Open Access

Mutant huntingtin activates Nrf2-responsive genes and impairs dopamine synthesis in a PC12 model of Huntington's disease

BMC Molecular Biology20089:84

DOI: 10.1186/1471-2199-9-84

Received: 05 May 2008

Accepted: 09 October 2008

Published: 09 October 2008

Abstract

Background

Huntington's disease is a progressive autosomal dominant neurodegenerative disorder that is caused by a CAG repeat expansion in the HD or Huntington's disease gene. Although micro array studies on patient and animal tissue provide valuable information, the primary effect of mutant huntingtin will inevitably be masked by secondary processes in advanced stages of the disease. Thus, cell models are instrumental to study early, direct effects of mutant huntingtin. mRNA changes were studied in an inducible PC12 model of Huntington's disease, before and after aggregates became visible, to identify groups of genes that could play a role in the early pathology of Huntington's disease.

Results

Before aggregation, up-regulation of gene expression predominated, while after aggregates became visible, down-regulation and up-regulation occurred to the same extent. After aggregates became visible there was a down-regulation of dopamine biosynthesis genes accompanied by down-regulation of dopamine levels in culture, indicating the utility of this model to identify functionally relevant pathways. Furthermore, genes of the anti-oxidant Nrf2-ARE pathway were up-regulated, possibly as a protective mechanism. In parallel, we discovered alterations in genes which may result in increased oxidative stress and damage.

Conclusion

Up-regulation of gene expression may be more important in HD pathology than previously appreciated. In addition, given the pathogenic impact of oxidative stress and neuroinflammation, the Nrf2-ARE signaling pathway constitutes a new attractive therapeutic target for HD.

Background

Huntington's disease (HD) is a progressive autosomal dominant neurodegenerative disease caused by a CAG repeat expansion in the coding region of the HD gene, resulting in an expansion of polyglutamines at the N-terminus of the huntingtin protein and accumulation of the mutant protein into cytoplasmic and nuclear aggregates [1]. Larger expansions result in increased aggregation and an earlier onset of pathological and clinical features [2]. The formation of aggregates is considered a hallmark of HD [3, 4]. The neuropathology of HD involves a selective dysfunction and death of specific neuronal subpopulations within the central nervous system [5].

Gene expression studies on animal model material and low grade patient material have provided important information on cellular processes and pathways involved in HD pathology [6, 7]. Not only is there a loss of normal huntingtin function [8], upon expansion there is a toxic gain of function resulting in a disruption of cellular functions, including transcriptional deregulation, caspase activation and aberrant proteasomal processing [9]. In addition, an increase in reactive oxygen species was found.

Furthermore, the regional pattern of transcriptional pathology in humans is in agreement with the pattern of neurodegeneration [6]. The first detectable changes in gene expression in mice carrying the first exon of mutant huntingtin coincided with the first occurrence of pathological and behavioural changes [10], again underscoring the fact that gene expression is a good reflection of ongoing changes towards pathology. Furthermore, transcriptional changes, especially in the mouse models reflecting more advanced stages of the disease, were similar to the changes seen in human HD brain [7].

Although micro array studies on patient and animal tissue provide valuable information, the primary effect of mutant huntingtin will inevitably be masked by secondary processes in advanced stages of the disease. Thus, cell models are instrumental to study early, direct effects of mutant huntingtin, offering new insights into the pathogenic mechanisms of HD. Especially studies of the early stage are extremely important, because in this stage the phenotype can still be reverted. A well established HD cell model is the rat phaeochromocytoma (PC) 12 cell line, which inducibly expresses exon 1 of the HD gene [11, 12]. So far comprehensive expression profiling studies exploiting data of the completed rat genome project were lacking. The aim of this study was to find mRNA changes early in the cellular pathology before and after the occurrence of aggregates and to identify groups of genes that could play a role in the pathology of HD.

Methods

Cell culture

Inducible rat PC12 cell lines expressing an exon 1 fragment of huntingtin with 23 (Q23) or 74 (Q74) glutamine repeats fused to the Green Fluorescent Protein (GFP), [11, 12] were cultured in standard high glucose Dulbecco's modified Eagle's medium (DMEM, Invitrogen Life Technologies, Carlsbad, USA) supplemented with 100 U/ml penicillin/streptomycin (Invitrogen Life Technologies), 2 mM L-glutamine (Invitrogen Life Technologies), 10% heat-inactivated horse serum (Invitrogen Life Technologies), 5% Tet-approved heat inactivated fetal bovine serum (Clontech, Palo Alto, USA), 100 μg/ml G418 (Invitrogen Life Technologies) and 75 μg/ml hygromycin (Invitrogen Life Technologies) at 37°C and 10% CO2. Cells were induced with 1 μg/ml doxycycline (dox, Clontech) and harvested on day 0 (uninduced cells), 1 day (when only a few cells expressing mutant huntingtin contain aggregates) and 5 days (when nearly all cells expressing mutant huntingtin contain aggregates) [12]. The same culture conditions were used for PC12 cells without a construct, to eliminate the effect of doxycycline treatment on gene expression.

