Effects and Mechanism of Particulate Matter on Tendon Healing Based on Integrated Analysis of DNA Methylation and RNA Sequencing Data in a Rat Model.
Su-Yel LeeMin-Hyeok LeeSeong-Kyeong JoIn-Ha YooBoler-Erdene SarankhuuHyun-Jin KimYea-Eun KangSeong Eun LeeTae-Yeon KimMoon-Hyang ParkChoong-Sik LeeSeung-Yun HanJi-Hyun MoonJu Young JungGeum-Lan HongNam-Jeong YooEun-Sang YoonJae-Kyu ChoiHo-Ryun WonJi Woong SonJae Hwang SongPublished in: International journal of molecular sciences (2022)
Exposure to particulate matter (PM) has been linked with the severity of various diseases. To date, there is no study on the relationship between PM exposure and tendon healing. Open Achilles tenotomy of 20 rats was performed. The animals were divided into two groups according to exposure to PM: a PM group and a non-PM group. After 6 weeks of PM exposure, the harvest and investigations of lungs, blood samples, and Achilles tendons were performed. Compared to the non-PM group, the white blood cell count and tumor necrosis factor-alpha expression in the PM group were significantly higher. The Achilles tendons in PM group showed significantly increased inflammatory outcomes. A TEM analysis showed reduced collagen fibrils in the PM group. A biomechanical analysis demonstrated that the load to failure value was lower in the PM group. An upregulation of the gene encoding cyclic AMP response element-binding protein (CREB) was detected in the PM group by an integrated analysis of DNA methylation and RNA sequencing data, as confirmed via a Western blot analysis showing significantly elevated levels of phosphorylated CREB. In summary, PM exposure caused a deleterious effect on tendon healing. The molecular data indicate that the action mechanism of PM may be associated with upregulated CREB signaling.
Keyphrases
- particulate matter
- air pollution
- dna methylation
- polycyclic aromatic hydrocarbons
- heavy metals
- single cell
- binding protein
- gene expression
- water soluble
- cell proliferation
- risk assessment
- metabolic syndrome
- mesenchymal stem cells
- machine learning
- stem cells
- deep learning
- oxidative stress
- skeletal muscle
- bone marrow
- transcription factor
- data analysis
- rotator cuff