Open Access

Differential gene expression in ADAM10 and mutant ADAM10 transgenic mice

  • Claudia Prinzen1,
  • Dietrich Trümbach2,
  • Wolfgang Wurst2,
  • Kristina Endres1,
  • Rolf Postina1 and
  • Falk Fahrenholz1Email author
BMC Genomics200910:66

DOI: 10.1186/1471-2164-10-66

Received: 19 June 2008

Accepted: 05 February 2009

Published: 05 February 2009

Abstract

Background

In a transgenic mouse model of Alzheimer disease (AD), cleavage of the amyloid precursor protein (APP) by the α-secretase ADAM10 prevented amyloid plaque formation, and alleviated cognitive deficits. Furthermore, ADAM10 overexpression increased the cortical synaptogenesis. These results suggest that upregulation of ADAM10 in the brain has beneficial effects on AD pathology.

Results

To assess the influence of ADAM10 on the gene expression profile in the brain, we performed a microarray analysis using RNA isolated from brains of five months old mice overexpressing either the α-secretase ADAM10, or a dominant-negative mutant (dn) of this enzyme. As compared to non-transgenic wild-type mice, in ADAM10 transgenic mice 355 genes, and in dnADAM10 mice 143 genes were found to be differentially expressed. A higher number of genes was differentially regulated in double-transgenic mouse strains additionally expressing the human APP[V717I] mutant.

Overexpression of proteolytically active ADAM10 affected several physiological pathways, such as cell communication, nervous system development, neuron projection as well as synaptic transmission. Although ADAM10 has been implicated in Notch and β-catenin signaling, no significant changes in the respective target genes were observed in adult ADAM10 transgenic mice.

Real-time RT-PCR confirmed a downregulation of genes coding for the inflammation-associated proteins S100a8 and S100a9 induced by moderate ADAM10 overexpression. Overexpression of the dominant-negative form dnADAM10 led to a significant increase in the expression of the fatty acid-binding protein Fabp7, which also has been found in higher amounts in brains of Down syndrome patients.

Conclusion

In general, there was only a moderate alteration of gene expression in ADAM10 overexpressing mice. Genes coding for pro-inflammatory or pro-apoptotic proteins were not over-represented among differentially regulated genes. Even a decrease of inflammation markers was observed. These results are further supportive for the strategy to treat AD by increasing the α-secretase activity.

Background

Accumulation of amyloid β-peptides (Aβ) in the brain is believed to contribute to the development of Alzheimer disease (AD). Soluble oligomeric forms of Aβ are neurotoxic [13]. Aβ, a 40–43 amino acid-comprising proteolytical fragment of the amyloid precursor protein (APP), is released from APP by sequential cleavages via β- and γ-secretases. However, the predominant route of APP processing consists of successive cleavages by α- and γ-secretases. Alpha-secretase attacks APP inside the Aβ sequence, and therefore prevents formation of neurotoxic Aβ. In addition, the soluble N-terminal domain of APP (APPsα) is released, which has neurotrophic and neuroprotective properties [4, 5], and enhances LTP [6]. In behavioral paradigms, APPsα was demonstrated to improve memory in normal and amnesic mice [7]. Reduced amounts of APPsα were detected in the cerebrospinal fluid of AD patients [8, 9].

Proteinases of the ADAM (a d isintegrin a nd m etalloproteinase) family are main candidates for physiologically relevant α-secretases, and we demonstrated that ADAM10 has α-secretase activity in vitro and in cultured cells [10]. ADAM10-deficient mice have been generated [11], but their early lethality at day E9.5 prevents a reliable analysis of ADAM10's α-secretase function in vivo, especially in neuronal cells.

To investigate whether an increase in activity of putative α-secretases in vivo prevents plaque formation and cognitive deficits, we generated transgenic mice overexpressing either the α-secretase ADAM10 (ADAM10 mice) or the catalytically inactive ADAM10[E384A] mutant (dnADAM10 mice) [12]. Neuronal overexpression of ADAM10 had no detrimental effects on ADAM10 single-transgenic mice: these animals exhibited normal behavioral abilities [13]. We found that a moderate neuronal overexpression of ADAM10 in mice carrying the human APP[V717I] mutation (ADAM10/APP[V717I] mice) increased the secretion of APPsα, reduced the formation of Aβ peptides, and prevented their deposition in plaques. Functionally, impaired long-term potentiation and cognitive deficits were alleviated. Expression of dominant-negative ADAM10[E384A] in APP[V717I] mice (dnADAM10/APP[V717I] mice) led to reduction of APPsα and to enhancement of the number and size of amyloid plaques in the brain [12].

Histological analyses of mono-transgenic ADAM10 mice revealed an increase in cortical cholinergic, glutamatergic and GABAergic presynaptic bouton densities in 8 months old mice; the cholinergic presynaptic bouton density remained elevated even during aging in ADAM10 mice [14].

In addition to their metalloproteinase domain, ADAMs contain a disintegrin domain as a modulator of cell-cell and cell-matrix interactions [15]. As ADAM10 itself has been reported to be a substrate for ectodomain shedding by ADAM9 and subsequent cleavage by γ-secretase, the C-terminus of ADAM10 may represent a Notch-like signaling molecule [16]. Thus, independent of the catalytic activity of ADAM10, which has been implicated in Notch and β-catenin signaling, ADAM10 may also modulate gene expression via other domains.

To analyze the influence of ADAM10 and its dominant-negative form (dnADAM10) on the gene expression profile of the central nervous system (CNS), we investigated ADAM10 and dnADAM10 mice. We included in our study the double-transgenics ADAM10/APP[V717I] and dnADAM10/APP[V717I]. Since APP[V717I] mice show early phenotype changes (between months 4 and 7), we investigated the gene expression in 5 months old mice.

Methods

Animals

Animal husbandry was performed in accord with the guidelines of the German Council on Animal Care. All mouse strains (strain background FVB/N) analyzed in this study have been described previously [12]. The expression level of transgenic mature ADAM10 is 30% above endogenous levels and in dnADAM10 mice the expression of the catalytically inactive ADAM10 mutant is sevenfold above endogenous ADAM10 [12]. ADAM10 activity was determined in previous studies [12, 17] by quantitation of the APP cleavage product APPsα. In ADAM10 overexpressing mice the catalytic activity of ADAM10 against its substrate APP[V717I] was increased to about 250%. In mice overexpressing dnADAM10, the endogenous APP[V717I] cleavage activity was reduced to about 25% as compared to APP[V717I] mice [12].

For the first experimental series of the present study, female ADAM10, dnADAM10 and FVB/N wild-type mice were investigated; for the second series, female and male ADAM10/APP[V717I], dnADAM10/APP[V717I] and APP[V717I] mice were compared. In each case, brains of three 5 months old animals of each group were dissected and stored in RNA-later (Qiagen, Hilden, Germany) at -80°C to prevent RNA degradation.

RNA preparation and microarray analyses

Total RNA from whole mouse brains was isolated by using the RNeasy Kit (Qiagen, Hilden, Germany), including on-column DNase I digestion according to the manufacturer's recommendations. The quality of isolated RNA was controlled by the Lab-on-Chip-System Bioanalyser 2100 (Agilent Technologies Inc., Palo Alto, CA, USA).

The expression-profiling analysis for mono-transgenic mice (ADAM10, dnADAM10 mice and non-transgenic FVB/N control animals) was carried out at RZPD (Berlin, Germany). Samples from double-transgenic mice (ADAM10/APP[V717I, dnADAM10/APP[V717I] and mono-transgenic APP[V717I] control mice) were analyzed at the Microarray Facility (Tübingen, Germany). In all cases, the Mouse Genome 430 2.0 Array (Affymetrix, Santa Clara, CA, USA) containing 45000 probe sets of 34000 genes was used for mRNA expression profiling.

Statistical analysis and gene annotations

For the first series (mono-transgenic mice) 9 gene chip arrays and for the second series (double-transgenic mice) 18 gene chip arrays were analyzed. Data mining was performed by using the ChipInspector analysis software (Genomatix, Munich, Germany), which identifies significant changes based on single probes. The corresponding transcripts were then assigned after a user-defined number of significant probes. For all analyses, a transcript coverage greater than three probes was chosen. By this strategy, annotation errors and errors caused by the existence of alternative transcripts are reduced.

After total intensity normalization of each array, significantly changed genes were determined by significance analysis of microarrays (SAM) [18], using the exhaustive comparison mode at a false discovery rate (FDR) of 0.0% for double-transgenic, and 0.5% for mono-transgenic mice. For separate analysis of samples from double-transgenic female and male mice, a FDR of 1.3% was chosen. The resulting gene lists were restricted to the 600 most strongly regulated genes (up- as well as downregulated genes).

Regulated genes were then analyzed with the Bibliosphere software (Version 5.02; Genomatix, Munich, Germany) and mapped to Gene Ontology (GO) trees in order to identify their biological function. For identification of over-represented GO terms, the Bibliosphere software calculates a z-score for each term. The z-score represents the difference between observed and expected annotations, and is normalized to the standard deviation of a hypergeometric distribution. Only GO terms with a z-score > 1.96, which corresponds to a p-value of 0.05, have been considered.

To identify transcripts which are affected by ADAM10 and dnADAM10 overexpression in mono- and double-transgenic mice, we generated Venn diagrams with SAM-based gene lists. The expression profile of selected significantly regulated genes from microarrays was represented by heat maps using the R statistical software http://www.r-project.org. Hierarchical clustering was applied to investigate whether expression values can be separated according to experimental groups. In this study, two heat maps were generated: one compared the expression profiles of genes in ADAM10 and dnADAM10 mono-transgenic mice, as well as in FVB/N non-transgenic control mice; a second one compared the expression profiles of double-transgenics and APP[V717I] mice.

Because the two series of expression arrays were measured in different laboratories, a global normalization procedure was needed to make them comparable. The default background noise adjustment, provided by the Affymetrix system, is based on the difference of perfect matching probes (PM) minus mismatching probes (MM). Due to unspecific binding, the global background adjustment method robust multi-array average (RMA) expression measure, which ignores the MM intensities, has been developed [19]. Because RMA adjustment does not completely remove unspecific intensities [20], an enhanced method denoted GeneChip RMA (GCRMA) has been designed [21] which considers the sequence of probes.

