Group Title: BMC Nephrology
Title: Alterations of renal phenotype and gene expression profiles due to protein overload in NOD-related mouse strains
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Title: Alterations of renal phenotype and gene expression profiles due to protein overload in NOD-related mouse strains
Physical Description: Book
Language: English
Creator: Wilson, Karen
McIndoe, Richard
Eckenrode, Sarah
Morel, Laurence
Agarwal, Anupam
Croker, Byron
She, Jin-Xiong
Publisher: BMC Nephrology
Publication Date: 2005
Abstract: BACKGROUND:Despite multiple causes, Chronic Kidney Disease is commonly associated with proteinuria. A previous study on Non Obese Diabetic mice (NOD), which spontaneously develop type 1 diabetes, described histological and gene expression changes incurred by diabetes in the kidney. Because proteinuria is coincident to diabetes, the effects of proteinuria are difficult to distinguish from those of other factors such as hyperglycemia. Proteinuria can nevertheless be induced in mice by peritoneal injection of Bovine Serum Albumin (BSA). To gain more information on the specific effects of proteinuria, this study addresses renal changes in diabetes resistant NOD-related mouse strains (NON and NOD.B10) that were made to develop proteinuria by BSA overload.METHODS:Proteinuria was induced by protein overload on NON and NOD.B10 mouse strains and histology and microarray technology were used to follow the kidney response. The effects of proteinuria were assessed and subsequently compared to changes that were observed in a prior study on NOD diabetic nephropathy.RESULTS:Overload treatment significantly modified the renal phenotype and out of 5760 clones screened, 21 and 7 kidney transcripts were respectively altered in the NON and NOD.B10. Upregulated transcripts encoded signal transduction genes, as well as markers for inflammation (Calmodulin kinase beta). Down-regulated transcripts included FKBP52 which was also down-regulated in diabetic NOD kidney. Comparison of transcripts altered by proteinuria to those altered by diabetes identified mannosidase 2 alpha 1 as being more specifically induced by proteinuria.CONCLUSION:By simulating a component of diabetes, and looking at the global response on mice resistant to the disease, by virtue of a small genetic difference, we were able to identify key factors in disease progression. This suggests the power of this approach in unraveling multifactorial disease processes.
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BMC Nephrology Central

Research article

Alterations of renal phenotype and gene expression profiles due to
protein overload in NOD-related mouse strains
Karen HS Wilson1,5, Richard A Mclndoe1, Sarah Eckenrode1,
Laurence Morel2, Anupam Agarwal4, Byron P Croker*2,3 and Jin-Xiong She* I

Address: 'Center for Biotechnology and Genomic Medicine, Medical College of Georgia, 1120 15th Street, PV6B108, Augusta, GA 30912-2400,
USA, 2Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, USA, 3North Florida/South
Georgia Veterans Health System, Gainesville, FL 32608, USA, 4MD Division of Nephrology, ZRB 614, University of Alabama at Birmingham, 1530
3rd Avenue South Birmingham, AL 35294, USA and 5The Royal Swedish Academy of Sciences, Kristinebergs Marina Forksningsstation,
Fiskebackskil, SE-45034, Sweden
Email: Karen HS Wilson; Richard A McIndoe;
Sarah Eckenrode; Laurence Morel; Anupam Agarwal;
Byron P Croker*; Jin-Xiong She*
* Corresponding authors

Published: 21 December 2005 Received: 04 July 2005
BMC Nephrology 2005, 6:17 doi: 10.1 186/1471-2369-6-17 Accepted: 21 December 2005
This article is available from:
2005 Wilson et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: Despite multiple causes, Chronic Kidney Disease is commonly associated with proteinuria.
A previous study on Non Obese Diabetic mice (NOD), which spontaneously develop type I diabetes,
described histological and gene expression changes incurred by diabetes in the kidney. Because proteinuria
is coincident to diabetes, the effects of proteinuria are difficult to distinguish from those of other factors
such as hyperglycemia. Proteinuria can nevertheless be induced in mice by peritoneal injection of Bovine
Serum Albumin (BSA). To gain more information on the specific effects of proteinuria, this study addresses
renal changes in diabetes resistant NOD-related mouse strains (NON and NOD.B 10) that were made to
develop proteinuria by BSA overload.
Methods: Proteinuria was induced by protein overload on NON and NOD.BI0 mouse strains and
histology and microarray technology were used to follow the kidney response. The effects of proteinuria
were assessed and subsequently compared to changes that were observed in a prior study on NOD
diabetic nephropathy.
Results: Overload treatment significantly modified the renal phenotype and out of 5760 clones screened,
21 and 7 kidney transcripts were respectively altered in the NON and NOD.B 10. Upregulated transcripts
encoded signal transduction genes, as well as markers for inflammation (Calmodulin kinase beta). Down-
regulated transcripts included FKBP52 which was also down-regulated in diabetic NOD kidney.
Comparison of transcripts altered by proteinuria to those altered by diabetes identified mannosidase 2
alpha I as being more specifically induced by proteinuria.
Conclusion: By simulating a component of diabetes, and looking at the global response on mice resistant
to the disease, by virtue of a small genetic difference, we were able to identify key factors in disease
progression. This suggests the power of this approach in unraveling multifactorial disease processes.

