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Abstract 


The continual emergence of novel influenza A strains from non-human hosts requires constant vigilance and the need for ongoing research to identify strains that may pose a human public health risk. Since 1999, canine H3 influenza A viruses (CIVs) have caused many thousands or millions of respiratory infections in dogs in the United States. While no human infections with CIVs have been reported to date, these viruses could pose a zoonotic risk. In these studies, the National Institutes of Allergy and Infectious Diseases (NIAID) Centers of Excellence for Influenza Research and Surveillance (CEIRS) network collaboratively demonstrated that CIVs replicated in some primary human cells and transmitted effectively in mammalian models. While people born after 1970 had little or no pre-existing humoral immunity against CIVs, the viruses were sensitive to existing antivirals and we identified a panel of H3 cross-reactive human monoclonal antibodies (hmAbs) that could have prophylactic and/or therapeutic value. Our data predict these CIVs posed a low risk to humans. Importantly, we showed that the CEIRS network could work together to provide basic research information important for characterizing emerging influenza viruses, although there were valuable lessons learned.

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PLoS Pathog. 2020 Apr; 16(4): e1008409.
Published online 2020 Apr 14. https://doi.org/10.1371/journal.ppat.1008409
PMCID: PMC7182277
PMID: 32287326

Characterizing Emerging Canine H3 Influenza Viruses

Luis Martinez-Sobrido, Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing,1,* Pilar Blanco-Lobo, Data curation, Formal analysis, Investigation, Methodology,1 Laura Rodriguez, Data curation, Formal analysis, Methodology,1,¤a Theresa Fitzgerald, Formal analysis, Methodology,2 Hanyuan Zhang, Conceptualization, Formal analysis, Writing – original draft,3,4 Phuong Nguyen, Formal analysis, Methodology,2 Christopher S. Anderson, Formal analysis, Resources,2 Jeanne Holden-Wiltse, Conceptualization, Formal analysis, Visualization,5 Sanjukta Bandyopadhyay, Conceptualization, Data curation, Formal analysis,5 Aitor Nogales, Formal analysis, Methodology, Resources,1 Marta L. DeDiego, Formal analysis, Methodology, Resources,2 Brian R. Wasik, Conceptualization, Formal analysis, Methodology, Resources, Writing – review & editing,6 Benjamin L. Miller, Conceptualization, Formal analysis, Methodology, Supervision, Writing – original draft, Writing – review & editing,3,4 Carole Henry, Formal analysis, Methodology, Writing – review & editing,7 Patrick C. Wilson, Conceptualization, Formal analysis, Funding acquisition, Resources, Writing – review & editing,7 Mark Y. Sangster, Conceptualization, Formal analysis,2 John J. Treanor, Formal analysis, Funding acquisition, Supervision, Writing – review & editing,2 David J. Topham, Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Supervision, Writing – original draft, Writing – review & editing,2 Lauren Byrd-Leotis, Data curation, Formal analysis, Methodology,8,9 David A. Steinhauer, Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Supervision, Writing – review & editing,8 Richard D. Cummings, Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Supervision, Writing – review & editing,8,9 Jasmina M. Luczo, Conceptualization, Formal analysis, Methodology, Writing – review & editing,10 Stephen M. Tompkins, Conceptualization, Formal analysis, Funding acquisition, Supervision, Writing – review & editing,10 Kaori Sakamoto, Investigation, Methodology, Visualization,11 Cheryl A. Jones, Formal analysis, Methodology,10 John Steel, Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Supervision, Writing – review & editing,8,¤b Anice C. Lowen, Conceptualization, Data curation, Formal analysis, Funding acquisition, Supervision, Writing – review & editing,8 Shamika Danzy, Methodology,8 Hui Tao, Data curation, Methodology,8 Ashley L. Fink, Formal analysis, Investigation, Methodology, Writing – original draft,12 Sabra L. Klein, Conceptualization, Formal analysis, Funding acquisition, Investigation, Supervision, Writing – original draft, Writing – review & editing,12 Nicholas Wohlgemuth, Formal analysis, Methodology,12 Katherine J. Fenstermacher, Methodology,12 Farah el Najjar, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing,12 Andrew Pekosz, Conceptualization, Formal analysis, Funding acquisition, Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing,12 Lauren Sauer, Project administration, Resources,13 Mitra K. Lewis, Project administration,13 Kathryn Shaw-Saliba, Data curation, Project administration,13 Richard E. Rothman, Funding acquisition, Project administration, Supervision,13 Zhen-Ying Liu, Project administration, Supervision,14 Kuan-Fu Chen, Project administration, Supervision,14 Colin R. Parrish, Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Writing – review & editing,6 Ian E. H. Voorhees, Conceptualization, Data curation, Formal analysis, Investigation, Writing – review & editing,6 Yoshihiro Kawaoka, Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing,15 Gabriele Neumann, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing – review & editing,15 Shiho Chiba, Formal analysis, Methodology, Resources,15 Shufang Fan, Conceptualization, Formal analysis, Investigation, Methodology, Resources,15 Masato Hatta, Conceptualization, Data curation, Formal analysis, Investigation, Methodology,15 Huihui Kong, Conceptualization, Formal analysis, Investigation, Methodology,15 Gongxun Zhong, Conceptualization, Formal analysis, Investigation, Methodology,15 Guojun Wang, Conceptualization, Data curation, Investigation, Methodology,16,17 Melissa B. Uccellini, Project administration,16,17 Adolfo García-Sastre, Conceptualization, Funding acquisition, Project administration, Supervision,16,17,18,19 Daniel R. Perez, Funding acquisition, Methodology, Supervision, Writing – review & editing,20 Lucas M. Ferreri, Formal analysis, Investigation, Methodology,20 Sander Herfst, Conceptualization, Data curation, Formal analysis, Methodology, Supervision,21 Mathilde Richard, Formal analysis, Investigation, Methodology,21 Ron Fouchier, Conceptualization, Funding acquisition, Supervision, Writing – review & editing,21 David Burke, Conceptualization, Data curation, Investigation,22 David Pattinson, Conceptualization, Formal analysis,22 Derek J. Smith, Conceptualization, Data curation, Formal analysis, Funding acquisition, Supervision, Validation, Writing – review & editing,22 Victoria Meliopoulos, Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing,23 Pamela Freiden, Formal analysis, Methodology,23 Brandi Livingston, Investigation, Methodology,23 Bridgett Sharp, Formal analysis, Methodology,23 Sean Cherry, Conceptualization, Data curation, Methodology,23 Juan Carlos Dib, Project administration, Resources, Supervision,24 Guohua Yang, Methodology,23 Charles J. Russell, Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing,23 Subrata Barman, Methodology,23 Richard J. Webby, Formal analysis, Funding acquisition, Methodology, Supervision,23 Scott Krauss, Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing,23 Angela Danner, Conceptualization, Formal analysis, Methodology,23 Karlie Woodard, Methodology,23 Malik Peiris, Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Writing – original draft, Writing – review & editing,25 R. A. P. M. Perera, Conceptualization, Formal analysis, Methodology,25 M. C. W. Chan, Conceptualization, Formal analysis, Methodology, Supervision, Writing – original draft, Writing – review & editing,25 Elena A. Govorkova, Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing,23 Bindumadhav M. Marathe, Formal analysis, Methodology,23 Philippe N. Q. Pascua, Formal analysis, Methodology,23 Gavin Smith, Conceptualization, Data curation, Formal analysis, Project administration, Supervision, Visualization, Writing – review & editing,26 Yao-Tsun Li, Conceptualization, Formal analysis,26 Paul G. Thomas, Conceptualization, Formal analysis, Funding acquisition, Methodology, Supervision, Writing – review & editing,27 and Stacey Schultz-Cherry, Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing23,*
Carolina B. Lopez, Editor

Associated Data

Supplementary Materials
Data Availability Statement

Abstract

The continual emergence of novel influenza A strains from non-human hosts requires constant vigilance and the need for ongoing research to identify strains that may pose a human public health risk. Since 1999, canine H3 influenza A viruses (CIVs) have caused many thousands or millions of respiratory infections in dogs in the United States. While no human infections with CIVs have been reported to date, these viruses could pose a zoonotic risk. In these studies, the National Institutes of Allergy and Infectious Diseases (NIAID) Centers of Excellence for Influenza Research and Surveillance (CEIRS) network collaboratively demonstrated that CIVs replicated in some primary human cells and transmitted effectively in mammalian models. While people born after 1970 had little or no pre-existing humoral immunity against CIVs, the viruses were sensitive to existing antivirals and we identified a panel of H3 cross-reactive human monoclonal antibodies (hmAbs) that could have prophylactic and/or therapeutic value. Our data predict these CIVs posed a low risk to humans. Importantly, we showed that the CEIRS network could work together to provide basic research information important for characterizing emerging influenza viruses, although there were valuable lessons learned.

Author summary

The 2009 influenza pandemic was a stark reminder that ongoing vigilance is critical to protect the public from an influenza pandemic. The continual evolution of influenza viruses and emergence from animal reservoirs, leads to the need to quickly identify strains that pose a public health risk. In these studies, members of the National Institutes of Allergy and Infectious Diseases (NIAID) Centers for Excellence in Influenza Research and Surveillance (CEIRS) network worked together to demonstrate that the emerging canine H3 influenza viruses posed a low risk to public health and identified several therapeutic options in the event of an emergence. In addition to providing important new basic research, many lessons were learned that may be important in dealing with any emerging disease outbreak.

Introduction

In the United States (US), the 2017–2018 influenza season was one of the most severe in recent memory resulting in a total of 171 laboratory-confirmed influenza-associated pediatric deaths and over 30,000 confirmed hospitalizations [1]. Devastating influenza outbreaks are not unique to humans. In recent years, H3 subtype canine influenza viruses (CIVs) have resulted in many thousands or millions of respiratory infections in dogs in the United States.

The H3N2 CIV first appeared in the United States in Illinois in the spring of 2015 but was derived from a virus that had been circulating in China and South Korea since 2005 or 2006 [24]. Dogs infected with H3N2 CIV exhibited respiratory influenza-like symptoms, shed virus through nasal discharge, and the virus was readily transmitted between dogs via direct contact [5] causing several outbreaks throughout the United States [4,6]. This H3N2 CIV is avian in origin [2,49] but prior to 2015, a separate CIV strain derived from equine H3N8 influenza viruses, circulated in the United States [10].

The zoonotic potential of H3 CIV is unknown. Serological studies suggested that human H1N1 and H3N2 viruses could infect dogs, albeit inefficiently, and A/Hong Kong/68-like and influenza B viruses were isolated from dogs in Taiwan in 1971 [11,12]. Swine-origin H1N1 CIV have also been isolated in dogs in China [13]. Since dogs are susceptible to infection with at least three different influenza A subtypes (H3N8, H3N2 and H1N1) and can also be infected with diverse human influenza viruses, these animals have the potential to act as mixing vessels in which novel viruses are generated by reassortment. Genetic exchange through reassortment allows the formation of chimeric genotypes in which some gene segments are well adapted to human hosts. Compared to strains in which the full genome has evolved in a non-human host, such reassortant viruses may more easily overcome the species barrier to cause an outbreak in humans [14].

In the studies described here, members of the National Institutes of Allergy and Infectious Diseases (NIAID) Centers of Excellence for Influenza Research and Surveillance (CEIRS) network collaborated to provide important basic research to address the public health risk of emerging H3 CIVs. The network performed studies specifically addressing the criteria described in the public health algorithms developed by the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) to estimate the potential risk to human health and of pandemic emergence. Our studies demonstrated that the H3 CIVs bound preferentially to α2,3-linked sialic acids (“avian-like receptors”) yet replicated in primary human nasal and bronchial epithelial cells. Mild-to-moderate disease was observed in infected mice depending on the mouse line. The viruses transmitted in ferrets and guinea pigs and were sensitive to matrix 2 (M2) and neuraminidase (NA) inhibitors. There were low levels of preexisting antibody (Ab) immunity in humans and vaccination with a recent human H3N2 strain did not lead to increased serum neutralizing antibody (NAb) titers to the H3N2 CIV. Finally, we identified nine anti-H3 human monoclonal antibodies (hmAbs), derived from influenza-vaccinated individuals, with strong neutralizing activity against both H3N2 and H3N8 CIVs. Together, our results suggest that H3 CIVs pose a low risk to humans, with younger people representing the highest population at risk. Importantly, we showed that the CEIRS network could work together to provide basic research information characterizing emerging influenza viruses and we identified areas where more efficient and rapid responses to future emerging influenza viruses can be developed. Lessons that can be applied to other human disease outbreaks.

