Viruses and their hosts are constantly engaged in a battle over an evolutionary timescale. To avoid infection, host cells develop new machinery to inhibit viral invasion, and in response, the virus develops ways to subvert this host machinery and infect the cell. This “evolutionary arms race” happens across many viruses, including HIV-1, the virus that targets the immune system and results in lifelong infection.
One of the most well-characterized arms races involves HIV-1’s Vif protein and the human antiviral protein, APOBEC3G or A3G. A3G is a cytidine deaminase that acts on single-stranded viral DNA replication intermediates. HIV infections are lifelong because the virus can integrate viral genes into the human genome using the enzyme reverse transcriptase. A3G can interrupt this process by being incorporated into budding virions. When these virions infect another cell, A3G localizes to the site of viral DNA synthesis and introduces missense mutations that impair viral replication and block infection.
To counteract A3G, HIV-1 encodes Vif, a protein that recruits other host proteins to degrade A3G, before it can be packaged into new virions. Vif sequences from people living with HIV are highly diverse, but how this variation impacts viral evolution and pathogenesis in people was unclear. To address this, Dr. Caroline Langley, a recent PhD graduate from the Emerman lab, used a deep mutational scanning approach across two distinct HIV strains to parse out the impacts of distinct Vif mutations on viral fitness.
To start, Langley created comprehensive deep mutational scanning libraries for Vif amino acid positions 12 to 115, a region involved in interactions with A3G. Because A3G is mutagenic, the team needed a way to distinguish those naturally generated changes from the mutations they had deliberately engineered. Their carefully constructed library introduced alternative amino acids using codon substitutions that ensured all mutations were equally represented while reducing the frequency of A3G-mediated mutations. After developing this library, they cloned it into an HIV-1 backbone and transfected the virus into human cells to produce pools of virions carrying their mutations of interest.
With the HIV-1 virions in hand, the team next moved to testing the effect of each mutation on HIV-1 fitness. They infected a human T-cell line with the virions. Three days later, they harvested the newly produced virions and used them to infect another batch of T-cells. After another three days, they harvested the virions again and sequenced the Vif genes that passed the rigorous selection process.
With this strategy, viruses with nonfunctional Vif protein are depleted from the pool because they fail to counteract human A3G. However, viruses with functional Vif persist because they can restrict A3G. By measuring which mutations became more or less common over time, Langley and her team could determine the relative fitness of each mutation.
They used this deep mutational scanning and selection approach to first quantify fitness of Vif variants in the HIV-1LAI strain. Other groups had previously solved a high-resolution structure for Vif bound to A3G, RNA, and the protein degradation complex it recruits in the HIV-1LAI strain. With this structural information, the team could connect the effects of any particular mutation to specific parts of the Vif that may be impacting viral fitness.
They found that Vif is largely intolerant to mutations. Across the amino acids tested, the median enrichment score was -1.47, highlighting that most mutations reduced viral fitness. Five sites were especially sensitive to mutations across replicates. Of these, four sites directly contact the protein degradation complex recruited by Vif, and one of them falls in a motif required for A3G neutralization.
The screen also revealed residues that appear to be more mutationally tolerant. Of these, they were particularly interested in Histidine 42 (H42). H42 is critical for binding RNA and bridging Vif and A3G, and it is perfectly conserved across currently circulating HIV-1strains and the strain of SIV that evolved into the primary human HIV strain. The group was surprised that H42 appeared to be so mutationally tolerant in their screen, so they measured A3G packaging into virions containing each H42 substitution. Substitutions that reduced viral fitness in the deep mutational scan dataset had higher levels of A3G packaging relative to their wild type counterparts, but variants that were neutral or positively enriched in the scan had no difference in A3G packaging relative to wild type virions. These data show that H42 is tolerant to several missense mutations despite its evolutionary conservation, and that the conservation is not strictly due its role in A3G antagonism.
Next, the group repeated the deep mutational scanning approach with HIV-11203. They found five sites that were highly constrained in this HIV strain. Although none of these sites overlapped with the constrained sites in HIV-1LAI, they were still present in similar structural regions of Vif. They also detected 18 mutationally tolerant sites in HIV-11203, four of which overlapped with the mutationally tolerant sites in HIV-1LAI. Langley next identified 11 residues whose tolerance to mutations differed between HIV-11203 and HIV-1LAI. Of these, nine residues encoded identical amino acids in both HIV-1 strains, suggesting that differences in constraint could be due to strain-specific Vif optimization rather than differences in primary sequences.
Position 83 was identified as the only A3G-interacting residue with different mutational tolerance between HIV-11203 and HIV-1LAI. Langley and her team were especially interested in this residue because an ancient mutation from tyrosine to histidine at this site enabled transmission of SIV into humans, ultimately giving rise to HIV-1. Additionally, different HIV-1 subtypes have different amino acid frequencies at this site. Follow up work with HIV-11203 and HIV-1LAI showed that position 83 mutations enhanced A3G antagonism in one genetic background but not the other, again demonstrating that there has been strain-specific optimization for Vif over time. This is a powerful example of how Vif’s evolutionary trajectory is constrained by its specific genetic context, and, importantly, these insights could not have been predicted by the published structural data, highlighting the power of deep mutational scanning in understanding viral protein evolution.
Overall, the team’s work revealed mutational tolerance at unexpected sites in the HIV-1 Vif protein even though many of these sites are highly conserved across evolution and required for binding to A3G, RNA, and the proteins that mediate degradation. These findings challenge the assumption that conserved residues are always functionally rigid and suggest an evolved structural robustness in Vif that allow it to maintain its primary function while branching into other pathways. In the future, the group hopes that others in the field will use deep mutational scanning to understand viral selection pressures across evolutionary timescales.
This work was supported by funding from the National Institutes of Health and Howard Hughes Medical Institute.
Fred Hutch/University of Washington/Seattle Children’s Cancer Consortium Member Dr. Harmit Malik contributed to this research.
Langley CL, Lilly M, Malik HS, Emerman M. Strain-specific epistasis shapes fitness landscapes of APOBEC3G antagonism by HIV-1 Vif proteins. Sci Adv. 2026 Jul 24;12(30):eaed4872. doi: 10.1126/sciadv.aed4872.
Kelsey Woodruff is a PhD candidate in the Termini Lab at Fred Hutch Cancer Center. She studies how acute myeloid leukemia cells remodel the sugars on their membranes to reprogram cancer cell signaling. Originally from Indiana, she holds a bachelor's degree in Biochemistry from Ball State University. Outside of lab, you can find her crocheting and enjoying the Seattle summers.