Page 1 of 9
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The cause of the relentless progression of chronic kidney
disease (CKD) to chronic renal failure is likely to be mul-
tifactorial. CKD itself has a variety of inciting etiologies
[1]. Accumulating clinical evidence indicates that pro-
teinuria is associated with CKD [2] and predictive of pro-
gression in CKD regardless of diverse etiologies [3].
Subsequent animal studies and in vitro experiments pro-
vided additional evidence for proteinuria in progressive
CKD. Because kidney complications occur frequently in
diabetic patients, we recently conducted a microarray
study on gene transcripts altered by diabetes in non-obese
diabetic (NOD) mice kidneys [4]. As NOD spontaneously
develops both diabetes and proteinuria, our previous
studies could not distinguish gene expression changes due
to diabetes versus proteinuria. To identify gene expression
changes due to proteinuria alone, we investigate gene
expression changes in two NOD-related mouse strains
(NON and NOD.B10) that are diabetes resistant but can
nevertheless develop proteinuria if subjected to protein
overload by peritoneal injection of Bovine Serum Albu-
min (BSA). The protein overload model is a conceptually
simple, clear and direct model [5,6] to demonstrate the
pathogenicity of proteinuria. The use of NON and
NOD.B10 serves as a control for the differences due to
genetic background, as NOD.B10 differs from NOD by
the MHC genes and NON differs from NOD for approxi-
mately 30-40% of the polymorphic markers. Our studies
demonstrate a number of gene expression changes
induced by protein overload. Some of them appear to be
related to the signaling pathways in proteinuria. These
studies confirm suspected therapeutic targets for preven-
tion of CKD.

NON and NOD.B10 mice were obtained from Jackson
Laboratories, Bar Harbor, ME. All animal studies were
approved by the University of Florida's IUCAC prior to the
start of these experiments. Two mouse strains were
assayed for gene expression profile changes due to protein
overload. Data was collected from 5 7 animals per
strain. Male 8 10 weeks old NOD.B10 and NON mice
were given intraperitoneal (IP) injections of bovine serum
albumin (BSA, 1 g/100 g body weight) (CAT# A-7906;
Sigma Chemical Company, St. Louis, MO, USA) in saline
(25% solution weight/volume) or normal saline 5 days a
week, for 10 weeks and sacrificed 10 weeks post treat-
ment. We extended the injection protocol by four weeks
compared to previous studies [6,7]. The reference RNA for
micorarray hybridization was made from a pool of total
RNA obtained from eight 10 week non-diabetic female
NOD kidneys and described previously [4].

Tissue preservation and histology
Immediately after sacrificing mice, the kidneys were col-
lected, flash frozen in liquid nitrogen and stored at -80 C
until RNA extraction. At terminal surgery for sacrifice, the
two poles of the right kidney were removed, snap frozen,
and held at -800 C for RNA extraction. Kidney sections
were stained using periodic acid Schiff (PAS). Histologic
features of mesangial expansion or Intercapillary glomer-
ulosclerosis as defined by Kimmelstiel and Wilson (1936)
[8] were graded for comparison using the following
glomerulosclerosis score (GS): none = 0, stalk glomeru-
lopathy = 1 [9], segmental intercapillary = 2, diffuse inter-
capillary = 3, and nodular intercapillary = 4. Histologic
sections were blind ranked and analyzed by the Wilcoxon
rank test for statistical significance.

