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a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m
w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s
Research Report
The expression of Troponin T1 gene is induced by ketamine in adult mouse brain Xiu R. Lowe a,b,c,⁎, Xiaochen Lu b , Francesco Marchetti a,b , Andrew J. Wyrobek a,b a
Life Science, Lawrence Berkeley National Laboratory, Berkeley, CA, USA Bioscience, Lawrence Livermore National Laboratory, Livermore, CA, USA c Department of Psychiatry, Kaiser Permanente Medical Group, Inc., Hayward, CA, USA b
A R T I C LE I N FO
AB S T R A C T
Article history:
The glutamatergic system has been implicated in neuropsychiatric disorders, such as
Accepted 1 July 2007
schizophrenia, bipolar disorder and Alzheimer's disease, which also have a high prevalence
Available online 2 August 2007
of metabolic syndrome. Treatment with ketamine, a non-competitive glutamate N-methyl-
Keywords:
neuroprotection and neurotoxicity. We investigated gene expression in brain tissue of
Ketamine
adult mice treated with ketamine to characterize the expression profiles and to identify the
Troponin T1
affected metabolic pathways. Adult male mice were treated by a single intraperitoneal (i.p.)
Metabolic syndrome
injection of either s(+)ketamine (80 mg/kg) or distilled water (as the control). Fifty genes were
Mouse brain
differentially expressed in ketamine-treated mouse brains compared with control mice
D-aspartic
acid (NMDA) receptor antagonist, is known to have paradoxical effects of
using oligonucleotide microarray analysis, and the expression of Troponin T1 (Tnnt1) gene was consistently elevated (2- to 4-fold) (p b 0.001). Ketamine-induced Tnnt1 expression was confirmed and characterized using RNA in situ hybridization techniques in paraffin embedded brain tissue sections. Tnnt1 expression was induced in the granule layer of the hippocampus, amygdala, hypothalamus, Purkinje cells of cerebellum (p b 0.0001), and cerebral cortex. Tnnt1 gene is known to interact directly with FoxO1, which is involved in multiple peripheral metabolic pathways and central energy homeostasis. Our findings suggest that the induction of Tnnt1 gene expression in adult mouse brains by ketamine may illustrate the genes involved in the metabolic syndromes observed in neuropsychiatric disorders. © 2007 Elsevier B.V. All rights reserved.
1.
Introduction
A metabolic syndrome, defined as having three or more of the following conditions, i.e. central obesity, dyslipidemia, hypertension and hyperglycemia, is associated with adverse health outcomes including cardiovascular disease and diabetes (Citrome, 2005; Grundy, 2004). It is well established that a
higher prevalence of metabolic syndrome is observed in psychiatric populations (Casey, 2005; Ford et al., 2002). Drugnaïve and drug-free schizophrenia patients were found to have significantly increased visceral fat and impaired fasting glucose tolerance (Holt et al., 2004; Ryan et al., 2003; Thakore et al., 2002). The prevalence of the metabolic syndrome in patients with bipolar disorder is also alarmingly high (Fagiolini
⁎ Corresponding author. Life Science Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA. Fax: +1 510 675 4648. E-mail address:
[email protected] (X.R. Lowe). 0006-8993/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2007.07.039
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et al., 2005). In addition, Razay et al. (2007) reported that Alzheimer's disease is associated with metabolic syndrome. However, the pathophysiology of the increased risks of metabolic syndrome in neuropsychiatric patients is not yet fully understood (Casey, 2005). The highly complex glutamatergic system has been associated with a variety of psychiatric disorders, e.g., schizophrenia and bipolar disorder (Manji et al., 2003; Blackwood et al., 2007) and in neurodegenerative disorders such as Alzheimer's disease (Lipton, 2004). The NMDA-type glutamate receptor normally opens in response to the binding of the neurotransmitter glutamate, the primary excitatory neurotransmitter in the brain. Clinical treatment with NMDA receptor antagonists such as ketamine, phencyclidine (PCP) and dizocilpine (MK801), induce a broad range of cognitive adverse effects including deficits in working memory, verbal fluency, vigilance tasks, and symptoms that resemble various aspects of schizophrenia (dose-dependence). These NMDA receptor antagonists have also been shown to interfere with sensory information processing (Krystal et al., 1994). Yet, NMDA antagonists can both generate and prevent neurotoxicity associated with excitotoxicity (Sharp et al., 1995). Memantine, an NMDA-receptor antagonist, has been approved by the U.S. Food and Drug Administration (FDA) for