Improving risk assessment of the emergence of novel influenza A viruses by incorporating environmental surveillance

Environmental transmission of influenza A virus in mallards

IMPORTANCE

Wild birds are the natural reservoir hosts of influenza A viruses. Highly pathogenic strains of influenza A viruses pose risks to wild birds, poultry, and human health. Thus, understanding how these viruses are transmitted between birds is critical. We conducted an experiment where we experimentally infected mallards which are ducks that are commonly exposed to influenza viruses. We exposed several contact ducks to the experimentally infected duck to estimate the probability that a contact duck would become infected from either exposure to the virus shed directly from the infected duck or shared water contaminated with the virus from the infected duck. We found that environmental transmission from contaminated water best predicted the probability of transmission to naïve contact ducks, relatively low levels of virus in the water were sufficient to cause infection, and the probability of a naïve duck becoming infected varied over time.

Environmental DNA/RNA for pathogen and parasite detection, surveillance, and ecology

Detection of pathogens, parasites, and other symbionts in environmental samples via eDNA/eRNA (collectively eNA) is an increasingly important source of information about their occurrence and activity. There is great potential for using such detections as a proxy for infection of host organisms in connected habitats, for pathogen monitoring and surveillance, and for early warning systems for disease. However, many factors require consideration, and appropriate methods developed and verified, in order that eNA detections can be reliably interpreted and adopted for surveillance and assessment of disease risk, and potentially inclusion in international standards, such as the World Organisation for Animal Health guidelines. Disease manifestation results from host-symbiont-environment interactions between hosts, demanding a multifactorial approach to interpretation of eNA signals.

Persistence of low pathogenic avian influenza virus in artificial streams mimicking natural conditions of waterfowl habitats in the Mediterranean climate

Avian influenza viruses (AIVs) can affect wildlife, poultry, and humans, so a One Health perspective is needed to optimize mitigation strategies. Migratory waterfowl globally spread AIVs over long distances. Therefore, the study of AIV persistence in waterfowl staging and breeding areas is key to understanding their transmission dynamics and optimizing management strategies. Here, we used artificial streams mimicking natural conditions of waterfowl habitats in the Mediterranean climate (day/night cycles of photosynthetic active radiation and temperature, low water velocity, and similar microbiome to lowland rivers and stagnant water bodies) and then manipulated temperature and sediment presence (i.e., 10-13 °C vs. 16-18 °C, and presence vs. absence of sediments). An H1N1 low pathogenic AIV (LPAIV) strain was spiked in the streams, and water and sediment samples were collected at different time points until 14 days post-spike to quantify viral RNA and detect infectious particles. Viral RNA was detected until the end of the experiment in both water and sediment samples. In water samples, we observed a significant combined effect of temperature and sediments in viral decay, with higher viral genome loads in colder streams without sediments. In sediment samples, we didn't observe any significant effect of temperature. In contrast to prior laboratory-controlled studies that detect longer persistence times, infectious H1N1 LPAIV was isolated in water samples till 2 days post-spike, and none beyond. Infectious H1N1 LPAIV wasn't isolated from any sediment sample. Our results suggest that slow flowing freshwater surface waters may provide conditions facilitating bird-to-bird transmission for a short period when water temperature are between 10 and 18 °C, though persistence for extended periods (e.g., weeks or months) may be less likely. We hypothesize that experiments simulating real environments, like the one described here, provide a more realistic approach for assessing environmental persistence of AIVs.

Avian influenza A virus susceptibility, infection, transmission, and antibody kinetics in European starlings