Microarray fabrication and hybridization
Total RNA was extracted from kidneys using a midi-kit
from Qiagen Co. (Hilden, Germany). The procedure for
printing the microarrays, hybridization to the microarrays
and analysis was previously described [4]. Briefly, a 5760
clone subtractive cDNA library was prepared and printed
on glass slides using the BioRobotics MicroGrid TAS II.
The RNA material used to interrogate the microarrays was
prepared separately. Total RNA were individually
extracted from whole kidneys of mice belonging to each
study group and the reference group (described in the pre-
vious section). The reference RNA pool was made by com-
bining equal quantities of total RNA from the kidneys of
the reference group of mice. Each of the study and refer-
ence RNAs were subsequently converted to cDNA and
respectively labeled with Cy-3 and Cy-5 fluorophores. Cy-
3 labeled probes from each study mouse were then com-
bined to an equal quantity of the universal Cy-5 labeled
reference and hybridized to the slides. After scanning the
slides at two wavelengths, corresponding to the Cy-3 and
Cy-5 dye fluorescence, two images were computer gener-
ated and artificially superimposed. Numerical values
(expression levels) for each DNA spot on the array were
extracted from the images using AnalyzerDG (Molecular-
Ware Cambridge, MA). Each hybridization reaction was
repeated twice to ensure reproducibility and confidence in
the measurement and the mean values of hybridization
signals were used. The data (along with background and
error measurements) were stored into a file in the form of
expression ratios of the study-sample/reference intensi-
ties. Statistical analyses were performed on the expression
data in order to find differentially expressed genes that
could distinguish treated from untreated animals. Genes
showing significantly different expression differences
between the compared groups were clustered with Cluster
and their expression pattern graphically illustrated using
TreeView (as described in [4]).

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BMC Nephrology 2005, 6:17

Figure I
Histopathology of protein overload kidney from con-
trol and experimental animals. Parts A, C, E, G are all
the same magnification (scale bar 0.1 mm) for comparison of
relative sizes among groups. Similarly, parts B, D, F, H are all
the same magnification (scale bar 0.1 mm) and each figure has
the justiglomerular apparatus (JGA) denoted by an arrow
head to show the vascular pole. A) Survey view showing
normal cortex (200x) for NOD.B 10 treated with saline (PAS
stain). B) Higher magnification of saline-treated NOD.B10
showing normal glomerular structure (400x). JGA is shown
(arrow) and tubular pole is opposite. C) BAS-treated
NOD.B 10 (PAS stain). Survey view showing increased stain-
ing in all 4 glomeruli accentuating Glomerular lobules (200x).
D). Higher magnification of a BSA-treated NOD.B 10 glomer-
ulus showing expansion extending from the JGA region
(arrows) to the peripheral mesangium accentuating the
glomerular lobularity (400x). E) Saline treated NON (PAS
stain) survey view of 5 glomeruli with preserved parenchyma
(200x). Glomerular hyaline is just visible. F). Higher magnifi-
cation of saline-treated NON shows intracapillary hyaline
thrombi (arrows, 400x). G) BAS-treated NON (PAS stain)
survey view (200x) of cortex with 4 glomeruli showing
changes similar to those seen in BSA-treated NOD.B 10 mice.
No residual intracapillary thrombi are present. H) Higher
power view of two BSA-treated NON glomeruli with varying
degrees of mesangial expansion. JGA is indicated by arrow

Histology features were assessed in control and BSA
groups of each strain and summarized by the mean Inter-
capillary glomerulosclerosis score (GS score). NOD.B10
mice treated with saline have normal histology (GS = 0),
while BSA treated mice average GS scores of 3.0 (p <
0.005). Glomeruli from BSA treated mice also show dis-
tinct hypertrophy in comparison to controls. This is best
appreciated at low magnification (Figure la vs. Ic) when
a representative population of each sample can be
observed. The NON strain presents more complex features
(Figure le and If). The control animals have early features
of lipoprotein glomerulopathy as reported previously
[10]. The intracapillary hyaline thrombi are visible in
most glomeruli (Figure If, arrows). Mild mesangeal
expansion (GS = 0.6) is also present. Treated NON mice
show glomerular hypertrophy (Figure Ig vs. Figure le)
and increased mesangeal expansion (GS = 3.3, p < 0.005)
which is similar in the BSA-treated NOD.B10 group.
Coincidentally the intracapillary hyaline deposits are
absent from treated NON mice.

Impact of protein overload on gene expression
NON mice
Among the 5760 clones screened by microarray, 21
unique transcripts differ between the BSA and saline
treated NON mice (Figure 2A and Table 1). Eighteen of
these genes are up-regulated and 3 are down-regulated.
The up-regulated clones represent genes pertinent to kid-
ney function, such as ornithine transcarbamylase, an
enzyme of the urea cycle, and ferritin heavy chain (fth), an
enzyme that stores iron in a soluble non-toxic form. The
transcript for mannosidase 2 alpha 1 (Man2al), an
enzyme involved in extracellular N-glycan branching, is
also up-regulated. The gene for Man2al which maps to
chromosome (Chr.) 17 on a probable QTL for lymphocy-
tosis [11] has previously been associated with diabetes
and autoimmune diseases such as lupus nephritis. In the
BSA treated NON mice, Man2al is up-regulated 1.4 fold,
in a very similar manner to the up-regulation observed in
kidneys of db/db mice with type 2 diabetes and albu-
minuria (1.4-1.7 or 1.8 reported in the literature [ 12,13]).
Some up-regulated transcripts in the BSA treated NON
mice suggest recruitment of immune related pathways
and inflammation. These transcripts include calmodulin
kinase beta (CaMKII), calcineurin B, a regulator of T cell
receptor signalling and platelet endothelial adhesion mol-
ecule 1 (PECAM-1), which is a potential prognostic
marker for leukocyte infiltration [14]. Moreover, in BSA
treated NON mice the folate receptor 1 (Folrl) gene and
the insulin-induced gene 1 (Insig-1) transcripts increase
by 1.8 and 2.1 fold respectively, compared to controls.
This is interesting because in kidney mesangial cell cul-
tures, subjected to inflammatory stimuli, Folrl expression