the treatment of Alzheimer's disease (Lipton, 2004). Zarate et al. (2006) reported robust and rapid antidepressant effects following a single intravenous dose of ketamine in human. The paradoxical characteristics of the NMDA receptor blocking drugs, such as ketamine, makes these drugs valuable in the study of the pathophysiology of neuropsychiatric illness and medical comorbidity (Imre et al., 2006). Microarray expression profiling (Yin et al., 2003; Saba and Booth, 2006) and RNA in situ hybridization techniques (Kim et al., 2000; Luo et al., 2006) provide a means of evaluating the relative expression of thousands of genes in parallel and characterizing the RNA expression patterns at regional/ cellular levels, respectively. We employed large-scale random oligonucleotide microarrays and RNA in situ hybridization to characterize the transcript profiles of the brain tissues of adult male mice after a single i.p. injection of ketamine (80 mg/kg), a dose has been shown to produce microglial activation, which is a marker of neural injury (Nakki et al., 1996; Thomas, 1992). This dose was also within the range of literature reported treatment dosing between 25 mg/kg and 120 mg/kg (Hayashi et al., 2002; Sharp et al., 1995). Our hypothesis is that the glutamatergic system, which is known to be involved with the neuropsychiatric diseases (including schizophrenia/bipolar disorder/Alzheimer's disease), may be associated with the metabolic syndrome observed in these neuropsychiatric patients. The objectives of this study were to use the mouse brain model to identify genes that (a) responded to ketamine in the brain at early time point after treatment (30 min); (b) were involved in the metabolic pathways; and (c) showed regional and cellular specific expression patterns within the treated brain. Our study identified novel molecular and cellular mechanisms employed by the brain after ketamine exposure and offers new insight into understanding the relationship between the glutamatergic system, metabolic syndrome and neuropsychiatric disease.
2.
Results
2.1.
Behavioral effect of mice treated with ketamine
After single i.p. injection of ketamine at 80 mg/kg, stereotyped behaviors were observed in all 19 adult mice treated with ketamine, including locomotor hyperactivity, sniffing behaviors, remaining in the same place in the cage with fast repetitive head and/or foreleg movement, backing up, jumping, seizures, abnormally posture and dyskinetic movement. These symptoms lasted about 10 min after the injection and no casualties were observed. As expected, the distilled watertreated mice did not exhibit abnormal movement.
2.2. Tnnt1 transcript expression was significantly increased in the brains of adult mice treated with ketamine, as detected by microarray analysis Brain tissues from the hippocampus, amygdala and hypothalamus regions, which are known to be involved in emotion, memory, cognitive functions and metabolic regulation, were combined from 5 mice to form a subgroup (Fig. 1). RNA isolated from combined brain tissues was hybridized to an Affymetrix microarray chip. Differential expression levels of 12,488 genes were assessed. As shown in Table 1, there was no significant variation of expression levels among three replicates within each treatment group, which further demonstrated the reliability and reproducibility of this technique. Fifty genes were differentially expressed at the 0.10 level of false discovery rate (FDR) (Table 1). Table 2 showed the global function of these genes using Gene Ontology (GO) biological process analysis. Among these 50 genes, 34 were involved in two networks using Ingenuity System analysis, with statistical significance (p− 33–p− 21) (Fig. 2). About half of these genes were associated with pathways related with tissue/ organ/system development (e.g. GBX2 and EGR2) or pathways related with cancer/apoptosis (e.g., PRKCD, SPP1, PTGS2 and GADD45G). About 20 genes were up-regulated after ketamine treatment, Troponin T1 (Tnnt1) gene showed consistent elevation (2- to 4fold) in the brains of treated mice when compared with those of the controls. Tnnt1 nucleotides (GenBank accession number: AV213431 and AJ131711) showed ∼ 4-fold increases for AV213431 (p b 0.001) and ∼ 2-fold increases for AJ131711 (p b 0.03). Through Ingenuity System analysis, Tnnt1 gene was found to be solely regulated by FoxO1 gene (Fig. 2), a gene involved in multiple hepatic metabolic pathways including glycolysis, lipogenic and sterol synthentic pathways (Zhang et al., 2006; Matsumoto et al., 2006), and central energy homeostasis (Kim et al., 2006a). Therefore, Tnnt1 gene was chosen for further investigation of regional and cellular expression patterns in the adult mouse brains using RNA in situ hybridization.
