ORIGINAL RESEARCH article

Front. Neurosci., 10 September 2020

Sec. Neurodegeneration

Volume 14 - 2020 | https://doi.org/10.3389/fnins.2020.580524

miRNA Alterations Elicit Pathways Involved in Memory Decline and Synaptic Function in the Hippocampus of Aged Tg4-42 Mice

  • 1. Division of Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Georg-August-University, Göttingen, Germany

  • 2. Research Group Computational Systems Medicine, Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan (WZW), Technical University of Munich (TUM), Weihenstephan, Germany

  • 3. Human Molecular Genetics Group, Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany

Abstract

The transcriptome of non-coding RNA (ncRNA) species is increasingly focused in Alzheimer’s disease (AD) research. NcRNAs comprise, among others, transfer RNAs, long non-coding RNAs and microRNAs (miRs), each with their own specific biological function. We used smallRNASeq to assess miR expression in the hippocampus of young (3 month old) and aged (8 month old) Tg4-42 mice, a model system for sporadic AD, as well as age-matched wildtype controls. Tg4-42 mice express N-truncated Aβ4–42, develop age-related neuron loss, reduced neurogenesis and behavioral deficits. Our results do not only confirm known miR-AD associations in Tg4-42 mice, but more importantly pinpoint 22 additional miRs associated to the disease. Twenty-five miRs were differentially expressed in both aged Tg4-42 and aged wildtype mice while eight miRs were differentially expressed only in aged wildtype mice, and 33 only in aged Tg4-42 mice. No significant alteration in the miRNome was detected in young mice, which indicates that the changes observed in aged mice are down-stream effects of Aβ-induced pathology in the Tg4-42 mouse model for AD. Targets of those miRs were predicted using miRWalk. For miRs that were differentially expressed only in the Tg4-42 model, 128 targets could be identified, whereas 18 genes were targeted by miRs only differentially expressed in wildtype mice and 85 genes were targeted by miRs differentially expressed in both mouse models. Genes targeted by differentially expressed miRs in the Tg4-42 model were enriched for negative regulation of long-term synaptic potentiation, learning or memory, regulation of trans-synaptic signaling and modulation of chemical synaptic transmission obtained. This untargeted miR sequencing approach supports previous reports on the Tg4-42 mice as a valuable model for AD. Furthermore, it revealed miRs involved in AD, which can serve as biomarkers or therapeutic targets.

Introduction

MiRs are short non-coding RNAs that are heavily involved in post-transcriptional regulation of gene expression through targeting specific mRNAs (Bartel, 2004). The miR transcriptome (miRNome) includes all miR species and renders a profile of gene regulation at the studied time point and location. Altered miR expression profiles therefore provide information not only about the miRs themselves, but also about their target genes and, hence, the regulated processes. As miRs have already been implicated in neurodevelopment and brain aging, as well as in synapse function and cognitive performance, in both, health and disease (Salta and De Strooper, 2012, 2017b), this information can pinpoint mechanisms involved in the molecular pathogenesis of Alzheimer’s disease (AD). Furthermore, miRs can easily be targeted by artificial oligonucleotides to influence gene regulation for therapeutic processes (Roshan et al., 2009). Hence, miRNome profiling ultimately promotes the search for new biomarkers and therapeutics.

Next-generation sequencing (NGS) of the miR pool offers an unbiased technical approach to identify the miR signature of cells, tissues or organs. Previous reports have demonstrated the power of NGS to unravel the molecular profile of pathological alterations in neurodegenerative diseases like AD (Twine et al., 2011). Differentially expressed genes (DEGs) were identified by RNASeq of young, and aged Tg4-42 mice in comparison with 5XFAD mice, another AD mouse model (Bouter et al., 2014). Many of the DEGs specifically found in the 5XFAD model belong to neuroinflammatory processes typically associated with plaques. Other DEGs were found in both AD mouse models indicating common disease pathways associated with behavioral deficits and neuron loss. The 5XFAD model develops early plaque formation, intraneuronal Aβ aggregation, neuron loss, and behavioral deficits (Oakley et al., 2006; Jawhar et al., 2012). As such the 5XFAD model is widely used in the AD field. High-throughput RNASeq analysis of young 5XFAD mice, e.g., identified DEGs in the frontal cortex mainly associated with cardiovascular disease and DEGs in the cerebellum mainly associated with mitochondrial dysfunction (Kim et al., 2012).

A plethora of previous publications discuss miRs as potentially involved in the pathogenesis of AD and/or as putative biomarkers for AD including several systematic assessments of the importance of miRs in this disorder [reviewed for example by Salta and De Strooper (2012, 2017b), Angelucci et al. (2019), Wang et al. (2019)]. Notably, the expression of miR-338-5p was significantly down-regulated in the hippocampus of patients with AD and 5XFAD transgenic mice (Qian et al., 2019). The expression of miR-146a correlated with plaque load and synaptic pathology in Tg2576 and in 5XFAD mice (Li et al., 2011).

We have performed NGS of the miRNome of the hippocampus of young (3 month old) and aged (8 month old) Tg4-42 mice, which represent a unique model for sporadic AD. The Tg4-42 model expresses only wildtype non-mutant Aβ4–42 and develops at the age of 8 months, severe neuron loss and hippocampus-related behavioral deficits (Bouter et al., 2013). At 3 months of age, Tg4-42 mice show reduced neurogenesis (Gerberding et al., 2019) and synaptic hyperexcitability (Dietrich et al., 2018), which represents an early sign of AD-typical alteration. Reduced glucose metabolism detected by FDG-PET in vivo imaging (Bouter et al., 2019) correlates well with the observed neuron loss and neurological deficits at 8 months of age (Bouter et al., 2013). The aim of the current study was to identify miRs and their targets to unravel molecules and processes triggered by AD-typical memory deficits and hippocampal neuron death. Therefore, we compared the age of 3 months (prior to neuron loss and neurological alterations) with the age of 8 months (after onset of neuron loss and neurological alterations).

Materials and Methods

Transgenic Mice

We used the transgenic mouse lines Tg4-42 kept on the C57Bl/6J genetic background. Tg4-42 mice express human Aβ4–42 fused to the murine TRH signal peptide under the control of the neuronal Thy-1 promoter (Bouter et al., 2013). Young (3 month) and aged (8 month) Tg4-42 and age-matched wildtype control mice (WT, C57BL/6J) were studied. All animals were handled according to the German guidelines for animal care. All efforts were made to minimize suffering and the number of animals used for this study.

Tissue Harvesting

Mice were sacrificed via CO2 anaesthetization followed by cervical dislocation. Brain hemispheres were carefully dissected and the hippocampus removed, frozen on dry ice and stored at −80°C for subsequent use.