Results

Risk assessment criteria

The goal of this exercise was to determine how effectively the CEIRS network could work together to provide key basic research on H3 CIVs addressing components of the 10 scientific criteria outlined in the CDC Influenza Risk Assessment Tool (IRAT, [15]) and/or WHO Tool for Influenza Pandemic Risk Assessment (TIPRA, [16]). These criteria include specific properties of the virus (genomic variation, receptor binding, transmission in laboratory animals, and antiviral susceptibility or resistance), attributes of the population (pre-existing immunity, disease severity and pathogenesis, and antigenic relationship of the emerging virus to vaccines or vaccine candidates), as well as ecology and epidemiology (global distribution in animals, infection in animal species, and human infections (Table 1). This information can then be used to calculate risk using the IRAT/TIPRA algorithms.

Table 1

Summary of risk assessment scientific criteria.
Risk Elements for Likelihood Risk ScoreRepresentative Criteria (examples)
Receptor binding properties• α2,3-linked sialic acids
• α2,3 and α2,6-linked sialic acids
• α2,6-linked sialic acids
Transmission in animal models• No direct or respiratory droplet
• Consistent direct contact
• Consistent respiratory droplet
Genomic characteristics• No molecular signatures of human infection and disease.
• Molecular signatures
• Contains genes derived from a virus circulating in mammals
Infection in animals• Wild species
• Poultry or mammals
• Endemicity
• Numbers of impacted animals
Geographic distribution in animals• Local and contained
• Regional within well-defined geographic boundaries.
• Widespread no boundaries
Risk Elements for Impact Risk Score
Disease severity (human)• Uncomplicated
• Uncomplicated but some severe illness (underlying conditions)
• Severe disease
Population immunity• Cross-reactive antibodies > 30% of population except children < 17
• Cross-reactive antibodies > 30% of people >50
• Minimal (<10%) cross-reactive antibodies
Susceptibility to antiviral treatment• Resistant to adamantanes
• Above + resistant to 1 NA inhibitor
• Above + resistant to > 1 NA inhibitor
Genomic characteristicsAs above
Receptor binding propertiesAs above
Human infection• Single case
• Isolated or sporadic cases
• Frequent separate clusters

Viral strains

Phylogenetic analysis of canine H3 viral sequences obtained from the Influenza Research Database (fludb.org) was performed and several genetically related viral strains (Table 2) were chosen for comparison in this exercise. A/canine/Illinois/41915/2015 (CIV-41915) and the human seasonal A/Bethesda/55/2015 (Beth15) H3N2 viruses were selected because viral isolates were available within the network. A/canine/Indiana/1177-17-1/2017 (rCIV-1177) and A/canine/Illinois/11613/2015 (rCIV-11613) H3N2 viruses were chosen for full genome synthesis and recombinant viruses were generated using reverse genetics [1719]. The ability to successfully synthesize an emerging virus is an important exercise as it is likely that in future outbreaks sequences will be obtained and shared before viral isolates are available [20]. Additional human H3N2 and a canine H3N8 virus (Table 1) were used in the human immunity studies to more broadly assess responses to H3 viruses. Viral stocks and synthetic viruses were distributed to the network participants within weeks of the project initiation. Viral passage history is included in the Methods section.

Table 2

Viruses used in the study and their abbreviations.
SubtypeVirus AbbreviationVirus Name
H3N2CIV-41915aA/canine/Illinois/41915/2015
H3N2rCIV-1177bA/canine/Indiana/1177-17-1/2017
H3N2rCIV-11613bA/canine/Illinois/11613/2015
H3N2rCIV-11613-mCherrybA/canine/Illinois/11613/2015 mCherry
H3N2Beth15aA/Bethesda/55/2015
H3N2HK99aA/Hong Kong/1174/1999
H3N2WY03aA/Wyoming/3/2003
H3N2rWY03bA/Wyoming/3/2003
H3N2rWY03-mCherrybA/Wyoming/3/2003 mCherry
H3N2WI05aA/Wisconsin/67/2005
H3N2HK14aA/Hong Kong/4801/2014
H3N8CIV-23aA/canine/NY/dog23/2009
H3N8rCIV-23bA/canine/NY/dog23/2009
H3N8rCIV-23-mCherrybA/canine/NY/dog23/2009 mCherry

aNatural isolate

brecombinant virus

Replication in primary human respiratory epithelial cells and explants

To monitor replication potential in humans, primary human nasal and bronchial epithelial cells (hNECs and hBECs, respectively) were cultured at an air-liquid interface [21,22] and then inoculated with Beth15, CIV-41915 and rCIV-1177 H3N2 viruses at a multiplicity of infection (MOI) of 0.1 (Fig 1). Viral replication was assessed at 32°C and 37°C to determine whether the physiological range of temperatures of the respiratory tract influenced virus replication. Beth15 and CIV-41915 viruses had similar kinetics and reached similar peak infectious virus titers of around 106 tissue culture infectious dose 50 (TCID50)/ml in hNECs at 32°C. In contrast, rCIV-1177 virus had slower kinetics and lower peak infectious virus titers of 105 TCID50/ml (Fig 1A). At 37°C, the Beth15 and rCIV-1177 viruses replicated with similar kinetics and peak titers, but CIV-41915 virus had higher peak infectious virus titers (Fig 1A). In hBECs, at 32°C the CIVs replicated to significantly lower peak titers compared to Beth15 virus (Fig 1B) while there were no differences in replication of the three viruses in hBEC cultures at 37°C (Fig 1B). In contrast, only the human Beth15 and A/Hong Kong/1174/99 (HK99 H3N2) viruses productively replicated in ex vivo human bronchus explant cultures, with the CIVs showing no replication (Fig 1C). These results indicate that the CIVs replicate efficiently in primary human respiratory cells but not bronchus explant cultures.

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Replication in primary cells and explants.

(A) hNEC or (B) hBEC cultures were inoculated with Beth15, CIV-41915 or rCIV-1177 viruses at a MOI of 0.1 or MOI of 1 and incubated at 32°C or 37°C. At the indicated time, apical media was collected, and virus titers determined. Data are pooled from 2 independent experiments with n = 3 wells per virus for each experiment (n = 6 total). Two-way ANOVA was used for statistical analysis (a = p<0.05, b = p<0.001 compared to Beth15 virus). Dotted line indicates limit of detection. (C) Human bronchus explant culture was submerged in 106 TCID50/ml virus for 1 hour at 37°C, washed and placed onto a surgical sponge in a 24-well tissue culture plate filled with 1 ml/well of culture medium to create an ALI. Supernatant was collected at 1, 24, and 48 hpi and virus titer determined. Experiments were performed with tissues from 3 donors (n = 3). Two-way ANOVA was used for statistical analysis (* = p<0.03, ** = p<0.0005, *** = p<0.0001 compared to mock).

Receptor binding and HA stability

Both receptor binding specificity and HA stability at acidic pH are important criteria for assessing emergence risk, as those have been observed to be key determinants in other examples of successful adaptation and transmission when crossing species barriers [23]. The amino acids around the receptor binding site of the H3 CIVs suggest preferential binding to α2,3-linked sialic acid (SA) receptors like other Eurasian lineage avian H3 viruses [3]. Indeed, glycan binding analysis confirmed that the binding profile of CIV-41915 differed qualitatively from that of the human Beth15 H3N2 virus, as the latter virus preferentially bound α2,6-linked SA receptors, while CIV-41915 preferentially bound avian α2,3-linked SA receptor (Fig 2).

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Glycan array binding.

Fluorescently labeled CIV-41915 and Beth15 viruses were incubated on the glycan microarray for 1 hour at 4°C, to inhibit viral neuraminidase activity, then the slide was washed to remove unbound virus and scanned using a ProScanArray microarray scanner for Alexa Fluor 488 fluorescence and results shown as RFU. Each bar represents a single glycan. Green box = α2,3; pink box = α2,3 + α2,6; blue box = α2,6; orange box = α2,8; and purple box = miscellaneous + NeuGc glycans.

HA acid stability is the pH at which HA is triggered to undergo conformational changes needed to trigger fusion of the viral envelope with the endosomal membrane, or in the absence of a target membrane the pH at which virion infectivity is irreversibly inactivated. HA stability has been linked to pandemic potential and the ability to cross the species barrier, suggesting that it is an important viral characteristic to measure when assessing risk [24]. The H3 CIVs and the human H3N2 viruses had similar pH of fusion values as measured by syncytia formation (5.45–5.50, Table 3). For human H3N2, the pH values of HA-mediated fusion and inactivation were within 0.1 units. However, for the H3N2 CIVs the inactivation pH values were approximately 0.3–0.4 units lower than their activation pH values, showing these viruses had increased resistance to acid inactivation. Despite the divergence of HA activation and inactivation pH values of the H3N2 canine viruses, the values remained within the range of those reported for human-adapted influenza viruses. Overall, these studies suggest that while the H3N2 CIV maintains avian receptor binding specificity, HA stability of CIVs resemble that of mammalian viruses.

Table 3

HA acid stability of H3N2 human and CIVs.
ViruspH of syncytiapH of inactivation
Beth155.455.55
CIV-419155.505.09
rCIV-11775.45<5.2

Pathogenicity in mice

Viruses that bind to α2,3-linked SA receptors typically do not require adaptation to cause disease in mice [25]. Indeed, intranasal inoculation of DBA/2J mice (n = 5 per group) with 106 TCID50 CIV-41915 or rCIV-1177 led to significant weight loss and 60% (CIV-41915) to 100% (rCIV-1177) mortality. Euthanasia upon reaching humane end points accounted for 60% of DBA/2J mortality following infection with rCIV-1177 (Fig 3A and 3B). In contrast, BALB/c (Fig 3A and 3B) and C57Bl/6 mice exhibited no significant morbidity (weight loss) during infection despite having lung viral titers. However, DBA/2J mice had ~1-log higher titers compared to BALB/c at days 3 and 5 post-infection with the CIV-41915 virus and at 5 dpi with the rCIV-1177 virus (Fig 3C). Detection of increased viral loads, and increased susceptibility of DBA/2J mice to influenza virus infection is consistent with previous findings [26,27]. Beth15 virus caused no morbidity and lacked detectable viral titers in the lungs. These data highlight that unlike the human H3N2 virus, the H3N2 CIVs replicate in mice but morbidity was only observed with specific mouse lines.

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Pathogenicity in mice.

(A-B) Body weight and survival: Six-week-old BALB/c and DBA/2J mice (n = 5 per group) were lightly anesthetized with isoflurane and inoculated intranasally with 106 TCID50 CIV-41915 (left panel) or rCIV-1177 (right panel) in 50 μl DMEM. Mice were monitored daily for clinical disease and weighed every other day. (C) Virus loads present in whole lungs were determined 3 and 5 dpi (n = 5 mice per group). Virus titers are expressed as mean±95% CI and * = p <0.05 as compared to BALB/C.

