Transcriptome sequencing of ceRNA network constructing in status epilepticus mice treated by low-frequency repetitive transcranial magnetic stimulation

doi:10.21203/rs.3.rs-2340029/v1

Download PDF

Research Article

Transcriptome sequencing of ceRNA network constructing in status epilepticus mice treated by low-frequency repetitive transcranial magnetic stimulation

https://doi.org/10.21203/rs.3.rs-2340029/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 03 May, 2023

Read the published version in Journal of Molecular Neuroscience →

You are reading this latest preprint version

It is shown that much advances were made in the treatment of repetitive transcranial magnetic stimulation (rTMS) for neurological and psychiatric diseases in recent years studies. This study aimed to reveal how rTMS exerts it therapeutic effects by regulating competitive endogenous RNAs (ceRNAs) of lncRNA-miRNA-mRNA. The distinction in lncRNA, miRNA and mRNA expression between low-frequency rTMS-treated male SE mice and male SE mice treated with sham rTMS were analyzed by high-throughput sequencing. The Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out. Gene-Gene Cross Linkage Network was established, and pivotal genes were screened out. qRT-PCR was used to verify gene-gene interactions. In short, there were 1615 lncRNAs, 510 mRNAs and 17 miRNAs differentially expressed between the low-frequency rTMS group and the sham rTMS group. The expression difference of these lncRNAs, mRNAs, and miRNAs by microarray detection were consistent with the resutls by qPCR. GO functional enrichment showed that immune-associated molecular mechanisms and biological processes, GABA-A receptor activity play a role in SE mice treated with low-frequency rTMS. As revealed by KEGG pathway enrichment analysis, differentially expressed genes are correlated to T cell receptor signaling pathway, primary immune deficiency and Th17 cell differentiation signaling pathway. Gene -gene cross linkage network was established on the basis of Pearson's correlation coefficient and miRNA. In conclusion, LF-rTMS alleviates SE through regulating the GABA-A receptor activity transmission, improving immune functions and biological processes, implicating that LF-rTMS may be a viable therapeutic option for epilepsy.

Transcriptome sequencing

low-frequency rTMS

Long non-coding RNA

MiRNA

Interaction network

Epilepsy, not rare as a neurological disease, has a negative impact on sufferers ' lives.(Devinsky O et al., 2018). Epilepsy, with a character of unexplained spontaneous episodes on a regular basis, is considered to be an important cause of death and disability. One in 100 people of the world is entangled with the “devil” of epilepsy. (Sander JW, 2003). Much progress has been made in the treatment of epilepsy over the past 20 years, but a significant challenge still exists. The current treatment of epilepsy focuses on preventing or inhibiting the symptoms of epilepsy, far from delaying the progression of the disease. Therefore, exploring new therapies is of great significance for the recovery of epileptic patients.

Since the establishment of non-invasive transcranial magnetic stimulation(TMS) in the 1980s(Barker AT et al., 1986;Barker AT et al., 1985).multiple repetitive TMS(rTMS) protocols are applicable for stimulating the human brain, including patterned and straightforward mode (e.g., theta burst stimulation) that make it no longer difficult to examine or change brain plasticity in disease-free volunteers and patients with neurological disorders. rTMS is one type of TMS that can be seen everywhere in the treatment of various neuropsychiatric diseases,such as Alzheimer's disease, epilepsy, depression and anxiety disorder, sleep disorder, and neurodevelopmental disorders(Bystritsky A et al., 2008;Inghilleri M et al., 2006;Lomarev MP et al., 2006;Masuda F, 2019;Peng Z et al., 2018;Peng ZW et al., 2018).

rTMS induces a certain intensity of induced current in the cerebral cortex by generating a pulsed magnetic field through the time-varying current, which crosses the scalp and skull. Thus, it has certain rehabilitative effect on peripheral and central nervous system injury diseases(Borckardt JJ et al., 2009;Málly J and Stone TW, 2007). rTMS can produce an ever-repeating magnetic signal stimulation of the cortex, increasing the sum of the durations of the magnetic stimulation. rTMS can lead to a more pronounced change in neuronal activity and thus act to excite or inhibit the cortex. rTMS can stimulate the cortex at a time when the neurons should not be stimulated, and therefore can have a functional effect on the cortex(Corti M et al., 2012). In addition, rTMS can stimulate neurons when they should not be stimulated, thus not only can it have a functional effect on local and remote cortices, but also this biological effect can persist for some time after the stimulation has ended(Pell GS et al., 2011). Although rTMS is wide in clinical application, the molecular genetic mechanisms of rTMS-evoked plasticity in the brain remain unclear.

The basic fundamental of TMS is to provoke magnetic fields above the brain to activate cortical neurons indirectly through synaptic inputs(Driver J et al., 2009;Ruff CC et al., 2006). Recently reported that rTMS can activate cortical areas far from the stimulation center and generate long-term electrophysiological changes(Huang YZ et al., 2005;Speer AM et al., 2000). Thus TMS can transmit EEG signals to the distal end of the stimulus center via synaptic connections(Post A and Keck ME, 2001). There is evidence that high-frequency (HF) rTMS (>5 Hz) evokes an inspiring effect, while low-frequency(LF) rTMS (<1 Hz) leads to a depressing effect in the brain(Fitzgerald PB et al., 2006). LTD is considered to be one of the key mechanisms for LF-rTMS to alter cortico-motor excitability, and the molecular mechanisms underlying LTD may involve NMDA receptors on the postsynaptic membrane(Chervyakov AV et al., 2015). Moreover, LF-rTMS might play an anti-epileptic role by affecting the expression of GAD65 and NMDAR1(Zhang J et al., 2008).Other studies suggest that LF-rTMS can lower the depolarization response of mouse neurons to achieve the purpose of anticonvulsant (Moradi Chameh H et al., 2015;Shojaei A et al., 2014). Furthermore, LF-rTMS could also release some anticonvulsant substances to cerebrospinal fluid to produce antiepileptic effect (Anschel DJ et al., 2003). rTMS also can promote to release neurotransmitters of the animals (Keck ME et al., 2000) and the depressed patients’brain (Baeken C et al., 2011) in specific regions, such as 5-HT, glutamate, and gamma-aminobutyric acid (GABA). Since the research of transcranial magnetic stimulation for epilepsy is mostly clinical trial and meta-analysis, its exact therapeuticmechanisms are still undefined.In the present study, we established a gene-gene cross linkage network based on LF-rTMS related competitive endogenous RNAs (ceRNAs) , indicating a new direction for exploring the intrinsic mechanisms of rTMS with different parameters.

