Skip to main content

Advertisement

Log in

Constructing and Validating a Network of Potential Olfactory Sheathing Cell Transplants Regulating Spinal Cord Injury Progression

  • Published:
Molecular Neurobiology Aims and scope Submit manuscript

Abstract

The pathology of spinal cord injury (SCI), including primary and secondary injuries, primarily involves hemorrhage, ischemia, edema, and inflammatory responses. Cell transplantation has been the most promising treatment for SCI in recent years; however, its specific molecular mechanism remains unclear. In this study, bioinformatics analysis verified by experiment was used to elucidate the hub genes associated with SCI and to discover the underlying molecular mechanisms of cell intervention. GSE46988 data were downloaded from the Gene Expression Omnibus dataset. In our study, differentially expressed genes (DEGs) were reanalyzed using the “R” software (R v4.2.1). Functional enrichment and protein–protein interaction network analyses were performed, and key modules and hub genes were identified. Network construction was performed for the hub genes and their associated miRNAs. Finally, a semi-quantitative analysis of hub genes and pathways was performed using quantitative real-time polymerase chain reaction. In total, 718 DEGs were identified, mainly enriched in immune and inflammation-related functions. We found that Cd4, Tp53, Rac2, and Akt3 differed between vehicle and transplanted groups, suggesting that these genes may play an essential role in the transplantation of olfactory ensheathing cells, while a toll-like receptor signaling pathway was significantly enriched in Gene set enrichment analysis, and then, the differences were statistically significant by experimentally verifying the expression of their associated molecules (Tlr4, Nf-κb, Ikkβ, Cxcl2, and Tnf-α). In addition, we searched for upstream regulatory molecules of these four central genes and constructed a regulatory network. This study is the first to construct a regulatory network for olfactory ensheathing cell transplantation in treating SCI, providing a new idea for SCI cell therapy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data Availability

The data used to support the findings of this study have been included in this article.

Abbreviations

SCI:

Spinal cord injury

GSE:

GEO series

DEGs:

Differentially expressed genes

PPI:

Protein–protein interaction network

GSEA:

Gene set enrichment analysis

qRT-PCR:

Quantitative real-time polymerase chain reaction

Tp53:

Tumor suppressor p53

Rac2:

Rac family small GTPase 2

OECs:

Olfactory ensheathing cells

miRNA:

MicroRNA

mRNA:

Messenger RNA

KEGG:

Kyoto Encyclopedia of Genes and Genome

HE:

Hematoxylin and eosin

SEM:

Mean standard error

References

  1. Eckert MJ, Marti MJ (2017) Trauma: spinal cord injury. Surg Clin North Am 97(5):1031–1045

    Article  PubMed  Google Scholar 

  2. Ibrahim E, Brackett NL, Lynne CM (2016) Advances in the management of infertility in men with spinal cord injury. Asian J Androl 18(3):382–90

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Witiw CD, Fehlings MG (2015) Acute spinal cord injury. J Spinal Disord Tech 28(6):202–210

    Article  PubMed  Google Scholar 

  4. Lee BB et al (2014) The global map for traumatic spinal cord injury epidemiology: update 2011, global incidence rate. Spinal Cord 52(2):110–116

    Article  PubMed  CAS  Google Scholar 

  5. Yang R et al (2017) Epidemiological characteristics of traumatic spinal cord injury in Guangdong, China. Spine (Phila Pa 1976) 42(9):E555-e561

    Article  PubMed  Google Scholar 

  6. Chen J et al (2021) Epidemiological features of traumatic spinal cord injury in Guangdong Province, China. J Spinal Cord Med 44(2):276–281

    Article  PubMed  Google Scholar 

  7. Assinck P et al (2017) Cell transplantation therapy for spinal cord injury. Nat Neurosci 20(5):637–647

    Article  PubMed  CAS  Google Scholar 

  8. Radtke C, Kocsis JD (2014) Olfactory-ensheathing cell transplantation for peripheral nerve repair: update on recent developments. Cells Tissues Organs 200(1):48–58

    Article  PubMed  CAS  Google Scholar 

  9. Gu J et al (2019) Olfactory ensheathing cells promote nerve regeneration and functional recovery after facial nerve defects. Neural Regen Res 14(1):124–131

    Article  PubMed  PubMed Central  Google Scholar 

  10. Tsai S, Gamblin TC (2019) Gamblin, molecular characteristics of biliary tract and primary liver tumors. Surg Oncol Clin N Am 28(4):685–693

    Article  PubMed  Google Scholar 

  11. Yan P et al (2018) In silico analyses for potential key genes associated with gastric cancer. Peer J 6:e6092

    Article  PubMed  PubMed Central  Google Scholar 

  12. Ye B et al (2018) High-throughput sequencing of the immune repertoire in oncology: applications for clinical diagnosis, monitoring, and immunotherapies. Cancer Lett 416:42–56

