Identificación de Cofilin-1 como proteína vinculada a la plasticidad neural

Neuroscience Letters 731 (2020) 135056
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Neuroscience Letters
journal homepage: www.elsevier.com/locate/neulet
Research article
Identification of cofilin 1 as a candidate protein associated to mouse visual
cortex plasticity
T
Natalia Bornia, Alfonso Taboada, Agustina Dapueto, Francesco Mattia Rossi*
Laboratorio de Neurociencias “Neuroplasticity Unit”, Facultad de Ciencias, Universidad de la República, Iguá 4225, 11400, Montevideo, Uruguay
ARTICLE INFO
ABSTRACT
Keywords:
Visual cortex
Plasticity
Proteomics
Basic proteins
Histones
Cofilin 1
In order to characterize the mechanisms controlling plasticity in the mouse visual cortex, we used, for the first
time on brain samples, an unconventional proteomic approach to separate acid-extracted proteins by bi-dimensional electrophoresis (AUT/SDS or AUT/AU gels). The analysis was performed on high plasticity critical
period young vs. low plasticity adult, and on fluoxetine-induced high plasticity vs. low plasticity untreated adult
mice. Mass spectrometry allowed for the identification of 11 proteins that are differentially expressed between
critical period and adult mice, and 5 between fluoxetine-treated and control adult mice. We then focused on
cofilin 1, as the intensity level of the corresponding spot on 2D gels was higher in both high plasticity conditions.
Western blot showed that cofilin 1 expression is dynamically regulated during postnatal life, reaching a peak at
the critical period, and decreasing at adult stage, and that it increases in fluoxetine-treated vs. untreated adult
mice. In summary, by using a 2D gel electrophoresis differential approach on basic proteins followed by mass
spectrometry and immunoblot analysis, we identified cofilin 1 as a potential candidate controlling plasticity
levels of the mouse visual cortex.
1. Introduction
In the mouse visual cortex, the critical period for experience-dependent plasticity, defined as the sensitivity to a short period of
monocular deprivation, starts after the third and ends around the fifth
week of postnatal life, with peak sensitivity around the fourth. Later,
alterations of visual experience have little or no effect, meaning that
plasticity levels are extremely reduced. Interestingly, various approaches that potentiate cortical plasticity in the adult and restore juvenile-like levels have been recently identified. Among these, the
pharmacological treatment with the anti-depressive fluoxetine has
raised particular interest for its potential clinical application [1–3].
The proposed general framework of mechanisms defining cortical
plasticity levels involves a fundamental role of inhibition, as well as the
balance with excitation, contributing to the opening and closure of the
critical period. Moreover, a fundamental role of structural factors,
acting as physical brakes and contributing to the closure of the critical
period. Accumulating evidence suggests that, while specific mechanisms exist, developmental and adult plasticity share common features.
However, the molecular mechanisms underlying the potentiation of
adult plasticity remain largely unknown [4,5].
A few recent large scale transcriptomic and proteomic approaches in
the visual system demonstrated the existence of groups of genes and
proteins that are differentially regulated during postnatal development
and that may underlie plastic processes [6–10]. While numerous proteomic works used the conventional 2D gel approach (iso-electrofocusing on immobilized pH gradient strips followed by 1D gel electrophoresis) [11], here we exploit, for the first time on brain samples, a
different approach selective for basic proteins on acetic acid, urea,
Triton X-100 / SDS (AUT/SDS) or / acetic acid, urea (AUT/AU) gels. We
focus on developmental and fluoxetine-induced adult plasticity conditions to better characterize possible similarity of the mechanisms defining the two plasticity experimental models. Our results contribute to
the characterization of the molecular signature of physiological and
Abbreviations: 2D, bi-dimensional; %Vol, relative volume parameter; AD, adult; APS, ammonium persulfate; AU, acetic acid, urea; AUT, acetic acid, urea, Triton X100; BSA, bovine serum albumin; CHAPS, 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate; CHCA, α-cyano-4-hydroxycinnamic acid; CHO, Chinese
hamster ovary; CP, critical period; CTR, control; DTT, dithiothreitol; FLX, fluoxetine; H, hippocampus; HeLa, human cervix adenocarcinoma; HRP, Horseradish
peroxidase; MCx, motor cortex; P, postnatal age; PBST, Phosphate Buffer Saline solution containing Tween-20; SDS, sodium dodecyl sulphate; TFA, trifluoroacetic
acid; VCx, visual cortex
⁎
Corresponding author.