Hybridization design

For each construct, we performed duplicate experiments with 2 independent cell lines for each construct (biological replicates). Furthermore, from each cell line, two separate RNA isolations were performed (technical replicates). RNA was harvested prior to induction (day 0), after 24 hours of induction (day 1) and after 5 days of induction. RNA was isolated with the QIAGEN RNeasy Mini Kit (QIAGEN, Hilden, Germany) with on-column DNase treatment. First-strand and second-strand cDNA synthesis from total RNA was performed and biotin-modified NTPs were incorporated into the in vitro transcribed cRNA with the Illumina TotalPrep RNA Amplification Kit (Ambion, Foster City, USA). This biotin modified cRNA was hybridized to the Illumina RatRef-12 Expression BeadChip array (Illumina Inc., San Diego, CA, USA) and labelled with Streptavidin-Cy3.

Statistical analysis

The average expression value of all beads per probe with no background correction was obtained from BeadStudio 3.1.7. Further data analysis was performed in 'R' version 2.4.1. [13]. Data were normalized with the VSN method using the VSN package for 'R' [14]. To establish significance of differential gene expression, we used the empirical Bayes moderated t-statistics implemented in LIMMA package version 2.8.1. for 'R' [15] and contrasts between Q23 and Q74 were calculated per time point. Results were adjusted for multiple testing by the Benjamini-Hochberg method. Only probes were considered where the ratio on day 0 had a P-value of >0.05 and the ratio on day1 or day 5 had a P-value of <0.05. Microarray data discussed in this work have been deposited in NCBI's Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO series accession number GSE10581.

Functional classification

Functional classification was performed with the web based tool DAVID http://david.abcc.ncifcrf.gov[16]. This objective tool uses the one-tail Fisher Exact Probability Value for gene-enrichment analysis. Significant gene ontology terms for the Biological Process (BP), Cellular Component (CC) and Molecular Function (MF) ontologies were analysed. Transcripts that showed a significant increased or decreased differential expression at 1 day and 5 days were analyzed separately against a background list of all genes present on the platform. Only categories with a P-value < 0.05 containing two or more genes were considered.

Quantitative RT-PCR

Isolated total RNA, as described above, was also used for qRT-PCR. RNA was quantified spectrometrically and integrity was checked with the Agilent 6000 Nano Assay (Agilent, Santa Clara, USA). Reverse transcription of RNA was performed with the Transcriptor First Strand cDNA Synthesis Kit (Roche, Basel, Switzerland). First Strand cDNA Synthesis was performed with 2 μg of total RNA and 2 μl (600 pmol/μl) random hexamer primers.

The LightCycler 480 PCR and detection system (Roche) was used for amplification and real-time quantification. PCR reactions of each sample were performed in triplicate in a final volume of 10 μl in a 384 well plate (for primer sequences see Additional File 1). The PCR mixture contained 2 μl of 50× diluted cDNA template, 2 μl of 5× qPCR-&GO LC480 Green Mastermix (Roche) (with 12.5 mM MgCl2) and primers at a final concentration of 250 nM with the following conditions: initial denaturation at 95°C for 10 min, followed by 45 amplification cycles at 95°C for 10 s, 60°C for 30 s, and 72°C for 20 s and final extension at 72°C for 5 min. After the amplification reaction melting curve analysis was performed, starting at 60°C and increasing to 98°C with 5 acquisitions/°C. Relative mRNA levels were calculated with the efficiency-corrected Ct method with β-actin and Ywhaz as reference genes and mRNA levels on day 0 (uninduced cells) as calibrator [17].

Immunohistochemistry

Cells were fixed in 4% paraformaldehyde for 15 min and permeabilized in 50% methanol and 1% H2O2 for 20 min. After three washes in PBS containing 0.2% Triton X-100 (PBS-Triton), cells were incubated overnight at 4°C with rabbit anti tyrosine hydroxylase (1:2000, Santa Cruz Biotechnology Inc., USA) in PBS-Triton with 1% normal goat serum and 0.4% Thimerosal (Sigma, St. Louis, USA). Cells were subsequently incubated with rabbit anti Alexa 594 (Invitrogen Life Technologies) and examined on a Leica TCS SL confocal microscope.