2.1. Mouse models of status epilepticus

Adult male C57BL/6 mice (22g-28g) purchased from Changzhou Cavens Laboratory Animal Co., Ltd. were raised at 25°C, 60% humidity, 12h:12h light-dark cycle. Sufficient water and food was provided. Establishment of status epilepticus (SE) model was performed by intraperitoneal injection of pilocarpine. Specifically, mice were weighed and given intraperitoneal injection of pilocarpine ( 300mg/kg, Sigma, St.Louis, MO,USA), 30min before intraperitoneal injection of methylscopolamine ( 2ml / kg, Sigma, St.Louis, MO,USA ) to block the peripheral cholinergic side effects of pilocarpine. The seizures of mice were observed, and the severity of seizures was ranked by the modified Racine score(Racine RJ, 1972). The SE mice were considered for this study. Intraperitoneally injection of 4mg/kg diazepam (Sigma, St. Louis, MO, USA) to quell seizures was performed after SE onset for 2 h. At 6 h after magnetic stimulation of different time points, the mice were killed and the cortex were collected. Animal experiments complied with the Institutional Animal Care and Use Committee (IACUC) of Nanjing Medical University. Also they were authorized by the ethics committee of the Affiliated Changzhou No.2 People’s Hospital (No. 2014Keyan002-01)

2.2. Procedure for microelectrod implantation, recording and analysis

of video-EEG recording

After rTMS, Mice were implanted with stainless steel microelectrodes. In brief, mice in each group were anesthetized by inhalation of 2% isoflurane, and then fixed on the brain stereotaxic apparatus. Electrodes were implanted in bilateral somatosensory cortex (Bregma, − 1.0mm; lateral, 2.0 mm; depth, 1.8 mm) and reference electrodes were implanted in shallow frontal cortex (Bregma, + 2.6 mm; lateral, 1.8 mm; depth, 0.5 mm). EEG was recorded 5 days after surgery. Acquisition system included 8 single-channel biological amplifiers (ADInstruments Ltd., Sydney, Australia) and analog–digital converter (PowerLab ML870, AD Instruments), acquisition conditions: sampling rate 200 Hz, time constant 0.1 sec, low-pass filter 60 by using the software Labchart V6.0 or higher (ADInstruments). Simultaneous digital vEEG recording was conducted using high-resolution infrared cameras. Abnormal EEG (most likely paroxysmal) was analyzed to monitor epileptic seizures in mice. The epileptiform spikes were distincted from artifacts according to amplitude and duration of spikes and inter spike interval. All epileptic spikes above baseline form a spike wave group. The times of spontaneous recurrent seizure (SRS) incidence and the spike rate were quantified using NeuroScore 3.2.0 software.

2.3. Experimental procedures

Mice were distributed into two groups: (a) SE group, (b) rTMS treatment SE group. Wildtype C57BL/6 mice were placed into a restraint device for rTMS(Zhang C et al., 2019). On the animal head center, a 70 mm figure-of-eight coil (YIRUIDE, Wuhan, China, 3.0 Tesla) was placed. LF-rTMS was delivered with the following parameters: 0.5Hz, 600 pulses, 20 minutes, 20% intensity (triggering no obvious muscle twitches of limbs), five days in a row (once each morning and afternoon). For the sake of adapting to the restraint device, naive mice were put into it thrice (maintaining for one to two minutes every time) a day before the whole rTMS. Six hours after the whole rTMS(Day Five), cervical dislocation was adopt to sacrifice the mice .Then their cerebral cortex were taken out and kept at -80°C before needed.

2.4. RNA Extraction and Microarray Experiments

The experiments carried out were in the lab of OeBiotech Corporation (Shanghai, China). Agilent Mouse lncRNA Microarray V3 (4*180K, Design ID: 084388) and miRNA Microarray Release 21.0 (8*60K, Design ID: 070155) were used in this experiment(Tang L et al., 2019). In short, Trizol method was employed to extract RNA.Then it was quantified through NanoDrop ND-2000 (Thermo Scientific). Agilent Bio Analyzer 2100 (Agilent Technologies) was used to evaluate RNA integrity. The sample labeling, microarray hybridization, and washing were administered under manufacturer ' s standard protocol. In summary, the RNA was amplified according to requirements of the manufacturer, then labeled with Cyanine-3-CTP, purified and hybridized to the chip. Furthermore, the arrays were finally scanned by the Agilent Scanner G2505C (Agilent Technologies) after washing.

2.5. Construction of lncRNA-miRNA-mRNA

The ceRNA network was constructed by the differentially expressed lncRNAs (DELs), mRNAs (DEGs), and miRNAs(DEMs). Firstly, the forecasted targets of DEMs were from miRanda as well as Pearson correlation coefficient(PCC) .miRanda(http://www.microrna.org/microrna/getDownloads.do) was employed to forecast the miRNA responsive elements (MRE) of target genes. Moreover, binding sites of assayed miRNAs on basis of the sequences of lncRNAs and mRNAs were also from it(Enright AJ et al., 2003). Before the determination of overlap RNAs,these forecasted mRNAs and lncRNAs were in comparison with those assayed from microarray. The pseudo-positive of coulped miRNA-mRNA and miRNA-lncRNA was reduced after filtrating the highlycoulped miRNA-mRNA and miRNA-lncRNA through the PCC, and calculating the P-value of PCC of every single couple through Fisher’sasymptotic distribution(Guttman M et al., 2009). The interactions of negative PCC were supposed to be selected only when its P value < 0.01. Then shared couples from the forecasted coulped miRNA-mRNA as well as miRNA-lncRNA through miRanda and PCC were included for further analyses. Finally, a ceRNA network correlated with the SE mice treated with LF- rTMS was plotted by Cytoscape 3.7.2 (https://cytoscape.org/) in reference to forecasted shared couples of miRNA-mRNA as well as miRNA-lncRNA.