E-mail addresses: [email protected] (N. Bornia), [email protected] (A. Taboada), [email protected] (A. Dapueto),
[email protected] (F.M. Rossi).
https://doi.org/10.1016/j.neulet.2020.135056
Received 3 December 2019; Received in revised form 5 May 2020; Accepted 14 May 2020
Available online 22 May 2020
0304-3940/ © 2020 Elsevier B.V. All rights reserved.
Neuroscience Letters 731 (2020) 135056
N. Bornia, et al.
pharmacologically-induced plasticity, and identify cofilin 1 as a potential common candidate associated to plasticity processes in the
mouse visual cortex.
between the mean of the population under analysis with p < 0.05 as
threshold for significance.
2.5. Mass spectrometry and bioinformatics
2. Material and methods
Mass spectrometry (MS) analysis was performed in the Analytical
Biochemistry and Proteomics Unit, Institut Pasteur, Montevideo,
Uruguay, as previously described [10]. Briefly, protein spots were
manually excised from the gel, destained, and air dried. Following
proteolytic in-gel digestion with sequencing-grade trypsin, peptides
were extracted from gels, concentrated by vacuum drying, and desalted
with reverse-phase microcolumns C18 (OMIX Pipette tips, Varian).
Peptides were eluted on the spectrometer plate with 2 μL of matrix
solution (CHCA in acetonitrile 60 %, TFA 0.1 %). MS measurements
were carried out in a MALDI-TOF/TOF system (4800 MALDI TOF/TOF
Analyzer AB Sciex), and spectra acquired in reflector mode and internally calibrated with autolytic fragments of trypsin. MS/MS analysis
of selected m/z values was performed to increase the confidence of the
identification. Proteins were identified by database searching (NCBIir
2019/05/30) with m/z values obtained in MS and MS/MS acquisition
modes using the MASCOT program (Matrix Science, www.
matrixscience.com) in the Sequence Query search mode. Search parameters were: up to one trypsin miscleavage allowed; cysteine carbamidomethylation and methionine oxidation as variable modifications;
mass tolerance of 0.08 and 0.35 Da for precursor and fragment ions
respectively. Proteins with significant mascot scores and at least one
peptide sequences confirmed by MS/MS were considered positively
identified (p < 0.05).
Following protein MASCOT identification, additional information
was searched in the Protein Knowledgebase UniProtKB (www.uniprot.
org) with the corresponding accession code. For localization and biological process, the Gene Ontology search was used. Relation with
specific processes was investigated using the National Center for
Biotechnology Information database (www.ncbi.nlm.nih.gov).
2.1. Animals and treatment
All experiments were performed in accordance with the EC
Directive 86/609/EEC for animal experiments (directive from the
European Commission of the European Economic Community) and with
the Uruguayan Research Ethic Committees. A total of 67 C57BL6/J
mice (both sexes) at different postnatal (P) ages (n = 5, P7; n = 5, P15;
n = 16, P28; n = 13, P60; and n = 28, P98) provided by the Transgenic
and Experimental Animal Unit, Institut Pasteur of Montevideo,
Uruguay, were used. Mice were bred under specific pathogen-free
conditions, housed (6/cage) in individual ventilated cages with positive
pressure (20 ± 1 °C, relative humidity 40–60 %, 14/10 h. light-dark
cycle), fed with standard mouse diet ad libitum, and had free access to
water. Fluoxetine-hydrochloride (Laboratorio Gador S.A., Uruguay)
oral treatment (P70 mice, 4 weeks, 0.1 mg/mL in tap water), followed
drug concentrations and schedules previously used [10,12]. For all
experiments, mice were sacrificed by cervical dislocation at approximately the same time of the day (between 8:00 and 10:00 a.m.), right
and left primary visual cortices (or other areas) dissected under a stereoscopic microscope on ice in saline solution (NaCl 0.9 %), pooled
together and stored at −80 °C for further processing. The boundaries of
the tissues to collect were visually identified using the stereotaxic coordinates of the mouse brain atlas as a guide [13].
