Sage Journals: Discover world-class research

Abstract

Methamphetamine (METH) is a toxic drug of abuse, which can cause significant decreases in the levels of monoamines in various brain regions. However, animals treated with progressively increasing doses of METH over several weeks are protected against the toxic effects of the drug. In the present study, we tested the possibility that this pattern of METH injections might be associated with transcriptional changes in the rat striatum, an area of the brain which is known to be very sensitive to METH toxicity and which is protected by METH preconditioning. We found that the presence and absence of preconditioning followed by injection of large doses of METH caused differential expression in different sets of striatal genes. Quantitative PCR confirmed METH-induced changes in some genes of interest. These include small heat shock 27 kD proteins 1 and 2 (HspB1 and HspB2), brain derived neurotrophic factor (BDNF), and heme oxygenase-1 (Hmox-1). Our observations are consistent with previous studies which have reported that ischemic or pharmacological preconditioning can cause reprogramming of gene expression after lethal ischemic insults. These studies add to the growing literature on the effects of preconditioning on the brain transcriptome.

Keywords

methamphetamine preconditioning striatum BDNF heat shock proteins

INTRODUCTION

Methamphetamine (METH) is an illicit drug which has become an international public health problem. Specifically, METH abuse is associated with many negative consequences which include altered behavioral and cognitive functions (Murray 1998; Scott et al. 2007; Darke et al. 2008). Withdrawal from METH causes anhedonia and intense craving for the drug (Zweben et al. 2004; Sekine et al. 2006; Darke et al. 2008). The negative neuropsychiatric consequences of METH abuse are thought to be due to drug-induced neurodegenerative effects in METH addicts (Scott et al. 2007). Patterns of METH abuse are multiple but usually involve the intake of small doses of the drug followed by gradual increases to larger doses of the psychostimulant (Kramer et al. 1967). Neuropsychological tests have revealed that METH addicts who abuse these large doses suffer from cognitive deficits (Simon et al. 2002; Sekine et al. 2003) and structural abnormalities in their brains (Chang et al. 2007; Sekine et al. 2008). METH-dependent patients indeed suffer from decreases in dopamine (DA) (Volkow et al. 2001) and of serotonin (5-HT) transporters (Sekine et al. 2006).

Many of these neuropathological changes have been replicated in animal models (Krasnova and Cadet 2009). Specifically, METH can cause decreases in DA, 5-HT, and DA transporters (DAT) in various brain regions (Cadet et al. 1994; Deng et al. 1999; Ladenheim et al. 2000; Thomas and Kuhn 2005; Cadet et al. 2007). These experiments focused on the use of moderate to large doses of METH injected during single-day binges (Cadet et al. 2003). However, several groups have now experimented with administration of increasing METH doses over several days prior to challenging the animals with toxic doses of the drug and have found that these patterns of drug administration can provide protection against METH toxicity (Johnson-Davis et al. 2003; Danaceau et al. 2007; Graham et al. 2008; Cadet et al. 2009a). Cadet and colleagues (2009a) have recently suggested that this pattern of drug administration is comparable with other models of brain preconditioning (Calabrese 2008; Obrenovitch 2008) and might involve similar molecular mechanisms of protection (Cadet and Krasnova 2009). For example, it has been reported that brain preconditioning by various manipulations is associated with differential gene expression in the presence of ischemic injuries (Dirnagl et al. 2003; Stenzel-Poore et al. 2003; Dhodda et al. 2004; Koerner et al. 2007; Stenzel-Poore et al. 2007). We thus conducted the present study to test if the absence and presence of METH preconditioning might be also associated with METH-induced differential gene expression in the striatum, a brain region which is known to be affected by METH (Krasnova and Cadet 2009).

MATERIALS AND METHODS

Animals

Male Sprague-Dawley rats (Charles Rivers Laboratories, Raleigh, NC), weighing 330–370 g in the beginning of the experiment were used in the present study. Animals were housed in a humidity- and temperature-controlled room and were given free access to food and water. All animal procedures were performed according to the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the local Animal Care Committee.

Drug Treatment and Tissue Collection

Following habituation, rats were injected intraperitoneally with either (±)-METH-hydrochloride (NIDA, Baltimore, MD) or an equivalent volume of 0.9% saline for a period of three weeks as described elsewhere (Graham et al. 2008; Cadet et al. 2009a). The saline- or METH-pretreated animals received either saline or METH (5 mg/kg × 8 at 1 h intervals) challenges 72 hours after the preconditioning period. This dose of METH is known to cause significant decreases in the levels of monoamines in the rat striatum (Krasnova and Cadet 2009). The four groups of animals were: saline/saline (SS), saline/METH (SM), METH preconditioning/saline (MS), and METH preconditioning/METH (MM). The animals were euthanized 24 h after the injection of the last dose of METH. Their brains were quickly removed, brain regions were dissected on ice, snap frozen on dry ice, and stored at −80°C until used in microarray analyses or quantitative PCR experiments as described below.

RNA Extraction and Microarray Hybridization

Total RNA was isolated using Qiagen RNeasy Midi kit (Qiagen, Valencia, CA) according to the manufacturer's instructions. RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA) and showed no degradation. Microarray hybridization was carried out using Illumina's RatRef-12 Expression BeadChips arrays (22, 227 probes) (Illumina Inc., San Diego, CA). In brief, a 600 ng aliquot of total RNA from each striatal sample was amplified using Ambion's Illumina RNA Amplification kit (Ambion, Austin, TX). Single-stranded RNA (cRNA) was generated and labeled by incorporating biotin-16-UTP (Roche Diagnostics Corporation, Indianapolis, IN). 750 ng of each cRNA sample were hybridized to Illumina arrays at 55 °C overnight according to the Illumina Whole-Genome Gene Expression Protocol for BeadStation (Illumina Inc.). Hybridized biotinylated cRNA was detected with cyanine3-streptavidine (GE Healthcare, Piscataway, NJ) and quantified using Illumina's BeadStation 500GX Genetic Analysis Systems scanner.