Western blotting

Whole cell extracts (25 μg per lane) were separated by SDS-PAGE and transferred to a PVDF membrane (Roche). Blots were labelled with rabbit anti Tyrosine Hydroxylase 1:2000 (sc-14007, Santa Cruz Biotechnology Inc., Santa Cruz, USA) followed by goat anti rabbit IgG conjugated to horseradish peroxidase (Santa Cruz) in a 1:10,000 dilution and visualized by ECL plus (Amersham, Buckinghamshire, United Kingdom). Blots were stripped by incubating in stripping buffer (100 mM β-mercapto-ethanol, 2% SDS, 62.5 mM Tris-HCl pH 8.0) for 30 min at 55°C and subsequently labelled for rabbit anti actin antibody 1:600 (clone C4, ICN Biochemicals Inc., Costa Mesa, USA) and goat anti rabbit IgG conjugated to horseradish peroxidase (Santa Cruz) to check that equal amounts of protein were loaded.

High Performance Liquid Chromatography (HPLC)

Whole cell extracts were prepared as described in the Western blotting paragraph for HPLC analysis. Extracts from 2 independent cell lines for each construct were frozen immediately at -20°C until further analysis. Dopamine concentration was measured by HPLC technology with electron capture detection with a detection limit of 0.01 nmol/L [18]. Dopamine concentrations are represented as μmol dopamine per gram of protein extract.

Results

On day 1 after doxycycline-mediated induction of the expression constructs, when aggregates had just started to form, there were 145 of the approximately 22,500 transcripts with a significantly changed ratio between Q23 and Q74 (P < 0.05 after correction for multiple testing). Of those, 97 showed an increased expression compared to the expression level on day 0, and 48 showed a decreased expression. After 5 days of induction, when there was extensive aggregation of the Q74 but not the Q23 containing protein, there were 1233 transcripts differentially expressed of which 573 transcripts were up and 660 were down. Of the 145 differentially expressed transcripts at day 1, there were 51 also differentially expressed at day 5, while 8 could be expected by chance alone. The other 95 returned to control levels at day 5.

Cellular processes changed before formation of aggregates

We were particularly interested in the molecular pathways changed in the early stages of HD. Therefore, we evaluated which pathways were represented in the list of transcripts with differential expression at day 1. Since there were no significant categories when GO-based functional classification was performed, all significantly changed transcripts at 1 day were grouped according to their function (see Table 1). Out of the 97 up-regulated transcripts, 54 were included in the analysis while the remaining 43 transcripts were of unknown function. Out of the 48 down-regulated transcripts, 39 were analyzed and there were 9 transcripts of unknown function. The largest functional group consisted of up-regulated transcripts coding for ion channels and receptors, with an over-representation of olfactory receptors. The next two largest groups contained transcriptional and chromatin remodelling related transcripts that were both up- and down-regulated. Transcripts involved in cytoskeletal organization and cellular matrix were mostly down-regulated in the mutant cells and there seemed to be early signs of oxidative stress and impairment in vesicle trafficking.
Table 1

Functional grouping of genes that show a significant change in expression between mutant and wild-type cells (Q74-Q23) after 1 day of induction

Genes up after 1 day of mutant huntingtin expression

Genes down after 1 day of mutant huntingtin expression

Gene

Accession #

Gene

Accession #

Gene

Accession #

Gene

Accession #

Apoptosis-related proteins

Cell cycle and growth factors

Gstp1

XM_579338

Tnfaip8*

XM_225940

Igf2

NM_031511

Cdc14a*

XM_227618

Cell cycle and growth factors

Smpd3

NM_053605

  

Tgfa

NM_012671

  

Cell signalling

Cell signalling

Arl6*

XM_344009

Plxnb1*

XM_236640

Flrt2*

XM_234361

Rgs14

NM_053764

Calm1

XM_579543

Panx2

XM_579735

Rasl11b

NM_001002830

GAP1(sim)

XM_227132

Chromatin remodeling – transcription

Rgs2

NM_053453

  