Small RNA Next-Generation Sequencing

Small RNA-isolation was performed using the miRVana miRNA Isolation Kit (Life Technologies) according to the manufacturer’s instructions. For library preparation, we used the Ion Total RNA-Seq Kit v2 for Small RNA Libraries (Life Technologies) for sequencing on an Ion PGM system (Thermo Fisher Scientific) running Torrent Suite software 5.12.1., again following the instructions of the manufacturer. STAR v2.6.0a with default parameters was used to map the reads to the GRCm38 (mm10) mouse assembly (Dobin et al., 2013). Afterward, read counts per feature were determined with HTSeq v0.10.0 (Anders et al., 2015). Bam files were submitted to the European Nucleotide Archive1 with the accession identification number of the project PRJEB39314.

Differential Expression Analysis

During quality control of the mapped data, RNAs with less than 10 readcounts across all samples were excluded and technical replicates were collapsed after heatmap inspection (Supplementary Figure S1). Transcripts with less than 10 reads across all remaining samples were discarded. The heatmap in Supplementary Figure S1 was compiled with variance-stabilized data, while the differential expression analyses were conducted on the raw count data, due to DESeq2’s statistical model (Love et al., 2014). The comparisons were done across contrasts corresponding to the age groups or the genotypes, respectively. Correction for multiple testing was done via independent hypothesis weighting as implemented in DESeq2 (Love et al., 2014), and a result was deemed significant if FDR <0.05.”

MiR Target and Overrepresentation Analysis

For the target mining of differentially expressed miRs (FDR<0.05) we used miRWalk version 3 (Sticht et al., 2018), which uses a random forest based algorithm, and TarPmiR (Ding et al., 2016), to predict possible miR targets. It also allows to compare the results with the predictions of other target mining algorithms such as TargetScan (Agarwal et al., 2015) and miRDB (Chen and Wang, 2020), as well as validated interactions from miRTarBase (Chou et al., 2018). Only gene targets that were confirmed by at least two of these databases were considered for the further analysis to minimize false positives. The analysis required unique miR names mapped to the specific strand. Hence, we used both miR-3p and miR-5p, if available. The identified targets were then used to conduct a Gene Ontology (GO) (Rigden and Fernandez, 2018) overrepresentation analysis with the PANTHER algorithm (Mi et al., 2019) relying on the GO release of December 9th, 2019, to check for biological processes that are targeted by the differentially expressed miRs.

Results

NGS of Non-coding RNAs in Mouse Hippocampus

Small RNASeq yielded 761,373 and 1,054,109 raw sequence reads for young and old wildtype (WT) mouse hippocampi, respectively. For young WT mice on average 160,723 reads (n = 4; on average 84% of raw reads) and for old WT mice 213,338 reads (n = 4; on average 81% of raw reads) per animal were mapped.

For Tg4-42 mice a total of 758,968 (4 young animals) and 2,252,799 (4 old animals, each sequenced twice) raw reads were produced. In young Tg4-42 mice, mapping was successful for on average 160,808 reads per sample (on average 85% of raw reads) and for old Tg4-42 mice on average 449,797 mapped reads per animal (224,899 reads per sample; on average 80% of raw reads) were obtained.

Analyses of miRs at 3 and 8 Months of Age in Tg4-42 and Wildtype Mice

In order to demonstrate the expression and significant distribution of identified miRs volcano plots were created (Figures 1A,B). In total, 237 miRs were detected. There was a significant change in expression of 58 miRs observed between young and aged Tg4-42, as well as between young and aged WT mice (Figure 1C). No significant differences were observed across genotypes within an age group (data not shown). Of 33 differentially expressed miRs exclusively found in aged Tg4-42 mice, some were reported to be association with AD. The remaining miRs could now be associated with an AD-typical mouse model for the first time. Figure 2 demonstrates the levels of all miRs with a significantly altered expression level between 3 and 8 months of age either in Tg4-42, WT or in both. In aged Tg4-42 mice, mostly decreased levels of miRs have been observed.

FIGURE 1

FIGURE 2

Table 1 lists references for known links to AD, other neurodegenerative disorders and/or brain function. Five miRs identified in aged WT mouse brain were increased and four decreased during aging (Table 2). MiRs found in both Tg4-42 and WT hippocampi were decreased during aging, only one was increased (Table 3). The GO annotation analysis of predicted miR targets in Tg4-42 revealed that reduced long-term synaptic potentiation, learning or memory, regulation of trans-synaptic signaling and modulation of chemical synaptic transmission obtained top scores (Figure 3A). None of these annotations were overrepresented in WT mice (Figure 3B). The GO analysis of predicted miR targets in either Tg4-42 or WT mice or both elicited also other cellular components (Table 4), molecular functions (Table 5) and biological processes (Table 6).

TABLE 1

MiRs significantly altered in hippocampus between 3 and 8 month-old exclusively in Tg4-42 mice.

References are given for known links to Alzheimer’s disease, other neurodegenerative disorders and/or brain function. Supplementary Table S1 shows the entire list of miRs level changes. Decreased expression level at 8 month of age, −; increased expression level at 8 month of age, +.

TABLE 2

ExpressionReferences
miR-100−1.1Lu et al., 2017; Elliott et al., 2018; Ottaviani et al., 2019
miR-1298−1.9
miR-153+1.2Gui et al., 2015
miR-191−0.7Smith et al., 2010
miR-34b−1.5
miR-423+1.0
miR-666−1.4
miR-667+1.6

MiRs significantly altered in hippocampus between 3 and 8 month-old exclusively in wildtype mice.

References are given for known links to Alzheimer’s disease, other neurodegenerative disorders and/or brain function. Supplementary Table S1 shows the entire list of miRs level changes. Decreased expression level at 8 month of age, −; increased expression level at 8 month of age, +.

TABLE 3

Expression In WT miceExpression In Tg4-42 miceReferences
miR-127−1.1−0.7Essandoh et al., 2016
miR-128-1−1.7↓ 1.2Tiribuzi et al., 2014
miR-128-2−1.4−1.5
miR-130a−1.9−1.3Zhao et al., 2014
miR-138-1−0.9−0.8Lin et al., 2018
miR-140−0.9−1.0
miR-150−1.8−1.0Punga et al., 2015
miR-204−1.0−2.3Cammaerts et al., 2015
miR-212−1.7−0.8Wang W.X. et al., 2011
miR-221−1.3−1.0Seeley et al., 2018
miR-222−0.6−1.0Wang et al., 2015; Seeley et al., 2018
miR-23a−1.9−2.6Fenoglio et al., 2016
miR-23b−1.0−0.7
miR-300−1.0−0.5Li et al., 2018
miR-30a−1.1−0.7Sun et al., 2016
miR-30d−0.6−0.6
miR-3102+1.2+1.3
miR-328+0.7+1.8
miR-329−1.3−1.0Urdinguio et al., 2010
miR-34c−1.0−1.2Haramati et al., 2011
miR-382−1.1−1.1Song et al., 2017
miR-434−1.2−1.3
miR-877+0.8+1.5Zhao et al., 2020
miR-99a−0.8−1.3Bras et al., 2018
miR-99b−0.7−0.9Cao et al., 2017

MiRs significantly altered in hippocampus between 3 and 8 month-old wildtype mice and Tg4-42 mice.