We performed background adjustment as well as quantile normalization for all data sets (raw format, cell files) with the GCRMA method (standard settings) by using the CARMAweb interface [22]. Subsequently, an unpaired two-tailed Student's t-test was applied for each respective gene to determine whether it is differentially expressed in the two sample groups. Since microarray analysis operates with large numbers of multiple comparisons, a false discovery rate-controlling method has to be applied. Therefore, by using the Benjamini-Hochberg (BH) method, adjusted p-values were calculated [23].

The GCRMA method is also appropriate for detection of minor changes in gene expression, and was required for comparative analysis of mono- and double-transgenic mice, due to the low intensities of the microarrays from the first series (mono-transgenic mice) as compared to those of the second series (double-transgenic mice). By comparing data derived from mono- and double-transgenic mice, we analyzed global biological trends of ADAM10 and dnADAM10 overexpression in FVB/N and FVB/N APP[V717I] strain backgrounds.

To identify transcripts which were commonly affected by APP[V717I]overexpression in all double-transgenic mice, we generated a Venn diagram with GCRMA-based gene lists (BH<0.005).

Quantitative real-time RT-PCR

A two-step real-time reverse transcription (RT)-PCR was used to measure the expression of candidate genes. Isolated total RNA (1 μg) was used to synthesize cDNA in a 20 μl reaction with the QuantiTect Reverse Transcription Kit (Qiagen, Hilden, Germany) according to the manufacturer's manual. By adding water, the reaction volume was subsequently increased to 500 μl. Real-time RT-PCR was carried out in 96-well plates, using the 7000 ABI prism sequence detection system (Applied Biosystems, Darmstadt, Germany) and QuantiTect Primer Assays (Qiagen, Hilden, Germany). The primers for selected candidate genes are listed in table 1.
Table 1

QuantiTect Primer Assays (Qiagen, Hilden, Germany)

Gene name

Gene ID

Assay

ADAM10

11487

Mm_Adam10_1_SG

Fatty acid binding protein 7

12140

Mm_Fabp7_1_SG

Calcium binding protein S100a9

20202

Mm_S100a9_1_SG

Calcium binding protein S100a8

20201

Mm_S100a8_1_SG

Glutamate receptor, ionotropic, AMPA1

14799

Mm_Gria_1_SG

Glutamate receptor, ionotropic, AMPA2

14800

Mm_Gria2_1_SG

Low density lipoprotein receptor-related protein 1

16971

Mm_Lrp1_1_SG

Very low density lipoprotein receptor

22359

Mm_Vldlr_1_SG

Microtubule-associated protein tau

17762

Mm_Mapt_1_SG

Neuroligin 1

192167

Mm_Nlgn1_1_SG

GAPDH

14433

Mm_Gapdh_2_SG

Real-time RT-PCR reactions in a volume of 30 μl were performed in duplicate or triplicate under the following conditions: 5 μl of diluted cDNA (see above), 15 μl 2× QuantiTect PCR master mix (Qiagen, Hilden, Germany) and 300 nM of respective primer pair. After the initial denaturing and enzyme activation step (95°C for 15 min), 40 cycles (94°C for 15s, 55°C for 30s, and 72°C for 30s) were performed. A single DNA melting profile was observed in dissociation assay conditions demonstrating amplification of a unique product free of primer dimers.

For detection of Hes5 in 15 day old mice a one step Real-time RT-PCR was performed using the QuantiTect-SYBR-Green One-Step-RT PCR-Kit (Qiagen, Hilden, Germany) and 250 ng RNA in a reaction volume of 30 μl. The specific primer pair was as follows: Hes5RT_for 5'GAAAAACCGACTGCGGAAGCC3' and Hes5RT_rev 5'ACGGCCATCTCCAGGATGTC3'.

For data analysis, the threshold cycle (Ct) which indicates the relative abundance of a particular transcript, was calculated. Standard curves were generated by amplification of serially diluted cDNA. According to this method, the amount of all relevant genes was normalized to the amount of endogenous GAPDH present in the same sample. Measured values from control samples (non-transgenic FVB/N mice or mono-transgenic APP[V717I] mice) were set to 100%. Changes in gene expression are presented as the mean of alteration ± SD. The data were analyzed for statistical significance using one-way ANOVA (*, p < 0.05; **, p < 0.01; ***, p < 0.001).

Western blotting

Mouse brain tissue was stored on dry ice immediately after dissection. Ice-cold TRIS buffer (20 mM Tris/HCl, pH 8.5) containing proteinase inhibitors (Inhibitor complete mini, Roche Diagnostics Corp., Mannheim, Germany) was added, and tissue was homogenized in a tissue lyser (Qiagen, Hilden, Germany). The supernatants resulting from centrifugation at 34000 rpm for 1.75 hours were separated on 14% SDS-gels and transferred to nitrocellulose membrane by tank blot system (40 μg protein per sample). For the detection and quantification of soluble FABP7 antibody AB9558 (Chemicon, Temecula, USA), and the appropriate horseradish peroxidase-coupled secondary antibody (Pierce, Rockford, USA) were used.

ELISA

Hemispheres of mouse brain were weighed, proteins extracted and calprotectin (S100a8/a9) was quantified as recommended by the ELISA manufacturer (Immundiagnostik, Bensheim, Germany). In brief, tissue was homogenized in extraction buffer for 2 min at 20 Hz in a tissue lyzer and extraction was performed for 20 min at 4°C under agitation. After centrifugation (14000 rpm, 15 min) the supernatant and protein standards were added to microtiter plates in a total volume of 100 μl in duplicates. Incubation of the plate and measurement of optical densities at 405 nm were performed following the manufacturer's instructions. The relative amount of calprotectin was calculated by division of background-corrected values by wet tissue weight.

Results

Microarray analysis of gene regulation in ADAM10-transgenic mice

We performed microarray analysis with cDNA transcribed from total RNA of the brains of mice aged five months. Mono-transgenic ADAM10 as well as dnADAM10 mice were investigated in comparison to non-transgenic FVB/N wild-type mice (n = 3 females), to analyze the influence of the α-secretase ADAM10 or its catalytically inactive form (dnADAM10) on the gene expression profile of the CNS.

To elucidate the effect of ADAM10 and dnADAM10 on gene expression in an APP background, we compared samples derived from double-transgenic ADAM10/APP[V717I] and dnADAM10/APP[V717I] mice with those from mono-transgenic APP[V717I] mice. Because we wanted to test whether the modulation of ADAM10 activity might be a risk to the adult organism in respect to future therapeutic approaches, we chose 5 months old mice for our investigations. At this age, APP[V717I] animals show cognitive deficits, whereas amyloid plaque formation occurs several months later [24].

The SAM plots in Fig. 1 represent the distribution of all probe signals on the microarray chip. Depending on the statistical stringency (FDR, delta) as represented by the red lines, significant probes are selected. Probe signals between the red lines are not significant, signals above the upper line correspond to significantly upregulated genes; signals below the lower line correspond to significantly downregulated genes. Tables 2 and 3 show the numbers of these differentially expressed genes.
Table 2

Numbers of significantly regulated genes in mono-transgenic mice (5 months, 3 females per group) restricted by the given d-values.

Mouse Genome 430 2.0 Array (Affymetrix)

45 000 probe sets, 39 000 transcripts, 34 000 characterized

ADAM10 versus FVB/N (wild-type)

355 genes, FDR = 0.5%

dnADAM10 versus FVB/N (wild-type)

143 genes, FDR = 0.5%

300 upregulated

(d-value > 2.23)

55 downregulated

(d-value < -1.72)

50 upregulated

(d-value > 1.43)

93 downregulated

(d-value < -1.36)

Table 3

Numbers of significantly regulated genes in double-transgenic mice (5 months, 3 females and 3 males per group) restricted by the given d-values.

Mouse Genome 430 2.0 Array (Affymetrix)

45 000 probe sets, 39 000 transcripts, 34 000 characterized

ADAM10/APP[V717I] versus APP[V717I]

592 genes, FDR = 0.0%

dnADAM10/APP[V717I] versus APP[V717I]

600 genes, FDR = 0.0%

295 upregulated

(d-value > 2.06)

297 downregulated

(d-value < -1.56)

300 upregulated

(d-value > 3.29)

300 downregulated

(d-value < -2.85)

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig1_HTML.jpg
Figure 1

Significance analysis of microarrays. The SAM plots represent the differentially expressed genes of mono-transgenic (A and B with FDR 0.5), and double-transgenic mice (C and D with FDR 0.0). The Delta parameter, represented by red lines, defines the significance field (-1.72/+2.23 (A: ADAM10 versus FVB/N), -1.36/+1.43 (B: dnADAM10 versus FVB/N), -1.56/+2.06 (C: ADAM10/APP[V717I] versus APP[V717I]), -2.85/+3.29 (D: dnADAM10/APP[V717I] versus APP[V717I])). Shown above the upper line are the genes upregulated significantly, and below the lower line the genes downregulated significantly.

The comparison of samples from ADAM10 and FVB/N mice revealed 355 differentially expressed genes: 300 genes were up- and 55 genes were downregulated. In dnADAM10 mice, the number of regulated genes was lower; as compared to FVB/N mice, 143 genes were differentially expressed. Among these, 50 genes were up- and 93 genes downregulated (Tab. 2).

Against the background of APP[V717I] overexpression, generally more genes were found to be differentially expressed. As compared to APP[V717I] mice, 592 genes (295 up- and 297 downregulated) were differentially expressed in ADAM10/APP[V717I] mice, and more than 600 genes in dnADAM10/APP[V717I] animals (Tab. 3). In the latter, the number of significantly regulated genes was restricted to 600, including the highest up- and downregulated genes. For the complete list of significantly regulated genes, see Additional file 1, Tables S1-S4. The data presented in this publication have been deposited in NCBI's Gene Expression Omnibus (GEO), and are accessible by the GEO Series accession numbers GSE10908 and GPL1261 http://www.ncbi.nlm.nih.gov/geo/info/faq.html#deposit.

