Identifying the Biomarkers of Spinal Cord Injury and the effects of Neurotrophin-3 Based on MicroRNA and mRNA Signature

doi:10.21203/rs.3.rs-20687/v1

Download PDF

Research article

Identifying the Biomarkers of Spinal Cord Injury and the effects of Neurotrophin-3 Based on MicroRNA and mRNA Signature

https://doi.org/10.21203/rs.3.rs-20687/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background

To gain a better understanding of the molecular mechanisms of spinal cord injury and the effects of Neurotrophin-3, differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) were analyzed.

Methods

The miRNA transcription profile of GSE82195 and the mRNA transcription profile of GSE82196 were downloaded from the Gene Expression Omnibus (GEO). Then, DERs were identified using limma. The noise-robust soft clustering of the intersection DERs was performed using Mfuzz package. Additionally, the integrated miRNAs–targets regulatory network was constructed using Cytoscape. Finally, the Comparative Toxicogenomics Database 2019 update was used to search the central nervous system injury related pathway.

Results

A total of 444 DERs including 382 DEGs and 62 DEmiRNAs were screened between group injury and group none whlie 576 DERs including 523 DEGs and 55 DEmiRNAs were screened between group NT-3 and group injury. Moreover, 80 intersections DERs were identified. DREs in cluster 1 were firstly significantly down-regulated in group injury and subsequently were significantly up-regulated in group NT-3. DERs in cluster 2 were firstly up-regulated in group injury and subsequently down-regulated in group NT-3. OPRL1 and GHSR were enriched in the KEGG pathway of Neuroactive ligand-receptor interaction. OPRL1 was involved in the chemical homeostasis and ion homeostasis while GHSR was related to the regulation of fatty acid metabolic process and regulation of cellular ketone metabolic process.

Conclusion

rno-miR-3072 and rno-miR-667-5p and OPRL1 and GHSR might participate in the pathogenesis of neurological injury and the neurotrophin-3 treatment.

Cellular & Molecular Neuroscience

Cognitive Neuroscience

Developmental Neuroscience

Computational Neuroscience

spinal cord injury

regulatory network

Neurotrophin-3

Spinal cord injury results in permanent disability due to the limited growth capacity of adult central nervous system axons[1]. Impairment of sensorimotor processing in the spinal cord, reduce mobility and upper limb function due to corticospinal tract lesions in spinal cord injury or stroke[2] is a major cause of disability in the world [3]. In the rat model, it has been found that complete transection of corticospinal pathways in the pyramids could lead to increased spasms, excessive mono- and polysynaptic spinal reflexes and impaired locomotion [4].

Neurotrophin-3 (NT-3) is a growth factor found in many body tissues including the heart, intestines, skin, nervous system and in skeletal muscles including muscle spindles [5]. It has been proven that NT-3 is required for the survival, correct connectivity and function of sensory afferents that innervate muscle spindles[6].

MicroRNAs (miRNAs) with the length from 18–25 nucleotides, is a class of non-protein coding RNAs which have been shown to be involved in a wide variety of biological processes as regulatory molecules through suppress the mRNA expression or translation. In 2018, Claudia et al. [7] conducted RNA (miRNA and mRNA) sequence (now available at GSE82195 and GSE82196) describing transcriptional changes in cervical dorsal root ganglia after bilateral pyramidotomy and forelimb intramuscular gene therapy with an adeno-associated viral vector encoding human neurotrophin-3 and Many of the dysregulated genes are involved in axon guidance and plasticity. Intramuscular neurotrophin-3 treatment normalized many of those gene changes and may be one of the mechanisms how reflexes, functional recovery and molecular markers in the spinal cord are restored.

In our study, using the same microarray data by Claudia et al., we aimed to further screen the DEmiRNAs and DEGs with linear models for microarray data (limma) package based on a threshold FDR-value < 0.05 and |log2 FC| > 0.5) and clustering analysis using Mfuzz package, miRNAs-mRNAs regulatory network followed by Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment as well as the central nervous system injury related KEGG pathway screening. It has been shown that analyses based on differential statistical tests may result in different outcomes [8]. Therefore, we believe some different results may be obtained.

RNA sequencing data and the data preprocessing

The miRNA transcription profile of GSE82195 and the mRNA transcription profile of GSE82196 [7] (Illumina HiSeq 2500) including dorsal root ganglion (DRG) tissue samples of normal adult rat (none, n = 6), 10 weeks post-pyramidotomy, intramuscular AAV-1 GFP (injury, n = 6) and 10 weeks post-pyramidotomy, intramuscular AAV-1 prepro-neurotrophin-3 (NT-3, n = 6) were downloaded from the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/). The preprocess Core package in R language (version 1.44, https://www.bioconductor.org/packages/devel/bioc/html/preprocessCore.html) was employed to perform the background correction and the normalization [9].

