Skip to main content
NCBI home page
Journal of Neurophysiology logoLink to Journal of Neurophysiology
. 2020 Oct 14;124(6):1571–1577. doi: 10.1152/jn.00503.2020

Exercise-mediated alteration of hippocampal Dicer mRNA and miRNAs is associated with lower BACE1 gene expression and Aβ1-42 in female 3xTg-AD mice

Cory M Dungan 1,2,3, Taylor Valentino 2,6, Ivan J Vechetti Jr 2,6, Christopher J Zdunek 2, Michael P Murphy 3,4, Ai-Ling Lin 3,5, John J McCarthy 2,6, Charlotte A Peterson 1,2,✉
PMCID: PMC7814900  PMID: 33052800

Abstract

Changes to cerebral miRNA expression have been implicated in the progression of Alzheimer’s disease (AD), as miRNAs that regulate the expression of gene products involved in amyloid beta (Aβ) processing, such as BACE1, are dysregulated in those that suffer from AD. Exercise training improves cognition and reduces BACE1 and Aβ-plaque burden; however, the mechanisms are not fully understood. Using our progressive weighted wheel running (PoWeR) exercise program, we assessed the effect of 20 wk of exercise training on changes in hippocampal miRNA expression in female 3xTg-AD (3xTg) mice. PoWeR was sufficient to promote muscle hypertrophy and increase myonuclear abundance. Furthermore, PoWeR elevated hippocampal Dicer gene expression in 3xTg mice, while altering miRNA expression toward a more wild-type profile. Specifically, miR-29, which is validated to target BACE1, was significantly lower in sedentary 3xTg mice when compared with wild-type but was elevated following PoWeR. Accordingly, BACE1 gene expression, along with detergent-soluble Aβ1–42, was lower in PoWeR-trained 3xTg mice. Our data suggest that PoWeR training upregulates Dicer gene expression to alter cerebral miRNA expression, which may contribute to reduced Aβ accumulation and delay AD progression.

NEW & NOTEWORTHY Previous studies have outlined the beneficial effects of exercise on lowering BACE1 expression and reducing Aβ plaques. This study extends upon the work of others by outlining a new potential mechanism by which exercise elicits beneficial effects on Alzheimer’s disease pathology, specifically through modulation of Dicer and miRNA expression. This is the first study to examine Dicer and miRNA expression in the hippocampus of the 3xTg model within the context of exercise.

Keywords: Alzheimer’s disease, Dicer, exercise, miRNA, 3xTg

INTRODUCTION

Dysregulation of microRNAs (miRNAs) has been implicated as a contributing factor in the progression of Alzheimer’s disease (AD), where it plays a role in the pathogenesis of AD (Wang et al. 2011). The importance of miRNAs for brain health is further highlighted through studies investigating Dicer, the miRNA-processing enzyme that is essential for the maturation of miRNAs (reviewed in Shukla et al. 2011). In mouse, ablation of Dicer in various brain regions drastically lowers miRNA abundance, leading to neuronal loss (Hébert et al. 2010), brain shrinkage (Cuellar et al. 2008; De Pietri Tonelli et al. 2008; Hébert et al. 2010), and tau hyperphosphorylation (Hébert et al. 2010), along with changes in behavior (Cuellar et al. 2008; Davis et al. 2008) and premature death (Cuellar et al. 2008; Davis et al. 2008; De Pietri Tonelli et al. 2008; Hébert et al. 2010). Thus, normal miRNA abundance, and the processing of miRNAs by Dicer, are crucial for brain health and development.

The amyloid precursor protein (APP)-processing enzyme beta-secretase 1 (BACE1) is strongly linked to the development of AD because it is a key enzyme for the development of the hallmark amyloid beta (Aβ) plaques that accompany AD pathology. Individuals with AD exhibit significantly higher BACE1 expression compared with people without AD (Hébert et al. 2008), and deletion of BACE1 prevents the accumulation of Aβ and the development of AD (Luo et al. 2001). BACE1 expression is regulated through various mechanisms (reviewed in Hampel et al. 2020), including negative regulation by miRNAs such as miR-29 (Hébert et al. 2008; Zong et al. 2011), miR-107 (Wang et al. 2008), and miR-328 (Boissonneault et al. 2009), all miRNAs that are lower in AD brains. Endurance exercise downregulates BACE1 expression (Zhang et al. 2018) and reduces Aβ accumulation (Adlard et al. 2005) in AD mouse models and has been shown to alter brain miRNA abundance in non-AD models (Cosín-Tomás et al. 2014; Xu et al. 2020). Considering even small changes to BACE1 expression can cause a robust increase in amyloid plaques (Li et al. 2006), any change to pathways regulating BACE1 expression, including miRNA abundance, could contribute to AD pathology.

Given that endurance and resistance exercise upregulate Dicer expression in human skeletal muscle (Garner et al. 2020), and combined exercise is most effective in maintaining physical function, we set out to examine the effectiveness of a combined mouse exercise program, progressive weighted wheel running (PoWeR) (Dungan et al. 2019) in the 3xTg mouse model of AD. We tested the hypothesis that 20 wk of PoWeR would result in elevated Dicer gene expression, changes in miRNA abundance, and reduced BACE1 gene expression in the hippocampus.

METHODS

Ethical approval.

