VirologyIncidence of matrix genes mutations affecting PCR tests among influenza H3N2 clades circulating during the 2014/15 season
Introduction
The World Health Organization (WHO) Global Influenza Surveillance Network has defined seven genetic groups for influenza A(H3N2) viruses based on HA gene sequences, with more recent isolates being from the genetic group 3C. This group has three subdivisions: 3C.1, 3C.2, and 3C.3, which are antigenically similar (Broberg et al., 2015). In 2014, three new genetic subgroups with unique HA mutations emerged: 3C.2a, 3C.3a, and 3C.3b. Antigenic drift was demonstrated in subgroups 3C.2a and 3C.3a (European Centre for Disease Prevention and Control, 2015). Indeed, the 2014/15 influenza season in the United States of America (USA) was characterized by widespread circulation of multiple clades of H3N2 viruses, with the majority being antigenically different from the H3N2 vaccine component (clade 3C.1 A/Texas/50/2012), leading to reduced vaccine effectiveness (Appiah et al., 2015, Flannery et al., 2015).
Besides affecting vaccine efficacy, influenza evolution has been associated with changes in diagnostic test sensitivity, particularly with rapid immunoassays (RIDT) (Busson et al., 2014, Centers for Disease Control and Prevention (CDC), 2009, Drexler et al., 2009, Ginocchio et al., 2009). Cell culture reliability has also been influenced at times, with changes in cell-line permissiveness (Frank et al., 1979, Memoli et al., 2009). Nucleic acid amplification tests for influenza A are designed to detect highly conserved genomic targets, generally in the matrix protein 1 (M1) gene (Ward et al., 2004; World Health Organization (WHO), 2009, 2011). However, mutations affecting the performance of commercial assays have long been observed with individual A(H1N1)pdm09 isolates (Binnicker et al., 2013, Dhiman et al., 2010, Zheng et al., 2010).
More recently, M1 mutations affecting the performance of polymerase chain reaction (PCR) tests with populations of H3N2 viruses have been reported in Taiwan, Belgium, Germany, and the USA (Huzly et al., 2016, Overmeire et al., 2016, Stellrecht et al., 2017, Yang et al., 2014), with a C163T mutation being the most problematic (Overmeire et al., 2016, Stellrecht et al., 2017). Although exact primer and probe sequences for most commercial assays are proprietary, it is presumed that they follow WHO recommendations. It was reported that C163T mutations in 3C.2a isolates from Belgium resulted in a mismatch with the probe from one commercial assay and subsequent false-negative test results (Overmeire et al., 2016). Previously, my laboratory compared the limit of detection of five commercial assays among an assortment of viral isolates from different clades and demonstrated that assays having the lowest clinical sensitivity with specimens from the 2014/15 season also had the lowest analytical sensitivity with isolates harboring the C163T point mutation (Stellrecht et al., 2017).
The manufacturer of one commercial kit modified their package insert in 2015 to indicate assay limitations with A/New York/1/2015 (H3N2), but they reported that this issue was restricted to viruses circulating in a discrete region of New York State. Indeed, it was unknown how common the M1 C163T mutation was among influenza isolates or even how conserved the M1 target region was among circulating viral clades during the 2014/15 season. It was also unknown if particular M1 mutations were associated with the various co-circulating subclades. Hence, H3N2 isolates from three distinct locations across the world were investigated to assess the incidence of mutations within the M1 target region during the 2014/15 respiratory virus season. From these data, mutation patterns in the target region were determined, and attempts were made to associate these patterns with H3N2 clades.
Section snippets
HA and M1 sequences
Sequence data were obtained from the Global Initiative on Sharing Avian Influenza Database (GISAID) EpiFlu. This dataset is comprised of influenza sequences uniquely submitted from contributors such as the Office International des Epizooties; National Reference Laboratories; and all the WHO Collaborating Centers for Surveillance, Epidemiology, and Control of Influenza for the semiannual vaccine strain selection (Shu and McCauley, 2017). Included were all unique human H3N2 isolates for which
Influenza H3N2 clade determination
In an analysis of the HA genes, all viruses except the vH3 (not shown) clustered into the 3C subgroups (Fig. 1, Table 1). The predominant clade in this sample set was 3C.2a at 75%. 3C.3b was the second most prevalent clade at 16%. However, the clade distribution was skewed by overrepresentation of the population with USA data. Each location demonstrated different clade rates. Isolates from Australia were equally distributed over four clades, with the rates for 3C.2a, 3C.3, and 3C.3b ranging
Discussion
During the 2014/15 northern hemisphere’s influenza season, A/H3N2 viruses predominated and accounted for 83% of the typed isolates in Europe and 99% in Canada and the USA (World Health Organization (WHO), 2015). This season was remarkable due to the number of co-circulating clades of virus. Since the majority of isolates were antigenically different from the H3N2 vaccine component (clade 3C.1 A/Texas/50/2012), leading to reduced vaccine effectiveness (Appiah et al., 2015, Flannery et al., 2015
Conclusions
The prevalence of M1 mutations affecting sensitivity of PCR tests was widespread with a higher incidence in the USA. Often, population inferences of M1 mutations can be made based on viral clade. However, caution is warranted, and continual analyses are necessary as gene segment reassortment can quickly affect the predictive capacity.
The following are the supplementary data related to this article.
Acknowledgments
I acknowledge the authors and the originating and submitting laboratories of the sequences from GISAID's EpiFlu Database from which the clade and M1 gene mutation prevalences are based. All submitters of data may be contacted directly via the GISAID Web site: www.gisaid.org. I also thank Ms. Eileen Graffunder from the Epidemiology Department at Albany Medical Center for her assistance with the statistical analyses and Mr. Jesse Cimino for his editorial assistance.
Competing interests
The author’s institution received several research grants from Abbott Molecular, BD, BioMerieux, and Roche Diagnostics. Dr. Stellrecht received reimbursement of travel expenses for attending meetings and conferences from Abbott Molecular, Quidel, and Roche Diagnostics.
Funding
None.
Ethical approval
Not applicable.
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