2.3. The expression of Tnnt1 transcript was induced by ketamine in the brain tissue section, as detected by RNA in situ hybridization Tnnt1 RNA probe labeled with biotin was hybridized to brain tissue sections prepared from ketamine-treated and control
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9
Fig. 1 – The scheme of experimental design: microarray and RNA in situ hybridization.
animals (Fig. 1). The digitally scanned images (Aperio Images) were analyzed manually without further modification or enhancement. The transcripts of Tnnt1 gene were detected within the cytoplasm of pyramidal neurons of the cerebral cortex and Purkinje cells of the cerebellum (Fig. 4). Among the control mice, all but one were found to have specific regional expression patterns for the Tnnt1 gene: i.e., expressed in the choroid plexus epithelium cells and ependymal lining of ventricles, weakly expressed in the hippocampus region (Fig. 3), and with no detectable expression in other regions (Fig. 4g). One control mouse (C4) showed high levels of Tnnt1 expression in all regions of the brain, which was confirmed by repeated hybridization (data not shown). Thus, it was considered an outlier and excluded from further analysis. Compared with controls, the expression of Tnnt1 RNA was significantly induced in the granule layer of the hippocampus, amygdala and hypothalamus regions (as expected based on microarray analysis) and other regions (Figs. 3 and 4) in all four mice treated with ketamine. The signals detected in the choroid plexus epithelium cells of ketamine-treated mice were much stronger than those of control mice (Fig. 3). Tnnt1 is a slow skeletal muscle gene, while the function of cerebellum involves coordination and control of voluntary movement (Kischel et al., 2005; Miall and Reckess, 2002). Thus, the region-specific expression pattern was further examined in the Purkinje cells of the cerebellum (Fig. 4). The Purkinje cells of the cerebellum were
manually counted for each animal (two slides per mouse) and the percentages of Tnnt1-positive cells was significantly increased in ketamine-treated mice compared with those of the control animals (p b 0.0001) (Fig. 5).
3.
Discussion
We found that ketamine treatment induced Tnnt1 expression in adult mouse brains as detected by both microarray and RNA in situ hybridization.
3.1. The expression of Tnnt1 gene was detected in the brains of control adult male mice In the current study, we detected the expression of Tnnt1 gene in choroid plexus neuroepithelium and weak expression in the granule layer of hippocampus in the brains of distilled watertreated adult male mice. De Vitry et al. (1994) reported the transient expression of myogenic proteins including Troponin T and desmin in a culture of embryonic and neonatal rat brain stem, but not in the adult brain. A database that lists current literatures of gene expression patterns in mouse brain, Allen Institute for Brain Science (Allen Brain Atlas: www.brain-map. org), also reported that the Tnnt1 gene was only expressed in the mouse embryonic brain. The discrepancy between these
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Table 1 – The profile of differentially expressed genes modulated by ketamine using microarray analysis Symbol
Prkcd Tnnt1 Cipp
Name
