Search

Human and simian immunodeficiency viruses (HIV/SIVs) use CD4 as the primary receptor to enter target cells. Here, we show that the chimpanzee CD4 is highly polymorphic, with nine coding variants present in wild populations, and that this diversity interferes with SIV envelope (Env)-CD4 interactions. Testing the replication fitness of SIVcpz strains in CD4+ T cells from captive chimpanzees, we found that certain viruses were unable to infect cells from certain hosts. These differences were recapitulated in CD4 transfection assays, which revealed a strong association between CD4 genotypes and SIVcpz infection phenotypes. The most striking differences were observed for three substitutions (Q25R, Q40R, and P68T), with P68T generating a second N-linked glycosylation site (N66) in addition to an invariant N32 encoded by all chimpanzee CD4 alleles. In silico modeling and site-directed mutagenesis identified charged residues at the CD4-Env interface and clashes between CD4- and Env-encoded glycans as mechanisms of inhibition. CD4 polymorphisms also reduced Env-mediated cell entry of monkey SIVs, which was dependent on at least one D1 domain glycan. CD4 allele frequencies varied among wild chimpanzees, with high diversity in all but the western subspecies, which appeared to have undergone a selective sweep. One allele was associated with lower SIVcpz prevalence rates in the wild. These results indicate that substitutions in the D1 domain of the chimpanzee CD4 can prevent SIV cell entry. Although some SIVcpz strains have adapted to utilize these variants, CD4 diversity is maintained, protecting chimpanzees against infection with SIVcpz and other SIVs to which they are exposed. [ABSTRACT FROM AUTHOR]

Abstract: Short tandem repeats (STRs), also known as microsatellites, are commonly used to noninvasively genotype wild‐living endangered species, including African apes. Until recently, capillary electrophoresis has been the method of choice to determine the length of polymorphic STR loci. However, this technique is labor intensive, difficult to compare across platforms, and notoriously imprecise. Here we developed a MiSeq‐based approach and tested its performance using previously genotyped fecal samples from long‐term studied chimpanzees in Gombe National Park, Tanzania. Using data from eight microsatellite loci as a reference, we designed a bioinformatics platform that converts raw MiSeq reads into locus‐specific files and automatically calls alleles after filtering stutter sequences and other PCR artifacts. Applying this method to the entire Gombe population, we confirmed previously reported genotypes, but also identified 31 new alleles that had been missed due to sequence differences and size homoplasy. The new genotypes, which increased the allelic diversity and heterozygosity in Gombe by 61% and 8%, respectively, were validated by replicate amplification and pedigree analyses. This demonstrated inheritance and resolved one case of an ambiguous paternity. Using both singleplex and multiplex locus amplification, we also genotyped fecal samples from chimpanzees in the Greater Mahale Ecosystem in Tanzania, demonstrating the utility of the MiSeq‐based approach for genotyping nonhabituated populations and performing comparative analyses across field sites. The new automated high‐throughput analysis platform (available at https://github.com/ShawHahnLab/chiimp) will allow biologists to more accurately and effectively determine wildlife population size and structure, and thus obtain information critical for conservation efforts. [ABSTRACT FROM AUTHOR]