The Mutational Robustness of Influenza A Virus

Abstract

A virus' mutational robustness is described in terms of the strength and distribution of the mutational fitness effects, or MFE. The distribution of MFE is central to many questions in evolutionary theory and is a key parameter in models of molecular evolution. Here we define the mutational fitness effects in influenza A virus by generating 128 viruses, each with a single nucleotide mutation. In contrast to mutational scanning approaches, this strategy allowed us to unambiguously assign fitness values to individual mutations. The presence of each desired mutation and the absence of additional mutations were verified by next generation sequencing of each stock. A mutation was considered lethal only after we failed to rescue virus in three independent transfections. We measured the fitness of each viable mutant relative to the wild type by quantitative RT-PCR following direct competition on A549 cells. We found that 31.6% of the mutations in the genome-wide dataset were lethal and that the lethal fraction did not differ appreciably between the HA- and NA-encoding segments and the rest of the genome. Of the viable mutants, the fitness mean and standard deviation were 0.80 and 0.22 in the genome-wide dataset and best modeled as a beta distribution. The fitness impact of mutation was marginally lower in the segments coding for HA and NA (0.88 ± 0.16) than in the other 6 segments (0.78 ± 0.24), and their respective beta distributions had slightly different shape parameters. The results for influenza A virus are remarkably similar to our own analysis of CirSeq-derived fitness values from poliovirus and previously published data from other small, single stranded DNA and RNA viruses. These data suggest that genome size, and not nucleic acid type or mode of replication, is the main determinant of viral mutational fitness effects.

Fig 1. Direct competition assay for relative fitness.

(A) Equal infectious units of a barcoded version of the WT were competed against WT at an moi of 0.01, and the amount of each virus at each passage was compared to the input by RT-qPCR as described in the methods. The slope of the regression of the difference in the log10 change in ratio for each virus over time is the fitness. The assay was performed in triplicate and the slopes of the three lines are 0.007, 0.129, and 0.007, which corresponds to a fitness of 1.02 ± 0.008 for the barcoded virus relative to WT. (B) Sample data for two single nucleotide mutants. Each was competed against the barcoded WT as in (A) and relative fitness measured as calculated in the methods. One replicate each of NA-18 (circles, fitness = 0.64) and HA-40 (squares, fitness = 1.02) is shown. Note that we fit our regressions through passages 1–4 and excluded P0 as slight deviations from a 1:1 ratio of the two viruses in the inoculum can skew the slope when fit through this data point.

Fig 2. Location and fitness for all mutations.

Each mutation in Tables 1 and 3 is shown in its reading frame(s) with substitution type (nonsynonymous, synonymous, or noncoding) and fitness (see legend).

Fig 3. Histograms and cumulative distribution functions of influenza A virus mutational fitness effects.

Data are shown for all single nucleotide mutants (A, n = 128), the randomly selected genome-wide dataset (B, n = 95), the HA and NA dataset (C, n = 57), and the “internal” dataset (D, n = 71). Relative fitness values, bin width 0.1, are shown on the x-axis, and number of mutations in each histogram bar (left) and percent in cumulative distribution (right) are shown on the y-axes. The cumulative distribution functions show only the viable mutations (fitness > 0).

Fig 4. Fitness impact of mutations on HA.

Mutations were placed onto a structural model of the hemagglutinin protein (PBD 1RVX). Shown are mutations on the head and stem regions, HA1 and HA2. Non-coding mutations (HA-8) and mutations on the signal peptide (HA-11), splice site (HA-1), and transmembrane domain (HA-40, HA-15, HA-10, HA-20) are not shown. Mutations are color coded as follows according to their relative fitness: lethal mutations are red, 0.6–0.8 are orange, 0.8–1.0 are yellow, and 1.0–1.2 are green. We found no HA mutations with a fitness between 0–0.6.

Fig 5. Correlation of fitness values with site entropy and preference.

(A) Fitness of nonsynonymous HA mutants vs. site entropy (top) and fitness of all HA mutants vs. site preference (bottom) as reported in [46]. Unscaled values are shown. Correlations were similar for scaled values, see S3 Table. (B) Fitness of nonsynonymous NP mutants vs. site entropy (top) and fitness of all NP mutants vs. site preference (bottom) as reported for PR8 in [55]. (C) Fitness of nonsynonymous NP mutants vs. site entropy (top) and fitness of all NP mutants vs. site preference (bottom) as reported for A/Aichi/1968 (H3N2) in [55]. Note that scale in (A) for site preference is different as there were synonymous mutants in this dataset, but not in the NP datasets.