All animal procedures were approved by the Institutional Animal Care and Use Committee of the University of Kentucky. Mice were housed in a temperature- and humidity-controlled room and maintained on a 14:10-h light-dark cycle, and food and water were provided ad libitum. Animals were euthanized via exsanguination under isoflurane anesthesia, followed by cervical dislocation.

Animals.

Two-month-old female wild-type (B6129SF2/J) and 3xTg-AD mice were purchased from the Jackson Laboratory. We chose this age and sex because we wanted mice to begin exercise before the reported onset of AD pathology in this strain (Oddo et al. 2003) and male 3xTg mice do not develop robust AD pathology (Carroll et al. 2010). Groups of wild-type (n = 6) and 3xTg (n = 5) were singly house and remained sedentary for the duration of the study. A group of singly housed 3xTg mice (n = 5) performed 20 wk of PoWeR. Mice were fed standard rodent chow (Tekland 2018C; Envigo), and food was not removed before euthanization. Exercise wheels were locked 24 h before euthanization. Mice were 7.5–8 mo of age when euthanized.

Progressive weighted wheel running.

The protocol used in this study was adapted from our original protocol in C57Bl/6J mice (Dungan et al. 2019). Briefly, 2-mo-old 3xTg mice were acclimated to an unweighted running wheel for 1 wk before the start of the study. The loading strategy used is depicted in Fig. 1A. Mice were singly-housed to monitor total distance run (km/day), which was recorded using ClockLab software (Actimetrics). Magnets weighing 1 g were used to load the wheels (B661, K&J Magnetics).

Fig. 1.

Fig. 1.

Open in a new tab

Twenty weeks of progressive weighted wheel running (PoWeR) in female 3xTg mice promotes muscle hypertrophy and elevated myonuclear density. A: study design schematic with each arrowhead representing 1 wk, with the amount of weight added to the wheel indicated; mice were euthanized after 20 wk of PoWeR. B: average kilometers ran per day over 20 wk. C and D: end of study values for body weight (C) and absolute plantaris weight (D). E and F: representative images for fiber-type specific cross-sectional area (CSA) and myonuclear analyses in sedentary (E) and PoWeR-trained (F) mice. Dystrophin is in red; oxidative muscle fibers is in green; glycolytic muscle fibers are in black; and DAPI is in blue. G–I: quantification of muscle fiber CSA (G), myonuclei per fiber (H), and percentage of oxidative muscle fibers (I). Open bars are sedentary 3xTg mice; hashed bars are PoWeR-trained 3xTg mice; n = 5/group. *P < 0.05, significance between groups.

Immunohistochemistry.

Immunohistochemistry (IHC) analysis on plantaris muscles was performed as previously described by our laboratory, using antibodies against MyHC Type 1 (BA.D5; DSHB), MyHC Type 2a (SC.71, DSHB), and dystrophin (ab15277; Abcam) that are well-established specific antibodies (Fry et al. 2017). Images were captured using a Zeiss upright fluorescent microscope (Zeiss AxioImager M1, Germany) and were quantified using MyoVsion automated analysis software (Wen et al. 2018).

RNA isolation and RT-qPCR.

RNA was isolated from flash-frozen hippocampus tissue using the Direct-zol RNA Miniprep Plus kit (Zymo Research). RNA concentration was measured using a Nanodrop (Thermo Fisher), and RNA integrity was determined using an Agilent Bioanalyzer 2100 (Agilent). cDNA was synthesized using SuperScript IV VILO (Thermo Fisher) according to the manufacturer’s instructions. RT-qPCR was performed on a QuantStudio 3 (Thermo Fisher) using primers for the following: Dicer forward: TGTGATCCAGAGGAATTGGA and reverse: ACGGTCCACAGTCTACCACA; BACE1 forward: ACAACCTGAGGGGAAAGTCC and reverse: CAGGATGTTGAGCGTCTGTGG; PGK forward: CGAGCCTCACTGTCCAAACT and reverse: GTCTGCAACTTTAGCGCCTC; VCP forward: CTCCCTCCAAAGGCGTTCTT and reverse: TGGCCTCAGATTCCCCAAAC; and GAPDH forward: CTTTGGCATTGTGGAAGGGC and reverse: CAGGGATGATGTTCTGGGCA. Data were processed using the 2−(DeltaCt) method.

Nanostring.

One hundred nanograms of total RNA were used in the Nanostring nCounter miRNA Expression Panels, which were processed according to the manufacturer’s instructions. Data were acquired using nSolver software (Nanostring), and miRNAs with an average raw read count below 100 were excluded from the analysis. Raw read counts were first normalized by the geometric mean of the positive control and then by the geometric mean of the top 50 most abundant miRNAs. Data are expressed as normalized arbitrary units.

miRNA target prediction analysis.

Online prediction software was utilized to identify candidate target miRNAs for BACE1. Lists of miRNAs were generated using TargetScan (Agarwal et al. 2015) and miRSystem (Lu et al. 2012), and the common miRNAs were identified. The common miRNAs between the two programs were then compared with our list of miRNAs.

Protein isolation and Aβ1–42 ELISA.

Protein was isolated from the residual Trizol fraction following RNA extraction using a detailed protocol published by our laboratory (Wen et al. 2020). Detergent-soluble Aβ1–42 was then quantified using a commercially available ELISA (KHB3544; Thermo Fisher).

Statistics.

