Neuroscience 294 (2015) 29–37

SPATIAL COGNITIVE DEFICITS IN AN ANIMAL MODELOF WERNICKE–KORSAKOFF SYNDROME ARE RELATEDTO CHANGES IN THALAMIC VDAC PROTEIN CONCENTRATIONS

K. O. BUENO, a L. DE SOUZA RESENDE, a A. F. RIBEIRO, a

D. M. DOS SANTOS, c E. C. GONCALVES, b F. A. B. VIGIL, a

I. F. DE OLIVEIRA SILVA, d L. F. FERREIRA, a

A. M. DE CASTRO PIMENTA c AND A. M. RIBEIRO a*

aDepartamento de Bioquımica e Imunologia, Laboratorio de

Neurociencia Comportamental e Molecular, LaNeC, Instituto de

Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo

Horizonte, Minas Gerais 31270-010, Brazil

bDepartamento de Genetica, Laboratorio de Polimorfismo de

DNA, Instituto de Ciencias Biologicas, Universidade Federal do

Para, Belem, Para 66075-000, Brazil

cDepartamento de Bioquımica e Imunologia, Laboratorio de

Venenos e Toxinas Animais, LVTA, Instituto de Ciencias

Biologicas, Universidade Federal de Minas Gerais, Belo

Horizonte, Minas Gerais 31270-010, BrazildDepartamento de Analises Clınicas e Toxicologicas – Faculdade

de Farmacia, Universidade Federal de Minas Gerais, Belo

Horizonte, Minas Gerais 31270-010, Brazil

Abstract—Proteomic profiles of the thalamus and the cor-

relation between the rats’ performance on a spatial learning

task and differential protein expression were assessed in

the thiamine deficiency (TD) rat model of Wernicke–

Korsakoff syndrome. Two-dimensional gel-electrophoresis

detected 320 spots and a significant increase or decrease

in seven proteins. Four proteinswere correlated to rat behav-

ioral performance in the Morris Water Maze. One of the four

proteins was identified by mass spectrometry as Voltage-

Dependent Anion Channels (VDACs). The association of

VDAC is evident in trials in which the rats’ performance

was worst, in which the VDAC protein was reduced, as con-

firmed by Western blot. No difference was observed on the

mRNA of Vdac genes, indicating that the decreased VDAC

expression may be related to a post-transcriptional process.

http://dx.doi.org/10.1016/j.neuroscience.2015.03.0010306-4522/� 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

*Corresponding author. Address: Avenida Presidente Antonio Carlos,6627, FaFiCH, sala F1002, Pampulha, Belo Horizonte, Minas GeraisCEP: 31270-901, Brazil. Tel: +55-31-34092642; fax: +55-31-99838401.

E-mail addresses: Keniaobueno@gmail.com (K. O. Bueno),leticiasresende@gmail.com (L. de Souza Resende), andreafron@gmail.com (A. F. Ribeiro), santosdm@gmail.com (D. M. dos Santos),ecostag@ufpa.br (E. C. Goncalves), fabio_vigil@yahoo.com.br(F. A. B. Vigil), iedafos@farmacia.ufmg.br (I. F. de Oliveira Silva),liviafreiref@yahoo.com.br (L. F. Ferreira), apimenta@icb.ufmg.br(A. M. de Castro Pimenta), angelamr@icb.ufmg.br (A. M. Ribeiro).Abbreviations: 2D SDS–PAGE, two-dimensional sodium dodecylsulfate–polyacrylamide gel electrophoresis; VDACs, Voltage-Dependent Anion Channels; ATN, anterior thalamic nuclei; IML,internal medullary lamina; IPG, immobilized pH gradient; MWM,Morris Water Maze; PCR, polymerase chain reaction; PTD,pyrithiamine-induced TD; TD, thiamine deficiency; WE, Wernicke’sEncephalopathy; WKS, Wernicke–Korsakoff syndrome.

29

The results show that TD neurodegeneration involves

changes in thalamic proteins and suggest that VDAC protein

activity might play an important role in an initial stage of the

spatial learning process. � 2015 IBRO. Published by Elsevier

Ltd. All rights reserved.

Key words: thiamine deficiency, spatial learning, thalamus,

proteomic, VDAC, rats.

