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Bioinformatics-Based Identification of Human B-Cell Receptor (BCR) Stimulation-Associated Genes and Putative Promoters
- Source :
- BioMedInformatics, Vol 4, Iss 2, Pp 1384-1395 (2024)
- Publication Year :
- 2024
- Publisher :
- MDPI AG, 2024.
-
Abstract
- Genome engineered B-cells are being developed for chronic, systemic in vivo protein replacement therapies and for localized, tumor cell-actuated anticancer therapeutics. For continuous systemic engineered protein production, expression may be driven by constitutively active promoters. For actuated payload delivery, B-cell conditional expression could be based on transgene alternate splicing or heterologous promotors activated after engineered B-cell receptor (BCR) stimulation. This study used a bioinformatics-based approach to identify putative BCR-stimulated gene promoters. Gene expression data at four timepoints (60, 90, 210, and 390 min) following in vitro BCR stimulation using an anti-IgM antibody in B-cells from six healthy donors were analyzed using R (4.2.2). Differentially upregulated genes were stringently defined as those with adjusted p-value < 0.01 and a log2FoldChange > 1.5. The most upregulated and statistically significant genes were further analyzed to find those with the lowest unstimulated B-cell expression. Of the 46 significantly upregulated genes at 390 min post-BCR stimulation, 6 had average unstimulated expression below the median unstimulated expression at 390 min for all 54,675 gene probes. This bioinformatics-based identification of 6 relatively quiescent genes at baseline that are upregulated by BCR-stimulation (“on-switch”) provides a set of promising promotors for inclusion in future transgene designs and engineered B-cell therapeutics development.
Details
- Language :
- English
- ISSN :
- 26737426
- Volume :
- 4
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- BioMedInformatics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.767cf045505c4fcfb611e91e3b010a26
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/biomedinformatics4020076