| Literature DB >> 31058187 |
Ya-Ni Wang1,2,3, Yu-Fei Xu1,2,3, Ya-Xue Liang1,2,3, Xiao-Yun Fan1,2,3, Xiao-Jun Zha4.
Abstract
Eosinophil asthma is characterized by the infiltration of eosinophils to the bronchial epithelium. The toxic cationic protein released by eosinophils, mainly major basic protein (MBP), is one of the most important causative factors of epithelium damage. Poly-L-Arginine (PLA) is a kind of synthetic cationic polypeptides, which is widely used to mimic the effects of MBP on epithelial cells in vitro. However, little is known about the changes of differentially expressed genes (DEGs) and transcriptome profiles in cationic protein stimulated epithelial cells. In this study, we compared the expression of DEGs and transcriptome profiles between PLA-treated airway epithelial cells NCI-H292 and control. The results showed that there were a total of 230 DEGs, of which 86 were upregulated and 144 were downregulated. These DEGs were further analyzed using gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The results showed that the upregulated DEGs were involved in cholesterol synthesis, protein binding, and composition of cellular membranes, mainly enriched in metabolic and biosynthesis pathways. While downregulated DEGs were implicated in cell adhesion, extracellular matrix (ECM) composition and cytoskeleton and were enriched in ECM pathway. In conclusion, our research provided the mechanism of the cationic polypeptides acting on the airway epithelial cells on the basis of transcriptomic profile, and this could be regarded as important indications in unveiling the pathologic role of natural cationic proteins in the damage to epithelial cells of asthmatics.Entities:
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Year: 2019 PMID: 31058187 PMCID: PMC6463615 DOI: 10.1155/2019/3638469
Source DB: PubMed Journal: Biomed Res Int Impact factor: 3.411
Primers applied in qRT-PCR.
| Genes | Primer sequence |
|---|---|
| GAPDH | Forward 5′-TCC AAA ATC AAG TGG GGC GA-3′ |
| Reverser 5′-TGA TGA CCC TTT TGG CTC CC-3 | |
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| ACAT2 | Forward 5′-TCA ATG AAG CCT TTG CAG-3′ |
| Reverser 5′-CAA TAT TGA CCT TCT CTG GG-3′ | |
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| HMGCS1 | Forward 5′-TTG GCT TCA TGA TCT TTC AC-3′ |
| Reverser 5′-AAT TTA ACA TCC CCA AAG GC-3′ | |
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| SQLE | Forward 5′-GGC GAG GAG GAG CGA GTC TG-3′ |
| Reverser 5′-ACC AAG AGG AGC ACG GAG AGC-3′ | |
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| COL4A3 | Forward 5′-AGCAAGGGTTGTGTCTGTAAAG-3′ |
| Reverse 5′-CAGAAAATCCTGGCAATCCACT-3′ | |
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| DAG1 | Forward 5′-CTCTCTGTGGTTATGGCTCAGT-3′ |
| Reverse 5′-CTGTTGGAATGGTCACTCGAAAT-3′ | |
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| LAMB2 | Forward 5′-CCTGGGAACTTCGACTGGG-3′ |
| Reverse 5′-AAGCACTTCTTTTCGTCCTGC-3′ | |
Figure 1Cluster Analysis of DEGs between PLA and Control. (a) Hierarchical cluster of DEGs between PLA and control. Red is for upregulation and green is for downregulation. (b) Scatter Plot of DEGs. Red plots represent upregulated differentially genes; green plots are for downregulated differentially genes; grey plots represent the genes with no difference. (c) Volcano Plot of DEGs. 2 vertical green lines are upregulated (right) and downregulated (left). Red plots are upregulated differentially genes, green plots are downregulated differentially genes; grey plots represent the genes with no difference. All DEGs were selected for fold change > 1.5, and p-value ≤ 0.05.
Top 10 differentially expressed upregulated genes.
| Track ID | Genes Name | fold change | p value |
|---|---|---|---|
| ENSG00000241945.7_1 | PWP2 | 4.451316597 | 6.27223E-05 |
| ENSG00000197632.8_2 | SERPINB2 | 3.312277915 | 0.035457486 |
| ENSG00000134363.11_1 | FST | 3.186931709 | 0.010070294 |
| ENSG00000178974.9_2 | FBXO34 | 3.008371721 | 0.015287343 |
| ENSG00000137440.4_1 | FGFBP1 | 2.917532326 | 0.002590321 |
| ENSG00000176624.10_1 | MEX3C | 2.878662293 | 0.00125028 |
| ENSG00000175832.12_2 | ETV4 | 2.823278148 | 0.016254865 |
| ENSG00000144063.3_1 | MALL | 2.798830894 | 0.012302349 |
| ENSG00000244405.7_2 | ETV5 | 2.614272424 | 0.016262142 |
| ENSG00000168461.12_2 | RAB31 | 2.499049946 | 0.025288264 |
Top 10 differentially expressed downregulated genes.
| Track ID | Genes Name | fold change | p value |
|---|---|---|---|
| ENSG00000173402.11_2 | DAG1 | 0.111305498 | 0.00286521 |
| ENSG00000265590.9_2 | AP000275.65 | 0.261138897 | 0.004955402 |
| ENSG00000139112.10_2 | GABARAPL1 | 0.332518764 | 0.035665775 |
| ENSG00000173237.4_1 | C11orf86 | 0.351447927 | 0.032322783 |
| ENSG00000173227.13_2 | SYT12 | 0.361878119 | 0.010471093 |
| ENSG00000164825.3_1 | DEFB1 | 0.362656856 | 0.028808651 |
| ENSG00000167705.11_2 | RILP | 0.372534337 | 0.010070846 |
| ENSG00000142178.7_1 | SIK1 | 0.399425757 | 0.007069334 |
| ENSG00000144476.5_2 | ACKR3 | 0.417565995 | 0.039210441 |
| ENSG00000064205.10_1 | WISP2 | 0.426699977 | 0.03010091 |
Figure 2GO analyze DEGs through MF terms, CC terms, and BP terms.
Figure 3KEGG pathway analysis. (a) KEGG analyzed the top 10 significantly pathways of upregulated DEGs. (b) KEGG analysis of all downregulated terms. The bars are arranged from low to high according to the p-value.
Figure 4Validation of 6 differentially expressed genes by qRT-PCR. (A) ACAT2; (B) HMGCS1; (C) SQLE; (D) COL4A3; (E) DAG1; (F) LAMB2. Results were consistent with the RNA-Seq. ∗p< 0.05; ∗∗p<0.01; ∗∗∗p<0.001.