| Literature DB >> 34440425 |
Takehito Sugasawa1, Takuro Nakano2, Shin-Ichiro Fujita1, Yuki Matsumoto3, Genki Ishihara3, Kai Aoki1,4, Koki Yanazawa2, Seiko Ono2, Shinsuke Tamai2, Lev Manevich2,5, Haruna Ueda6, Noriyo Ishibashi7, Kenshirou Tamai7, Yasuharu Kanki1, Yasuko Yoshida1,8, Koichi Watanabe9, Tohru Takemasa9, Yasushi Kawakami1, Kazuhiro Takekoshi1.
Abstract
Despite the World Anti-Doping Agency (WADA) ban on gene doping in the context of advancements in gene therapy, the risk of EPO gene-based doping among athletes is still present. To address this and similar risks, gene-doping tests are being developed in doping control laboratories worldwide. In this regard, the present study was performed with two objectives: to develop a robust gene-doping mouse model with the human EPO gene (hEPO) transferred using recombinant adenovirus (rAdV) as a vector and to develop a detection method to identify gene doping by using this model. The rAdV including the hEPO gene was injected intravenously to transfer the gene to the liver. After injection, the mice showed significantly increased whole-blood red blood cell counts and increased expression of hematopoietic marker genes in the spleen, indicating successful development of the gene-doping model. Next, direct and potentially indirect proof of gene doping were evaluated in whole-blood DNA and RNA by using a quantitative PCR assay and RNA sequencing. Proof of doping could be detected in DNA and RNA samples from one drop of whole blood for approximately a month; furthermore, the overall RNA expression profiles showed significant changes, allowing advanced detection of hEPO gene doping.Entities:
Keywords: RNA sequencing; adenoviral vector; athlete; erythropoietin; gene doping; gene therapy; sports
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Year: 2021 PMID: 34440425 PMCID: PMC8392868 DOI: 10.3390/genes12081249
Source DB: PubMed Journal: Genes (Basel) ISSN: 2073-4425 Impact factor: 4.096
Figure 1Establishment of a gene-doping model using rAdV-hEPO. The phenotypes and parameters related to hematopoiesis were assessed in the Con. (n = 12) and rAdV-hEPO (n = 15) groups. (A) An overview of the experiment, (B) a photograph of the liver and spleen of a representative mouse, (C) body weight of the mice, (D) liver and spleen weight, (E) RBC count (104/μL), (F) Hgb level (g/dL), (G) HCT (%), (H) expression of the hEPO gene in the liver, (I) representative images of total EPO and GAPDH on WB analysis of liver specimens, (J) quantification of the band intensity on WB, (K) a representative image of the actual reaction plate of ELISA for the hEPO protein, which was performed as duplicate measurements of 6 samples, (L) results of quantification with ELISA, (M) analysis of the expression levels of genes encoding hematopoietic markers in the liver and spleen, (N) micrographs of GATA1-stained spleen sections evaluated using IHC. N.D.: not detected. * p < 0.05, *** p < 0.001.
Figure 2Direct proof in whole-blood DNA from AdEPO mice. (A) Strategy for designing specific primer-probe pairs for the viral genome. “Pr” indicates a primer-probe pair. (B) Detection of direct proof using the TaqMan qPCR assay performed with whole-blood DNA from the control (n = 12) and AdEPO mice (n = 15). (C–G) Sanger sequence analysis of the pooled amplicon on the TaqMan qPCR assay using five primer-probe pairs; R.S. indicates a reference sequence that completely matches the amplicon over 40 nucleotides on any primer-probe pair. N.D.: not detected. *** p < 0.001.
Figure 3Hematopoietic changes caused by rAdV-hEPO supporting the whole-blood RNA-seq findings. (A) PCA plot showing similarities between samples. (B) Bar plot and pie chart showing the 1128 DEGs included among all detected genes in whole blood and rates of the gene types. (C) Heat map indicating the DEG profile. Values in the rows are z-scores. GSEA showing enriched terms: heme metabolism (D), hematopoiesis mature cell (E), and GATA1 target (F) terms. (G) Relative gene expression levels (Con. = 1.0) showing gene expression in the GATA1 target term in (F). Biological-related functions are described under gene names. The genes were visualized according to the GSEA enrichment results with a “Yes” value. Error bars indicate the standard error of the mean (SEM). (H) Bar plot showing the CTSA to predict cell-type-specific enrichment in DEGs. The gray line represents a significant threshold (p < 0.05). (I) Box plot showing single-cell gene normalized expression (“NX”) of DEGs in each cell type. Single-cell gene expression levels of DEGs were classified by cell-type-specific definitions by TissueEnrich for each cell-type. (J) Relative gene expression levels (Con. = 1.0) showing erythroid cell-enriched gene expressions in DEGs. Abbreviations: long non-coding RNA (lncRNA), small nucleolar RNA (snoRNA), small nuclear RNA (snRNA), and immunoglobulin constant germline gene (IGC gene).
Figure 4Single RNAs identified as indirect proof by bioinformatics screening. (A) Venn diagram showing the number of DEGs with filtering for high expression and high fold expression. (B) Scatter plot showing nine overlapping genes with filtering. (C) Relative gene expressions (Con. = 1.0) showing nine overlapping genes. (D) Genome browser indicating the read mapping results of the top four genes. (E) Confirmation of the top four genes as indirect proof by using the TB Green qPCR assay. *** p < 0.001.
Figure 5Detection of direct and indirect proof for a long time period. To detect direct and indirect proof, small amounts of whole blood were harvested from the tail tips of mice (n = 12) until 30 days after the injection. From approximately 50 μL of whole blood, DNA/RNA was extracted, and the TaqMan or TB Green qPCR assays were performed to detect direct and indirect proof. (A) Overview of the experiments in this section, (B–F) continuous detection of direct proof for 30 days by five primer-probe pairs using the TaqMan qPCR assay; “Pr” refers to a primer-probe, (G–J): detection of changes in gene expression as indirect proof using the TB Green qPCR assay. N.D.: not detected. * p < 0.05, ** p < 0.01 and *** p < 0.001 vs. pre-value.