For comparisons between sedentary and PoWeR-trained 3xTg mice, a two-tailed t test was performed. For comparisons between sedentary wild-type, sedentary 3xTg, and PoWeR-trained 3xTg mice, a one-way ANOVA was used. If the one-way ANOVA was significant, a Tukey’s post hoc test was performed. Significance was set a P < 0.05.

RESULTS

Five months of PoWeR causes exercise-mediated adaptations in skeletal muscle of 3xTg mice.

Trained 3xTg mice ran an average of 6.9 km/day throughout the 20-wk training period, although running volume dropped from ∼11 km/day to ∼3 km/day over the training period (Fig. 1B). Body weight was not significantly different between sedentary and exercised 3xTg mice (Fig. 1C). Absolute muscle mass of the plantaris was significantly higher following PoWeR training (Fig. 1D), and PoWeR-trained mice had larger muscle fibers (Figs. 1, E–G), more myonuclei per fiber (Fig. 1H), and a trend for an oxidative fiber-type shift (Fig. 1I; P = 0.07). Taken together, our results indicate that PoWeR-trained 3xTg mice underwent physiologic muscle adaptations comparable to non-AD mice.

PoWeR alters hippocampal Dicer gene expression and miRNA abundance.

Dicer gene expression was lower in the hippocampus of sedentary 3xTg mice when compared with wild-type (Fig. 2A) but was significantly upregulated following PoWeR (Fig. 2A). We next used Nanostring to quantify miRNA abundance in the hippocampus. Following normalization, we compiled two sets of miRNAs: 1 that contained 78 differentially expressed miRNAs between sedentary wild-type and 3xTg mice (46 were lower in 3xTg mice; Table 1) and 1 that contained 63 differentially expressed miRNAs between sedentary and PoWeR-trained 3xTg mice (51 were higher in PoWeR-trained mice; Table 2). There were 38 miRNAs shared between the 2 analyses (underlined in Tables 1 and 2); 9 had an average expression value of greater than 1 (∼4,000 copies). To determine if BACE1 mRNA was a predicted target of these miRNAs, we compared the list of predicted miRNA target genes using two different software packages. Of the nine miRNAs, only miR-29 was validated to target BACE1 (Hébert et al. 2008; Zong et al. 2011) and was identified using both programs. miR-29a, -29b, and -29c were all significantly lower in sedentary 3xTg mice compared with wild type and higher following PoWeR (Fig. 2B). There were an additional four miRNAs that have been validated [miR-107 (Wang et al. 2008) and miR-328 (Boissonneault et al. 2009)] or predicted (miR-129 and miR-140) to target BACE1 from the 38 miRNAs in common, which were lower in sedentary 3xTg mice and higher following PoWeR. There was significantly lower BACE1 mRNA following PoWeR (Fig. 2C), along with lower detergent-soluble Aβ1–42 (Fig. 2D). Together, these data suggest that the exercise-mediated reduction of BACE1 and Aβ could be due to, at least in part, upregulation of miRNAs that target BACE1.

Fig. 2.

Fig. 2.

Open in a new tab

Higher Dicer gene expression and alterations to hippocampal miRNAs are associated with lower BACE1 mRNA and detergent-soluble Aβ1–42. A: fold-change expression of Dicer1 mRNA relative to sedentary wild-type mice. B: Nanostring analysis of miR-29 expressed as arbitrary units. C: fold-change expression of BACE1 mRNA relative to sedentary wild-type mice. D: detergent-soluble Aβ1–42 expressed as picograms per milliliter. E: Nanostring analysis of let-7 expressed as arbitrary units. Divot bars are wild-type mice; open bars are sedentary 3xTg mice; hashed bars are PoWeR-trained 3xTg mice; n = 5–6/group. *P < 0.05, significance vs. sedentary wild type. ^P < 0.05, significance vs. sedentary 3xTg.

Table 1.