Protein kinase C, delta Troponin T1, skeletal, slow Channel-interacting PDZ domain protein Shox2 Short stature homeobox 2 Prkcd Protein kinase C, delta Gbx2 Gastrulation brain homeobox 2 Rgs16 Regulator of G-protein signaling 16 Tnnt1 Troponin T1, skeletal, slow Spp1 Secreted phosphoprotein 1 Rgs16 Regulator of G-protein signaling 16 Prss18 Protease, serine, 18 Aldh1a1 Aldehyde dehydrogenase family 1, subfamily A1 Nkx6-2 NK6 transcription factor-related, locus 2 (Drosophila) Nkx2-2 NK2 transcription factor-related, locus 2 (Drosophila) Nefh Neurofilament, heavy polypeptide Evi2 Ecotropic viral integration site 2 Adarb1 Adenosine deaminase, RNA-specific, B1 Mobp Myelin-associated oligodendrocytic basic protein Wnt3 Wingless-related MMTV integration site 3 Serine (or cysteine) proteinase Serpinb1a inhibitor, clade B, member 1a Sep_4 Septin 4 Nav1 Neuron navigator 1 Pde1a Phosphodiesterase 1A, calmodulin-dependent D10Jhu81e DNA segment, Chr 10, Johns Hopkins University 81 expressed NA NA Sox11 SRY-box containing gene 11 Socs3 Suppressor of cytokine signaling 3 Nfil3 Nuclear factor, interleukin 3, regulated Smarca4 SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4 Alox12b Arachidonate 12-lipoxygenase, 12R type Myh7 Myosin, heavy polypeptide 7, cardiac muscle, beta Rala v-ral simian leukemia viral oncogene homolog A (ras-related) Hspa5 Heat shock 70 kDa protein 5 (glucose-regulated protein) 2810012H18Rik RIKEN cDNA 2810012H18 gene Egr1 Early growth response 1 Ptgs2 Prostaglandin-endoperoxide synthase 2 Zfp312 Zinc finger protein 312 Nsap1-pending NS1-associated protein 1 Clk CDC-like kinase Fln29-pending FLN29 gene product Gadd45g Growth arrest and DNA-damageinducible 45 gamma 1110021E09Rik RIKEN cDNA 1110021E09 gene
Ketaminetreated a
Distilled water treated a C
A
T Accession test number
B
7.58 8.40 4.79
7.73 8.54 4.65
7.35 10.02 9.80 9.34 8.51 10.22 10.22 10.92 4.70 6.65 6.43 6.62
2.17 1.97 1.85
6.85e−04 1.35e − 03 9.79e − 06
13.79 X60304 12.06 AV213431 24.85 AF060539
5.33 9.06 5.52 8.51
5.51 9.16 5.68 8.46
5.84 8.86 5.52 8.25
6.61 10.35 6.60 9.00
1.82 1.39 0.93 0.80
5.14e − 02 3.40e − 04 3.55e − 03 4.47e − 02
6.51 15.60 10.57 6.79
U66918 AB011812 Z48800 U94828
6.83 6.81 6.64 7.37 7.46 7.77 7.02 7.15 6.94 7.52 7.93 7.78 6.39 6.46 6.48 7.14 7.09 7.15 6.64 6.87 6.86 7.33 7.42 7.63 10.27 10.25 10.23 10.71 11.00 11.04
0.77 0.71 0.68 0.67 0.67
3.54e − 02 4.39e − 02 1.35e − 03 4.36e − 02 3.54e − 02
7.62 6.90 12.28 6.97 7.36
AJ131711 X13986 AV349152 Y18723 M74570
7.69 10.35 6.51 9.14
C
P value
A
7.84 10.54 6.40 9.48
B
Fold change (log2 ratio)
7.51
7.67
7.66
8.18
8.32
8.29
0.65
5.08e − 02
6.59 L08074
6.72
6.85
6.83
7.28
7.36
7.61
0.61
5.32e − 02
6.37 U31566
9.24 8.97 9.20
9.39 9.03 9.34
9.28 8.89 9.31
9.80 9.47 9.71
9.89 9.38 9.67
9.90 9.58 9.78
0.56 0.51 0.44
4.33e − 02 7.61e − 02 4.47e − 02
7.08 M35131 5.90 M34896 6.79 AW124433
12.35 12.44 12.49
12.83
12.85
12.84
0.41
3.54e − 02
7.47 AI839662
7.12
7.02
7.05
7.49
7.43
7.39
0.38
7.28e − 02
6.01 M32502
4.51
4.50
4.50
4.83
4.82
4.89
0.35
5.08e − 02
6.60 AA762212
10.88 10.83 10.82 7.22 7.15 7.20 5.84 5.70 5.81
11.20 6.82 5.43
11.15 6.85 5.52
11.14 6.90 5.33
0.32 −0.33 −0.35
9.49e − 02 9.94e − 02 9.62e − 02
5.55 X61452 −5.37 AA968123 −5.41 U56649
9.98
9.90 10.01
9.70
9.60
9.50
−0.37
9.62e − 02
−5.43 AI852165
6.20 4.55 6.66 6.91
