Abstract

   Fragile X mental retardation protein (FMRP) encoded by Fragile X mental
   retardation 1 (FMR1) gene is a RNA-binding regulator of mRNA
   translation, transport and stability with multiple targets responsible
   for proper synaptic function. Epigenetic silencing of FMR1 gene
   expression leads to the development of Fragile X syndrome (FXS) that is
   characterized by intellectual disability and other behavioral problems
   including autism. In the rat FXS model, the lack of FMRP caused a
   deficit in hippocampal-dependent memory. However, the hippocampal
   changes of FMRP in aging rats are not fully elucidated. The current
   study addresses the changes in FMRP levels in dentate gyrus (DG) from
   young (17 weeks) and aging (22 months) Sprague – Dawley rats. The aging
   animal group showed significant decline in spatial reference memory.
   Protein samples from five rats per each group were analyzed by
   quantitative proteomic analysis resulting in 153 significantly changed
   proteins. FMRP showed significant reduction in aging animals which was
   confirmed by immunoblotting and immunofluorescence microscopy.
   Furthermore, bioinformatic analysis of the differential protein dataset
   revealed several functionally related protein groups with individual
   interactions with FMRP. These include high representation of the RNA
   translation and processing machinery connected to FMRP and other
   RNA-binding regulators including CAPRIN1, the members of Pumilio (PUM)
   and CUG-BP, Elav-like (CELF) family, and YTH N(6)-methyladenosine
   RNA-binding proteins (YTHDF). The results of the current study point to
   the important role of FMRP and regulation of RNA processing in the rat
   DG and memory decline during the aging process.

   Keywords: Fragile X syndrome, Fragile X mental retardation protein,
   brain aging, dentate gyrus, proteomics, RNA-binding protein

Introduction

   The Fragile X mental retardation protein (FMRP) is a RNA-binding
   regulator encoded by Fragile X mental retardation 1 (FMR1) gene. This
   protein is ubiquitously produced in mammalian tissues with high levels
   in brain ([45]Tamanini et al., 1997), and localized predominantly in
   cytosolic light and heavy membranes, and nucleus ([46]Taha et al.,
   2014). It contains two K-homology domains (KH1 and KH2) and a
   C-terminal RGG box, involved in RNA-binding, together with nuclear
   localization and nuclear export signal ([47]Adinolfi et al., 1999;
   [48]Valverde et al., 2007). These structural features suggest the
   molecular functions of FMRP which have been associated with mRNA
   stability ([49]Zalfa et al., 2007), nuclear – cytoplasmic shuttling of
   mRNA ([50]Eberhart et al., 1996) and repression of mRNA translation
   ([51]Jin and Warren, 2000; [52]Li et al., 2001; [53]Kalidas and Smith,
   2003). The total number of FMRP functions in vivo is not known and a
   multitude of FMRP targets was proposed based on large-scale analyses
   ([54]Ascano et al., 2012; [55]Ouwenga and Dougherty, 2015).

   Fragile X mental retardation protein has been implicated as a regulator
   of synaptic plasticity and thereby learning and memory (reviewed in
   [56]Bostrom et al., 2016). The functions of FMRP in nervous system have
   been related to the control of synaptic protein synthesis in response
   to neurotransmitter activation and affecting the formation of axonal
   and dendritic structures ([57]Feng et al., 1997; [58]Greenough et al.,
   2001; [59]Weiler et al., 2004; [60]Zimmer et al., 2017). The
   FMRP-mediated regulation of mRNA translation has been also directly
   linked to neurotransmitter receptor systems involved in synaptic
   plasticity. As an example, it was shown that the activation of
   metabotropic glutamate receptors (mGluR) affects FMRP localization in
   dendrites and synapses ([61]Antar et al., 2004), FMRP deficiency leads
   to excessive mGluR5- and local protein synthesis-dependent
   internalization of AMPA receptors ([62]Nakamoto et al., 2007) and that
   the expression of the NMDA receptor subunit NR2A is regulated by
   FMRP-associated microRNAs ([63]Edbauer et al., 2010).