For detection of transcripts that were commonly regulated by either ADAM10 or dnADAM10 overexpression in mono- and double-transgenic mice, Venn diagrams were generated with SAM-based gene lists (Fig. 2). The comparison of ADAM10 versus FVB/N (355 genes), and ADAM10/APP[V717I] versus APP[V717I] (592 genes) revealed 29 genes which were regulated by ADAM10 overexpression in either mono- or double-transgenic mice (Additional file 1, Tab. S5). When dnADAM10 versus FVB/N (143 genes) and dnADAM10/APP[V717I] versus APP[V717I], were compared, only eight genes were identified to be commonly regulated by dnADAM10 overexpression (Additional file 1, Tab. S6). This result indicates that the genetic background strongly influences the effect of ADAM10 on gene expression.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig2_HTML.jpg
Figure 2

Venn diagrams with SAM-based gene lists of mono- and double-transgenic mice. Venn diagram I (ADAM10 versus FVB/N (A) is compared with ADAM10/APP[V717I] versus APP[V717I] (B)), and Venn diagram II (dnADAM10 versus FVB/N (A) is compared with dnADAM10/APP[V717I] versus APP[V717I] (B)), generated by a custom-written Perl-script, show the effects of the overexpression of ADAM10 and dnADAM10 in mono- and double-transgenic mice. The numbers in the space of overlapping circles represent the number of transcripts that were affected in both mouse lines.

Common genetic profile in mono- and double-transgenic animals

Heat maps (Fig. 3) indicate that the chips of each series had their own characteristic genetic profile. For heat maps, genes of special interest were chosen (mono-transgenic mice: Adam10, Fabp7, S100a8, S100a9, Nlgn1; double-transgenic mice: Mapt, Gria1, Vldlr, Lrp1, Bace1, Psen1, Psen2, ApoE). The heat map in Fig. 3A reveals that in mice overexpressing bovine ADAM10, approximately the same amount of murine Adam10 is expressed as compared to wild-type mice (nearly all over yellow coloring). Fabp7 is distinctly higher expressed in all dnADAM10 mice (red color) in contrast to wild-type mice (orange color). The expression of Nlgn1 in ADAM10 and dnADAM10 mice is higher (yellow to green) than in FVB/N mice (green color)). Finally, S100a8 and S100a9 show lower expression in ADAM10 and dnADAM10 mice (blue color) in relation to FVB/N wild-type mice (yellow to blue). These results are in accordance with the observations made by the real-time RT-PCR as described below. Furthermore, hierarchical clustering showed that the expression profiles of the mono-transgenic mouse genes are separated to the original conditions. In the case of heat map in Fig. 3B, the small differences in the expression of Mapt, Gria1, Vldlr and Lrp1 are fitting to the results of real-time RT-PCR analyses as described below. Hierarchical clustering revealed that the expression profiles of double-transgenic mice genes are not clearly clustered according to the experimental settings, presumably due to the more complex conditions caused by APP overexpression. Also, a clear distinction between male and female mice could not be observed.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig3_HTML.jpg
Figure 3

Heat map representing the clustering of genes in mono- and double transgenic mice. A) ADAM10, dnADAM10 and FVB/N mice; B) AD10/APP[V717I], dnAD10/APP[V717I], and APP[V717I] mice. Selected significantly regulated genes on individual chips are shown. The upper graph (I) represents the hierarchical clustering, the colored scales (II) the difference in gene expression. Unsupervised cluster analysis showed that the expression profiles of mono-transgenic mouse genes (A) cluster according to the experimental conditions. In case of double-transgenic mice (B), cluster analysis revealed a more rough agreement in the discrimination of gene expression with experimental groups. The blue (lower expression) to red (higher expression) color scale indicates 2-based logarithms of the mean expression values of the single probes after ChipInspector normalization (Genomatix, Munich, Germany).

ADAM10-regulated biological pathways

For pathway analysis, the complete gene lists were analyzed with the Bibliosphere software (Genomatix) and mapped to Gene Ontology (GO) trees.

Functional groups are only listed when their z-score of individual GO-categories is higher than 1.96. With respect to the known cellular function of disintegrin metalloproteases in general, and the α-secretase activity of ADAM10 in particular, we investigated biological processes including cell communication (GO:0007154), nervous system development (GO:0007399), cell adhesion (GO:0007155) and cell death (GO:0008219). Furthermore, we examined neuron projection (GO:0043005), synaptic junction (GO:0045202) and transmission (GO:0007268). At the molecular level, we focused on receptor binding (GO:0005102) and receptor activity (GO:0004872) (Tab. 4, 5, 6, 7).
Table 4

Significantly regulated genes in mono-transgenic ADAM10 mice in relation to FVB/N wild-type mice

Gene ID

Gene symbol

Description

Fold change

log ratio

d-value

Functional groups

27360

Add3

adducin 3 (gamma)

1.519

0.603

2.841

receptor binding and activity

68465

Adipor2

adiponectin receptor 2

1.365

0.449

2.294

cell communication

11658

Alcam

activated leukocyte cell adhesion molecule

1.471

0.557

2.298

nervous system development; neuron projection

211673

Arfgef1

ADP-ribosylation factor guanine nucleotide-exchange factor 1(brefeldin A-inhibited)

1.503

0.588

2.644

cell communication

11855

Arhgap5

Rho GTPase activating protein 5

1.621

0.697

2.526

cell communication

98660

Atp1a2

ATPase, Na+/K+ transporting, alpha 2 polypeptide

0.792

-0.337

-1.972

cell communication; synapse

11941

Atp2b2

ATPase, Ca++ transporting, plasma membrane 2

1.734

0.794

2.717

cell communication; nervous system development; receptor binding and activity; synapse

22589

Atrx

alpha thalassemia/mental retardation syndrome X-linked homolog (human)

1.507

0.592

2.876

nervous system development

30948

Bin1

bridging integrator 1

1.451

0.537

2.318

cell communication; synapse

12298

Cacnb4

calcium channel, voltage-dependent, beta 4 subunit

1.800

0.848

2.913

cell communication; synapse

12322

Camk2a

calcium/calmodulin-dependent protein kinase II alpha

1.779

0.831

2.547

cell communication; receptor binding and activity; synapse

16149

Cd74

CD74 antigen (invariant polypeptide of major histocompatibility complex, class II antigen-associated)

0.724

-0.466

-2.270

cell communication; cell death

212285

Centd1

centaurin, delta 1

1.569

0.650

2.530

cell communication

12633

Cflar

CASP8 and FADD-like apoptosis regulator

1.393

0.478

2.497

cell death

12704

Cit

citron

1.476

0.562

2.405

cell communication; nervous system development

12803

Cntf

ciliary neurotrophic factor

1.496

0.581

2.355

cell communication; nervous system development

70086

Cysltr2

cysteinyl leukotriene receptor 2

1.307

0.386

2.251

cell communication

13618

Ednrb

endothelin receptor type B

1.364

0.448

2.506

cell communication; nervous system development

13838

Epha4

Eph receptor A4

1.622

0.698

2.439

cell communication; nervous system development

67456

Ergic2

ERGIC and golgi 2

1.367

0.451

2.316

cell communication; synapse

14397

Gabra4

gamma-aminobutyric acid (GABA-A) receptor, subunit alpha 4

1.542

0.625

2.316

cell communication; synapse

14417

Gad2

glutamic acid decarboxylase 2

1.636

0.710

3.290

cell communication; neuron projection; synapse

14674

Gna13

guanine nucleotide binding protein, alpha 13

1.502

0.587

2.257

cell communication

14677

Gnai1

guanine nucleotide binding protein, alpha inhibiting 1

1.576

0.656

2.911

cell communication

14680

Gnal

guanine nucleotide binding protein, alpha stimulating, olfactory type

1.598

0.676

3.061

cell communication

53623

Gria3

glutamate receptor, ionotropic, AMPA3 (alpha 3)

1.480

0.566

2.388

synapse

56637

Gsk3b

glycogen synthase kinase 3 beta

1.540

0.623

2.382

cell communication; cell death

15208

Hes5

hairy and enhancer of split 5 (Drosophila)

0.749

-0.416

-1.800

nervous system development

16419

Itgb5

integrin beta 5

0.786

-0.347

-2.185

cell adhesion; cell communication

16510

Kcnh1

potassium voltage-gated channel, subfamily H (eag-related), member 1

1.398

0.483

2.291

cell communication; receptor binding and activity

16561

Kif1b

kinesin family member 1B

1.555

0.637

2.573

cell communication; synapse

16573

Kif5b

kinesin family member 5B

1.904

0.929

3.186

neuron projection; synapse

16574

Kif5c

kinesin family member 5C

1.656

0.728

2.463

nervous system development; neuron projection; synapse

110829

Lims1

LIM and senescent cell antigen-like domains 1

1.533

0.616

2.309

cell adhesion

108030

Lin7a

lin-7 homolog A (C. elegans)

1.346

0.429

2.260

cell communication; synapse

319387

Lphn3

latrophilin 3

1.295

0.373

2.344

cell communication

16971

Lrp1

low density lipoprotein receptor-related protein 1

0.707

-0.500

-2.139

cell communication

16998

Ltbp3

latent transforming growth factor beta binding protein 3

0.791

-0.338

-2.180

cell communication; receptor binding and activity

50791

Magi2

membrane associated guanylate kinase, WW and PDZ domain containing 2

1.426

0.512

2.399

cell communication

192167

Nlgn1

neuroligin 1

1.518

0.602

2.386

cell communication; nervous system development; synapse

18549

Pcsk2

proprotein convertase subtilisin/kexin type 2

1.492

0.577

2.393

nervous system development

18573

Pde1a

phosphodiesterase 1A, calmodulin-dependent

1.796

0.845

3.130

cell communication; receptor binding and activity

18596

Pdgfrb

platelet derived growth factor receptor, beta polypeptide

0.800

-0.322

-1.867

cell communication

18613

Pecam1

platelet/endothelial cell adhesion molecule 1

0.778

-0.363

-2.093

cell communication

18795

Plcb1

phospholipase C, beta 1

1.652

0.724

3.345

cell communication

18798

Plcb4

phospholipase C, beta 4

1.480

0.566

2.451

cell communication

242083

Ppm1l

protein phosphatase 1 (formerly 2C)-like

1.604

0.682

2.277

cell communication

26932

Ppp2r5e

protein phosphatase 2, regulatory subunit B (B56), epsilon isoform

1.578

0.658

2.298

cell communication

19281

Ptprt

protein tyrosine phosphatase, receptor type, T

1.409

0.495

2.354

cell communication

19328

Rab12

RAB12, member RAS oncogene family

1.250

0.322

2.259

cell communication

270192

Rab6b

RAB6B, member RAS oncogene family

1.696

0.762

2.837

cell communication; synapse

56044

Rala

v-ral simian leukemia viral oncogene homolog A (ras related)