6.28 4.63 6.78 6.89
6.29 4.78 6.79 7.06
5.80 4.28 6.36 6.51
5.93 4.25 6.35 6.57
5.89 4.29 6.36 6.50
−0.38 −0.38 −0.39 −0.43
7.28e − 02 9.49e − 02 5.32e − 02 9.62e − 02
−6.01 −5.54 −6.44 −5.46
10.05 10.00 10.06
9.58
9.72
9.54
−0.43
9.62e − 02
−5.45 AW124186
AW125643 AW107922 AV374868 U83148
6.44
6.20
6.38
5.94
5.82
5.96
−0.44
9.62e − 02
−5.49 Y14334
8.72
8.65
8.79
8.20
8.17
8.42
−0.45
7.96e − 02
−5.82 AJ223362
5.72
5.81
5.97
5.44
5.30
5.39
−0.46
7.61e − 02
−5.91 Z48587
10.92 11.07 11.03
10.58
10.44
10.42
−0.53
3.54e − 02
−7.38 AJ002387
9.93 9.65 9.70 11.23 11.15 11.17 5.67 5.37 5.53
9.21 10.75 5.05
9.27 10.55 4.90
9.16 10.59 4.92
−0.54 −0.55 −0.57
8.47e − 02 3.54e − 02 7.96e − 02
−5.72 AI853930 −7.33 M28845 −5.81 M88242
8.81 7.47 10.05 9.41 8.44
8.61 7.43 9.86 9.58 8.48
8.90 7.33 9.75 9.76 8.35
8.25 6.93 9.39 9.03 8.02
8.20 6.89 9.13 8.88 7.88
8.16 6.70 9.42 9.02 7.53
−0.57 −0.57 −0.57 −0.61 −0.61
8.06e − 02 4.36e − 02 8.48e − 02 7.53e − 02 9.49e − 02
−5.78 −6.96 −5.68 −5.95 −5.55
8.19
8.04
7.85
7.51
7.51
7.16
−0.63
9.62e − 02
−5.51 AI837467
AW047710 AI846392 M38381 AW049897 AF055638
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Table 1 (continued) Symbol
Sap30 Fosb Cbfa2t3h
Egr2 Crym Dcn Hspa1a Bat8 a
Name
sin3-associated polypeptide FBJ osteosarcoma oncogene B Core-binding factor, runt domain, alpha subunit 2; translocated to, 3 homolog (human) Early growth response 2 Crystallin, mu Decorin Heat shock protein 1A HLA-B-associated transcript 8
Distilled water treated a
Ketaminetreated a
Fold change (log2 ratio)
P value
T Accession test number
A
B
C
A
B
C
5.60 9.54 7.13
5.85 9.27 7.23
5.95 9.58 7.40
5.13 8.84 6.76
5.05 8.67 6.49
5.32 8.82 6.35
−0.64 −0.69 −0.72
5.14e − 02 9.62e − 02 5.32e − 02
−6.51 AF075136 −5.44 X14897 −6.35 AF038029
9.11 9.00 8.94 8.75 8.67 8.43 9.67 10.93 8.85 10.28
9.13 8.97 8.62 9.76 8.76
8.45 7.97 7.47 8.56 7.08
8.20 8.27 8.02 8.57 6.74
8.41 7.93 7.40 8.44 6.63
−0.73 −0.83 −0.94 −1.59 −2.48
2.91e − 02 2.37e − 02 6.56e − 02 8.48e − 02 5.32e − 02
−7.97 −8.30 −6.14 −5.70 −6.36
M24377 AF039391 X53929 M12571 AF109906
Expression levels for each chip are shown as logarithms to the base 2 and ranged in descending order.
literatures and our findings may be due to the different techniques used in our study: (a) cardiac perfusion, which has been shown to increase the sensitivity of RNA detection, was used in both microarray and RNA in situ hybridization to preserve RNA before the tissue/cell isolation; (b) paraffin-embedded section and not the frozen section was used for RNA in situ hybridization, which may have led to better protection of the tissue/cell morphology; (c) we optimized hybridization conditions including the probe generation/pre-hybridization treatment/hybridization temperature, which may have increased the sensitivity and specificity of RNA detection in our study. Consistent with our findings in control mice, De Vitry et al. (1994) demonstrated the co-presence of the choroid plexus neuorepithelium and Tnnt+, desmin+ cells within a limited zone of the embryonic brain stem. Also, besides choroid plexus epithelium and granule cells of the hippocampus, the expression of the Tnnt1 gene was not detected in any of the other regions of the brains of adult control mice, which further illustrated the specificity of RNA detection in our study.