Transmission in ferrets and guinea pigs

A key property of emerging influenza strains is their ability to infect and transmit in mammals. To assess transmission of CIV-41915 virus, donor ferrets were intranasally inoculated with 106 TCID50/ml, while guinea pigs were inoculated with between 10 and 1,000 plaque forming units (pfu). Twenty-four-hour post-infection (hpi), naïve animals were placed in direct (both hosts) or airborne contact (ferrets only) with donor (inoculated) animals. Animals were monitored for clinical signs and viral titers in nasal washes measured through 7–8 dpi (Fig 4). None of the infected animals exhibited clinical signs of infection including weight loss or fever, but the virus did transmit to 100% of the direct contact ferrets (Fig 4A). It also transmitted to 73 to 83% of the contact guinea pigs regardless of the viral dose (Fig 4B and Table 4). While there was no airborne transmission with rCIV-1177 virus, one CIV-41915 respiratory contact ferret had nasal titers at day 7 post-infection and seroconverted with an hemagglutination inhibition (HAI) titer of 320. These studies highlight that the CIVs can transmit by direct contact, but that respiratory droplet transmission is inefficient [3,9]. It is important to note that the titer used to infect ferrets, while the accepted dose, may not be representative of the infectious dose in nature.

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Transmission in ferrets and guinea pigs.

(A) 4 to 6-month-old seronegative ferrets were lightly anesthetized and intranasally inoculated with 106 TCID50 of CIV-41915 in 1.0 ml sterile PBS. At 1 dpi, naïve contacts were placed in the same cage with directly inoculated ferrets while respiratory contacts were placed in adjacent cages separated by a wire grill. Nasal washes were collected every other day for 7 dpi and viral titers determined in MDCK cells. Lines represent individual animals. (B) Guinea pigs were intranasally inoculated 10 to 103 PFU. At 1 dpi, naïve contacts were placed in the same cage with directly inoculated animals. Nasal washes were collected from anesthetized animals on days 2, 4, 6 and 8 post-inoculation and viral titers determined in MDCK cells. Lines represent individual animals.

Table 4

Infection and transmission of CIV-41915 in guinea pigs.
Inoculum (pfu)Infected (%)Transmissions (%)
12/12 (17%)1/2 (50%)
1011/12 (92%)8/11 (73%)
10012/12 (100%)9/12 (75%)
100012/12 (100%)10/12 (83%)

Antiviral susceptibility

The antiviral susceptibility of a new virus is a major determinant when assessing the impact an emerging strain might have on the human population. Thus, the mean inhibitory concentration 50 (IC50) values of neuraminidase (NA) inhibitors (Oseltamivir, Zanamir and Peramivir) and the M2 inhibitor Amantadine were determined against CIV-41915, rCIV-1177 and Beth15 viruses by NA enzyme inhibition and phenotypic assays respectively [28]. The H3 CIVs were sensitive to all Food and Drug Administration (FDA)-approved antiviral drugs in contrast to the Beth15 virus, which was resistant to amantadine as predicted by the presence of the S31N substitution in M2 [29] (Table 5). These studies confirm that the H3 CIVs are sensitive to both FDA-approved antiviral drugs.

Table 5

Susceptibility of H3N2 CIVs to antiviral drugs in phenotypic assays.
Influenza virusNA enzyme inhibition assay
(Mean IC50 ± SD, nM)a
Phenotypic assay
(Mean IC50 ± SD, μM)b
Oseltamivir carboxylateZanamivirPeramivirAmantadine
CIV-419150.13 ± 0.010.85 ± 0.010.15 ± 0.020.6 ± 0.1
rCIV-11770.20 ± 0.011.14 ± 0.030.19 ± 0.020.3 ± 0.1
Beth150.16 ± 0.010.33 ± 0.020.12 ± 0.02> 100

aConcentration of NA inhibitor that reduced NA activity by 50% relative to a reaction mixture containing virus but no inhibitor. Values are the mean ± SD from three independent experiments.

bPerformed in accordance with the CDC protocol. Values are the mean ±SD from three independent experiments.

Determining human immunity against CIVs

Sequence-based antigenic distance calculations

The level of population immunity is a major determinant when assessing the impact an emerging strain would have on the human population. This can be determined genetically by using the protein sequences of the HA and NA to predict antigenic relationships between virus and vaccine strains by sequence-based antigenic distance calculations [3032] or using viral-specific antisera to perform antigenic cartography. Given the lack of ferret antisera to CIVs, we performed sequence-based antigenic distance calculations by analyzing 19,070 H3 sequences from 1963–2017 belonging to 10 animal species and 9 influenza subtypes, 21,792 N2 sequences from 1957–2017 and 2,290 N8 sequences from 1963–2017 belonging to 14/16 subtypes and 12/9 animal species respectively. Sequences were aligned and the number of amino acid changes between strains calculated (Hamming distance). H3 had an aligned length of 579 amino acids with a mean distance of 43.5 and a maximum Hamming distance of 357 giving maximum percent difference of 62%. N2 had an aligned length of 490 amino acids with a mean distance of 48, a maximum distance of 154, and a maximum percent difference of 31%. N8 had an aligned length of 470 amino acids with a mean distance of 40.3, a maximum distance of 113, and a maximum percent difference of 24%. Overall, the three proteins had similar mean Hamming distances, despite differences in aligned amino acid length; with HA having the highest variability between strains, while N2 and N8 had similar numbers of amino acid changes.

To facilitate visualization of the data sets, we employed classic multidimensional scaling (principal component analysis) to reduce the dimensionality of the Hamming distance matrix and allow “mapping” of the strains in 2 dimensions. H3 (Fig 5A) and N8 (Fig 5C) had similar conservation of distance, with N2 (Fig 5B) slightly reduced (GOF: 0.69, 0.69, 0.58, respectively). All proteins showed clear clustering with N8 forming 3 distinct clusters (Fig 5C). The H3 HA of both H3N2 CIV-11613 (designated IL15 in Fig 5A and 5B) and H3N8 CIV A/canine/NY/dog23/2009 (rCIV-23 but designated as NY09 in Fig 5A and 5C) clustered closely with avian and equine HA sequences (Fig 5A), likely reflecting their species of origin before moving into dogs. Likewise, clustering for N2 (Fig 5B) was close to primarily avian and to some human N2 strains. Overall, host species was the best predictor of clustering.

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Cartography mapping of H3, N2 and N8 influenza proteins.

Sequence-based maps of H3 (A), N2 (B) and N8 (C) viral proteins. Each point represents a single virus strain. Points are colored based on the species the virus was isolated from (A-C). Position of CIV-11613 (IL15), CIV-23 (NY09), HK68, PC73, Wy03, WI05, Vic11 and HK14 are indicated. Scale bar, 20 amino acids distance.

The relative location in sequence space can be used to predict antigenic relatedness to vaccine viral strains [32]. Thus, we determined the proximity of the viruses used in the H3N2 human vaccines to CIVs. We found that H3 CIV were closest to early H3N2 vaccine strains A/Hong Kong/1/1968 H3N2 (HK68) and A/Port Chalmers/1/1973 H3N2 (PC73) (Fig 5A). Similarly, the N2 of CIV-41915 was closely related to HK68 and PC73 vaccine strains (Fig 5B). In contrast, recent H3N2 vaccine strains such as A/Victoria/361/2011 (VI11) or A/Hong Kong/4801/2014 (HK14) resided furthest from H3N2 CIV strains (Fig 5A and 5B) suggesting that H3N2 CIVs are antigenically more like early human H3N2 viruses than contemporary strains.

Pre-existing immunity in human sera

Based on the sequence relationships observed, we hypothesized that sera from individuals exposed to early H3N2 influenza strains, either by infection or vaccination, would cross-react to H3 CIVs, but that little cross-reactivity would be found in sera from individuals exposed to more recent human H3N2 strains. We therefore examined the viral-specific IgG titer by enzyme-linked immunosorbent assay (ELISA), HAI, and NA-specific enzyme-linked lectin assay (ELLA) in 153 sera from healthy subjects born in the US between 1934 to 2012, and HAI titers in 225 sera from Guangzhou, China and 53 sera from Colombia, South America. Greater than 97% of the samples from the US cohort had antibodies against the human and canine H3 viruses by ELISA (IgG titer > 20) regardless of age (Fig 6A). In contrast, only 19.6% of the subjects had a detectable HAI titer (≥10) against rCIV-11613 and 9.1% against the rCIV-23 H3N8 with only 7.8% and 0.65% of these people having seroprotective titers (≥40 HAI [33]) respectively. This is compared to 95.4% of the people having HAI titer (≥10) against human A/Wyoming/3/2003 (rWY03, Fig 6B) with 90.1% having seroprotective HAI titers ≥40 (Fig 6B). Interestingly, 93.3% of people with H3N2 CIV HAI titers were born before 1970 while 57.1% with HAI titer against H3N8 CIV were born before 1970. A similar trend was observed with the Guangzhou samples but not the Colombian samples where no people were HAI positive for H3 CIV (S1 Table).

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Pre-existing population immunity against H3N2 and H3N8 CIV in human sera.

The presence of antibodies against rCIV-11613 H3N2 (black, left), rCIV-23 H3N8 (red, middle) and WY03 H3N2 (blue, right) was examined in triplicate by (A) ELISA, (B) HAI and (C) ELLA assays using 153 human sera samples collected from healthy subjects born between 1934 and 2012 and grouped in 10 years intervals. Dotted black lines indicate the limit of detection of each of the assays. Undetectable titers were assigned a value of 10, 5 and 8 for ELISA, HAI and NAI respectively. Each dot represents the mean titer (represented as log2) of a specific human subject.

Since NA antibodies can also provide protection [34,35], we tested for the presence of CIV N2 and N8 antibodies by ELLA (Fig 6C). 83% of the subjects had a NA inhibition titer (NAI titer ≥16) against rCIV-11613 N2, while only 49% of the subjects were positive against rCIV-23 N8. Most (98.7%) of the human sera contained functional anti-NA antibodies against human WY03 H3N2. Interestingly, the median NAI titer against rCIV-11613 N2 in subjects born before 1970 was significantly higher than those in younger subjects (median NAI titer 1024 vs. 64; p<0.001). No association was found between the age and NAI titer against CIV-23 N8 (p = 0.07) or human rWY03 H3N2 virus (p = 0.08). Overall, antibodies recognizing canine N8 and N2 CIV proteins were found more frequently in people born before 1970. Younger people may therefore be considered at higher risk for H3 CIV infections while older people might have been exposed to influenza strains antigenically like currently circulating H3 CIVs, providing them with some residual cross-reactive and protective immunity.

Finally, we investigated the impact of confirmed human H3 infection with or without documented receipt of the seasonal influenza vaccine on CIV neutralizing Ab (NAb) titers. Serum samples were obtained from patients enrolled at either the Johns Hopkins Health System (JHMI) or Chang Gung Memorial Hospital (CGMH) in Taipei, Taiwan with confirmed H3N2 infection and documentation of receipt of the seasonal influenza vaccine during the 2016–17 season (Fig 7) [36,37]. At baseline (i.e., at the time of enrollment), seroprotective NAbs (>1:40) against CIV-41915 were detected in 54% in contrast to 81% against human Beth15 H3N2 virus (Fig 7A). At CGMH, the overall NAb titers were lower for both human Beth15 CIV-41915 H3N2 viruses when compared to the titers at JHMI but there was no statistically significant difference between Beth15 and CIV-41915 NAb titers (Fig 7A). As predicted by antigenic cartography, vaccination with a contemporary HK14 H3N2 vaccine had no impact on NAb titers against CIV-41915 at either site but did increase titers against the human Beth15 H3N2 virus (Fig 7B and 7C). These results demonstrate that vaccination with human seasonal H3N2 vaccines does not change the Ab response to the H3 CIV in patients infected with H3N2 viruses.

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Neutralizing Ab titers to human Beth15 and CIV-41915 H3N2 viruses in patients with confirmed H3N2 infections during the 2016–17 season.

(A) Human sera collected from Johns Hopkins Health System (JHMI) and Chang Gung Memorial Hospital (CGMH) in Taipei, Taiwan were subject to two-fold serial dilutions prior to incubation with 100 TCID50 of either Beth 15 or CIV-41915. MDCK cells were then infected with the virus-sera mixture and following 24-hour incubation, cells were fixed and stained with Napthol blue black. The baseline neutralizing antibody titer was determined as the highest serum dilution that eliminated cytopathic effects in 50% of the wells. (B and C) Sera was collected from JHMI and CGMH at the time of hospital confirmation of H3N2 infection, with documentation about whether patients had or had not been vaccinated during the 2016–17 season and neutralizing antibody titers were determined as in (A). (b = p<0.001, d = p<0.0001 compared to Beth15).

