Exploring associations between viral titer measurements and disease outcomes in ferrets inoculated with 125 contemporary influenza A viruses.

As use of the ferret model to study influenza A virus (IAV) pathogenicity increases, periodic assessment of data generated in this model is warranted, to identify features associated with virus replication throughout the respiratory tract and to refine future analyses. However, protocol-specific differences present between independent laboratories limit easy aggregation of virological data. We compiled viral titer and clinical data from >1,000 ferrets inoculated with 125 contemporary IAV under a consistent experimental protocol (including high- and low-pathogenicity avian, swine-origin, and human viruses, spanning H1, H2, H3, H5, H7, and H9 subtypes) and examined which meaningful and statistically supported associations were present among numerous quantitative measurements. Viral titers correlated positively between ferret nasal turbinate tissue, lung tissue, and nasal wash specimens, though the strength of the associations varied, notably regarding the particular nasal wash summary measure employed and properties of the virus itself. Use of correlation coefficients and mediation analyses further supported the interconnectedness of viral titer measurements taken at different sites throughout the respiratory tract. IAV possessing mammalian host adaptation markers in the HA and PB2 exhibited more rapid growth in the ferret upper respiratory tract early after infection, supported by quantities derived from infectious titer data to capture infection progression, compared with viruses bearing hallmarks of avian IAV. Collectively, this work identifies summary metrics most closely linked with virological and phenotypic outcomes in ferrets, supporting continued refinement of data analyzed from in vivo experimentation, notably from studies conducted to evaluate the public health risk posed by novel and emerging IAV.IMPORTANCEFerrets are frequently employed to study the pandemic potential of novel and emerging influenza A viruses. However, systematic retrospective analyses of data generated from these experiments are rarely performed, limiting our ability to identify trends in this data and explore how analyses can be refined. Using logarithmic viral titer and clinical data aggregated from one research group over 20 years, we assessed which meaningful and statistically supported associations were present among numerous quantitative measurements obtained from influenza A virus (IAV)-infected ferrets, including those capturing viral titers, infection progression, and disease severity. We identified numerous linear correlations between parameters assessing virus replication at discrete sites in vivo, including parameters capturing infection progression not frequently employed in the field, and sought to investigate the interconnected nature of these associations. This work supports continued refinement of data analyzed from in vivo experimentation, notably from studies which evaluate the public health risk posed by IAV.

Apolipoprotein A1 and high-density lipoprotein limit low-density lipoprotein transcytosis by binding SR-B1.

Atherosclerosis results from the deposition and oxidation of LDL and immune cell infiltration in the sub-arterial space leading to arterial occlusion. Studies have shown that transcytosis transports circulating LDL across endothelial cells lining blood vessels. LDL transcytosis is initiated by binding to either scavenger receptor B1 (SR-B1) or activin A receptor-like kinase 1 on the apical side of endothelial cells leading to its transit and release on the basolateral side. HDL is thought to partly protect individuals from atherosclerosis due to its ability to remove excess cholesterol and act as an antioxidant. Apolipoprotein A1 (APOA1), an HDL constituent, can bind to SR-B1, raising the possibility that APOA1/HDL can compete with LDL for SR-B1 binding, thereby limiting LDL deposition in the sub-arterial space. To examine this possibility, we used in vitro approaches to quantify the internalization and transcytosis of fluorescent LDL in coronary endothelial cells. Using microscale thermophoresis and affinity capture, we find that SR-B1 and APOA1 interact and that binding is enhanced when using the cardioprotective variant of APOA1 termed Milano (APOA1-Milano). In male mice, transiently increasing the levels of HDL reduced the acute deposition of fluorescently labeled LDL in the atheroprone inner curvature of the aorta. Reduced LDL deposition was also observed when increasing circulating wild-type APOA1 or the APOA1-Milano variant, with a more robust inhibition from the APOA1-Milano. The results suggest that HDL may limit SR-B1-mediated LDL transcytosis and deposition, adding to the mechanisms by which it can act as an atheroprotective particle.

Utility of Human In Vitro Data in Risk Assessments of Influenza A Virus Using the Ferret Model.