3.2. Ketamine-induced robust expression of Tnnt1 transcript in the brain of adult mouse It has been reported that repeated administration of a subanesthetic dose (30 mg/kg/day for 5 days) of the NMDA receptor antagonist ketamine (NRHypo) can produce an animal model of schizophrenia (Tomiya et al., 2006). Hayase et al. (2006) observed ketamine single dose-induced behavioral effecthyperlocomotion in both 30 mg/kg and 100 mg/kg groups (60 min post-treatment). Hayashi et al. (2002) reported that a single dose of ketamine at 75 mg/kg did not increase neuronal degeneration in the developing rat brain. Nakki et al. (1996) illustrated that a single dose of 40 mg/kg of ketamine was needed to induce HSP70 expression compared with that needed to produce microglial activation (80 mg/kg), at 1–5 days post-treatment. HSP70 expression serves to protect the neurons from further injury while microglial activation is a marker of neural injury (Nakki et al., 1996). Recently, Xu et al. (2007) reported the optimizing anesthetic dosage of ketamine in murine as at 100 mg/kg. Sato et al. (2005) demonstrated the timing-dependence of hypnotic effect achieved by a single dose of 200 mg/kg of ketamine. Considering the dosedependent effects of ketamine on behaviors, gene expressions
and various neurons, our experiments were performed using a single dose of 80 mg/kg at 30 min post-treatment, which allowed us to explore the early effects of the NMDA antagonist in gene expression that might be involved in metabolic syndrome. The MGU-74av2 GeneChips® used in the present study contained a large set of randomly selected genes, thus, providing a near-global view of the ketamine effect that was not prejudiced in favor of preconceived cellular functions or biochemical pathways. Our results showed that 50 genes were differentially affected in the mouse brain after ketamine treatment and 34 of these genes were represented in the two significant networks (Fig. 2). The numbers of differentially expressed genes detected in our microarray analysis were within the range of those reported in the literatures using similar commercial Affymetric mouse Gene Chips (Bonin et al., 2004; Fernandez-Medarde et al., 2007; Yin et al., 2003). The microarray analysis allowed us to discover the expression of
Table 2 – GO function analysis of differentially expressed genes Function Calcium signaling Amyotrophic lateral sclerosis signaling IL-6 signaling Huntington's disease signaling B cell receptor signaling Wnt/β-catenin signaling IL-10 signaling GM-CSF signaling Xenobiotic metabolism signaling VEGF signaling Synaptic long-term potentiation Synaptic long-term depression PI3K/AKT signaling Neuregulin signaling Insulin receptor signaling IGF-1 signaling Fc epsilon RI signaling ERK/MAPK signaling Ephrin receptor signaling Cell cycle: G1/S checkpoint regulation Axonal guidance signaling
Associated genes 6 6 5 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3
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Fig. 2 – Network pathway and functional canonical analysis via Ingenuity System. Colored: genes modulated by ketamine treatment and detected by microarray analysis; Red: up-regulated; Green: down-regulated; Solid line with arrow: direct acts on; Solid line without arrow: interacts each other; cp: canonical pathways.
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Fig. 3 – The comparisons of Tnnt1 expression in the brains of adult mice treated with the ketamine (K1, K3, K4 and K5) or distilled water (C1, C2, and C3) using RNA in situ hybridization. Magnification: 10×, top two rows; 40×, 3rd row. Neg: hybridization without Tnnt1 RNA probe. H: hippocampus; chpl: choroid plexus epithelium cells.
slow skeletal muscle Tnnt1 gene in the adult mouse brain induced by ketamine, which has not to our knowledge been previously reported. Several factors may have contributed to our detection of the ketamine effect on Tnnt1 induction in adult mouse brains in the current study. The dose of ketamine treatment of 80 mg/kg was at the upper range of doses (between 25 and 120 mg /kg), used in previous studies in rodents (Sharp et al., 1995). Gene expression analysis at 30 min post-treatment allowed early detection of transcript response in the brain after ketamine treatment. In addition, selection of the specific regions of the brain including hippocampus, amygdala and hypothalamus used in our microarray analyses may have increased the sensitivity of detection of ketamine effects on gene expression. Further studies including the effect of varied ketamine dosing (specifically with sub-anesthetic dose at 30 mg/kg), timing of response and with Troponin T1 protein analysis in the brain of rodents are needed.