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BMC Nephrology 2005, 6:17

ferritin heavy chain
ornithine transcarbanwlise
dvnein light intermediate chain 53/55
mannosidase 2 alaha 1
Ihlorhondrtial tlTA-Tlhr gene
Forl I
hnlii addehyde dehvdrouenase
SPPY do'nun-,-ontaining SOCS box protein SSB-4
[1T2BP- I
calcineurin B line I
[lins RClus rutoclhondrion conlete genane
Hhl DAGKthed/l Idi1
Mus numsculus hi othetical protein
HiMs nmisculus iitochondrial aenone
16S rai gene mitochondrial gene for mitochondrial product

B: NOD.B10

Mus musculus hypothetical protein
solute carrier family 25

C: NON + NOD.B10

WawIla.e ? aIu114 1

Exrssion ratio
05 30

Figure 2
Microarray profiles of mouse kidneys treated with
BSA or saline. A) Microarray profiles in kidneys from
NON mice treated with BSA versus saline. Each column in
the picture represents the median value of two array experi-
ments for an individual mouse. Each row represents a differ-
ent gene on the array. The identity of each gene is displayed
on the right hand side of the picture. On each row of the pic-
ture, the red, green or black colors refer to the relative
expression of the studied gene compared to the reference.
Green represents lower expression, red represents higher
expression and black represents equal levels of expression.
The intensity of red and green color is proportional to the
increase or decrease of gene expression relative to the refer-
ence. B) Expression profiles in kidneys from NOD.BIO0 mice
treated with BSA versus saline. C) Combined analysis of
NON and NOD.B 10 treated with BSA versus saline.

has been shown to increase 2.0 fold, 6 hours after stimu-
lation, while Insig-1 expression increases by 1.9 fold
within 2 hours of stimulation [151. The increase in Insig-
1 may additionally point to a role for lipid metabolism
during proteinuria. Some BSA up-regulated genes in the
NON mice map to noteworthy chromosomal locations.
For example, PECAM 1 and the gene for Insulin Growth
Factor 2 Binding Protein 1 (Igf2Bpl, also called CRDBP)

which protects c-Myc mRNA, from degradation [16] map
to mouse Chr. 11. PECAM-1 is located near protein kinase
C alpha, an enzyme implicated in albuminuria during
type 1 diabetic nephropathy [17]. Moreover, several other
genes between PECAM-1 and Igf2Bpl, such as Growth
Hormone, STAT3, and STAT5 [18,19] are involved in dia-
betic nephropathy or diabetes and an identified IDD4
interval spans STAT3 [20]. Down-regulated gene products
in BSA treated NON mice encode primarily mitochondrial
genes, as well as the immunophilin FKBP-52.

NOD. B10 mice
7 transcripts are affected by BSA treatment in NOD.B10
mice (Figure 2B and Table 1). Three are up-regulated, two
of which overlap with the up-regulated transcripts in the
NON mice (CaMKII and a DAGKO homologous clone).
The third up-regulated transcript is for ribosomal protein
S-23 (RpS23), which has also been demonstrated to be
up-regulated in mouse kidney following angiotensin II
administration [211. Four transcripts are down-regulated
(Figure 2B). Two are mitochondrial genes, solutee carrier
family 25 member a3 (Slc25a3) and cytochrome oxidase
subunit 7b (Cox7b)) while the two others (acetyl CoA
transporter and vesicle-associated membrane protein-
associated protein-A (VAPA)), are involved in lipid trans-
port and processing. VAPA, whose gene maps closely on
Chr. 17 (63.3 cM) to Man2al (62.3 cM) (discussed
above), is a syntaxin-like protein implicated in Endoplas-
mic Reticulum/Golgi vesicle transport and phospholipid
regulation in mammalian cells. VAPA was recently found
in a complex with Oxycosterol-binding protein (OSBP), a
protein involved in sterol homeostasis. The VAPA-OSBP
complex intervenes at a stage of protein and lipid export
from the ER [22]. Acetyl CoA transporter transfers ganglio-
sides from the ER to the Golgi apparatus for O-acetylation.