2.6. Quantitative reverse transcription-polymerase chain reaction

analysis

To confirm results of microarray, real-time reverse transcription polymerase chain reaction (RT-PCR) was adopted to detect the expression levels of cirRNAs, lncRNAs and miRNAs and mRNAs in the cerebral cortex of C57BL/6 mice. According to the corresponding sequences in GenBank, primers were synthesized by Guangzhou Aiji Biotechnology Co. Ltd. RNA was extracted strictly according to the trizol method, and the obtained RNA A260 / A280 > 1.8 met the purity requirement. The total RNA extracted was subjected to reverse transcription and PCR amplification according to the instructions of RT-PCR reaction kit (TaKaRa). PCR reaction conditions: 95°C 30 s, 95°C 5 s, 60°C 20 s, a total of 40 cycles.

2.7. Data Analysis

The array images were examined by feature extraction software (version 10.7.1.1, Agilent Technologies) to elicit the original data.Next, the originaldata’s fundamental analysis was accomplished by Genespring (version 13.1, Agilent Technologies). Primarily, the original data was standardized processing by the quantile algorithm. The lncRNA Microarray probes that with fewest one conditions out of 2 conditions tagged in “P” were selected for further data analysis. The miRNA Microarray probes that at least 100.0 percent of samples in either condition have tagged in "Detected" were selected for next data analysis. Differential expression of lncRNAs (DELs), mRNAs (DEGs), and miRNAs(DEMs) were obtained by calculating fold change and p value obtained by t test. Ones with fold change > = 2.0 and P-value < 0.05 were considered as differentially expressed genes. The same genes were selected from the differentially expressed target genes predicted by the three databases (TargetScan, microRNAorg, PITA). Afterward, GO analysis and KEGG analysis was utilized to expound the roles of these differentially expressed mRNAs, and the target mRNAs of abnormal miRNAs. Finally, Hierarchical Clustering and volcano plots were complished to describe the distinct mRNAs, lncRNAs, or miRNAs expression patterns schema among samples.

3.1 LF-rTMS significantly decreases epiletiform discharges and

spontaneious seizures during SE

To determine whether LF-rTMS exerts a significant anti-epileptogenic effect in SE mice, we applied video-EEG to monitor epileptiform discharges and seizure behaviors after magnetic stimulation. As shown in Fig. 1, unlike the sham rTMS group, the amount of epileptic spikes in mice treated with LF-rTMS was decreased significantly (Fig. 1A-1B). Correspondingly, the number of spontaneous recurrent seizures were also decreased in SE mice treated with LF-rTMS (Fig. 1C)

3.2 Differentially expressed RNAs in SE mice treated with low-frequency rTMS

The standardized original data from array graph were utilized to assess the expression levels of lncRNAs, mRNAs and miRNA in the sham rTMS-treated SE mice and the LF- rTMS-treated SE mice. A total of 1615 significantly dysregulated (1029 up- and 586 down-regulated) lncRNAs were determined (Supplementary Table S1). A sum of 510 genes were recognized to be distinctly expressed in SE mice treated with LF-rTMS when compared to the sham rTMS-treated SE mice. These included 383 upregulated genes and 127 downregulated genes (Supplementary Table S2). There are 209 upregulated and 68 down-regulated circRNAs (Supplementary Table S3). A total of 17 differentially expressed miRNAs were initially screened, including 12 upregulated and 5 downregulated miRNAs (Supplementary Table S4). The volcano and heat maps are shown in Figs. 1 and 2. The top upregulated and downregulated 10 significantly DELs, DEMs and DEGs are listed in Table 1. The distinguishable lncRNAs, mRNAs, miRNAs expression patterns in the two groups were displayed by Hierarchical clustering (Fig. 2). The differentiable expression patterns of lncRNA, mRNA, and miRNA in the two groups were rendered by accomplishing hierarchical clustering.

Table 1

Differentially expressed genes (DEGs) in SE mice treated with low-frequency rTMS as compared with SE mice treated with sham rTMS.
Regulate	lncRNA			mRNA			miRNA
Regulate	TargetID	log₂FC	P.Value	GeneSymbol	log₂FC	P.Value	miRNA name	log₂FC	P.Value
Up	NONMMUT135597.1	5.36851	0.00734	Lsmem1	4.98728	0.00487	mmu-miR-6984-3p	4.85315	0.01743
	XR_870399	4.87991	0.00080	Zfp235	4.21518	0.00713	mmu-miR-28a-5p	2.91005	0.00073
	NONMMUT113376.1	4.66178	0.00134	Isl1	4.21013	0.00233	mmu-miR-376a-5p	2.86186	0.00133
	NONMMUT136502.1	4.63616	0.00256	Asb3	3.94305	0.00451	mmu-miR-138-2-3p	2.82168	0.00131
	NONMMUT017997.2	4.57706	0.00099	Slc22a26	3.93373	0.00881	mmu-miR-7216-5p	2.79403	0.00073
	NONMMUT130005.1	4.45396	0.03657	Lpxn	3.79102	0.02338	mmu-miR-342-5p	2.76946	0.00041
	NONMMUT120599.1	4.44599	0.00958	Tcaf3	3.77073	0.00261	mmu-miR-186-5p	2.72357	0.00015
	NONMMUT083899.1	4.25848	0.00869	Armcx6	3.70858	0.00842	mmu-miR-379-3p	2.64449	0.00072
	NONMMUT115312.1	4.23432	0.00195	Rbm47	3.48942	0.00148	mmu-miR-3102-3p	2.59325	0.00378
	NONMMUT017995.2	4.11820	0.00383	Irf6	3.46616	0.03459	mmu-miR-29b-1-5p	2.53349	0.00146
Down	NONMMUT124392.1	-3.30967	0.02232	Gm904	-3.32593	0.01590	mmu-miR-7222-3p	-5.99159	0.00045
	NONMMUT085198.1	-3.28886	0.01050	Timm10b	-2.31445	0.02437	mmu-miR-6973b-5p	-2.60895	0.00006
	NONMMUT131055.1	-3.15322	0.01775	CA465148	-2.26467	0.02471	mmu-miR-1934-3p	-2.49315	0.00168
	NONMMUT120897.1	-3.11824	0.03348	Nuf2	-2.15046	0.04716	mmu-miR-19a-3p	-2.38574	0.00030
	NR_040578	-3.06152	0.01840	Olfr180	-1.89311	0.02974	mmu-miR-744-5p	-2.14357	0.00529
	NR_015609	-3.00397	0.00002	Novel	-1.85536	0.04408	NA	NA	NA
	XR_863618	-2.99008	0.04145	Cbln3	-1.84957	0.04584	NA	NA	NA
	TC1616118	-2.93429	0.01006	Podxl	-1.82505	0.03964	NA	NA	NA
	NONMMUT016592.2	-2.92660	0.02872	Kdm2a	-1.80582	0.03478	NA	NA	NA
	NONMMUT116230.1	-2.83651	0.04839	Olfr124	-1.74116	0.03158	NA	NA	NA