   Impairment of FMR1 gene expression due to amplification of CGG repeat
   in its 5′-UTR and hypermethylation leads to several syndromes. The full
   mutation allele (>200 CGG repeats) results in lack of FMRP and
   development of Fragile X syndrome (FXS) that is characterized by
   cognitive disabilities and behavioral disorders ([64]Wang et al.,
   2012). The mouse and rat FMR1 knock-out (KO) models have been
   extensively used to study behavioral deficits, and alterations in brain
   physiology and development associated with FXR ([65]Till et al., 2012,
   [66]2015). Interestingly, a recent quantitative proteomic study of FMR1
   KO mouse revealed a significant overlap of a dysregulated proteome
   between the FXR condition and normal aging ([67]Tang et al., 2015) and
   the FMRP levels were found to be decreased in aged mouse brain
   ([68]Singh et al., 2007; [69]Singh and Prasad, 2008).

   The information on aging-dependent changes of FMRP in rat brain and
   specific brain subareas is limited. The dentate gyrus (DG) is a
   hippocampal subregion that plays a critical role in information
   processing including spatial memory ([70]Jonas and Lisman, 2014;
   [71]Bott et al., 2016) and the aging-related functional alterations in
   this region were previously described for rats, mice, and other
   mammalian models ([72]Lister and Barnes, 2009). The results obtained
   from FMR1 KO mouse models indicate an important function of FMRP in
   physiology, structure and connectivity of DG, and the related behavior
   ([73]Bostrom et al., 2016; [74]Lai et al., 2016; [75]Scharkowski et
   al., 2017). Previous studies on rats showed deficits in
   hippocampal-dependent memory in a FMR1 KO model ([76]Till et al., 2015)
   and behavior-induced changes of FMRP level in DG ([77]Irwin et al.,
   2005). However, validated information on FMRP levels in DG in rat
   during normal aging is missing. In the current study, FMRP levels in DG
   were compared between the young (17 weeks) and aging (22 months)
   Sprague-Dawley rats. In the initial hole-board test the aging group
   showed a significant decline in spatial reference memory. Protein
   samples of DG from five rats per each group were then analyzed by
   quantitative proteomic analysis resulting in 153 significantly changed
   proteins. FMRP showed significant reduction in aging animals which was
   confirmed by immunoblotting and immunofluorescence microscopy.
   Furthermore, bioinformatic analysis of the differential protein dataset
   revealed several functionally related protein groups with individual
   interactions with FMRP. These included high representation of RNA
   translation and processing machinery connected to FMRP and other
   RNA-binding regulators. The results of the current study point to an
   important role of FMRP and the regulation of RNA processing in the rat
   DG related to memory decline during the aging process.

Materials and Methods

Animals

   Animals were bred and maintained in the Core Unit of Biomedical
   Research, Division of Laboratory Animal Science and Genetics, Medical
   University of Vienna. The animals lived in a separate experimental room
   1 week before and throughout the experiment. Rats were housed
   individually in standard Makrolon cages filled with autoclaved
   woodchips (temperature: 22 ± 2°C; humidity: 55 ± 5%; 12 h artificial
   light/12 h dark cycle: light on at 7:00 am). The study was carried out
   in accordance the recommendation of the European Communities Council
   Directive of 24 November 1986 (86/609/EEC) evaluated by the ethics
   committee of the Medical University of Vienna, Vienna, Austria. The
   protocol was approved by Federal Ministry of Education, Science and
   Culture, Austria.

Hole-Board Memory Test

   The hole-board consisted of a 1 m × 1 m board made of black plastic
   surrounded by translucent plexiglass walls. Each side of the wall bears
   proximal spatial cues. Distal cues were provided by room structures
   visible outside the board. Four out of sixteen regularly arranged holes
   (diameter and depth 7 cm) were baited (dustless precision pellets, 45
   mg, Bioserv^®). The pattern of baited holes remained the same during
   the entire test. In order to avoid olfactory orientation pellets were
   also present in an area below the board. Rats were familiarized to the
   experimenter through 10 min handling sessions per day for 4 days prior
   to the experiment, followed by 2 days of habituation to the hole-board
   during which the animals were allowed to explore the maze for 15 min
   each day with access to food pellets. The weight of each rat was
   gradually reduced by food restriction to reach 85% of its free-feeding
   body weight before the start of the experiment. Tap water was given ad
   libitum. Thereafter the rats were trained for 3 days (five trials on
   day 1, four trials on day 2 and a retention trial at day 3). Every
   trial lasted for 120 s or until all four pellets were eaten. The
   apparatus was cleaned with 0.1% incidin between trials in order to
   remove the rat odor cues. The interval between two successive trials
   for an individual was 20 min. A camera mounted on the room ceiling
   recorded the performance of the rats in the maze. The visits of holes
   and removals of pellets were noted for each trial. In order to compare
   rats with similar levels of motivation, rats with less than 40
   hole-visits in total over the 10 trials were excluded from the
   analysis. Reference memory errors were noted as the number of visits to
   the unbaited holes. The Reference Memory Index (RMI) was calculated
   using the formula: (first + revisits of baited holes)/total visits of
   all holes. All behavioral training/testing was performed during the
   light phase of the light–dark cycle. Rats were decapitated, the brains
   were rapidly removed and dissected on a Para Cooler (RWW
   Medizintechnik, Hallerndorf, Germany) at 4°C to obtain DG. The tissue
   was immediately stored at -80°C until further analysis.