    Article  PubMed  CAS  Google Scholar 

  13. Çakmak HA, Demir M (2020) MicroRNA and cardiovascular diseases. Balkan Med J 37(2):60–71

    PubMed  PubMed Central  Google Scholar 

  14. Chen L et al (2018) Proteomics for biomarker identification and clinical application in kidney disease. Adv Clin Chem 85:91–113

    Article  PubMed  CAS  Google Scholar 

  15. Su W et al (2021) Exploring the pathogenesis of psoriasis complicated with atherosclerosis via microarray data analysis. Front Immunol 12:667690

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Li R, Sim I (2019) How clinical trial data sharing platforms can advance the study of biomarkers. J Law Med Ethics 47(3):369–373

    Article  PubMed  Google Scholar 

  17. Subramanian A et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102(43):15545–15550

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Debrabant B (2017) The null hypothesis of GSEA, and a novel statistical model for competitive gene set analysis. Bioinformatics 33(9):1271–1277

    Article  PubMed  CAS  Google Scholar 

  19. Szklarczyk D et al (2017) The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res 45(D1):D362-d368

    Article  PubMed  CAS  Google Scholar 

  20. Franceschini A et al (2013) STRING v91: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 41(Database issue):D808-15

    PubMed  CAS  Google Scholar 

  21. Bader GD, Hogue CW (2003) An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4:2

    Article  PubMed  PubMed Central  Google Scholar 

  22. de Rivero Vaccari JP et al (2008) A molecular platform in neurons regulates inflammation after spinal cord injury. J Neurosci 28(13):3404–3414

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hasegawa T et al (2023) Cytotoxic CD4(+) T cells eliminate senescent cells by targeting cytomegalovirus antigen. Cell 186(7):1417-1431.e20

    Article  PubMed  CAS  Google Scholar 

  24. Itano AA, Jenkins MK (2003) Antigen presentation to naive CD4 T cells in the lymph node. Nat Immunol 4(8):733–739

    Article  PubMed  CAS  Google Scholar 

  25. Kane LP, Lin J, Weiss A (2000) Signal transduction by the TCR for antigen. Curr Opin Immunol 12(3):242–249

    Article  PubMed  CAS  Google Scholar 

  26. Fu Y et al (2023) Identification and validation of immune-related genes diagnostic for progression of atherosclerosis and diabetes. J Inflamm Res 16:505–521

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Gay D et al (1987) Functional interaction between human T-cell protein CD4 and the major histocompatibility complex HLA-DR antigen. Nature 328(6131):626–629

    Article  PubMed  CAS  Google Scholar 

  28. Klatzmann DR, McDougal JS, Maddon PJ (1990) The CD4 molecule and HIV infection. Immunodefic Rev 2(1):43–66

    PubMed  CAS  Google Scholar 

  29. Gebhardt T et al (2011) Different patterns of peripheral migration by memory CD4+ and CD8+ T cells. Nature 477(7363):216–219

    Article  PubMed  CAS  Google Scholar 

  30. Laumaea A et al (2023) Small CD4 mimetics sensitize HIV-1-infected macrophages to antibody-dependent cellular cytotoxicity. Cell Rep 42(1):111983

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Diallo MS et al (2021) A comparison of cell activation, exhaustion, and expression of HIV coreceptors and restriction factors in HIV-1- and HIV-2-infected nonprogressors. AIDS Res Hum Retroviruses 37(3):214–223

    Article  PubMed  CAS  Google Scholar 

  32. Yan H et al (2022) Design of a bispecific HIV entry inhibitor targeting the cell receptor CD4 and viral fusion protein Gp41. Front Cell Infect Microbiol 12:916487

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Donehower LA et al (2019) Integrated analysis of TP53 gene and pathway alterations in the cancer genome atlas. Cell Rep 28(5):1370-1384.e5

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Sablina AA et al (2005) The antioxidant function of the p53 tumor suppressor. Nat Med 11(12):1306–1313

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Kotipatruni RR et al (2011) p53- and Bax-mediated apoptosis in injured rat spinal cord. Neurochem Res 36(11):2063–2074

    Article  PubMed  CAS  Google Scholar 

  36. Mehta SL et al (2013) Overexpression of human selenoprotein H in neuronal cells enhances mitochondrial biogenesis and function through activation of protein kinase A, protein kinase B, and cyclic adenosine monophosphate response element-binding protein pathway. Int J Biochem Cell Biol 45(3):604–611