INTRODUCTION

Thiamine deficiency (TD) can lead to a neurological

disorder termed Wernicke’s Encephalopathy (WE),

characterized by acute confusion, ataxia, and eye

movement abnormalities (Homewood and Bond, 1999).

In some conditions, WE can evolve into a chronic syn-

drome named Wernicke–Korsakoff syndrome (WKS)

(Hazell and Butterworth, 2009).

The pathophysiology underlying TD is multifactorial in

nature, involving a broad cascade of events that ultimately

result in focal neuronal cell death similar to the

pathological mechanisms inherent in neurodegenerative

diseases (Jhala and Hazell, 2011). Focal brain lesions

similar to those that occur in patients with WE/WKS can

be experimentally induced in rodents using pyrithiamine-

induced TD (PTD) combined with a thiamine-deficient diet

(Watanabe, 1978; Beauchesne et al., 2010).

The results of previous studies carried out by our

group (Pires et al., 2005) and other authors (Langlais

and Savage, 1995), using the PTD model, have shown

that this vitamin deficiency induces spatial learning and

memory deficits. Diencephalic amnesia produced by TD

is consistently associated with neuropathology in the

anterior and midline thalamic nuclei, mammillary bodies,

and the mammillothalamic tract (Langlais et al., 1992).

The morphological injuries caused by TD are

preceded by functional changes in neurotransmission

systems, among them, the serotonergic (Nakagawasai

et al., 2007a), dopaminergic (Nakagawasai et al.,

2007b), glutamatergic (Savage et al., 1999), GABAergic

(Butterworth, 1989) and cholinergic (Savage et al.,

2003; Pires et al., 2005; Vetreno et al., 2008) systems.

However, the molecular mechanisms underlying the neu-

rodegeneration process associated with TD are still

unknown.

Proteomics is a high-throughput protein analysis that

enables us to detect, simultaneously, large numbers of

30 K. O. Bueno et al. / Neuroscience 294 (2015) 29–37

differentially expressed proteins in samples obtained from

several sorts of diseased tissue (Verrills, 2006). By

identifying changes in protein expression in the thalamus,

hypotheses may be drawn from molecular mechanisms

underlying these alterations as to how TD may cause

structural and functional brain damage.

The purposes of the present study were to verify the

effects of severe TD on the proteomic profile of the

thalamus and to assess the correlation between rat’s

performance on a spatial learning task and thalamic

protein level change. A second goal was to identify the

proteins that showed differential expression between

groups and to correlate them with the latency of finding

the platform of Morris Water Maze (MWM).

EXPERIMENTAL PROCEDURES

Animals and treatments

Thirty-two Wistar male rats, approximately 2 months old

were individually housed in a 12/12-h light/dark cycle,

and divided into two groups: (i) Control (C, n= 16), in

which the rats received a standard control diet

associated with daily saline i.p. injections and (ii)

pyrithiamine-induced TD (PTD, n= 16), in which the

rats received a thiamine-deficient diet associated with

daily i.p. injections of pyrithiamine (0.25 mg/kg), which is

an inhibitor of the enzyme that is responsible for the

production of the active form of thiamine. The episode

of TD was interrupted after the onset of the last

neurological signs, i.e., seizures and impaired righting

reflexes, by the administration of two i.p. injections of

thiamine (100 mg/kg each) at an 8-h interval. After

treatment, all subjects were housed two per cage with

unlimited access to water and regular chow. Following

three weeks of recovery, PTD and C rats were trained

and tested in the MWM task (Morris, 1984; Carvalho

et al., 2006). The data obtained from this spatial cognitive

test were published elsewhere (Vigil et al., 2010).

On the first day following the behavioral tests, rats

were decapitated, their brains removed, and the

thalamus dissected from one hemisphere and stored at

�80 �C for use in proteomic analysis, as described

below. One additional experiment (total rats, n= 14)

was carried out using other groups of rats, which were

submitted to the same treatments (Control and PTD).

The thalamus samples from one of the brain

hemispheres obtained from the animals of both groups

were used for Western blot (n= 14) and real-time

polymerase chain reaction (PCR) analyses (n= 10).

