A whole-genome bioinformatics approach to selection of antigens for systematic antibody generation.
Here, we present an antigen selection strategy based on a whole-genome bioinformatics approach, which is facilitated by an interactive visualization tool displaying protein features from both public resources and in-house generated data. The web-based bioinformatics platform has been designed for selection of multiple, non-overlapping recombinant protein epitope signature tags by display of predicted information relevant for antigens, including domain- and epitope sized sequence similarities to other proteins, transmembrane regions and signal peptides. The visualization tool also displays shared and exclusive protein regions for genes with multiple splice variants. A genome-wide analysis demonstrates that antigens for approximately 80% of the human protein-coding genes can be selected with this strategy.
Berglund
Lisa
L
School of Biotechnology, Royal Institute of Technology (KTH), AlbaNova University Center, Stockholm, Sweden.
Björling
Erik
E
Jonasson
Kalle
K
Rockberg
Johan
J
Fagerberg
Linn
L
Al-Khalili Szigyarto
Cristina
C
Sivertsson
Asa
A
Uhlén
Mathias
M
D000595:Amino Acid Sequence; D000917:Antibody Formation / Q000235:genetics*; D000941:Antigens / Q000235:genetics / Q000276:immunology*; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D000939:Epitopes / Q000235:genetics / Q000276:immunology; D015894:Genome, Human / Q000276:immunology*; D006801:Humans; D020407:Internet; D008969:Molecular Sequence Data; D012984:Software
D000941:Antigens; D000939:Epitopes