Differentilly Expressed Rnas Analysis

Limma package in R language [10] (Version 3.34.0, https://bioconductor.org/packages/release/bioc/html/limma.html) to screen the differentilly expressed RNAs (DERs) including differentially expressed genes (DEGs) and differentially expressed miRNA (DEmiRNAs) between group injury and group none, as well as the DEGs and DEmiRNAs between group NT-3 and group injury. We used the FDR-value < 0.05 and |log2 FC| > 0.5 as the cutoff criteria for DEGs and DEmiRNAs. Furthermore, the intersection DERs were also screened. The pheatmap package in R [11] (version 1.0.8, https://cran.r-project.org/package=pheatmap) was employed to conduct the bidirectional hierarchical clustering.

Clustering Analysis

With the aforementioned cut-off criteria, two clusters were obtained including cluster 1 (44 DERs, containing 10 miRNAs and 4 mRNAs) and cluster 2 (36 DERs, containing 10 miRNAs and 26 mRNAs) (Table 1). DREs in cluster 1 were firstly significantly downregulated in group injury and subsequently were significantly upregulated in group NT-3. DERs in cluster 2 were firstly upregulated in group injury and subsequently downregulated in group NT-3 (Fig. 3).

Table 1

The genes in clusters
cluster1	cluster2
Adsl	Abca4
Aurkb	Aptx
Bace2	Bdh2
Chdh	Cybrd1
Col9a1	Dmac2
Cxcl14	Drc1
Dhh	Fgd1
Ehd4	Fli1
Epha10	Frzb
Etv5	Gclc
Fam83d	Ghsr
Fam83f	Id1
Gas7	Mrnip
Gjb1	Nebl
Gucy2d	Nme3
Loxl4	Oprl1
Map4k4	Pdcd2l
Meox1	Pgf
Pdia5	Ppl
Plk2	Prkag3
Plxdc1	Rbpms2
Ppp4r1	rno-let-7d-3p
Ptger4	rno-miR-182
Radil	rno-miR-187-5p
Rasa3	rno-miR-27a-3p
Reln	rno-miR-29b-1-5p
rno-miR-145-5p	rno-miR-30e-3p
rno-miR-146b-5p	rno-miR-379-3p
rno-miR-1839-5p	rno-miR-455-3p
rno-miR-217-5p	rno-miR-505-5p
rno-miR-3072	rno-miR-672-3p
rno-miR-344b-1-3p	Slc22a25
rno-miR-3594-3p	Slc4a4
rno-miR-381-3p	Slc6a6
rno-miR-666-5p	Slc9a5
rno-miR-667-5p	Smpd2
Sh3rf1
Shbg
Shc4

Mirna-mrna Regulatory Networks Construction

By using DERs in the clusters, the the miRNA-mRNA regulatory network was constructed. Firstly, DEmiRNA targets was predicted using starBase database (Version 2.0, http://starbase.sysu.edu.cn/). Secondly, the miRNA-mRNA pair with the negative correlation were retained. lastly, the screened miRNA-mRNA pairs were visualized using Cytoscape software with the DEmiRNAs in cluster 1 and their target DEGs in cluster 2, as well as using the DEmiRNAs in cluster 2 and their target DEGs in cluster 1 (Version 3.6.1, http://www.cyto scape.org) [13]. DAVID (version 6.8, https://david.ncifcrf.gov/) was used to perform the GO and KEGG pathway enrichment for the mRNA in the network [14].

Central Nervous System Injury Related Kegg Pathway Screening

In the CTD database, 13 KEGG pathways were searched, among which Neuroactive ligand-receptor interaction (including two genes: OPRL1 and GHSR in cluster 2) was intersected with enriched KEGG pathway for the DEGs in the miRNA-mRNA regulatory network. GHSR could be the target of rno-miR-1839-5p and rno-miR-344-3p while OPRL1could be the target of rno-miR-3072 and rno-miR-667-5p (Fig. 6).

DERs analysis

A total of 444 DERs including 382 DEGs and 62 DEmiRNAs were screened between group injury and group none whlie 576 DERs including 523 DEGs and 55 DEmiRNAs were screened between group NT-3 and group injury. Moreover, 80 intersections DERs were identified. We used volcano plots for the visualization and assessment of the variation (or reproducibility) of RNAs expression (Fig. 1). The bidirectional hierarchical clustering revealed that DERs could distinguish these two groups (Fig. 2).