References are given for known links to Alzheimer’s disease, other neurodegenerative disorders and/or brain function. Supplementary Table S1 shows the entire list of miRs level changes. Decreased expression level at 8 month of age, −; increased expression level at 8 month of age, +.

FIGURE 3

TABLE 4

Tg4-42WT


Gene ontologyLabelFDRNo. genesNo. miRsFDRNo. genesNo. miRs
Significant in Tg4-42 and WT
1GO:0000785Chromatin2.24E-0216133.17E-02119
2GO:0005622Intracellular1.08E-04161348.21E-038218
3GO:0043231Intracellular membrane-bounded organelle3.51E-03125312.96E-026618
4GO:0043229Intracellular organelle1.18E-02137333.75E-027318
5GO:0005634Nucleus8.52E-0389301.56E-025217
6GO:0043226Organelle4.61E-03142338.78E-037618
Significant in Tg4-42 only
1GO:0110165Cellular anatomical entity1.11E-02189352.87E-019319
2GO:0005694Chromosome4.53E-0223152.32E-01139
3GO:0043227Membrane-bounded organelle3.42E-03132327.72E-026819
4GO:0098794Postsynapse2.73E-0218109.06E-0187
5GO:0032991Protein-containing complex9.02E-0376261.00E+03412
6GO:0045202Synapse4.25E-0331151.00E+0127
7GO:0097060Synaptic membrane2.43E-021471.00E+054
Significant in WT only
1GO:0031981Nuclear lumen1.65E-0154243.20E-023513

GO annotation and pathway enrichment analysis of predicted miR targets on Cellular Components.

Benjamini–Hochberg False Discovery Rate (FDR).

TABLE 5

Tg4-42WT


Gene ontologyLabelFDRNo. genesNo. miRsFDRNo. genesNo. miRs
Significant in Tg4-42 and WT
1GO:0005488Binding9.51E-05159361.22E-027920
2GO:0035326cis-regulatory region binding1.46E-0320152.17E-021210
3GO:0000987cis-regulatory region sequence-specific DNA binding1.35E-0320152.16E-021210
4GO:0003677DNA binding2.45E-0442211.69E-022414
5GO:0000981DNA-binding transcription factor activity, RNA polymerase II-specific2.35E-0425171.56E-021411
6GO:1901363Heterocyclic compound binding1.10E-0375282.48E-023916
7GO:0003676Nucleic acid binding1.08E-0353242.41E-022916
8GO:0097159organic cyclic compound binding1.62E-0375283.45E-023916
9GO:0005515Protein binding4.25E-06128333.60E-046716
10GO:0001067regulatory region nucleic acid binding5.16E-0426191.45E-021512
11GO:0000978RNA polymerase II cis-regulatory region sequence-specific DNA binding1.15E-0320152.09E-021210
12GO:0001012RNA polymerase II regulatory region DNA binding4.73E-0425182.00E-021411
13GO:0000977RNA polymerase II regulatory region sequence-specific DNA binding4.59E-0425181.99E-021411
14GO:0043565sequence-specific DNA binding1.03E-0329181.47E-021812
15GO:1990837sequence-specific double-stranded DNA binding1.24E-0325182.95E-021411
16GO:0008134Transcription factor binding1.06E-0219113.04E-02126
17GO:0140110Transcription regulator activity1.25E-0436201.77E-021912
18GO:0044212Transcription regulatory region DNA binding5.32E-0426191.73E-021512
19GO:0000976Transcription regulatory region sequence-specific DNA binding6.36E-0425182.27E-021411
Significant in Tg4-42 only
1GO:0001216DNA-binding transcription activator activity3.00E-0214107.50E-0297
2GO:0001228DNA-binding transcription activator activity, RNA polymerase II-specific2.92E-0214107.85E-0297
3GO:0003700DNA-binding transcription factor activity1.06E-0430187.46E-021411
4GO:0140297DNA-binding transcription factor binding1.14E-021387.67E-0285
5GO:0001217DNA-binding transcription repressor activity1.10E-021181.00E+044
6GO:0001227DNA-binding transcription repressor activity, RNA polymerase II-specific1.14E-021181.00E+044
7GO:0003690Double-stranded DNA binding1.30E-0326186.18E-021411
8GO:0043167Ion binding1.17E-0277308.46E-013716
9GO:0019904Protein domain specific binding4.26E-0321141.00E+064

GO annotation and pathway enrichment analysis of predicted miR targets on Molecular Function.

Benjamini–Hochberg False Discovery Rate (FDR).