Smad4

NM_019275

Cbx6*

XM_576309

Chromatin remodeling – transcription

Chc1l

NM_199084

Ttf2*

XM_215670

Hoxb13*

XM_220905

Vax2

NM_022637

Prickle1

XM_235609

Dnajb6*

XM_342607

LOC362865

XM_343194

LOC368057

XM_347220

Mdc1

XM_227971

  

Npas1*

XM_238770

Dclre1b*

XM_227537

Cytoskeleton – cellular matrix

Hoxb9*

XM_220887

  

Epb4.1l4a*

XM_226060

RGD1310323

NM_001008348

Cytoskeleton – cellular matrix

Add3

NM_031552

Cilp*

XM_236348

Mybph

NM_031813

  

Plekhh1*

XM_234332

  

Electron transport – mitochondrion

Electron transport – mitochondrion

LOC293949

XM_215248

  

Dhrs4

NM_153315

  

Ion channels – receptors

Ion channels – receptors

Ms4a8b*

XM_342026

Olr677*

NM_001001062

Boc*

XM_340986

Ms4a11*

XM_342028

Ccr7

NM_199489

Olr1340*

XM_236174

LOC501049

XM_576464

Olfml2b*

XM_222868

Trpv6

NM_053686

Olr1597*

NM_001000911

Trpv2

NM_017207

  

Olr29*

NM_001000691

Ttyh3*

XM_221962

Oxidative stress

Olr552*

NM_001001055

Il17rb*

XM_224604

Prdx6

NM_053576

  

Olr1751*

NM_001000492

  

RNA processing and ribosomal

Oxidative stress

Mrps15

NM_001007653

Rps16

XM_341815

Blvra

NM_053850

Indo

NM_023973

Vesicle trafficking

RNA processing and ribosomal

Sec24d*

XM_227663

Sytl4

NM_080410

Ear11

NM_138902

Rps24

NM_031112

Other

Trim21*

XM_219011

Ptrh1*

XM_342416

Tekt2*

XM_575908

LOC500847

XM_576239

Vesicle trafficking

Chst1*

XM_575178

Adhfe1*

XM_342794

Eml1*

XM_343109

  

Lypla2

NM_031342

Pigl

NM_138901

Other

LOC365544

XM_345087

Herpud1

NM_053523

LOC499985

XM_575339

Atad2*

XM_235326

LOC367880

XM_579653

  

Smyd2

XM_213972

LOC498435

XM_573687

    

Tpbg

NM_031807

Smpx

NM_053395

    

C4.4a

NM_021759

Mocs1*

XM_236911

    

Abhd1

NM_001008520

Serpinf1

NM_177927

    

Ppic

NM_001004215

Smp2a

NM_012695

    

Aak1*

XM_232172

Rhcg

NM_183053

    

Prss8

NM_138836

Prlph

NM_021580

    

LOC367332

XM_346086

Xylt1

XM_341912

    

Cyp4a10

NM_153307

      

* predicted

Cellular processes changed after formation of aggregates

Results of the GO-based functional classification of transcripts with differential expression between Q23 and Q74 expressing cells 5 days after induction, are presented in Table 2. Only functional categories that were significantly overrepresented (P < 0.05; hypergeometric test) compared to the full list of features present on the array are displayed. The most significant terms for the up-regulated transcripts were in the Biological Process (BP) category: negative regulation of dendrite morphogenesis and fibroblast proliferation, for the Cellular Component (CC) category: antioxidant activity and stress fiber, and for the Molecular Function (MF) category: electron transport activity and chemokine receptor binding. The most significant terms for the down-regulated transcripts were in the BP category: regulation of heart contraction and isoprenoid biosynthesis, for the CC category: endosome membrane and actin cytoskeleton, and for the MF category: double-stranded DNA binding and SH3/SH2 adaptor activity. Apoptosis related transcripts were expressed at higher levels in the Q74 cells, as were transcripts involved in mitochondrial biogenesis and electron transporter activity, and transcripts involved in antioxidant activity. This indicates an increased mitochondrial activity and a response to oxidative stress in our cell model that was already suggested at day 1. Actin and cytoskeletal-related transcripts were mostly decreased in expression in the mutant cell line compared to the wild-type cell line and there was a large transcription regulation component in the down-regulated transcripts. Cholesterol metabolism was also significant in the group of down-regulated transcripts, which is a pathway that was found in earlier gene expression studies in HD [19].
Table 2

Functional classification analysis of genes changed significantly after 5 days of mutant huntingtin expression

Functional Classification with genes that showed an increased expression after 5 days

Functional Classification with genes that showed a decreased expression after 5 days