Mirna-mrna Network Construction

By using the DEmiRNAs in cluster 2 and their target DEGs in cluster 1, the miRNA-mRNA regulatory network was constructed which contained 45 miRNA-mRNA pairs, while by using the DEmiRNAs in cluster 1 and their target DEGs in cluster 2, the miRNA-mRNA regulatory network was constructed which contained 31 miRNA-mRNA pairs (Fig. 4). Functional enrichment showed that 7 GO terms and 3 KEGG patyways were enriched for the DEGs in cluster 1 while 9 GO terms and 1 KEGG pathways were enriched for the DEGs in cluster 2 (Fig. 5)

In order to further investigate the mechanism of neurological injury and the neurotrophin-3 treatment to improves mobility, we re-analyzed the mRNA and miRNA expression of DRG tissues from the normal adult rat, 10 weeks post-pyramidotomy, intramuscular AAV-1 GFP adult rat and 10 weeks post-pyramidotomy, intramuscular AAV-1 prepro-neurotrophin-3 adult rat and screened the two genes OPRL1 and GHSR were firstly significantly upregulated in group injury and subsequently downregulated the with the treatment of NT-3. Besides, rno-miR-1839-5p, rno-miR-3072 and rno-miR-667-5p were firstly downregulated in group injury and subsequently upregulated with the treatment of NT-3.

GHSR (growth hormone secretagogue 1 receptor) is the receptor of Ghrelin which is a brain-gut peptide hormone secreted from the stomach to stimulate food intake. Additionally, GHSR has been found to mediate the neuroprotection in rodents including the activation of UCP2 and decreasing in mitochondrial ROS production, suppression of the pro-inflammatory cytokines TNFa, IL-6 and IL-1b and augmentation of midbrain dopamine neuron electrical activity [16]. The functional enrichment showed that GHSR was related to the regulation of fatty acid metabolic process and regulation of cellular ketone metabolic process. Former study has demonstrated that the ketogenic diet improves forelimb motor function after spinal cord injury in rodents [17]. And Omega-3 polyunsaturated fatty acids could promote functional recovery in rats undergoing spinal cord injury [18]. So, GHSR could be related to neurological injury and the neurotrophin-3 treatment by regulating the cellular ketone metabolic process and fatty acid metabolic process.

OPRL1 encodes a G protein-coupled receptor for nociceptin, an endogenous opioid-related neuropeptide which is one of four opioid receptors. Opioid receptor activation could attenuate the release of inhibitory neurotransmitters and changes in neuronal excitability [19] which indicated that OPRL1 could played a important role in the nervous system. The GO functional enrichment showed that OPRL1 was involved in the chemical homeostasis and ion homeostasis. It has been illustrated that through a return to homeostasis of chloride after spinal cord injury, exercise could help to contribute to reflex recovery [20]. Additionally, OPRL1 could be the target of rno-miR-3072 and rno-miR-667-5p. MiR-3072 has been found to be related to the decrease of damage and paralysis of lower limbs following spinal cord injury (SCI) [21]. rno-miR-667 may be associated with presence of nerve injury-induced hypersensitivity [22]. Therefore, we speculated that OPRL1 targeted by rno-miR-3072 and rno-miR-667-5p could play an important role in neurological injury and the neurotrophin-3 treatment.

Besides, OPRL1 and GHSR were enriched in the KEGG pathway of Neuroactive ligand-receptor interaction which is found to associated with central nervous system injury in CTD database.

DEmiRNAs rno-miR-3072, DEmiRNAs rno-miR-667-5p, OPRL1 and GHSR were identified might participate in the pathogenesis of neurological injury and the neurotrophin-3 treatment. However, further research is required to validate the results.

DEmiRNAs

differentially expressed microRNAs;

DEGs

differentially expressed genes;

DERs

differentilly expressed RNAs;

GEO

Gene Expression Omnibus;

DRG

Dorsal root ganglion;

GHSR

Growth hormone secretagogue 1 receptor;

NT-3

Prepro-neurotrophin-3;

Gene Ontology;

KEGG

Kyoto Encyclopedia of Genes and Genomes ;

Authors' contributions

Shanshan Yu and Shuang Qi conceived, designed, priformed the experiments and wrote the paper. Zinan Li analyzed and interpreted the data and contributed methods, materials, analysis tools or data. All authors read and approved the final manuscript.

Acknowledgements

Not applicable

Competing interests

The author declares that they have no competing interests.