Protein Sample Preparation

   All homogenization and centrifugation steps were carried out on ice and
   at 4°C, respectively. Brain tissues were homogenized in an ice-cold
   homogenization buffer [10 mM HEPES, pH 7.5, 300 mM sucrose, protease
   inhibitors (Roche)] using a Dounce homogenizer; the homogenate was
   centrifuged at 1000 × g for 10 min to remove cell debris and nuclei and
   the supernatant was collected. The pellet was resuspended again in the
   homogenization buffer and centrifuged at 1000 × g for 10 min. The
   pooled supernatants were then centrifuged at 100000 × g for 60 min to
   enrich membranes. The resulting membrane pellets were washed in 10 mM
   HEPES, pH 7.5, protease inhibitors (Roche) and solubilized in 50 mM
   TEAB buffer (Sigma–Aldrich), 7 M urea, 2 M thiourea, 4% CHAPS, 100 mM
   DTT and protease inhibitors (Roche). The protein concentration was
   determined by Pierce^TM 660 nm Protein Assay (Thermo Scientific).

Quantitative LC–MS/MS Analysis

   Protein samples were digested overnight with trypsin (Promega) using
   filter-aided sample preparation (FASP) ([78]Wisniewski et al., 2009)
   with 50 μg of protein per one reaction. The tryptic peptides were
   desalted using reversed-phase C18 stage tips ([79]Rappsilber et al.,
   2007) and reconstituted in 50 μL of 50 mM TEAB (Sigma–Aldrich, Hamburg,
   Germany). The samples (50 μg in 50 μL) were subsequently differentially
   labeled by TMT10plex^TM Isobaric Label Reagent Set (Thermo Scientific)
   according to the manufacturer’s instructions. Using an actual peptide
   concentration determined by Pierce^TM Quantitative Colorimetric Peptide
   Assay (Thermo Scientific) the samples were pooled by mixing an equal
   amount of labeled peptides from individual samples. The pooled sample
   was separated by reversed-phase liquid chromatography (RP-LC) at high
   pH as previously described ([80]Gilar et al., 2005) resulting in 25
   fractions. The peptide fractions were analyzed by liquid
   chromatography-tandem mass spectrometry (LC–MS/MS) with two technical
   replicates per sample using the LC separation procedure described
   previously ([81]Smidak et al., 2016). MS analysis was performed by the
   Thermo Scientific^TM Q Exactive^TM Plus Orbitrap mass spectrometer
   (Thermo Scientific) in positive ion mode with full-scan MS in the range
   of m/z 375–1400 at the resolution of 35,000 (at m/z 200). MS/MS scans
   were acquired at the resolution of 70,000 (m/z 200) through HCD
   fragmentation of 15 most intense ions at 32% normalized collision
   energy with a fixed mass of 100 m/z. Dynamic exclusion was enabled for
   30 s and for unassigned, +1 and ≥ +8 charges.