3.3 The GO and the KEGG pathway enrichment analysis

The GO and the KEGG pathway enrichment analyses were carried out on DEGs in the lncRNA-related ceRNA network. Using the Cluster Profile pachage in R software, GO analysis displayed DEGs were related to “GABA-A receptor activity” (Fig. 3). KEGG pathway analysis utilizingthe Cluster Profiler package indicated DEGs had an obvious relevance with various immune-related pathways, including T cell receptor signaling pathway, primary immunodeficiency, Th17 cell differentiation as well (Fig. 4).

3.4 The ceRNA network in SE mice treated with LF- rTMS

CeRNAs share MREs and modulate RNA transcripts by competitively interacting with general miRNA molecules (Zhang C,Lu R,Wang L,Yun W and Zhou X, 2019). CeRNAs network was established on the basis of DELs, DEGs, and DEMs in the SE mice treated with LF- rTMS and the SE mice treated with sham rTMS. Modulation forecasted through miRanda and PCC were between DEMs and the targets (miRNA-mRNA or miRNA-lncRNA). Then the forecasted shared couples of DEMs and the targets were picked for constructing ceRNA modulatory network. Then combined the miRNA-mRNA interplay with lncRNA-miRNA interplay, a network of ceRNA was established by Cytoscape. Nodes in the network indicated lncRNAs,mRNAs and miRNAs.The linked lines in the network symbolized interaction of these RNAs (Keck ME,Sillaber I,Ebner K,Welt T,Toschi N,Kaehler ST,Singewald N,Philippu A,Elbel GK,Wotjak CT,Holsboer F,Landgraf R and Engelmann M, 2000) (Fig. 5). A ceRNA network map was obtained by combining the related pairs obtained above and was visualized them with Cytoscape. There were 269 nodes in this network, including 180 lncRNAs, 5 miRNAs, and 84 mRNAs (Fig. 5).

Recently, many studies have demonstrated that DELs and DEMs play anecessary role in normal physiological functions by modulating gene expression at epigenetic, transcription and post-transcription level. Further, increasing evidence suggests that DELs and DEMs are emerging in the pathogenesis, diagnosis and treatment of epilepsy. Unlike protein-coding genes, lncRNAs have significant advances as diagnostic and prognostic biomarkers.It is currently known that lncRNA is involved in nervous system development, synapse occurrence and synaptic plasticity. The disorder of lncRNA may cause neurological diseases such as epilepsy, Parkinson’s disease (PD), and Alzheimer’s disease(AD)(Oe S et al., 2019). LncRNA and miRNA probably be related to specific biological processes in epilepsy, including ion/gated channels and GABA receptors (Gross C and Tiwari D, 2018;Haenisch S et al., 2016). LncRNA might also be involved in neuronal apoptosis, neuroinflammation and cognitive impairment in the development of epilepsy(Villa C et al., 2019). Indeed, miR-211 and miR-128 are essential factors that directly induce epilepsy in mice(Fan C et al., 2016;Tan CL et al., 2013). Therefore, ceRNA is expected to become a potential target for the treatment of epilepsy.

LF- rTMS can be applied to specific brain regions to generate a certain magnetic field and penetrate the scalp and skull, by using a short but powerful magnetic field pulse repeatedly on the cerebral cortex, as a result generating a certain intensity of current in the cortex, stimulating and influencing the local and functionally relevant state of the remote cortex, leading to a regional reorganization of cortical function, thereby producing the corresponding biological effects. These effects can last for a certain period of time after the end of stimulation, making it a good tool for studying the functional reconstruction of neural networks (Borckardt JJ,Smith AR,Reeves ST,Madan A,Shelley N,Branham R,Nahas Z and George MS, 2009;Feng H et al., 2020). As recently shown, LF-rTMS can cause variety in neuronal excitability, affect expression of neurotransmitters, regulate brain plasticity, improve neurological dysfunction, and thus achieve functional recovery. LncRNAs have been demonstrated to participated in multiple biological processes, including post-transcriptional and epigenetic regulation. It was reported that lncRNA inhibited the development of epilepsy by regulating miRNA to decrease neuronal apoptosis and neuroinflammation in vitro studies(Feng H et al., 2021;Feng H,Gui Q,Zhu W,Wu G,Dong X,Shen M,Luo H,Xue S and Cheng Q, 2020;Han CL et al., 2020). However, there was still a lack of global lncRNA-associated crosstalks in the treatment of LF-rTMS for epilepsy.

