Time-Series Expression Profile Analysis of Post-Traumatic Joint Contracture in Rats at the Early Stages of the Healing Process

Abstract

Yuxin Zhang,1– 3,* Zhigang Wu,1,* Shenji Lu,2 Minghui Lin,1 Xiaokun Yue,4 Zengguang Wang,4 Bin Cai1,2 1Department of Rehabilitation Medicine, Hainan Western Central Hospital, Danzhou, Hainan, People’s Republic of China; 2Department of Rehabilitation Medicine, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 3Department of Oral Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai, People’s Republic of China; 4Shanghai Key Laboratory of Orthopedic Implants, Department of Orthopaedic Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yuxin Zhang; Bin Cai, Department of Rehabilitation Medicine, Hainan Western Central Hospital, No. 2, Fubo East Road, Nada Town, Danzhou, Hainan, 571700, People’s Republic of China, Tel [phone], Email [email protected]; [email protected]: This study aimed to characterize the gene expression profile at the early stages of the healing process of post-traumatic joint contracture (PTJC).Methods: Twelve rats were used for PTJC model establishment and were divided into four groups according to the sampling time: S0d, S3d, S7d and S2w. Transcriptome sequencing was performed on fibrotic joint capsule samples in four groups followed by bioinformatics analyses including differentially expressed genes (DEGs) screening, Short Time-series Expression Miner (STEM) analysis, network construction, and pathway analysis. Five important genes were validated by qRT-PCR.Results: A total of 1171, 1052 and 793 DEGs were screened in S3d vs S0d, S7d vs S0d, and S2w vs S0d comparison groups, respectively. A total of 383 overlapping genes were screened out, which were significantly enriched in some inflammatory functions and pathways. Through STEM analysis, three clusters were identified, including 105, 57 and 57 DEGs, respectively. Then, based on the cluster genes, 10 genes, such as Il6, Timp1, Cxcl1, Cxcr4 and Mmp3, were further selected after PPI and pathway analyses. The expression levels of Il6, Timp1, Cxcl1, Cxcr4 and Mmp3 were validated by qRT-PCR.Conclusion: The present study screened out several genes with significant changes in expression levels at the early stages of the healing process in PTJC, such as Il6, Timp1, Cxcl1, Cxcr4 and Mmp3. Our study offers a valuable contribution to the understanding pathomechanism of PTJC.Keywords: post-traumatic joint contracture, transcriptome sequencing, Short Time-series Expression Miner analysis, joint capsule fibrosis

Keywords

• post traumatic joint contracture
• transcriptome sequencing
• short time-series expression miner analysis
• joint capsule fibrosis