Resistance Mutation R292K Is Induced in Influenza A(H6N2) Virus by Exposure of Infected Mallards to Low Levels of Oseltamivir

Resistance to neuraminidase inhibitors (NAIs) is problematic as these drugs constitute the major treatment option for severe influenza. Extensive use of the NAI oseltamivir (Tamiflu®) results in up to 865 ng/L of its active metabolite oseltamivir carboxylate (OC) in river water. There one of the natural reservoirs of influenza A, dabbling ducks, can be exposed. We previously demonstrated that an influenza A(H1N1) virus in mallards (Anas platyrhynchos) exposed to 1 µg/L of OC developed oseltamivir resistance through the mutation H274Y (N2-numbering). In this study, we assessed the resistance development in an A(H6N2) virus, which belongs to the phylogenetic N2 group of neuraminidases with distinct functional and resistance characteristics. Mallards were infected with A(H6N2) while exposed to 120 ng/L, 1.2 µg/L or 12 µg/L of OC in their sole water source. After 4 days with 12 µg/L of OC exposure, the resistance mutation R292K emerged and then persisted. Drug sensitivity was decreased ≈13,000-fold for OC and ≈7.8-fold for zanamivir. Viral shedding was similar when comparing R292K and wild-type virus indicating sustained replication and transmission. Reduced neuraminidase activity and decrease in recovered virus after propagation in embryonated hen eggs was observed in R292K viruses. The initial, but not the later R292K isolates reverted to wild-type during egg-propagation, suggesting a stabilization of the mutation, possibly through additional mutations in the neuraminidase (D113N or D141N) or hemagglutinin (E216K). Our results indicate a risk for OC resistance development also in a N2 group influenza virus and that exposure to one NAI can result in a decreased sensitivity to other NAIs as well. If established in influenza viruses circulating among wild birds, the resistance could spread to humans via re-assortment or direct transmission. This could potentially cause an oseltamivir-resistant pandemic; a serious health concern as preparedness plans rely heavily on oseltamivir before vaccines can be mass-produced.     

Role for nucleolin/Nsr1 in the cellular localization of topoisomerase I

Nucleolin functions in ribosome biogenesis and contains an acidic N terminus that binds nuclear localization sequences. In previous work we showed that human nucleolin associates with the N-terminal region of human topoisomerase I (Top1). We have now mapped the topoisomerase I interaction domain of nucleolin to the N-terminal 225 amino acids. We also show that the Saccharomyces cerevisiae nucleolin ortholog, Nsr1p, physically interacts with yeast topoisomerase I, yTop1p. Studies of isogenic NSR1(+) and Deltansr1 strains indicate that NSR1 is important in determining the cellular localization of yTop1p. Moreover, deletion of NSR1 reduces sensitivity to camptothecin, an antineoplastic topoisomerase I inhibitor. By contrast, Deltansr1 cells are hypersensitive to the topoisomerase II-targeting drug amsacrine. These findings indicate that nucleolin/Nsr1 is involved in the cellular localization of Top1 and that this localization may be important in determining sensitivity to drugs that target topoisomerases.     

Environmental levels of the antiviral oseltamivir induce development of resistance mutation H274Y in influenza A/H1N1 virus in mallards

Oseltamivir (Tamiflu®) is the most widely used drug against influenza infections and is extensively stockpiled worldwide as part of pandemic preparedness plans. However, resistance is a growing problem and in 2008–2009, seasonal human influenza A/H1N1 virus strains in most parts of the world carried the mutation H274Y in the neuraminidase gene which causes resistance to the drug. The active metabolite of oseltamivir, oseltamivir carboxylate (OC), is poorly degraded in sewage treatment plants and surface water and has been detected in aquatic environments where the natural influenza reservoir, dabbling ducks, can be exposed to the substance. To assess if resistance can develop under these circumstances, we infected mallards with influenza A/H1N1 virus and exposed the birds to 80 ng/L, 1 µg/L and 80 µg/L of OC through their sole water source. By sequencing the neuraminidase gene from fecal samples, we found that H274Y occurred at 1 µg/L of OC and rapidly dominated the viral population at 80 µg/L. IC₅₀ for OC was increased from 2–4 nM in wild-type viruses to 400–700 nM in H274Y mutants as measured by a neuraminidase inhibition assay. This is consistent with the decrease in sensitivity to OC that has been noted among human clinical isolates carrying H274Y. Environmental OC levels have been measured to 58–293 ng/L during seasonal outbreaks and are expected to reach µg/L-levels during pandemics. Thus, resistance could be induced in influenza viruses circulating among wild ducks. As influenza viruses can cross species barriers, oseltamivir resistance could spread to human-adapted strains with pandemic potential disabling oseltamivir, a cornerstone in pandemic preparedness planning. We propose surveillance in wild birds as a measure to understand the resistance situation in nature and to monitor it over time. Strategies to lower environmental levels of OC include improved sewage treatment and, more importantly, a prudent use of antivirals.     