Effect of overload treatment and effect of proteinuria in
diabetic nephropathy
To identify genes commonly affected by protein overload,
NON and NOD.B10 mouse strains were analyzed jointly
(Figure 2C). The effects of proteinuria in diabetic neph-
ropathy are difficult to distinguish from those of other fac-
tors such as hyperglycemia. For this reason, the overload
induced gene expression changes in NON and NOD.B10
were compared to changes induced by type 1 diabetes in
NOD [4]. Several genes seem to be affected by BSA treat-
ment only (Table 1 and Table 2) but noteworthy are the
genes for fth, a regulator of oxidative tolerance in the kid-
ney, and Man2al. For those genes, independent studies
tend to confirm key effects of proteinuria. For example, fth
expression is not significantly altered by diabetes in NOD
mice but it increases by 1.3 fold in NON and NOD.B10
mice treated with BSA. This suggests that fth gene expres-
sion is sensitive to proteinuria, a hypothesis which is rein-
forced by proteomic work on the OVE26 transgenic

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BMC Nephrology 2005, 6:17

Table I: Expression differences between BSA and saline treatment

Gene name/Function

Expression ratios


T2/C2 T3/C3

Kidney function
Ornithine transcarbamylase (OTC)
Folate receptor I (Folrl)
Lipid Metabolism
Insulin induced gene I (Insigl)
VAMP associated protein A (VAPA)
Acetyl-CoA transporter (AcylCoAtrsp)
Calmodulin-dependent protein kinase beta (CaMKII)
Homolog human calcineurin B, type I (Calcineurin BI)
Platelet Endothelial Cell Adhesion Molecule I (PECAMI)
SPRY domain-containing SOCS box 4 (SSB-4)
Signal Transduction
Homolog diacylglycerol kinase, theta (HmlgDAGK6)
Glucocorticoid receptor
Immunophilin FKBP-52 (FKBP52)
Insulin-like Growth factor binding protein I (IGF2bpIl)
Homolog apoptosis-related PNAS2 (Hmlg.apopts)
Histone Acetylase subunit MRG 15-1 (HistAcetyl)
DEAD/H box polypeptide 3 (DEAD3)
Ribosomal protein S23 (rib. prot. S23)
Ribosomal protein L21 (RpL21)
t-complex polypeptide I (tcp- I)
Mannosidase 2, alpha I (Man2al)
Type 6 control region flanking tRNA (mtDNACtrlRNA)
tRNA-Thr gene (tRNA-Thr)
16S ribosomal RNA gene (tl6srRNA)
Mouse mitochondrion, complete genome (Mitochond.)
Solute carrier family 25 member 3 (Slc25a3)
Cytochrome c oxidase subunit Vllb (Cox7b)
Protection against radicals
Ferritin heavy chain I (Fth I)
Organelle transport
Homolog rat dynein LIC-2 53/55 (HmlgratDncli2)
Reduction of aromatic aldehydes
Aldehyde dehydrogenase 3BI (ALDH3BI)
Clone RP23-465D7 on chromosome I I (RP23-465D7)
Hypothetical-Binding-protein-dependent transport (Hp)
Clone ct7-25g 12 (ct7-25g 12)

[Genbank:X07094] I
[Genbank:XM 133582] I

[Genbank:NM 153526] I
[Genbank:BC003866] 0.7
[Genbank:BC005616] 0.7

[Genbank:XM 132366] 1.4
[Genbank:BC027913] I
[Genbank:BC008519] I
[Genbank:NM 145134] I

[Genbank:NM 19901 1] 1.3

[Genbank:XI17069] I

[Genbank:XM 109627] I
[Genbank:AK00891 I] 0.9
[Genbank:AF319620] 0.7
[Genbank:NM 010028] I
[Genbank:AK012574] 1.3
[Genbank:U93863] 0.8
[Genbank:D 10606] I
[Genbank:XM 123163] I

[Genbank:U47435] 0.6
[Genbank:AJ3 3380] 0.6
[Genbank:AY01I 1146] I
[Genbank:J0 1420] I
[Genbank:BC0 18161] 0.7
[Genbank:NM 025379] 0.8

[Genbank:NM 010239] I

[Genbank:NM 031026] I

[Genbank:XM 129078] I

[Genbank:AKO 10392]