Differentially expressed miRNAs between Sed WT versus Sed 3xTg

Sed WT Sed 3xTg P Value Sed WT Sed 3xTg P Value
miR-29a 6.70 ± 0.101 4.66 ± 0.259 0.0001 miR-154 0.15 ± 0.003 0.11 ± 0.006 0.0001
let-7g 5.02 ± 0.105 7.39 ± 0.580 0.0034 miR-30b 0.17 ± 0.010 0.10 ± 0.017 0.0100
let-7d 3.69 ± 0.118 7.03 ± 0.643 0.0007 miR-107 0.14 ± 0.003 0.10 ± 0.006 0.0001
miR-132 2.92 ± 0.175 5.73 ± 0.895 0.0141 miR-130a 0.13 ± 0.008 0.10 ± 0.005 0.0067
miR-29b 4.71 ± 0.156 2.60 ± 0.283 0.0002 miR-377 0.14 ± 0.005 0.11 ± 0.008 0.0039
miR-125a 2.41 ± 0.056 3.65 ± 0.232 0.0007 miR-376a 0.16 ± 0.006 0.08 ± 0.010 0.0001
miR-29c 3.07 ± 0.103 2.03 ± 0.202 0.0018 miR-153 0.17 ± 0.014 0.07 ± 0.016 0.0027
miR-218 2.26 ± 0.090 1.71 ± 0.142 0.0133 miR-350 0.10 ± 0.004 0.13 ± 0.009 0.0169
miR-30c 1.32 ± 0.069 2.64 ± 0.302 0.0024 miR-328 0.12 ± 0.008 0.06 ± 0.003 0.0003
let-7i 1.64 ± 0.065 2.09 ± 0.053 0.0011 miR-221 0.14 ± 0.010 0.09 ± 0.010 0.0055
miR-181a 1.45 ± 0.051 2.15 ± 0.207 0.0099 miR-21 0.12 ± 0.009 0.07 ± 0.010 0.0095
let-7a 2.03 ± 0.150 1.35 ± 0.127 0.0125 miR-125b 0.09 ± 0.002 0.11 ± 0.007 0.0061
miR-126 1.28 ± 0.049 1.66 ± 0.138 0.0314 miR-1839 0.08 ± 0.003 0.12 ± 0.011 0.0055
miR-129 1.48 ± 0.085 0.99 ± 0.173 0.0356 miR-434 0.09 ± 0.003 0.07 ± 0.005 0.0031
miR-99a 0.71 ± 0.042 0.99 ± 0.093 0.0270 miR-20a+20b 0.07 ± 0.002 0.12 ± 0.016 0.0135
let-7f 1.07 ± 0.073 0.72 ± 0.043 0.0058 miR-411 0.07 ± 0.003 0.11 ± 0.010 0.0095
miR-342 0.70 ± 0.025 0.84 ± 0.035 0.0128 miR-200b 0.05 ± 0.005 0.11 ± 0.019 0.0191
miR-434 0.69 ± 0.025 0.53 ± 0.054 0.0293 miR-378 0.07 ± 0.004 0.08 ± 0.004 0.0178
miR-27a 0.44 ± 0.019 0.80 ± 0.095 0.0051 miR-532 0.07 ± 0.002 0.08 ± 0.005 0.0262
miR-23a 0.49 ± 0.023 0.66 ± 0.066 0.0488 miR-425 0.06 ± 0.005 0.08 ± 0.004 0.0139
miR-151 0.48 ± 0.011 0.63 ± 0.031 0.0015 miR-1937a+1937b 0.10 ± 0.009 0.05 ± 0.005 0.0012
miR-369 0.52 ± 0.013 0.40 ± 0.044 0.0219 miR-129 0.08 ± 0.004 0.04 ± 0.004 0.0003
miR-150 0.34 ± 0.013 0.55 ± 0.063 0.0091 miR-592 0.06 ± 0.004 0.08 ± 0.006 0.0499
miR-128 0.60 ± 0.057 0.30 ± 0.024 0.0029 miR-24 0.08 ± 0.004 0.05 ± 0.003 0.0001
miR-376b 0.50 ± 0.026 0.27 ± 0.022 0.0002 miR-384 0.08 ± 0.007 0.04 ± 0.003 0.0009
miR-495 0.43 ± 0.017 0.32 ± 0.021 0.0032 miR-125a 0.04 ± 0.003 0.06 ± 0.009 0.0443
miR-103 0.38 ± 0.012 0.20 ± 0.019 0.0000 miR-539 0.05 ± 0.003 0.06 ± 0.005 0.0412
miR-127 0.35 ± 0.026 0.20 ± 0.022 0.0039 miR-331 0.05 ± 0.003 0.04 ± 0.003 0.0367
miR-329 0.23 ± 0.005 0.29 ± 0.019 0.0110 miR-222 0.06 ± 0.003 0.03 ± 0.002 0.0000
miR-543 0.19 ± 0.006 0.27 ± 0.024 0.0063 miR-365 0.06 ± 0.004 0.04 ± 0.002 0.0024
miR-149 0.22 ± 0.007 0.18 ± 0.008 0.0093 miR-140 0.05 ± 0.003 0.04 ± 0.004 0.0430
miR-137 0.27 ± 0.014 0.16 ± 0.015 0.0003 miR-143 0.05 ± 0.002 0.03 ± 0.003 0.0012
miR-145 0.24 ± 0.014 0.14 ± 0.009 0.0007 miR-212 0.05 ± 0.004 0.04 ± 0.003 0.0111
miR-487b 0.23 ± 0.005 0.14 ± 0.011 0.0001 miR-361 0.06 ± 0.005 0.04 ± 0.003 0.0169
miR-410 0.24 ± 0.016 0.15 ± 0.012 0.0035 miR-1198 0.04 ± 0.001 0.05 ± 0.005 0.0408
miR-340 0.21 ± 0.007 0.18 ± 0.010 0.0275 miR-1937c 0.04 ± 0.003 0.03 ± 0.003 0.0018
miR-15a 0.12 ± 0.006 0.17 ± 0.020 0.0263 miR-674 0.03 ± 0.002 0.05 ± 0.005 0.0147
miR-99b 0.17 ± 0.008 0.12 ± 0.014 0.0090 miR-26a 0.05 ± 0.003 0.03 ± 0.004 0.0058
miR-130b 0.11 ± 0.007 0.20 ± 0.030 0.0157 miR-324 0.04 ± 0.003 0.03 ± 0.002 0.0030
Open in a new tab

Data are shown as the average arbitrary units ± SE; n = 5–6/group. Data were sorted by largest to smallest average arbitrary units for all groups. Wt, wild type; Sed, sedentary. Thirty-eight miRNAs that are common between Tables 1 and 2 are underlined. Bolded miRNAs have been validated to target BACE1.

Table 2.