Proteomic Data Analysis

   MS raw data were searched against UniProtKB Rattus norvegicus complete
   proteome database (UP000002494, 31569 sequences, downloaded on December
   2nd, 2016) using MASCOT 2.4 (MatrixScience) through Proteome Discoverer
   2.1 platform (Thermo Scientific). The search criteria were as follows:
   trypsin with a maximum of two missing cleavage sites; fixed
   modification: carbamidomethylation (C); variable modification:
   oxidation (M); search mode: MS/MS ion search with decoy database search
   included; peptide mass tolerance ± 10 ppm; MS/MS mass tolerance ± 0.02
   Da; and protein and peptide FDR 1%. Only proteins identified by two
   distinct peptides and one unique peptide were considered for the final
   dataset. The Reporter Ions Quantifier node in the Proteome Discoverer
   software was used to calculate the corresponding protein abundances
   based on the intensities of individual TMT reporter ion channels
   (126.13–131.14 m/z) corrected for reporter ions isotopic distribution.
   The protein abundances were normalized by the total intensity of each
   reporter in the PSMs (Peptide-Spectral-Matches) population. Differences
   in protein levels are expressed as log2-transformed normalized protein
   abundance ratio of aging versus young animal group evaluated by
   two-sided t-test using Perseus statistical package (version 1.3.0.4).
   p-Values < 0.05 with permutation-based FDR threshold 0.05 were used as
   cut-off for significance. Additional filtering for significantly
   changed proteins was applied based on log2 (protein ratio) threshold >
   |0.3|. Significantly changed proteins were analyzed for enrichment of
   GO annotations using ClueGO-Cytoscape platform ([82]Bindea et al.,
   2009; [83]Huntley et al., 2015) using GOA database 30.08.2017 and
   Benjamini–Hochberg correction (adjusted p-Values < 0.01). The lists of
   most representative pathways and biological functions/diseases, and
   protein interaction networks were generated by Ingenuity Pathway
   Analysis (IPA) software (Qiagen) using right-tailed Fisher’s exact test
   (p < 0.05). Functionally related protein clusters within the
   differential dataset were visualized by STRING v10.5^[84]1 and MCL
   algorithm with confidence threshold 0.5 and inflation parameter 3.

Western Blot

   The protein samples were separated by electrophoresis in 10% SDS-PAGE
   gel and transferred to PVDF membranes (GE Healthcare). The western blot
   procedure was performed as described previously ([85]Shanmugasundaram
   et al., 2017) with minor modifications. Briefly, the membrane was
   blocked for 1 h in 5% non-fat milk, 1x TBS, 0.05% Tween-20 and probed
   with the corresponding primary and secondary antibodies. For detection
   of FMRP protein the membrane was incubated in 3% non-fat milk, 1x TBS,
   0.1% Tween-20 with 1:1000 polyclonal mouse anti-FMRP antibody (MAB2160,
   Millipore) overnight at 4°C followed by incubation for 1 h at room
   temperature in 1:10000 HRP-conjugated anti-mouse secondary antibody
   (ab6728, Abcam). Actin as a loading control was detected by incubation
   in 3% non-fat dry milk, 1x TBS, 0.1% Tween-20 with 1:2000 anti-β-Actin
   antibody (4967S, Cell Signalling) overnight at 4°C followed by
   incubation for 1 h at room temperature in 1:10000 rabbit polyclonal
   antibody. The signals were quantified using ImageJ (NIH) software based
   on calculation of peak area and the intensity values for FMRP bands
   were normalized across the samples by actin control.

Immunofluorescence Detection and Microscopy

   For the analysis of FMRP expression eight young and eight aging rats
   were deeply anesthetized with isoflurane and transcardially perfused
   with 4% paraformaldehyde solution in 0.1 M sodium phosphate buffer, pH
   7.4. Brains were gently removed and post-fixed in the same fixative
   solution for 20–24 h at 4°C. Each brain was rinsed well with phosphate
   buffered saline (PBS) to remove formaldehyde and incubated in 30%
   sucrose with 0.02% NaN[3] at 4°C. Immediately prior to cutting, brains
   were embedded in O.C.T. Tissue-Tek (Sakura Finetek) and frozen at -20°C
   in a cryo chamber. Tissue was sectioned at 20 μm with a cryostat
   CryoStar NX50 (Thermo Scientific). Coronal cryo sections (Bregma
   3.30–3.80 mm) were blocked in 5% normal goat serum (NGS) (G9023,
   Sigma–Aldrich), 0.3% Triton X-100 (T8787, Sigma–Aldrich), 2% BSA
   (23208, Thermo Scientific) in 0.1 M PBS 7.4 for 2 h at 22–24°C and
   incubated with primary antibody (mouse anti-FMRP 1:500 MAB2016, Merck)
   for 48 h at 4°C in 0.1 M PBS, 1% NGS, 0.1% Triton X-100, 0.1% BSA with
   continuous stirring. After three washing steps in 0.1 M PBS, sections
   were incubated with the secondary antibody (1:1000 AlexaFluor488
   anti-mouse 4408S, Cell Signaling Technology) for 2 h at 22–24°C in 2%
   BSA. In addition, to remove lipofuscin-like autoimmunofluorescence, all
   sections were incubated in autoimmunofluorescence eliminator reagent
   (2160, Merck) for 5 min and then underwent six washing steps for 1 min
   each in 70% ethanol. DAPI staining was used to assess the gross cell
   morphology (D1306, Thermo Scientific). All sections were mounted with
   DAKO fluorescence mounting medium (Agilent Technologies) and analyzed
   by fluorescence microscopy. Immunoreactivity signal of FMRP in cells,
   processes and neutropil in the DG were acquired on a Zeiss LSM780
   confocal microscope (Zeiss, Jena, Germany) using 20x magnification. The
   image analysis software ImageJ (NIH) calculated the percentage of
   FMRP-positive area per section by thresholding FMRP immunoreactivity
   above background levels. The cell body layer of DG granule cells and
   hilus were separately outlined as regions of interest (ROI) according
   to the DAPI signal in each slice. Immunofluorescence imaging and data
   analysis were duplicated, evaluating two brain slices per rat in total.