The care and use of rats were in accordance with the

National Institute of Health Guide for Care and Use of

Laboratory Animals (Institute of Laboratory Animal

Resources Committee, 1985).

Protein separation by two-dimensional sodiumdodecyl sulfate–polyacrylamide gel electrophoresis(2D-SDS–PAGE)

The proteomic profile of the thalamus was analyzed using

2D SDS–PAGE. Samples were prepared as described

previously with some modifications (Paulson et al.,

2004). Briefly, eight thalamus samples selected randomly

(PTD, n= 4; Control, n= 4) were individually homoge-

nized, delipidized in chloroform/methanol/water (4/8/3 v/

v/v), mixed continuously for 1 h, and centrifuged (2000g,10 min). The supernatant, containing the lipids, was dis-

carded and the extraction procedure was repeated twice.

The pellet was air-dried in ±4 �C overnight, and then dis-

solved in a100-ll sample buffer (7 M urea, 2 M thiourea,

1% C7bZO� (Sigma) and 40 mM Tris). The samples were

incubated for 4 h, centrifuged (5000g, 5 min), and the

supernatant was collected. The total protein concentration

of the supernatant of each sample was measured using

the Lowry assay (Lowry et al., 1951).

A 2D SDS–PAGE protocol was followed as described

previously (Wildgruber et al., 2000). Immobilized pH

gradient strips (IPG strips, 7 cm, pH 3–11 NL) (GE

Healthcare, Pittsburgh, Pennsylvania, USA) were

passively rehydrated with samples containing 250 lg of

protein in 130 -ll rehydration buffer (Urea 7 M, Thiourea

2 M, 2% 3-[(3-cholamidopropyl)-dimethylammonio]-1-

propanosulfonate hydrate (CHAPS), 0.5% IPGs buffer,

0.002% Bromophenol Blue) for 12 h at room temperature.

The proteins in the rehydrated strips were focused using

the IPGphor isoelectric focusing (IEF) system

(Pharmacia Biotech, San Francisco, CA, USA). Prior to

the second dimension, the IPG strips were equilibrated

for 15 min in a 5 -ml equilibration buffer (75 mM Tris–

HCl, pH 8.8, 6 M Urea, 30% Glycerol, 2% SDS, 0.002%

Bromophenol Blue) containing 1% Dithiothreitol

(Promega�) and then with another 5 mL of equilibration

buffer containing 2.5% Iodoacetamide (Sigma�) for

15 min.

Second-dimension separation was performed on

12.5% SDS–PAGE using the miniVE Vertical

Electrophoresis System (Amersham Biosciences, San

Francisco, CA, USA). The gel was stained using

colloidal Coomassie Blue Protein (G250-Sigma�)

according to the supplier’s protocol.

Image analysis

The gels were scanned on the Image Master Labscan v.

3.01 (with a resolution of 300 dpi) and Image Master 2D

Platinum (Amersham Biosciences) software was used

for matching and analyzing protein spots on 2D SDS

gels. The gel with the highest number of spots was

defined as the ‘‘reference gel’’ which was used to create

a master image for the matching of corresponding

protein spots. Background subtraction was performed

and the intensity volume of each individual spot was

normalized. In the normalization process the optical

intensity of each spot was measured by the sum of

‘‘pixels’’ within the area of the spot (spot volume) and

then converted to a percentage relative to the total

intensity of the spots detected in the corresponding gel.

Thus, the amount of protein was expressed as the

relative percentage of spot volume.

In-gel tryptic digestion

The protein spots were manually excised from stained 2D

SDS gels with a scalpel blade and the spots were

K. O. Bueno et al. / Neuroscience 294 (2015) 29–37 31

incubated in 200 ll of 200 mM Ammonium bicarbonate/

Acetonitrile solution (ACN; 40:60) twice at 37 �C for

30 min each. The gel pieces were dried for 30 min in a

vacuum-centrifuge, rehydrated in a 20-ll chilled

digestion buffer (20 lg/ml trypsin (Sigma) in 100 lMHCl; 40 mM Ammonium bicarbonate in 9% Acetonitrile

solution) for 60 min and then incubated at 37 �C in this

same solution overnight. Peptides were extracted with

50% Acetonitrile/0.1% Trifluoroacetic acid and desalted

and concentrated using C18 ZipTips (Millipore, Billerica,

MA, USA).