Differentially expressed miRNAs between Sed 3xTg versus PoWeR 3xTg

Sed 3xTg PoWeR 3xTg P Value Sed 3xTg PoWeR 3xTg P Value
miR-125b 9.73 ± 0.591 16.35 ± 1.014 0.001 miR-434 0.07 ± 0.005 0.10 ± 0.005 0.001
miR-29a 4.66 ± 0.259 6.79 ± 0.318 0.002 miR-148b 0.08 ± 0.004 0.10 ± 0.002 0.009
let-7g 7.39 ± 0.580 4.67 ± 0.087 0.003 miR-551b 0.07 ± 0.006 0.12 ± 0.008 0.001
let-7d 7.03 ± 0.643 4.14 ± 0.148 0.004 miR-106a+17 0.07 ± 0.007 0.10 ± 0.004 0.004
miR-132 5.73 ± 0.895 2.99 ± 0.195 0.028 miR-146a 0.06 ± 0.004 0.09 ± 0.009 0.022
miR-29b 2.60 ± 0.283 3.81 ± 0.338 0.039 miR-129 0.04 ± 0.004 0.09 ± 0.008 0.001
miR-125a 3.65 ± 0.232 2.72 ± 0.109 0.012 miR-15b 0.06 ± 0.004 0.07 ± 0.002 0.012
miR-29c 2.03 ± 0.202 2.88 ± 0.225 0.036 miR-24 0.05 ± 0.003 0.07 ± 0.005 0.004
miR-30c 2.64 ± 0.302 1.72 ± 0.079 0.030 miR-181c 0.06 ± 0.005 0.07 ± 0.004 0.027
let-7i 2.09 ± 0.053 1.69 ± 0.067 0.003 miR-384 0.04 ± 0.003 0.06 ± 0.004 0.008
let-7e 1.46 ± 0.085 1.20 ± 0.006 0.028 miR-152 0.05 ± 0.003 0.06 ± 0.005 0.004
miR-720 0.74 ± 0.059 1.02 ± 0.067 0.022 miR-331 0.04 ± 0.003 0.07 ± 0.006 0.002
miR-342 0.84 ± 0.035 0.69 ± 0.014 0.010 miR-30e 0.04 ± 0.005 0.06 ± 0.003 0.018
miR-135a 0.53 ± 0.033 0.67 ± 0.036 0.026 miR-222 0.03 ± 0.002 0.05 ± 0.003 0.000
miR-376b 0.27 ± 0.022 0.36 ± 0.019 0.017 miR-365 0.04 ± 0.002 0.05 ± 0.004 0.003
miR-103 0.20 ± 0.019 0.38 ± 0.027 0.001 miR-140 0.04 ± 0.004 0.06 ± 0.004 0.002
miR-1944 0.26 ± 0.021 0.33 ± 0.016 0.038 miR-143 0.03 ± 0.003 0.06 ± 0.010 0.010
miR-127 0.20 ± 0.022 0.26 ± 0.012 0.042 miR-190 0.04 ± 0.005 0.05 ± 0.003 0.025
miR-149 0.18 ± 0.008 0.23 ± 0.006 0.003 miR-212 0.04 ± 0.003 0.05 ± 0.004 0.008
miR-145 0.14 ± 0.009 0.23 ± 0.024 0.010 miR-142 0.03 ± 0.004 0.06 ± 0.012 0.022
miR-487b 0.14 ± 0.011 0.18 ± 0.006 0.015 miR-369 0.03 ± 0.003 0.05 ± 0.005 0.009
miR-98 0.16 ± 0.008 0.13 ± 0.004 0.033 miR-1937c 0.03 ± 0.003 0.04 ± 0.006 0.020
miR-130b 0.20 ± 0.030 0.12 ± 0.005 0.047 miR-26a 0.03 ± 0.004 0.04 ± 0.004 0.019
miR-154 0.11 ± 0.006 0.17 ± 0.005 0.000 miR-324 0.03 ± 0.002 0.04 ± 0.002 0.008
miR-191 0.13 ± 0.008 0.17 ± 0.014 0.034 miR-431 0.03 ± 0.003 0.04 ± 0.003 0.023
miR-107 0.10 ± 0.006 0.15 ± 0.007 0.000 miR-1 0.02 ± 0.001 0.04 ± 0.006 0.021
miR-130a 0.10 ± 0.005 0.17 ± 0.019 0.008 miR-34b 0.03 ± 0.003 0.04 ± 0.005 0.049
miR-377 0.11 ± 0.008 0.13 ± 0.008 0.041 miR-34b 0.02 ± 0.003 0.04 ± 0.005 0.029
miR-350 0.13 ± 0.009 0.10 ± 0.005 0.046 miR-423 0.03 ± 0.002 0.04 ± 0.003 0.043
miR-328 0.06 ± 0.003 0.14 ± 0.018 0.004 miR-345 0.02 ± 0.002 0.04 ± 0.003 0.012
miR-21 0.07 ± 0.010 0.12 ± 0.009 0.004 miR-34a 0.02 ± 0.002 0.03 ± 0.002 0.047
miR-1839 0.12 ± 0.011 0.08 ± 0.004 0.020
Open in a new tab

Data are shown as the average arbitrary units ± SE; n = 5–6/group. Data were sorted by largest to smallest average arbitrary units for all groups. PoWeR, progressive weighted wheel running; Sed, sedentary. Thirty-eight miRNAs that are common between Tables 1 and 2 are underlined. Bolded miRNAs have been validated to target of BACE1.