Statistical Analysis

   Data obtained from western blot and immunofluorescence microscopy was
   analyzed using Microsoft Excel 2013 or Prism 5 (GraphPad Software) and
   the difference between animal groups was evaluated by Student’s t-test
   with the significance cut-off p < 0.05. The behavioral data was
   analyzed with SPSS Version 22 software (IBM^® SPSS^® Statistics) using
   general linear model – repeated measures ANOVA for the differences over
   the entire training, or separately for days 1 and 2, and univariate
   ANOVA for the retention trial. The significance cut-off was set at p <
   0.05. The values are expressed as mean ± SEM.

Results

Behavioral Testing

   Behavioral testing was performed to assess hippocampal-dependent memory
   performance in the subarea of interest. The cohort of 18 young and 104
   aging Sprague-Dawley rats were evaluated for spatial reference memory
   using the hole-board test. A significant effect of the entire training
   on memory performance (p = 0.032) was observed indicating that learning
   took place. Furthermore, the data showed a significant effect of the
   training-age factor interaction (p = 0.001) when the entire training
   was compared. The significant group differences were observed on day 2
   (p = 0.001) and at the retention test at day 3 (p = 0.011) with the
   group of young animals performing significantly better than aging group
   (Supplementary Figure [86]S1).

Quantitative Proteomics Reveals Decreased Levels of FMRP

   A quantitative MS-based approach was employed to identify proteins with
   significantly changed levels in the aging rats. The experimental design
   included two – young and aging – animal groups used in the previous
   behavioral test, five biological replicates per group. The
   membrane-enriched protein samples from DG were analyzed by LC–MS as
   TMT10plex labeling experiments in two sets representing two technical
   replicates per one biological replicate, i.e., two MS runs of each
   peptide fraction. Quantitative data for each individual are expressed
   as normalized protein abundance values for the corresponding TMT
   channel. A total number of 5832 proteins was identified in both groups,
   of which 153 were showing significantly different levels [p < 0.05,
   log2 (protein ratio) > |0.3|] between the groups. The complete list of
   significantly changed proteins as well as all identified proteins in
   the study is provided as supporting information (Supplementary Table
   [87]S1).

   The FMRP was unambiguously identified in the proteomic samples as
   downregulated [log2 (protein abundance ratio) = -0.39, p = 0.0005] in
   the aging group (Supplementary Table [88]S1) which was confirmed by
   western blotting (Figure [89]1A). The aging-dependent changes for FMRP
   in hippocampus were further analyzed by immunoflourescence microscopy
   with eight young and eight aging rats of the same behaviorally tested
   cohort. Consistently with general reduction in FMRP levels, there was a
   significant decrease (p = 0.002) in the total FMRP immunoreactivity per
   DG region in aging (7.86 ± 2.38) compared to young (12.85 ± 2.21)
   animals (Figure [90]1B). Furthermore, the comparison of individual DG
   subareas showed a significant decrease in FMRP labeling in aging rats
   in both, hilus (14.27 ± 3.03 vs. 8.72 ± 2.15, p = 0.002) and granular
   cell layer (21.55 ± 3.80 vs. 13.09 ± 6.08, p = 0.01).

FIGURE 1.