It is widely believed that miRNAs not only decrease mRNA reliability by linking with MRE but also block its translation. Owing to MRE, a single miRNA can target RNAs in “one to multiple”. On the contrary a single mRNA or LncRNA is modulated by miRNAs in “one to multiple” (Jeyapalan Z et al., 2011). Hereby, this ceRNA interaction may be a universal post-transcriptional modification. A miRNA is a noncoding RNA with the 5’ end that decreases gene expression by targeting mRNA with a complementary 3’-UTR. Accumulating evidence suggests that lncRNAs act as endogenous ceRNA through competitive inhibition of miRNA, thereby regulating other transcripts. CeRNA is involved in neuronal development, synaptic transmission and ion channels related to epileptogenesis. Additionally, it can also regulate neuronal inflammation, neuron apoptosis and autophagy to delay the progression of epilepsy. The detail functions and special expression pattern of miRNAs and lncRNAs in epilepsy remained largely unclear. However, the tricky ceRNA interplay mechanisms of lncRNA–miRNA–mRNA in LF-rTMS treatment for epilepsy remained to be investigated. In this study, we identified 1029 upregulated and 586 downregulated lncRNAs, 12 upregulated and 5 downregulated miRNAs, 383 upregulated and 127 downregulated mRNAs in the LF-rTMS-treated mice as compared to control mice. Although lncRNAs are considered to attract miRNAs competitively and then affect mRNAs expression, their biological characteristics and clinical relevance are still unclear. The constructed ceRNA regulatory network included five miRNAs (mmu-miR-7222-3p, mmu-miR-744-5p, mmu-miR-1934-3p, mmu-miR-19a-3p, and mmu-miR-8973b-5p).

Critical nodes identified in some studies and highly connected with other nodes of ceRNA network would be viewed as its topological properties to evaluate genes’ essentiality(Li Y et al., 2019;Ma N et al., 2019). As recently hypothesized, ceRNA is viewed as a new post-transcriptional regulation circuit. The lncRNAs, of this ceRNA network, connect with mRNAs that share MREs(Fan CN et al., 2018). After decade, hundreds of studies have seeked after the mechanisms of ceRNA in various neurological diseases, for instance, ischemic stroke and epilepsy(Brennan GP and Henshall DC, 2020;Homanics GE et al., 1997;Jiang H et al., 2017). To examine lncRNAs markedly linked with LF-rTMS treatment of epilepsy, in this paper, the mRNA and lncRNA expression alternation in mice after LF-rTMS, combined with miRNA-target interactions to establish ceRNA network, were utilized to seek for the deep significance of these lncRNAs in the molecular mechanisms of LF-rTMS treatment.

No definite signal pathway has been confirmed to be responsible for LF-rTMS treatment for epilepsy. In the present study, the differentially expressed genes appeared to take part in signaling pathways, involving GABA-A receptor activity, Th17 cell differentiation, T cell receptor signaling pathway, primary immunodeficiency and so on. GABA is a major neurotransmitter controling neuronal excitability. The suspected contacts in GABA and epilepsy as well as in GABA and brain development have been recognized(Homanics GE,DeLorey TM,Firestone LL,Quinlan JJ,Handforth A,Harrison NL,Krasowski MD,Rick CE,Korpi ER,Mäkelä R,Brilliant MH,Hagiwara N,Ferguson C,Snyder K and Olsen RW, 1997). Differential coassembly of α1-GABARs was associated with epileptic encephalopathy (Hannan S et al., 2020). Protrudin can modulate seizure activities by regulating GABA receptor(Lu X et al., 2019).HMGB1 / CXCL12-mediated immunity and Th17 cells are highly suggested as the core of autoimmune epilepsy (Han Y et al., 2020). Compared with antibody-mediated disease, T-cell-mediated disease has higher risk of epilepsy(Geis C et al., 2019). On the basis of our bioinformatics analysis, we speculated that GABA-A receptor activity, Th17 cell differentiation, T cell receptor signaling pathway are responsible pathways involved in the the molecular mechanisms of LF-rTMS treatment for epilepsy.Based on the role of LF-rTMS in regulating synaptic-associated protein level, glutamate concentration and GABA receptor, and even affecting GSK, TGF and other signaling pathways (Cacace AT et al., 2018;Dolgova N et al., 2021;Hou Y et al., 2021;Huang Z et al., 2017;Tan T et al., 2018),we explored the potential mechanisms of miRNA changes after LF-TMS treatment for epilepsy. Among the 12 up-regulated and 5 down-regulated miRNAs of rTMS treatment group, we seeked for several miRNAs that directly or indirectly affect epilepsy. According to previous reports, MiR-28 could up-regulate AQP4 (AQP4) by inhibiting aldehyde dehydrogenase 2 (ALDH2), and promote the recovery of water homeostasis after epilepsy(Hubbard JA et al., 2016;Li SP et al., 2015;Li Y et al., 2018). AQP4 was believed as the core of maintaining water and potassium homeostasis in brain, and AQP4 knockout mice showed spontaneous recurrent seizures with increased frequency and duration(Szu JI et al., 2020). In addition, mir-138 inhibited axon regeneration(Liu CM et al., 2013). Furthermore, mir-186 controls the surface expression of GluA2 (ionic glutamate receptor A2) in hippocampal neurons(Silva MM et al., 2019). Down-regulated miR-744 could downregulate Npas4 as an intrinsic regulator of seizures and epilepsy(Choy FC et al., 2017;Shan W et al., 2018). Together, these alterations represent an intrinsic therapeutic mechanism of LF-rTMS for epilepsy.

This study also has its limitation. First, the number of samples of LF-rTMS mice need to be further increased to clarify the differences. Second, in this study, the functions of dysregulated lncRNA were predicted as miRNA “sponge”. However, its association with LF-rTMS should be further investigated. Therefore, a careful interpretation of the above conclusions and results is needed.

In conclusion, a ceRNA based on lncRNA-miRNA-mRNA network was developed in the present study, providing a new strategy for investigating molecular mechanisms of LF-rTMS treatment for epilepsy. Furthermore, lncRNA-miRNA-mRNA pairs might view as valuable detectingbiomarkers or candidate curative targets for epilepsy.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose

Authors and Affiliations

Department of Neurology, Neuroscience Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, 13 Shiliugang Rd, Guangzhou 510315, Guangdong, China.

Shaotian Zhang

Special Medical Service Center, Neuroscience Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, 13 Shiliugang Rd, Guangzhou 510315, Guangdong, China.

Huihui Zou, Xiaopei Zou, Jiaqia Ke, Bofang Zheng &Xianju Zhou

Department of Clinical medicine，The First Clinical College of Guangzhou Medical University，Guangzhou 510315，Guangdong，China

Xinrun Chen

Department of Neurology, Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, China 510260

Jianna Wei

Author Contributions

Validation, Formal analysis, Investigation, Visualization, Writing−original draft, Writing−review and editing: Shaotian Zhang & Huihui Zou; Methodology, Formal analysis, Supervision, Project administration, Writing−review and editing: Xiaopei Zou, Jiaqia Ke & BofangZheng; Methodology, Formal analysis, Supervision, Writing−review and editing: Xinrun Chen& Xianju Zhou; Conceptualization, Validation, Data curation, Writing−review and editing: Jianna Wei.