1.582

0.662

2.544

cell communication

54409

Ramp2

receptor (calcitonin) activity modifying protein 2

1.693

0.760

2.640

cell communication

218397

Rasa1

RAS p21 protein activator 1

1.428

0.514

2.266

cell adhesion; cell communication; cell death

19737

Rgs5

regulator of G-protein signaling 5

1.677

0.746

2.390

cell communication

19894

Rph3a

rabphilin 3A

1.470

0.556

2.352

synapse

68585

Rtn4

reticulon 4

1.542

0.625

2.344

cell death; nervous system development

20202

S100a9

S100 calcium binding protein A9

0.668

-0.582

-2.146

cell communication

20377

Sfrp1

secreted frizzled-related sequence protein 1

0.793

-0.335

-1.730

cell communication

239250

Slitrk6

SLIT and NTRK-like family, member 6

1.324

0.405

2.293

nervous system development

93761

Smarca1

SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 1

1.309

0.388

2.351

nervous system development

66042

Sostdc1

sclerostin domain containing 1

0.725

-0.464

-1.768

cell communication

20742

Spnb2

spectrin beta 2

1.729

0.790

2.855

cell communication; receptor binding and activity

114716

Spred2

sprouty-related, EVH1 domain containing 2

1.514

0.598

2.653

cell communication

21961

Tns1

tensin 1

1.505

0.590

2.245

cell communication

22370

Vtn

vitronectin

0.778

-0.362

-1.925

cell adhesion

22371

Vwf

Von Willebrand factor homolog

0.715

-0.484

-2.099

cell adhesion

57750

Wdr12

WD repeat domain 12

1.391

0.476

2.446

cell communication

232341

Wnk1

WNK lysine deficient protein kinase 1

1.844

0.883

2.947

cell communication

22772

Zic2

Zinc finger protein of the cerebellum 2

1.941

0.957

3.062

nervous system development

Table 5

Significantly regulated genes in mono-transgenic dnADAM10 mice in relation to FVB/N wild-type mice

Gene ID

Gene symbol

Description

Fold change

log ratio

d-value

Functional groups

22589

Atrx

alpha thalassemia/mental retardation syndrome X-linked homolog (human)

1.392

0.477

1.533

nervous system development

109880

Braf

Braf transforming gene

0.568

-0.815

-5.060

cell communication

54598

Calcrl

calcitonin receptor-like

0.626

-0.675

-2.137

cell communication

12322

Camk2a

calcium/calmodulin-dependent protein kinase II alpha

0.686

-0.544

-2.523

cell communication; receptor binding and activity; synapse

12772

Ccr2

chemokine (C-C motif) receptor 2

0.724

-0.465

-1.783

cell communication

16149

Cd74

CD74 antigen (invariant polypeptide of major histocompatibility complex, class II antigen-associated)

0.737

-0.441

-2.329

cell communication; cell death

13175

Dcamkl1

doublecortin and calcium/calmodulin-dependent protein kinase-like 1

1.501

0.586

1.610

nervous system development

12140

Fabp7

fatty acid-binding protein 7

1.691

0.758

2.107

nervous system development

14281

Fos

FBJ osteosarcoma oncogene

0.669

-0.58

-1.805

nervous system development

14417

Gad2

glutamic acid decarboxylase 2

1.422

0.508

1.683

cell communication; neuron projection; synapse

14674

Gna13

guanine nucleotide binding protein, alpha 13

1.353

0.436

1.639

cell communication

14682

Gnaq

guanine nucleotide binding protein, alpha q polypeptide

1.323

0.404

1.621

cell communication; nervous system development; synapse

15557

Htr1f

5-hydroxytryptamine (serotonin) receptor 1F

1.363

0.447

1.539

cell communication

16594

Klc2

kinesin light chain 2

0.789

-0.341

-1.485

neuron projection

207911

Mchr1

melanin-concentrating hormone receptor 1

0.718

-0.477

-3.057

cell communication

17260

Mef2c

myocyte enhancer factor 2C

1.433

0.519

1.507

nervous system development

18823

Plp1

proteolipid protein (myelin) 1

1.358

0.442

1.565

cell communication; nervous system development;

19293

Pvalb

parvalbumin

0.847

-0.24

-1.493

neuron projection

19317

Qk

quaking

1.312

0.392

1.522

cell communication; nervous system development

54409

Ramp2

receptor (calcitonin) activity modifying protein 2

1.604

0.682

1.623

cell communication

19736

Rgs4

regulator of G-protein signaling 4

1.339

0.421

1.843

cell communication

20202

S100a9

S100 calcium binding protein A9

0.696

-0.522

-2.181

cell communication

Table 6

Significantly regulated genes in double-transgenic ADAM10/APP[V717I] mice in relation to mono-transgenic APP[V717I] mice

Gene ID

Gene symbol

Description

Fold change

log ratio

d-value

Functional groups

56215

Acin1

apoptotic chromatin condensation inducer 1

0.795

-0.331

-1.955

cell communication; cell death

329910

Acot11

acyl-CoA thioesterase 11

0.812

-0.301

-1.620

cell communication

432530

Adcy1

adenylate cyclase 1

0.810

-0.304

-1.880

cell communication; receptor binding and activity

68465

Adipor2

adiponectin receptor 2

0.781

-0.357

-1.868

cell communication

11540

Adora2a

adenosine A2a receptor

1.294

0.372

2.210

cell communication; synapse

11735

Ank3

ankyrin 3, epithelial

1.344

0.427

2.159

cell communication; nervous system development; synapse

11787

Apbb2

amyloid beta (A4) precursor protein-binding, family B, member 2

0.788

-0.344

-2.018

cell communication; cell death; nervous system development

226548

Aph1a

anterior pharynx defective 1a homolog (C. elegans)

0.807

-0.309

-1.879

cell communication

76117

Arhgap15

Rho GTPase activating protein 15

1.275

0.351

2.139

cell communication

76294

Asb5

ankyrin repeat and SOCs box-containing protein 5

1.254

0.327

2.079

cell communication

98660

Atp1a2

ATPase, Na+/K+ transporting, alpha 2 polypeptide

0.820

-0.287

-1.746

cell communication; synapse

12043

Bcl2

B-cell leukemia/lymphoma 2

0.815

-0.295

-1.741

cell communication; cell death

72567

Bclaf1

BCL2-associated transcription factor 1

1.326

0.407

2.183

cell death

12122

Bid

BH3 interacting domain death agonist

1.291

0.369

2.278

cell death

109880

Braf

Braf transforming gene

0.812

-0.301

-1.837

cell communication

12227

Btg2

B-cell translocation gene 2, anti-proliferative

1.342

0.424

2.357

cell death

12300

Cacng2

calcium channel, voltage-dependent, gamma subunit 2

0.803

-0.316

-1.872

cell communication

12325

Camk2g

calcium/calmodulin-dependent protein kinase II gamma

0.810

-0.304

-1.711

receptor binding and activity

12319

Car8

carbonic anhydrase 8

0.785

-0.349

-1.679

cell communication

12361

Cask

calcium/calmodulin-dependent serine protein kinase (MAGUK family)

0.832

-0.265

-1.689

receptor binding and activity; synapse

226751

Cdc42bpa

Cdc42 binding protein kinase alpha

1.288

0.365

2.130

cell communication

12575

Cdkn1a

cyclin-dependent kinase inhibitor 1A (P21)

0.779

-0.36

-2.004

cell death

235415

Cplx3

complexin 3

1.276

0.352

2.294

cell communication; synapse

12955

Cryab

crystallin, alpha B

0.744

-0.427

-2.161

cell communication

12977

Csf1

colony stimulating factor 1 (macrophage)

0.822

-0.282

-1.717

cell adhesion; cell communication; receptor binding and activity

27373

Csnk1e

casein kinase 1, epsilon

0.791

-0.338

-2.160

cell communication

13000

Csnk2a2

casein kinase 2, alpha prime polypeptide

0.801

-0.321

-1.909

cell communication

16007

Cyr61

cysteine rich protein 61

1.298

0.376

2.213

receptor binding and activity

54722

Dfna5h

deafness, autosomal dominant 5 homolog (human)

0.803

-0.316

-1.714

cell communication

330938

Dixdc1

DIX domain containing 1

0.825

-0.278

-1.770

cell communication

50768

Dlc1

deleted in liver cancer 1

0.794

-0.332

-1.894

cell communication

13430

Dnm2

dynamin 2

0.815

-0.295

-2.004

synapse

13527

Dtna

dystrobrevin alpha

1.271

0.346

2.240

synapse

13841

Epha7

Eph receptor A7

1.300

0.379

2.146

cell communication; nervous system development

14254

Flt1

FMS-like tyrosine kinase 1

0.787

-0.345

-2.064

cell communication

118446

Gje1

gap junction membrane channel protein epsilon 1

1.349

0.432

2.453

cell communication;

69367

Glrx2

glutaredoxin 2 (thioltransferase)

1.252

0.324

2.066

cell communication; cell death

14682

Gnaq

guanine nucleotide binding protein, alpha q polypeptide

0.813

-0.298

-1.776

cell communication; nervous system development;synapse

224792

Gpr116

G protein-coupled receptor 116

1.279

0.355

2.154

cell communication

14799

Gria1

glutamate receptor, ionotropic, AMPA1 (alpha 1)

0.776

-0.365

-1.975

synapse

14800

Gria2

glutamate receptor, ionotropic, AMPA2 (alpha 2)