Protecting naïve populations

Identifying human derived hmAbs cross-reactive to H3 CIVs

Our studies suggest that older people might have been exposed to influenza strains with some antigenic similarity to currently circulating H3 CIVs affording them with residual cross-reactive and protective immunity. Arrayed Imaging Reflectometry (AIR) has been used to provide information about anti-HA antibody titers in sera against different HA subtypes [38]. More recently, it has been used to demonstrate the multiplex capability of antibody arrays for live influenza virus characterization [39]. Here, we use AIR as a high-throughput screening approach to evaluate the cross-reactivity of a panel of recombinant hmAbs cloned from plasmablasts of volunteers vaccinated with different H3N2 strains (A/Perth/16/2009, A/Wisconsin/67/2005, A/Texas/50/2012, and A/Uruguay/716/2007) [39] against H3N2 and H3N8 CIVs and antigenically similar (HK68) or distinct (A/Wisconsin/67/2005, WI05) human H3N2 viruses. The array included a panel of seventeen H1-reactive, 65 H3-reactive and 6 H1/H3 cross-reactive hmAbs (Fig 8A). H7-reactive hmAbs were also included as controls for the human viruses (Fig 8B). Fig 9A–9D shows the data from representative arrays. We used a hierarchical clustering heatmap to reflect the quantitative response of each hmAb in the array to each of the indicated viruses (Fig 9E).

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Layout information of the array.

(A) Array for rCIV-11613, rCIV-23, and human HK68 or (B) Wis05 H3N2 viruses. Human IgG was used as control for nonspecific IgG binding. Three anti-fluorescein (anti-FITC) solutions were uses as negative control at a concentration of 100 μg/ml (FITC-100), 200μg/ml (FITC-200) and 400μg/ml (FITC-400). Bovine IgG secondary antibodies reactive to the bovine sera used for blocking were used as positive control.

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Cross-reactivity of hmAbs by AIR.

AIR images of arrays exposed to (A) rCIV-11613 H3N2, (B) rCIV-23 H3N8, (C) HK68 and (D) WI05 viruses. (E) Hierarchical cluster map of the hmAb responses. Values in this map are scaled relative to the antibody producing the strongest response for each virus. Arrows show the antibody clustering groups.

We identified 21 hmAbs reacting to both H3 CIVs, whereas 8 hmAbs reacted only to H3N2 rCIV-11613 (042-10065-2B03, 037-10036-5A01, C1-2A02, 229-1C01, 229-2E06, 008-10053-5E04, 009-10061-2E02, and 019-10117-3F02) and 2 hmAbs (C1-B01 and 228-3C06) only reacted to H3N8 rCIV-23. Of the 31 hmAbs that reacted to either H3 CIVs, 27 were also reactive to HK68 with only 15 reactive to WI05 H3N2 human viruses (Fig 9A–9D). Visualizing the AIR data as a cluster heatmap to examine the relationships between H1, H3, and H1/H3-reactive hmAbs demonstrated that H3 CIVs clustered with HK68 while WI05 clustered independently (Fig 9E), correlating with the sequence-based antigenic distance calculations map (Fig 5).

The cross-reactivity of 30 of the identified hmAbs (228-3C06 was no longer available) against H3 CIVs was further confirmed by immunofluorescent microscopy using mCherry-labeled viruses (S1 Fig). rWY03 and HK68 H3N2 human viruses served as internal controls. The fluorescence signal was quantified and relative binding of each hmAb was calculated considering the signal of the hmAb 017–10116 5B03 as the maximum 100% signal (Fig 10). The percentage of reactivity was used to categorize the hmAbs in 6 groups (Figs (Figs99 and and10):10): Group 1: ≥30% reactivity against H3 CIVs and WI03 H3N2; Group 2: ≥30% reactivity against H3 CIVs, but <30% for r/WY03 H3N2; Group 3: ≥30% reactivity against H3N2 CIV-41915 but <30% for H3N8 rCIV-23 and WI03 H3N2; Group 4: ≥30% reactivity against H3N2 CIV-41915 and WI03 H3N2 but <30% for H3N8 rCIV-23; Group 5: ≥30% reactivity against WI03 H3N2 but <30% for rCIV-23 H3N8 and H3N2 CIV-41915; and, Group 6: non-reactivity or <30% reactivity against rCIV-23 H3N8 and/or H3N2 CIV-41915, or WI03 H3N2. Unfortunately, the epitopes of these hmAbs are unknown.

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Cross-reactivity of hmAbs by immunofluorescence.

MDCK cells were infected with rCIV-11613, rCIV-23, rWY03 or HK68 viruses at a MOI of 3. At 18 hpi, cells were fixed, permeabilized and incubated with 1 μg/ml of the indicated hmAbs. After incubation with a secondary anti-human FITC-conjugated antibody, fluorescence was imaged under a fluorescent microscope. Fluorescence intensity was measured using the ImageJ 1.51s and data was displayed using a Heatmap visualization method. For each virus, the hmAb providing the highest intensity (017–10116 5B03) was considered as 100% and was used to normalize the percentage of reactivity of the rest of the hmAbs. The percentage of reactivity was used to categorized the hmAbs in 6 groups: Group 1: ≥30% reactivity against H3 CIVs and rWY03 H3N2; Group 2: ≥30% reactivity against H3 CIVs, but <30% for rWY03 H3N2; Group 3: ≥30% reactivity against H3N2 rCIV-11613 CIV but <30% for H3N8 rCIV-23 and rWY03 H3N2; Group 4: ≥30% reactivity against H3N2 rCIV-11613 and rWY03 H3N2 but <30% for H3N8 rCIV-23 CIV; Group 5: ≥30% reactivity against rWY03 H3N2 but <30% for rCIV-23 H3N8 and H3N2 rCIV-11613; and, Group 6: non-reactivity or <30% reactivity against rCIV-23 H3N8 and/or H3N2 rCIV-11613, or rWY03. Representative images of the reactivity of the hmAbs against infected cells are shown in the right. Scale represent % of recognition. Scale bars, 200 𝜇m.

Overall, there was good correlation between the AIR and the immunofluorescence results for CIVs (summarized in Table 6). However, discordant results were found in Groups 3, 4 and 5, where some clones detected the CIVs by AIR but not by immunofluorescence, suggesting that the sensitivity of AIR might be greater than immunofluorescence. This analysis shows that AIR could be used as a fast, reliable and sensitive high-throughput screening approach to identify hmAbs with cross-reactivity against different viruses, including H3N8 and H3N2 CIVs. Our data also indicate that previous vaccination or exposure to closely related human H3N2 viruses may elicit Ab responses that cross-react efficiently to the HA protein of H3N2 CIV and, to a lesser extent, H3N8 CIV.

Table 6

Summary of the characteristics of the hmAbs.
AIRIFANT50HAI
MAbrCIV H3N2rCIV H3N8rCIV H3N2rCIV H3N8r/Wy
H3N2
rCIV H3N2rCIV H3N8r/Wy
H3N2
rCIV H3N2rCIV H3N8r/Wy
H3N2
Group 1017-10116-5B03+++++0.0110.0210.017>1>10.062
042-100809-2F04+++++0.0170.0050.046>1>1>1
011-10069-3E06+++++0.0190.020.002>1>1>1
S6-B01+++++0.0140.0070.005>1>1>1
SFV005-2G02+++++0.0900.0171.56>1>1>1
045-051310-2B06+++++0.0580.015>2>1>1>1
008-10053-6C05+++++0.0440.0330.004>1>10.25
042-10065-2B03+++++0.0760.490.014>1>1>1
229–14036-2F03+++++0.043>20.012>1>1>1
Group 2045-051310-2C01++++->20.039>2>1>1>1
229–14036-1G01++++-0.520>2>2>1>1>1
229–14036 2G06++++-0.50.5>2>1>1>1
Group 3062860153-E05+-+--0.063>2>20.015>1>1
017-10116-5D02+++--0.004>2>20.125>1>1
017-10116-5G02+-+--0.041>2>20.5>1>1
030-121509-3B01+-+--0.6>2>2>1>1>1
Group 4028-10134-4F03+++-+0.003>20.003>1>10.015
229–14036-1C01+-+-+0.005>20.018>1>10.062
008-10053-1G05+++-+0.0040.0150.001>1>10.007
034-10040-1F01+++-+>2>20.014>1>10.031
034-10040-4F02+-+-+0.009>20.028>1>10.015
Group 6229-2E06----->2>2>2>1>1>1
008-10053-5E04----->2>2>2>1>1>1

H3 cross-reactive hmAbs neutralize H3 CIVs in vitro

Passive immunotherapy could be a plausible strategy to control CIV infection [40,41]. We therefore used recombinant mCherry-expressing human (rWY03-mCherry) and canine (rCIV-11613-mCherry and rCIV-21-mCherry) H3N2 viruses to examine the ability of the identified cross-reactive hmAbs to neutralize H3 CIV infections in vitro using a fluorescence-based microneutralization assay [42,43]. Eight of 9 hmAbs from Group 1 (Fig 11A) and 1 of 5 from Group 4 neutralized both H3N2 and H3N8 CIVs (Fig 11D). In contrast, 1 of 9 from Group 1 (Fig 11A), 3 of 4 from Group 3 (Fig 11C) and 3 from Group 4 (Fig 11D) specifically neutralized only the H3N2 rCIV-11613-mCherry while only 1 of 3 from Group 2 specifically neutralized H3N8 rCIV-23-mCherry (Fig 11B). Only hmAbs from Groups 1 and 4 displayed neutralization activity against human H3N2 rWY03-mCherry virus (Fig 11A and 11D), and none of the hmAbs from Group 6 displayed neutralization activity (Fig 11E). HAI assay, which generally only detects antibodies that bind the head domain of HA [44], identified only 3 hmAbs from Group 3 with activity against H3N2 rCIV-11613 (Table 6). No HAI titer was detected for the other 18 hmAbs at 0.01 mg/ml, the limit of detection in our assay. Overall, these results show that plasmablast cells from influenza vaccinated or infected humans could be used as sources for hmAbs that recognize and functionally neutralize H3 CIVs.

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Neutralizing activity of hmAbs.

MDCK cells were infected with the mCherry-expressing rCIV-23 H3N2 (black line), rCIV-23 H3N8 (red line) or rWY03 H3N2 (blue line) recombinant viruses at 0.005 MOI. After 1-hour adsorption at room temperature, cells were incubated with 2-fold serial dilutions of the indicated hmAbs (starting concentration of 0.2 mg/ml) belonging to the Groups 1 (A), 2 (B), 3 (C), 4 (D) or 6 (E). Group 5 hmAbs (≥30% reactivity against rWY03 H3N2 but <30% for rCIV-23 H3N8 and rCIV-23 H3N2) were not included in the assay. At 60 hpi, fluorescence expression was quantified using a fluorescence plate reader and sigmoidal dose response curves were used to calculate the hmAbs concentration that reduced the virus infectivity by 50% (Neutralization titer 50, NT50). Mock-infected and infected cells in the absence of hmAbs were used as controls to normalize the percentage of inhibition. Data show the mean and +/- SDs of the results determined for triplicate. An inhibition of 50% is indicated as a dotted black line.

Discussion

Identification of emerging influenza strains and assessing their pandemic potential is a crucial component of surveillance (https://www.hhs.gov/about/agencies/oga/global-health-security/pandemic-influenza/index.html; [45,46]). Reassortment and zoonotic transmission are the most likely threats, and the causative viruses must be quickly identified and characterized so that control and preventative measures can be taken. For example in 1997, the human H5N1 isolate was collected from the trachea of a three-year-old child and rapidly distributed to WHO Collaborating Centers for analysis [4749]. Studies concluded that while that H5N1 isolate was not easily transmissible, it should be closely monitored since reassortment could potentially result in a devastating pandemic [49]. Similarly, a zoonotic outbreak of H7N9 virus in 2013 precipitated a rapid assessment of viral pathogenicity and transmissibility in model animals [50].