   FIGURE 1
   [91]Open in a new tab

   Comparison of FMRP levels between aging and young rats based on
   proteomics, immunoblotting and immunofluorescence (IF) microscopy. (A)
   The protein abundance levels of FMRP in young and aging rats obtained
   from a quantitative proteomic study (left) and immunoblot analysis
   (right). (B) Distribution of FMRP immunofluorescence analyzed in the
   hippocampal subareas of young and aging rats. Fluorescence images
   represent 10×, 20×, and 100× magnification of DG with FMRP labeled
   cells and neuropil in young and aging rats. Graphs represent percentage
   (%) of FMRP immunoreactivity in the granular layer (GL) and hilar (H)
   subareas of the DG area, as well as percentage (%) of total FMRP
   immunoreactivity throughout the whole DG. The differences were
   evaluated using Student’s t-test (p < 0.05). Values are expressed as
   mean ± SEM. ^∗p < 0.05, ^∗∗p < 0.01, ^∗∗∗p < 0.001.

Bioinformatic Analysis of Proteomic Results

   To dissect the global proteomic changes identified in the current study
   functional enrichment analysis was applied to differential protein
   dataset. The biological processes and molecular functions that may be
   altered in aging animals were identified based on Gene Onthology (GO)
   enrichment (p < 0.01). The results for biological processes showed the
   overrepresentation of GO terms associated with RNA metabolism,
   regulation of RNA splicing and stability, membrane raft organization,
   cell junction assembly, regulation of endocytosis, and synaptic
   plasticity. The most significant molecular functions were related to
   RNA binding activity, glycosaminoglycan binding activity, structural
   constituents of extracellular matrix and cytoskeleton (Figure [92]2A).
   For more detailed annotation the data were submitted to IPA software
   (Qiagen) that infers activation states (z-score) of the representative
   pathways and biological functions (p < 0.05). The aging-dependent
   downregulation of EIF2 signaling (z-score = 2.646) followed by
   dysregulation in 14-3-3 mediated signaling, axonal guidance signaling
   and cell junction signaling were found as the most significant
   pathways. The analysis of biological functions showed coordinated
   expression changes leading to an increase of RNA splicing (z-score =
   2.00), cell-to-cell contact (z-score = 2.05), a decrease in development
   of neurons (z-score = -2.13) and formation of microtubules (z-score =
   -2.14) in the aging group. The complete results obtained from GO
   enrichment and IPA analysis are provided as a supporting information
   (Supplementary Table [93]S2).

FIGURE 2.

   FIGURE 2
   [94]Open in a new tab

   Functional enrichment analysis and FMRP (FMR1)-associated interaction
   network of significantly changed proteins in aging rats. (A) The GO
   categories of the most regulated biological processes and molecular
   functions associated with significantly changed proteins in the aging
   group. The GO enrichment analysis (Benjamini–Hochberg p-Values < 0.01)
   was performed using ClueGO-Cytoscape platform ([95]Bindea et al., 2009;
   [96]Huntley et al., 2015). (B) The protein interaction network of
   significantly changed proteins centered around FMRP retrieved from IPA
   analysis (QIAGEN). Green color represents downregulated proteins and
   red color represents upregulated proteins in the aging group. The
   protein nodes are connected based on RNA/DNA – interactions
   (directional lines) or protein – protein interactions (simple lines).
   Autoregulation is represented by loops. The gene abbreviations are
   given in the text and Supplementary Table [97]S1.

   The STRING network (STRING v10.5 database^[98]2) of significant
   proteins formed several clusters of closely related members associated
   with previously enriched processes. Most of the clusters were connected
   with each other reflecting the functional closeness of the identified
   machineries (Supplementary Figure [99]S2). These include small groups
   of proteins involved in the formation of membrane structures and
   membrane vesicle trafficking (FLOT1, FLOT2, PASCIN2, BIN1, CLINT1),
   proteins associated with cell junctions (GJB2 GJB6, GJA1), and separate
   cluster of proteoglycans and proteoglycan-linked proteins (HAPLN1,
   VCAN, BCAN, ACAN, NCAN, TNC) linked to the group containing guanidine
   nucleotide binding (G) proteins (GNB4, GNG13). The enrichment of RNA
   metabolic activity in the significant proteomic dataset was represented
   by two big interconnected clusters associated with RNA processing and
   translation. Both clusters are linked to RNA-binding regulators
   involved in RNA transport and stability including FMRP, CAPRIN1, the
   members of Pumilio (PUM) and CUG-BP, Elav-like (CELF) family, and YTH
   N(6)-methyladenosine RNA-binding proteins (YTHDF).