0.740

-0.435

-1.907

cell communication; synapse

14804

Grid2

glutamate receptor, ionotropic, delta 2

0.806

-0.312

-1.793

synapse

14943

Gzmf

granzyme F

0.801

-0.321

-1.928

cell death

15258

Hipk2

homeodomain interacting protein kinase 2

0.761

-0.394

-2.283

cell communication; cell death

26557

Homer2

homer homolog 2 (Drosophila)

0.774

-0.37

-2.144

cell communication

14828

Hspa5

heat shock 70 kD protein 5 (glucose-regulated protein)

0.716

-0.481

-1.984

cell communication; cell death

56213

Htra1

HtrA serine peptidase 1

0.795

-0.331

-1.834

cell communication; receptor binding and activity

15951

Ifi204

interferon activated gene 204

1.268

0.343

2.104

cell death

16323

Inhba

inhibin beta-A

0.718

-0.477

-2.551

cell death; receptor binding and activity

241226

Itga8

integrin alpha 8

1.270

0.345

2.112

cell adhesion; cell communication

16419

Itgb5

integrin beta 5

0.832

-0.265

-1.649

cell adhesion; cell communication

16443

Itsn1

intersectin 1 (SH3 domain protein 1A)

0.826

-0.275

-1.839

cell communication

22343

Lin7c

lin-7 homolog C (C. elegans)

0.831

-0.267

-1.652

cell communication; synapse

330814

Lphn1

latrophilin 1

0.803

-0.316

-1.934

cell communication

16998

Ltbp3

latent transforming growth factor beta binding protein 3

1.291

0.368

2.202

cell communication; receptor binding and activity

17762

Mapt

microtubule-associated protein tau

0.727

-0.459

-2.312

nervous system development

17118

Marcks

myristoylated alanine rich protein kinase C substrate

0.799

-0.324

-1.815

receptor binding and activity

13728

Mark2

MAP/microtubule affinity-regulating kinase 2

0.817

-0.291

-1.922

cell communication

17193

Mbd4

methyl-CpG binding domain protein 4

0.818

-0.289

-1.753

cell death

52065

Mfhas1

malignant fibrous histiocytoma amplified sequence 1

0.759

-0.398

-2.297

cell communication

59030

Mkks

McKusick-Kaufman syndrome protein

0.749

-0.416

-2.427

cell communication

17346

Mknk1

MAP kinase-interacting serine/threonine kinase 1

1.273

0.348

2.113

cell communication

17748

Mt1

metallothionein 1

0.807

-0.31

-1.974

cell communication

17750

Mt2

metallothionein 2

0.780

-0.359

-2.141

cell communication

17909

Myo10

myosin X

0.824

-0.28

-1.751

cell communication

17918

Myo5a

myosin Va

1.309

0.389

2.105

cell communication; receptor binding and activity; synapse

17984

Ndn

necdin

1.315

0.395

2.209

cell communication; nervous system development

192167

Nlgn1

neuroligin 1

1.381

0.466

2.470

cell communication; nervous system development; synapse

18125

Nos1

nitric oxide synthase 1, neuronal

0.795

-0.331

-1.953

cell communication; receptor binding and activity; synapse

225872

Npas4

neuronal PAS domain protein 4

1.355

0.438

2.375

cell communication

18212

Ntrk2

neurotrophic tyrosine kinase, receptor, type 2

0.797

-0.327

-1.978

cell communication; synapse

18378

Omp

olfactory marker protein

0.790

-0.34

-1.907

cell communication

18389

Oprl1

opioid receptor-like 1

1.330

0.411

2.066

cell communication

18577

Pde4a

phosphodiesterase 4A, cAMP specific

0.812

-0.301

-1.903

cell communication

18578

Pde4b

phosphodiesterase 4B, cAMP specific

0.812

-0.301

-1.586

cell communication

18583

Pde7a

phosphodiesterase 7A

0.830

-0.268

-1.656

cell communication

14827

Pdia3

protein disulfide isomerase associated 3

0.812

-0.3

-1.829

cell death

74055

Plce1

phospholipase C, epsilon 1

0.807

-0.309

-1.923

cell communication

67916

Ppap2b

phosphatidic acid phosphatase type 2B

0.784

-0.351

-2.088

cell communication

170826

Ppargc1b

peroxisome proliferative activated receptor, gamma, coactivator 1 beta

0.749

-0.417

-2.262

cell communication

333654

Ppp1r13l

protein phosphatase 1, regulatory (inhibitor) subunit 13 like

0.820

-0.287

-1.903

cell death

73728

Psd

pleckstrin and Sec7 domain containing

1.291

0.368

2.130

cell communication

19246

Ptpn1

protein tyrosine phosphatase, non-receptor type 1

0.754

-0.407

-2.217

cell communication

19268

Ptprf

protein tyrosine phosphatase, receptor type, F

0.815

-0.296

-1.789

cell communication

19334

Rab22a

RAB22A, member RAS oncogene family

0.817

-0.292

-1.773

cell communication

19337

Rab33a

RAB33A, member of RAS oncogene family

1.276

0.352

2.165

cell communication

19340

Rab3d

RAB3D, member RAS oncogene family

0.792

-0.337

-1.964

cell communication

19415

Rasal1

RAS protein activator like 1 (GAP1 like)

1.312

0.392

2.203

cell communication

17252

Rdh11

retinol dehydrogenase 11

1.300

0.378

2.172

cell communication

56533

Rgs17

regulator of G-protein signaling 17

1.309

0.388

2.141

cell communication

56470

Rgs19

regulator of G-protein signaling 19

1.275

0.35

2.124

cell communication

19893

Rpgr

retinitis pigmentosa GTPase regulator

1.322

0.403

2.232

cell communication

77945

Rpgrip1

retinitis pigmentosa GTPase regulator interacting protein 1

0.784

-0.351

-1.946

cell communication

110876

Scn2a1

sodium channel, voltage-gated, type II, alpha 1

0.798

-0.325

-1.848

cell communication; cell death

58234

Shank3

SH3/ankyrin domain gene 3

0.779

-0.361

-2.189

cell communication; cell death

27401

Skp2

S-phase kinase-associated protein 2 (p45)

1.278

0.354

2.111

cell death

65962

Slc9a3r2

solute carrier family 9 (sodium/hydrogen exchanger), isoform 3 regulator 2

0.816

-0.293

-1.665

cell communication

17128

Smad4

MAD homolog 4 (Drosophila)

0.802

-0.318

-1.838

cell communication

20411

Sorbs1

sorbin and SH3 domain containing 1

0.779

-0.361

-1.938

cell adhesion; cell communication

20692

Sparc

secreted acidic cysteine rich glycoprotein

0.756

-0.403

-2.405

cell communication

114715

Spred1

sprouty protein with EVH-1 domain 1, related sequence

0.796

-0.329

-1.928

cell communication

114716

Spred2

sprouty-related, EVH1 domain containing 2

0.776

-0.365

-1.933

cell communication

14270

Srgap2

SLIT-ROBO Rho GTPase activating protein 2

0.825

-0.278

-1.778

cell communication

20848

Stat3

signal transducer and activator of transcription 3

0.808

-0.308

-1.710

cell communication

20913

Stxbp4

syntaxin binding protein 4

0.786

-0.347

-2.069

cell communication

240725

Sulf1

sulfatase 1

0.833

-0.264

-1.811

cell death

104015

Synj1

synaptojanin 1

1.366

0.45

2.207

cell communication; synapse

24071

Synj2bp

synaptojanin 2 binding protein

0.752

-0.411

-2.093

cell communication

21415

Tcf3

transcription factor 3

0.799

-0.323

-1.978

cell communication

21416

Tcf7l2

transcription factor 7-like 2, T-cell specific, HMG-box

1.352

0.435

2.231

cell communication

110595

Timp4

tissue inhibitor of metalloproteinase 4

0.797

-0.328

-1.646

cell communication; synapse

22031

Traf3

Tnf receptor-associated factor 3

0.812

-0.3

-1.800

cell communication; cell death

94090

Trim9

tripartite motif protein 9

0.759

-0.397

-1.905

cell communication; synapse

22421

Wnt7a

wingless-related MMTV integration site 7A

0.827

-0.274

-1.758

cell communication; nervous system development; synapse

78889

Wsb1

WD repeat and SOCS box-containing 1

1.288

0.365

2.069

cell communication

22627

Ywhae

tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, epsilon polypeptide

1.319

0.399

2.098

cell communication

235320

Zbtb16

zinc finger and BTB domain containing 16

0.776

-0.366

-1.759

cell death

Table 7

Significantly regulated genes in double-transgenic dnADAM10/APP[V717I] mice in relation to mono-transgenic APP[V717I] mice

Gene ID

Gene symbol

Description

Fold change

log ratio

d-value

Functional groups

268860

Abat

4-aminobutyrate aminotransferase

1.503

0.588

3.791

cell communication; synapse

67269

Agtpbp1

ATP/GTP binding protein 1

1.397

0.482

3.311

cell communication; synapse

226548

Aph1a

anterior pharynx defective 1a homolog (C. elegans)

0.724

-0.466

-3.127

cell communication

11938

Atp2a2

ATPase, Ca++ transporting, cardiac muscle, slow twitch 2

1.456

0.542

3.900

cell communication

140494

Atp6v0a4

ATPase, H+ transporting, lysosomal V0 subunit A4

0.762

-0.392

-2.972

cell communication

12122

Bid

BH3 interacting domain death agonist

1.381

0.466

3.765

cell death

12293

Cacna2d1

calcium channel, voltage-dependent, alpha2/delta subunit 1

1.460

0.546

4.086

cell communication

20303

Ccl4

chemokine (C-C motif) ligand 4

0.755

-0.405

-2.995

receptor binding and activity

12772

Ccr2

chemokine (C-C motif) receptor 2

0.648

-0.625

-3.824

cell communication

12955

Cryab

crystallin, alpha B

0.711

-0.492

-3.095

cell communication

12977

Csf1

colony stimulating factor 1 (macrophage)