2.2. Sample preparation
Basic proteins were extracted from brain samples by acid extraction
as previously described [12]. For 1D SDS gels, the pellet was resuspended in 50 μL of a buffer containing Tris 40 mM (pH 7.5), urea
7 M, thiourea 2 M, CHAPS 4 % (w/v), DTT 56 mM; for 2D AUT /SDS
and AUT/AU gels or 1D AU gels, in urea 8 M, acetic acid 5 %, β-mercaptoethanol 5 %, crystal violet 0.02 %.
2.6. Western blot
Western blot experiments were performed as previously described
[12] (Table 1). To verify homogeneous loading, membranes were
stripped (5 min, NaOH 0.2 M), and reincubated with the anti-tubulin
βIII antibody. Immunereactive bands were visualized using enhanced
chemioluminescence system (Amersham) and processed with a Chemi
Gbox system (Syngene). The specificity of anti-histones and other antibodies (except for cofilin 1, tested here) was previously tested [12].
2.3. Gel preparation and running conditions
SDS-PAGE was performed on 15 % acrylamide/bis-acrylamide gels
(1 h, 160 V). AUT gels were prepared with a solution containing acrylamide/bis-acrylamide 12 %, urea 6 M, glacial acetic acid 5 %, Triton X100 0.4 %, APS 0.1 %, TEMED 1 %, and samples run in acetic acid, urea
running buffer (200 V, reversed conditions). Lanes containing the
samples were cut out, adjusted in Tris 50 mM (pH 6.8) and the AUT gel
slice assembled on top of a 15 % SDS-PAGE (or AU, see below) gel and
run as usual. AU gels were prepared with a solution containing acrylamide/bis-acrylamide 12 %, urea 8.6 M, glacial acetic acid 5 %, APS
0.1 %, TEMED 1 %, and samples run in acetic acid, urea running buffer
(100 V, reversed conditions).
After running, gels were directly stained with Coomassie Brilliant
Blue R-250, colloidal Coomassie Brilliant Blue G250, or with the Silver
staining method.
2.7. Western blot densitometry and statistical analysis
The intensity of bands was quantified using the NIH Image J 1.46 r
free analysis software as previously described [12]. The signal obtained
with the anti-cofilin 1 antibody was normalized to the anti-tubulin βIII
antibody signal following stripping and reincubation of the same
membrane. Alternatively, the membrane was horizontally cut in two
parts, the upper processed with the anti-tubulin βIII and the lower with
the anti-cofilin 1 antibody. The cofilin 1/tubulin (COF/TUB) ratio data
(arbitrary unit, a.u.) was compared among the different groups, and the
statistical study performed using the Past 2.14 free analysis system [14]
with the one-way ANOVA post hoc Levene´s test with p < 0.05 as
threshold for significance. Data in graphs are expressed as
average ± SEM.
2.4. Bi-dimensional gel image analysis and statistical analysis
As previously described [10], gels were scanned in an UMAX
PowerLook 1120 scanner using the LabScan 5.0 software (Genebio
Amersham Biosciences), and images analyzed using the Melanie 6.0
software (Genebio Amersham Biosciences). The relative volume parameter (%Vol) was used to evaluate protein level differences between
gels. Data were analyzed for statistical differences using the Past 2.14
free analysis system [14] with the non-parametric Mann-Whitney U test
on normalized data (CP vs. AD, and FLX vs. CTR) to identify differences
3. Results
3.1. Proteomic analysis on different plasticity models of the mouse visual
cortex
The proteomic approach was used on young mice (P28) at the peak
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N. Bornia, et al.