Although Dicer regulates global miRNA abundance, it can also be negatively regulated by miRNAs, specifically members of the let-7 family (Forman et al. 2008). We observed significantly higher let-7d, -7g, and -7i abundance in sedentary 3xTg mice compared with wild type (Fig. 2E), which were lower following PoWeR (Fig. 2E). The change in let-7 with AD and exercise corresponds to our observed changes in Dicer gene expression (Fig. 2A).

DISCUSSION

In the present study, we used our PoWeR model of murine exercise training to expand on the results of others that show exercise lowers BACE1 gene expression and Aβ accumulation in the hippocampus. Our results indicate that miRNAs involved in regulating BACE1 are lower in sedentary female 3xTg mice compared with wild type and are elevated following exercise. Dicer mRNA is lower in sedentary female 3xTg compared with wild type and is higher following exercise, suggesting that elevation of Dicer expression following exercise leads to changes in miRNA abundance and slows AD pathology. To our knowledge, this is the first report of Dicer gene expression in the hippocampus of the 3xTg model with or without exercise.

Endurance exercise has been shown to lower Aβ abundance in mouse models of AD (Adlard et al. 2005; Zhang et al. 2018). The mechanisms responsible for these changes are very complex; however, we focused on reduction in BACE1 expression (Zhang et al. 2018). BACE1 is a provocative target for the treatment of AD, as deletion of BACE1 reduces Aβ plaques and prevents a decline in cognition in mice (Luo et al. 2001). We show that exercise lowers BACE1 gene expression and propose that this is mediated, in part, by an upregulation of the miR-29 family. BACE1 is a validated target of miR-29 (Hébert et al. 2008; Zong et al. 2011) and is lower in AD patients (Hébert et al. 2008; Wang et al. 2011). Considering miR-29 was one of the most abundant miRNAs in our analysis, the exercise-mediated elevation of the miR-29 family could be responsible for our observed changes in BACE1 mRNA abundance and, indirectly, Aβ. In addition to miR-29, some of the less abundant miRNAs in our list were validated [miR-107 (Wang et al. 2008) and miR-328 (Boissonneault et al. 2009)] or predicted (miR-129 and miR-140) to target BACE1 and were lower with AD and higher following PoWeR, further supporting a role for miRNAs in the regulation of BACE1 expression with exercise.

Global changes in miRNA abundance are a consistent finding in those that suffer from AD. There are various factors that could contribute to dysregulation of miRNAs in AD brains; however, Dicer stands out as a likely candidate due to the key role it plays in brain size (Cuellar et al. 2008; De Pietri Tonelli et al. 2008; Hébert et al. 2010), behavior (Cuellar et al. 2008; Davis et al. 2008), and longevity (Cuellar et al. 2008; Davis et al. 2008; De Pietri Tonelli et al. 2008; Hébert et al. 2010). We report that Dicer mRNA is lower in the hippocampus of female 3xTg mice compared with wild type. PoWeR was sufficient to upregulate Dicer gene expression, which was associated with higher abundance in 51 out of 63 miRNAs. Others have shown endurance exercise is sufficient to alter miRNA abundance in non-AD mouse models (Cosín-Tomás et al. 2014; Xu et al. 2020); however, we are the first to show that these changes in miRNA abundance are associated with correspondingly higher Dicer gene expression. In our analysis, members of the let-7 family were higher in sedentary 3xTg mice when compared with wild-type and were lower following exercise. As let-7 negatively regulates Dicer expression, this could be a mechanism by which AD and exercise modulate Dicer expression to alter global miRNA abundance and AD progression.

There are several limitations to the present study. First, we do not have an exercised wild-type control, so we cannot determine if exercise upregulates Dicer in the brains of wild-type mice, although exercise upregulates Dicer in human skeletal muscle (Garner et al. 2020). Second, due to the limited size of the hippocampus, extensive analyses of different Aβ isoforms and Tau were not possible. Reports are mixed on the effect of exercise on Tau hyperphosphorylation, but exercise consistently lowers Aβ40, Aβ42, insoluble Aβ, and Aβ plaques in models of AD (Adlard et al. 2005; Kim et al. 2019; Zhang et al. 2018). Third, it is unknown if the genetic overexpression of APP in the 3xTg model can have secondary effects on downregulating miRNA and Dicer; however, our results suggest elevated APP results in higher let-7 expression, which negatively regulates Dicer. As APP is overexpressed in AD brains compared with aged-matched controls (Neve et al. 1988; Rockenstein et al. 1995), we believe the findings are relevant to potential effects of exercise on human AD pathology.

Collectively, our data show that PoWeR upregulates Dicer gene expression and miRNAs important for the regulation of BACE1, adding a new potential mechanism for the beneficial effects of exercise on AD pathology. Combining endurance and resistance exercise training may be the most beneficial strategy for both slowing AD progression and maintaining physical function.

GRANTS

This research was supported by NIH Grants AR-060701, AG-049806, and DK-119619 (to J.J.M. and C.A.P.) and AG-028383 and AG-057461 (to C.M.D.).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

A.L. conceived and designed research; T.R.V., I.J.V., and C.J.Z. performed experiments; T.R.V., I.J.V., and C.J.Z. analyzed data; T.R.V., I.J.V., C.J.Z., and M.P.M. interpreted results of experiments; C.M.D. and J.M. drafted manuscript; C.M.D., T.R.V., I.J.V., M.P.M., A.L. and J.M. edited and revised manuscript; C.M.D., T.R.V., I.J.V., C.J.Z., M.P.M., A.L. and J.M. approved final version of manuscript.