Ontology

Term

# genes

P value

Ontology

Term

# genes

P value

BP

Negative regulation of dendrite

morphogenesis

3

0,004904

BP

Regulation of heart contraction

7

0,000823

 

Negative regulation of fibroblast proliferation

3

0,004904

 

Isoprenoid biosynthesis

4

0,003744

 

Cell adhesion

16

0,009781

 

Galactose metabolism

3

0,005365

 

Response to DNA damage stimulus

8

0,011782

 

Angiogenesis

9

0,007585

 

Positive regulation of caspase activity

4

0,014506

 

Response to stress

40

0,007784

 

Positive regulation of hydrolase activity

4

0,019419

 

Neg. regulation of transcription

from RNA polII promoter

8

0,007866

 

Apoptotic nuclear changes

3

0,021186

 

Cell motility

18

0,008263

 

Mitochondrial membrane organization

and biogenesis

3

0,021186

 

Pos. regulation of transcription

from RNA polII promoter

10

0,010333

 

Metal ion homeostasis

8

0,021801

 

Actin cytoskeleton organization

and biogenesis

10

0,011951

 

Carbohydrate biosynthesis

6

0,023170

 

Blood vessel morphogenesis

9

0,015755

 

Biopolymer metabolism

38

0,024409

 

Cholesterol metabolism

7

0,016064

 

Fibroblast proliferation

3

0,026721

 

Glucose catabolism

6

0,022220

 

Protein oligomerization

4

0,035235

 

Histogenesis and organogenesis

3

0,024619

CC

Antioxidant activity

5

0,015651

 

Regulation of neuronal synaptic

plasticity

4

0,029030

 

Stress fiber

3

0,017610

 

Somitogenesis

3

0,033500

 

Cytoplasmic membrane-bound vesicle

10

0,019229

 

Synaptic transmission, dopaminergic

3

0,033500

 

Nuclear chromosome

4

0,030424

 

cAMP metabolism

4

0,039722

MF

Electron transporter activity

11

0,001023

 

Neurotransmitter transport

6

0,046079

 

Chemokine receptor binding

6

0,001069

CC

Endosome membrane

3

0,008890

 

Metalloendopeptidase inhibitor activity

3

0,007766

 

Actin cytoskeleton

9

0,033881

 

Selenium binding

4

0,008247

 

Cell projection

13

0,033985

 

Protease inhibitor activity

7

0,013043

 

Cytoplasmic membrane-bound

vesicle

12

0,038151

 

GTPase activity

8

0,013763

 

Mitochondrion

24

0,043218

 

Guanyl nucleotide binding

9

0,040251

 

Spindle

4

0,048198

 

Zinc ion binding

17

0,041022

MF

Double-stranded DNA binding

7

0,001838

244 genes

included in

analysis

    

SH3/SH2 adaptor activity

5

0,004637

     

Oxidoreductase activity, acting

on the CH-CH group of donors

6

0,004683

     

Cell cycle regulator

4

0,005046

     

Epidermal growth factor

receptor binding

3

0,023409

     

Protein phosphorylated amino

acid binding

3

0,023409

     

Actin binding

10

0,026446

     

Monoamine transporter activity

3

0,031878

     

SNAP receptor activity

3

0,031878

     

Carbohydrate kinase activity

4

0,031902

     

Transcriptional activator activity

11

0,045287

    

331 genes

included in

analysis

   

BP: Biological Process.

CC: Cellular Component.

MF: Molecular Function

Besides these significantly changed GO terms, a closer examination of the array data revealed 5 transcripts of the TGF beta signalling pathway significantly down-regulated after 5 days (see Table 3) with the TGF beta transducer Smad4 already down-regulated after 1 day of mutant huntingtin expression. Two out of the eight Smad proteins involved in the TGF beta signalling pathway were down-regulated as well as TGF beta1.
Table 3

Oxidative stress related genes that show a significant change with microarray analysis after mutant huntingtin expression

Nrf2 responsive genes

Gene name

Accession#

Ratio day 0

Ratio day 1

Ratio day 5

P value day 0

P value day 1

P value day 5

 