Table 1
Antibodies used in Western blot. Name and code of primary and corresponding secondary antibody, dilution (vol:vol) and concentration when available in data
sheet (μg/mL), are reported. Blocking solution was non-fat dry milk 5 % in PBST, except for a (BSA 5 %). b Antibody concentration not available. Abbreviations: CS,
Cell Signaling; SC, Santa Cruz; Ab, Abcam; S, Sigma.
Primary antibody
Dilution
(conc. μg/mL)
anti-H2A CS#2578
anti-H2B CS#8135
anti-H3 CS#4499
anti-H4 CS#2935
anti- p(S10)H3 SC#8656
anti- Ac(K9)H3 CS#9649
anti-Ac(K8)H4 CS#2594a
anti-cofilin 1 Ab#54,532
anti-tubulin βIII Ab#7751
1:500b
1:1000b
1:2000b
1:1000b
1:1000 (0.2)
1:2000b
1:5000b
1:1000 (1.0)
1:2000 (0.5)
Secondary antibody (HRP-linked)
goat anti-rabbit S#A0545
goat anti-rabbit S#A0545
goat anti-rabbit S#A0545
horse anti-mouse CS#7076
goat anti-rabbit S#A0545
goat anti-rabbit S#A0545
goat anti-rabbit S#A0545
goat anti-mouse S#A4416
goat anti-mouse S#A4416
of the critical period of plasticity, adult mice (P60, AD) with low
plasticity levels, fluoxetine-treated adult mice (P98, FLX) with pharmacologically-restored high levels of plasticity, and control untreated
adult mice (P98, CTR) with low plasticity levels. Several bi-dimensional
gels for each pair of experimental condition (CP vs. AD: n = 10 AUT/
SDS and n = 6 AUT/AU gels; FLX vs. CTR: n = 14 AUT/SDS gels, AUT/
AU gels were not used for this comparison) were run in parallel to reduce variability, always loaded with 45 μg of samples and stained with
the Silver staining method.
Fig. 1 shows representative images of part of AUT/SDS
(10−37 kDa) and AUT/AU gels. The pattern profile in both AUT/SDS
and AUT/AU gels is very similar among the different experimental
conditions, and the method allowed a high spot resolution (methods
shown in Suppl. Fig. 1 and 2).
Dilution
(conc. μg/mL)
1:5000b
1:5000b
1:5000b
1:5000b
1:5000b
1:5000b
1:5000b
1:5000b
1:5000b
total of 28 spots were selected in AUT/SDS gels.
Considering AUT/AU gels, exclusively the image analysis software
was used to select protein spots. Following the same procedure as before, a total of 23 well defined spots were selected from these gels.
Selected spots on AUT/SDS and AUT/AU gels are shown in Fig. 2.
3.3. Mass spectrometry identification
Among the 28 spots selected in AUT/SDS gels, 14 were successfully
identified, while of the 23 spots selected in AUT/AU gels, only 5 were
identified, possibly due to technical issues, as contaminants or undetectable amount of protein material (Table 2). The proteins identified
in AUT/AU gels were also identified in AUT/SDS gels, suggesting a
good efficiency of the experimental approach used (Suppl. Table 1 and
2). As shown, part of the identified proteins belongs to the histone family of proteins (n = 6), while other are non-histone proteins (n = 8).