The 2017–2018 influenza season brought problems with responses to H3N2 subtype seasonal influenza strains to the forefront of public health. Decreased vaccine efficacy and increased complications leading to hospitalizations [51,52] highlight the need to have carefully planned and preemptive response to both existing seasonal and new influenza pandemics. The continual emergence of novel influenza strains from non-human hosts, as well as new antigenic and virulence variants from humans, puts immense pressure on public health agencies to determine which of the many viruses in circulation may pose a risk to public health. Making well informed decisions about which viruses to focus on is also a key issue, given the cost of producing and stockpiling a candidate vaccine virus or developing other countermeasures. To aid in the decision process, WHO and CDC developed related algorithms that can be populated by specific information including (but not limited to) specific features of the virus, disease and spread and population immunity (Table 1) to predict risk [15,16]. A summary of influenza A viruses assessed using the CDC IRAT can be found at https://www.cdc.gov/flu/pandemic-resources/monitoring/irat-virus-summaries.htm. The goal of this exercise was to determine how quickly the CEIRS network could provide critical data on a new virus.

The global CEIRS network is unique in its ability to do the broad basic research addressing many of the required criteria and develop new tools and systems to lead the field in exciting new interdisciplinary directions and control strategies. The appearance of the avian-like H3N2 CIV in the US in 2015 presented an opportunity to test the CEIRS network pre-pandemic risk assessment plan pipeline. Upon selection of the viral strains, groups were assigned specific tasks and time to completion was monitored. Available viral isolates were distributed and generation of reverse genetics derived viruses from publicly available sequences was initiated within weeks. In 2 months, the network demonstrated that the H3 CIV preferentially bound to α2,3 sialic acid receptors but replicated efficiently in primary human nasal and bronchial epithelial cells; replicated and caused disease in DBA2/J mice and transmitted effectively in direct contact ferrets and guinea pigs without causing clinical signs of infection. Using sera from human cohorts located in the US, Asia and South America, we demonstrated that younger subjects born after 1970 had no cross-protective humoral immunity, even if vaccinated for seasonal human H3 viruses, and may be considered at high-risk for H3 CIV infections. There was, however, a high rate of pre-existing NA cross-reactive Abs to H3N2 CIV, especially in the older population. Given the evidence that NA antibodies are associated with decreased disease and shortened duration of viral shedding [53,54], it is possible that the NA antibodies would reduce pathogenesis in and transmission. Importantly, if an H3 CIV did emerge in humans, our studies suggest the available FDA-approved antiviral drugs could be used and hmAbs could be effective for passive immunization.

The CEIRS network study goes beyond characterization of emerging viruses. It highlights new approaches (e.g. AIR), tools (e.g. primary human respiratory cells and explants; reporter viruses) and involved hypothesis-driven work (i.e. identifying cross-reactive hmAbs) that were only possible due to ongoing fundamental basic research. This was the first study, to our knowledge, to directly compare transmission in the ferret and guinea pig models. Ongoing studies within the CEIRS network are expanding this comparison to other viral strains. We also provided the initial comparison of viral replication in isolated primary respiratory bronchial epithelial cells and bronchus explants demonstrating that the results differ. In contrast to the human viruses, the CIVs replicated, although not to high titers, in the hBECs but failed to replicate. This could be due to donor variability, differences in sialic acid linkage distribution, or the impact of having a mixed culture of lung cells in the explant. Ongoing studies are aimed at defining these differences and identifying the best system for characterization of emerging viruses; especially avian and mammalian strains. Overall, the outcome of the current and ongoing studies will provide important new information to fundamental research, but also to refine and update the public health algorithms.

Several critical lessons were learned during this exercise. First–having a sequence does not guarantee that you can generate a virus. We specifically included H3 CIV strains that would need to be synthesized and rescued by reverse genetics as this is the most likely scenario [55,56]. Attempts to rescue complete H3 recombinant canine viruses were unsuccessful. This likely resulted from the lack of 5’ and 3’ untranslated region (UTR) sequence information in the public databases. UTRs are critical for gene expression [57]. However, 6+2 viruses containing CIV HA and NA on a PR8 backbone were created and distributed to all groups leading to the second lesson learned. Several groups were unable to receive WT and/or recombinant viruses due to technology transfer issues, and material transfer agreements (MTA) and patent rights between institutions were barriers to sharing of these reagents. While outside the control of the CEIRS network investigators, this had a major impact on the exercise, the timeliness of the studies and was the reason the viruses tested in experiments differed. An outcome of the exercise was establishment of universal MTAs between all CEIRS institutions and agreements that in the case of a public health emergency, public health need would overshadow commercial considerations and patent rights. While not an issue for this exercise, previous situations have shown that obtaining appropriate import permits and biosafety approvals from various government agencies (USDA, CDC, etc.) can lead to significant delays in initiating research efforts. This is especially true with emerging viruses from non-human hosts where different government agencies may need time to determine which agency holds jurisdiction and what permits and/or biosafety conditions will be required. Although we are confident that the CEIRS network could rapidly respond to an emerging virus or pandemic (as we did in during the 2009 pandemic and in response to the H7N9 virus in 2013) by redirecting existing resources, including personnel, to provide critical fundamental research on novel influenza strains our response time can always be improved. Our pipeline, coupled with the global surveillance efforts in humans and other mammals, birds and at the animal-human interface, may identify the emerging viruses of concern.

Collectively, this collaborative CEIRS exercise demonstrated our ability to respond to a potentially emergent virus with putative risk to humans, generating reagents and assays critical to assessing risk of infection and pathogenesis to humans. The lessons learned from this exercise go beyond influenza virus, being important for studies of emerging infectious diseases of all types.

Materials and methods

Ethics statement

All experiments were approved and conducted in appropriate animal biosafety level facilities in compliance with the policies of the National Institutes of Health, the United States Animal Welfare Act, in strict compliance with European guidelines (European Union [EU] directive on animal testing 86/609/EEC) and Dutch legislation (Experiments on Animals Act, 1997) and with the approval of the University of Georgia (#A2017 05–009), St Jude Children’s Research Hospital (535 and 428), Emory University (PROTO201700595), Icahn School of Medicine at Mount Sinai (IACUC-2013-1408), University of Rochester (101890 / 2014-019E) and Erasmus University (Erasmus MC permit AVD101002015340, protocol number 15-340-07) Animal Care and Use Committees and Institutional Biosafety Committees. Animals were euthanized following AVMA approved guidelines. All human samples were collected upon written and/or oral consent on studies approved by the DMID, and the University of Rochester (NCT03328325), Johns Hopkins (IRB00091667), St Jude Children’s Research Hospital (INDIFLU) and University of Hong Kong (UW 14–119) individual institutional review boards. All data analyzed were anonymized.

Viruses

A complete listing of viruses and abbreviations can be found in Table 2. HK68 and WI05 were obtained from BEI Resources (NR-28620 and NR-41800, respectively), propagated in Madin-Darby canine kidney (MDCK) cells and p1 stocks used in experiments. The CIV-41915 virus was originally isolated in MDCK cells by the Cornell Animal Health and Diagnostic Center and MDCK p2 stocks were distributed to the network from Dr. Parrish’s laboratory. The Beth15 H3N2 human strain was isolated in human nasal epithelial cell cultures and further propagated in MDCK cells. Vials of p2 working stock was distributed to the CEIRS network from Dr. Pekosz laboratory. All viruses were used at p1 or p2 stocks or as stated in the specific methods.

Reverse genetics

Recombinant viruses were generated using plasmid-based reverse genetics techniques as previously described [5860].

Cells

MDCK (ATCC CCL-34 and IRR FR-58) and Vero (ATCC CCL-81) cells were grown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 5–10% fetal bovine serum (FBS), 2 mM GlutaMax, 100 U/ml Penicillin and 100 μg/ml Streptomycin. Human bronchial epithelial cells (hBECs) were obtained from Lonza (CC-2540) and grown in expansion media (Airway Epithelial Cell Growth Medium, Promocell) prior to seeding on transwell inserts. Cells were maintained at an air-liquid interface (ALI) for three weeks to allow differentiation. Human nasal epithelial cells (hNECs) were obtained from disease-free tissues and maintained at ALI as previously described [22].

Ex-vivo culture of human respiratory tract explants

Fresh residual tissues from normal human bronchus and lung were obtained from patients undergoing surgical resection at Queen Mary Hospital, Hong Kong and cells cultured as previously described [6163]. Briefly, bronchial tissue fragments were placed on a surgical sponge (Simport) floating in a 24-well tissue culture plate containing F-12K nutrient mixture (Gibco), 100 U/ml penicillin, and 100 μg/ml streptomycin, to create an air-liquid interface. Lung explants were cultured similarly but without the use of surgical sponge. All tissues were maintained at 37°C, 5% CO2.

Multicycle growth kinetics

MDCK cells

Cells were plated at 5×105 cells/well in triplicate in 12-well tissue culture plates, grown to confluency and infected at a MOI of 0.001 [64]. After 1 hour of adsorption at room temperature, fresh media supplemented with 1 μg/ml TPCK-treated trypsin (Sigma) was added and cells were placed at 33°C, 37°C or 39°C. Tissue culture supernatants were collected at the designated times post-infection and viral titers were determined by immunofocus assay (fluorescent forming units, FFU/ml) using mouse mAbs against NP including: HB-65 (ATCC, H16-L10-4R5) for rCIV-23 H3N8 and rWY03 H3N2; and HT-103 for H3N2 rCIV-11613 [65]. Mean values and standard deviations (SDs) were calculated using Microsoft Excel software.

hNECs and hBECs

Differentiated cells at ALI were equilibrated for 2 days at 32°C or 37°C, washed with 150 μl of infection media (DMEM supplemented with 0.3% BSA [Sigma], 100 U/mL penicillin, 100 μg/mL streptomycin, 2 mM GlutaMAX [Gibco]) and the basolateral media changed immediately before infection with MOI of 0.1. Virus was incubated for 2 hours at 32°C, washed and cells incubated at 32°C or 37°C. At the indicated times, 100 μl of media was added to the apical chamber incubated for 10 minutes at 32°C, collected and viral titers determined by tissue culture infectious dose 50 (TCID50) assay [66]. Endpoint calculations were determined by the Reed-Muench algorithm [67].

Ex-vivo human respiratory tract explants

Human respiratory tract explant cultures were submerged in 1 ml of virus at ~106 TCID50/ml for 1 hour at 37°C, carefully washed with PBS to remove unbound virus, and placed onto a surgical sponge in a 24-well tissue culture plate filled with 1 ml/well of culture medium containing F-12K nutrient mixture (Gibco), 100 U/ml penicillin, and 100 μg/ml streptomycin, to create an ALI and maintained at 37°C. Supernatant from culture media of virus infected bronchial tissues was collected at 1, 24, and 48-hour post-infection (hpi) and titrated by TCID50 assay on MDCK cells. Experiments were performed with tissues from 3 donors (n = 3).

Plaque assays

Plaque assays were performed on MDCK cells plated at 1x106 cells/well in 6-well tissue culture plates and grown to confluency as described [68]. TCID50 assays were performed on confluent MDCK cells in 96-well tissue culture plates as described [68]. Endpoint calculations were determined by the Reed-Muench algorithm [67].

HA acid stability

HA acid stability was measured by syncytia assay as described [69]. Briefly, 17 to 24 hpi, HA-expressing Vero cells were incubated for 5 minutes with TPCK-treated trypsin and pH-adjusted PBS buffers, the pH then neutralized by washing with PBS, and then incubated in regular medium for 3 hours at 37°C. Subsequently, the cells were fixed and stained for microscopy.