Detoxification

Nqo1

NM_017000

0,153161338

0,09509419

0,9313329

0,833712475

0,927082425

0,000223519

Gsta4

XM_217195

-0,275666227

-0,314801025

0,413131618

0,253015701

0,120614239

0,006374434

Gstp2

NM_138974

0,382499361

0,418277366

1,459294326

0,30465786

0,189513652

2,28E-07

Antioxidant/reducing Potential

Gclc

NM_012815

0,050889982

0,064489288

0,553224444

0,935159305

0,921933889

0,000668569

Txnrd1

NM_031614

0,043006071

0,068186563

0,416963683

0,920763898

0,85987218

0,000404461

Prdx6

NM_053576

-0,529339334

-0,578113241

-0,680873497

0,084587704

0,038158555

0,003140611

Taldo1

NM_031811

0,009418008

0,032634451

-0,237774271

0,986167462

0,947870016

0,026954523

Me1

NM_012600

-0,000528861

0,013155505

0,269261838

0,998825398

0,98787689

0,021535996

Gene name

Accession#

Ratio day 0

Ratio day 1

Ratio day 5

P value day 0

P value day 1

P value day 5

 

TGF beta signalling pathway

Bambi

NM_139082

-0,039617538

-0,026338592

-0,864880442

0,977785277

0,990188964

0,00336128

Smad4

NM_019275

-0,203348936

-0,40795009

-0,373068895

0,356782837

0,006017924

0,003289649

Map3k1

NM_053887

-0,299368715

-0,358856734

-0,690663403

0,55056724

0,382654757

0,004166232

Tgfb1

NM_021578

-0,126020083

-0,168731098

-0,366913617

0,684930689

0,490885028

0,004166232

Madh7 (smad7)

NM_030858

-0,264074403

-0,230874139

-0,588447764

0,720614387

0,784042896

0,049193592

Oxidative stress

Epas1

NM_023090

-0,270174359

-0,478814403

-1,093139357

0,688153639

0,259648489

0,000173015

Frd1

XM_574642

0,131200174

0,166324378

0,387371459

0,560092481

0,355116774

0,000497262

Mt3

NM_053968

0,415104171

0,340566391

1,552629091

0,456685437

0,588382185

4,64E-06

Gpx1

NM_030826

0,118639332

0,007736138

0,307368335

0,5834878

0,991968688

0,002399689

Electron transport activity

Nqo1

NM_017000

0,153161338

0,09509419

0,9313329

0,833712475

0,927082425

0,000223519

Cyb561

XM_221030

-0,028644328

-0,034319208

-0,617267222

0,977340962

0,978641469

0,003179802

Cxcl10

NM_139089

0,113398034

0,222659258

1,175083864

0,855674156

0,616446381

1,06E-06

Phgdh

NM_031620

0,019449285

0,127790463

0,21275382

0,963270227

0,538281599

0,044674848

Akr1b4

NM_012498

0,211752133

0,205849841

0,441397541

0,661683708

0,680952818

0,037660927

▲: increased expression; : decreased expression; underscore means P value<0.05

Dopamine biosynthesis critically affected

Further examination of the dopamine biosynthesis pathway by qRT-PCR revealed 5 genes involved in the dopamine biosynthesis expressed at lower levels in the mutant cell line compared to the wild-type cells (see Figure 1A).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2199-9-84/MediaObjects/12867_2008_Article_341_Fig1_HTML.jpg
Figure 1

Down regulation of the dopamine biosynthesis pathway in the PC12 model of Huntington's disease. A: qRT-PCR was performed on samples from Q 23 and Q74 cells for 0, 1 and 5 days. All values are expressed as relative mRNA levels compared to expression levels of uninduced cells. SPR: Sepiapterin reductase, GCH1: GTP cyclohydroxylase 1, TH: Tyrosine hydroxylase, DDC: Dopa decarboxylase, DBH: Dopamine β-hydroxylase. * Significant differences between the day 1 and 5 days; * P < 0.05, **P < 0.005, ***P < 0.0005 student's t-test. Significant differences between Q23 on day 1 and Q74 on day 1; + P < 0.05, ++P < 0.005 student's t-test. B: Confocal microscopic images of Q23 and Q74 PC12 cells after 5 days of induction. Green represents huntingtin-GFP and red represents TH immunohistochemistry. In Q23 cells, both huntingtin and TH show a diffuse staining, while in Q74 cells, large aggregates are visible and a clear reduction of TH fluorescence. Scale bar = 25 μm. C: Western blot analysis on whole cell lysates of Q23 and Q74 cells with TH and β-actin as loading control. A clear reduction in TH level can be seen in the 5 day Q74 samples. D: HPLC measurements in whole cell lysates of Q23 and Q74 cells after 0, 1 and 5 days of huntingtin expression show a significant reduction in dopamine levels in the 5 day Q74 samples. (* P < 0.05, student's t-test).