As influenza A viruses (IAV) continue to cross species barriers and cause human infection, the establishment of risk assessment rubrics has improved pandemic preparedness efforts. In vivo pathogenicity and transmissibility evaluations in the ferret model represent a critical component of this work. As the relative contribution of in vitro experimentation to these rubrics has not been closely examined, we sought to evaluate to what extent viral titer measurements over the course of in vitro infections are predictive or correlates of nasal wash and tissue measurements for IAV infections in vivo. We compiled data from ferrets inoculated with an extensive panel of over 50 human and zoonotic IAV (inclusive of swine-origin and high- and low-pathogenicity avian influenza viruses associated with human infection) under a consistent protocol, with all viruses concurrently tested in a human bronchial epithelial cell line (Calu-3). Viral titers in ferret nasal wash specimens and nasal turbinate tissue correlated positively with peak titer in Calu-3 cells, whereas additional phenotypic and molecular determinants of influenza virus virulence and transmissibility in ferrets varied in their association with in vitro viral titer measurements. Mathematical modeling was used to estimate more generalizable key replication kinetic parameters from raw in vitro viral titers, revealing commonalities between viral infection progression in vivo and in vitro. Meta-analyses inclusive of IAV that display a diverse range of phenotypes in ferrets, interpreted with mathematical modeling of viral kinetic parameters, can provide critical information supporting a more rigorous and appropriate contextualization of in vitro experiments toward pandemic preparedness. IMPORTANCE Both in vitro and in vivo models are employed for assessing the pandemic potential of novel and emerging influenza A viruses in laboratory settings, but systematic examinations of how well viral titer measurements obtained in vitro align with results from in vivo experimentation are not frequently performed. We show that certain viral titer measurements following infection of a human bronchial epithelial cell line are positively correlated with viral titers in specimens collected from virus-inoculated ferrets and employ mathematical modeling to identify commonalities between viral infection progression between both models. These analyses provide a necessary first step in enhanced interpretation and incorporation of in vitro-derived data in risk assessment activities and highlight the utility of employing mathematical modeling approaches to more closely examine features of virus replication not identifiable by experimental studies alone.

Correction: Time to revisit the endpoint dilution assay and to replace the TCID50 as a measure of a virus sample's infection concentration.

[This corrects the article DOI: 10.1371/journal.pcbi.1009480.].

Correction: A mathematical model describing the localization and spread of influenza A virus infection within the human respiratory tract.

[This corrects the article DOI: 10.1371/journal.pcbi.1007705.].

Time to revisit the endpoint dilution assay and to replace the TCID50 as a measure of a virus sample's infection concentration.

The endpoint dilution assay's output, the 50% infectious dose (ID50), is calculated using the Reed-Muench or Spearman-Kärber mathematical approximations, which are biased and often miscalculated. We introduce a replacement for the ID50 that we call Specific INfection (SIN) along with a free and open-source web-application, midSIN (https://midsin.physics.ryerson.ca) to calculate it. midSIN computes a virus sample's SIN concentration using Bayesian inference based on the results of a standard endpoint dilution assay, and requires no changes to current experimental protocols. We analyzed influenza and respiratory syncytial virus samples using midSIN and demonstrated that the SIN/mL reliably corresponds to the number of infections a sample will cause per mL. It can therefore be used directly to achieve a desired multiplicity of infection, similarly to how plaque or focus forming units (PFU, FFU) are used. midSIN's estimates are shown to be more accurate and robust than the Reed-Muench and Spearman-Kärber approximations. The impact of endpoint dilution plate design choices (dilution factor, replicates per dilution) on measurement accuracy is also explored. The simplicity of SIN as a measure and the greater accuracy provided by midSIN make them an easy and superior replacement for the TCID50 and other in vitro culture ID50 measures. We hope to see their universal adoption to measure the infectivity of virus samples.

Correction: A mathematical model describing the localization and spread of influenza A virus infection within the human respiratory tract.

[This corrects the article DOI: 10.1371/journal.pcbi.1007705.].

A mathematical model describing the localization and spread of influenza A virus infection within the human respiratory tract.

