under the direction of Larry Herbst and the AECOM
Transgenic Core for their expert assistance. Lipoprotein analysis was performed in
the Cardiovascular Core Laboratory of the Cincinnati Mouse Metabolic Phenotype
Center, supported by NIDDK (DK59630). This work was supported by NIH grants
R01-DK55758, R24-DK071030-01, R01-CA112023, and R21-DK075887 (to P.E. Scherer);
R01-DK066618 (to G.J. Schwartz), the New York Obesity Research Center (NIH
DK026687); and the Skirball Institute for Nutrient Sensing (to G.J. Schwartz and
P.E. Scherer). P.E. Scherer is also a recipient of an Irma T. Hirschl Career
Scientist Award. M.E. Trujillo is supported by a mentor-based postdoctoral
fellowship award from the American Diabetes Association (7-05-MI-09). T. Schraw is
supported by a postdoctoral fellowship from the American Heart Association (Heritage
Foundation; 0625998T). S.M. Hofmann is supported by a Scientist Development Grant
from the American Heart Association (AHA 0635079N).
Footnotes
Nonstandard abbreviations used: aP2, adipocyte/macrophage
fatty-acid–binding protein; CCR2, C-C motif chemokine receptor-2;
DAG, diacylglycerol; 2DG, 2-deoxyglucose; DGAT-1, DAG acyltransferase; FPLC,
fast-performance liquid chromatography; G-6-P, glucose-6-phosphate; GDI, GDP
dissociation inhibitor; GDP, guanosine diphosphate; LPL, lipoprotein lipase;
OGTT, oral glucose tolerance test; PEPCK, phosphoenolpyruvate carboxykinase;
qRT-PCR, quantitative RT-PCR; RER, respiratory exchange ratio; SVC, stromal
vascular cell; VO2, oxygen volume per time; WAT, white adipose
tissue.
Conflict of interest: The authors have declared that no conflict of
interest exists.
Citation for this article:
J. Clin. Invest.
117:2621–2637 (2007). doi:10.1172/JCI31021
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