0.767

-0.383

-2.920

cell adhesion; cell communication; receptor binding and activity

56066

Cxcl11

chemokine (C-X-C motif) ligand 11

0.760

-0.395

-2.953

receptor binding and activity

20315

Cxcl12

chemokine (C-X-C motif) ligand 12

1.373

0.457

3.359

receptor binding and activity

224997

Dlgap1

discs, large (Drosophila) homolog-associated protein 1

1.417

0.503

3.720

cell communication; synapse

13527

Dtna

dystrobrevin alpha

1.338

0.42

3.294

synapse

23882

Gadd45g

growth arrest and DNA-damage-inducible 45 gamma

1.371

0.455

3.534

cell death

14943

Gzmf

granzyme F

0.745

-0.424

-3.031

cell death

215114

Hip1

huntingtin interacting protein 1

0.772

-0.373

-2.971

cell death

15257

Hipk1

homeodomain interacting protein kinase 1

0.726

-0.461

-3.122

cell death

15452

Hprt1

hypoxanthine guanine phosphoribosyl transferase 1

1.375

0.459

3.326

cell communication; cell death; synapse

215257

Il1f9

interleukin 1 family, member 9

0.706

-0.503

-3.808

receptor binding and activity

16323

Inhba

inhibin beta-A

0.744

-0.426

-2.892

cell death; receptor binding and activity

16325

Inhbc

inhibin beta-C

0.715

-0.483

-3.508

receptor binding and activity

16179

Irak1

interleukin-1 receptor-associated kinase 1

1.431

0.517

3.661

receptor binding and activity

80782

Klrb1d

killer cell lectin-like receptor subfamily B member 1D

0.735

-0.444

-3.340

cell death

16818

Lck

lymphocyte protein tyrosine kinase

0.698

-0.519

-3.204

cell communication; cell death

17248

Mdm4

transformed mouse 3T3 cell double minute 4

1.377

0.462

3.303

cell death

59030

Mkks

McKusick-Kaufman syndrome protein

0.723

-0.468

-3.503

cell communication

17910

Myo15

myosin XV

0.753

-0.41

-2.883

cell communication

18125

Nos1

nitric oxide synthase 1, neuronal

0.741

-0.432

-3.040

cell communication; receptor binding and activity; synapse

21907

Nr2e1

nuclear receptor subfamily 2, group E, member 1

0.702

-0.511

-3.426

cell communication; cell death

57270

Olfr1508

olfactory receptor 1508

0.735

-0.444

-3.162

cell communication

18378

Omp

olfactory marker protein

0.756

-0.403

-2.860

cell communication

170677

Pcdh21

protocadherin 21

0.614

-0.703

-3.902

cell communication

14827

Pdia3

protein disulfide isomerase associated 3

0.745

-0.424

-2.866

cell death

18821

Pln

phospholamban

0.741

-0.432

-3.181

cell communication

333654

Ppp1r13l

protein phosphatase 1, regulatory (inhibitor) subunit 13 like

0.733

-0.449

-3.361

cell death

54189

Rabep1

rabaptin, RAB GTPase binding effector protein 1

1.377

0.462

3.307

cell death; receptor binding and activity

17252

Rdh11

retinol dehydrogenase 11

1.374

0.458

3.317

cell communication

212541

Rho

rhodopsin

0.762

-0.393

-3.078

cell communication

19877

Rock1

Rho-associated coiled-coil containing protein kinase 1

1.402

0.487

3.841

cell death

19893

Rpgr

retinitis pigmentosa GTPase regulator

1.361

0.445

3.332

cell communication

110876

Scn2a1

sodium channel, voltage-gated, type II, alpha 1

1.393

0.478

3.500

cell communication; cell death

58234

Shank3

SH3/ankyrin domain gene 3

0.769

-0.379

-2.946

cell communication; cell death

22293

Slc45a2

solute carrier family 45, member 2

0.731

-0.453

-3.211

cell communication

20682

Sox9

SRY-box containing gene 9

0.754

-0.408

-3.089

cell death

20977

Syp

synaptophysin

1.448

0.534

3.608

cell communication; synapse

20979

Syt1

synaptotagmin I

1.397

0.482

3.587

cell communication; synapse

21823

Th

tyrosine hydroxylase

0.761

-0.394

-2.993

cell communication; synapse

94090

Trim9

tripartite motif protein 9

0.716

-0.481

-2.963

cell communication; synapse

59025

Usp14

ubiquitin specific peptidase 14

1.383

0.468

3.342

cell communication; synapse

16963

Xcl1

chemokine (C motif) ligand 1

0.749

-0.416

-3.003

receptor binding and activity

The highest number of regulated genes in ADAM10 mono-transgenic mice (Tab. 4) belonged to the category of cell communication (53 genes), followed by the categories of synaptic junction and transmission (16 genes), and of nervous system development (15 genes). In dnADAM10 mice, fewer genes were found especially in the category of cell communication (15 genes).

In mono-transgenic mice, genes in the functional groups of inflammation or cell death were not over-represented (z-score < 1.96). In contrast, the category of cell death was over-represented in both double-transgenic mouse lines (Tab. 6 and 7), probably due to APP[V717I] overexpression.

The major difference in the two double-transgenic lines was the 3-fold higher number of regulated genes in the category of cell communication in the ADAM10/APP[V717I] double-transgenic line (96 genes), as compared to dnADAM10/APP[V717I] mice.

The results show that overexpression of proteolytically active ADAM10 generally influences cellular communication in mice, independently of their genetic background. One example for a regulated gene of this category is the calcium/calmodulin-dependent protein kinase II alpha (Camk2α), which is upregulated in mono-transgenic ADAM10 mice (Tab. 4) and downregulated in dnADAM10 mice (Tab. 5). Other genes of this category are the LDL receptor-related protein (Lrp1, Tab. 4, Additional file 1, Table S1), neuroligin (Nlgn1, Tab. 4, 6) and the very low density lipoprotein receptor (Vldlr, Additional file 1, Table S3).

ADAM10 overexpression has been shown to increase cortical synaptogenesis as revealed by immunohistochemistry [14]. Accordingly, here we confirmed these results on the mRNA level for two neurotransmitter systems: the glutamate receptor Gria3 and the glutamic acid decarboxylase 2 (Gad2) as well as the GABA-A receptor subunit alpha 4 (Gabra4). These are examples of up-regulated genes within the category of synaptic junction and transmission (Tab. 4).

Because ADAM10 has proteolytical activity, we were also interested in gene expression of putative ADAM10 substrates like APP and Egfr (Tab. 8). Their expressions were not regulated in mono-transgenic mice, and therefore they are not listed in tables 4, 5, 6, 7 and tables S1-S4.
Table 8

Substrates of ADAM10 [43] which are not regulated in mono-transgenic mice within the parameters given in the Methods section

Substrate groups

Symbol name of Mouse Gene

CNS substrates of ADAM10

App, Aplp2, Prnp, Efna2, L1cam, Cdh2, Pcdhg, Dll1, Notch1

Substrates of ADAM10 in inflammation

Cx3cl1, Cxcl16, Cdh5, F11r (JAM-A), Il6r, Fasl, Tnfrsf8 (CD30), Cd44

Growth factors and receptors cleaved by ADAM10

Egfr, Egf, Btc, Erbb2

Notch-1 expression was not changed in mice aged 5 months and its target gene Hes5 was only slightly affected in ADAM10 mice (Tab. 4). However, it has been reported that the ADAM10 knock out leads to severely affected Notch signaling and embryonic lethality at day 9.5 [11]. As in our transgenic animals ADAM10 was under control of the postnatal active neuron-specific mouse Thy 1-promoter, ADAM10 has no effect during embryogenesis. To examine whether the lack of influence of ADAM10 on the Notch pathway in our transgenic mice is due to the relative late stage (5 months) of investigation, we analyzed the expression of the Notch-1 target gene Hes5 in transgenic mice aged 15 days (Fig. 4): about 40% induction was observed in the ADAM10 overexpressing mice and a reduction of about 50% in the dnADAM10 transgenic mice.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig4_HTML.jpg
Figure 4

Hes5 mRNA levels in 15 days old ADAM10 transgenic mice. Brains of 15 days old FVB/N (Wt), ADAM10 (AD) or ADAM10 dominant negative mutant (dn) overexpressing mice were analyzed for the amount of the Notch-1 target gene Hes5 mRNA. Quantification was performed by real-time RT-PCR. Values represent means ± SEM of four mice per group normalized to GAPDH mRNA (one way ANOVA, Dunnett's Multiple Comparison Test; p < 0.05, *).

In addition, we found that overexpression of ADAM10 and dnADAM10 did not affect expression of either endogenous Adam10 or of other putative α-secretases like Adam9, Adam17 and Bace2 in adult mice. In general, the observed alteration of gene expression was low in all analyzed mouse lines (see the fold changes in Tab. 4, 5, 6, 7).

Alzheimer disease-related genes regulated by ADAM10

The GeneCards database (Weizmann Institute of Science, Version 2.36), which contains 934 genes connected with AD (gene list see Additional file 1, Tab. S7), was used for identification of AD-related genes regulated by ADAM10.

In ADAM10 mice, 25 AD genes (7% of 355 genes) were differently regulated, and in dnADAM10 mice 13 AD genes (9% of 143 genes) (Fig. 5) were altered including genes involved in cholesterol and lipid homeostasis, like Lrp1, Vldlr, and fatty acid-binding protein Fabp7. Other regulated genes code for inflammation-associated members of the S100 protein family (S100a8 and S100a9).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig5_HTML.jpg
Figure 5

Alzheimer disease genes in mono- and double-transgenic mice. Differentially expressed genes of ADAM10 versus FVB/N with FDR 0.5 (355 genes), of dnADAM10 versus FVB/N with FDR 0.5 (143 genes), of ADAM10/APP[V717I] versus APP[V717I] with FDR 0.0 (592 genes) and of dnADAM10/APP[V717I] versus APP[V717I] with FDR 0.0, restricted to 300 up- and 300 downregulated genes (600 genes), were compared to AD genes (934 genes) from GeneCards (Weizmann Institute of Science, Version 2.36). In ADAM10 versus FVB/N 25 AD genes (7% of 355 genes), in dnADAM10 versus FVB/N 13 AD genes (9% of 143 genes), in ADAM10/APP[V717I]versus APP[V717I] 43 AD genes (7% of 592 genes) and in dnADAM10/APP[V717I] versus APP[V717I] 30 AD genes (5% of 600 genes) were found.