1.7 I NS 2.66E-05 NS
1.8 I NS 4.12E-04 NS





1.9 1.6 1.93E-02 4.54E-03




0.8 0.8 NS 6.81E-03 3.27E-03



2.43 E-04


7.71 E-04


1.5 1.3 NS 1.66E-05 4.17E-02

1.4 I NS 9.46E-05 NS

1.7 1.4 NS 4.17E-04 3.71E-02

3.1 IE-02



T I: NOD.B 10 treated with BSA, C I: NOD.B 10 saline controls, T2: NON treated with BSA, C2: NON saline controls, T3: combined analysis of
NOD.B 10 and NON treated with BSA, C3: combined analysis of NOD.B 10 and NON saline control. NS: Non Significant. Genes found to
discriminate between any two of the groups of mice are represented. For each gene, the mean expression value ratio between treated and control
animals are represented. Student test p values obtained for significant comparison are also shown.

mouse, another mouse model for type 1 diabetes [23].
Compared to the diabetic NOD mouse, which displays
characteristics of early human diabetic nephropathy, the
diabetic OVE26 transgenic mouse, displays characteristics
significantly closer to advanced human diabetic nephrop-
athy [24], which include notably a dramatic increase of
urinary albumin excretion. In diabetic OVE26 mice with
proteinuria, the protein level of fth increases by 1.93 fold

compared to control mice [23], suggesting, by compari-
son to NOD and to our present study, that proteinuria is
a key factor. Like fth, Man2al gene expression does not
significantly change in type 1 diabetic NOD mice. How-
ever BSA treated NON and NOD.B10 mice are subject to
a 1.5 fold increase in expression of this gene. Remarkably,
results from a recent genomic profiling study on the
impact of type 1 and 2 diabetes on the kidney [13] show

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p values

BMC Nephrology 2005, 6:17

that Man2al expression does not change significantly in
streptozotocin treated mice, a model for type 1 diabetes,
when animals do not present advanced mesangial matrix
expansion nor albuminuria. In the same study however,
Man2al is up-regulated 1.4 times in hyperglycemic/
hyperalbuminuric mice compared to control mice.
Man2al is also up-regulated 1.8 fold, in mice with
advanced mesangial expansion compared to controls.

The NON mice used in this work, which were more
affected by protein overload, experienced additional BSA
up-regulation of the transcript for the t-complex 1 (tcp-1).
Remarkably Tcp-1 maps to Chr 17 at 11.6 cM in a recently
identified QTL for proteinuria (between D17Mitll113 (6
cM) and D17Mit46 (15 cM)) [25] indicating that this gene
may also be more specifically regulated by proteinuria in
the kidney.

Some genes in our study are affected in the same way by
protein overload and diabetes, suggesting that their
expression is regulated by either mild proteinuria (or pro-
teinuria onset) or alternatively other factors. Such is the
case for the immunophilin FKBP-52 transcript which is
down-regulated 0.8 fold in the kidney of both mouse
strains treated with BSA and diabetic NOD mice.

Proteinuria is a risk factor for progression of diverse causes
of CKD that account for two thirds of patient entries into
end stage renal disease programs in the US [1]. The largest
single cause of progressive CKD is diabetic nephropathy.
An analysis of the protein overload model might help dis-
sect mechanisms of pathogenesis that are common to dia-
betic nephropathy and other etiologies of CKD linked by
proteinuria. Furthermore, the power of the analysis would
be strengthened by comparing changes in transcription
between diabetes and proteinuria without diabetes. The
analysis would be facilitated by using animals with simi-
lar genetic backgrounds. Similarities in genotype would
reduce variances in phenotypic expression which were
incidental to pathogenesis. In a previous study we
reported the changes seen in early diabetic NOD mice
which is a prototypic mouse model of type I diabetes. For
the present study we chose two genetically related strains.
NON is non-obese non-diabetic, related to NOD by com-
mon parentage and shares some of the diabetogenic loci
with NOD but significantly its H-2 locus imparts diabetes
resistance even on the NOD background [26]. While free
of diabetes NON does exhibit lipoprotein glomerulopa-
thy. Extending this principle, the NOD.B 10H-2b congenic
strain differs only at the H-2 locus and is also diabetes free