Microarray Data Analysis

The raw data for the analyses of the four groups of animals are available upon request. The Illumina BeadStudio software was used to measure fluorescent hybridization signals. Data were extracted by BeadStudio (Illumina Inc.) and then analyzed using GeneSpring software v. 7.3.1 (Silicon Genetics, Redwood City, CA). Raw data were imported into GeneSpring and normalized using global normalization. The normalized data were used to identify changes in gene expression in four group comparisons: MS vs SS, SM vs SS, MM vs SS, and MM vs MS. A gene was identified as significantly changed if it showed increased or decreased expression according to an arbitrary cut-off of 1.7-fold changes at p < 0.025.

Real-time PCR

Total RNA extracted from the rat striatum was also used to confirm the expression of genes of interest by real-time RT-PCR as previously described (Krasnova et al. 2007; Krasnova et al. 2008). In brief, unpooled total RNA obtained from 5–7 rats per group was reverse-transcribed with oligo dT primers and Advantage RT for PCR kit (Clontech, Mountain View, CA). PCR experiments were performed using light cycler technology and LightCycler FastStart DNA Master SYBR Green I kit (Roche) according to manufacturer's protocol. Sequences for gene-specific primers corresponding to PCR targets were obtained using LightCycler Probe Design software (Roche). The primers were synthesized and HPLC-purified at the Synthesis and Sequencing Facility of Johns Hopkins University (Baltimore, MD). Quantitative PCR values were normalized using 18S rRNA and quantified. The results are reported as relative changes which were calculated as the ratios of normalized gene expression data of each group compared to the SS group.

Statistical Analysis

Statistical analysis was performed using analysis of variance (ANOVA) followed by Fisher's protected least significant difference post-hoc comparison (StatView 4.02, SAS Institute, Cary, NC). Values are shown as means ± SEM. The null hypothesis was rejected at p < 0.05.

RESULTS

Identification of genes regulated by METH preconditioning and by METH challenges in the rat striatum

As reported elsewhere, METH preconditioning caused protection against METH-induced depletion in striatal DA and 5-HT levels (Cadet et al. 2009a). In order to assess transcriptional effects of toxic doses of METH in the rat striatum, we used Illumina RatRef-12 Expression BeadChips arrays that contain 22, 523 probes. The results of 3 comparisons between the four groups of rats: MS vs SS, SM vs SS, and MM vs MS are presented in the Venn diagram (Fig. 1). To be identified as changed, the genes had to show 1.7-fold difference with control expression at p < 0.025. A total of 230 genes were differentially impacted in the three comparisons, the distribution and overlap of these genes are shown in Fig. 1. Partial lists of these genes are given in tables 1–4.

FIGURE 1.

METH preconditioning induces differential striatal transcriptional responses to large doses METH. The Venn diagram shows the overlap of genes identified by the three sets of comparisons. The animals were injected and euthanized as described in the text. RNA was extracted from rat striatal tissues. The microarray experiments were performed as described in the method section. Genes were identified as significantly changed if they show greater than ±1.7-fold changes at p < 0.025.

Effects of METH preconditioning on striatal gene expression

Table 1 shows that chronic administration of low non-toxic doses of METH caused significant changes in the expression of 42 genes, with 30 being up-regulated and 12 down-regulated (MS vs SS). Of these genes, there were 34 that were found only in the MS vs SS comparison while 3 were found co-localized within the SM vs SS and 5 genes within the MM vs MS comparison. The most up-regulated gene was the predicted gene, Cd97, which showed 27-fold increases. (We are using only abbreviations in the text since the full name of the genes can be found in the tables that provide the list of METH-regulated genes). METH preconditioning caused 18-fold increases in the expression of Gabrr2 which is a receptor in GABA-mediated inhibitory synapses in the brain (Schmidt 2008). Another gene of interest is Fgf3, a member of the Fgf family of trophic factors (Itoh and Ornitz, 2008), which shows about 12-fold increases after repeated injections of non-toxic doses of METH.

TABLE 1.

Effects of METH preconditioning alone on striatal gene expression.

Fold Changes
MS/SS	Gene Symbol	Common	Description
18.32	Adam18	tMDCIII	a disintegrin and metallopeptidase domain 18
18.18	Gabrr2	Gabrr2	gamma-aminobutyric acid (GABA-C) receptor, subunit rho 2
13.91	Sftpb	Sp-b	surfactant associated protein B
11.89	Fgf3	Int2	fibroblast growth factor 3
8.73	Grpca	Grpca	glutamine/glutamic acid-rich protein A
1.89	Fmo2	Fmo2	flavin containing monooxygenase 2
1.75	E2f1	E2f1	E2F transcription factor 1
−1.71	Lox		Rattus norvegicus lysyl oxidase (Lox), mRNA.
−2.92	Foxi2	Fkhl5; Foxf1	forkhead box I2
−16.23	Pcdhac1	Pcdhac1; rCNRvc1	protocadherin alpha subfamily C, 1

Data were obtained from the MS vs SS comparison. Predicted genes are not listed. The genes are listed in descending order according to METH-induced fold changes in gene expression.

Effects of METH challenges on striatal gene expression in the absence of METH preconditioning

Table 2 shows partial lists of genes affected by binge METH challenge in the striatum in the absence of METH preconditioning (SM vs SS). METH challenge caused significant changes in a total of 98 genes. Of these, 79 were up-regulated (Table 2) and 19 were down-regulated (not shown). The most significantly changed gene was Hcst which showed about a 45-fold increase. Other up-regulated genes of interest include Bcl2-like 10, Hsp27/HspB1, GFAP, Hmox-1, and caspase 4. GFAP expression has been shown to be induced by toxic doses of METH (Deng et al. 1999; Krasnova et al. 2010). The members of the Bcl2 family of mitochondrial proteins are also influenced by toxic doses of the drug (Jayanthi et al. 2001) and are involved in METH-induced neuronal apoptosis (Cadet et al. 1997). The expression of Hsp27/HspB1 (Jayanthi et al. 2009) and of Hmox-1 (Cadet et al. 2009b; Jayanthi et al. 2009) is also changed by toxic doses of METH. Some of these genes are similar to those reported by another group (Thomas et al., 2004).