Within the human respiratory tract (HRT), virus diffuses through the periciliary fluid (PCF) bathing the epithelium. But virus also undergoes advection: as the mucus layer sitting atop the PCF is pushed along by the ciliated cell's beating cilia, the PCF and its virus content are also pushed along, upwards towards the nose and mouth. While many mathematical models (MMs) have described the course of influenza A virus (IAV) infections in vivo, none have considered the impact of both diffusion and advection on the kinetics and localization of the infection. The MM herein represents the HRT as a one-dimensional track extending from the nose down towards the lower HRT, wherein stationary cells interact with IAV which moves within (diffusion) and along with (advection) the PCF. Diffusion was found to be negligible in the presence of advection which effectively sweeps away IAV, preventing infection from disseminating below the depth at which virus first deposits. Higher virus production rates (10-fold) are required at higher advection speeds (40 µm/s) to maintain equivalent infection severity and timing. Because virus is entrained upwards, upper parts of the HRT see more virus than lower parts. As such, infection peaks and resolves faster in the upper than in the lower HRT, making it appear as though infection progresses from the upper towards the lower HRT, as reported in mice. When the spatial MM is expanded to include cellular regeneration and an immune response, it reproduces tissue damage levels reported in patients. It also captures the kinetics of seasonal and avian IAV infections, via parameter changes consistent with reported differences between these strains, enabling comparison of their treatment with antivirals. This new MM offers a convenient and unique platform from which to study the localization and spread of respiratory viral infections within the HRT.

Quantification of Ebola virus replication kinetics in vitro.

Mathematical modelling has successfully been used to provide quantitative descriptions of many viral infections, but for the Ebola virus, which requires biosafety level 4 facilities for experimentation, modelling can play a crucial role. Ebola virus modelling efforts have primarily focused on in vivo virus kinetics, e.g., in animal models, to aid the development of antivirals and vaccines. But, thus far, these studies have not yielded a detailed specification of the infection cycle, which could provide a foundational description of the virus kinetics and thus a deeper understanding of their clinical manifestation. Here, we obtain a diverse experimental data set of the Ebola virus infection in vitro, and then make use of Bayesian inference methods to fully identify parameters in a mathematical model of the infection. Our results provide insights into the distribution of time an infected cell spends in the eclipse phase (the period between infection and the start of virus production), as well as the rate at which infectious virions lose infectivity. We suggest how these results can be used in future models to describe co-infection with defective interfering particles, which are an emerging alternative therapeutic.

Modelling endurance and resumption times for repetitive one-hand pushing.

This study's objective was to develop models of endurance time (ET), as a function of load level (LL), and of resumption time (RT) after loading as a function of both LL and loading time (LT) for repeated loadings. Ten male participants with experience in construction work each performed 15 different one-handed repetaed pushing tasks at shoulder height with varied exerted force and duration. These data were used to create regression models predicting ET and RT. It is concluded that power law relationships are most appropriate to use when modelling ET and RT. While the data the equations are based on are limited regarding number of participants, gender, postures, magnitude and type of exerted force, the paper suggests how this kind of modelling can be used in job design and in further research. Practitioner Summary: Adequate muscular recovery during work-shifts is important to create sustainable jobs. This paper describes mathematical modelling and presents models for endurance times and resumption times (an aspect of recovery need), based on data from an empirical study. The models can be used to help manage fatigue levels in job design.

A drug-disease model describing the effect of oseltamivir neuraminidase inhibition on influenza virus progression.

A population drug-disease model was developed to describe the time course of influenza virus with and without oseltamivir treatment and to investigate opportunities for antiviral combination therapy. Data included viral titers from 208 subjects, across 4 studies, receiving placebo and oseltamivir at 20 to 200 mg twice daily for 5 days. A 3-compartment mathematical model, comprising target cells infected at rate ß, free virus produced at rate p and cleared at rate c, and infected cells cleared at rate δ, was implemented in NONMEM with an inhibitory Hill function on virus production (p), accounting for the oseltamivir effect. In congruence with clinical data, the model predicts that the standard 75-mg regimen initiated 2 days after infection decreased viral shedding duration by 1.5 days versus placebo; the 150-mg regimen decreased shedding by an additional average 0.25 day. The model also predicts that initiation of oseltamivir sooner postinfection, specifically at day 0.5 or 1, results in proportionally greater decreases in viral shedding duration of 5 and 3.5 days, respectively. Furthermore, the model suggests that combining oseltamivir (acting to subdue virus production rate) with an antiviral whose activity decreases viral infectivity (ß) results in a moderate additive effect dependent on therapy initiation time. In contrast, the combination of oseltamivir with an antiviral whose activity increases viral clearance (c) shows significant additive effects independent of therapy initiation time. The utility of the model for investigating the pharmacodynamic effects of novel antivirals alone or in combination on emergent influenza virus strains warrants further investigation.

A conservation law for virus infection kinetics in vitro.