Ethics approval

All animal experiments complied with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and the rules of the Animal Ethical Committee of Nanjing Medical University.

Consent for Publication

No conflict of interest exists in the submission of this manuscript, and this manuscript is approved by all authors for publication.

Anschel DJ, Pascual-Leone A, Holmes GL (2003), Anti-kindling effect of slow repetitive transcranial magnetic stimulation in rats. Neurosci Lett 351:9–12.
Baeken C, De Raedt R, Bossuyt A, Van Hove C, Mertens J, Dobbeleir A, Blanckaert P, Goethals I (2011), The impact of HF-rTMS treatment on serotonin(2A) receptors in unipolar melancholic depression. Brain Stimul 4:104–111.
Barker AT, Freeston IL, Jabinous R, Jarratt JA (1986), Clinical evaluation of conduction time measurements in central motor pathways using magnetic stimulation of human brain. Lancet 1:1325–1326.
Barker AT, Jalinous R, Freeston IL (1985), Non-invasive magnetic stimulation of human motor cortex. Lancet 1:1106–1107.
Borckardt JJ, Smith AR, Reeves ST, Madan A, Shelley N, Branham R, Nahas Z, George MS (2009), A pilot study investigating the effects of fast left prefrontal rTMS on chronic neuropathic pain. Pain Med 10:840–849.
Brennan GP, Henshall DC (2020), MicroRNAs as regulators of brain function and targets for treatment of epilepsy. Nat Rev Neurol 16:506–519.
Bystritsky A, Kaplan JT, Feusner JD, Kerwin LE, Wadekar M, Burock M, Wu AD, Iacoboni M (2008), A preliminary study of fMRI-guided rTMS in the treatment of generalized anxiety disorder. J Clin Psychiatry 69:1092–1098.
Cacace AT, Hu J, Romero S, Xuan Y, Burkard RF, Tyler RS (2018), Glutamate is down-regulated and tinnitus loudness-levels decreased following rTMS over auditory cortex of the left hemisphere: A prospective randomized single-blinded sham-controlled cross-over study. Hear Res 358:59–73.
Chervyakov AV, Chernyavsky AY, Sinitsyn DO, Piradov MA (2015), Possible Mechanisms Underlying the Therapeutic Effects of Transcranial Magnetic Stimulation. Front Hum Neurosci 9:303.
Choy FC, Klarić TS, Koblar SA, Lewis MD (2017), miR-744 and miR-224 Downregulate Npas4 and Affect Lineage Differentiation Potential and Neurite Development During Neural Differentiation of Mouse Embryonic Stem Cells. Mol Neurobiol 54:3528–3541.
Corti M, Patten C, Triggs W (2012), Repetitive transcranial magnetic stimulation of motor cortex after stroke: a focused review. Am J Phys Med Rehabil 91:254–270.
Devinsky O, Vezzani A, O'Brien TJ, Jette N, Scheffer IE, de Curtis M, Perucca P (2018), Epilepsy. Nat Rev Dis Primers 4:18024.
Dolgova N, Wei Z, Spink B, Gui L, Hua Q, Truong D, Zhang Z, Zhang Y (2021), Low-Field Magnetic Stimulation Accelerates the Differentiation of Oligodendrocyte Precursor Cells via Non-canonical TGF-β Signaling Pathways. Mol Neurobiol 58:855–866.
Driver J, Blankenburg F, Bestmann S, Vanduffel W, Ruff CC (2009), Concurrent brain-stimulation and neuroimaging for studies of cognition. Trends Cogn Sci 13:319–327.
Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS (2003), MicroRNA targets in Drosophila. Genome Biol 5:R1.
Fan C, Wu Q, Ye X, Luo H, Yan D, Xiong Y, Zhu H, Diao Y, et al. (2016), Role of miR-211 in Neuronal Differentiation and Viability: Implications to Pathogenesis of Alzheimer's Disease. Front Aging Neurosci 8:166.
Fan CN, Ma L, Liu N (2018), Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer. J Transl Med 16:264.
Feng H, Gui Q, Wu G, Zhu W, Dong X, Shen M, Fu X, Shi G, et al. (2021), Long noncoding RNA Nespas inhibits apoptosis of epileptiform hippocampal neurons by inhibiting the PI3K/Akt/mTOR pathway. Exp Cell Res 398:112384.
Feng H, Gui Q, Zhu W, Wu G, Dong X, Shen M, Luo H, Xue S, et al. (2020), Long-noncoding RNA Peg13 alleviates epilepsy progression in mice via the miR-490-3p/Psmd11 axis to inactivate the Wnt/β-catenin pathway. Am J Transl Res 12:7968–7981.
Fitzgerald PB, Fountain S, Daskalakis ZJ (2006), A comprehensive review of the effects of rTMS on motor cortical excitability and inhibition. Clin Neurophysiol 117:2584–2596.
Geis C, Planagumà J, Carreño M, Graus F, Dalmau J (2019), Autoimmune seizures and epilepsy. J Clin Invest 129:926–940.
Gross C, Tiwari D (2018), Regulation of Ion Channels by MicroRNAs and the Implication for Epilepsy. Curr Neurol Neurosci Rep 18:60.
Guttman M, Amit I, Garber M, French C, Lin MF, Feldser D, Huarte M, Zuk O, et al. (2009), Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature 458:223–227.
Haenisch S, von Rüden EL, Wahmkow H, Rettenbeck ML, Michler C, Russmann V, Bruckmueller H, Waetzig V, et al. (2016), miRNA-187-3p-Mediated Regulation of the KCNK10/TREK-2 Potassium Channel in a Rat Epilepsy Model. ACS Chem Neurosci 7:1585–1594.
Han CL, Liu YP, Guo CJ, Du TT, Jiang Y, Wang KL, Shao XQ, Meng FG, et al. (2020), The lncRNA H19 binding to let-7b promotes hippocampal glial cell activation and epileptic seizures by targeting Stat3 in a rat model of temporal lobe epilepsy. Cell Prolif 53:e12856.
Han Y, Yang L, Liu X, Feng Y, Pang Z, Lin Y (2020), HMGB1/CXCL12-Mediated Immunity and Th17 Cells Might Underlie Highly Suspected Autoimmune Epilepsy in Elderly Individuals. Neuropsychiatr Dis Treat 16:1285–1293.
Hannan S, Affandi AHB, Minere M, Jones C, Goh P, Warnes G, Popp B, Trollmann R, et al. (2020), Differential Coassembly of α1-GABA(A)Rs Associated with Epileptic Encephalopathy. J Neurosci 40:5518–5530.
Homanics GE, DeLorey TM, Firestone LL, Quinlan JJ, Handforth A, Harrison NL, Krasowski MD, Rick CE, et al. (1997), Mice devoid of gamma-aminobutyrate type A receptor beta3 subunit have epilepsy, cleft palate, and hypersensitive behavior. Proc Natl Acad Sci U S A 94:4143–4148.
Hou Y, Zhao J, Yang D, Xuan R, Xie R, Wang M, Mo H, Liang L, et al. (2021), LF-rTMS ameliorates social dysfunction of FMR1(-/-) mice via modulating Akt/GSK-3β signaling. Biochem Biophys Res Commun 550:22–29.
Huang YZ, Edwards MJ, Rounis E, Bhatia KP, Rothwell JC (2005), Theta burst stimulation of the human motor cortex. Neuron 45:201–206.
Huang Z, Tan T, Du Y, Chen L, Fu M, Yu Y, Zhang L, Song W, et al. (2017), Low-Frequency Repetitive Transcranial Magnetic Stimulation Ameliorates Cognitive Function and Synaptic Plasticity in APP23/PS45 Mouse Model of Alzheimer's Disease. Front Aging Neurosci 9:292.
Hubbard JA, Szu JI, Yonan JM, Binder DK (2016), Regulation of astrocyte glutamate transporter-1 (GLT1) and aquaporin-4 (AQP4) expression in a model of epilepsy. Exp Neurol 283:85–96.