By using the Protein Knowledgebase, proteins were assigned to the
following cellular/subcelullar localizations: Cytoplasm, Cytoskeleton,
Mitochondrion, Myelin Sheath, Nucleus, and Red Blood Cells. As for the
main biological processes, proteins were assigned to: Actin Depolymerization, Myelination, Nucleosome Assembly, Oxygen Transport,
Protein Folding, Respiratory Chain, and RNA Processing. The average
3.2. Spot selection
Considering AUT/SDS gels, we restricted our selection to the best
resolved part of gels (between 10 and 37 kDa). To facilitate spot selection, a Western blot analysis with anti-histones antibodies was also
performed [12] (Suppl. Fig. 3). The image analysis software was further
used to select additional spots. Taking into account all these aspects, a
Fig. 1. 2D gel electrophoresis. Above, representative images of part (10-37 kDa) of AUT/SDS gels showing the spot pattern profile of 45 μg of acid-extracted visual
cortex sample from critical period (CP, P28), adult (AD, P60) and fluoxetine-treated adult mice (FLX, P98), stained with the Silver staining method. The gel obtained
with P98 untreated control mice is not shown. MW: molecular weight in kDa. Below, representative images of part of AUT/AU gels showing the spot pattern profile of
45 μg of acid-extracted visual cortex sample from critical period (CP, P28) and adult (AD, P60) mice stained with the Silver staining method. Full images of both
AUT/SDS and AUT/AU gels are shown in Suppl. Fig. 1.
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N. Bornia, et al.
Fig. 2. Selected spots on 2D gels. Representative images of AUT/SDS (A) and AUT/AU (B) gel obtained running 45 μg of acid-extracted visual cortex sample and
stained with the Silver staining method (B, same image as in Fig. 1, AUT/AU gel, CP). Lines indicate the selected spots (n = 28 for AUT/SDS, and n = 23 for AUT/AU
gels). Black lines and numbers indicate the spots successfully identified by MS (n = 14 for AUT/SDS gels, n = 5 for AUT/AU gels) with the corresponding spot
number (spot number reference list in Suppl. Table 1 and 2).
isoelectric point theoretical value of the identified proteins was
9.7 ± 0.4 (7.12–11.18), confirming that the acid extraction method was
efficient in enriching samples in basic proteins.
3.5. Analysis of cofilin 1 expression in the mouse visual cortex in different
experimental plasticity models
We then focused on cofilin 1, as the modulation of the optical
density level of the corresponding spot suggested a potential role in the
control of cortical plasticity.
A Western blot analysis was performed on mice at P7 and P15 (precritical period, low or no plasticity), P28 (peak of plasticity), adult
(P60, low plasticity), and fluoxetine-treated (P98, pharmacologicallyrestored high plasticity) vs. untreated adult (P98, low plasticity). The
efficiency of the anti-cofilin 1 antibody was previously tested (Suppl.
Fig. 4).
Fig. 3 shows a representative image of an experiment performed on
samples from the different conditions. The graph shows that cofilin 1
expression is dynamically modulated in the mouse visual cortex during
development: it increases from P7 to P15 by approximately 45 %, and
to P28 by approximately 80 %, and then, at P60, it decreases to values
similar to those observed at P7. Comparison of the values obtained in
fluoxetine-treated and untreated adult mice, indicates that cofilin 1
expression increases in the former by 90 % approximately.
3.4. Protein level modulation in different experimental plasticity models of
the mouse visual cortex
Among the 14 proteins identified in AUT/SDS gels, 11 presented
significant variations between critical period and adult mice: 6 proteins
increased (H2B and H3 histones, RS16, RS10, PPIA, and COF1), while 5
decreased (two H2A histone spots, MBP, HBA, and NDUA4) in the CP
when compared to AD (Table 2). In AUT/AU gels, among the 5 identified proteins, 4 presented a significant variation: one increased (H2B
histone, and HBA), and two decreased (H2A histone, and MBP) in the
CP when compared to AD (Suppl. Table 3).
As for the FLX vs. CTR comparison, among the 14 proteins identified
in AUT/SDS gels, 4 presented significant variations (Table 2): 3 proteins
increased (two H2A spots, and COF1), while 1 increased (H2B histone)
in the FLX samples when compared to CTR (AUT/AU gels were not used
for this comparison).