TABLE 6

Tg4-42WT


Gene ontologyLabelFDRNo. genesNo. miRsFDRNo. genesNo. miRs
Significant in Tg4-42 and WT
1GO:0048856Anatomical structure development1.05E-0585322.28E-024214
2GO:0048646Anatomical structure formation involved in morphogenesis1.83E-0221112.61E-03168
3GO:0009653Anatomical structure morphogenesis8.34E-0546224.24E-053012
4GO:0048513Animal organ development1.22E-0353245.78E-033112
5GO:0007420Brain development1.59E-0319112.81E-03136
6GO:0000902Cell morphogenesis4.41E-0217113.64E-02127
7GO:0032989Cellular component morphogenesis3.30E-0219121.17E-02148
8GO:0016043Cellular component organization8.48E-0580245.23E-034311
9GO:0071840Cellular component organization or biogenesis1.67E-0481246.33E-034411
10GO:0007417Central nervous system development1.44E-0220123.08E-02136
11GO:0048598Embryonic morphogenesis2.44E-0216122.65E-03138
12GO:0007167Enzyme linked receptor protein signaling pathway2.72E-0317123.38E-03126
13GO:0060322Head development3.91E-0319115.83E-03136
14GO:0007275Multicellular organism development1.30E-0477294.27E-034214
15GO:0009890Negative regulation of biosynthetic process3.09E-0537234.01E-021812
16GO:2000113Negative regulation of cellular macromolecule biosynthetic process3.14E-0535224.08E-021712
17GO:0010629Negative regulation of gene expression1.15E-0539231.61E-022013
18GO:0010605Negative regulation of macromolecule metabolic process2.61E-0550234.26E-022513
19GO:0051172Negative regulation of nitrogen compound metabolic process2.58E-0548224.97E-022312
20GO:1903507Negative regulation of nucleic acid-templated transcription8.74E-0531202.82E-021611
21GO:0045934Negative regulation of nucleobase-containing compound metabolic process3.80E-0535201.84E-021811
22GO:1902679Negative regulation of RNA biosynthetic process8.73E-0531202.80E-021611
23GO:0051253Negative regulation of RNA metabolic process5.03E-0533202.14E-021711
24GO:0045892Negative regulation of transcription, DNA-templated8.63E-0531202.76E-021611
25GO:0007399Nervous system development1.52E-0343202.46E-022410
26GO:0048518Positive regulation of biological process9.98E-0797307.35E-055215
27GO:0009891Positive regulation of biosynthetic process4.06E-0542224.52E-052712
28GO:0031328Positive regulation of cellular biosynthetic process2.76E-0542223.37E-052712
29GO:0031325Positive regulation of cellular metabolic process9.67E-0764281.12E-053814
30GO:0048522Positive regulation of cellular process7.16E-0790281.78E-055014
31GO:0010628Positive regulation of gene expression9.37E-0849222.74E-052812
32GO:0010557Positive regulation of macromolecule biosynthetic process7.11E-0642224.21E-052612
33GO:0010604Positive regulation of macromolecule metabolic process1.33E-0766282.40E-053714
34GO:0009893Positive regulation of metabolic process7.36E-0768292.64E-053814
35GO:0051173Positive regulation of nitrogen compound metabolic process2.30E-0661281.51E-053714
36GO:1903508Positive regulation of nucleic acid-templated transcription3.00E-0639221.58E-052512
37GO:0045935Positive regulation of nucleobase-containing compound metabolic process1.21E-0746259.54E-062813
38GO:1902680Positive regulation of RNA biosynthetic process2.83E-0639221.37E-052512
39GO:0051254Positive regulation of RNA metabolic process2.66E-0845251.64E-052713
40GO:0045944Positive regulation of transcription by RNA polymerase II1.07E-0328164.64E-041910
41GO:0045893Positive regulation of transcription, DNA-templated7.21E-0638211.80E-052512
42GO:0022603Regulation of anatomical structure morphogenesis9.88E-0427163.42E-02159
43GO:0009889Regulation of biosynthetic process1.03E-0873286.46E-043514
44GO:0031326Regulation of cellular biosynthetic process9.92E-0973285.24E-043514
45GO:2000112Regulation of cellular macromolecule biosynthetic process1.02E-0869273.29E-043414
46GO:0031323Regulation of cellular metabolic process1.18E-0896303.35E-044615
47GO:0010468regulation of gene expression5.80E-0978276.35E-043614
48GO:0010556Regulation of macromolecule biosynthetic process9.78E-0971284.07E-043414
49GO:0060255Regulation of macromolecule metabolic process1.05E-0896301.33E-034515
50GO:0019222regulation of metabolic process1.26E-08100312.53E-034615
51GO:0051171Regulation of nitrogen compound metabolic process1.03E-0892303.23E-044515
52GO:1903506Regulation of nucleic acid-templated transcription3.18E-0862263.24E-043113
53GO:0019219Regulation of nucleobase-containing compound metabolic process2.72E-0869292.01E-043514
54GO:0080090Regulation of primary metabolic process9.49E-0995303.46E-044515
55GO:2001141Regulation of RNA biosynthetic process3.06E-0862263.16E-043113
56GO:0051252Regulation of RNA metabolic process9.26E-0967293.19E-043314
57GO:0006357Regulation of transcription by RNA polymerase II8.21E-0746235.09E-042413
58GO:0006355Regulation of transcription, DNA-templated6.53E-0861253.38E-043113
59GO:0048731System development3.77E-0572282.69E-033913
60GO:0009888Tissue development3.53E-0230173.96E-021911
61GO:0035239Tube morphogenesis2.66E-0320102.96E-02127
Significant in Tg4-42 only
1GO:0009887Animal organ morphogenesis2.48E-0222152.10E-01129
2GO:0008306Associative learning4.10E-02651.00E+0021
3GO:0007610Behavior1.71E-0320129.40E-0175
4GO:0065007Biological regulation7.24E-04143353.44E-016716
5GO:0048514Blood vessel morphogenesis2.02E-021389.93E-0154
6GO:0048468Cell development1.12E-0439194.83E-01169
7GO:0030154Cell differentiation1.09E-0361264.39E-012813
8GO:0034330Cell junction organization5.87E-0315113.88E-0174
9GO:0048667Cell morphogenesis involved in neuron differentiation2.35E-021391.14E-0186
10GO:0032990Cell part morphogenesis1.22E-0215118.20E-0297
11GO:0048858Cell projection morphogenesis7.70E-0315116.72E-0297
12GO:0048869cellular developmental process1.78E-0361264.59E-012813
13GO:0044260Cellular macromolecule metabolic process5.72E-0463245.02E-01298
14GO:0044237Cellular metabolic process4.38E-0280281.00E+00339
15GO:0009987Cellular process1.28E-02155371.00E+006916
16GO:0044267Cellular protein metabolic process2.83E-0245205.60E-01228
17GO:0006464cellular protein modification process8.05E-0340199.41E-02228
18GO:0070887Cellular response to chemical stimulus1.47E-0344192.56E-01218
19GO:0006974Cellular response to DNA damage stimulus2.24E-021691.00E+0033
20GO:0071495Cellular response to endogenous stimulus3.29E-0323142.78E-01116
21GO:0071363Cellular response to growth factor stimulus1.19E-0213112.08E-0175
22GO:0071310Cellular response to organic substance1.70E-0337181.68E-01188
23GO:0033554Cellular response to stress2.60E-0227151.00E+0086
24GO:0050890Cognition8.16E-0414116.99E-0154
25GO:1904888Cranial skeletal system development4.16E-02553.06E-0133
26GO:0007010Cytoskeleton organization1.23E-0224152.90E-01125
27GO:0048589Developmental growth2.96E-021371.34E-0186
28GO:0032502Developmental process4.12E-0587326.05E-024214
29GO:0009790Embryo development3.48E-0224155.95E-02159
30GO:0060429Epithelium development2.60E-0222141.05E-011310
31GO:0007186G protein-coupled receptor signaling pathway1.82E-02439.95E-0132
32GO:0035195Gene silencing by miRNA7.35E-03556.48E-0122
33GO:0048699Generation of neurons1.40E-0335171.12E-011810
34GO:0040007Growth3.84E-021371.51E-0186
35GO:0035556Intracellular signal transduction3.13E-0330158.90E-01127
36GO:0070059Intrinsic apoptotic signaling pathway in response to endoplasmic reticulum stress4.26E-02446.05E-0122
37GO:0007612Learning6.44E-03989.88E-0132
38GO:0007611Learning or memory2.69E-0414115.76E-0154
39GO:0007616Long-term memory6.81E-03551.15E-0133
40GO:0043170Macromolecule metabolic process3.88E-0476289.76E-01329
41GO:0043412Macromolecule modification1.78E-0241191.84E-01228
42GO:0007613Memory2.35E-03983.43E-0144
43GO:0035278miRNA mediated inhibition of translation2.69E-02331.00E+0011
44GO:0050804Modulation of chemical synaptic transmission2.01E-0419128.98E-0165
45GO:0032501Multicellular organismal process1.82E-0294317.10E-014514
46GO:0061061muscle structure development2.24E-0214104.53E-0175
47GO:0048519Negative regulation of biological process7.27E-0477271.49E-013813
48GO:0009895Negative regulation of catabolic process4.44E-021071.00E+0033
49GO:0010648Negative regulation of cell communication4.37E-0226121.00E+00107
50GO:0010721Negative regulation of cell development9.76E-031381.00E+0032
51GO:0045596Negative regulation of cell differentiation1.89E-0321121.00E+0065
52GO:0034249Negative regulation of cellular amide metabolic process4.37E-02771.00E+0011
53GO:0031327Negative regulation of cellular biosynthetic process1.75E-0537236.36E-021712
54GO:0031330Negative regulation of cellular catabolic process4.05E-02961.00E+0022
55GO:0031324Negative regulation of cellular metabolic process3.16E-0653236.26E-022412
56GO:0048523Negative regulation of cellular process4.26E-0472251.06E-013612
57GO:0032269Negative regulation of cellular protein metabolic process4.24E-0221121.00E+0086
58GO:0051093Negative regulation of developmental process2.57E-0325147.96E-01107
59GO:1902532Negative regulation of intracellular signal transduction2.94E-021488.35E-0166
60GO:0010558Negative regulation of macromolecule biosynthetic process4.95E-0535225.11E-021712
