A recoding method to improve the humoral immune response to an HIV DNA vaccine.

Publication Type:

Journal Article


PloS one, Volume 3, Issue 9, p.e3214 (2008)


2008, Acquired Immunodeficiency Syndrome, AIDS Vaccines, Algorithms, Amino Acid Motifs, Animals, Antibody Formation, Codon, Computational Biology, DNA, Complementary, Gene Expression Regulation, Gene Products, gag, Humans, MICE, Monte Carlo Method, Public Health Sciences Division


This manuscript describes a novel strategy to improve HIV DNA vaccine design. Employing a new information theory based bioinformatic algorithm, we identify a set of nucleotide motifs which are common in the coding region of HIV, but are under-represented in genes that are highly expressed in the human genome. We hypothesize that these motifs contribute to the poor protein expression of gag, pol, and env genes from the c-DNAs of HIV clinical isolates. Using this approach and beginning with a codon optimized consensus gag gene, we recode the nucleotide sequence so as to remove these motifs without modifying the amino acid sequence. Transfecting the recoded DNA sequence into a human kidney cell line results in doubling the gag protein expression level compared to the codon optimized version. We then turn both sequences into DNA vaccines and compare induced antibody response in a murine model. Our sequence, which has the motifs removed, induces a five-fold increase in gag antibody response compared to the codon optimized vaccine.