TABLE 2.

METH-induced increases in striatal gene expression in the absence of METH preconditioning.

Fold Changes
SM/SS	Gene Symbol	Common	Description
44.60	Hcst	Hcst	hematopoietic cell signal transducer
21.13	Il1a	IL-1 alpha	interleukin 1 alpha
15.80	Lfng	Lfng	lunatic fringe gene homolog (Drosophila)
14.83	H19	H19	Rattus norvegicus H19 fetal liver mRNA (H19), misc RNA.
12.53	Bcl2l10	Bcl2l10	Bcl2-like 10
11.22	Mb	Mb	myoglobin
10.88	Timp1	Timp; TIMP-1	tissue inhibitor of metallopeptidase 1
8.19	Hspb1	Hsp25; Hsp27	heat shock 27kDa protein 1
4.83	Cd44	CD44A; METAA; RHAMM	CD44 antigen
4.45	Lcn2	Lcn2	lipocalin 2
4.41	S100a3	S100a3	S100 calcium binding protein A3
3.05	Fmo2	Fmo2	flavin containing monooxygenase 2
2.82	Gfap	Gfap	Rattus norvegicus glial fibrillary acidic protein (Gfap), mRNA.
2.74	Pdpn	E11; Gp38; OTS-8; RTI40; T1-alpha	podoplanin
2.67	Emp3		epithelial membrane protein 3
2.64	Serping1		serine (or cysteine) peptidase inhibitor, clade G, member 1
2.53	Parp3	Adprtl3	poly (ADP-ribose) polymerase family, member 3
2.50	Cd14	Cd14	CD14 antigen
2.34	Chi3l1	Chi3l1	chitinase 3-like 1
2.32	Tyrobp	Karap	Tyro protein tyrosine kinase binding protein
2.28	Gpd1	GPDH; Gpd3	glycerol-3-phosphate dehydrogenase 1 (soluble)
2.25	Tmbim1		transmembrane BAX inhibitor motif containing 1
2.20	Nes	Nes	nestin
2.17	Cox6a2	COX6B; COX6AH	cytochrome c oxidase, subunit VIa, polypeptide 2
2.16	Prelp	Prelp	proline arginine-rich end leucine-rich repeat protein
2.13	Plp2	A4-LSB	proteolipid protein 2
2.12	C1qb	C1qb	complement component 1, q subcomponent, beta polypeptide
2.02	Ptpn6	Ptph6; Shp-1	protein tyrosine phosphatase, non-receptor type 6
1.96	Sv2c	Sv2c	synaptic vesicle glycoprotein 2c
1.95	Prkcdbp	Srbc; DIG-2	protein kinase C, delta binding protein
1.95	Vamp5	Vamp5	vesicle-associated membrane protein 5
1.95	S100a4	CAPL; MTS1	S100 calcium-binding protein A4
1.93	Fxyd5	RIC	FXYD domain-containing ion transport regulator 5
1.92	Ddit4l	Ddit4l	DNA-damage-inducible transcript 4-like (Ddit4l), mRNA.
1.92	Col5a1	Col5a1	procollagen, type V, alpha 1
1.90	Fgfrl1	Fgfr5	fibroblast growth factor receptor-like 1
1.90	Arf6	Arf6	ADP-ribosylation factor 6
1.89	Hla-dma	RT1-DMa; RT1.DMa	major histocompatibility complex, class II, DM alpha
1.89	Pycard	Asc	PYD and CARD domain containing
1.85	Cdo1	Cdo1	cysteine dioxygenase 1, cytosolic
1.84	Clic1	Clic1	chloride intracellular channel 1
1.82	Ccl21b		chemokine (C-C motif) ligand 21b (serine)
1.81	Stat3		signal transducer and activator of transcription 3
1.80	Hmox1	Ho1; Heox; Hmox; Ho-1; HEOXG; hsp32	heme oxygenase (decycling) 1
1.79	Chek2	Chk2; Rad53	CHK2 checkpoint homolog (S. pombe)
1.79	Casp4	Casp11	caspase 4, apoptosis-related cysteine peptidase
1.76	Eif4ebp1	PHAS-I	eukaryotic translation initiation factor 4E binding protein 1
1.74	Tgfb1	Tgfb1	transforming growth factor, beta 1
1.73	Lgals3	gal-3	lectin, galactose binding, soluble 3
1.71	ZnT3	Slc30a3	solute carrier family 30 (zinc transporter), member 3
1.70	Emp1	TMP; CL-20; EMP-1; ENP1MR	epithelial membrane protein 1

The data were generated from the SM vs SS comparison. Predicted genes are not included. The genes are listed in descending order according to fold changes in gene expression.

Effects of METH challenges on striatal gene expression in the presence of METH preconditioning

Table 3 shows a partial list of genes whose expression was affected by the injections of large doses of METH in the presence of METH preconditioning (MM vs MS). Ninety genes were affected in that comparison. Of these, 32 were up-regulated and 58 were down-regulated by the large dose METH challenge. Sixty seven of these genes were changed only after METH challenge in the striata of rats preconditioned with METH while 18 genes were also contained in the MM vs MS comparison (Fig. 1). In addition, 5 genes showed changes in expression in the MS vs SS comparison. The most up-regulated gene was H19. Other up-regulated genes of interest include Timp1, Nes, GFAP, and Vgf. HspB1 which was up-regulated in the absence of METH preconditioning is also up-regulated in the MM vs MS comparison, but to a lesser extent. In contrast, S100a3 and GFAP were up-regulated to similar extent in the absence or presence of METH preconditioning.

TABLE 3.

METH-induced changes in striatal gene expression in the presence of METH preconditioning.