61GO:0051045Negative regulation of membrane protein ectodomain proteolysis1.03E-02339.48E-0222
62GO:0009892Negative regulation of metabolic process3.02E-0656256.65E-022613
63GO:0051241Negative regulation of multicellular organismal process1.50E-0227165.08E-01138
64GO:0051961Negative regulation of nervous system development4.69E-021171.00E+0021
65GO:0050768Negative regulation of neurogenesis3.01E-021171.00E+0021
66GO:0043524Negative regulation of neuron apoptotic process2.88E-02871.55E-0155
67GO:1901215Negative regulation of neuron death1.51E-021091.29E-0166
68GO:0045665Negative regulation of neuron differentiation1.82E-021071.00E+0011
69GO:2000635Negative regulation of primary miRNA processing3.82E-02226.20E-0111
70GO:0048585Negative regulation of response to stimulus4.16E-0229131.00E+00107
71GO:0023057Negative regulation of signaling4.42E-0226121.00E+00107
72GO:0000122Negative regulation of transcription by RNA polymerase II3.74E-0322154.21E-01108
73GO:0017148Negative regulation of translation2.46E-02771.00E+0011
74GO:0040033negative regulation of translation, ncRNA-mediated2.70E-02331.00E+0011
75GO:0022008Neurogenesis8.64E-0437191.45E-011810
76GO:0048666Neuron development2.70E-0322131.69E-01117
77GO:0030182Neuron differentiation2.64E-0325155.69E-02149
78GO:0031175neuron projection development1.78E-0320131.46E-01107
79GO:0048812Neuron projection morphogenesis6.34E-0315116.01E-0297
80GO:0006807Nitrogen compound metabolic process4.11E-0274271.00E+00329
81GO:0006996Organelle organization3.94E-0351215.06E-02289
82GO:0016310Phosphorylation4.05E-0221141.00E+0096
83GO:0120039Plasma membrane bounded cell projection morphogenesis6.89E-0315116.34E-0297
84GO:0045597Positive regulation of cell differentiation1.50E-0224138.00E-02148
85GO:0030307Positive regulation of cell growth3.58E-02865.61E-0144
86GO:0048639Positive regulation of developmental growth1.63E-031186.76E-0144
87GO:0051094Positive regulation of developmental process1.57E-0230152.09E-01169
88GO:0045927Positive regulation of growth1.40E-031391.00E+0044
89GO:1900273positive regulation of long-term synaptic potentiation1.60E-02431.00E+0011
90GO:0061014Positive regulation of mRNA catabolic process1.56E-02551.00E+0011
91GO:0048636Positive regulation of muscle organ development1.57E-02641.00E+0011
92GO:1901863Positive regulation of muscle tissue development2.84E-03751.00E+0022
93GO:0050769Positive regulation of neurogenesis3.52E-021581.56E-0195
94GO:0045666Positive regulation of neuron differentiation1.66E-021486.05E-0295
95GO:0010976Positive regulation of neuron projection development2.09E-021286.07E-0285
96GO:1900153Positive regulation of nuclear-transcribed mRNA catabolic process, deadenylation-dependent decay6.12E-03441.00E+0011
97GO:0060213Positive regulation of nuclear-transcribed mRNA poly(A) tail shortening1.98E-03441.00E+0011
98GO:0045844Positive regulation of striated muscle tissue development1.56E-02641.00E+0011
99GO:0050806Positive regulation of synaptic transmission8.45E-03981.00E+0033
100GO:0009791Post-embryonic development2.00E-02777.25E-0133
101GO:0016441Posttranscriptional gene silencing1.38E-02557.50E-0122
102GO:0035194Posttranscriptional gene silencing by RNA1.29E-02557.29E-0122
103GO:0019538Protein metabolic process4.44E-0251231.00E+00228
104GO:0036211Protein modification process7.99E-0340199.33E-02228
105GO:0006468Protein phosphorylation4.16E-0217114.21E-0196
106GO:0042981Regulation of apoptotic process2.00E-0229163.06E-01159
107GO:0050770Regulation of axonogenesis1.82E-02966.59E-0265
108GO:0050789regulation of biological process1.53E-04141359.13E-026716
109GO:0065008Regulation of biological quality1.90E-0569231.68E-01318
110GO:0009894Regulation of catabolic process2.68E-0322153.68E-01106
111GO:0010646Regulation of cell communication1.14E-0460223.45E-012612
112GO:0060284Regulation of cell development2.47E-0223118.90E-01105
113GO:0045595Regulation of cell differentiation1.35E-0338176.79E-02209
114GO:0022604Regulation of cell morphogenesis4.39E-0214105.97E-0175
115GO:0042127Regulation of cell population proliferation2.30E-0231171.00E+00107
116GO:0034248Regulation of cellular amide metabolic process2.68E-021291.00E+0022
117GO:0031329Regulation of cellular catabolic process1.96E-0320146.40E-0185
118GO:0051128Regulation of cellular component organization1.65E-0346231.50E-012311
119GO:0060341Regulation of cellular localization1.04E-0323116.31E-0195
120GO:0050794Regulation of cellular process8.35E-05136345.79E-026515
121GO:0032268Regulation of cellular protein metabolic process7.75E-0344234.38E-012112
122GO:0048638Regulation of developmental growth1.25E-021398.77E-0155
123GO:0050793Regulation of developmental process5.53E-0346211.33E-012410
124GO:0040029Regulation of gene expression, epigenetic1.92E-02971.00E+0032
125GO:0060968Regulation of gene silencing1.81E-02661.00E+0011
126GO:0060964Regulation of gene silencing by miRNA7.93E-03551.00E+0011
127GO:0060966Regulation of gene silencing by RNA1.02E-02551.00E+0011
128GO:0040008Regulation of growth5.38E-0319121.00E+0066
129GO:0032879Regulation of localization5.41E-0452175.64E-02278
130GO:1900271Regulation of long-term synaptic potentiation2.85E-04767.69E-0122
131GO:0042391Regulation of membrane potential2.93E-021273.32E-0173
132GO:0065009Regulation of molecular function4.38E-0241203.15E-012210
133GO:2000026Regulation of multicellular organismal development6.79E-0339195.69E-022210
134GO:0051239Regulation of multicellular organismal process1.52E-0251238.43E-022811
135GO:0048634Regulation of muscle organ development1.89E-02859.31E-0133
136GO:1901861Regulation of muscle tissue development4.60E-03964.39E-0144
137GO:0051960Regulation of nervous system development3.96E-0325122.89E-01126
138GO:0050767Regulation of neurogenesis5.14E-0323115.93E-01105
139GO:0043523Regulation of neuron apoptotic process7.20E-031191.56E-0166
140GO:1901214Regulation of neuron death7.69E-0313114.55E-0166
141GO:0045664Regulation of neuron differentiation2.62E-0321105.01E-0195
142GO:0010975Regulation of neuron projection development2.13E-021694.40E-0185
143GO:0099601Regulation of neurotransmitter receptor activity3.27E-02559.02E-0122
144GO:1900151Regulation of nuclear-transcribed mRNA catabolic process, deadenylation-dependent decay7.94E-03441.00E+0011
145GO:0060211Regulation of nuclear-transcribed mRNA poly(A) tail shortening2.94E-03441.00E+0011
146GO:0060147Regulation of posttranscriptional gene silencing1.03E-02551.00E+0011
147GO:2000634Regulation of primary miRNA processing3.80E-02226.19E-0111
148GO:0043067Regulation of programmed cell death2.26E-0229162.02E-01169
149GO:0032880Regulation of protein localization4.11E-0222132.95E-01127
150GO:0051246Regulation of protein metabolic process1.28E-0245235.12E-012212
151GO:0023051Regulation of signaling4.97E-0561223.54E-012612
152GO:0016202Regulation of striated muscle tissue development1.70E-02859.25E-0133
153GO:0051963Regulation of synapse assembly1.86E-02755.64E-0253
154GO:0050807Regulation of synapse organization2.61E-021081.69E-0164
155GO:0050803Regulation of synapse structure or activity3.38E-021081.98E-0164
156GO:0048167Regulation of synaptic plasticity2.92E-0615127.00E-0144
157GO:0045974Regulation of translation, ncRNA-mediated2.67E-02331.00E+0011
158GO:0051049Regulation of transport1.26E-0236143.17E-01186
159GO:0099177Regulation of trans-synaptic signaling2.04E-0419128.99E-0165
160GO:0060627Regulation of vesicle-mediated transport4.23E-021587.31E-0172
161GO:0042221Response to chemical1.26E-0254229.38E-01248
162GO:0009719Response to endogenous stimulus1.53E-0327151.87E-01137
163GO:0032354Response to follicle-stimulating hormone1.91E-02331.45E-0122
164GO:0034698Response to gonadotropin4.15E-02332.28E-0122
165GO:0070848Response to growth factor1.52E-0213112.37E-0175
166GO:0009725Response to hormone2.19E-0216114.43E-0185
167GO:0010033Response to organic substance4.12E-0240195.53E-01208
168GO:0050779RNA destabilization3.48E-02441.00E+0011
169GO:0060021Roof of mouth development1.41E-04985.24E-0133
170GO:0050808Synapse organization1.49E-021191.00E+0043
171GO:0035295Tube development1.45E-0324126.01E-02138
Significant in WT only
1GO:0016477Cell migration6.09E-011471.15E-02147
2GO:0000904Cell morphogenesis involved in differentiation6.51E-021491.90E-02116
3GO:0048870Cell motility4.92E-011671.18E-02157
4GO:0051674Localization of cell4.93E-011671.20E-02157
5GO:0040011Locomotion1.65E-0121108.95E-03177
6GO:0060485Mesenchyme development6.24E-02861.82E-0276
7GO:0006928Movement of cell or subcellular component1.46E-0124111.84E-02187
8GO:0001843Neural tube closure4.55E-01444.21E-0255
9GO:0051169Nuclear transport1.39E-01741.54E-0274
10GO:0006913Nucleocytoplasmic transport1.39E-01741.57E-0274
11GO:0050772Positive regulation of axonogenesis1.42E-01544.71E-0365
12GO:0010770Positive regulation of cell morphogenesis involved in differentiation2.79E-01641.12E-0275
13GO:0048729Tissue morphogenesis1.15E-0114103.68E-02119
14GO:0060606Tube closure4.63E-01444.27E-0255