3.3. The significance of Tnnt1 expression in brain induced by ketamine Troponin T, a slow skeletal muscle gene, is the tropomyosinbinding subunits of the troponin complex and interacts with tropomyosin, Troponin C (TnC), Troponin I (TnI) and F-actin. Kischel et al. (2005) identified four slow skeletal Troponin T isoforms in rat muscles; Tnnt1 is one of the high-molecularweight isoform, with higher Ca2+ affinity in modified Ca2+
activities compared with the isoforms TnT3 and TnTx. Skeletal muscle is usually a target tissue of insulin-like growth factors (IGFs) and growth hormone (Basso et al., 2004; Nakashima et al., 2006) and is involved in energy homeostasis and various metabolic pathways (Kim et al., 2006b). We have detected ketamine-induced expression of the Tnnt1 gene in the adult mouse brain at the hippocampus region, which is consistent with the expression location of FoxO1 previously reported (Hoekman et al., 2006), suggesting that FoxO1 may play a role in the regulation of the expression of the Tnnt1 in the central nervous system. Kamei et al. (2004) reported that Troponin T1 expression was down-regulated by the FoxO1 gene in the skeletal muscle in energy-deprived states. FoxO1 (FKHR) is a member of a subfamily of the forkhead type transcription factors. Previous studies showed that the FoxO1 gene influences the transcription of genes involved in metabolism, cell cycle, apoptosis and cell differentiation in peripheral tissues (Kamei et al., 2004; Zhang et al., 2006; Huang et al., 2006). Recent studies indicated that FoxO1 was strongly expressed in the adult mouse brain, specifically in the striatum and neuronal subsets of the hippocampus (dentate gyrus and ventral/posterior part of CA regions) (Hoekman et al., 2006). Gan et al. (2005) demonstrated that insulin-like growth factor-1 (IGF-1) and nerve growth factor (NGF) potently regulated FoxO1 nuclear/cytoplasm shuttling via P13K/Akt cascade in PC12 cells, a cultured neuronal cell line. Kim et al. (2006a) reported that activation of FoxO1 in the hypothalamus of normal mice increases food intake and body weight, whereas inhibition of FoxO1 decreases both, suggesting
14
B RA IN RE S EA RCH 1 17 4 (2 0 0 7 ) 7 –1 7
Fig. 4 – The comparisons of Tnnt1 expression in the brains of adult mice treated with the ketamine or distilled water (control) using RNA in situ hybridization. (a, b, e and g) control animals; (c, d, f and h) ketamine-treated mice. Top row: cerebellum (magnification: 10×, a and c; 40×, b and d); (e and f) cerebral cortex (magnification: 40×); (g and h) coronal sections (magnification: 2×); PC/arrows: Purkinje cells of cerebellum; CTX: cerebral cortex, pyramidal cells; H: hippocampus; Hy: hypothalamus; A: amygdala.
that FoxO1 plays a role in the central energy homeostasis and hunger/appetite behaviors. Weight gain and abdominal adiposity may be central to the pathophysiology of the metabolic syndrome observed among neuropsychiatric patients (Holt et al., 2004; Razay et al., 2007). It has been speculated that not all metabolic disturbances result from increased adiposity. Studies demonstrated that insulin resistance independent of adiposity may result from a direct alteration of insulin sensitivity and/or insulin secretion (Ford et al., 2002). The interaction between the Tnnt1 and FoxO1 genes is associated with the alterations in gene products in the insulin-signaling pathway and glucose transport function in the peripheral tissues, e.g., muscle and liver (Zhang et al., 2006; Kamei et al., 2004). Future studies are warrant to investigate the temporal expression of FoxO1 and Tnnt1 induced by ketamine using co-hybridization RNAs or immunochemistry techniques; to explore the roles of these genes in the metabolic pathways in the central nervous system, and to understand the molecular mechanism of the increased risks of metabolic syndrome observed in neuropsychiatric patients.
4.
Experimental procedures
4.1.
Animals and treatment
Eight- to eleven-week-old male B6C3F1 mice, were treated with 0.5 mL of either distilled water or s(+)ketamine (Sigma-Aldrich, USA) at 80 mg/kg diluted in distilled water, via intraperitoneal (i.p.) single injection. 15 mice for each treatment group were
used for microarray analysis and 4 mice for each treatment group for RNA in situ hybridization (Fig. 1). The mice were deeply anaesthetized by Aerrane (isoflurane) inhalant 30 min post-treatment. The brain tissues were fixed by cardiac perfusion with 4% paraformaldehyde. Procedures for handling mice conformed to IACUC guidelines at the Lawrence Livermore National Laboratory.
Fig. 5 – The comparison of the percentages of Purkinje cells that expressed Tnnt1 transcript between the ketamine-treated (K) and control (C) adult mice using RNA in situ hybridization (p<0.0001). The numbers on the top of each column indicated the total numbers of Purkinje cells scored.
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4.2.