Fold Changes
(MM/MS)	Gene Symbol	Common	Description
13.43	H19		Rattus norvegicus H19 fetal liver mRNA (H19), misc RNA.
11.12	Gys2	GLYSN	glycogen synthase 2
5.67	Timp1	Timp; TIMP-1	tissue inhibitor of metallopeptidase 1
4.47	Hspb1	Hsp25; Hsp27	heat shock 27kDa protein 1
3.50	Cd44	CD44A; METAA	CD44 antigen
3.30	S100a3	S100a3	S100 calcium binding protein A3
2.95	Cxcl10	IP-10; Scyb10	chemokine (C-X-C motif) ligand 10
2.20	Nes	Nes	nestin
2.19	Gfap	Gfap	Rattus norvegicus glial fibrillary acidic protein (Gfap), mRNA.
2.18	Pdpn	E11; Gp38; OTS-8	podoplanin
1.94	Chi3l1	Chi3l1	chitinase 3-like 1
1.83	Tmbim1		transmembrane BAX inhibitor motif containing 1
1.82	Tyrobp	Karap	Tyro protein tyrosine kinase binding protein
1.81	Vgf	Vgf	VGF nerve growth factor inducible
1.81	Serping1		serine (or cysteine) peptidase inhibitor, clade G, member 1
1.76	Prelp	Prelp	proline arginine-rich end leucine-rich repeat protein
−1.72	Slc4a1		solute carrier family 4, member 1
−1.75	Gucy1b2	SGC; Gucy1b2a; Gucy1b2b	guanylate cyclase 1, soluble, beta 2
−1.75	Grem1	drm; Cktsf1b1	gremlin 1 homolog, cysteine knot superfamily (Xenopus laevis)
−1.79	Ces2	rCES2; CES RL4	carboxylesterase 2 (intestine, liver)
−1.81	Hcn1	Hcn1	hyperpolarization-activated cyclic nucleotidegated potassium channel 1
−1.86	Sstr1		Rattus norvegicus somatostatin receptor 1 (Sstr1), mRNA.
−1.87	Ahr		Rattus norvegicus aryl hydrocarbon receptor (Ahr), mRNA.
−1.94	Rnasel	Rnasel	ribonuclease L (2′,5′-oligoisoadenylate synthetase-dependent)
−1.95	Pnck	Camk1b	pregnancy upregulated non-ubiquitously expressed CaM kinase
−2.13	Slit1		Rattus norvegicus slit homolog 1 (Drosophila) (Slit1), mRNA.
−3.37	Rtn4r		Rattus norvegicus reticulon 4 receptor (Rtn4r), mRNA.
−4.18	St8sia6	Siat8f	ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 6
−14.21	Arl10	Arl10	ADP-ribosylation factor-like 10
−15.94	Nfatc2ip		nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 2 interacting protein
−20.45	Dnase1l3		deoxyribonuclease I-like 3
−27.30	Cldn3	Cldn3	claudin 3
−30.18	Ntn2l	Ntn3	netrin 2-like (chicken)
−42.53	Pla2g1b	Pla2g1b	phospholipase A2, group IB
−44.28	Col23a1	Col23a1	procollagen, type XXIII, alpha 1

The data were generated from the MM vs MS comparison. Predicted genes are not included. The genes are listed in descending order according to fold changes in gene expression.

Differential METH-induced striatal gene expression in the absence and presence of METH preconditioning

In order to dissect the effects of METH preconditioning further, we compared the levels of gene expression between the MM and the SM groups (MM vs SM). We found that 77 genes were affected, with 36 being up-regulated and 41 down-regulated. Table 4 shows a partial list of these genes. The most up-regulated gene was Igsf7. Other up-regulated genes of interest include Lif and Egfl6. Down-regulated genes of interest include BDNF and Nurr1.

TABLE 4.

Differential METH-induced striatal gene expression in the absence and presence of METH preconditioning.

Fold Changes
(MM/SM)	Gene Symbol	Common	Description
23.64	Igsf7	Igsf7; Mair-II	immunoglobulin superfamily, member 7
15.17	Lif	Lif	leukemia inhibitory factor
10.55	Nanog	Nanog	Nanog homeobox
7.40	Fut11		fucosyltransferase 11
7.38	Kcnq2	Kcnq2	potassium voltage-gated channel, subfamily Q, member 2
1.88	Chrna7	BTX	cholinergic receptor, nicotinic, alpha polypeptide 7
1.74	Egfl6	Egfl6	EGF-like-domain, multiple 6
−1.72	Lxn		latexin
−1.75	Bdnf		brain derived neurotrophic factor
−1.76	Hgfac	Hgfac	hepatocyte growth factor activator
−1.79	Abcb1b	Mdr1; Pgy1; Abcb1	ATP-binding cassette, sub-family B (MDR/TAP), member 1B
−1.86	Hcn1	Hcn1	hyperpolarization-activated cyclic nucleotidegated potassium channel 1
−2.02	Nr4a2	Nurr1	nuclear receptor subfamily 4, group A, member 2
−2.07	Hs3st2	Hs3st2	heparan sulfate (glucosamine) 3-O-sulfotransferase 2
−2.61	Klk8	bsp1	kallikrein 8 (neuropsin/ovasin)
−2.65	Nov	Nov	nephroblastoma overexpressed gene
−2.77	Cnga1	HCN; Cncg	cyclic nucleotide gated channel alpha 1
−11.10	Npm2	Npm2	nucleophosmin/nucleoplasmin 2
−20.75	Neurod1	Neurod1	neurogenic differentiation 1

Data were obtained from the MM vs SM comparison. Predicted genes are not listed. The genes are listed in descending order according to the METH-induced fold changes.

