Research Article: The Mutational Robustness of Influenza A Virus

Date Published: August 29, 2016

Publisher: Public Library of Science

Author(s): Elisa Visher, Shawn E. Whitefield, John T. McCrone, William Fitzsimmons, Adam S. Lauring, Neil M. Ferguson.

http://doi.org/10.1371/journal.ppat.1005856

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.

Partial Text

The predictable burden of seasonal influenza and the unpredictability of the next pandemic are attributable in large part to the rapid evolution of influenza virus [1–4]. Like other RNA viruses, influenza viruses replicate with extremely low fidelity, with a mutation rate of roughly 2 x 10−5 substitutions per nucleotide copied per cellular infection [5–7]. Influenza viruses also undergo reassortment of their genomic segments, a combinatorial exchange of genetic material analogous to recombination in other RNA viruses [8,9]. Together, low replicative fidelity and frequent reassortment allow influenza virus populations to generate significant diversity. This capacity may allow influenza viruses to maintain, or to quickly generate, the requisite mutations that mediate cross species transmission, escape from neutralizing antibody, or drug resistance [10].

Our primary goal was to determine the distribution of mutational fitness effects across the influenza A genome. We generated all single nucleotide mutations in the commonly used laboratory strain, A/WSN/33/H1N1, hereafter referred to as WSN33 or wild type (WT) [41]. In WSN33, the 8 genomic segments range in size from 0.9 to 2.3 kb. We planned to make 149 mutants and grouped them into two libraries–“genome-wide” and “comparison”–of pre-specified size and composition. Of the 149 total mutations we attempted (S1 Table), we successfully generated 128 (86%). For our “genome-wide” library, we reasoned that in order to achieve an unbiased distribution of mutations throughout the genome, our library should contain a number of mutations on each segment that is proportional to the size of each segment—PB2 17.2%, PB1 17.2%, PA 16.4%, HA 13.1%, NP 11.5%, NA 10.4%, M 7.5%, NS 6.5%, of the total genome respectively. We used a custom R script to choose randomly the nucleotide position and substitution type in accordance with this distribution. For our unbiased genome-wide analysis (n = 95), we generated 14 (14.7%) PB2, 16 (16.8%) PB1, 16 (16.8%) PA, 14 (14.7%) HA, 12 (12.6%) NP, 10 (10.5%) NA, 8 (8.4%) M and 5 (5.3%) NS mutations. Though we failed to generate 14% of attempted mutations, this did not significantly alter the distribution of the mutations across the eight segments (S1A Fig).

We report the first genome-wide study of the mutational fitness effects of single nucleotide mutations in influenza A virus. Unlike other studies of mutational tolerance in influenza, we took great pains to define the lethal fraction, a key parameter in the distribution of MFE. We ensured the relative clonality of nearly all of our stocks by next generation sequencing and used a highly quantitative assay for fitness measurements. Both the lethal fraction and the overall distribution of MFE of influenza A are quite similar to what has been found for ssDNA and other RNA viruses. Consistent with what has been assumed, but to our knowledge never shown, the surface proteins of influenza virus appear to be slightly more tolerant of point mutation than the internal viral proteins. This finding did not achieve statistical significance. These results have important implications for quantitative models of influenza evolution and our general understanding of the mutational robustness of RNA viruses.

 

Source:

http://doi.org/10.1371/journal.ppat.1005856

 

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