Table 2
MS identified proteins in AUT/SDS gels and level comparison between plasticity models. The spot number, full name, Swiss Prot protein access code, theoretical pI and MW (Da), average normalized spot % Vol ratio between critical period and adult mice (CP/AD), and between fluoxetine-treated and untreated adult
mice (FLX/CTR) with corresponding SEM (in bold when statistically significant), main localization (Cp, Cytoplasm; Csk, Cytoskeleton; MS, Myelin Sheath; Mt,
Mitochondrion; Nu, Nucleus; RBC, Red Blood Cells), and indication of the main biological processes (AD, Actin Depolymerization; M, Myelination; NA, Nucleosome
assembly; OT, Oxygen Transport; PF, Protein Folding; RC, Respiratory Chain; RP, RNA Processing), are reported. The dotted line separates histone from non-histone
proteins. For histones, the variants identified in the corresponding spot are reported in parenthesis. In the case of spot #3 H2B, the variant types 1-A, 1-B, 1-M were
not identified. As for the spots # 12 and 13 H2A, the variants macroH2A, types 2-A, 2-B, 2-C, 3, H2A.x, H2A.J were not identified.
Spot N°
Full name
Access code
pI
Mass
(Da)
CP/AD ± SEM
FLX/CTR ± SEM
Localization
Function
1
3
Histone H4
Histone H2B (type 1-C/E/F/G/I, 1-D, 1-F/J/L,
1-K, 1-H, 1-P, 2-B, 2-E, 2-F, 3-A, 3-B)
Histone H3 (H3.1-H3.2-H3.3)
Histone H2A (type 1, 1-A, 1-D, 1-H, 1-K, 1-F; H2A.Z, H2A.V)
Histone H2A (type 1, 1-A, 1-D, 1-H, 1-K, 1-F; H2A.Z, H2A.V)
Histone H1.0
Myelin basic protein
40S ribosomal protein S16
Haemoglobin subunit alpha
Haemoglobin subunit beta-1
NADH dehydrogenase 1 alpha subcomplex subunit 4
40S ribosomal protein S10
Peptidyl-prolyl cis-trans isomerase A (cyclophilin A)
Cofilin-1
H4_MOUSE
H2B_MOUSE
11.18
10.31
11,360
13,994
1.21 ± 0.23
1.23 ± 0.08
0.89 ± 0.16
0.76 ± 0.10
Nu
Nu
NA
NA
H3_MOUSE
H2A_MOUSE
H2A_MOUSE
H10_MOUSE
MBP_MOUSE
RS16_MOUSE
HBA_MOUSE
HBB1_MOUSE
NDUA4_MOUSE
RS10_MOUSE
PPIA_MOUSE
COF1_MOUSE
10.60
10.60
10.60
10.90
10.72
10.21
7.96
7.12
9.52
10.15
7.74
8.22
12,054
14,135
14,135
20,861
14,202
16,445
15,085
15,840
9,327
18,916
17,971
18,560
2.72 ± 0.19
0.69 ± 0.05
0.54 ± 0.08
0.85 ± 0.18
0.42 ± 0.18
2.39 ± 0.44
0.79 ± 0.04
0.86 ± 0.16
0.70 ± 0.09
2.12 ± 0.25
1.44 ± 0.09
1.56 ± 0.05
1.15 ± 0.21
1.52 ± 0.18
1.46 ± 0.10
1.15 ± 0.22
0.95 ± 0.26
0.91 ± 0.12
0.99 ± 0.07
1.13 ± 0.14
1.21 ± 0.20
1.21 ± 0.24
1.06 ± 0.09
1.69 ± 0.09
Nu
Nu
Nu
Nu
MS
Cp
RBC
RBC
Mt
Cp
Cp
Csk
NA
NA
NA
NA
M
RP
OT
OT
RC
RP
PF
AD
9
12
13
14
2
4
5
6
7
8
10
11
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[17], we were able to unambiguously identify in the mouse visual
cortex the H1.0 variant of H1 isoform, and the canonical H4 isoform. As
for H2A and H2B, MS analysis was able to identify some specific variants and to exclude others in the selected spots. As for H3, the localization of the identified spot corresponds to the position reported by
others as the H3.3 variant. The use of larger gels, of alternative extraction methods as the salt extraction that preserves variants and
posttranslational modifications labile in acid solutions, and of other
mass spectrometers as the LTQ Velos nano-ESI-lineal ion trap, may
result useful to improve this approach [18].