GO annotation and pathway enrichment analysis of predicted miR targets on Biological Process.

Benjamini–Hochberg False Discovery Rate (FDR).

Discussion

We performed NGS of the miRNome of the hippocampus of Tg4-42 mice, a model for sporadic AD. We assessed the pool of miRs before and after onset of AD-typical changes like gliosis, reduced glucose uptake into the brain, neuron loss and loss of reference memory (Bouter et al., 2013, 2019; Dietrich et al., 2018; Gerberding et al., 2019). The Tg4-42 mouse model is one of few mouse models developing neuron death in the CA1 region of the hippocampus (Bayer and Wirths, 2014), as such it might provide a powerful tool for preclinical drug testing and identification of the underlying molecular pathways driving AD pathology. The difference of diverse miR levels between 3 and 8 months of age in Tg4-42 elicits the AD-typical effects after onset of neuron loss and behavioral deficits. We cannot draw any conclusion on the difference in miR levels in aged mice, as the normal lifespan is at least 24 months.

At least 1% of the human genome encodes miR and every miR can regulate up to 200 mRNAs suggesting that dysregulation of miR expression could be associated with several human pathological conditions including central neurological disorders (Angelucci et al., 2019). In addition to NGS of the miRs, we have performed a search for the targets of identified miRs using state-of-the-art bioinformatics and addressed the question whether the affected processes are meaningful in the context of known AD-typical changes in the Tg4-42 mouse model.