Mass spectrometric analysis and proteinidentification

Mass spectrometry (MS) analysis was performed on

a MALDI-TOF-TOF Autoflex III spectrometer (Bruker-

Daltonics, Bremen, Germany). Extracted peptides

(0.5 ll) were spotted onto an AnchorChip� 600/384

(BrukerDaltonics, Bremen, Germany) target microtiter

plate (MTP), mixed with a saturated solution of

a-cyano-4-hydroxycinnamic acid (0.5 ll) and allowed

to crystallize at room temperature. Samples were

analyzed by matrix-assisted laser desorption/ionization

time-of-flight (MALDI-TOF/TOF). The MS and the MS/

MS spectra were acquired in the reflector mode with

external calibration, using the calibration mixture

Peptide Calibration Standard II (BrukerDaltonics,

Bremen, Germany). The MS and MS/MS data were

submitted to a MASCOT (http://www.matrixscience.com,

downloaded, May 20, 2013). The search parameters

were as follows: database, NCBI non redundant:

taxonomy, Rattus: type of search, peptide mass

fingerprint combined with MS/MS ion search; amino acid

sequence, enzyme, trypsin; fixed modification,

carbamidomethylation (Cys); variable modifications,

oxidation (Met); mass values, monoisotopic; peptide

charge state, (1) maximum missed cleavages, (2) and a

peptide mass tolerance of 0.05% Da (50 ppm).

Western blotting

After electrophoresis, proteins were transferred to a

nitrocellulose membrane (Millipore, Billeria, MA, USA).

Following, blocking non-specific binding with 10% non-fat

milk in TBS with 0.05% Tween-20 (TBS-T) overnight,

membranes were incubated 2 h at room temperature with

anti-VDAC (0.1:1000) antibodies (Catalog Number-

AB10527 Millipore). After three washes with TBS-T, blots

were incubated 1 h at room temperature with HRP-

conjugated anti-rabbit (0.2:1000) antibodies (Catalog

Number-AQ132P Millipore) (Ribeiro et al., 2010). After

three washes with TBS-T, blots were developed with ECL

and exposed to films. The density of the spots was ana-

lyzed using the Image J program (http://imagej.nih.gov/ij).

Molecular analysis

For the RNA extraction, the samples (PTD, n= 5; C,

n= 5) were thawed, and total RNA was extracted using

TRIzol� according to the manufacturer’s protocol

(Invitrogen, Sao Paulo, Brazil). Samples were quantified

using NanoDrop� ND-2000v3 1.0 (Thermo Fisher

Scientific, Waltham, MA, USA). The minimum

acceptable 260:280 nm ratio was >1.6.

The reverse transcription was performed in a total

volume of 20 ll using 2 lg of total RNA and oligo (dT20)

primers (ExxtendBiotecnologia Ltda., Paulinia, Brazil).

RevertAid� H Minus (Fermentas, Sao Paulo, Brazil) was

used according to the manufacturer’s protocol.

To the real-time PCR, the reactions from the extracted

samples of the thalamus of control and deficient rats were

made in 7900HT� Fast Real Timer PCR (Applied

Biosystems, Sao Paulo, Brazil) utilizing SYBR� Green

PCR Master Mix (Applied Biosystems, Sao Paulo,

Brazil). PCR amplification was performed without the

extension step (95 �C for 10 min, followed by 40 cycles

of 95 �C for 15 s and 60 �C for 60 s). Fluorescence

acquisition was measured in the last step of each cycle

(60 �C).Data were analyzed using 7900HT (Applied

Biosystems) software and a Microsoft Excel spreadsheet.

The minimum acceptable correlation coefficient was 0.98.

In all reactions, a negative control without sample was

tested. Melting curves were examined to guarantee the

absence of any spurious products. To normalize mRNA

levels, two reference genes (Ppia, peptidylprolyl

isomerase A; Hprt, hypoxanthine phosphoribosyltrans-

ferase) were used, and the relative quantity was

calculated following Vandesompele et al. (2002).