In ADAM10/APP[V717I] mice, 43 AD genes (7% of 592 genes), and in dnADAM10/APP[V717I] mice, 30 AD genes (5% of 600 genes) were altered in expression (Fig. 5). The relatively small number of ADAM10-regulated AD genes in double-transgenic mice probably reflects brain dissection at the age of five months, before plaque formation begins. In all transgenic lines, we did not detect differences in the expression of presenilins 1 and 2. Bace1 was slightly upregulated (25%) in dnADAM10/APP[V717I] mice. The Aβ-degrading enzymes neprilysin (Mme) and insulin-degrading enzyme (Ide) were also not regulated in mono-transgenic mice. Solely, in ADAM10/APP[V717I] mice, Ide was slightly down-regulated (Additional file 1, Table S3).

In order to examine an influence of sex, a separate ChipInspector analysis restricted to the 600 most up- and downregulated genes was performed with samples from both female and male double-transgenic mice (Tab. 9, 10). The gene lists of female and male double-transgenic mice were then compared to the GeneCards AD gene list. The percentages of altered AD-related genes in female double-transgenic ADAM10/APP[V717I] and dnADAM10/APP[V717I]female mice are similar to the numbers found in male ADAM10/APP[V717I]and dnADAM10/APP[V717I] mice (Fig. 6). Thus, sexual dimorphism does not cause severe differences in ADAM10-dependent expression of AD-related genes. One exception was the insulin-like growth factor (Igf1), which was downregulated in female dnADAM10/APP[V717I] mice (0.65; FDR = 1.3%), but not in the corresponding male animals (1.17; FDR = 1.8).
Table 9

Numbers of significantly regulated genes in male double-transgenic mice restricted by the given d-values.

Mouse Genome 430 2.0 Array (Affymetrix)

45 000 probe sets, 39 000 transcripts, 34 000 characterized

male ADAM10/APP[V717I] versus APP[V717I]

600 genes, FDR = 1.3%

male dnADAM10/APP[V717I] versus APP[V717I]

600 genes, FDR = 1.3%

414 upregulated

(d-value > 1.18)

186 downregulated

(d-value < -0.71)

320 upregulated

(d-value > 1.29)

280 downregulated

(d-value < -0.75)

Table 10

Numbers of significantly regulated genes in female double-transgenic mice restricted by the given d-values

Mouse Genome 430 2.0 Array (Affymetrix)

45 000 probe sets, 39 000 transcripts, 34 000 characterized

female ADAM10/APP[V717I] versus APP[V717I]

600 genes, FDR = 1.3%

female dnADAM10/APP[V717I] versus APP[V717I]

600 genes, FDR = 1.3%

184 upregulated

(d-value > 0.61)

416 downregulated

(d-value < -0.66)

300 upregulated

(d-value > 1.44)

300 downregulated

(d-value < -1.38)

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig6_HTML.jpg
Figure 6

Alzheimer disease genes in female and male double-transgenic mice. Differentially expressed genes of female and male ADAM10/APP[V717I] versus APP[V717I] and of dnADAM10/APP[V717I]versus APP[V717I] with FDR 1.3, restricted to the 600 best up- and downregulated genes were analyzed for AD genes (934 genes) from GeneCards (Weizmann Institute of Science, Version 2.36). In female ADAM10/APP[V717I] versus APP[V717I] mice 49 AD genes (8% of 600 genes) and in female dnADAM10/APP[V717I] versus APP[V717I] animals 35 AD genes (6% of 600 genes) were found to be affected. In male ADAM10/APP[V717I] versus APP[V717I] mice 42 AD genes (7% of 600 genes) and in male dnADAM10/APP[V717I] versus APP[V717I] mice 31 AD genes (5% of 600 genes) were found to be affected. The corresponding d-values are listed separately for male (Tab. 9) and female mice (Tab. 10).

Genes regulated through APP[V717I] overexpression

To determine the effect of APP[V717I] overexpression on gene regulation in transgenic mice, we compared APP[V717I] mice with FVB/N mice, ADAM10/APP[V717I] mice with ADAM10 mice, and dnADAM10/APP[V717I] mice with dnADAM10 mice. After background adjustment and normalization with the GCRMA procedure, a Venn diagram of genes regulated in the transgenic mice was generated (Fig. 7). The overlap of the three groups represents 617 genes regulated by APP[V717I] overexpression, independent of the strain background. This high number of genes altered by APP[V717I] expression demonstrates the strong influence of human APP[V717I] overexpression in the AD mouse model used.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig7_HTML.jpg
Figure 7

Venn diagram of regulated genes in investigated mouse lines after CARMA-analysis (BH<0.005). Venn diagram of APP[V717I]versus FVB/N (A), ADAM10/APP[V717I] versus ADAM10 (B) und dnADAM10/APP[V717I] versus dnADAM10 (C), generated by a custom-written Perl-script showing the effect of APP[V717I] overexpression in double-transgenic mice. The numbers in the spaces of overlapping circles represent the number of transcripts that were affected in all mouse groups. The numbers in the outer portion of each circle represent the number of transcripts that were exclusively affected in two mouse groups.

AD-related genes that were regulated in double-transgenic, but not in mono-transgenic mice include microtubule-associated protein tau (Mapt) (Tab. 6; Tab. S3) and the ionotropic glutamate receptors AMPA 1 (Gria 1) and AMPA 2 (Gria 2) (Tab. 6; Tab. S3).

Confirmation of microarray data

For validation of the results obtained by microarray analysis, real-time RT-PCR was applied on the original RNA samples (Fig. 8 and 9). Changes in gene expression levels of selected transcripts were normalized to the gene expression of GAPDH, which was not regulated in our transgenic mouse strains.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig8_HTML.jpg
Figure 8

Analyses of gene expression of selected candidate genes by real-time RT-PCR in mono-transgenic mice. Expression levels of individual genes in mono-transgenic mice in relation to gene expression in FVB/N wild-type mice. Shown are the results from RT-PCR and microarray analyses. Values presented: mean of fold changes ± SD of three animals. A: ADAM10; B: S100a8; C: Nlgn1; D: S100a9; E: Fabp7. Statistical significance was determined by using ANOVA analysis, followed by Dunnett's post hoc comparison (*), p ≤ 0.05; (**), p ≤ 0.001; (***), p ≤ 0.001.

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig9_HTML.jpg
Figure 9

Analyses of gene expression of selected candidate genes by real-time RT-PCR in double-transgenic mice. Expression levels of individual genes in double-transgenic mice in relation to gene expression in APP[V717I] mono-transgenic mice. Shown are the results from RT-PCR and microarray analyses. Values presented: mean of fold changes ± SD of 4–6 animals. A: ADAM10; B: Vldlr; C: Gria1; D: Gria2; E: Mapt; F: Nlgn1. Statistical significance was determined by using ANOVA analysis, followed by Dunnett's post hoc comparison (*), p ≤ 0.05; (**), p ≤ 0.001; (***), p ≤ 0.001.

In the microarray analyses, the calcium-binding proteins (S100a8 and S100a9) were found to be downregulated in ADAM10 and dnADAM10 mice. Both genes are associated with various inflammatory processes including Alzheimer's disease [25]. By using real-time RT-PCR, significant downregulation of S100a8 and S100a9 was confirmed (Fig. 8B and 9D). Additionally, quantification of dimers of S100a8 and a9 (calprotectin) by ELISA revealed a slight reduction in both transgenic mouse lines (Fig. 10C) which is in accordance with the findings for mRNA levels. The decrease of about 10 to 15% of calprotectin as compared to wild-type mice was not statistically significant which might be due to ELISA-specific detection of heterodimers. We cannot exclude that changes concerning both monomeric proteins might be more substantial, but a detection of the monomeric form of S100a9 by Western blotting failed as a consequence of its low expression level.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-10-66/MediaObjects/12864_2008_Article_1950_Fig10_HTML.jpg
Figure 10

Effect of Adam10 on Fabp7 and S100a8/a9 proteins in mouse brain. A) Fabp7 protein expression was analyzed in fractions of soluble brain proteins of mono-transgenic mice by Western blotting (Wt: wild-type, AD: ADAM10, dn: dominant negative ADAM10). As a control for antibody specificity, a lysate of HEK293 cells overexpressing V5-tagged murine Fabp7 (19 kDa; +) was used. B) Quantification of Fabp7 was performed with at least 5 animals per group. Values represent mean ± SEM, and values obtained for wild-type animals (Wt) were set to 100% (one way ANOVA, Bonferroni post-test; ns, not significant; p < 0.001, ***). C) Expression of dimeric S100a8/a9 (calprotectin) was quantified by ELISA in mouse brain extracts. Measured absorptions at 405 nm were normalized to wet tissue weight (mean ± SEM; n = 4).

Fatty acid-binding protein 7 (Fabp7), which is elevated in Down syndrome fetal brains [26], was found to be upregulated in dnADAM10 mice by microarray analysis. A significantly increased Fabp7 expression was confirmed in dnADAM10 mice by real-time RT-PCR. As observed by real-time RT-PCR, expression of Fabp7 was slightly reduced in ADAM10 mice, but this effect did not reach a significant level (Fig. 8E). Fabp7 protein expression was analyzed in the soluble protein fraction from brains of mono-transgenic mice by Western blotting. While ADAM10 had no significant effect on Fabp7 expression, the dominant-negative form dnADAM10 increased the amount of the Fabp7 protein (Fig. 10A/B), which is in accordance with the results obtained by microarray and PCR analysis.

Neuroligin 1, a postsynaptic cell-adhesion molecule of excitatory synapses, plays a role in neuronal differentiation and axogenesis [27]. In microarray analyses, neuroligin 1 gene expression was induced in ADAM10 mice. This tendency, although without reaching significance, was also confirmed in real-time RT-PCR (Fig. 8C).

Other proteins identified by gene profiling and associated with Alzheimer disease are the low density lipoprotein receptor-related protein 1 (Lrp1) [28], the very low density lipoprotein receptor (Vldlr) [29], the microtubule-associated protein tau (Mapt) [30] and the ionotropic glutamate receptors AMPA1 and AMPA2 (Gria1 and Gria2) [31]. Downregulation of Lrp1 by ADAM10, as observed in the chip analyses, was not confirmed by real-time RT-PCR (results not shown). For Vldlr, we found by real-time RT-PCR a significant downregulation in ADAM10/APP[V717I] mice, but its upregulation in dnADAM10/APP[V717I] mice, as detected with the microarray, could not be confirmed (Fig. 9B).