Quantitative PCR for genes of interest

We examined METH-induced changes in the expression of Hsp27/HspB1 which was up-regulated to differential degrees in both the SM and MM groups in the microarray experiments. METH injections caused about 22- and 7-fold increases in the levels of Hsp27/HspB1 mRNA in the SM and MM groups, respectively (Fig. 2A). The changes observed in the MM were significantly less pronounced than those observed in the SM group. We also measured the expression of HspB2, another member of the HspB family of small heat shock proteins (sHSPs) (Hu et al. 2008) which has been shown to exert protection against ischemia-induced damage (Morrison et al. 2004). The METH injections caused significant increases in HspB2 mRNA levels in the absence but not in the presence of METH preconditioning (Fig. 2B).

FIGURE 2.

Quantitative PCR validates the effects of large doses of METH on striatal HspB1 and HspB2 mRNA levels. Data were obtained using RNA isolated from 5–6 animals per group and measured individually. The mRNA levels were normalized to 18S rRNA levels. The values are shown as means ± SEM in comparison to the SS group. METH caused substantial increases in (A) HspB1 in both the SM and MM groups and (B) HspB2 only in the SM group. Keys to statistics: *, **, *** p < 0.05, 0.01, 0.001, respectively, in comparison to the SS group; #, ### p < 0.05, 0.001, respectively, in comparison to the MS group; !!!, p < 0.001, in comparison to the SM group.

The PCR experiments also confirmed that the expression of Hmox-1 was up-regulated in the SM but not in the MM group (Fig. 3A). In addition, we also measured the expression of Hmox-2, another member of the Hmox family even though it was not identified as being regulated by METH in the microarray data. As shown in Fig. 3B, there were small decreases in the MM group which were significantly different from the SM group. Because Hmox-1 expression is regulated by NRF2 protein translocation from the cytosol to the nucleus (Surh et al. 2009), we tested the idea that multiple injections of METH might cause increases in Nrf2 mRNA. We found that the METH challenge did cause increases in Nrf2 expression in the absence (SM) but not in the presence of METH preconditioning (MM) (Fig. 3C). Because Hmox-1 is up-regulated by endoplasmic reticulum (ER) stress (Gozzelino et al. 2010), we also tested the possibility that DnaJc3 (p58IPK) which is involved in protecting cells against ER stress (Rutkowski et al. 2007) might be induced by METH. Indeed, the large METH doses caused significant increases in DnaJc3 expression in the absence but not in the presence of METH preconditioning (Fig. 3D).

FIGURE 3.

Effects of large doses of METH on striatal Hmox-1, Hmox-2, Nrf2, and DnaJc3 mRNA levels. Data were obtained using RNA isolated from 5–6 animals per group and measured individually. The mRNA levels were normalized to 18S rRNA levels. The values are means ± SEM in comparison to the SS group. METH caused substantial increases in (A) Hmox-1 in the SM group but not in (B) Hmox-2. There were also METH-induced increases in the expression of (C) Nrf2 in the SM group and of (D) DnaJc3 in both the SM and MM groups. Keys to statistics: *, **, *** p < 0.05, 0.01, 0.001, respectively, in comparison to the SS group; #, ### p < 0.05, 0.001, respectively, in comparison to the MS group; !!, !!!, p < 0.001, respectively, in comparison to the SM group.

Because the microarray experiments identified BDNF as being down-regulated in the MM in comparison to the SM group and because BDNF has been shown to provide protection against transneuronal degeneration of DA neurons (Canudas et al. 2005), we sought to confirm these data by quantitative PCR. Figure 4A shows that there were significant decreases in BDNF expression in the presence of METH preconditioning (MM group). We also measured the expression of GDNF that has been shown to protect against METH toxicity (Cass et al. 2006). There were some decreases in GDNF mRNA levels in MM group that did not reach statistical significance (Fig. 4B).

FIGURE 4.

Effects of large doses of METH on striatal BDNF and GDNF mRNA levels. Tissues were processed and mRNA levels measured as described in the text. METH caused significant decreases in (A) BDNF in MM group. (B) GDNF expression was not significantly affected in any of the groups. Keys to statistics: * p < 0.05, in comparison to the SS group.

DISCUSSION

The main findings in these experiments are that acute injections of large doses of METH caused differential gene expression in the striata of rats depending on whether the animals have been pre-exposed repeatedly to smaller non-toxic doses of the drug or not. The present observations allowed for the creation of differentially expressed genes after exposure to large doses of METH. These results are important because there are very few reports on the effects of chronic METH treatment on large scale gene expression in the rat striatum. We hope that the results of our study will provide a comprehensive database for future investigations of METH preconditioning, METH toxicity, and drug-induced neuroplastic changes in the rat striatum.

In this study, we found that the vast majority of genes regulated by the single-day binge METH injections are different from those regulated by acute METH injections (Cadet et al. 2001; Jayanthi et al. 2009). These differences might be due to the fact that data reported in the previous studies were obtained from animals euthanized within the first 4 hours after the METH injections (Cadet et al. 2001; Jayanthi et al. 2009). It is important to point out that the genes identified in the striatum are also different from the genes identified in the midbrain after METH preconditioning, indicating that the preconditioning process might be regionally specific in terms of METH-induced gene expression (Cadet et al. 2009b). These regional differences might be secondary to the fact that the data of the former study came from the rat midbrain which is the site of origin for dopaminergic neurons whereas the present data were obtained from intrinsic striatal non-dopaminergic neurons. Nevertheless, our data support the idea that METH preconditioning is associated with significant alterations of the striatal transcriptional responses to large doses of METH. In what follows, we discuss the role of some interesting genes whose METH-induced changes in expression were confirmed by quantitative PCR.

Mammalian HSPs, which include Hsp27/HspB1, are molecular chaperones that participate in the proper folding of proteins and help to maintain their native conformations during stressful events (Arya et al. 2007). Hsp27/HspB1 is a novel regulator of intracellular redox state (Arrigo 2007). HSPs also participate in the transfer of improperly folded proteins to the proteasome for degradation. HSPs are induced by heat shock, hypoxic and ischemic events, and oxidative stress (Arrigo 2007; Arya et al. 2007). Recent studies have documented a role for these proteins in neurodegenerative processes and have demonstrated that HSPs are important in cellular protection against aggregation-prone proteins and in animal models of neurodegeneration (Muchowski and Wacker 2005). Thus, our demonstration of METH-induced expression of the chaperones, Hsp27/HspB1 (Franklin et al. 2005) and HspB2 (Hu et al. 2008), suggests that striatal cells are able to mount adaptive defensive HSP-modulated networks against the toxic effects of the drug. Hsp27/HspB1 appears to exert its protective effects, in part, by inhibiting caspase-dependent apoptotic pathways (Garrido et al. 1999; Voss et al. 2007).