Primer design – Exon sequences were obtained from

the National Center for Biotechnology Information

database (http://www.ncbi.nlm.nih.gov, Vdac1: NM

031353.1, Vdac2: NM 031354.1, Vdac3: NM 031355.1,

accessed 16 September 2013). Primer sequences were

designed using Primer3 v.0.4.0 (Rozen and Skaletsky,

2000), and the quality and specificity of the primer

pairs were examined using NetPrimer (http://www.

premierbiosoft.com/netprimer/netprlaunch/netprlaunch.

html) and Primer-BLAST (http://www.ncbi.nlm.nih.gov/tools/

primer-blast/index.cgi?LINK_LOC=BlastHome)), respec-

tively. All primers were positioned in inter-exon regions.

Primers were synthesized by Exxtend (ExxtendBio

tecnologia, Paulinia, Brazil). The primers had the following

sequences: Vdac1F 50-TGGCTACAAGACGGACGAAT-

30; Vdac1R 50-CAGGCGAGATTGACAGCAG-30; Vdac2F50-GGCTACAGGACTGGGGACTT-30; Vdac2R 50-CCTG

ATGTCCAAGCAAGGTT-30; Vdac3F 50-TTGACACAGCC

AAATCCAAA-30 and Vdac3R 50-CCTCCAAATTCAGTG

CCATC-30. For the reference genes, primers had the

following sequences: PpiaF, 50-CAAACACAAATGGTTC

CCAGT-30; PpiaR 50-GCTCATGCCTTCTTTCACCT-30;

HprtF 50-CAGGCCAGACTTTGTTGGAT-30; HprtR 50-TCC

ACTTTCGCTGATGACAC-30.

Statistical analysis

Significant differences in protein expression between PTD

and C were assessed using the Student t-test. The

behavioral performance in the spatial navigation task

was analyzed using a two-way ANOVA with repeated

measures on the last element (2 � 5 factorial design:

two kinds of diet and five training sessions). Regression

analyses were used to determine the degree to which

Fig. 1. Two-dimensional gel-electrophoresis assays illustrating the

qualitative analysis of the rat thalamus proteins. The sixteen encircled

proteins indicate qualitative differences and the arrows indicate seven

proteins differentially expressed between C (n= 4) and PTD groups

(n= 4). The proteins were separated on pH 3–11 nonlinear immobi-

lized pH gradient strips, followed by a second-dimension separation

on 12.5% SDS–polyacrylamide gels.

32 K. O. Bueno et al. / Neuroscience 294 (2015) 29–37

biochemical and behavioral performance in each session

was linearly correlated. The normal distribution was

tested using the Kolmogorov–Smirnov test. For real-time

PCR data, besides the Kolmogorov–Smirnov test,

homoscedasticity of variance by the Lilliefors test was

also used. The relative amount of mRNA normalized for

each candidate gene was compared using a t-test for

independent samples. All values are expressed as

mean and the level of significance was p< 0.05. Real-

time PCR data analyses were performed with the

STATISTICA v. program. 6.1 (Stasoft, Sao Caetano do

Sul, Brazil).

RESULTS

MWM task

As published elsewhere (Vigil et al., 2010), significant

main effects of TD (F(1,30) = 6.00; p= 0.02) and sessions

(F(4,120) = 27.06; p= 0.00) were observed. Statistical

analysis also showed that the performance of rats from

the control group was significantly better compared to that

of the thiamine-deficient rats in the third (t= 2.7,

p= 0.01) and the fourth (t= 3.6, p= 0.001) sessions.

Although thiamine-deficient rats showed a slower acquisi-

tion performance than control rats, they were able to learn

the task, as in the fifth session there was no significant dif-

ference (t= 1.0, p= 0.33) between the performances of

rats from the two groups.

Image analysis

The thalamic proteomic data showed that 320 spots were

expressed in the average gel of each group. This means

that in the range of the analysis employed here there was

no difference between the numbers of proteins expressed

in the thalamus of C and PTD rats (Fig. 1).

Seven thalamic proteins were found to be differentially

regulated as a function of TD. Among them, the levels of

three increased and the levels of four decreased (Fig. 2).