To analyze the effect of these mRNA changes on protein level, the TH protein was examined by immunohistochemistry on cultured cells revealing a diffuse cytoplasmic localization in the cells expressing wild type and mutant huntingtin but there was a marked decrease of TH fluorescence in mutant cells (see Figure 1B). This reduction in TH was confirmed by Western blotting of cell lysates from independent isolations and a representative result is shown in Figure 1C. This decrease in TH resulted in a significant decrease in dopamine levels after 5 days in the cells expressing mutant huntingtin as measured by HPLC (see Figure 1D).

Oxidative stress

Many oxidative stress-related transcripts were up-regulated and several classic Nrf2 (NF-E2 related factor 2/Nfe2l2) responsive transcripts and oxidative stress related genes (see Table 3) were differentially expressed after analysis of the gene expression array.

Nrf2-responsive genes have been identified in previous studies in cultures of primary cortical astrocytes and primary neuronal cultures and were classified as genes involved in the antioxidant and detoxification response, transcription, growth, inflammation and signalling pathways [2022]. Interestingly, most Nrf2-responsive transcripts involved in detoxification and antioxidant/reducing potential were increased in expression in the present study, while Nrf2-responsive transcripts involved in transcription, growth, inflammation and signalling pathways were not changed or expressed at lower levels in the mutant cells. Subsequently, Nrf2-responsive genes involved in antioxidant/reducing potential as well as some non-Nrf2 responsive genes involved in protection against oxidative stress were further examined by qRT-PCR analysis. This analysis included additional oxidative stress related genes that were present on the microarray but where the change in gene expression did not reach statistical significance. Increased Nrf2-responsive transcripts that have a protective role in the metabolic detoxification of reactive intermediates are shown in Figure 2A. Nrf2-responsive genes that act as antioxidants and are reducing agents that prevent oxidative reactions that were expressed at higher levels in the mutant cell line are shown in Figure 2B. While most Nrf2-responsive genes were up-regulated, Hmox1, Taldo1 and Prdx6 were down-regulated.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2199-9-84/MediaObjects/12867_2008_Article_341_Fig2_HTML.jpg
Figure 2

Nrf2-responsive genes and oxidative stress related genes were examined by quantitative real-time PCR on samples from cells expressing wild type (Q23) and mutant (Q74) huntingtin for 0, 1 and 5 days. All values are expressed as relative mRNA levels compared to expression levels on day 0 (uninduced cells) with β-actin and Ywhaz as reference genes. A: Nrf2 and Nrf2-responisve genes involved in detoxification. NRF2: NF-E2 related factor 2, NQO1: NAD(P)H dehydrogenase quinone 1, GSTA4: glutathione S-transferase alpha 4, GSTP2: glutathione S-transferase pi2. B: Nrf2-responsive genes involved in antioxidant/reducing potential. CAT: catalase, GCLC: the catalytic subunit of glutamate-cysteine ligase, GCLM: the modifier subunit of glutamate-cysteine ligase, HMOX1: heme oxygenase 1, TALDO1: transaldolase 1, FTL1: ferritin light chain, Me1: malic enzyme 1. C: Non-Nrf2 responsive genes involved in protection against oxidative stress. GPX1: glutathione peroxidase, SOD1: superoxide dismutase 1, SOD2: superoxide dismutase 2, MT3: metallothionein 3. * Represents significant differences between the day 1 and day 5 time points (* P < 0.05, **P < 0.005, ***P < 0.0005 student's t-test). + Represents significant differences.

Other transcripts, not identified as Nrf2- target genes, but important antioxidant enzymes involved in the protection against oxidative stress, that were also expressed at higher levels in the mutant cell line are shown in Figure 2C. Finally, several transcripts involved with electron transport activity were expressed at higher levels on the array in the cells expressing mutant huntingtin (see Table 3).

Discussion

To identify groups of genes that could play a role in the pathology of HD, we studied mRNA changes in an inducible PC12 HD model before and after aggregates became visible. GO term analysis revealed many similarities with previous human and whole animal gene expression studies indicating that this model system is useful to study pathological markers for HD [6, 7, 23, 24]. This is the first study to show the involvement of Nrf2-responsive genes in the oxidative stress response in HD. Oxidative stress related transcripts were altered in expression, suggesting a protective response in cells expressing mutant huntingtin at an early stage of cellular pathology. Furthermore, there was a down-regulation of dopamine biosynthesis resulting in lower dopamine levels in culture. Our results further demonstrate an early impairment of transcription, the cytoskeleton, ion channels and receptors.