   The IPA network analysis on the individual RNA/DNA – protein or protein
   – protein interactions of FMRP with the other significant proteins
   connected FMRP to nuclear FMRP interactor – NUFIP2, RNA-binding
   regulator – PUM2, purine rich element binding protein – PURB, splicing
   factor – SFPQ, BCL2 binding anthanogene – BAG3 and tubulin alpha-4A
   chain – TUBAA. Additionally, the network showed close association to
   several signaling nodes of ERK1/2 and SRC family and to general
   regulation of gene expression through histones and RNA polymerase
   (Figure [100]2B).

Discussion

   The critical role of FMRP in hippocampus was previously demonstrated in
   human Fragile X syndrome (FXR) patients and mouse FMR1 KO FXR models. A
   large spectrum of FXR-associated pathological changes found in mouse
   hippocampus include altered morphology of dendritic spines, behavioral
   changes, impairment of hippocampal synaptic plasticity and
   hippocampal-dependent memory tasks (reviewed in [101]Bostrom et al.,
   2016). Furthemore, deficits in long-term memory in hippocampus and
   spatial learning were observed in rat models of FXR ([102]Tian et al.,
   2017). Many of FXR symptoms share a high degree of similarity to
   systemic changes and cognitive decline during normal aging which points
   to aging-related changes in the processes regulated by FMRP.

   The lack of FMRP in mouse and rat KO models have been previously
   associated with impaired functionality of DG and hippocampal-dependent
   spatial memory ([103]Franklin et al., 2014; [104]Hébert et al., 2014;
   [105]Yau et al., 2016) with both affected during normal aging in
   mammals ([106]Lister and Barnes, 2009). In the current study, FMRP
   levels were analyzed in the DG of young (17 weeks) and aging (22
   months) rats and the results were confirmed by three different
   methodological approaches – quantitative proteomics, immunoblotting,
   and immunofluorescence microscopy. The cohorts of both animal groups
   were first behaviorally tested for performance in a
   hippocampal-dependent memory task and confirmed a significant decline
   in spatial reference memory in aging rats. Proteomic results showed a
   significant reduction of FMRP levels in the samples from the aging
   group. Immunoblotting was performed with KO-verified antibody MAB2160,
   previously used for analysis of FMRP in a rat FXR model ([107]Till et
   al., 2015). Several isoforms of FMRP around 70 kDa were detected with
   all signals significantly decreased in the aging rats. Consistently
   with proteomic- and immunoblotting data, the reduction of FMRP levels
   in total area or individual subareas of aging DG was confirmed by
   immunofluorescence microscopy.

   Reduction of FMRP in aging rats observed in the current study
   corroborates with the previous studies on changes of FMRP levels in
   total brain tissue from young and aging mice ([108]Singh et al., 2007;
   [109]Singh and Prasad, 2008). Interestingly, the authors found
   sex-related discrepancies in the level changes of FMR1 mRNA with
   consistent reduction of FMRP in the aging group which was attributed to
   interactions with specific transcription factors ([110]Singh and
   Prasad, 2008). All rats used in the experiments presented herein were
   males and the corresponding sex-related differences in the levels of
   FMRP and FMR1 mRNA in the aging rat brain remain to be investigated.

   In addition to FMRP the quantitative proteomic experiment allowed
   simultaneous detection of 153 proteins that were significantly up- or
   downregulated in the aging compared to young rats. Based on functional
   enrichment- and network analysis these proteins could be clustered into
   several groups implicated in the altered biological processes. The
   highest protein ratios were detected for proteoglycans and
   proteoglycan-associated proteins brevican (BCAN), neurocan (NCAN),
   versican (VCAN), aggrecan (ACAN), tenscin (TNC), and hyaluronan and
   proteoglycan link proteins (HAPLNs). These proteins are part of the
   extracellular brain matrix that plays a numerous roles in brain
   morphogenesis by controlling migration, proliferation and
   differentiation of neurons and facilitating molecular signaling
   ([111]Oohashi et al., 2015). The experiments in KO mice proved that
   these molecules have an essential function in maintaining synaptic
   plasticity in the DG ([112]Jansen et al., 2017). The proteins of
   membrane vesicles, lipid rafts and cell junctions formed another group
   significantly deregulated in the aging rats. These include Flotillins
   (FLOTs), Bridge integrator-1 (BIN1) or Protein Kinase C And Casein
   Kinase Substrate In Neurons 2 (PACSIN2) that were previously linked to
   synapse formation and function in hippocampus ([113]Swanwick et al.,
   2010; [114]Anggono et al., 2013; [115]Monje et al., 2013; [116]Zhang et
   al., 2015).