Conservation laws are among the most important properties of a physical system, but are not commonplace in biology. We derived a conservation law from the basic model for viral infections which consists in a small set of ordinary differential equations. We challenged the conservation law experimentally for the case of a virus infection in a cell culture. We found that the derived, conserved quantity remained almost constant throughout the infection period, implying that the derived conservation law holds in this biological system. We also suggest a potential use for the conservation law in evaluating the accuracy of experimental measurements.

The H275Y neuraminidase mutation of the pandemic A/H1N1 influenza virus lengthens the eclipse phase and reduces viral output of infected cells, potentially compromising fitness in ferrets.

The H275Y amino acid substitution of the neuraminidase gene is the most common mutation conferring oseltamivir resistance in the N1 subtype of the influenza virus. Using a mathematical model to analyze a set of in vitro experiments that allow for the full characterization of the viral replication cycle, we show that the primary effects of the H275Y substitution on the pandemic H1N1 (H1N1pdm09) strain are to lengthen the mean eclipse phase of infected cells (from 6.6 to 9.1 h) and decrease (by 7-fold) the viral burst size, i.e., the total number of virions produced per cell. We also find, however, that the infectious-unit-to-particle ratio of the H275Y mutant strain is 12-fold higher than that of the oseltamivir-susceptible strain (0.19 versus 0.016 per RNA copy). A parallel analysis of the H275Y mutation in the prior seasonal A/Brisbane/59/2007 background shows similar changes in the infection kinetic parameters, but in this background, the H275Y mutation also allows the mutant to infect cells five times more rapidly. Competitive mixed-strain infections in vitro, where the susceptible and resistant H1N1pdm09 strains must compete for cells, are characterized by higher viral production by the susceptible strain but suggest equivalent fractions of infected cells in the culture. In ferrets, however, the mutant strain appears to suffer a delay in its infection of the respiratory tract that allows the susceptible strain to dominate mixed-strain infections.

The effect of random virus failure following cell entry on infection outcome and the success of antiviral therapy.

A virus infection can be initiated with very few or even a single infectious virion, and as such can become extinct, i.e. stochastically fail to take hold or spread significantly. There are many ways that a fully competent infectious virion, having successfully entered a cell, can fail to cause a productive infection, i.e. one that yields infectious virus progeny. Though many stochastic models (SMs) have been developed and used to estimate a virus infection's establishment probability, these typically neglect infection failure post virus entry. The SM presented herein introduces parameter [Formula: see text] which corresponds to the probability that a virion's entry into a cell will result in a productive cell infection. We derive an expression for the likelihood of infection establishment in this new SM, and find that prophylactic therapy with an antiviral reducing [Formula: see text] is at least as good or better at decreasing the establishment probability, compared to antivirals reducing the rates of virus production or virus entry into cells, irrespective of the SM parameters. We investigate the difference in the fraction of cells consumed by so-called extinct versus established virus infections, and find that this distinction becomes biologically meaningless as the probability of establishment approaches zero. We explain why the release of virions continuously over an infectious cell's lifespan, rather than as a single burst at the end of the cell's lifespan, does not result in an increased risk of infection extinction. We show, instead, that the number of virus released, not the timing of the release, affects infection establishment and associated critical antiviral efficacy.

Quantification system for the viral dynamics of a highly pathogenic simian/human immunodeficiency virus based on an in vitro experiment and a mathematical model.

BACKGROUND: Developing a quantitative understanding of viral kinetics is useful for determining the pathogenesis and transmissibility of the virus, predicting the course of disease, and evaluating the effects of antiviral therapy. The availability of data in clinical, animal, and cell culture studies, however, has been quite limited. Many studies of virus infection kinetics have been based solely on measures of total or infectious virus count. Here, we introduce a new mathematical model which tracks both infectious and total viral load, as well as the fraction of infected and uninfected cells within a cell culture, and apply it to analyze time-course data of an SHIV infection in vitro. RESULTS: We infected HSC-F cells with SHIV-KS661 and measured the concentration of Nef-negative (target) and Nef-positive (infected) HSC-F cells, the total viral load, and the infectious viral load daily for nine days. The experiments were repeated at four different MOIs, and the model was fitted to the full dataset simultaneously. Our analysis allowed us to extract an infected cell half-life of 14.1 h, a half-life of SHIV-KS661 infectiousness of 17.9 h, a virus burst size of 22.1 thousand RNA copies or 0.19 TCID50, and a basic reproductive number of 62.8. Furthermore, we calculated that SHIV-KS661 virus-infected cells produce at least 1 infectious virion for every 350 virions produced. CONCLUSIONS: Our method, combining in vitro experiments and a mathematical model, provides detailed quantitative insights into the kinetics of the SHIV infection which could be used to significantly improve the understanding of SHIV and HIV-1 pathogenesis. The method could also be applied to other viral infections and used to improve the in vitro determination of the effect and efficacy of antiviral compounds.

