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Bioinformatics-Based Identification of Human B-Cell Receptor (BCR) Stimulation-Associated Genes and Putative Promoters

Authors :
Ethan Deitcher
Kirk Trisler
Branden S. Moriarity
Caleb J. Bostwick
Fleur A. D. Leenen
Steven R. Deitcher
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