Acid inactivation and luciferase infectivity assay

To measure the abilities of the viruses to retain or lose infectivity as a function of exposure to solutions of varying acid pH, virus stocks were incubated 1 hour at 37°C in pH-adjusted PBS solutions before the pH was neutralized. Viruses were subsequently used to infect MDCK Luc9.1 reporter cell (generous gift of Dr. Ruben Donis). Renilla luciferase enzymatic activity was used to assay for retention of infectivity. The susceptibility to inactivation by exposure to low pH was reported as pH50.

Fluorescent labeling of viruses and binding to CFG glycan microarray

To fluorescently label viral particles, 200 μl of virus was incubated with 25 μg of Alexafluor 488 (Invitrogen) in 1 M NaHCO3 (pH 9.0) for 1 hour at room temperature. Excess label was removed via dialysis in PBS using a 7,000-molecular-weight-cutoff Slide-A-Lyzer mini-dialysis unit (Thermo Scientific) overnight at 4°C. In all cases, labeled viruses were used in experiments the following day. Labeled virus was incubated on the glycan microarray (CFG version 5.3 from the National Center for Functional Glycomics) for 1 hour at 4°C, to inhibit viral NA activity, then the slide was washed to remove unbound virus and scanned using a ProScanArray microarray scanner (Perkin Elmer) at 495 nm (ex) and 519 nm (em) for Alexa Fluor 488 fluorescence.

Immunofluorescence microscopy

MDCK cells were plated at 1×105 cells/well in 48-well tissue culture plates and grown to confluency. Cells were then mock or infected with the indicated viruses at a MOI of 3 and incubated at 33°C. At 12 hpi, cells were fixed with 4% paraformaldehyde and permeabilized for 15 minutes at room temperature with 0.5%Triton X-100. After incubating in block solution (2.5% BSA in PBS) for 1 hour at room temperature, cells were incubated with the following mAbs (1μg/ml) or pAbs (dilution 1:1000) diluted in blocking solution for 1 hour at 37°C: anti-HA A/duck/Shantou/1283/2001 H3N8 goat pAb (BEI Resources NR-34586), A/equine/Miami/1/1963 H3N8 mouse mAb equine 7.1, or A/Hiroshima/52/2005 mouse pAb (BEI Resources F-287) for the staining of rCIV H3N2-, rCIV H3N8- or r/Wy H3N2-infected cells, respectively; anti-NA A/Singapore/1/1957 H2N2 goat pAb (BEI Resources NR-3137), A/equine/Miami/1/1963 H3N8 goat pAb (BEI Resources NR-3145) or hmAb 109219 (kindly provided by James J. Kobie) for the staining of rCIV H3N2-, rCIV H3N8- or r/Wy H3N2-infected cells, respectively; anti-NS1 1A7and 4D4 [70] mouse mAbs cocktail (1:1, 2 μg/ml). After incubation with the primary antibodies, cells were washed and incubated with a 1:200 dilution of fluorescein isothiocyanate (FITC)-conjugated anti-mouse (Dako), anti-goat (Jackson Immuno Research) or anti-human (Jackson Immuno Research) secondary antibodies in blocking solution, along with 4′,6-diamidino-2-phenylindole (DAPI; Research Organics) for 1 hour at 37°C. After washing, fluorescent staining and mCherry expression were evaluated and images were captured using a fluorescent microscope (Olympus IX81 with camera QIMAGING, Retiga 2000R).

Animal experiments

Mice

Six- to eight-week-old C57BL/6 (National Cancer Institute, NCI), BALB/c (Envigo) or DBA/2J (The Jackson Laboratories) were lightly anesthetized with isoflurane and intranasally (i.n.) inoculated with 50 μl of 106 TCID50 of CIV-41915 p3, rCIV-1177 p3, Beth55 p4 or DMEM diluent. Mice were monitored daily for clinical disease signs and weighed every 48 hours. Viral titers in whole lungs were determined at 3 and 5 dpi (n = 5 mice per group) by TCID50. Seroconversion was determined at 26 dpi.

Ferrets

Influenza virus seronegative 4 to 6-month-old outbred male ferrets (Triple F Farms, PA, n = 9 per virus and n = 3 per group) were lightly anesthetized and intranasally inoculated with 106 TCID50 of virus (p3) in 1.0 ml sterile phosphate-buffered saline. At 1 dpi, one naïve contact ferret was placed in the same cage with a directly inoculated ferret and one aerosol contact was placed in an adjacent cage separated by a wire grill. All ferrets were monitored daily for weight loss, body temperature, and clinical signs of infection for 12 dpi [71] [72]. To monitor virus shedding, nasal washes were collected every other day for 12 dpi and viral titers determined by TCID50. Seroconversion was determined at 21 dpi.

Guinea pigs

CIV-41915 was passaged once in embryonated hen eggs and contact transmission experiments were performed as described [73]. Briefly, female Hartley strain guinea pigs (Charles River Laboratories) were intranasally inoculated with 10, 100 and 1,000 PFU (n = 4 per group). At 24 hpi, each inoculated animal was co-housed with a naïve contact animal for seven days. Nasal washes were collected from anesthetized animals on days 2, 4, 6 and 8 post-inoculation, and stored at -80°C prior to viral quantitation by plaque assay on MDCK cells. Experiments were performed under conditions of 10°C and 20% relative humidity and repeated three times.

Susceptibility to antiviral drugs

Stocks of oseltamivir carboxylate, zanamivir, peramivir, and amantadine hydrochloride (amantadine) (Sigma) were prepared in distilled water, filter-sterilized, and stored in aliquots at –20ºC. Susceptibility to NA inhibitors with WT viruses was assessed in a fluorescence-based assay using 100 μM fluorogenic substrate 2'-(4-methylumbelliferyl)-α-D-N-acetylneuraminic acid (MUNANA) (Sigma) [74]. IC50 values were calculated using GraphPad Prism 6 software (GraphPad Software, La Jolla, CA). Phenotypic susceptibility to amantadine was assessed using biological assays in MDCK cells [28].

Sequence-based maps

Viral protein sequences and associated metadata for H3, N2, and N8 influenza virus subtypes were obtained from the Influenza Research Database (fludb.org). For quality control, sequences that were either missing or contained erroneous amino acids were removed. Sequences for each viral protein were aligned using MUSCLE algorithm [75]. Hamming distances were calculated pairwise for all aligned protein sequences within each group (i.e. H3, N2, N8 stains) using the stringdist package in R [76]. Dimensional reduction of the resulting Hamming distance matrix was performed using cmdscale function in the base package of R. Goodness-of-fit (GOF) calculations were performed as previously described [32].

Enzyme-linked immunosorbent assay (ELISA)

Canine and human influenza virus-specific IgG levels in human sera were measured by ELISA. Briefly, MaxiSorp 96-well plates (Nunc) were coated with optimized dilutions of CIV-41915, rCIV-23 H3N8 or WY03 H3N2 infected or mock-infected MDCK cell extracts. Serial 3-fold sera dilutions (starting at 1/20) were added to blocked (1% BSA in PBS) plates, followed by a 2-hour incubation at room temperature. Bound antibodies were detected by addition of alkaline phosphatase-conjugated anti-human IgG (Mabtech cloneMT78), followed by p-nitrophenyl phosphate substrate. After color development, the reaction was stopped by addition of 0.5 M NaOH and absorbance was read at 405 nm. IgG antibody titers were determined by comparison of parallel sample titrations in wells coated with infected or mock-infected cell extracts. The titer was defined as the reciprocal of the highest sample dilution that gave an OD 2-fold greater against the infected versus the mock-infected cell extracts. Titers < 20 were assigned an arbitrary value of 10 for analysis.

HAI assays

Sera samples were treated with receptor-destroying enzyme (RDE, Denka Seiken) overnight at 37°C, heat inactivated for 30 minutes at 56°C and HAI assays performed with turkey red blood cells (RBCs) as described [77]. To evaluate the neutralizing activity of hmAbs, HAI assays were performed as described above with a starting concentration of 0.01 mg/ml of each of the hmAbs.

Serum neutralization assays

Two-fold serial dilutions of RDE-treated sera in virus infection media (DMEM containing penicillin, streptomycin, 0.5% BSA, and 5 μg/mL TPCK-treated trypsin) were mixed with 100 TCID50 of each virus for 1 hour at room temperature. Confluent MDCK cells were inoculated with the sera and virus mixture in quadruplicate wells for 24 hours at 32°C. Following the 24-hour incubation, the inoculum was removed, the cells were washed, new infection media added and incubated at 32°C until CPE was observed. The cells were then fixed with 4% formaldehyde and stained with Napthol blue black at room temperature overnight. The neutralizing antibody titer was calculated as the highest serum dilution that eliminated virus cytopathic effects in 50% of the wells.

Fluorescent-based microneutralization assay (FMNA)

To assess the neutralization activity of hmAbs a FMNA was performed as previously described with slight modifications [42]. MDCK cells were plated at 5x104 cells/well in 96-well tissue culture plates, incubated overnight and infected with the mCherry-expressing rCIV or WY03 H3N2 at a MOI of 0.005 in triplicate and incubated with media supplemented with 2-fold serial dilutions of hmAbs (starting concentration of 0.02 mg/ml). At 60 hpi, cells were washed with PBS and fluorescence was evaluated by fluorescence microscopy and quantified using a fluorescence plate reader (SpectralMax iD3, Molecular Devices) [42,43]. Infected cells in absence of hmAb represented 100% of infection. Cells in absence of viral infection were used to calculate the fluorescence background. Sigmoidal dose-response curves were generated (GraphPad Prism 7.0c) to calculate NT50values.

Enzyme-linked lectin assay (ELLA)

The inhibition of NA enzymatic activity by human sera samples was evaluated by ELLA as previously described [78,79]. Briefly, recombinant PR8 viruses expressing H4 HA (A/Mallard/Netherlands/1/1999 H4N6, BEI Resources NR-28996) and the NA from rCIV-11613, rCIV-23, or WY03 H3N2 viruses were used. Microtiter 96-well plates were coated with 100 μl of 50 μg/ml fetuin (Sigma) and incubated at 4°C overnight. The following day, heat-inactivated (30 minute at 56°C) human sera samples were 2-fold serially diluted (starting dilution 1/16) and mixed with the virus. The dilutions were then incubated on the fetuin-coated plates for 18 hour at 37°C and bound fetuin detected by incubation with 100 μl of peanut agglutinin conjugated to horseradish peroxidase (PNA-HRP) (1 μg/ml, Sigma) for 2 hour at room temperature followed by incubation with 3,3’,5,5’ tetramethylbenzidine substrate (TMB, Sigma) for 15 minutes at room temperature. Optical density was measured at 450 nm. For each assay, wells containing only virus (maximum signal) and wells containing only PBS-1% BSA (background signal) were included as internal controls. For analysis, background absorbance values were subtracted from the absorbance obtained from the human sera. The sera dilution at which 50% of the maximum signal was inhibited was concluded to be the NAI50 titer. When NAI titers were below the limit of detection (< 16), an arbitrary value of 8 was assigned.

Arrayed imaging reflectometry (AIR)

Preparation of hmAbs and label-free microarray sensor was described in detail elsewhere [44,80]. For high-multiplex sensing, duplicate spots were printed for each hmAb. Anti-FITC antibody spots were printed adjacent to each hmAb probe and used as the baseline for detection. Human IgG was spotted as a negative control for non-specific binding. Purified bovine IgG secondary antibodies were used for quality control of array printing. Experiments with human H3N2 vaccine strains and H3N2 and H3N8 rCIVs were conducted in 96-well plates. Two blocking solutions consisting of 10 mg/ml BSA in sodium acetate buffer (50 mM at pH 5.0) and 10% FBS in modified PBS-EDTA-Tween 20 (10 mM PBS, 5 mM EDTA, and 0.5% Tween 20 at pH 7.4) assay wash buffer (AWB) were prepared. After blocking, the chips were transferred for virus exposure. Solutions of human H3N2 strains and H3N2 and H3N8 rCIVs were prepared in 10-fold dilutions in 10% FBS in AWB. Blank 10% FBS solutions were used as negative control groups. In each case, three chips per condition were incubated overnight at room temperature, then washed in AWB several times. Finally, the chips were rinsed in distilled water and dried in nitrogen before array imaging. Once dried, chips were imaged immediately on a prototype AIR reader (Adarza BioSystems, Inc). AIR images were acquired in a 16-bit TIFF format, with exposure times varied from 50 ms to 1 second. The AIR image files were then analyzed using NIH-ImageJ (version 1.46r). The median value of the reflection intensities averaged from three chips represents the amount of material bound to each hmAb, and these data were normalized relative to the positive control (human IgG). All experiments were repeated at least twice.