Linear regression analysis

The results of linear regression between the performance

of the rats in the MWM task and the levels of each of the

seven altered thalamic proteins showed that four proteins

correlate with the latency to find the platform in the third

session of MWM (Fig. 3), the session in which the rats

showed the worst performance during the learning

process. Negative correlation was found between the

relative volume of spots 7868 (r= �0.77, p= 0.02),

7869 (r= �0.86, p= 0.005) and 8105 (r= �0.83,p= 0.009) and latency in the third session. On the

other hand, the protein spot 8096 was positively

correlated with the latency in the third section (r= 0.90,

p= 0.002). No significant correlation was found for the

other three proteins (spots 7858, 8123 and 8228).

Mass spectrometric analysis and proteinidentification

Through mass spectrometry the protein of the 8105 spot

was characterized. The MASCOT identified it as VDACs

(Voltage-Dependent Anion Channels) with score 50

(p< 0.005)/NCBI: 20130519. Mass: 30851. Type of

search: MS/MS Ion Search. Instrument type: MALDI-

TOF-TOF. Fig. 4A shows a descriptive table of the

identified protein. The remaining proteins could not be

identified.

Western blotting

To confirm 2D SDS–PAGE results, seven thalamus

samples from PTD rats and seven from control rats

were further analyzed by Western blot. The specificity of

the antibodies against VDAC was verified by Western

blot. Western blot results showed that the protein spot

corresponding to the protein spot features identified by

2D SDS–PAGE were decreased in the PTD rats

compared with the control rats (p= 0.029) (Fig. 4B, C).

These results confirmed the data obtained by 2D SDS–

PAGE analysis and protein identification by MS.

Molecular analysis

No differences in mRNA levels of Vdac genes were

observed between the groups (tVdac1 = �0.32,p> 0.05; tVdac2 = �0.43, p> 0.05; tVdac3 = �0.90,p> 0.05).

DISCUSSION

As described by Vigil et al. (2010), thiamine-deficient sub-

jects showed an impaired performance in the water maze

Fig. 2. Proteins with significant differences between C (n= 4) and PTD (n= 4) groups (p< 0.05).

K. O. Bueno et al. / Neuroscience 294 (2015) 29–37 33

spatial test, although these rats were able to learn the

task by the fifth session. This result is consistent with pre-

vious findings obtained by our group (Pires et al., 2005)

and other authors (Langlais and Savage, 1995; Mumby

et al., 1999) in which thiamine-deficient rats showed spa-

tial-learning deficits. The spatial cognitive performance is

mainly associated with the hippocampus (Morris et al.,

1990; Moser et al., 1995; Yu et al., 2013) and, as far as

we know, this study is the first to show that rat’s perfor-

mance in the MWM task is related to changes in the levels

of proteins in the thalamus.

According to Aggleton and Brown (1999) the link from

the hippocampus to the mammillary bodies and anterior

thalamic nuclei (ATN), via the fornix, is critical for normal

episodic memory. Moreover, damage to this axis is

responsible for the core deficits in anterograde amnesia

(Aggleton and Sahgal, 1993; Savage et al., 2011).

A number of studies have been conducted to

determine the role of the thalamus in diencephalic

amnesia produced by TD. Damage to internal medullary

lamina (IML) and ATN have been reported to underlie

learning and memory impairments observed in

Fig. 3. Scatter plot of the volume of each thalamic protein and the behavioral performance expressed as latency to find the platform in the third

session of MWM task. Negative correlations were found between the relative volume of spots (n= 8).

34 K. O. Bueno et al. / Neuroscience 294 (2015) 29–37

PTD-treated rats (Langlais et al., 1992; Langlais and

Savage, 1995). Langlais et al. (1992) showed that PTD

rats without IML gliotic scarring display a learning curve

in the MWM similar to the control rats, while PTD rats with

IML lesions have longer latencies. The ATN are also

important for learning and memory as damage to this

region produces a persistent amnestic syndrome. There

is evidence for considerable neuronal loss (50–90%) in

the ATN following acute PTD treatment (Langlais and

Savage, 1995). Complete lesions of the ATN impair perfor-

mance on two behavioral tests to assess hippocampal-

dependent learning and memory (spontaneous alternation

and delayed alternation tests). In contrast, incomplete

ATN lesions do not impair spontaneous alternation perfor-

mance (Savage et al., 2011).

