Comparison of methods to detect HIV dual infection.
Current methods to detect intraclade HIV dual infection are poorly suited for determining its prevalence in large cohorts. To investigate the potential of ultra-deep sequencing to screen for dual infection, we compared it to bulk sequence-based synonymous mixture index and the current standard of single genome sequencing. The synonymous mixture index identified samples likely to harbor dual infection, while ultra-deep sequencing captured more intra-host viral diversity than single genome sequencing at approximately 40% of the cost and 20% of the laboratory and analysis time. The synonymous mixture index and ultra-deep sequencing are promising methods for rapid and cost-effective systematic identification of HIV dual infection.
University of California, San Diego, La Jolla, California 92093-0679, USA. mpacold@ucsd.edu
Mary
M
Pacold
Davey
D
Smith
Susan
S
Little
Pok Man
PM
Cheng
Parris
P
Jordan
Caroline
C
Ignacio
Douglas
D
Richman
Sergei Kosakovsky
SK
Pond
D000328:Adult; D016000:Cluster Analysis; D014644:Genetic Variation; D006678:HIV / Q000145:classification* / Q000235:genetics / Q000302:isolation & purification*; D015658:HIV Infections / Q000821:virology*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D008297:Male; D008875:Middle Aged; D008969:Molecular Sequence Data; D017422:Sequence Analysis, DNA; D017385:Sequence Homology; D014773:Virology / Q000379:methods*