Avian influenza A viruses (IAVs) pose risks to public, agricultural, and wildlife health. Bridge hosts are spillover hosts that share habitat with both maintenance hosts (e.g., mallards) and target hosts (e.g., poultry). We conducted a comprehensive assessment of European starlings (Sturnus vulgaris), a common visitor to both urban and agricultural environments, to assess whether this species might act as a potential maintenance or bridge host for IAVs. First, we experimentally inoculated starlings with a wild bird IAV to investigate susceptibility and replication kinetics. Next, we evaluated whether IAV might spill over to starlings from sharing resources with a widespread IAV reservoir host. We accomplished this using a specially designed transmission cage to simulate natural environmental transmission by exposing starlings to water shared with IAV-infected mallards (Anas platyrhynchos). We then conducted a contact study to assess intraspecies transmission between starlings. In the initial experimental infection study, all inoculated starlings shed viral RNA and seroconverted. All starlings in the transmission study became infected and shed RNA at similar levels. All but one of these birds seroconverted, but detectable antibodies were relatively transient, falling to negative levels in a majority of birds by 59 days post contact. None of the contact starlings in the intraspecies transmission experiment became infected. In summary, we demonstrated that starlings may have the potential to act as IAV bridge hosts if they share water with IAV-infected waterfowl. However, starlings are unlikely to act as maintenance hosts due to limited, if any, intraspecies transmission. In addition, starlings have a relatively brief antibody response which should be considered when interpreting serology from field samples. Further study is needed to evaluate the potential for transmission from starlings to poultry, a possibility enhanced by starling's behavioral trait of forming very large flocks which can descend on poultry facilities when natural resources are scarce.

Experimental virus evolution in cancer cell monolayers, spheroids, and tissue explants

Viral laboratory evolution has been used for different applications, such as modeling viral emergence, drug-resistance prediction, and therapeutic virus optimization. However, these studies have been mainly performed in cell monolayers, a highly simplified environment, raising concerns about their applicability and relevance. To address this, we compared the evolution of a model virus in monolayers, spheroids, and tissue explants. We performed this analysis in the context of cancer virotherapy by performing serial transfers of an oncolytic vesicular stomatitis virus (VSV-Δ51) in 4T1 mouse mammary tumor cells. We found that VSV-Δ51 gained fitness in each of these three culture systems, and that adaptation to the more complex environments (spheroids or explants) correlated with increased fitness in monolayers. Most evolved lines improved their ability to suppress β-interferon secretion compared to the VSV-Δ51 founder, suggesting that the selective pressure exerted by antiviral innate immunity was important in the three systems. However, system-specific patterns were also found. First, viruses evolved in monolayers remained more oncoselective that those evolved in spheroids, since the latter showed concomitant adaptation to non-tumoral mouse cells. Second, deep sequencing indicated that viral populations evolved in monolayers or explants tended to be more genetically diverse than those evolved in spheroids. Finally, we found highly variable outcomes among independent evolutionary lines propagated in explants. We conclude that experimental evolution in monolayers tends to be more reproducible than in spheroids or explants, and better preserves oncoselectivity. Our results also suggest that monolayers capture at least some relevant selective pressures present in more complex systems.

Highly Pathogenic Avian Influenza Viruses at the Wild-Domestic Bird Interface in Europe: Future Directions for Research and Surveillance

Highly pathogenic avian influenza (HPAI) outbreaks in wild birds and poultry are no longer a rare phenomenon in Europe. In the past 15 years, HPAI outbreaks—in particular those caused by H5 viruses derived from the A/Goose/Guangdong/1/1996 lineage that emerged in southeast Asia in 1996—have been occuring with increasing frequency in Europe. Between 2005 and 2020, at least ten HPAI H5 incursions were identified in Europe resulting in mass mortalities among poultry and wild birds. Until 2009, the HPAI H5 virus outbreaks in Europe were caused by HPAI H5N1 clade 2.2 viruses, while from 2014 onwards HPAI H5 clade 2.3.4.4 viruses dominated outbreaks, with abundant genetic reassortments yielding subtypes H5N1, H5N2, H5N3, H5N4, H5N5, H5N6 and H5N8. The majority of HPAI H5 virus detections in wild and domestic birds within Europe coincide with southwest/westward fall migration and large local waterbird aggregations during wintering. In this review we provide an overview of HPAI H5 virus epidemiology, ecology and evolution at the interface between poultry and wild birds based on 15 years of avian influenza virus surveillance in Europe, and assess future directions for HPAI virus research and surveillance, including the integration of whole genome sequencing, host identification and avian ecology into risk-based surveillance and analyses.