ACKNOWLEDGMENTS

The authors thank Dr. Linda Van Eldik for thoughtful comments on the project. The authors apologize for the omission of any relevant references due to space limitations.

REFERENCES

  1. Adlard PA, Perreau VM, Pop V, Cotman CW. Voluntary exercise decreases amyloid load in a transgenic model of Alzheimer’s disease. J Neurosci 25: 4217–4221, 2005. doi: 10.1523/JNEUROSCI.0496-05.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Agarwal V, Bell GW, Nam JW, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. eLife 4: e05005, 2015. doi: 10.7554/eLife.05005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Boissonneault V, Plante I, Rivest S, Provost P. MicroRNA-298 and microRNA-328 regulate expression of mouse beta-amyloid precursor protein-converting enzyme 1. J Biol Chem 284: 1971–1981, 2009. doi: 10.1074/jbc.M807530200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Carroll JC, Rosario ER, Kreimer S, Villamagna A, Gentzschein E, Stanczyk FZ, Pike CJ. Sex differences in β-amyloid accumulation in 3xTg-AD mice: role of neonatal sex steroid hormone exposure. Brain Res 1366: 233–245, 2010. doi: 10.1016/j.brainres.2010.10.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Cosín-Tomás M, Alvarez-López MJ, Sanchez-Roige S, Lalanza JF, Bayod S, Sanfeliu C, Pallàs M, Escorihuela RM, Kaliman P. Epigenetic alterations in hippocampus of SAMP8 senescent mice and modulation by voluntary physical exercise. Front Aging Neurosci 6: 51, 2014. doi: 10.3389/fnagi.2014.00051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cuellar TL, Davis TH, Nelson PT, Loeb GB, Harfe BD, Ullian E, McManus MT. Dicer loss in striatal neurons produces behavioral and neuroanatomical phenotypes in the absence of neurodegeneration. Proc Natl Acad Sci USA 105: 5614–5619, 2008. doi: 10.1073/pnas.0801689105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Davis TH, Cuellar TL, Koch SM, Barker AJ, Harfe BD, McManus MT, Ullian EM. Conditional loss of Dicer disrupts cellular and tissue morphogenesis in the cortex and hippocampus. J Neurosci 28: 4322–4330, 2008. doi: 10.1523/JNEUROSCI.4815-07.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. De Pietri Tonelli D, Pulvers JN, Haffner C, Murchison EP, Hannon GJ, Huttner WB. miRNAs are essential for survival and differentiation of newborn neurons but not for expansion of neural progenitors during early neurogenesis in the mouse embryonic neocortex. Development 135: 3911–3921, 2008. doi: 10.1242/dev.025080. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Dungan CM, Murach KA, Frick KK, Jones SR, Crow SE, Englund DA, Vechetti IJ Jr, Figueiredo VC, Levitan BM, Satin J, McCarthy JJ, Peterson CA. Elevated myonuclear density during skeletal muscle hypertrophy in response to training is reversed during detraining. Am J Physiol Cell Physiol 316: C649–C654, 2019. doi: 10.1152/ajpcell.00050.2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Forman JJ, Legesse-Miller A, Coller HA. A search for conserved sequences in coding regions reveals that the let-7 microRNA targets Dicer within its coding sequence. Proc Natl Acad Sci USA 105: 14879–14884, 2008. doi: 10.1073/pnas.0803230105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Fry CS, Kirby TJ, Kosmac K, McCarthy JJ, Peterson CA. Myogenic progenitor cells control extracellular matrix production by fibroblasts during skeletal muscle hypertrophy. Cell Stem Cell 20: 56–69, 2017. doi: 10.1016/j.stem.2016.09.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Garner RT, Solfest JS, Nie Y, Kuang S, Stout J, Gavin TP. Multivesicular body and exosome pathway responses to acute exercise. Exp Physiol 105: 511–521, 2020. doi: 10.1113/EP088017. [DOI] [PubMed] [Google Scholar]
  13. Hampel H, Vassar R, De Strooper B, Hardy J, Willem M, Singh N, Zhou J, Yan R, Vanmechelen E, De Vos A, Nisticò R, Corbo M, Imbimbo BP, Streffer J, Voytyuk I, Timmers M, Tahami Monfared AA, Irizarry M, Albala B, Koyama A, Watanabe N, Kimura T, Yarenis L, Lista S, Kramer L, Vergallo A. The β-secretase BACE1 in Alzheimer’s disease. Biol Psychiatry S0006-3223(20)30063-9, 2020. doi: 10.1016/j.biopsych.2020.02.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Hébert SS, Horré K, Nicolaï L, Papadopoulou AS, Mandemakers W, Silahtaroglu AN, Kauppinen S, Delacourte A, De Strooper B. Loss of microRNA cluster miR-29a/b-1 in sporadic Alzheimer’s disease correlates with increased BACE1/beta-secretase expression. Proc Natl Acad Sci USA 105: 6415–6420, 2008. doi: 10.1073/pnas.0710263105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hébert SS, Papadopoulou AS, Smith P, Galas MC, Planel E, Silahtaroglu AN, Sergeant N, Buée L, De Strooper B. Genetic ablation of Dicer in adult forebrain neurons results in abnormal tau hyperphosphorylation and neurodegeneration. Hum Mol Genet 19: 3959–3969, 2010. doi: 10.1093/hmg/ddq311. [DOI] [PubMed] [Google Scholar]