Our study indicates that some histone variants are modulated in the
different experimental plasticity conditions analyzed. While H1 and H4
levels apparently remain stable, the H2A, H2B and H3 are up or down
regulated.
It is worth mentioning that the H2A.Z, H2B.E and H3.3 variants
have been shown to play a critical role during development and in
activity-dependent plasticity processes, such as learning and memory
tasks, in different brain areas [16]. These observations and the results
obtained here, suggest a possible role of these variants in plastic processes also in the mouse visual cortex.
4.2. Non-histone proteins
Fig. 3. Western blot analysis of cofilin 1. Representative image of an experiment on 45 μg of protein extracts of (from left to right) P7, P15, P28, P60,
fluoxetine-treated (FLX) and untreated (CTR) adult mice, with the anti-cofilin 1
(COF, below) and the anti-tubulin βIII antibody (TUB, above). MW: molecular
weight in kDa. The graph shows the quantification of the data obtained normalizing cofilin 1 to tubulin data (COF/TUB in arbitrary unit, a.u.). P7:
0.79 ± 0.03, n = 5; P15: 1.14 ± 0.05, n = 5; PC: 1.42 ± 0.03, n = 6; AD:
0.64 ± 0.07, n = 7. FLX: 1.33 ± 0.04, n = 7; CTR: 0.71 ± 0.06, n = 7. Oneway ANOVA post hoc Levene´s test with p < 0.05 as threshold for significance
(a, no statistical difference: P7 vs. P60, p = 0.29; P7 vs. CTR, p = 0.32; P60 vs.
CTR, p = 041. b, statistical difference from a and c; c, statistical difference from
a and b). Data in the graphs are expressed as average ± SEM.
Mitochondrial genes, as the NADH dehydrogenase 1 subunits, have
been associated to plasticity processes. Our results are in agreement
with recent evidence in the cat visual cortex showing a differential
expression of NADH subunits as a function of plasticity levels [19]. The
possible involvement of this enzyme in plasticity processes could occur
not only by acting on the respiratory chain, but also on the transport
through the mitochondrial membrane and on calcium homeostasis
[19].
Cyclophilin, a protein involved in protein folding, has been associated to an inhibitory role on lesion-induced plasticity in the cat visual
cortex during synaptic connection remodeling [20]. The present data
suggest a similar role also on physiological plasticity processes in the
mouse visual cortex.
Myelin Basic Protein (MBP) is the most abundant protein component constituting the nervous system myelin sheath, involved in cortical
plasticity, degeneration, and inflammation [21–23]. Maturation of
cortical myelin acts as a potent brake for neurite dynamics and growth,
limiting developmental plasticity also in the visual cortex [24,25]. The
observation that MBP increases with age in the mouse visual cortex is in
agreement with these data and confirms the efficiency of the methodological approach used.
Cofilin 1 is particularly abundant in the brain, specifically in cortex,
hippocampus, cerebellum, and striatum. This protein plays a fundamental role in the turnover of actin filaments in the cytoskeleton and
specifically in dendritic spines, where it has been associated, mainly in
hippocampal studies, to structural and functional plasticity processes.
Pharmacological and genetic manipulations have highlighted its relevance for synapse physiology and behavior, and identified it as a key
regulator of synaptic plasticity [26,27]. Here, we observed that cofilin 1
levels are higher in the visual cortex of high-plasticity levels mice (CP
and FLX). These data are in agreement with a previous proteomic report
on cortical synaptosomes, showing a decrease of cofilin 1 levels from
critical period to adult in the mouse visual cortex [9].
Western blot analysis confirmed and extended the proteomic results.