Availability of data and materials

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

The authors received no financial support for this study.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Fink KL, Strittmatter SM, Cafferty WB. Comprehensive Corticospinal Labeling with mu-crystallin Transgene Reveals Axon Regeneration after Spinal Cord Trauma in ngr1-/- Mice. J Neurosci. 2015;35(46):15403–18.
Maraka S, Jiang Q, Jafari-Khouzani K, Li L, Malik S, Hamidian H, Zhang T, Lu M, Soltanian-Zadeh H, Chopp M, et al. Degree of corticospinal tract damage correlates with motor function after stroke. Ann Clin Transl Neurol. 2014;1(11):891–9.
Ma VY, Chan L, Carruthers KJ. Incidence, prevalence, costs, and impact on disability of common conditions requiring rehabilitation in the United States: stroke, spinal cord injury, traumatic brain injury, multiple sclerosis, osteoarthritis, rheumatoid arthritis, limb loss, and back pain. Arch Phys Med Rehabil. 2014;95(5):986–95 e981.
Kathe C, Hutson TH, McMahon SB, Moon LD. Intramuscular Neurotrophin-3 normalizes low threshold spinal reflexes, reduces spasms and improves mobility after bilateral corticospinal tract injury in rats. Elife 2016, 5.
Murase K, Igarashi K, Hayashi K. Neurotrophin-3 (NT-3) levels in the developing rat nervous system and in human samples. Clin Chim Acta. 1994;227(1–2):23–36.
Boyce VS, Mendell LM. Neurotrophins and spinal circuit function. Front Neural Circuits. 2014;8:59.
Kathe C, Moon LDF. RNA sequencing dataset describing transcriptional changes in cervical dorsal root ganglia after bilateral pyramidotomy and forelimb intramuscular gene therapy with an adeno-associated viral vector encoding human neurotrophin-3. Data Brief. 2018;21:377–85.
Afsari B, Geman D, Fertig EJ. Learning dysregulated pathways in cancers from differential variability analysis. Cancer Inform. 2014;13(Suppl 5):61–7.
Heng L, Jia Z, Bai J, Zhang K, Zhu Y, Ma J, Zhang J, Duan H. Molecular characterization of metastatic osteosarcoma: Differentially expressed genes, transcription factors and microRNAs. Mol Med Rep. 2017;15(5):2829–36.
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.
Wang L, Cao C, Ma Q, Zeng Q, Wang H, Cheng Z, Zhu G, Qi J, Ma H, Nian H, et al. RNA-seq analyses of multiple meristems of soybean: novel and alternative transcripts, evolutionary and functional implications. BMC Plant Biol. 2014;14:169.
Kumar L. M EF: Mfuzz: a software package for soft clustering of microarray data. Bioinformation. 2007;2(1):5–7.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.
Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.
Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ. The Comparative Toxicogenomics Database: update 2019. Nucleic Acids Res. 2019;47(D1):D948–54.
Stutz B, Nasrallah C, Nigro M, Curry D, Liu ZW, Gao XB, Elsworth JD, Mintz L, Horvath TL. Dopamine neuronal protection in the mouse Substantia nigra by GHSR is independent of electric activity. Mol Metab. 2019;24:120–38.
Streijger F, Plunet WT, Lee JH, Liu J, Lam CK, Park S, Hilton BJ, Fransen BL, Matheson KA, Assinck P, et al. Ketogenic diet improves forelimb motor function after spinal cord injury in rodents. PLoS One. 2013;8(11):e78765.
Figueroa JD, Serrano-Illan M, Licero J, Cordero K, Miranda JD, De Leon M. Fatty Acid Binding Protein 5 Modulates Docosahexaenoic Acid-Induced Recovery in Rats Undergoing Spinal Cord Injury. J Neurotrauma. 2016;33(15):1436–49.
Seo EJ, Efferth T, Panossian A. Curcumin downregulates expression of opioid-related nociceptin receptor gene (OPRL1) in isolated neuroglia cells. Phytomedicine. 2018;50:285–99.
Cote MP, Gandhi S, Zambrotta M, Houle JD. Exercise modulates chloride homeostasis after spinal cord injury. J Neurosci. 2014;34(27):8976–87.
Ueno K, Samura M, Nakamura T, Tanaka Y, Takeuchi Y, Kawamura D, Takahashi M, Hosoyama T, Morikage N, Hamano K. Increased plasma VEGF levels following ischemic preconditioning are associated with downregulation of miRNA-762 and miR-3072-5p. Sci Rep. 2016;6:36758.
Tavares-Ferreira D, Lawless N, Bird EV, Atkins S, Collier D, Sher E, Malki K, Lambert DW, Boissonade FM. Correlation of miRNA expression with intensity of neuropathic pain in man. Mol Pain. 2019;15:1744806919860323.

Download PDF

Version 1

posted

You are reading this latest preprint version

Identifying the Biomarkers of Spinal Cord Injury and the effects of Neurotrophin-3 Based on MicroRNA and mRNA Signature

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Background

Methods

RNA sequencing data and the data preprocessing

Differentilly Expressed Rnas Analysis

Clustering Analysis

Mirna-mrna Regulatory Networks Construction

Central Nervous System Injury Related Kegg Pathway Screening

Results

DERs analysis

Mirna-mrna Network Construction

Discussion

Conclusion

Abbreviations

Declarations

References

Status:

Version 1