Neuraminidase Inhibitor Susceptibility Testing in Human Influenza Viruses: A Laboratory Surveillance Perspective

Neuraminidase inhibitors (NAIs) are vital in managing seasonal and pandemic influenza infections. NAI susceptibilities of virus isolates (n = 5540) collected during the 2008–2009 influenza season were assessed in the chemiluminescent neuraminidase inhibition (NI) assay. Box-and-whisker plot analyses of log-transformed IC50s were performed for each virus type/subtype and NAI to identify outliers which were characterized based on a statistical cutoff of IC50 >3 interquartile ranges (IQR) from the 75th percentile. Among 1533 seasonal H1N1 viruses tested, 1431 (93.3%) were outliers for oseltamivir; they all harbored the H275Y mutation in the neuraminidase (NA) and were reported as oseltamivir-resistant. Only 15 (0.7%) of pandemic 2009 H1N1 viruses tested (n = 2259) were resistant to oseltamivir. All influenza A(H3N2) (n = 834) and B (n = 914) viruses were sensitive to oseltamivir, except for one A(H3N2) and one B virus, with D151V and D197E (D198E in N2 numbering) mutations in the NA, respectively. All viruses tested were sensitive to zanamivir, except for six seasonal A(H1N1) and several A(H3N2) outliers (n = 22) which exhibited cell culture induced mutations at residue D151 of the NA. A subset of viruses (n = 1058) tested for peramivir were sensitive to the drug, with exception of H275Y variants that exhibited reduced susceptibility to this NAI. This study summarizes baseline susceptibility patterns of seasonal and pandemic influenza viruses, and seeks to contribute towards criteria for defining NAI resistance

Novel bioinformatic methods for emerging pathogens with applications in influenza diagnostics

With the recent and continued growth of publicly available sequence databases, diagnostic applications of sequence-based techniques such as PCR and DNA microarrays are currently of widespread interest. Efforts are underway to greatly expand global surveillance and pandemic preparedness for influenza, driving the need for rapid, low-cost analytical techniques capable of discriminating between several subtypes of the virus. Low-density oligonucleotide microarrays provide several desirable characteristics, but must be designed carefully to ensure that the limited probe set can detect the widest possible range of viruses in addition to discriminating between virus subtypes. A new microarray probe design protocol was developed to specifically address large, highly variable sequence databases, such as those for influenza genes, using a reductionist approach. Databases were sorted into phylogenetic clusters containing similar viruses, then analyzed to find highly conserved regions of sequence within each cluster. Probe oligos were designed from these conserved regions. Several new pieces of software were written to aid in this design process, most notably ConFind, a tool for identifying conserved regions of sequence data from sequence alignments with missing or ambiguous sequence data. FluChip-55, designed using this methodology, allows three common subtypes of influenza to be distinguished. Further enhancements to the design protocol were developed to aid in developing several diagnostic microarrays, including a microarray for detecting antiviral resistance mutations and the MChip, an influenza subtyping microarray based on pattern recognition. Comparisons of influenza M gene sequences and observed microarray intensity data revealed that the MChip probe oligos do not follow the trends observed for hybridizations in solution-like conditions in cases where the oligo does not perfectly match the influenza gene target. A new position-weighting model for mismatched hybridizations on microarray surfaces was proposed to better model the observed trends. In combination with a method for normalizing single-color microarray fluorescence intensities, the position-weighted mismatch model accurately predicted intensities observed for the MChip oligos by considering only the positions of mismatches between an oligo and the corresponding influenza M gene target

Evaluation of MChip with Historic Subtype H1N1 Influenza A Viruses, Including the 1918 “Spanish Flu” Strain▿

The robustness of a recently developed diagnostic microarray for influenza, the MChip, was evaluated with 16 historic subtype H1N1 influenza A viruses (A/H1N1), including A/Brevig Mission/1/1918. The matrix gene segments from all 16 viruses were successfully detected on the array. An artificial neural network trained with temporally related A/H1N1 viruses identified A/Brevig Mission/1/1918 as influenza virus A/H1N1 with 94% probability

Robust Sequence Selection Method Used To Develop the FluChip Diagnostic Microarray for Influenza Virus

DNA microarrays have proven to be powerful tools for gene expression analyses and are becoming increasingly attractive for diagnostic applications, e.g., for virus identification and subtyping. The selection of appropriate sequences for use on a microarray poses a challenge, particularly for highly mutable organisms such as influenza viruses, human immunodeficiency viruses, and hepatitis C viruses. The goal of this work was to develop an efficient method for mining large databases in order to identify regions of conservation in the influenza virus genome. From these regions of conservation, capture and label sequences capable of discriminating between different viral types and subtypes were selected. The salient features of the method were the use of phylogenetic trees for data reduction and the selection of a relatively small number of capture and label sequences capable of identifying a broad spectrum of influenza viruses. A detailed experimental evaluation of the selected sequences is described in a companion paper. The software is freely available under the General Public License at http://www.colorado.edu/chemistry/RGHP/software/