Epidemic management and control through risk-dependent individual contact interventions

Testing, contact tracing, and isolation (TTI) is an epidemic management and control approach that is difficult to implement at scale because it relies on manual tracing of contacts. Exposure notification apps have been developed to digitally scale up TTI by harnessing contact data obtained from mobile devices; however, exposure notification apps provide users only with limited binary information when they have been directly exposed to a known infection source. Here we demonstrate a scalable improvement to TTI and exposure notification apps that uses data assimilation (DA) on a contact network. Network DA exploits diverse sources of health data together with the proximity data from mobile devices that exposure notification apps rely upon. It provides users with continuously assessed individual risks of exposure and infection, which can form the basis for targeting individual contact interventions. Simulations of the early COVID-19 epidemic in New York City are used to establish proof-of-concept. In the simulations, network DA identifies up to a factor 2 more infections than contact tracing when both harness the same contact data and diagnostic test data. This remains true even when only a relatively small fraction of the population uses network DA. When a sufficiently large fraction of the population (≳ 75%) uses network DA and complies with individual contact interventions, targeting contact interventions with network DA reduces deaths by up to a factor 4 relative to TTI. Network DA can be implemented by expanding the computational backend of existing exposure notification apps, thus greatly enhancing their capabilities. Implemented at scale, it has the potential to precisely and effectively control future epidemics while minimizing economic disruption.     

THE IMPORTANCE OF MOSQUITO BEHAVIOURAL ADAPTATIONS TO MALARIA CONTROL IN AFRICA

Over the past decade the use of long‐lasting insecticidal nets (LLINs), in combination with improved drug therapies, indoor residual spraying (IRS), and better health infrastructure, has helped reduce malaria in many African countries for the first time in a generation. However, insecticide resistance in the vector is an evolving threat to these gains. We review emerging and historical data on behavioral resistance in response to LLINs and IRS. Overall the current literature suggests behavioral and species changes may be emerging, but the data are sparse and, at times unconvincing. However, preliminary modeling has demonstrated that behavioral resistance could have significant impacts on the effectiveness of malaria control. We propose seven recommendations to improve understanding of resistance in malaria vectors. Determining the public health impact of physiological and behavioral insecticide resistance is an urgent priority if we are to maintain the significant gains made in reducing malaria morbidity and mortality.     

Impacts of dispersal on rapid adaptation and dynamic stability of Daphnia in fluctuating environments

Prior ecological research has shown that spatial processes can enhance the temporal stability of populations in fluctuating environments. Less explored is the effect of dispersal on rapid adaptation and its concomitant impact on population dynamics. For asexually reproducing populations, theory predicts that dispersal in fluctuating environments can facilitate asynchrony among clones and enhance stability by reducing temporal variability of total population abundance. This effect is predicted when clones exhibit heritable variation in environmental optima and when fluctuations occur asynchronously among patches. We tested this in the field using artificial ponds and metapopulations composed of a diverse assemblage of Daphnia pulex clones. We directly manipulated dispersal presence/absence and environmental fluctuations in the form of nutrient pulses. Consistent with predictions, dispersal enhanced temporal asynchrony among clones in the presence of nutrient pulses; this in turn stabilized population dynamics. This effect only emerged when patches experienced spatially asynchronous nutrient pulses (dispersal had no effect when patches were synchronously pulsed). Clonal asynchrony was driven by strong positive selection for a single clone that exhibited a performance advantage under conditions of low resource availability. Our work highlights the importance of dispersal as a driver of eco-evolutionary dynamics and population stability in variable environments.     

Topoisomerase IIB and an extracellular nuclease interact to digest sperm DNA in an apoptotic-like manner

We previously demonstrated that mammalian spermatozoa contain a nuclease activity that cleaves DNA into loop-sized fragments. We show here that this activity is mediated by a nuclear matrix-associated topoisomerase IIB (TOP2B) interacting with an extracellular Mn2+/Ca2+-dependent nuclease. Together, these enzymes cleave all of the DNA into fragments of 50 kb, and this cleavage can be reversed by EDTA. If dithiothreitol is included, the nuclease digests the DNA, and if the protamines are removed the DNA is completely digested. A similar, TOP2B-mediated, chromatin fragmentation, which is reversible, followed by digestion of the DNA by an intracellular nuclease occurs in somatic cells during apoptosis. The extracellular location of the sperm nuclease made it possible to reconstitute the fragmentation activity in isolated spermatozoa, thus allowing us to identify two novel aspects of the mechanism. First, the fragmentation of all of the DNA to 50 kb by TOP2B required the addition of the extracellular nuclease or factor. Second, the subsequent, complete digestion of the DNA by the nuclease could be inhibited by etoposide, suggesting that the nuclease digestion requires TOP2B religation of the cleaved DNA. These data are the first demonstration of an active TOP2B in spermatozoa, suggesting this inert chromatin may be more active than previously thought. They also show that the unique chromatin structure of spermatozoa may provide an important model to study the regulated degradation of chromatin by TOP2B and associated nucleases.     