Long-term neurochemical alterations within the

thalamus and its involvement in the cognitive

impairments in the PTD model have also been reported

after the restoration of thiamine levels. There are

significant reductions in overall GABA and glutamate

levels in the midbrain thalamus (Langlais et al.,

1988).Significant increases in serotonin and its metabolite

were reported by Langlais et al. (1988) after PTD treat-

ment. Vigil et al. (2010) demonstrated a correlation

between a serotonergic thalamic parameter and the

rodent performance in a spatial task, indicating that a

higher thalamic 5-hydroxyindolacetic acid (5-HIAA) con-

centration was associated with poorer performance in

the beginning of the acquisition process.

Although the role of the thalamus in the behavioral

deficits related to TD has been recognized for many

years, the molecular mechanisms underlying these

changes are still unknown. The data of the present

study, besides demonstrating the occurrence of

increased and decreased protein levels in the thalamus

of PTD rats, also indicate that some of these proteins

might have a role in the molecular mechanism involved

in the neurobiology of the spatial learning task.

It is interesting to mention that a significant correlation

between the volumes of the altered proteins was verified

only with the latency to find the platform in the third

session of the MWM task. Following recovery from an

acute bout of pyrithiamine-induced TD, rats are impaired

in their ability to learn a spatial navigation task (third

and fourth sessions) but with additional training, PTD

rats are able to attain latencies similar to those of the

control group. This learning curve showing a cognitive

deficit during the intermediate sessions of training,

followed by a performance recovery – similar to control

rats – in the last session, was previously found by our

group and other authors for PTD (Langlais et al., 1992;

Carvalho et al., 2006) and also for old rats (Oliveira-

Silva et al., 2007; Oliveira et al., 2010). One possible

explanation for these findings is that the learning, which

involves a neurobiological dynamic process, has a kinetic

mechanism in which the intermediate steps are essential

for encoding the information responsible for behavioral

changes. Hence, as a consequence of neurodegenerative

processes, the speed of learning is affected, but during

the training sessions all the rats are able to learn the task.

To our knowledge, this is the first time that the

identified protein, VDAC, has been shown to be related

to thiamin-deficiency dysfunction. However, it is known

that it is implicated in cognitive functions (Weeber et al.,

2002; Levy et al., 2003). VDAC, also known as Porins,

are the most abundant proteins in the mitochondrial outer

membrane (Linden et al., 1984). This protein has a major

function as part of the apoptosis mechanism (Zaid et al.,

2005; McCommis and Baines, 2012) and in the metabolite

transport between the mitochondria and the cytoplasm,

Fig. 4. Protein data. (A) The descriptive data of the identified proteins. (B) Representative image of the Western blot analysis confirming the identity

of spot 8105 as VDAC (arrow). The other spots presumably refer to isoforms of VDAC. (C) Quantitative results of analysis of relative density with a

significant difference between C (n= 7) and PTD (n= 7) groups (p= 0.029).

K. O. Bueno et al. / Neuroscience 294 (2015) 29–37 35

regulating energy metabolism in neurons by maintaining

cellular ATP levels (Colombini, 2004; Shoshan-Barmatz

et al., 2006). Kielar et al. (2009) showed level increases

of VDAC in the thalamus of mouse associated with neu-

rodegeneration in the Batten disease model. On the other

hand, Yoo et al. (2001), in postmortem studies, showed

that patients with Alzheimer’s disease had significantly

decreased levels of VDAC1 (Yoo et al., 2001). Weeber

et al. (2002) showed that the regulation of VDAC activity

may influence important synapse functions in the hip-

pocampus. They found that long-term potentiation

(LTP), a long-lasting enhancement in the amplitude of

synaptic replay that has been correlated with learning

and memory (Malenka and Nicoll, 1999) is significantly

impaired in Vdac1 knockout mice. It is possible that the

altered expression of VDAC modifies synapse function

with consequent interference in learning and memory pro-

cesses. VDAC-deficient mice exhibited significantly worse

performance in some steps of the training than those of

wild-type controls in the MWM task. These results are

similar to those obtained by our group using thiamine-

deficient rats. It is important to mention that in addition

to the hippocampal and thalamic areas, there are other

brain areas that play roles in memory and spatial learning

processes (Aggleton et al., 2010).Thus, additional pro-

teomic studies would be important in order to determine

if the observed changes shown here are brain region-

specific. Nevertheless, our finding that in severe TD there

is a negative correlation between the VDAC levels in the

thalamus and latency to find the platform in the MWM in

the third session of training indicates that this protein might

play an important role in the neurobiological mechanism

of the initial stage of the spatial acquisition task.