By real-time RT-PCR, the microtubule-associated protein tau was shown to be significantly downregulated in both double-transgenic mouse lines (Fig. 9E). Also in the case of the ionotropic glutamate receptors AMPA1 (Gria1) and AMPA2 (Gria 2), real-time RT-PCR confirmed the results of the microarray analyses: both genes are downregulated in ADAM10/APP[V717I] mice (Fig. 9C and 9D).

Discussion

Increasing the α-secretase cleavage of APP represents a plausible strategy for the treatment of Alzheimer disease, because via this route it is possible to decrease the concentration of neurotoxic Aβ peptides and to increase the amount of neuroprotective APPsα simultaneously.

The aim of this study was to investigate the influence of increased amounts of ADAM10 proteins on gene expression in the mouse CNS. To this end, we analyzed transgenic mice either overexpressing catalytically active ADAM10, or a dominant-negative mutant of ADAM10 (dnADAM10) which is able to inhibit endogenous mouse enzymes with α-secretase activity [10, 12]. An additional reason for investigation of dnADAM10 mice is determined by the multi-domain structure of ADAMs because specific biological functions have been assigned to protein domains outside the catalytic centre of ADAMs [15].

In ADAM10 mice, more genes were regulated than in dnADAM10 animals; this indicates that, due to the many substrates of ADAM10, an increase in their cleavage products might change the expression of genes involved in cell communication and synaptic transmission. No change, however, was detected in the expression of the substrates as a feedback reaction.

In all transgenic mice the endogenous ADAM10 level was not influenced through overexpression of ADAM10 or its inactive variant as revealed by real-time RT-PCR. Also the other ADAM family members Adam9 and Adam17/TACE were not regulated differentially in the investigated transgenic mice, thus indicating that a reduced α-secretase activity as observed in dnADAM10 mice [12] was not compensated by the induction of gene expression of other potential α-secretases.

Since ADAM10 has been implicated in Notch signaling [11, 32], we investigated this pathway. On the RNA level, we found no regulation of Notch-1 in mono- and double-transgenic mice at the age of 5 months: expression of the Notch target gene Hes5 was only slightly changed in mono-transgenic ADAM10 mice. This is in accordance with earlier real-time RT-PCR experiments, where no significant difference was found in Hes5 transcription levels between adult mice overexpressing ADAM10 and non-transgenic mice [12]. This lack of influence on Notch signaling is probably due to the late stage of analysis, since we found small but significant effects of ADAM10 on Hes5 mRNA levels in transgenic mice aged 15 days.

ADAM10 has been reported to mediate cadherin shedding, β-catenin translocation and expression of β-catenin target genes [33, 34]. In double-transgenic dnADAM10/APP[V717I] mice various cadherins (Cdh8, Cdh10 and Cdh13), β-catenin (Ctnnb1), several Wnts (Wnt4, Wnt7a and Wnt9a) and Jun kinase (Jun) were upregulated (about 30%). The upregulation of these genes might represent a compensatory mechanism to by-pass a reduced catalytic activity of ADAM10 and β-catenin signaling. In mice overexpressing active ADAM10, no significant changes of β-catenin target genes, for example c-myc and cyclin D1, were found.

Also for other ADAM10 substrates like L1cam, proteins involved in inflammation like Fasl, and for growth factor receptors like Egfr (see also table 8), we could not demonstrate any alteration.

Most genes in ADAM10 and ADAM10/APP[V717I] mice were found to be altered in the pathway of cell communication, followed by genes in categories of nervous system development and synaptic junction and transmission (Tab. 4, 5, 6, 7). One example for a regulated gene in the category of cell communication and synaptic function is the calcium/calmodulin-dependent protein kinase II alpha (Camk2α), one of the most abundant kinases in the brain, which is involved in long term potentiation. Camk2α was upregulated in ADAM10 mice, and downregulated in dnADAM10. Another gene of cell communication and synaptic function is neuroligin (Nlgn1), a brain-specific acetylcholinesterase homologous protein, which was upregulated in ADAM10/APP[V717I] mice (Fig. 9F). This component of excitatory synapses plays a role in neuronal differentiation and axogenesis [27]. An increase in cortical synaptogenesis as found by Bell et al. in ADAM10 mice [14], was confirmed through upregulation of the glutamate receptor Gria3 and the glutamic acid decarboxylase 2 (Gad2) as well as the GABA-A receptor subunit alpha 4 (Gabra4).

Downregulation of the ionotropic glutamate receptors AMPA1 (Gria1) and AMPA2 (Gria2) as observed in our microarray study was confirmed by real-time RT-PCR: reduced mRNA levels of Gria1 and Gria2 were detected in ADAM10/APP[V717I] mice. The downregulation of these two genes possibly depends on overexpression of APP[V717I] as described before [35, 36].

The number of regulated genes involved in the development of AD was relatively small in the brains of double-transgenic ADAM10/APP[V717I] and dnADAM10/APP[V717I] mice, and almost equivalent to mono-transgenic ADAM10 or dnADAM10 mice (Fig. 5). We did not detect differences in most genes directly involved in APP processing; but reduction of α-secretase activity induced a slight upregulation of Bace1 in dnADAM10/APP[V717I] mice.

Comparative GCRMA analysis demonstrated the strong influence of human APP[V717I] overexpression on gene expression in double-transgenic mice. Tau (Mapt) was directly downregulated through APP[V717I] overexpression in ADAM10/APP[V717I] versus ADAM10 mice. Altered expression of AD-related genes was independent of sex, with one exception: insulin-like growth factor 1 (Igf-1), which has been implicated in Alzheimer pathology [37, 38], was downregulated in double-transgenic female dnADAM10/APP[V717I] mice.

By microarray analysis, we observed in mono-transgenic mice a downregulation of members of the S100 protein family, small calcium-binding proteins responsible for a wide range of intra- and extracellular functions [39]. S100a8 and S100a9 were expressed to a lower extent in ADAM10 and dnADAM10 mice. PCR analysis and ELISA confirmed this effect (Fig. 8B and 8D, Figure 10C). S100a8 and S100a9 form the dimer calprotectin which is a marker for inflammation [40]. Immunohistochemical analysis recently showed S100A9 in association with the neuropathological hallmarks of sporadic and familiar AD: it was found in senile plaques, in activated glia cells and in neurons with neurofibrillary tangle morphology [25]. The downregulation of S100a9 by both ADAM10 and dnADAM10 overexpression is probably mediated by their common domains (the disintegrin and cystein-rich domain as well as the C-terminus).

A member of the fatty acid-binding proteins (Fabp7) was regulated by ADAM10 in mono-transgenic mice. Fabp7, also named brain lipid-binding protein (B-Fabp), is localized in the cytoplasm and in the nucleus, and is involved in the uptake, storage and/or delivery of fatty acids and retinoids into the nucleus [41]. Fabp7 is mainly expressed in radial glial cells, and is necessary for proper migration of immature neurons to cortical layers. Increased amounts of Fabp7 in the brains of individuals with Down syndrome suggest that higher concentrations of Fabp7 contribute to brain abnormalities and mental retardation [26]. We observed a significant upregulation of Fabp7 mRNA and protein in dnADAM10 mice. Since in Down syndrome patients α-secretase activity significantly decreases with age [42], our results provide a connection between inhibition of α-secretase (in our study by dnADAM10) and upregulation of Fabp7.

Conclusion

This study shows that overexpression of ADAM10 or dnADAM10 in the brain of adult mice does not lead to drastic alteration of gene expression. In particular, ADAM10 or dnADAM10 overexpression does not result in an increased expression of genes coding for pro-inflammatory or pro-apoptotic proteins. On the contrary, overexpression of ADAM10 and its mutant even leads to a decreased amount of the inflammation marker calprotectin (the dimer of S100a8 and S100a9).

The relatively low number of genes affected by the ADAM10 modulation and the mild characteristic of altered expression levels might be related to the age of the mice we investigated. Since expression in the whole brain was analyzed, a higher change of gene expression may occur in single areas like the hippocampus. From other reports it is evident that manipulation of ADAM10 in embryonic or early ontogenic stages could have severe side effects but therapeutic approaches concerning Alzheimer's disease always will focus on adult patients. Our results in sum therefore provide evidence that, due to its effect on inflammation markers and on Fabp7 expression, ADAM10 might have beneficial effects in addition to those that are due to its α-secretase activity. These results further support the strategy of ADAM10 upregulation as a therapeutic approach for the treatment of AD.

Abbreviations

(AD): 

Alzheimer disease

(APP): 

amyloid precursor protein

(Aβ peptides): 

Amyloid β-peptides

(ADAM10): 

a disintegrin and metalloproteinase 10.

Declarations

Acknowledgements

We thank Dr. Michael Bonin and Sven Poths (Microarray Facility, Department of Human Genetics, Tübingen, Germany), and Dr. Florian Wagner (RZPD German Resource Center for Genome Research, Berlin, Germany) for support of the microarray analysis. We also thank Annette Roth (Institute of Biochemistry, University Mainz, Germany) for performing the real-time RT-PCR. We are grateful to Dr. Fred van Leuven (Katholieke Universiteit Leuven/Belgium) for the APP[V717I] mice. We acknowledge the financial support by the Federal Ministry of Education and Research (BMBF) in the framework of the National Genome Research Network (NGFN), Förderkennzeichen FKZ01GS0470, FKZ01GS08130, and FKZ01GS08133, the financial support by the Helmholtz Association in the framework of the Virtual Institute of Neurodegeneration and Ageing and the Helmholtz Alliance for Mental Health in an Ageing Society, and the support by DFG (German Research Foundation) in the framework of the SFB 596: Molecular Mechanisms of Neurodegeneration, subproject A12.

Authors’ Affiliations

(1)
Institute of Biochemistry, Mainz, Johannes Gutenberg-University
(2)
Helmholtz Zentrum München – German Research Center for Environmental Health, Institute for Developmental Genetics

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© Prinzen et al; licensee BioMed Central Ltd. 2009

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