    Article  PubMed  CAS  Google Scholar 

  37. Kanno H et al (2012) The role of mTOR signaling pathway in spinal cord injury. Cell Cycle 11(17):3175–3179

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Wennerberg K, Der CJ (2004) Rho-family GTPases: it’s not only Rac and Rho (and I like it). J Cell Sci 117(Pt 8):1301–1312

    Article  PubMed  CAS  Google Scholar 

  39. Didsbury J et al (1989) rac, a novel ras-related family of proteins that are botulinum toxin substrates. J Biol Chem 264(28):16378–16382

    Article  PubMed  CAS  Google Scholar 

  40. Hall A, Lallin G (2010) Rho and Ras GTPases in axon growth, guidance, and branching. Cold Spring Harb Perspect Biol 2(2):a001818

    Article  PubMed  PubMed Central  Google Scholar 

  41. Yang Z et al (2017) Identification of crucial genes associated with rat traumatic spinal cord injury. Mol Med Rep 15(4):1997–2006

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Iversen PO et al (2000) Depressed immunity and impaired proliferation of hematopoietic progenitor cells in patients with complete spinal cord injury. Blood 96(6):2081–2083

    Article  PubMed  CAS  Google Scholar 

  43. Dooley JL et al (2009) Regulation of inflammation by Rac2 in immune complex-mediated acute lung injury. Am J Physiol Lung Cell Mol Physiol 297(6):L1091–L1102

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Tian Y, Autieri MV (2007) Cytokine expression and AIF-1-mediated activation of Rac2 in vascular smooth muscle cells: a role for Rac2 in VSMC activation. Am J Physiol Cell Physiol 292(2):C841–C849

    Article  PubMed  CAS  Google Scholar 

  45. Spillane M, Gallo G (2014) Involvement of Rho-family GTPases in axon branching. Small GTPases 5:e27974

    Article  PubMed  PubMed Central  Google Scholar 

  46. Numano F et al (2009) Critical involvement of Rho GTPase activity in the efficient transplantation of neural stem cells into the injured spinal cord. Mol Brain 2:37

    Article  PubMed  PubMed Central  Google Scholar 

  47. Lundquist EA (2003) Rac proteins and the control of axon development. Curr Opin Neurobiol 13(3):384–390

    Article  PubMed  CAS  Google Scholar 

  48. Carmona FJ et al (2016) AKT signaling in ERBB2-amplified breast cancer. Pharmacol Ther 158:63–70

    Article  PubMed  CAS  Google Scholar 

  49. Sarbassov DD et al (2005) Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex. Science 307(5712):1098–1101

    Article  PubMed  CAS  Google Scholar 

  50. Alessi DR et al (1997) Characterization of a 3-phosphoinositide-dependent protein kinase which phosphorylates and activates protein kinase Balpha. Curr Biol 7(4):261–269

    Article  PubMed  CAS  Google Scholar 

  51. Walker KS et al (1998) Activation of protein kinase B beta and gamma isoforms by insulin in vivo and by 3-phosphoinositide-dependent protein kinase-1 in vitro: comparison with protein kinase B alpha. Biochem J 331(Pt 1):299–308

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Meier R et al (1997) Mitogenic activation, phosphorylation, and nuclear translocation of protein kinase Bbeta. J Biol Chem 272(48):30491–30497

    Article  PubMed  CAS  Google Scholar 

  53. Recabarren D, Alarcón M (2017) Gene networks in neurodegenerative disorders. Life Sci 183:83–97

    Article  PubMed  CAS  Google Scholar 

  54. Yao R et al (2021) Euxanthone inhibits traumatic spinal cord injury via anti-oxidative stress and suppression of p38 and PI3K/Akt signaling pathway in a rat model. Transl Neurosci 12(1):114–126

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Zhao R et al (2022) Baicalin attenuates blood-spinal cord barrier disruption and apoptosis through PI3K/Akt signaling pathway after spinal cord injury. Neural Regen Res 17(5):1080–1087

    Article  PubMed  CAS  Google Scholar 

  56. Hu J et al (2021) Chondroitinase ABC Promotes Axon Regeneration and Reduces Retrograde Apoptosis Signaling in Lamprey. Front Cell Dev Biol 9:653638

    Article  PubMed  PubMed Central  Google Scholar 

  57. Li H et al (2020) Initiation of PI3K/AKT pathway by IGF-1 decreases spinal cord injury-induced endothelial apoptosis and microvascular damage. Life Sci 263:118572

    Article  PubMed  CAS  Google Scholar 

  58. Goswami R et al (1999) Overexpression of Akt (protein kinase B) confers protection against apoptosis and prevents formation of ceramide in response to pro-apoptotic stimuli. J Neurosci Res 57(6):884–893