The histologic responses to protein overload had similar-
ities in both non-diabetic strains examined here which

were more profound than we previously observed for
NOD mice coincident with diabetes [41 or the changes
described in the db/db mouse model of type II diabetes
[28]. Renal hypertrophy of glomeruli and tubules is a
common feature of diabetes [18,29,30] as well as other
conditions, including high protein diet and compensatory
hypertrophy [31]. Similarly glomerulosclerosis with
mesangeal expansion is typical of diabetic nephropathy
but may also be seen in other conditions [8]. Regardless,
the histologic response of NON was more complex with
the unexpected resolution of glomerular capillary lipo-
protein thrombi. The mechanism of lipoprotein deposi-
tion is unclear but the deposits normally increase with age
and are characteristic of the glomeruli [10]. This may be
related to the relatively unique flow characteristics of the
glomerulus. In glomerular hypertrophy flow is increased
[29] and may be accompanied by an increase in the
number of glomerular capillaries and an increase in their
size [32]. Any of these factors may prevent or reverse the
formation of intracapillary thrombi. The more complex
histopathologic response seen in NON is also reflected at
the gene expression level, whereby, in NOD. B 10, only 7
transcripts are altered by overload treatment, as opposed
to 21 transcripts in the NON model. Some of the common
features of BSA treatment in NON and NOD.B10 mice
nevertheless transpire through the transcription profiles,
whereby BSA upregulated genes in NOD.B10 essentially
overlap with those observed in the NON.

Immune related response
CaMKII is up-regulated in both NON and NOD.B10
treated groups. The major causes of nephropathy in CKD
(diabetes and hypertension) have not traditionally been
considered autoimmune or even immune mediated.
However, in several rodent models, there is increasing evi-
dence that adaptive cellular immunity and innate immu-
nity play a pathogenetic role [33], as well as models that
are generally considered idiopathic proteinuria including
protein overload [6]. In this context CaMKII, has been
shown to modulate the activity of NFKB, a central media-
tor of immune, inflammatory and stress responses [34].
NON mice, which are most affected by the overload treat-
ment, display the additional up-regulation of calcineurin
B and PECAM- 1, suggesting a more pronounced leukocyte
infiltration of the kidney as noted above. PECAM-1,
whose gene is also up-regulated in type 1 diabetic neph-
ropathy [35] participates in leukocyte transmigratory
processes and is regulated by modulators of NFKB [36].
Calcineurin B is the regulatory subunit of calcineurin
which plays a pivotal role in antigen stimulated T cell acti-
vation [33]. Our findings extend the rapid response
microarray studies of Nagasawa et. al. [7] to protein over-
load, which also show involvement of an immune related
response, with the up-regulation of osteopontin, a chem-
otactic and adhesion molecule for macrophages which

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BMC Nephrology 2005, 6:17

Table 2: Common genes altered by protein overload and diabetes

Expression ratios

P values

tcp- I [Genbank:D 10606]
FKBP52 [Genbank:X17069]
VAPA [Genbank:BC003866]
Cox7b [Genbank:NM 025379]
mtDNACtrlRNA [Genbank:U47435]
Slc25a3 [Genbank:BC018161]
AcylCoAtrsp [Genbank:BC005616]
RpL21 [Genbank:U93863]
HistAcetyl [Genbank:AF3 19620]
Hmlg.apopts [Genbank:AK00891 I]
rib. prot. S23 [Genbank:AKO 12574]

T I/CI T2/C2 T3/C3 D2/C4 D I/C4 TI/CI T2/C2 T3/C3 D2/C4 DI /C4

I 1.9 I 0.7 0.7 NS 5.3E-04 NS 0.002 3.5E-05





TI, T2, T3, treated animals and CI, C2, C3 controls are as in Table (I), NOD long-term diabetic (D2), NOD new-onset diabetic (DI), non-diabetic
NOD control (C4). For each gene, the mean expression value ratio between treated (or diabetic) and control animals are represented. Student test
p values obtained for every comparison are also shown.

promotes macrophage infiltration during interstitial
fibrosis and wound healing.

Involvement of Fkbp-52
FKBP-52, an immunophilin, is down-regulated in the BSA
treated NON and NOD.B10 mice. FKBP-52 binds to
immunosuppressants such as FK506 and is part of the
nontransformed glucocorticoid-receptor (GC-receptor).
In the kidney cortical collecting duct, maneuvers inactivat-
ing FKBP-52 or slowing it's disassociation from the recep-
tor complex, reduce the response of calcineurin to steroid
hormones [37]. FKBP-52 can be co-purified with CaMK
and is also phosphorylated in vitro by CaMK [38]. This has
led to suggest that FKBP-52 plays a role in signaling path-
ways involving phosphorylation by CaMK. Moreover,
CaMK inhibitors, as well as immunosuppressants have
strictly parallel effects even in different cell types [39]. Tak-
ing into account that the transcription of FKBP-52 varies
due to BSA-treatment coincidentally with CaMKII, the
FKBP-52/CaMKII axis may have a role in the response to
BSA-treatment in mice. FKBP-52 may nevertheless have a
more diversified role since it is also down-regulated in
type I diabetes [4]. In human, the specific target for FKBP-
52 is phytanoyl-CoA alpha-hydroxylase (PAHX), an
orthologue of mouse LN1, which is potentially involved
in the progression of lupus nephritis [40]. PAHX and
SCD-1, another enzyme downregulated in NOD diabetic
mice, play a sequential role in peroxisomal lipid process-
ing, suggesting that disruptions in lipid homeostasis occur
in diabetes and proteinuria.