Prevalence and phylogeny of coronaviruses in wild birds from the Bering Strait area (Beringia)

Coronaviruses (CoVs) can cause mild to severe disease in humans and animals, their host range and environmental spread seem to have been largely underestimated, and they are currently being investigated for their potential medical relevance. Infectious bronchitis virus (IBV) belongs to gamma-coronaviruses and causes a costly respiratory viral disease in chickens. The role of wild birds in the epidemiology of IBV is poorly understood. In the present study, we examined 1,002 cloacal and faecal samples collected from 26 wild bird species in the Beringia area for the presence of CoVs, and then we performed statistical and phylogenetic analyses. We detected diverse CoVs by RT-PCR in wild birds in the Beringia area. Sequence analysis showed that the detected viruses are gamma-coronaviruses related to IBV. These findings suggest that wild birds are able to carry gamma-coronaviruses asymptomatically. We concluded that CoVs are widespread among wild birds in Beringia, and their geographic spread and frequency is higher than previously realised. Thus, Avian CoV can be efficiently disseminated over large distances and could be a genetic reservoir for future emerging pathogenic CoVs. Considering the great animal health and economic impact of IBV as well as the recent emergence of novel coronaviruses such as SARS-coronavirus, it is important to investigate the role of wildlife reservoirs in CoV infection biology and epidemiology.     

Non-alcoholic fatty liver disease in a rural,physically active,low income population in Sri Lanka

Background

Non-alcoholic fatty liver disease (NAFLD) is recognized as a metabolic disorder largely seen in urbanized populations. The purpose of this study was to assess prevalence and risk factors for NAFLD in a rural, physically active, economically deprived population in Sri Lanka.

Methods

By visiting individual households in the community, 35-64 year old adults resident in two selected estates in the Nuwara Eliya District of Sri Lanka, were invited to participate in the study. Blood pressure and anthropometric measurements were made on all participants. Blood samples were obtained for the assay of fasting glucose, serum lipids, serum insulin and alanine aminotransferase. NAFLD was diagnosed on established ultrasound criteria for fatty liver in the absence of hepatitis B and C markers and high alcohol consumption.

Results

Of those invited, 403 (65%) participated in the study. Almost all participants were either Indian or Sri Lankan Tamils and 53% were females. Prevalence of NAFLD was 18% in this population. Twice as many males were diagnosed as having NAFLD compared to females. Male sex, high BMI, high waist circumference, high diastolic blood pressure and high plasma glucose levels were significant predictors of NAFLD.

Conclusion

Nearly one in five people in this predominantly Indian Tamil, rural, physically active, economically deprived population had NAFLD. The condition was associated with constituent features of the metabolic syndrome. These results support studies reporting ethnic variations in disease susceptibility and suggest that genetic factors may also play a role in determining disease risk.

     

Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics

A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and, over the last two decades, have been applied to infectious disease epidemiology. For any system of interest, the ideal filter depends on the nonlinearity and complexity of the model to which it is applied, the quality and abundance of observations being entrained, and the ultimate application (e.g. forecast, parameter estimation, etc.). Here, we compare the performance of six state-of-the-art filter methods when used to model and forecast influenza activity. Three particle filters—a basic particle filter (PF) with resampling and regularization, maximum likelihood estimation via iterated filtering (MIF), and particle Markov chain Monte Carlo (pMCMC)—and three ensemble filters—the ensemble Kalman filter (EnKF), the ensemble adjustment Kalman filter (EAKF), and the rank histogram filter (RHF)—were used in conjunction with a humidity-forced susceptible-infectious-recovered-susceptible (SIRS) model and weekly estimates of influenza incidence. The modeling frameworks, first validated with synthetic influenza epidemic data, were then applied to fit and retrospectively forecast the historical incidence time series of seven influenza epidemics during 2003–2012, for 115 cities in the United States. Results suggest that when using the SIRS model the ensemble filters and the basic PF are more capable of faithfully recreating historical influenza incidence time series, while the MIF and pMCMC do not perform as well for multimodal outbreaks. For forecast of the week with the highest influenza activity, the accuracies of the six model-filter frameworks are comparable; the three particle filters perform slightly better predicting peaks 1–5 weeks in the future; the ensemble filters are more accurate predicting peaks in the past.