We also found that the METH challenge caused 3-fold increases in Hmox-1 expression in the absence of METH preconditioning and that these increases were attenuated in the striata of the METH preconditioned rats. Because Hmox-1 is an enzyme that can be induced by oxidative stress (Calabrese et al. 2004; Li et al. 2007) and because METH toxicity is mediated, in part, via oxidative stress (Krasnova and Cadet 2009), the present observations suggest that the METH challenge might have caused more oxidative stress in the striata of animals pretreated with saline. However, since saline-pretreated animals do show METH toxicity, these METH-induced increases in Hmox-1 might not be sufficient to protect post-synaptic cells from drug-related damage. It is important to point that overexpression of Hmox-1 can protect against METH toxicity in vitro (Huang et al. 2009). Nevertheless, it appears that a substantial increase in the level of the enzyme might be necessary before protection against METH toxicity can be observed in vivo. This remains to be demonstrated.

The expression of BDNF which is involved in the regulation of cell survival (Canudas et al. 2005) and in synaptic plasticity (Kuipers and Bramham 2006), was significantly decreased by the METH challenge only in the presence of METH preconditioning. These results were unexpected since we had observed increases in BDNF expression in the midbrain where the DA neurons are located (Cadet et al. 2009b). The present observations in the rat striatum suggest that the increases in BDNF in midbrain dopaminergic neurons might cause increases in the release of BDNF in the striatum and compensatory down-regulation of its expression in intrinsic striatal cells via epigenetic changes in the regulation of BDNF through promoter methylation (Dennis and Levitt 2005). These epigenetic changes might also involve decreased recruitment of acetylated histones on BDNF promoters since histone deacetylase (HDAC) inhibitors have been reported to cause increases in BDNF transcription (Wu et al. 2008). In any case, these dichotomous results in the terminal regions and in the cell body area emphasize the need to determine regional effects of toxic agents on the brain.

This discussion also applies to the effects of METH on striatal Hspb2 and Hmox1 mRNA levels which showed increases in response to the challenge with high doses of METH in the absence but not in the presence of METH preconditioning. The situation was reversed in the midbrain of these animals because METH preconditioning enhanced the METH challenge-induced increases in Hspb2 and Hmox-1 mRNA levels in the rat midbrain (Cadet et al., 2009b). These results support our thesis that the brain cannot be thought of as a homogeneous structure when assessing the molecular effects of preconditioning and/or toxic compounds.

In summary, we found that the challenge with large doses of METH is associated with differential transcriptional responses in the rat striatum in the absence and presence of preconditioning with repeated injections of small nontoxic doses of the drug. These results suggest that intrinsic striatal cells exposed to low METH doses develop a certain degree of tolerance to the effects of the drug on the expression of genes that are triggering the nefarious METH effects. Future studies are underway to test the possibility that METH preconditioning can also protect against METH-induced cell death in the striatum.

Footnotes

ACKNOWLEDGMENTS

The study is supported by Intramural Research Program of the National Institute on Drug Abuse, NIH, DHHS.

References

Arrigo

. 2007. The cellular “networking” of mammalian Hsp27 and its functions in the control of protein folding, redox state and apoptosis. Adv Exp Med Biol 594:14–26

Arya

Mallik

, and Lakhotia

. 2007. Heat shock genes - integrating cell survival and death. J Biosci 32:595–610

Cadet

and Krasnova

. 2009. Cellular and molecular neurobiology of brain preconditioning. Mol Neurobiol 39:50–61

Cadet

Sheng

Ali

Rothman

Carlson

, and Epstein

. 1994. Attenuation of methamphetamine-induced neurotoxicity in copper/zinc superoxide dismutase transgenic mice. J Neurochem 62:380–383

Cadet

Ordonez

, and Ordonez

. 1997. Methamphetamine induces apoptosis in immortalized neural cells: protection by the proto-oncogene, bcl-2. Synapse 25:176–184

Cadet

Jayanthi

McCoy

Vawter

, and Ladenheim

. 2001. Temporal profiling of methamphetamine-induced changes in gene expression in the mouse brain: evidence from cDNA array. Synapse 41:40–48

Cadet

Jayanthi

, and Deng

. 2003. Speed kills: cellular and molecular bases of methamphetamine-induced nerve terminal degeneration and neuronal apoptosis. Faseb J 17:1775–1788

Cadet

Krasnova

Jayanthi

, and Lyles

. 2007. Neurotoxicity of substituted amphetamines: molecular and cellular mechanisms. Neurotox Res 11:183–202

Cadet

Krasnova

Ladenheim

Cai

McCoy

, and Atianjoh

. 2009a. Methamphetamine preconditioning: differential protective effects on monoaminergic systems in the rat brain. Neurotox Res 15:252–259

10.

Cadet

McCoy

Cai

Krasnova

Ladenheim

Beauvais

Wilson

Wood

Becker

, and Hodges

. 2009b. Methamphetamine preconditioning alters midbrain transcriptional responses to methamphetamine-induced injury in the rat striatum. PLoS One 4:e7812

11.

Calabrese

. 2008. Converging concepts: adaptive response, preconditioning, and the Yerkes-Dodson Law are manifestations of hormesis. Ageing Res Rev 7:8–20

12.

Calabrese

Stella

Butterfield

, and Scapagnini

. 2004. Redox regulation in neurodegeneration and longevity: role of the heme oxygenase and HSP70 systems in brain stress tolerance. Antioxid Redox Signal 6:895–913

13.