Cross-reactivity of hmAbs by immunofluorescence and HeatMap

MDCK cells were plated at 1×105 cells/well in a 48-well tissue culture plate and mock-infected or infected with rCIV-41915, WY03 or HK68 H3N2 at a MOI of 3 at 33°C in triplicate. At 12 hpi, cells were fixed with 4% paraformaldehyde (PFA) and permeabilized for 15 minutes at room temperature with 0.5%Triton X-100 in PBS. Cells were incubated with 1 μg/ml of the indicated anti-HA hmAbs diluted in 2.5% BSA in PBS blocking solution for 1 hour at 37°C followed by an incubation with a 1:200 FITC-conjugated anti-human secondary Ab (Jackson Immuno Research). Fluorescence was evaluated under a fluorescent microscope (Olympus IX81) and images were captured (QIMAGING, Retiga 2000R). The fluorescence intensity of these images was measured using the ImageJ 1.51s software and data was displayed using a Heatmap visualization method (GraphPad Prism 7.0c). For analysis, the hmAb displaying the maximum signal for each viral HA was considered 100% and used to normalize data to reflect relative binding of each hmAb.

Statistical analysis

Statistical analysis was performed using the statistical package SPSS version 20.0 or Prism (GraphPad, La Jolla, CA). In vivo and in vitro studies were analyzed using two-tailed Student’s test. Serum IgG titers are expressed at geometric mean±95% CI. Differences between medians of pre-existing human antibodies were compared using Mann-Whitney U test. Correlation between HAI and MN titers were analyzed by Pearson correlation test. P-values <0.05 were considered significant.

Supporting information

S1 Fig

Cross-reactivity of hmAbs by immunofluorescence.

MDCK cells were infected (MOI of 3) with H3N2 or H3N8 rCIV, rWy03 H3N2 and HK68 H3N2. At 12 hpi cells were fixed, permeabilized and incubated with 1 μg/ml of the indicated hmAbs. After incubation with a secondary anti-human FITC-conjugated Ab, fluorescence was imaged under a fluorescent microscope. The hmAbs were grouped based on their ability to recognize H3N2 and H3N8 rCIV, and rWy03 H3N2. Representative images of the reactivity of the hmAbs against infected cells are shown in the right. The scale represents % of recognition. Scale bars, 200 𝜇m.

(TIF)

S1 Table

Human HAI titers against H3 CIV.

Sera was tested for HAI titers against select H3 CIVs.

(DOCX)

Funding Statement

This project was funded by the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Department of Health and Human Services, Centers of Excellence for Influenza Research and Surveillance (CEIRS) contract Nos. HHSN272201400004C, HHSN272201400005C, HHSN272201400006C, HHSN272201400007C, HHSN272201400008C and NIH grant P41GM103694 to RDC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

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2020 Apr; 16(4): e1008409.
Published online 2020 Apr 14. 10.1371/journal.ppat.1008409.r001

Decision Letter 0

Volker Thiel, Section Editor and Carolina B. Lopez, Associate Editor

4 Nov 2019

Dear Dr. Schultz-Cherry:

Thank you very much for submitting your manuscript "Characterizing Emerging Canine H3 Influenza Viruses: Challenging the Centers of Excellence for Influenza Research and Surveillance (CEIRS) Network Pipeline." (PPATHOGENS-D-19-01711) for review by PLOS Pathogens. Your manuscript was fully evaluated at the editorial level and by independent peer reviewers. The reviewers appreciated the attention to an important topic but identified some aspects of the manuscript that should be improved.

As you know, this manuscript is quite unusual, and as you can see particularly in comments from reviewers 1,2 there're some comments addressing the proposition of the manuscript that should be carefully addressed and clarified. In addition there're a number of comments concerning the scientific merits that, given the large number of collaborating laboratories, can be addressed in the context of a "minor" revision (though for one individual lab it would probably be a major revision). Finally, please check the entire manuscript for inconsistencies (methods, figure panels, writing style ect). As suggested by reviewer 2 it might be best if a single authors goes through the whole manuscript. 

We therefore ask you to modify the manuscript according to the review recommendations before we can consider your manuscript for acceptance. Your revisions should address all the specific points made by each reviewer. Please make sure that the wording of the manuscript and its title do not sound as a "sales pitch" and do a careful proofreading and editing of the final manuscripts. 

In addition, when you are ready to resubmit, please be prepared to provide the following:

(1) A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

(2) Two versions of the manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at gro.solp@serugif.

We hope to receive your revised manuscript within 60 days or less. If you anticipate any delay in its return, we ask that you let us know the expected resubmission date by replying to this email.

[LINK]

If you have any questions or concerns while you make these revisions, please let us know.

Sincerely,

Carolina B. Lopez, Ph.D.

Associate Editor

PLOS Pathogens

Volker Thiel

Section Editor

PLOS Pathogens

Kasturi Haldar

Editor-in-Chief

PLOS Pathogens

orcid.org/0000-0001-5065-158X

Grant McFadden

Editor-in-Chief

PLOS Pathogens

orcid.org/0000-0002-2556-3526

***********************

Reviewer's Responses to Questions

Part I - Summary

Please use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship.

Reviewer #1: This paper describes the efforts of a large consortium of CEIRS-funded investigators to perform quantitative risk assessment on the potential for human emergence of recently circulating canine H3 viruses. This is meant as a proof-of-principle of the utility of the CEIRS network for supporting large, multi-investigator efforts aimed at facing specific public health threats posed by influenza viruses. They describe a comprehensive assessment of phenotypic correlates of emergence potential for a small sample of canine H3N2 and H3N8 viruses. They show variable ability of canine viruses to replicate in primary human cells from upper vs. lower airway, that they can readily transmit via contact between guinea pigs, receptor binding profiles and pH characteristics of HA, that the viruses are sensitive to licensed antivirals, and that people born after 1970 have limited immune recognition of canine H3s. Plus a bunch of other stuff that I don’t need to list. Altogether, they conclude that canine H3 viruses pose a very limited emergence threat and suggest that they would be effectively controlled by existing antivirals and broadly-reactive anti-H3 therapeutic monoclonal Abs.

Overall, the paper presents a nice, comprehensive data set that addresses an important open question. With a couple of minor exceptions, the conclusions are well supported by the data, and the experimental approaches used are sound. Given the huge number of labs involved, the paper is well-written and cohesive, but is a little sloppy with some missing or unexplained figures and poor descriptions of some of the data/rationales. It also comes across as weirdly sales-pitchy in terms of the CEIRS angle. The paper would benefit from toning that down a bit and focusing on the science.

Reviewer #2: This is an unusual manuscript to be asked to review since its prime claim seems to be whether the NIAID CEIRS collaboration was able to provide research results that can be used to perform a risk assessment of the pandemic potential of influenza viruses from dogs. The risk assessment frameworks for the results to be applied to are the Influenza Risk Assessment Tool (IRAT), developed by CDC, and the Tool for Influenza Pandemic Risk Assessment (TIPRA), developed by WHO. The unusual question that has been posed is reflected in the unusual type of title of the manuscript.

Reviewer #3: In the research article entitled “Characterizing Emerging Canine H3 Influenza Viruses: Challenging the Centers of Excellence for Influenza Research and Surveillance (CEIRS) Network Pipeline”, the authors test the efficiency of the CEIRS network to respond to emerging threats. It is critical to perform these exercises to ensure productive cross-network interactions and assess response times. Importantly, the authors identify key areas, based on this exercise, that can be improved upon for future studies with emerging pandemic threats. This assessment is not only useful for the CEIRS network but also for other scientific centers tasked with addressing large research areas.

In addition to testing the CEIRS network response capability, the authors provide a wealth of data on emerging canine influenza viruses (CIV) as a pandemic threat. In this area the authors test the transmissibility of CIV in multiple animal models, characterize the phenotype of these viruses, and assess pre-existing immunity in the human population by age. Below are specific comments for each of the parameters tested of CIV that would assist the reader in following this comprehensive study.

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Part II – Major Issues: Key Experiments Required for Acceptance

Please use this section to detail the key new experiments or modifications of existing experiments that should be absolutely required to validate study conclusions.

Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject".

Reviewer #1: - Many of the experimental efforts did not include a representative H3N8 virus. Is there a reason for that? Without this, it is impossible to determine how broadly the results in question extend to all canine H3 viruses or just H3N2s.

- Figure 12 is missing

- The ferret transmission experiment uses a physiologically irrelevant infection dose of 10^6 pfu. I recognize that the flu field has settled on this dose as the gold standard for ferret infections for some reason, but it makes it impossible to determine whether the transmission results in that experiment reflect what would be expected during natural infection. This experiment should either be repeated using a relevant dose (as was done for the guinea pig experiments), removed form the paper, or the text should clearly highlight that the results may be non-representative of reality due to the experimental design.

Reviewer #2: The panel of viruses examined included natural H3N2 viruses from dogs and their RG equivalents, an H3N8 virus from dogs and two RGs based on it, along with a panel of human H3N2 viruses and some RG reassortants. The passage histories of the viruses have not been given and, for human H3N2 viruses at least, passage history and the changes acquired on passage need to be taken into serious consideration. Whether this is the case for canine H3 viruses ought also to be considered.

Table 3 shows the low pH inactivation of virus and the pH of syncytium formation by three viruses. The authors need to present a conclusion on whether the differences observed between the pH of inactivation of the two canine viruses is significantly different from the single example of a human H3N2 virus. The conclusion presented on lines 193-194 seems to require further justification.

The authors describe pathogenicity studies in mice and show that the DBA/2J mice are sensitive to infection by CIV-41915 and rCIV-1177. It might be worth explaining whether CIV-41915 and rCIV-1177 resulted in the death of those mice scored as fatally infected or whether they were culled having reached a humane end-point. It Is not clear what conclusion ought to be reached with such varying results between inbred mouse lines.

Figure 6 shows the results of transmission between infected ferrets or guinea pigs and direct contacts. The style of the results being presented ought to be generally similar. Figure 5A does not seem to look to be data from nine single animals (as described in the materials and methods (lines 633 to 634) and here it is implied that more than one virus was tested for ferrets).

Table 5 and Figure 6 show antiviral sensitivity results. Here different viruses were assessed by different methods. It is particularly striking that the absolute sensitivity of the different viruses to the drugs are different in the different assays. This is not perhaps surprising for the NA inhibitors (a sialidase inhibition assay versus a virus replication assay) but the assays for amantadine resistance have similar types of read-outs and the sensitivity of the viruses to amantadine appear to be very different indeed. That said, there is no doubt that the conclusions drawn overall are robust.

Antigenic differences between the viruses and circulating human viruses have been assessed in several ways. Amino acid sequence-based methods have been presented here extensively based on the claim (lines 246 to 248) that these methods can predict antigenic relatedness. Figure 7 shows a cluster analysis of the viruses but this does not directly assess the antigenic relatedness of the viruses within a subtype. No assessment of antigenic discrimination by post-infection ferret antisera has been given – yet the sera might well have been collected in the studies. With these sera the hypotheses presented in the paragraph from lines 271 to 280 (particularly lines 278 to 280) about the relatedness of the CIV viruses to old H3N2 viruses ought to have been tested directly.