Lipid processing
In NOD.B10 and NON mice, BSA treatment affects several
transcripts involved in lipid processing. In NON, Insig-1 is
up-regulated. When up-regulated, Insig-1 is known to
block up-regulation of Peroxisome Proliferator receptor

(PPAR) gamma-2 [41]. This is interesting because PPAR-
gamma agonists have also been shown to protect against
diabetic nephropathy in type 1 diabetes models [42-44] as
well as in type 2 diabetes concurrent with obesity [45].
Such agonists also protect against nondiabetic glomerulo-
sclerosis [46]. PPAR gamma expression is known to be
under the control of the Signal transducer and activator of
transcription (STAT) 5 [47] and it has recently been
reported [191 that albumin treatment of proximal tubular
cells increases the activity of STATs. We did not detect
changes of STATs at the expression level. This could be
explained by the absence of the STAT genes on our micro-
array or a change of STAT activity. The PPAR gamma and
janus kinase-signal transducer and activator of transcrip-
tion (JAK-STAT) signaling pathways may therefore play a
role in the response to BSA treatment. Remarkably, STAT
5 proteins can also associate with the GC-receptor in a
highly regulated manner [48]. Since glucocorticoids stim-
ulate the expression of PPAR gamma in adipocytes and
FKBP-52 is part of the GC-receptor complex, there may be
a crosstalk between the glucorticoid receptor, PPAR
gamma and JAK-STAT signaling during BSA treatment.

Possible effects of strain differences
Although the experimental design tries to dissect the
effects of proteinuria from the initial source of CKD, some
of the responses observed in this study could point out
differences between mouse strains. For example, although
the GC-receptor may be involved, it may act slightly dif-
ferently in each strain. In this regard, it is relevant to point
out the increase of the Igf2bpl protein in BSA treated
NON mice. Igf2bpl is known to stabilize c-Myc mRNA,
preventing its degradation. It is known thatT lymphocytes
of NOD mice are resistant to apoptosis induced by gluco-
corticoids which normally down-regulate c-myc through
the activated GC-GC receptor complex. Martins and Aguas

Page 7 of 9
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Gene Name ID

BMC Nephrology 2005, 6:17

[49] investigated whether expression of Myc protein, in
response to dexamethasone stimulation, was the same in
NOD mice compared to NON and other mice not prone
to diabetes. They found a consistent increase in the levels
of Myc protein after GC-treatment of lymphocytes of
NOD mice, in contrast with the down-regulation of c-myc
in lymphocytes from mice not prone to diabetes, suggest-
ing that the GC-receptor may not regulate c-Myc expres-
sion in the same way in the NOD and NON mice. We and
others [45] also observed that lipid processing and PPAR
gamma play a role in kidney complications, and because
PPAR gamma and STAT5b are known to auto-regulate
each other in a retrocontrol manner [47], we also dis-
cussed a possible cross-talk between PPARs and STATs.
However, the auto-regulation mechanism of PPAR
gamma by STAT5b may be deficient in NOD mice, in light
of recent evidence that NOD mice present a mutation in
the DNA binding domain of STAT5b, which reduces
STAT5b DNA binding affinity [50].

In summary, this study highlights some of the differen-
tially regulated pathways that may be important in the
progression of CKD. Some of the pathways appear to be
common to different inciting etiologies and others may be
unique as demonstrated by the NON versus NOD.B10
paradigm. By global histologic criterion these two strains
appear to have the same end point but they begin at dif-
ferent places. This paradigm is reflected in the gene expres-
sion analysis and suggests the power of this approach in
unraveling a complex disease process.

Competing interests
The authors) declare that they have no competing inter-

Authors' contributions
KW drafted the outline of this manuscript and contributed
to the discussion of the microrray results. She also con-
structed the substractive library, PCR amplified and puri-
fied the 5760 library clones for the array chips, conducted
the microarray hybridizations followed by data analysis
and sequencing of the clones of interest. JXS contribution
is in experimental design, data interpretation and prepara-
tion of manuscript. BC's role in the project was to design,
supervise and complete the in vivo work and the pathol-
ogy. LM participated in data acquisition. RMI provided
bioinformatics support, and data analysis. AA assisted in
the design and data interpretation of the manuscript. SE
printed the arrays. All authors have read and approved the

This project was supported by a NIDDK Biotechnology Center grant (U24
DK58778) and a grant from NIAID (2PO 1I AI-42288) to J.X.S.

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