Real-time PCR for Vdac1, Vdac2 and Vdac3 genes

was carried out with the objective to verify whether the

levels of VDAC protein changes were related to the

levels of their corresponding mRNA. No significant

difference among the groups was observed. This result

suggests that the variation in the VDAC levels found in

the present study was not due to changes in the

regulation of RNA expression and, as a result it might

be a consequence of post-translational change. The

absence of a relationship between mRNA transcripts

and the protein expressions can be explained by a

36 K. O. Bueno et al. / Neuroscience 294 (2015) 29–37

post-transcriptional mechanism, which controls the

protein translation rate (Harford and Morris, 1997) and

by the differences in half-lives of specific proteins or

mRNAs (Varshavsky, 1996). One possible explanation

for the observed decrease in the VDAC level induced by

TD could be the occurrence of an increase in Parkin-

mediated Lys 27 poly-ubiquitylation of VDAC, which was

found to be related to neurodegeneration (Geisler et al.,

2010; Burte et al., 2014).

In short, the main findings of the present work are: (i)

TD increased and decreased thalamic protein levels; (ii)

four thalamic protein changes are related to spatial

cognitive performance of rats; (iii) changes in VDAC,

one of the four proteins altered by TD, relate to rats’

spatial learning; (iv) the association of VDAC is evident

in the session with the rats’ worst performance, and (v)

no difference was observed on the mRNA of Vdacgenes, indicating that the decreased VDAC expression

may be related to a post-transcriptional process.

CONCLUSIONS

The present results show for the first time that TD

neurodegeneration involves changes in thalamic

proteins that are related to rat’s performance on spatial

cognitive tasks. We hypothesize that, of the seven

proteins altered by TD described here, four – including

VDAC – might have a role as a molecular component of

the neurobiological substrate of the initial step of the

spatial learning process. In addition, if the training

persists, other biological mechanisms might come into

play to compensate for the early dysfunction and

consequently the behavioral deficits are minimized.

The present data provide a new pathway for the study

of molecular mechanisms related to thiamine-induced

learning and memory impairments. Further experiments

need to be designed to identify and characterize the

other three altered thalamic proteins. Regarding these

three proteins, the present findings allow prioritization of

targets for future mechanistic studies of thalamic protein

involvement in the TD neurodegenerative process.

AUTHOR CONTRIBUTIONS

Ribeiro, A.M., was the general coordinator of the

research, conceived the project, designed the

experiments and analyzed the data.

Bueno, K.O., and Resende, L.S., carried out all the

biochemical experiments.

Vigil, F.A.B., and Oliveira-Silva, I.F., and Ferreira,

L.F., carried out the behavioral tests.

Goncalves, E.C., collaborated with the 2D SDS–

PAGE experiments.

Ribeiro, A.F., was responsible for the real-time PCR

experiments and data analysis.

Pimenta, A.M.C., and Santos, D.M., collaborated on

the Mass Spectrometry analysis.

Ribeiro, A.M., Resende, S.R., and Bueno, K.O.,

conducted the data analysis and wrote the manuscript.

Acknowledgments—This research was supported by CAPESThe

role of VDAC in cell death: frien (Coordenacao de

Aperfeicoamento de Pessoal de Nıvel Superior) and CNPQ

(Conselho Nacional de Desenvolvimento Cientıfico e

Tecnologico). Leticia Resende received scholarship from

FAPEMIG (Fundacao de Amparo a Pesquisa do estado de

Minas Gerais) and Kenia de Oliveira Bueno and Andrea

Frozino Ribeiro from CAPES. The authors declare that there

are no conflicts of interest regarding the publication of this paper.

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(Accepted 2 March 2015)(Available online 09 March 2015)