Bioinformatic Design of Dendritic Cell-Specific Synthetic Promoters.
ACS Synth Biol
; 11(4): 1613-1626, 2022 04 15.
Article
em En
| MEDLINE
| ID: mdl-35389220
Next-generation DNA vectors for cancer immunotherapies and vaccine development require promoters eliciting predefined transcriptional activities specific to target cell types, such as dendritic cells (DCs), which underpin immune response. In this study, we describe the de novo design of DC-specific synthetic promoters via in silico assembly of cis-transcription factor response elements (TFREs) that harness the DC transcriptional landscape. Using computational genome mining approaches, candidate TFREs were identified within promoter sequences of highly expressed DC-specific genes or those exhibiting an upregulated expression during DC maturation. Individual TFREs were then screened in vitro in a target DC line and off-target cell lines derived from skeletal muscle, fibroblast, epithelial, and endothelial cells using homotypic (TFRE repeats in series) reporter constructs. Based on these data, a library of heterotypic promoter assemblies varying in the TFRE composition, copy number, and sequential arrangement was constructed and tested in vitro to identify DC-specific promoters. Analysis of the transcriptional activity and specificity of these promoters unraveled underlying design rules, primarily TFRE composition, which govern the DC-specific synthetic promoter activity. Using these design rules, a second library of exclusively DC-specific promoters exhibiting varied transcriptional activities was generated. All DC-specific synthetic promoter assemblies exhibited >5-fold activity in the target DC line relative to off-target cell lines, with transcriptional activities ranging from 8 to 67% of the nonspecific human cytomegalovirus (hCMV-IE1) promoter. We show that bioinformatic analysis of a mammalian cell transcriptional landscape is an effective strategy for de novo design of cell-type-specific synthetic promoters with precisely controllable transcriptional activities.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
/
Células Endoteliais
Tipo de estudo:
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
ACS Synth Biol
Ano de publicação:
2022
Tipo de documento:
Article