Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

Abstract

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.

A Mechanism for Priming and Realignment during Influenza A Virus Replication

“…3 , viral RNA synthesis by the V273A mutant, but also by the S269A mutant, was impaired compared to the wild type and was found to have differential effects on cRNA and mRNA synthesis. These observations corroborate previously reported RNP reconstitutions with the same mutants ( 20 ) and experiments showing that a V273A, V273L, or V273D mutation reduces the fitness of A/WSN/33 (H1N1) viruses by >90% ( 21 ). Based on these observations, we suggest that an inefficient realignment of the nascent vRNA results in the synthesis of truncated vRNA products that may not be bound by the IAV RdRp.…”

Effects of Mutations on Replicative Fitness and Major Histocompatibility Complex Class I Binding Affinity Are Among the Determinants Underlying Cytotoxic-T-Lymphocyte Escape of HIV-1 Gag Epitopes

“…We have previously demonstrated the feasibility of using quantitative high-throughput genetics to systematically evaluate the fitness effects of point mutations in HIV-1, HCV and influenza virus ( 25 – 27 , 29 ). In this study, we generated plasmid libraries of single nucleotide mutations in the Gag region of HIV-1 molecular clone NL4-3 using error-prone PCR mutagenesis.…”

“…Several T cell vaccine strategies focus on using evolutionarily conserved regions in HIV genome as immunogens, with the promise that escape mutations in the conserved regions will incur higher fitness cost ( 46 – 50 ). However, many studies have documented that conserved regions are not necessarily essential for viral fitness, although there is some correlation ( 27 , 29 ). Our systematic investigations of single amino acid mutations in Gag will more precisely pinpoint the sequences that are essential for viral replication and that are less likely to escape CTL, thereby aiding the rational design of immunogens for vaccine development.…”

Interaction of virus populations with their hosts

“…Coevolution of amino acids at or around important functional domains may contribute to functional stability (Gloor et al, 2005). Homologous structure analyses can be applied to identify functional residues in proteins (Du et al, 2016). Intramolecular coevolution can be measured for amino acid pairs by the probability of their occurrence at some defined positions, also termed mutual information criterion (MIC) (Korber et al, 1993).…”