Human immunity has been subsequently analysed. It is very surprising that there are such high titres seen to the A/Wyoming/3/2003 antigen by HI. I would presume that these sera would be considered to be the equivalent of pre-vaccination sera and a typical panel of pre-vaccination human sera might have mean GMTs of 30 to 100. These HI titres presented here for A/Wyoming/3/2003 look very much higher with some antisera having titres of over 1,000 and so the protocols used need to be reassessed by the panel of authors. With the HI panel showing such a concern for A/Wyoming/3/2003, all the other results also need to be carefully reassessed. 

Human post-vaccination sera were also analysed with two panels of sera. The authors describe a ‘baseline’ titre of neutralising antibody – I have presumed that this is pre-vaccination titres. It is a pity that these were not also assessed by HI assay as well as the VN assay. The results shown in figures 8B and 8C seem to show pre-vaccination and post-vaccination titres in the figure legend, but this is not what is shown in the figure which shows unvaccinated and vaccinated individuals. I was confused which was the correct interpretation. Pre- and post-vaccination paired sera would present the strongest evidence for any cross-reactivity or not.

Human mAbs were also analysed. Here a large panel of mAbs have been put into groups but the epitopes recognised by the panel of mAbs do not seem to have been defined and this makes interpretation of the results difficult. This also applies to Figure 11 – and the coding had to be deduced from the results. These results were also very difficult to interpret. Table 6 is not well described or well presented. The significance of the results in this whole section is difficult to establish.

One of the key elements of WHO’s TIPRA is for the experts to make an assessment of the confidence scores for each of the scoring elements. Here this does not seem to have been carried out; this could well have been done either in the results section or, perhaps better, in the discussion. This assessment would allow the authors to assess the significance of their own results. An important point of the risk assessment frameworks is to assess where there is limited information, thereby indicating what types of new data are required for improved risk assessments. The authors should take an opportunity to do this. They might cover the points raised here about difficulty in interpretation of some of the presented results.

The discussion, as it stands, repeats many of the points covered in the introduction. However, the discussion raises other very important points – particularly relating to the use of RG viruses. The authors offer a possible solution to this.

Reviewer #3: (No Response)

**********

Part III – Minor Issues: Editorial and Data Presentation Modifications

Please use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity.

Reviewer #1: - Rationale for the specific virus strain selections in fig 1 and fig 2 not well explained

- Line 158: data do not actually show a comparison between natural and recombinant versions of 11613, the natural isolate tested is 41915.

- Fig 2: no description of 2E anywhere, and 2D is not described in the legend

- Fig 3: x-axes would help. Also, the examination of a single canine isolate seems insufficient to draw broad conclusions. should compare representatives from H2N8 and H3N2 trees

- Line 279: Does this analysis provide any information not provided by a maximum likelihood phylogenetic tree of the relevant gene segments?

- Figure 7: For consistency, would be good to indicate the specific strains used in the human serological analyses in figure 8 on these plots.

- The high, age-independent ELISA and ELLA titers against the canine N2 and N8 proteins are surprising, as the authors note. Does this suggest that the sequence-based antigenic analysis fails to accurately capture something important about NA-Ab interactions?

- Figure 10E: legend is insufficient. What are values shown on heat map? Also, do the IF data suggest that AIR may miss some cross-reactivity? For example, 017-10116-5B03 shows maximal signal against rWY03 by IF but looks like it has no signal against this virus by AIR? It looks like the discordance between the two datasets is more complicated than simply a greater degree of sensitivity of AIR vs. IF as the authors claim. For example, 028-10134-4F03 apparently shows strong reactivity with rCIV-11613, moderate reactivity with rWY03 and little to no reactivity with rCIV-23 and HK68 by IF in figure 11, but the same mAb shows significant reactivity with the two canine IAVs but not HK68 or rWY03 by AIR in fig. 10. This is a qualitative difference in the predicted reactivity, not simply a difference in sensitivity. There may be others as well, but I don’t have time to scan through the whole thing. The authors should confirm whether the differences in results provided by the two methods are a consistent sensitivity issue or are more complicated.

Reviewer #2: Minor points

The manuscript has the signs of being written by several authors. I would suggest a single author goes through the whole manuscript (particularly in the materials and methods section) to ensure a consistent standard of use of English and the amount of detail given.

Line 31. The words ‘minimal risk’ are probably not the appropriate words to describe the outcome since ‘low risk’ would be better. It is easy to think of influenza viruses of lower risk to humans than the mammalian adapted canine influenza viruses.

Line 90. If the authors mean Low Pathogenicity (or Low Pathogenic) Avian Influenza viruses then this should be clearly stated as it has a precise meaning in OIE regulations and other legislation, whereas nonpathogenic is not well defined.

Line 96. It would be nice to provide a few more words about the nature of the human influenza viruses isolated from dogs and how well they were characterised.

Lines 201 and 211. PFU units were used for the infection of guinea pigs and TCID50 units were used for infecting ferrets. It would be good if the authors were able to equate the infecting doses.

Line 205. To reduce the possibility of confusion, I think the term ‘line’ should be used for the mice rather than the word ‘strain’, which might be taken to refer to a virus.

Lines 278 and 321 and Table 2 – I suspect the authors might be referring to A/Hong Kong/4801/2014 since this was presumably the vaccine virus used (line 321) rather than A/Hong Kong/1/2014.

Line 537. A reference to TEC MM is needed.

Line 540. I suspect the word ‘residue’ might well ought to have been ‘residual’.

Lines 592-593, the nature of the MDCK Luc9.1 cell needs to be given.

Reviewer #3: Specific comments:

Addition of a timeline figure to visually demonstrate the length each component took the contribution of each CEIRS centers and highlight areas where the networks worked together would be very useful for this exercise. Based on the discussion (line 430-431) it seems that all of this work was completed within 2 months – which is outstanding for a first test and highlights the power of the CEIRS network.

List viruses used in study

• Please add the passage history for both natural isolates and recombinant viruses to this list, as it may be distinct for each virus and important to understand if they were passaged in eggs prior to analysis for viral phenotypic characteristics. Especially since these details are not provided in the materials and methods section.

Replication in primary human respiratory epithelial cells and explants:

• CIV-1177 is denoted at recombinant in the text (line 163) but not in figure 2 or line 168. Given that both recombinant and non-recombinant strains were used, it is necessary to ensure that each is denoted accurately for the reader.

Transmission in ferrets and Guinea pigs

• Line 216-217 states there was ‘no airborne transmission’ of CIV-41915 yet one animal shed detectable virus on day 3 post infection. Could the authors please provide the serology for this airborne transmission study as well as the one for rCIV-1177 which is listed as data not shown.

Cross-reactive human and CIV antibodies

1. Figure 8 and 9 are very well done and present exciting observation critical to address pandemic emergence and the proportion of the population that is susceptible to CIV.

2. The use of AIR is important – but the data presented in figure 10 is difficult to interrupt for the general reader. The majority of the antibodies tested are not specific to any virus and overwhelm part E. In addition it is unclear how A-D relate to the antibodies presented in figure E. Please adjust this presentation of these data to make it more reader-friendly. Also, a different nomenclature for the antibodies might be useful. A minor note is that some rows do not line up on the left edge of the heatmap – which is surprising and this reviewer is left wondering whether the heatmaps were generated at multiple times and then spliced and fit together? It seems as though all the data should be imported into the same script for heatmap generation.

3. Could the authors please denote them in figure 10 so the reader can easily compare the AIR profile to the cross-reactive IF profile. Even though it is presented on Table 6 – it would be nice to assess it in the figures. On Table 6 – could the authors add dividing lines between groups and antibodies.

In vitro neutralization of H3 CIVs with hmMAbs

• Figure 12 was not included in the manuscript so nothing could be assessed. Although the NT titers are provided in Table 6 – suggesting that Figure 12 is unnecessary.

A final comment is that there are a number of grammatical typos that should be fixed. Some examples include lines 94 (their -> the), 106 (add in ‘to’ between obtained and inform), 348 (30 should come after ‘of the’).

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

    2020 Apr; 16(4): e1008409.
    Published online 2020 Apr 14. 10.1371/journal.ppat.1008409.r002

    Author response to Decision Letter 0

    22 Jan 2020

    Attachment

    Submitted filename:

      2020 Apr; 16(4): e1008409.
      Published online 2020 Apr 14. 10.1371/journal.ppat.1008409.r003

      Decision Letter 1

      Volker Thiel, Section Editor and Carolina B. Lopez, Associate Editor

      6 Feb 2020

      Dear Dr. Schultz-Cherry,

      Thank you very much for submitting your manuscript "Characterizing Emerging Canine H3 Influenza Viruses." for consideration at PLOS Pathogens. Your revised manuscript was reviewed by members of the editorial board.  We are likely to accept this manuscript for publication, providing that you modify the manuscript as indicated below:

      1. The phrase "the CEIRS network could work together..." is repeated at least three times in the first few pages of the manuscript (in the abstract, last paragraph of the intro, and first paragraph of the results section). Please remove this sentence from the abstract and introduction as it distracts from the scientific rationale of the work.

      2. In the abstract, please either expand on the "valuable lessons learned" (last sentence) or remove this sentence from the abstract as it is vague.

      3. Unites States is define as US in line 45, but this definition is not used in the remaining of the manuscript.

      4. line 58: A/Hong/Kong... please add influenza A virus.

      5. line 78: "preexisting antibody (Ab) immunity"...that wording is not conventional use preexisting antibodies or preexisting humoral immunity.

      Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. 

      When you are ready to resubmit, please upload the following:

      [1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. 

      Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

      [2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

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      Kasturi Haldar

      Editor-in-Chief

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      orcid.org/0000-0001-5065-158X

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      Editor-in-Chief

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        2020 Apr; 16(4): e1008409.
        Published online 2020 Apr 14. 10.1371/journal.ppat.1008409.r004

        Author response to Decision Letter 1

        14 Feb 2020

        Attachment

        Submitted filename:

          2020 Apr; 16(4): e1008409.
          Published online 2020 Apr 14. 10.1371/journal.ppat.1008409.r005

          Decision Letter 2

          Volker Thiel, Section Editor and Carolina B. Lopez, Associate Editor

          19 Feb 2020

          Dear Dr. Schultz-Cherry,

          We are pleased to inform you that your manuscript 'Characterizing Emerging Canine H3 Influenza Viruses.' has been provisionally accepted for publication in PLOS Pathogens.

          Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch within two working days with a set of requests.

          Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

          IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

          Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

          Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Pathogens.

          Best regards,

          Carolina B. Lopez, Ph.D.

          Associate Editor

          PLOS Pathogens

          Volker Thiel

          Section Editor

          PLOS Pathogens

          Kasturi Haldar

          Editor-in-Chief

          PLOS Pathogens

          orcid.org/0000-0001-5065-158X

          Michael Malim

          Editor-in-Chief

          PLOS Pathogens

          orcid.org/0000-0002-7699-2064

          ***********************************************************

          Reviewer Comments (if any, and for reference):

            2020 Apr; 16(4): e1008409.
            Published online 2020 Apr 14. 10.1371/journal.ppat.1008409.r006

            Acceptance letter

            Volker Thiel, Section Editor and Carolina B. Lopez, Associate Editor

            8 Apr 2020

            Dear Dr. Schultz-Cherry,

            We are delighted to inform you that your manuscript, "Characterizing Emerging Canine H3 Influenza Viruses.," has been formally accepted for publication in PLOS Pathogens.

            We have now passed your article onto the PLOS Production Department who will complete the rest of the pre-publication process. All authors will receive a confirmation email upon publication.

            The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any scientific or type-setting errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript. Note: Proofs for Front Matter articles (Pearls, Reviews, Opinions, etc...) are generated on a different schedule and may not be made available as quickly.

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            Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Pathogens.

            Best regards,

            Kasturi Haldar

            Editor-in-Chief

            PLOS Pathogens

            orcid.org/0000-0001-5065-158X

            Michael Malim

            Editor-in-Chief

            PLOS Pathogens

            orcid.org/0000-0002-7699-2064


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