Canudas

Pezzi

Canals

Pallas

, and Alberch

. 2005. Endogenous brain-derived neurotrophic factor protects dopaminergic nigral neurons against transneuronal degeneration induced by striatal excitotoxic injury. Brain Res Mol Brain Res 134:147–154

14.

Cass

Peters

Harned

, and Seroogy

. 2006. Protection by GDNF and other trophic factors against the dopamine-depleting effects of neurotoxic doses of methamphetamine. Ann N Y Acad Sci 1074:272–281

15.

Chang

Alicata

Ernst

, and Volkow

. 2007. Structural and metabolic brain changes in the striatum associated with methamphetamine abuse. Addiction 102 Suppl 1:16–32

16.

Danaceau

Deering

Day

Smeal

Johnson-Davis

Fleckenstein

, and Wilkins

. 2007. Persistence of tolerance to methamphetamine-induced monoamine deficits. Eur J Pharmacol 559:46–54

17.

Darke

Kaye

McKetin

, and Duflou

. 2008. Major physical and psychological harms of methamphetamine use. Drug Alcohol Rev 27:253–262

18.

Deng

Ladenheim

Tsao

, and Cadet

. 1999. Null mutation of c-fos causes exacerbation of methamphetamine-induced neurotoxicity. J Neurosci 19:10107–10115

19.

Dennis

, and Levitt

. 2005. Regional expression of brain derived neurotrophic factor (BDNF) is correlated with dynamic patterns of promoter methylation in the developing mouse forebrain. Brain Res Mol Brain Res 140:1–9

20.

Dhodda

Sailor

Bowen

, and Vemuganti

. 2004. Putative endogenous mediators of preconditioning-induced ischemic tolerance in rat brain identified by genomic and proteomic analysis. J Neurochem 89:73–89

21.

Dirnagl

Simon

, and Hallenbeck

. 2003. Ischemic tolerance and endogenous neuroprotection. Trends Neurosci 26:248–254

22.

Franklin

Krueger-Naug

Clarke

Arrigo

, and Currie

. 2005. The role of heat shock proteins Hsp70 and Hsp27 in cellular protection of the central nervous system. Int J Hyperthermia 21:379–392

23.

Garrido

Bruey

Fromentin

Hammann

Arrigo

, and Solary

. 1999. HSP27 inhibits cytochrome c-dependent activation of procaspase-9. Faseb J 13:2061–2070

24.

Gozzelino

Jeney

, and Soares

. 2010. Mechanisms of cell protection by heme oxygenase-1. Annu Rev Pharmacol Toxicol 50:323–354

25.

Graham

Noailles

, and Cadet

. 2008. Differential neurochemical consequences of an escalating dose-binge regimen followed by single-day multiple-dose methamphetamine challenges. J Neurochem 105:1873–1885

26.

Yang

Zhou

Zeng

, and Wang

. 2008. HSPB2/MKBP, a novel and unique member of the small heat-shock protein family. J Neurosci Res 86:2125–2133

27.

Huang

Lin

, and Wang

. 2009. Methamphetamine induces heme oxygenase-1 expression in cortical neurons and glia to prevent its toxicity. Toxicol Appl Pharmacol 240:315–326

28.

Itoh

and Ornitz

. 2008. Functional evolutionary history of the mouse Fgf gene family. Dev Dyn 237:18–27

29.

Jayanthi

Deng

Bordelon

McCoy

, and Cadet

. 2001. Methamphetamine causes differential regulation of pro-death and anti-death Bcl-2 genes in the mouse neocortex. Faseb J 15:1745–1752

30.

Jayanthi

McCoy

Beauvais

Ladenheim

Gilmore

Wood

3rd Becker

, and Cadet

. 2009. Methamphetamine induces dopamine D1 receptor-dependent endoplasmic reticulum stress-related molecular events in the rat striatum. PLoS One 4:e6092

31.

Johnson-Davis

Fleckenstein

, and Wilkins

. 2003. The role of hyperthermia and metabolism as mechanisms of tolerance to methamphetamine neurotoxicity. Eur J Pharmacol 482:151–154

32.

Koerner

Gatting

Noppens

Kempski

, and Brambrink

. 2007. Induction of cerebral ischemic tolerance by erythromycin preconditioning reprograms the transcriptional response to ischemia and suppresses inflammation. Anesthesiology 106:538–547.

33.

Kramer

Fischman

, and Littlefield

. 1967. Amphetamine abuse. Pattern and effects of high doses taken intravenously. Jama 201:305–309

34.

Krasnova

and Cadet

. 2009. Methamphetamine toxicity and messengers of death. Brain Res Rev 60:379–407

35.

Krasnova

Betts

Dada

Jefferson

Ladenheim

Becker

Cadet

, and Hohmann

. 2007. Neonatal dopamine depletion induces changes in morphogenesis and gene expression in the developing cortex. Neurotox Res 11:107–130

36.

Krasnova

Wood

McCoy

Prabhu

Becker

Katz

Cadet

. 2008. Transcriptional responses to reinforcing effects of cocaine in the rat hippocampus and cortex. Genes Brain Behav 7:193–202

37.

Krasnova

Justinova

Ladenheim

Jayanthi

McCoy

Barnes

Warner

Goldberg

, and Cadet

. 2010. Methamphetamine self-administration is associated with persistent biochemical alterations in striatal and cortical dopaminergic terminals in the rat. PLoS One 5:e8790

38.

Kuipers

and Bramham

. 2006. Brain-derived neurotrophic factor mechanisms and function in adult synaptic plasticity: new insights and implications for therapy. Curr Opin Drug Discov Devel 9:580–586

39.

Ladenheim

Krasnova

Deng

Oyler

Polettini

Moran

Huestis

Cadet

. 2000. Methamphetamine-induced neurotoxicity is attenuated in transgenic mice with a null mutation for interleukin-6. Mol Pharmacol 58:1247–1256

40.