Inghilleri M, Conte A, Frasca V, Scaldaferri N, Gilio F, Santini M, Fabbrini G, Prencipe M, et al. (2006), Altered response to rTMS in patients with Alzheimer's disease. Clin Neurophysiol 117:103–109.
Jeyapalan Z, Deng Z, Shatseva T, Fang L, He C, Yang BB (2011), Expression of CD44 3'-untranslated region regulates endogenous microRNA functions in tumorigenesis and angiogenesis. Nucleic Acids Res 39:3026–3041.
Jiang H, Ma R, Zou S, Wang Y, Li Z, Li W (2017), Reconstruction and analysis of the lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in rheumatoid arthritis. Mol Biosyst 13:1182–1192.
Keck ME, Sillaber I, Ebner K, Welt T, Toschi N, Kaehler ST, Singewald N, Philippu A, et al. (2000), Acute transcranial magnetic stimulation of frontal brain regions selectively modulates the release of vasopressin, biogenic amines and amino acids in the rat brain. Eur J Neurosci 12:3713–3720.
Li SP, Liu B, Song B, Wang CX, Zhou YC (2015), miR-28 promotes cardiac ischemia by targeting mitochondrial aldehyde dehydrogenase 2 (ALDH2) in mus musculus cardiac myocytes. Eur Rev Med Pharmacol Sci 19:752–758.
Li Y, Liu SL, Qi SH (2018), ALDH2 Protects Against Ischemic Stroke in Rats by Facilitating 4-HNE Clearance and AQP4 Down-Regulation. Neurochem Res 43:1339–1347.
Li Y, Zou L, Yang X, Chu L, Ni J, Chu X, Guo T, Zhu Z (2019), Identification of lncRNA, MicroRNA, and mRNA-Associated CeRNA Network of Radiation-Induced Lung Injury in a Mice Model. Dose Response 17:1559325819891012.
Liu CM, Wang RY, Saijilafu, Jiao ZX, Zhang BY, Zhou FQ (2013), MicroRNA-138 and SIRT1 form a mutual negative feedback loop to regulate mammalian axon regeneration. Genes Dev 27:1473–1483.
Lomarev MP, Kanchana S, Bara-Jimenez W, Iyer M, Wassermann EM, Hallett M (2006), Placebo-controlled study of rTMS for the treatment of Parkinson's disease. Mov Disord 21:325–331.
Lu X, Yang Y, Zhou R, Li Y, Yang Y, Wang X (2019), Protrudin modulates seizure activity through GABA(A) receptor regulation. Cell Death Dis 10:897.
Ma N, Pan J, Ye X, Yu B, Zhang W, Wan J (2019), Whole-Transcriptome Analysis of APP/PS1 Mouse Brain and Identification of circRNA-miRNA-mRNA Networks to Investigate AD Pathogenesis. Mol Ther Nucleic Acids 18:1049–1062.
Málly J, Stone TW (2007), New advances in the rehabilitation of CNS diseases applying rTMS. Expert Rev Neurother 7:165–177.
Masuda F (2019), Potentials of rTMS for neurodevelopmental disorders and road to clarification of TMS neuropathology. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation 12:476.
Moradi Chameh H, Janahmadi M, Semnanian S, Shojaei A, Mirnajafi-Zadeh J (2015), Effect of low frequency repetitive transcranial magnetic stimulation on kindling-induced changes in electrophysiological properties of rat CA1 pyramidal neurons. Brain Res 1606:34–43.
Oe S, Kimura T, Yamada H (2019), Regulatory non-coding RNAs in nervous system development and disease. Front Biosci (Landmark Ed) 24:1203–1240.
Pell GS, Roth Y, Zangen A (2011), Modulation of cortical excitability induced by repetitive transcranial magnetic stimulation: influence of timing and geometrical parameters and underlying mechanisms. Prog Neurobiol 93:59–98.
Peng Z, Zhou C, Xue S, Bai J, Yu S, Li X, Wang H, Tan Q (2018), Mechanism of Repetitive Transcranial Magnetic Stimulation for Depression. Shanghai Arch Psychiatry 30:84–92.
Peng ZW, Xue F, Zhou CH, Zhang RG, Wang Y, Liu L, Sang HF, Wang HN, et al. (2018), Repetitive transcranial magnetic stimulation inhibits Sirt1/MAO-A signaling in the prefrontal cortex in a rat model of depression and cortex-derived astrocytes. Mol Cell Biochem 442:59–72.
Post A, Keck ME (2001), Transcranial magnetic stimulation as a therapeutic tool in psychiatry: what do we know about the neurobiological mechanisms? J Psychiatr Res 35:193–215.
Racine RJ (1972), Modification of seizure activity by electrical stimulation. II. Motor seizure. Electroencephalogr Clin Neurophysiol 32:281–294.
Ruff CC, Blankenburg F, Bjoertomt O, Bestmann S, Freeman E, Haynes JD, Rees G, Josephs O, et al. (2006), Concurrent TMS-fMRI and psychophysics reveal frontal influences on human retinotopic visual cortex. Curr Biol 16:1479–1488.
Sander JW (2003), The epidemiology of epilepsy revisited. Curr Opin Neurol 16:165–170.
Shan W, Nagai T, Tanaka M, Itoh N, Furukawa-Hibi Y, Nabeshima T, Sokabe M, Yamada K (2018), Neuronal PAS domain protein 4 (Npas4) controls neuronal homeostasis in pentylenetetrazole-induced epilepsy through the induction of Homer1a. J Neurochem 145:19–33.
Shojaei A, Semnanian S, Janahmadi M, Moradi-Chameh H, Firoozabadi SM, Mirnajafi-Zadeh J (2014), Repeated transcranial magnetic stimulation prevents kindling-induced changes in electrophysiological properties of rat hippocampal CA1 pyramidal neurons. Neuroscience 280:181–192.
Silva MM, Rodrigues B, Fernandes J, Santos SD, Carreto L, Santos MAS, Pinheiro P, Carvalho AL (2019), MicroRNA-186-5p controls GluA2 surface expression and synaptic scaling in hippocampal neurons. Proc Natl Acad Sci U S A 116:5727–5736.
Speer AM, Kimbrell TA, Wassermann EM, J DR, Willis MW, Herscovitch P, Post RM (2000), Opposite effects of high and low frequency rTMS on regional brain activity in depressed patients. Biol Psychiatry 48:1133–1141.
Szu JI, Patel DD, Chaturvedi S, Lovelace JW, Binder DK (2020), Modulation of posttraumatic epileptogenesis in aquaporin-4 knockout mice. Epilepsia 61:1503–1514.
Tan CL, Plotkin JL, Venø MT, von Schimmelmann M, Feinberg P, Mann S, Handler A, Kjems J, et al. (2013), MicroRNA-128 governs neuronal excitability and motor behavior in mice. Science 342:1254–1258.
Tan T, Wang W, Xu H, Huang Z, Wang YT, Dong Z (2018), Low-Frequency rTMS Ameliorates Autistic-Like Behaviors in Rats Induced by Neonatal Isolation Through Regulating the Synaptic GABA Transmission. Front Cell Neurosci 12:46.
Tang L, Liu L, Li G, Jiang P, Wang Y, Li J (2019), Expression Profiles of Long Noncoding RNAs in Intranasal LPS-Mediated Alzheimer's Disease Model in Mice. Biomed Res Int 2019:9642589.
Villa C, Lavitrano M, Combi R (2019), Long Non-Coding RNAs and Related Molecular Pathways in the Pathogenesis of Epilepsy. Int J Mol Sci 20.
Zhang C, Lu R, Wang L, Yun W, Zhou X (2019), Restraint devices for repetitive transcranial magnetic stimulation in mice and rats. Brain Behav 9:e01305.
Zhang J, Yu J, Wang X, Zhao H, Huang M, Zhang X, Zhao X, Huang H, et al. (2008), Effects of pretreatment with low-frequency repetitive transcranial magnetic stimulation on expressions of hippocampus GAD65 and NMDAR-1 in rats with pilocarpine-induced seizures. Chinese Journal of Neuroimmunology and Neurology 15:430–433.

