Efficiency of Promoters of Human Genes FAP and CTGF at Organism Level in a Danio rerio Model.
Polina I SelinaIrina V AlekseenkoAnastasia I KurtovaVictor V PleshkanElena E VoronezhskayaIlya V DemidyukSergey V KostrovPublished in: International journal of molecular sciences (2023)
The identification of tissue-specific promoters for gene therapeutic constructs is one of the aims of complex tumor therapy. The genes encoding the fibroblast activation protein ( FAP ) and the connective tissue growth factor ( CTGF ) can function in tumor-associated stromal cells but are practically inactive in normal adult cells. Accordingly, the promoters of these genes can be used to develop vectors targeted to the tumor microenvironment. However, the efficiency of these promoters within genetic constructs remains underexplored, particularly, at the organism level. Here, we used the model of Danio rerio embryos to study the efficiency of transient expression of marker genes under the control of promoters of the FAP , CTGF , and immediate early genes of Human cytomegalovirus (CMV). Within 96 h after the injection of vectors, the CTGF and CMV promoters provided similar equal efficiency of reporter protein accumulation. In the case of the FAP promoter, a high level of reporter protein accumulation was observed only in certain zebrafish individuals that were considered developmentally abnormal. Disturbed embryogenesis was the factor of changes in the exogenous FAP promoter function. The data obtained make a significant contribution to understanding the function of the human CTGF and FAP promoters within vectors to assess their potential in gene therapy.
Keyphrases
- genome wide
- genome wide identification
- gene therapy
- bioinformatics analysis
- endothelial cells
- growth factor
- dna methylation
- transcription factor
- induced pluripotent stem cells
- poor prognosis
- genome wide analysis
- binding protein
- gene expression
- pluripotent stem cells
- copy number
- amino acid
- small molecule
- induced apoptosis
- young adults
- electronic health record
- drug delivery
- bone marrow
- stem cells
- artificial intelligence
- signaling pathway
- big data
- brain injury
- risk assessment
- machine learning
- cell proliferation
- cell therapy