The increase of cofilin 1 from P7 to P28 may be associated to different
developmental processes, as, for instance, synaptogenesis which, in the
mouse visual cortex, peaks at P7, and cortical lamination [28]; and also
to a regulation by the visual input, as cofilin 1 expression is higher at
eye opening (P15) than earlier. The observation that cofilin 1 expression is high when plasticity levels are high (CP and FLX) suggests that
this protein may play a role in the control of plasticity also in the mouse
visual cortex.
Previously [10] we showed that fluoxetine treatment up regulates
4. Discussion
With the aim of identifying potential candidates controlling plasticity levels in the mouse visual cortex we used, to our knowledge for the
first time on brain samples, an unconventional proteomic approach to
extract and separate basic proteins. An advantage of this strategy is
that, contrary to standard 2D immobilized pH gradient approach, it
allows to efficiently resolve basic proteins [15]. None of the proteins
identified in this work were identified in our previous approach using
conventional 2D SDS PAGE [10], indicating that the two strategies are
useful and complementary.
As expected, a portion of the identified proteins were histones, the
main basic proteins present in acid-extracts [12], while others were
non-histone proteins. Finally, the analysis comparing mice with different plasticity levels, allowed the identification of a group of proteins
which are differentially modulated. The potential role of the more relevant proteins in the context of the regulation of plasticity is discussed
below.
4.1. Histone proteins
Epigenetic modifications are a fundamental mechanism of gene
expression regulation through which sensory experience can induce the
reorganization of neuronal connections in a plastic brain [16]. While
many studies have focused on posttranslational modifications of histones and their role in brain plasticity, also in the visual cortex, it is
only very recently that the turnover and exchange of histones and their
variants has been identified as an additional critical mechanism regulating transcription and plasticity [16].
Among the several histone variants known in the mammalian brain
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N. Bornia, et al.
the level of other proteins which are, as cofilin 1, directly involved in
the control of cytoskeleton organization. Interestingly, these proteins
(actin-related protein 2, profilin-2, small Rho GTPase cell division
control protein 42) have been shown to interact with each other and
also with cofilin 1 (through the Arp2/3 complex) and to control morphological plasticity of dendritic spines [26,27].
In conclusion, by using an unconventional 2D gel electrophoresis
differential proteomic approach on basic proteins followed by mass
spectrometry and immunoblot analysis, we identified cofilin 1 as a
potential candidate controlling plasticity levels of the mouse visual
cortex.
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Declaration of Competing Interest
Authors declare no conflicts of interests regarding data presented in
this manuscript.
CRediT authorship contribution statement
Natalia Bornia: Conceptualization, Methodology, Software, Data
curation, Writing - original draft. Alfonso Taboada: Supervision,
Writing - review & editing, Funding acquisition. Agustina Dapueto:
Visualization,
Investigation.
Francesco
Mattia
Rossi:
Conceptualization, Methodology, Software, Data curation, Writing original draft.
Acknowledgements
The authors wish to thank A. Villarino and M. Berois (Faculty of
Sciences, Universidad de la República, UdelaR, Montevideo, Uruguay)
for providing CHO cells; M. Bollati-Fogolín (Cell Biology Unit, Institut
Pasteur of Montevideo, Uruguay) for providing HeLa cells; D. Rilla
(Laboratorio Gador S.A., Montevideo, Uruguay) for providing fluoxetine-hydrochloride; Rosario Durán (Analytical Biochemistry and
Proteomics Unit, Institut Pasteur, Montevideo, Uruguay) for technical
support in mass spectrometry analysis; F. Zolessi and A. Villarino
(Faculty of Sciences, UdelaR, Montevideo, Uruguay) for experimental
support, and F. Zolessi for proof reading the article. This work was
supported by the Agencia Nacional de Investigación e Innovación
(ANII) and the Programa de Desarrollo de las Ciencias Básicas
(PEDEClBA), Uruguay. The authors confirm that the funders had no
influence over the study design, content of the article, or selection of
this journal.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the
online version, at doi:https://doi.org/10.1016/j.neulet.2020.135056.
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