  16. Kim D, Cho J, Kang H. Protective effect of exercise training against the progression of Alzheimer’s disease in 3xTg-AD mice. Behav Brain Res 374: 112105, 2019. doi: 10.1016/j.bbr.2019.112105. [DOI] [PubMed] [Google Scholar]
  17. Li Y, Zhou W, Tong Y, He G, Song W. Control of APP processing and Abeta generation level by BACE1 enzymatic activity and transcription. FASEB J 20: 285–292, 2006. doi: 10.1096/fj.05-4986com. [DOI] [PubMed] [Google Scholar]
  18. Lu TP, Lee CY, Tsai MH, Chiu YC, Hsiao CK, Lai LC, Chuang EY. miRSystem: an integrated system for characterizing enriched functions and pathways of microRNA targets. PLoS One 7: e42390, 2012. doi: 10.1371/journal.pone.0042390. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Luo Y, Bolon B, Kahn S, Bennett BD, Babu-Khan S, Denis P, Fan W, Kha H, Zhang J, Gong Y, Martin L, Louis JC, Yan Q, Richards WG, Citron M, Vassar R. Mice deficient in BACE1, the Alzheimer’s beta-secretase, have normal phenotype and abolished beta-amyloid generation. Nat Neurosci 4: 231–232, 2001. doi: 10.1038/85059. [DOI] [PubMed] [Google Scholar]
  20. Neve RL, Finch EA, Dawes LR. Expression of the Alzheimer amyloid precursor gene transcripts in the human brain. Neuron 1: 669–677, 1988. doi: 10.1016/0896-6273(88)90166-3. [DOI] [PubMed] [Google Scholar]
  21. Oddo S, Caccamo A, Shepherd JD, Murphy MP, Golde TE, Kayed R, Metherate R, Mattson MP, Akbari Y, LaFerla FM. Triple-transgenic model of Alzheimer’s disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron 39: 409–421, 2003. doi: 10.1016/S0896-6273(03)00434-3. [DOI] [PubMed] [Google Scholar]
  22. Rockenstein EM, McConlogue L, Tan H, Power M, Masliah E, Mucke L. Levels and alternative splicing of amyloid beta protein precursor (APP) transcripts in brains of APP transgenic mice and humans with Alzheimer’s disease. J Biol Chem 270: 28257–28267, 1995. doi: 10.1074/jbc.270.47.28257. [DOI] [PubMed] [Google Scholar]
  23. Shukla GC, Singh J, Barik S. MicroRNAs: processing, maturation, target recognition and regulatory functions. Mol Cell Pharmacol 3: 83–92, 2011. [PMC free article] [PubMed] [Google Scholar]
  24. Wang WX, Huang Q, Hu Y, Stromberg AJ, Nelson PT. Patterns of microRNA expression in normal and early Alzheimer’s disease human temporal cortex: white matter versus gray matter. Acta Neuropathol 121: 193–205, 2011. doi: 10.1007/s00401-010-0756-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Wang WX, Rajeev BW, Stromberg AJ, Ren N, Tang G, Huang Q, Rigoutsos I, Nelson PT. The expression of microRNA miR-107 decreases early in Alzheimer’s disease and may accelerate disease progression through regulation of beta-site amyloid precursor protein-cleaving enzyme 1. J Neurosci 28: 1213–1223, 2008. doi: 10.1523/JNEUROSCI.5065-07.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Wen Y, Murach KA, Vechetti IJ Jr, Fry CS, Vickery C, Peterson CA, McCarthy JJ, Campbell KS. MyoVision: software for automated high-content analysis of skeletal muscle immunohistochemistry. J Appl Physiol (1985) 124: 40–51, 2018. doi: 10.1152/japplphysiol.00762.2017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Wen Y, Vechetti IJ Jr, Valentino TR, McCarthy JJ. High-yield skeletal muscle protein recovery from TRIzol after RNA and DNA extraction. Biotechniques 69: 264–269, 2020. doi: 10.2144/btn-2020-0083. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Xu L, Zheng YL, Yin X, Xu SJ, Tian D, Zhang CY, Wang S, Ma JZ. Excessive treadmill training enhances brain-specific microRNA-34a in the mouse hippocampus. Front Mol Neurosci 13: 7, 2020. doi: 10.3389/fnmol.2020.00007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Zhang J, Guo Y, Wang Y, Song L, Zhang R, Du Y. Long-term treadmill exercise attenuates Aβ burdens and astrocyte activation in APP/PS1 mouse model of Alzheimer’s disease. Neurosci Lett 666: 70–77, 2018. doi: 10.1016/j.neulet.2017.12.025. [DOI] [PubMed] [Google Scholar]
  30. Zong Y, Wang H, Dong W, Quan X, Zhu H, Xu Y, Huang L, Ma C, Qin C. miR-29c regulates BACE1 protein expression. Brain Res 1395: 108–115, 2011. doi: 10.1016/j.brainres.2011.04.035. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Neurophysiology are provided here courtesy of American Physiological Society

RESOURCES