Hossieny

Qawasmeh

Beck

, and Stocker

. 2007. Pharmacologic induction of heme oxygenase-1. Antioxid Redox Signal 9:2227–2239

41.

Morrison

Whittaker

Klepper

Wawrousek

, and Glembotski

. 2004. Roles for alphaB-crystallin and HSPB2 in protecting the myocardium from ischemia-reperfusion-induced damage in a KO mouse model. Am J Physiol Heart Circ Physiol 286:H847–855

42.

Muchowski

and Wacker

. 2005. Modulation of neurodegeneration by molecular chaperones. Nat Rev Neurosci 6:11–22

43.

Murray

. 1998. Psychophysiological aspects of amphetamine-methamphetamine abuse. J Psychol 132:227–237

44.

Obrenovitch

. 2008. Molecular physiology of preconditioning-induced brain tolerance to ischemia. Physiol Rev 88:211–247

45.

Rutkowski

Kang

Goodman

Garrison

Taunton

Katze

Kaufman

, and Hegde

. 2007. The role of p58IPK in protecting the stressed endoplasmic reticulum. Mol Biol Cell 18:3681–3691

46.

Schmidt

. 2008. GABA(C) receptors in retina and brain. Results Probl Cell Differ 44:49–67

47.

Scott

Woods

Matt

Meyer

Heaton

Atkinson

, and Grant

. 2007. Neurocognitive effects of methamphetamine: a critical review and meta-analysis. Neuropsychol Rev 17:275–297

48.

Sekine

Minabe

Ouchi

Takei

Iyo

Nakamura

Suzuki

Tsukada

Okada

Yoshikawa

Futatsubashi

, and Mori

. 2003. Association of dopamine transporter loss in the orbitofrontal and dorsolateral prefrontal cortices with methamphetamine-related psychiatric symptoms. Am J Psychiatry 160:1699–1701

49.

Sekine

Ouchi

Takei

Yoshikawa

Nakamura

Futatsubashi

Okada

Minabe

Suzuki

Iwata

Tsuchiya

Tsukada

Iyo

, and Mori

. 2006. Brain serotonin transporter density and aggression in abstinent methamphetamine abusers. Arch Gen Psychiatry 63:90–100

50.

Sekine

Ouchi

Sugihara

Takei

Yoshikawa

Nakamura

Iwata

Tsuchiya

Suda

Suzuki

Kawai

Takebayashi

Yamamoto

Matsuzaki

Ueki

Mori

Gold

, and Cadet

. 2008. Methamphetamine causes microglial activation in the brains of human abusers. J Neurosci 28:5756–5761

51.

Simon

Domier

Sim

Richardson

Rawson

, and Ling

. 2002. Cognitive performance of current methamphetamine and cocaine abusers. J Addict Dis 21:61–74

52.

Stenzel-Poore

Stevens

Xiong

Lessov

Harrington

Mori

Meller

Rosenzweig

Tobar

Shaw

Chu

, and Simon

. 2003. Effect of ischaemic preconditioning on genomic response to cerebral ischaemia: similarity to neuroprotective strategies in hibernation and hypoxia-tolerant states. Lancet 362:1028–1037

53.

Stenzel-Poore

Stevens

King

, and Simon

. 2007. Preconditioning reprograms the response to ischemic injury and primes the emergence of unique endogenous neuroprotective phenotypes: a speculative synthesis. Stroke 38:680–685

54.

Surh

Kundu

, and Cha

. 2009. Role of Nrf2-mediated heme oxygenase-1 upregulation in adaptive survival response to nitrosative stress. Arch Pharm Res 32:1163–1176

55.

Thomas

Francescutti-Verbeem

Liu

, and Kuhn

. 2004. Identification of differentially regulated transcripts in mouse striatum following methamphetamine treatment-an oligonucleotide microarray approach. J Neurochem 88:380–393

56.

Thomas

and Kuhn

. 2005. Attenuated microglial activation mediates tolerance to the neurotoxic effects of methamphetamine. J Neurochem 92:790–797

57.

Volkow

Chang

Wang

Fowler

Leonido-Yee

Franceschi

Sedler

Gatley

Hitzemann

Ding

Logan

Wong

, and Miller

. 2001. Association of dopamine transporter reduction with psychomotor impairment in methamphetamine abusers. Am J Psychiatry 158:377–382

58.

Voss

Batra

Kolattukudy

Gonzalez-Mejia

Smith

, and Doseff

. 2007. Binding of caspase-3 prodomain to heat shock protein 27 regulates monocyte apoptosis by inhibiting caspase-3 proteolytic activation. J Biol Chem 282:25088–25099

59.

Chen

Dallas

Wilson

Block

Wang

Kinyamu

Gao

Leng

Chuang

Zhang

, and Hong

. 2008. Histone deacetylase inhibitors up-regulate astrocyte GDNF and BDNF gene transcription and protect dopaminergic neurons. Int J Neuropsychopharmacol 11:1123–1134

60.

Zweben

Cohen

Christian

Galloway

Salinardi

Parent

, and Iguchi

. 2004. Psychiatric symptoms in methamphetamine users. Am J Addict 13:181–190

Methamphetamine Preconditioning Causes Differential Changes in Striatal Transcriptional Responses to Large Doses of the Drug

Abstract

Keywords

INTRODUCTION

MATERIALS AND METHODS

Animals

Drug Treatment and Tissue Collection

RNA Extraction and Microarray Hybridization

Microarray Data Analysis

Real-time PCR

Statistical Analysis

RESULTS

Identification of genes regulated by METH preconditioning and by METH challenges in the rat striatum

Effects of METH preconditioning on striatal gene expression

Effects of METH challenges on striatal gene expression in the absence of METH preconditioning

Effects of METH challenges on striatal gene expression in the presence of METH preconditioning

Differential METH-induced striatal gene expression in the absence and presence of METH preconditioning

Quantitative PCR for genes of interest

DISCUSSION

Footnotes

ACKNOWLEDGMENTS

References