   Proteins related to translation machinery and RNA processing were the
   most represented group among the dysregulated proteins. The synthesis
   of new proteins is a key element for basic cellular functions but has
   been also implicated more specifically in memory formation. It was
   shown that protein synthesis is important for synaptic remodeling
   underlying the long-term memory ([117]Sutton and Schuman, 2006;
   [118]Alvarez-Castelao and Schuman, 2015), involved in the consolidation
   phase of hippocampal-dependent learning ([119]Rossato et al., 2007) and
   has a role in hippocampal synaptic plasticity ([120]Cajigas et al.,
   2010). The pathway enrichment analysis from the current study revealed
   a significant downregulation of EIF2 signaling (z-score = 2.646)
   representing a decrease in protein synthesis in DGs of the aging group.
   This has been also reported by previous studies on young and aging
   Sprague-Dawley rats ([121]Ingvar et al., 1985; [122]Smith et al., 1995)
   and represents confirmation of the proteomic results. Interestingly,
   the study of [123]Wei et al. (2015) recently revealed an important
   function of RNA-binding regulators in decoupling of transcription and
   translation processes during aging in prefrontal cortex of humans and
   monkeys. The network analysis of significant proteins presented herein
   connected the clusters of mRNA translation and splicing machineries to
   FMRP and several other RNA-binding regulators involved in RNA transport
   and stability including CAPRIN1, the members of Pumilio (PUM) and
   CUG-BP, Elav-like (CELF) family, and YTH N(6)-methyladenosine
   RNA-binding proteins (YTHDF). PUM proteins are closely related to FMRP
   through RNA-interactions and number of functions including DG
   neurogenesis and synaptic morphogenesis ([124]Vessey et al., 2010;
   [125]Zhang et al., 2017). CELF proteins has been proposed as regulators
   of synaptic plasticity and transmission in hippocampus ([126]Wagnon et
   al., 2012).

Conclusion

   The study presented herein showed that the level of the functional
   synaptic regulator, FMRP, in the rat DG is significantly reduced during
   aging. In addition, quantitative proteomics and bioinformatics
   identified several dysregulated protein clusters. The results
   emphasized the role of FMRP and other RNA-binding regulators in the
   modulation of DG protein synthesis during aging that warrant further
   analysis. The complete list of dysregulated proteins obtained from
   current study is presented in the result section and supplementary
   material, and might provide a useful dataset for further studies on
   aging in the rat hippocampus.

Author Contributions

   Conceived and designed the experiments: RS, FS, VK, HH, JW, and GL;
   performing experiments: RS, MK, TS, DR, JM, DF, and JW; collected data
   and processed them: RS, FS, TS, JM, DF, DR, and VK; interpreted the
   results: RS, GL, DM, and JW; wrote paper: RS, GL, VK, and DR; revised
   the intellectual content: GL, VK, DM, and HH. All authors read and
   approved the manuscript.

Conflict of Interest Statement

   The authors declare that the research was conducted in the absence of
   any commercial or financial relationships that could be construed as a
   potential conflict of interest.

Footnotes

   ^1

   [127]https://string-db.org/
   ^2

   [128]https://string-db.org/

Supplementary Material

   The Supplementary Material for this article can be found online at:
   [129]https://www.frontiersin.org/articles/10.3389/fnagi.2017.00384/full
   #supplementary-material
   TABLE S1

   The list of proteins identified in the quantitative proteomic study and
   the proteins with significantly changed levels between young and aging
   rats. The identified protein datasets with UniProt accession numbers,
   MS parameters and the statistics of the animal group comparison.
   [130]Click here for additional data file.^ (2.6MB, XLSX)
   [131]Click here for additional data file.^ (2.6MB, XLSX)
   TABLE S2

   The GO enrichment analysis and the identification of the most
   representative biological functions and canonical pathways associated
   with the differential protein dataset obtained from the quantitative
   proteomic study.
   [132]Click here for additional data file.^ (45.2KB, XLSX)
   [133]Click here for additional data file.^ (45.2KB, XLSX)
   [134]Click here for additional data file.^ (329.2KB, PDF)
   [135]Click here for additional data file.^ (478.1KB, PDF)

References