Phylodynamics and molecular evolution of influenza A virus nucleoprotein genes in Taiwan between 1979 and 2009

Genetic variations on 31 and 450 residues of influenza A nucleoprotein affect viral replication and translation

Background

Influenza A viruses cause epidemics/severe pandemics that pose a great global health threat. Among eight viral RNA segments, the multiple functions of nucleoprotein (NP) play important roles in viral replication and transcription.

Methods

To understand how NP contributes to the virus evolution, we analyzed the NP gene of H3N2 viruses in Taiwan and 14,220 NP sequences collected from Influenza Research Database. The identified genetic variations were further analyzed by mini-genome assay, virus growth assay, viral RNA and protein expression as well as ferret model to analyze their impacts on viral replication properties.

Results

The NP genetic analysis by Taiwan and global sequences showed similar evolution pattern that the NP backbones changed through time accompanied with specific residue substitutions from 1999 to 2018. Other than the conserved residues, fifteen sporadic substitutions were observed in which the 31R, 377G and 450S showed higher frequency. We found 31R and 450S decreased polymerase activity while the dominant residues (31 K and 450G) had higher activity. The 31 K and 450G showed better viral translation and replication in vitro and in vivo.

Conclusions

These findings indicated variations identified in evolution have roles in modulating viral replication in vitro and in vivo. This study demonstrates that the interaction between variations of NP during virus evolution deserves future attention.

Surveillance of upper respiratory infections using a new multiplex PCR assay compared to conventional methods during the influenza season in Taiwan

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This is the first study to evaluate the suitability of the FilmArray Respiratory Panel among influenza-like illness (ILI) patients during influenza season in Taiwan.

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Around 60% of ILI cases seen at the sentinel sites were not caused by influenza virus.

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Using this highly sensitive assay with clinical samples is feasible and has led to an increased rate of diagnosis.

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Modern diagnostic systems along with clinician prescription can help to avoid the misuse or overuse of medical resources and improve patient outcomes.

Objectives

To improve diagnosis as part of laboratory surveillance in Taiwan, influenza-like illness (ILI) surveillance was conducted using a new multiplex PCR assay (FilmArray) and the results compared to those of conventional methods The study was performed during the winter months.

Methods

Throat swabs from patients with an ILI presenting to physicians in sentinel practices were collected during the 2016–2017 influenza season.

Results

A total of 52 samples tested positive by FilmArray Respiratory Panel. Forty percent were influenza A virus, and subtype H3N2 virus was the major epidemic strain. However, nearly 60% of ILI cases seen at sentinel sites were caused by non-influenza pathogens. The results of the FilmArray assay and cell culture were identical, and this assay was more sensitive than a rapid influenza diagnostic test. Genetic analyses revealed new influenza A H3N2 variants belonging to a novel subclade 3C.2a2.

Conclusions

The FilmArray assay facilitates urgent testing and laboratory surveillance for common viral and bacterial respiratory pathogens. This study demonstrated the use of a highly sensitive assay using clinical samples that is feasible for application worldwide. This may lead to an increased rate of diagnosis of viral infections and to improved patient outcomes, and in particular to a reduction in the overuse of antibiotics and antivirals.

The effects of sampling strategy on the quality of reconstruction of viral population dynamics using Bayesian skyline family coalescent methods: A simulation study

The ongoing large-scale increase in the total amount of genetic data for viruses and other pathogens has led to a situation in which it is often not possible to include every available sequence in a phylogenetic analysis and expect the procedure to complete in reasonable computational time. This raises questions about how a set of sequences should be selected for analysis, particularly if the data are used to infer more than just the phylogenetic tree itself. The design of sampling strategies for molecular epidemiology has been a neglected field of research. This article describes a large-scale simulation exercise that was undertaken to select an appropriate strategy when using the GMRF skygrid, one of the Bayesian skyline family of coalescent methods, in order to reconstruct past population dynamics. The simulated scenarios were intended to represent sampling for the population of an endemic virus across multiple geographical locations. Large phylogenies were simulated under a coalescent or structured coalescent model and sequences simulated from these trees; the resulting datasets were then downsampled for analyses according to a variety of schemes. Variation in results between different replicates of the same scheme was not insignificant, and as a result, we recommend that where possible analyses are repeated with different datasets in order to establish that elements of a reconstruction are not simply the result of the particular set of samples selected. We show that an individual stochastic choice of sequences can introduce spurious behaviour in the median line of the skygrid plot and that even marginal likelihood estimation can suggest complicated dynamics that were not in fact present. We recommend that the median line should not be used to infer historical events on its own. Sampling sequences with uniform probability with respect to both time and spatial location (deme) never performed worse than sampling with probability proportional to the effective population size at that time and in that location and frequently was superior. As a result, we recommend this approach in the design of future studies. We also confirm that the inclusion of many recent sequences from a single geographical location in an analysis tends to result in a spurious bottleneck effect in the reconstruction and caution against interpreting this as genuine.

Epidemiology of pandemic influenza A/H1N1 virus during 2009-2010 in Taiwan

Outbreak of swine-origin influenza A/H1N1 virus (pdmH1N1) occurred in 2009. Taiwanese authorities implemented nationwide vaccinations with pdmH1N1-specific inactivated vaccine as of November 2009. This study evaluates prevalence, HA phylogenetic relationship, and transmission dynamic of influenza A and B viruses in Taiwan in 2009-2010. Respiratory tract specimens were analyzed for influenza A and B viruses. The pdmH1N1 peaked in November 2009, was predominant from August 2009 to January 2010, then sharply dropped in February 2010. Significant prevalence peaks of influenza B in April-June of 2010 and H3N2 virus in July and August were observed. Highest percentage of pdmH1N1- and H3N2-positive cases appeared among 11-15-year-olds; influenza B-positive cases were dominant among those 6-10 years old. Maximum likelihood phylogenetic trees showed 11 unique clusters of pdmH1N1, seasonal H3N2 influenza A and B viruses, as well as transmission clusters and mixed infections of influenza strains in Taiwan. The 2009 pdmH1N1 virus was predominant in Taiwan from August 2009 to January 2010; seasonal H3N2 influenza A and B viruses exhibited small prevalence peaks after nationwide vaccinations. Phylogenetic evidence indicated transmission clusters and multiple independent clades of co-circulating influenza A and B strains in Taiwan.

PhyloTempo: A Set of R Scripts for Assessing and Visualizing Temporal Clustering in Genealogies Inferred from Serially Sampled Viral Sequences

Serially-sampled nucleotide sequences can be used to infer demographic history of evolving viral populations. The shape of a phylogenetic tree often reflects the interplay between evolutionary and ecological processes. Several approaches exist to analyze the topology and traits of a phylogenetic tree, by means of tree balance, branching patterns and comparative properties. The temporal clustering (TC) statistic is a new topological measure, based on ancestral character reconstruction, which characterizes the temporal structure of a phylogeny. Here, PhyloTempo is the first implementation of the TC in the R language, integrating several other topological measures in a user-friendly graphical framework. The comparison of the TC statistic with other measures provides multifaceted insights on the dynamic processes shaping the evolution of pathogenic viruses. The features and applicability of PhyloTempo were tested on serially-sampled intra-host human and simian immunodeficiency virus population data sets. PhyloTempo is distributed under the GNU general public license at https://sourceforge.net/projects/phylotempo/.