MiRs Identified in the Hippocampus of 8 Month Old Tg4-42 Mice

A total of 33 miRs were altered in the hippocampus between 3 and 8 month-old exclusively found in Tg4-42 mice. All but one was significantly decreased at the age of 8 months. Some of the miRs identified were already linked to AD pathology, while others could be associated to AD for the first time. In gray matter of the brain of patients with AD, down-regulation of a set of miRs (including several miR-15/107 genes and miR-29 paralogs) correlated strongly with the density of amyloid plaques. MiR-212 was found decreased in white matter, whereas miR-424 was upregulated in AD (Wang A. et al., 2011). Expression of miR-107 and BACE1 mRNA correlated with alterations in brain pathology in individuals with mild cognitive impairment (Wang et al., 2016). MiR-107 reversed the impairments of spatial memory and long-term potentiation caused by intraventricular injection of Aβ1–42 (Shu et al., 2018). MiR-125a may have a role in regulating the translation of PSD-95 mRNA. Impairments in the local synthesis of PSD-95, important for synaptic structure and function, may affect dendritic spine development and synaptic plasticity in fragile X syndrome (Ifrim et al., 2015). MiR-125b-1 induced tau hyperphosphorylation and cognitive deficits in AD (Banzhaf-Strathmann et al., 2014), may be involved in the regulation of inflammatory factors and oxidative stress by SphK1 (Jin et al., 2018). It has been found to be associated with other neurodegenerative diseases as well (Lardenoije et al., 2015; Salta and De Strooper, 2017b). TGF-β induced miR-100 and miR-125b (Ottaviani et al., 2019). MiR-100 and miR-125b coordinately suppress Wnt/b-catenin negative regulators, thereby increasing Wnt signaling (Lu et al., 2017). A pathogenic-positive feedback loop has been identified in which Aβ induced Dickkopf-1 expression activating non-canonical Wnt signaling, promoting synapse loss and enhancing Aβ production (Elliott et al., 2018). MiR-129-2 was reported to be down-regulated in spinal cord (Strickland et al., 2011). MiR-132 is involved in synaptic plasticity (Bicker et al., 2014) and may be associated with TDP-43 binding in amyotrophic lateral sclerosis (Freischmidt et al., 2013). Prion-infected hippocampal neurons elicited altered expression of miR-132 (Majer et al., 2012) and have been discussed to play an important role in inflammation control (Essandoh et al., 2016). MiR profiling in the human brain has revealed miR-132 as one of the most severely down-regulated miRs at the intermediate and late Braak stages of AD, as well as in other neurodegenerative disorders (Salta and De Strooper, 2017a). MiR-132 has been implicated in synaptic plasticity together with miR-134 and miR-138 (Bicker et al., 2014). Duplication of the miR-138-2 locus was observed exclusively in early onset AD cases and miR-138 overexpression in vitro induced Aβ production and tau phosphorylation (Boscher et al., 2019). Interestingly, levels of miR-132 and miR-138-2 were significantly decreased in aged Tg4-42 mice indicating that dendritic mRNA transport and local translation in the postsynaptic compartment play an important role in synaptic plasticity, learning and memory (Bicker et al., 2014) in this model system for AD. In vitro Aβ treatment increased the expression of miR-139 targets (Noh et al., 2014), and has been found to be associated with other neurodegenerative diseases (Lardenoije et al., 2015; Salta and De Strooper, 2017b). MiR-181c correlated with genome-wide DNA methylation changes of ncRNAs in patients with AD (Villela et al., 2016), and is involved in epigenetics of aging and neurodegeneration (Lardenoije et al., 2015). Overexpression of miR-185 inhibits autophagy and apoptosis of dopaminergic neurons by regulating the AMPK/mTOR signaling pathway in Parkinson’s disease (Bicker et al., 2014). The 22q11.2 deletion is a known genetic risk factor for schizophrenia and mouse models of 22q11.2DS have demonstrated down-regulation of miR-185 in key brain areas of affected individuals. This reduction was associated with dendritic and spine development deficits in hippocampal neurons (Freischmidt et al., 2013). Association studies in the 3′UTR of BACE1 and the miR-29 gene cluster did not identify an association with AD. A weak statistical interaction was observed between rs535860 (BACE1 3′UTR) and rs34772568 (near miR-29a). The authors concluded a major contribution of this miR (Bettens et al., 2009). MiR-30a has been found to be associated with Parkinson disease (Margis et al., 2011) as well as Huntington disease (Lardenoije et al., 2015; Salta and De Strooper, 2017b). MiR-338-3p depletion has been shown to be important for auditory thalamo-cortical signaling in 22q11DS mice, and may trigger the pathogenic mechanism of 22q11DS-related psychosis (Chun et al., 2017). MiR-345-5p may act as blood biomarker in multiple sclerosis (Freiesleben et al., 2016), and miR-345-3p attenuated apoptosis and inflammation caused by oxidized low-density lipoprotein by targeting TRAF6 via TAK1/p38/NF-kB signaling (Wei et al., 2020). An in vitro study indicated that miR-34a may inhibit Aβ clearance by targeting endophilin-3 including uptake and autophagy-mediated degradation (Sun et al., 2018). The rs1050283 SNP likely acts as a risk factor for sporadic AD. It is associated with a decreased expression of oxidized LDL receptor 1 mRNA in the absence of miR-369-3p de-regulation and may affect the binding of miR-369-3p to its 3′UTR consensus sequence (Bettens et al., 2009). MiR-381 showed a protective effect against inflammatory damage (Li et al., 2020). MiR-409 was reported in IL-17-induced inflammatory cytokine production in astrocytes by targeting the SOCS3/STAT3 signaling pathway in EAE mice (Liu et al., 2019). MiR-541 acts on neurite outgrowth and differentiation via nerve growth factor and synapsin I in neuronal precursor cells (Chun et al., 2017). MiR-674 demonstrated an association with Parkinson disease and Huntington (Lardenoije et al., 2015; Salta and De Strooper, 2017b). CSF from individuals with AD contained increased amounts of miR-let7b, and intrathecal injection of miR-let7b in wild-type mice induced neurodegeneration (Lehmann et al., 2012). Elevated levels of miR-let7b and miR-let7e were found in CSF of patients with AD and major depressive symptoms, but not in patients with fronto-temporal disorder (Derkow et al., 2018). MiR-let7d is a key regulator of bi-directionally transcribed genes mediating epigenetic silencing and nucleolar organization (Singh et al., 2018). For miRs miR-129-1, miR-154, miR-15b, miR-219-2, miR-298, miR-323, miR-411, miR-500, miR-7-2, miR-92b, miR-let7i this study is the first to describe deregulation in an AD mouse model. Interestingly, GO-Annotation analysis (“Cellular Components”) revealed that only miRs, which were exclusively deregulated in the Tg4-42 model showed an enrichment of targets in connection with the synapse. Such and similar annotations were completely absent among the targets of miRs that were deregulated in both aged mutant and WT mice. With respect to the “Molecular Function” and “Biological Process” annotation, this difference is even more pronounced.

As the Tg4-42 model shows reduced neurogenesis, synaptic hyperexcitability and develops neuron loss as well as behavioral deficits without plaque formation, the newly found deregulated miRs in this model could be involved in plaque-independent pathological pathways. Taken together these observations strongly support our conclusion that the identified miRs play a role in the etiology of AD and thus deserve further investigation as putative biomarkers or therapeutics.

MiRs Identified in the Hippocampus of 8 Month Old Wildtype Mice

Eight miRs were exclusively altered in the hippocampus between 3 and 8 month-old in WT mice. TGF-β induced an lncRNA with its encoded miRs, miR-100 and miR-125b (Ottaviani et al., 2019). MiR-100 and miR-125b coordinately suppressed Wnt/β-catenin negative regulators thereby increased Wnt signaling (Lu et al., 2017). MiR-153 was over-expressed in CSF exosomes from patients with Parkinson disease (Serpente et al., 2011). There is evidence that miR-191 and miR-222 are co-regulated and are important for neurodevelopment (Li et al., 2020). MiR-1298, miR-34b, miR-423, miR-666 and miR-667 have not been previously reported to be association to AD, neurodegenerative disorders or brain function.