Oligonucleotide microarrays
15 mice each in ketamine or distilled water-treated group were randomly divided into 3 subgroups, with 5 mice per subgroup. 2- to 3-mm-thick coronal sections were obtained from each mouse and regions corresponding to the hippocampus, amygdala and hypothalamus were isolated bilaterally using a 3-mm-diameter hole puncher (Fig. 1). For each subgroup (5 mice), the isolated brain tissues were combined. From combined brain tissues, RNA was prepared using Trizol (Life Technologies, Rockville, MD, USA) and was hybridized with an oligonucleotide microarray chip. Therefore, three microarray chips were used per treatment group. The oligonucleotide microarray procedure was performed as described by Yin et al. (2003). Briefly, RNA was reversetranscribed using Superscript II reverse transcriptase (Life Technologies) and an oligo-dT primer encoding a T7 polymerase binding site. After second-strand synthesis, the cDNA was used as a template for in vitro transcription with the Enzo BioArray HighYield Transcript Kit (Enzo Biochem, New York, NY). A total of 15 μg of the resultant complementary RNA was hybridized to Affymetrix (MGU-74 av2) GeneChips®. Samples were incubated at 42 °C for 16 h rotating at 60 rpm. After hybridization, chips were washed and developed for detection with the Affymetrix Fluidics Workstations. Signals were detected using an argon-ion laser scanner (Agilent, Palo Alto, CA) and output for pixel intensity and confidence calls for each of the genes detected on the array were generated with Affymetrix Microarray Suite 5 (MAS-5). The statistical analysis was performed as described by Yin et al. (2003). Ingenuity Systems, a database network (Ingenuity Systems, Inc., http://www.ingenuity.com) that gathers updated information on pathways' interaction, was used to investigate the genes modulated by ketamine and to identify the genes associated with the metabolic pathways.
4.3.
RNA in situ hybridization
Brain tissue sections derived from 4 mice per treatment group, in sagittal and coronal planes, were isolated, fixed overnight, and paraffin embedded. Serial sections were cut at 5 μm. An antisense riboprobe was generated as described by Kim et al. (2000). Briefly, the transcribed region of mouse Tnnt1 (GenBank AJ20131711) was amplified using PCR with a pair of forward (5′GAAGCGCATGGAGAAAGACT-3′) and reverse (3′- TGCGGTCTTTTAGTGCAATG-5′) primers. The initial PCR product was further amplified with the same forward primer and T7-tag reverse primer (3′-TAATACGACTCACTATAGGG TGCGGTCTTTTAGTGCAATG-5′). The second PCR product was purified with phenol/chloroform and washed with TE on a microson-100 (Amicon, http://www.millipore.com) and concentrated to 1 μg/μL. 1 μg of template DNA was used to generate the antisense RNA probe using in vitro transcription with T7 polymerase and biotinylated UTP (Roche, Biotin RNA labeling kit, CA). Three paraffin-embedded slides per mouse were used for hybridization concurrently for all 8 mice. One slide was hybridized without antisense Tnnt1 probe as a negative control for the hybridization procedure. Hybridizations were performed using standard procedures (DAKO, Carpinteria, CA)
15
with some modifications. Anti-biotin antibody at 1:100 dilutions was used as a primary antibody and anti-mouse Broadspectrum antibody conjugated with HRP (Zymed, San Francisco, CA) was used as a secondary antibody. AEC substrate was used for color development and hematoxylin was used for counterstaining. The timing of color developing, arbitually determined, was used for every slide that was hybridized.
4.4.
Image acquisition and analysis
Three replicate slides per mouse were analyzed, of which two were digitally scanned for data analysis (Aperio Images, http:// www.aperio.com). The scanned images without further modification or enhancement were then manually analyzed on the computer or on the print images. The Purkinje cells were manually counted on the print images. The statistical analysis for p value was performed using t-test via VassarStats (http:// faculty.vassar.edu/lowry/VassarStats.html).
Acknowledgments We thank Dr. Adam Travis (M.D., Ph.D.) for critical review of the manuscript; Ms. Sylvia Ahn for the technical assistance in RNA in situ hybridization; Dr. Thomas Schmid (Ph.D.) as the laboratory manager; and Mr. Hitech for the assistance of microarray hybridization; Dr. Sanchita Bhattacharya (Ph.D.) for Ingenuity network pathway analysis; Dr. Nelson (Ph.D.) for statistical analysis of microarray data; Dr. Lisa Stabbs' staff for the technical equipment and consultant of RNA in situ hybridization; and Ms. Jennifer Lowe for the technical editing. This work was performed under the auspices of the U.S. Department of Energy by the University of California, Lawrence Berkeley National Laboratory under contract DE-AC0376SF009098 and Lawrence Livermore National Laboratory under contract W-7405-ENG-48. Funded in part by DOE Low Dose Research Program grant (SCW0391) to AJW.
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