No competing interests reported.

SupplementaryTableS1.docx
Supplementary Table S1 Significantly and differentially expressed lncRNAs in low frequency rTMS and sham rTMS mice
SupplementaryTableS2.docx
Supplementary Table S2 Significantly and differentially expressed mRNAs in low frequency rTMS and sham rTMS mice
SupplementaryTableS3.docx
Supplementary Table S3 Significantly and differentially expressed circRNAs in low frequency rTMS and sham rTMS mice
SupplementaryTableS4.docx
Supplementary Table S4 Significantly and differentially expressed miRNAs in low frequency rTMS and sham rTMS mice
supplementaryFigure1.docx
Supplementary Fig.1 Validation of differentially expressed lncRNAs, mRNAs, circRNAs and miRNAs in low frequency rTMS and sham rTMS mice

Download PDF

Journal Publication

published 03 May, 2023

Read the published version in Journal of Molecular Neuroscience →

Editorial decision: Major revision
28 Jan, 2023
Reviews received at journal
28 Jan, 2023
Reviewers agreed at journal
24 Jan, 2023
Reviewers invited by journal
07 Dec, 2022
Submission checks completed at journal
07 Dec, 2022
Editor assigned by journal
07 Dec, 2022
First submitted to journal
03 Dec, 2022

You are reading this latest preprint version

Transcriptome sequencing of ceRNA network constructing in status epilepticus mice treated by low-frequency repetitive transcranial magnetic stimulation

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Materials And Methods

2.1. Mouse models of status epilepticus

2.2. Procedure for microelectrod implantation, recording and analysis

2.3. Experimental procedures

2.4. RNA Extraction and Microarray Experiments

2.5. Construction of lncRNA-miRNA-mRNA

2.6. Quantitative reverse transcription-polymerase chain reaction

2.7. Data Analysis

Results

3.1 LF-rTMS significantly decreases epiletiform discharges and

3.2 Differentially expressed RNAs in SE mice treated with low-frequency rTMS

3.3 The GO and the KEGG pathway enrichment analysis

3.4 The ceRNA network in SE mice treated with LF- rTMS

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1