    Article  PubMed  CAS  Google Scholar 

  59. Liao HY et al (2022) Ski regulates proliferation and migration of reactive astrocytes induced by lipopolysaccharide (LPS) through PI3K/Akt pathway. J Neuroimmunol 364:577807

    Article  PubMed  CAS  Google Scholar 

  60. Zhang H, Gong M, Luo X (2020) Methoxytetrahydro-2H-pyran-2-yl)methyl benzoate inhibits spinal cord injury in the rat model via PPAR-γ/PI3K/p-Akt activation. Environ Toxicol 35(6):714–721

    Article  PubMed  CAS  Google Scholar 

  61. Behzadi E, Behzadi P (2016) The role of toll-like receptors (TLRs) in urinary tract infections (UTIs). Cent Eur J Urol 69(4):404–410

    CAS  Google Scholar 

  62. Bsibsi M et al (2006) Toll-like receptor 3 on adult human astrocytes triggers production of neuroprotective mediators. Glia 53(7):688–695

    Article  PubMed  Google Scholar 

  63. Kigerl KA et al (2007) Toll-like receptor (TLR)-2 and TLR-4 regulate inflammation, gliosis, and myelin sparing after spinal cord injury. J Neurochem 102(1):37–50

    Article  PubMed  CAS  Google Scholar 

  64. Lafon M et al (2006) The innate immune facet of brain: human neurons express TLR-3 and sense viral dsRNA. J Mol Neurosci 29(3):185–194

    Article  PubMed  CAS  Google Scholar 

  65. Wang Y et al (2020) Small-Molecule Modulators of Toll-like Receptors. Acc Chem Res 53(5):1046–1055

    Article  PubMed  CAS  Google Scholar 

  66. Akira S, Uematsu S, Takeuchi O (2006) Pathogen recognition and innate immunity. Cell 124(4):783–801

    Article  PubMed  CAS  Google Scholar 

  67. Vaure C, Liu Y (2014) A comparative review of toll-like receptor 4 expression and functionality in different animal species. Front Immunol 5:316

    Article  PubMed  PubMed Central  Google Scholar 

  68. Freria CM et al (2016) Impairment of toll-like receptors 2 and 4 leads to compensatory mechanisms after sciatic nerve axotomy. J Neuroinflammation 13(1):118

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Guo X et al (2022) Effects of exosomal microRNAs on oral mucosal epithelial cells cocultured with limbal niche cells. Contrast Media Mol Imaging 2022:9794950

  70. Slota JA, Booth SA (2019) MicroRNAs in neuroinflammation: implications in disease pathogenesis, biomarker discovery and therapeutic applications. Noncoding RNA 5(2):35

  71. Guo Y et al (2019) MicroRNAs in microglia: how do micrornas affect activation, inflammation, polarization of microglia and mediate the interaction between microglia and glioma? Front Mol Neurosci 12:125

    Article  PubMed  PubMed Central  Google Scholar 

  72. Zhou M et al (2018) Abnormal expression of MicroRNAs induced by chronic unpredictable mild stress in rat hippocampal tissues. Mol Neurobiol 55(2):917–935

    Article  PubMed  CAS  Google Scholar 

  73. Liu X et al (2019) MiR-409-3p and MiR-1896 co-operatively participate in IL-17-induced inflammatory cytokine production in astrocytes and pathogenesis of EAE mice via targeting SOCS3/STAT3 signaling. Glia 67(1):101–112

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We acknowledge the GEO databases for providing their platforms and the contributors for uploading meaningful datasets.

Funding

This work was supported by the Science and Technology Bureau of Quanzhou.

(Grant Number 2022C036R), Medical Innovation Science and Technology Project of Fujian Province (Grant Number 2020CXA047), and Natural Science Foundation of Fujian Province (Grant Number 2020J01227).

Author information

Authors and Affiliations

Authors

Contributions

YZ, YSY, and CMW contributed to the study design and data analysis. YZ wrote the paper. WCC and HFH critically revised the manuscript for its intellectual content.

Corresponding author

Correspondence to He-fan He.

Ethics declarations

Ethics Approval and Consent to Participate

All animal procedures were performed in accordance with the Care and Use of Laboratory Animals guidelines and were approved by Fujian Medical University.

Consent for Publication

Not applicable.

Competing interests

There author declare no competing conflicts.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Yang, Ys., Chen, Wc. et al. Constructing and Validating a Network of Potential Olfactory Sheathing Cell Transplants Regulating Spinal Cord Injury Progression. Mol Neurobiol 60, 6883–6895 (2023). https://doi.org/10.1007/s12035-023-03510-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12035-023-03510-9

Keywords

Navigation