Since it is not feasible to study early mRNA changes in humans and it is more difficult to detect mRNA changes in early stage mouse models of HD compared to later stages [10], cell models are important to study the early pathological cellular events in HD. Although cell models are a simplified representation of the disease, it is less likely that pathological markers are masked by secondary disease processes and heterogeneous cell populations. Notably, in the present study, the majority of transcripts that changed on day 1 showed an increase in expression, which is in contrast with previous studies where it was found that most transcripts were decreased in expression at the early stages in a mouse model of HD [7, 23, 24]. After 5 days of mutant huntingtin expression, more transcripts were significantly changed compared to 1 day, and the ratio of transcripts that increased to transcripts that decreased in expression was approximately 1:1, which is in agreement with previous findings [7]. This suggests that up-regulation of transcription may be more important in early HD pathology than previously appreciated. The relevance of studies on mRNA level for the identification of changes in biological processes is demonstrated for the dopamine biosynthesis pathway, for which we showed that a decrease in mRNA levels leads to concomitant changes in dopamine levels.

We found early signs of oxidative stress with a differential expression of mitochondrial, electron transport and oxidative stress related transcripts. The oxidative stress-response became more obvious after 5 days where transcripts of the Nrf2-ARE pathway were expressed at higher levels in the cells expressing mutant huntingtin. Genes containing the antioxidant response element (ARE) can be activated by Nrf2 in response to oxidative stress [25] in what is called the antioxidant response pathway [26].

Although there has been extensive evidence for a role of oxidative stress early in HD pathogenesis [27] and an age-dependent induction of compensatory mechanisms in response to oxidative stress has been found in the R6/2 mouse model of HD[28], this is the first study implicating Nrf2-responsive genes. While the majority of Nrf2-dependent transcripts increased in expression after the induction of mutant huntingtin, there were two transcripts that showed a validated decreased expression. Thus, only a subset of Nrf2 responsive genes is altered, possibly due to a different combination of transcription factor binding sites [29].

Mitochondrial dysfunction possibly contributes to this oxidative stress, since this is thought to lead to decreased production of ATP and an increase in reactive oxygen species (ROS), ultimately leading to cell damage and cell death [30]. A defect in mitochondrial complexes as well as an increase in oxidative damage products has been found in previous studies [28, 31, 32] and is in agreement with our findings of an increase in transcripts involved in electron transport activity and oxidative stress response in cells expressing mutant huntingtin.

We also found that the DNA repair gene Transaldolase1, which promotes DNA stability and repair [33], was expressed at lower levels in mutant cells compared to wild-type cells in the current study. This is in agreement with increased DNA oxidative damage products that have been found in post mortem HD brain tissue [34, 35].

That activation of the Nrf2 pathway can ameliorate the effects of oxidative stress was shown when induction of Nrf2-mediated transcription could protect cells from mitochondrial complex II inhibition [36] and defects in complex II have been implicated in HD [34, 37, 38]. Indeed, a study using an in vitro model of PD showed that activation of the Nrf2-ARE pathway protected against 6-hydroxydopamine neurotoxicity [39].

Conclusion

Combined micro array studies thus provide ample evidence for the induction of a protective oxidative stress response in cells expressing mutant huntingtin in an early stage of the pathology [27]. This response may ultimately be insufficient to protect cells from oxidative damage, contributing to the massive cell death seen in HD brains. Oxidative stress is thought to play a role in the pathogenesis of several other neurodegenerative diseases [40] and Nrf2 has been implicated in the pathology of Alzheimer's and Parkinson's disease. Given the pathogenic impact of oxidative stress and neuroinflammation, the Nrf2-ARE signalling pathway is an attractive therapeutic target for neurodegenerative diseases and warrants further studies.

Declarations

Acknowledgements

The authors wish to thank M. Frölich, LUMC department of Clinical Chemistry, for her help with the HPLC experiments, D.C. Rubinsztein, Cambridge Institute for Medical Research for the inducible PC12 HD cell line and the LUMC department of Molecular Cell Biology for the use of their microscopic facilities. Funding was provided by the Leiden University Medical Center.

Authors’ Affiliations

(1)
Center for Human and Clinical Genetics
(2)
Department of Neurology
(3)
Leiden Genome Technology Center, Leiden University Medical Center
(4)
Department of Clinical Genetics, Vrije Universiteit Medical Center

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© van Roon-Mom et al; licensee BioMed Central Ltd. 2008

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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