Higher level of replication efficiency of 2009 (H1N1) pandemic influenza virus than those of seasonal and avian strains: kinetics from epithelial cell culture and computational modeling.

The pathogenicity and transmission of influenza A viruses are likely determined in part by replication efficiency in human cells, which is the net effect of complex virus-host interactions. H5N1 avian, H1N1 seasonal, and H1N1 2009 pandemic influenza virus strains were compared by infecting human differentiated bronchial epithelial cells in air-liquid interface cultures at relatively low virus particle/cell ratios. Differential equation and computational models were used to characterize the in vitro kinetic behaviors of the three strains. The models were calibrated by fitting experimental data in order to estimate difficult-to-measure parameters. Both models found marked differences in the relative values of p, the virion production rate per cell, and R(0), an index of the spread of infection through the monolayer, with the values for the strains in the following rank order (from greatest to least): pandemic strain, followed by seasonal strain, followed by avian strain, as expected. In the differential equation model, which treats virus and cell populations as well mixed, R(0) and p varied proportionately for all 3 strains, consistent with a primary role for productivity. In the spatially explicit computational model, R(0) and p also varied proportionately except that R(0) derived for the pandemic strain was reduced, consistent with constrained viral spread imposed by multiple host defenses, including mucus and paracrine antiviral effects. This synergistic experimental-computational strategy provides relevant parameters for identifying and phenotyping potential pandemic strains.

The I222V neuraminidase mutation has a compensatory role in replication of an oseltamivir-resistant influenza virus A/H3N2 E119V mutant.

Oseltamivir-resistant A/H3N2 influenza isolates with or without the E119V and I222V neuraminidase (NA) mutations were recovered from an immunocompromised patient. Based on plaque size, yield assays, and NA activity, the impaired viral fitness of the E119V mutant was partially restored by the I222V NA mutation.

Neuraminidase inhibitors for treatment of human and avian strain influenza: A comparative modeling study.

Treatment of seasonal influenza viral infections using antivirals such as neuraminidase inhibitors (NAIs) has been proven effective if administered within 48h post-infection. However, there is growing evidence that antiviral treatment of infections with avian-derived strains even as late as 6 days post-infection (dpi) can significantly reduce infection severity and duration. Using a mathematical model of in-host influenza viral infections which can capture the kinetics of both a short-lived, typical, seasonal infection and a severe infection exhibiting sustained viral titer, we explore differences in the effects of NAI treatment on both types of influenza viral infections. Comparison of our model's behavior against experimental data from patients naturally infected with avian strains yields estimates for the times at which patients were infected that are consistent with those reported by the patients, and estimates of drug efficacies that are lower for patients who died than for those who recovered. In addition, our model suggests that the sustained, high, viral titers often seen in more severe influenza virus infections are the reason why antiviral treatment delayed by as much as 6 dpi will still lead to reduced viral titers and shortened illness. We conclude that NAIs may be an effective and beneficial treatment strategy against more severe strains of influenza virus characterized by high, sustained, viral titers. We believe that our mathematical model will be an effective tool in guiding treatment of severe influenza viral infections with antivirals.

Exploring the effect of biological delays in kinetic models of influenza within a host or cell culture.

BACKGROUND: For a typical influenza infection in vivo, viral titers over time are characterized by 1-2 days of exponential growth followed by an exponential decay. This simple dynamic can be reproduced by a broad range of mathematical models which makes model selection and the extraction of biologically-relevant infection parameters from experimental data difficult. RESULTS: We analyze in vitro experimental data from the literature, specifically that of single-cycle viral yield experiments, to narrow the range of realistic models of infection. In particular, we demonstrate the viability of using a normal or lognormal distribution for the time a cell spends in a given infection state (e.g., the time spent by a newly infected cell in the latent state before it begins to produce virus), while exposing the shortcomings of ordinary differential equation models which implicitly utilize exponential distributions and delay-differential equation models with fixed-length delays. CONCLUSIONS: By fitting published viral titer data from challenge experiments in human volunteers, we show that alternative models can lead to different estimates of the key infection parameters.