Selection of functional mutations in the U5-IR stem and loop regions of the Rous sarcoma virus genome

Identifying functionally important mutations from phenotypically diverse sequence data

Here we present a simple statistical method to determine the phenotypic contribution of a single mutation from libraries of mutants with diverse phenotypes in which each mutant contains a multitude of mutations. The central premise of this method is that, given M phenotypic classes, mutations that do not affect the phenotype should partition among the M classes according to a multinomial distribution. Deviations from this distribution are indicative of a link between specific mutations and phenotypes. We suggest that this method will aid the engineering of functional nucleic acids, proteins, and other biomolecules by uncovering target sites for rational mutagenesis. As a proof of the principle, we show how the method can be used to deduce the individual effects of mutations in a set of 69 P(L)-lambda promoter variants. Each of these promoters was generated by error-prone PCR and incorporated numerous mutations. The activity of the promoters was assayed using flow cytometry to measure the fluorescence of a green fluorescent protein reporter gene. Our analysis of the sequences of these mutants revealed seven positions having a statistically significant correlation with promoter activity. Using site-directed mutagenesis, we constructed point mutations for several sites, both statistically significant and insignificant, and combinations of these sites. Our results show that the statistical method correctly elucidated the phenotypic manifestations of these mutations. We suggest that this method may be useful for expediting directed evolution experiments by allowing both desired and undesired mutations to be identified and incorporated between rounds of mutagenesis.

Quantifying antagonistic epistasis in a multifunctional RNA secondary structure of the Rous sarcoma virus

Recent studies have suggested that antagonistic epistasis (i.e. mutations having smaller effects in combination than alone) may be common among RNA viruses, in contrast to other biological systems. Here, by re-analysing previously published data from a random viral library, selection and epistasis coefficients were estimated in the U5-IR stem and loop of theRous sarcoma virus, a region that adopts a conserved secondary structure and is involved in various essential steps of viral infection. The estimated mutational fitness effects are extremely high and genetic interactions are antagonistic on average. This pattern might be representative of RNA virus genomes, which show high compaction and frequent secondary structures. The implications for RNA virus adaptability are explored.

Identification of amino acids in HIV-1 and avian sarcoma virus integrase subsites required for specific recognition of the long terminal repeat Ends

A tetramer model for HIV-1 integrase (IN) with DNA representing 20 bp of the U3 and U5 long terminal repeats (LTR) termini was assembled using structural and biochemical data and molecular dynamics simulations. It predicted amino acid residues on the enzyme surface that can interact with the LTR termini. A separate structural alignment of HIV-1, simian sarcoma virus (SIV), and avian sarcoma virus (ASV) INs predicted which of these residues were unique. To determine whether these residues were responsible for specific recognition of the LTR termini, the amino acids from ASV IN were substituted into the structurally equivalent positions of HIV-1 IN, and the ability of the chimeras to 3 ' process U5 HIV-1 or ASV duplex oligos was determined. This analysis demonstrated that there are multiple amino acid contacts with the LTRs and that substitution of ASV IN amino acids at many of the analogous positions in HIV-1 IN conferred partial ability to cleave ASV substrates with a concomitant loss in the ability to cleave the homologous HIV-1 substrate. HIV-1 IN residues that changed specificity include Val(72), Ser(153), Lys(160)-Ile(161), Gly(163)-Val(165), and His(171)-Leu(172). Because a chimera that combines several of these substitutions showed a specificity of cleavage of the U5 ASV substrate closer to wild type ASV IN compared with chimeras with individual amino acid substitutions, it appears that the sum of the IN interactions with the LTRs determines the specificity. Finally, residues Ser(153) and Val(72) in HIV-1 IN are among those that change in enzymes that develop resistance to naphthyridine carboxamide- and diketo acid-related inhibitors in cells. Thus, amino acid residues involved in recognition of the LTRs are among these positions that change in development of drug resistance.