MiRs Identified in the Hippocampus of 8 Month Old Tg4-42 and Wildtype Mice

25 miRs were differentially expressed between 3 and 8 month-old Tg4-42 as well as WT mice. All but three of them were significantly decreased at 8 months of age. MiR-127 has been reported to modulate macrophage polarization and therefore may have a crucial role in inflammation (Essandoh et al., 2016). MiR-128-1 up-regulation correlated with Aβ degradation in monocytes from patients with sporadic AD (Tiribuzi et al., 2014). MiR-130a was involved in inflammatory processes by targeting the transforming growth factor-beta1 and interleukin 18 genes (Zhao et al., 2014). MiR-132 expression levels were found to be associated with hippocampal sclerosis in a subgroup of AD patients (Tasaki et al., 2018). MiR-138-1 was transcriptionally up-regulated during myelination and downregulated upon nerve injury (Lin et al., 2018). miR-150-5p may act as a circulating biomarker for patients with the autoimmune neuromuscular disorder myasthenia gravis (Punga et al., 2015). A genetic variant located near the miR-204 gene was significantly associated with schizophrenia resulting in reduced expression of miR-204 in neuronal-like SH-SY5Y cells (Cammaerts et al., 2015). MiR-212 was down-regulated in white matter of patients with AD (Wang W.X. et al., 2011). MiR-222 was down-regulated in the AD mouse model APPswe/PSΔE9 (Wang et al., 2015). Lipopolysaccharide stimulation in mice led to increased expression of miR-221 and miR-222, thereby causing transcriptional silencing of a subset of inflammatory genes, which depend on chromatin remodeling. In patients with sepsis, increased expression of miR-221 and miR-222 correlated with immunoparalysis and increased organ damage (Seeley et al., 2018). Preliminary results indicated that aberrant levels of circulating miR-23a are recovered in fingolimod-treated multiple sclerosis patients representing a potential biomarker (Fenoglio et al., 2016). MiR-300 was involved in the inflammatory response in endothelial cells and enhanced autophagy by activation of the AMPK/mTOR signaling pathway (Li et al., 2018). MiR-323 suppressed neuron death via the transforming growth factor-β1/SMAD3 signaling pathway (Che et al., 2019). The expression of miR-30a was associated as a prediction serum marker in epilepsy (Lin et al., 2018). MiR-34c has been shown to have a physiological role in regulating the central stress response (Cammaerts et al., 2015). MiR-329 was upregulated in a mouse model for Rett syndrome, which is a complex neurological disorder that has been associated with mutations in the gene coding for Mecp2 (Urdinguio et al., 2010). MiR-382 inhibited cell proliferation and invasion of retinoblastoma by targeting BDNF-mediated PI3K/AKT signaling pathway (Song et al., 2017). MiR-877-3P regulated vascular endothelial cell autophagy and apoptosis under the high-glucose condition (Zhao et al., 2020). MiR-99a was found overexpressed in the brain of patients with Down syndrome (Bras et al., 2018). MiR-99b may have a role in spinal cord injury via the regulation of mTOR (Cao et al., 2017). Again, several miRs, namely, miR-128-2, miR-140, miR-23b, miR-30d, miR-3102, miR-328 and miR-434 could be linked to an AD mouse model for the first time in this study.

Annotation Analysis of miR Targets

The analyses of the GO annotation of predicted miR targets in Tg4-42 and WT mice revealed diverse cellular component, molecular functions and biological processes similar to our previous study of the mRNome of the whole brain of Tg4-42 and 5XFAD mice (Bouter et al., 2014). The GO annotations in Tg4-42 hippocampus demonstrated that the most enriched pathways belong to synaptic signaling and transmission involved in memory processes, which was not found in WT mice. Hence, these pathways appear specific for the AD-typical mental decline and neurodegenerative events.

Conclusion

We were able to validate the Tg4-42 as a valuable model for sporadic AD. We could confirm previously reported AD-associations of several miRs. Importantly, the untargeted small RNASeq approach also allowed us to link several additional miRs to a mouse model for AD. The identified miRs have a role in the age-dependent deficits in learning and memory as well as neuron loss in the hippocampus in Tg4-42 mice. The annotation of miR target genes supported these strong reductions in synaptic processes involved in learning and memory.

Statements

Data availability statement

The datasets for this study have been uploaded to the European Nucleotide Archive (https://www.ebi.ac.uk/ena) with the accession identification number of the project PRJEB39314.

Ethics statement

The animal study was reviewed and approved by the Niedersächsisches Landesamt für Verbraucherschutz und Lebensmittelsicherheit, Röverskamp 5, 26203 Oldenburg, Germany and Landesamt für Gesundheit und Soziales LAGe So Darwinstr. 15, 10589 Berlin, Germany.

Author contributions

YB contributed to the experimental design and analyzed the data. TK and FR analyzed the data. AK and LJ contributed to the experimental design and were responsible for NGS-data generation and primary data analysis. TB wrote the manuscript, analyzed the data, and supervised the experimental design and the entire project. All authors read, reviewed, and approved the final manuscript.

Acknowledgments

We thank Robert Weissman and Stefan Weiss for bioinformatics support in primary data analysis and Corina Jensen and Christian Sperling for excellent technical assistance.

Conflict of interest

The University Medicine Göttingen holds a patent on the Tg4-42 mouse model for Alzheimer’s disease.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnins.2020.580524/full#supplementary-material

FIGURE S1

Heatmap of most variable genes for quality control. Individual sample after collapsing replicates with DESeq2. S1–20 represent individual sample labels.

TABLE S1

Analysis of hippocampal miR between young and aged Tg4-42 and wildtype mice. Plus log 2-fold change means higher levels at 8 months of age. Minus log 2-fold change means lower levels at 8 months of age. P-values are only shown if significant (<0.05). Abbreviations: 3M, 3 month old; 8M, 8 month old.

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Summary

Keywords

miRNA transcriptome, miRNA-Seq, NGS, transgenic mouse model, Tg4-42, Alzheimer

Citation

Bouter Y, Kacprowski T, Rößler F, Jensen LR, Kuss AW and Bayer TA (2020) miRNA Alterations Elicit Pathways Involved in Memory Decline and Synaptic Function in the Hippocampus of Aged Tg4-42 Mice. Front. Neurosci. 14:580524. doi: 10.3389/fnins.2020.580524

Received

06 July 2020

Accepted

18 August 2020

Published

10 September 2020

Volume

14 - 2020

Edited by

Jie Tu, Chinese Academy of Sciences (CAS), China

Reviewed by

Wang-Xia Wang, University of Kentucky, United States; Nataliya G. Kolosova, Russian Academy of Sciences, Russia

Updates

Copyright

*Correspondence: Andreas W. Kuss, Thomas A. Bayer,

This article was submitted to Neurodegeneration, a section of the journal Frontiers in Neuroscience

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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