Mammalian pathogenicity and transmissibility of low pathogenic avian influenza H7N1 and H7N3 viruses isolated from North America in 2018

Low pathogenic avian influenza (LPAI) H7 subtype viruses are infrequently, but persistently, associated with outbreaks in poultry in North America. These LPAI outbreaks provide opportunities for the virus to develop enhanced virulence and transmissibility in mammals and have previously resulted in both occasional acquisition of a highly pathogenic avian influenza (HPAI) phenotype in birds and sporadic cases of human infection. Two notable LPAI H7 subtype viruses caused outbreaks in 2018 in North America: LPAI H7N1 virus in chickens and turkeys, representing the first confirmed H7N1 infection in poultry farms in the United States, and LPAI H7N3 virus in turkeys, a virus subtype often associated with LPAI-to-HPAI phenotypes. Here, we investigated the replication capacity of representative viruses from these outbreaks in human respiratory tract cells and mammalian pathogenicity and transmissibility in the mouse and ferret models. We found that the LPAI H7 viruses replicated to high titre in human cells, reaching mean peak titres generally comparable to HPAI H7 viruses. Replication was efficient in both mammalian species, causing mild infection, with virus primarily limited to respiratory tract tissues. The H7 viruses demonstrated a capacity to transmit to naïve ferrets in a direct contact setting. These data support the need to perform routine risk assessments of LPAI H7 subtype viruses, even in the absence of confirmed human infection.

A comparison of amplification methods to detect Avian Influenza viruses in California wetlands targeted via remote sensing of waterfowl

Migratory waterfowl, including geese and ducks, are indicated as the primary reservoir of avian influenza viruses (AIv) which can be subsequently spread to commercial poultry. The US Department of Agriculture's (USDA) surveillance efforts of waterfowl for AIv have been largely discontinued in the contiguous United States. Consequently, the use of technologies to identify areas of high waterfowl density and detect the presence of AIv in habitat such as wetlands has become imperative. Here we identified two high waterfowl density areas in California using processed NEXt generation RADar (NEXRAD) and collected water samples to test the efficacy of two tangential flow ultrafiltration methods and two nucleic acid based AIv detection assays. Whole-segment amplification and long-read sequencing yielded more positive samples than standard M-segment qPCR methods (57.6% versus 3.0%, p < .0001). We determined that this difference in positivity was due to mismatches in published primers to our samples and that these mismatches would result in failing to detect in the vast majority of currently sequenced AIv genomes in public databases. The whole segment sequences were subsequently used to provide subtype and potential host information of the AIv environmental reservoir. There was no statistically significant difference in sequencing reads recovered from the Rexeed^TM filtration compared to the unfiltered surface water. This overall approach combining remote sensing, filtration and sequencing provides a novel and potentially more effective, surveillance approach for AIv.

Percolation models of pathogen spillover

Predicting pathogen spillover requires counting spillover events and aligning such counts with process-related covariates for each spillover event. How can we connect our analysis of spillover counts to simple, mechanistic models of pathogens jumping from reservoir hosts to recipient hosts? We illustrate how the pathways to pathogen spillover can be represented as a directed graph connecting reservoir hosts and recipient hosts and the number of spillover events modelled as a percolation of infectious units along that graph. Percolation models of pathogen spillover formalize popular intuition and management concepts for pathogen spillover, such as the inextricably multilevel nature of cross-species transmission, the impact of covariance between processes such as pathogen shedding and human susceptibility on spillover risk, and the assumptions under which the effect of a management intervention targeting one process, such as persistence of vectors, will translate to an equal effect on the overall spillover risk. Percolation models also link statistical analysis of spillover event datasets with a mechanistic model of spillover. Linear models, one might construct for process-specific parameters, such as the log-rate of shedding from one of several alternative reservoirs, yield a nonlinear model of the log-rate of spillover. The resulting nonlinearity is approximately piecewise linear with major impacts on statistical inferences of the importance of process-specific covariates such as vector density. We recommend that statistical analysis of spillover datasets use piecewise linear models, such as generalized additive models, regression clustering or ensembles of linear models, to capture the piecewise linearity expected from percolation models. We discuss the implications of our findings for predictions of spillover risk beyond the range of observed covariates, a major challenge of forecasting spillover risk in the Anthropocene. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.