Genetic variation and evolution of equine infectious anemia virus rev quasispecies during long term persistent infection

Genetic variation has been observed in many viruses. Viruses that carry their genetic information in the form of RNA exhibit high mutation rates because the viral polymerase lacks proof-reading mechanisms commonly found in DNA polymerase complexes. The combination of high mutation rates, small genome size, and high replication rates results in a population of closely related viral genotypes, which are commonly referred to as a quasispecies. A consequence of the genetic variation in viruses is possible variation in viral phenotype of the quasispecies population. Furthermore, changes in viral phenotype may be a biologically important factor in progression of disease. Here, we undertook a longitudinal study to describe the quasispecies nature and genetic variation in a lentivirus regulatory protein, Rev, during the course of disease in a pony experimentally infected with equine infectious anemia virus (EIAV). This study examined rev variants that comprised the quasispecies population in sequential sera samples. Over the course of disease, there was continual appearance of novel rev variants, with some variants growing in frequency to predominate certain time points. Phylogenetic and cluster analyses suggested that the Rev quasispecies was comprised of two distinct populations that co-existed during infection. These two quasispecies populations differed in their pattern of evolution, with one population accumulating changes in a linear, time-dependent manner, while the other population evolved radially from a common variant. Changes in the population size of the two Rev quasispecies coincided with changes in the clinical stages of disease. Rev variants from each population were biologically tested, and significant differences in Rev activity were detected between the two populations. Together, these results suggested that the distinct Rev populations differed in selective advantage. A statistical correlation was found between Rev quasispecies activity and temperature of the pony over the course of infection. Furthermore, the Rev quasispecies activity differed significantly between different stages of clinical disease. This study suggests that distinct quasispecies populations, which differed in pattern of evolution and niche advantage, co-existed during long term persistent infection by EIAV. A multi-population quasispecies model challenges our current thinking of viral populations and may have significant biological implications

Melioidosis diagnostic workshop, 2013.

Melioidosis is a severe disease that can be difficult to diagnose because of its diverse clinical manifestations and a lack of adequate diagnostic capabilities for suspected cases. There is broad interest in improving detection and diagnosis of this disease not only in melioidosis-endemic regions but also outside these regions because melioidosis may be underreported and poses a potential bioterrorism challenge for public health authorities. Therefore, a workshop of academic, government, and private sector personnel from around the world was convened to discuss the current state of melioidosis diagnostics, diagnostic needs, and future directions

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Genetic variation and evolution of equine infectious anemia virus rev quasispecies during long term persistent infection

Genetic variation has been observed in many viruses. Viruses that carry their genetic information in the form of RNA exhibit high mutation rates because the viral polymerase lacks proof-reading mechanisms commonly found in DNA polymerase complexes. The combination of high mutation rates, small genome size, and high replication rates results in a population of closely related viral genotypes, which are commonly referred to as a quasispecies. A consequence of the genetic variation in viruses is possible variation in viral phenotype of the quasispecies population. Furthermore, changes in viral phenotype may be a biologically important factor in progression of disease. Here, we undertook a longitudinal study to describe the quasispecies nature and genetic variation in a lentivirus regulatory protein, Rev, during the course of disease in a pony experimentally infected with equine infectious anemia virus (EIAV). This study examined rev variants that comprised the quasispecies population in sequential sera samples. Over the course of disease, there was continual appearance of novel rev variants, with some variants growing in frequency to predominate certain time points. Phylogenetic and cluster analyses suggested that the Rev quasispecies was comprised of two distinct populations that co-existed during infection. These two quasispecies populations differed in their pattern of evolution, with one population accumulating changes in a linear, time-dependent manner, while the other population evolved radially from a common variant. Changes in the population size of the two Rev quasispecies coincided with changes in the clinical stages of disease. Rev variants from each population were biologically tested, and significant differences in Rev activity were detected between the two populations. Together, these results suggested that the distinct Rev populations differed in selective advantage. A statistical correlation was found between Rev quasispecies activity and temperature of the pony over the course of infection. Furthermore, the Rev quasispecies activity differed significantly between different stages of clinical disease. This study suggests that distinct quasispecies populations, which differed in pattern of evolution and niche advantage, co-existed during long term persistent infection by EIAV. A multi-population quasispecies model challenges our current thinking of viral populations and may have significant biological implications.</p

Kinetics of Influenza A Virus Infection in Humans

Currently, little is known about the viral kinetics of influenza A during infection within an individual. We utilize a series of mathematical models of increasing complexity, which incorporate target cell limitation and the innate interferon response, to examine influenza A virus kinetics in the upper respiratory tracts of experimentally infected adults. The models were fit to data from an experimental H1N1 influenza A/Hong Kong/123/77 infection and suggest that it is important to include the eclipse phase of the viral life cycle in viral dynamic models. Doing so, we estimate that after a delay of ∼6 h, infected cells begin producing influenza virus and continue to do so for ∼5 h. The average lifetime of infected cells is ∼11 h, and the half-life of free infectious virus is ∼3 h. We calculated the basic reproductive number, R(0), which indicated that a single infected cell could produce ∼22 new productive infections. This suggests that antiviral treatments have a large hurdle to overcome in moderating symptoms and limiting infectiousness and that treatment has to be initiated as early as possible. For about 50% of patients, the curve of viral titer versus time has two peaks. This bimodal behavior can be explained by incorporating the antiviral effects of interferon into the model. Our model also compared well to an additional data set on viral titer after experimental infection and treatment with the neuraminidase inhibitor zanamivir, which suggests that such models may prove useful in estimating the efficacies of different antiviral therapies for influenza A infection

Subpopulations of Equine Infectious Anemia Virus Rev Coexist In Vivo and Differ in Phenotype

Lentiviruses exist in vivo as a population of related, nonidentical genotypes, commonly referred to as quasispecies. The quasispecies structure is characteristic of complex adaptive systems and contributes to the high rate of evolution in lentiviruses that confounds efforts to develop effective vaccines and antiviral therapies. Here, we describe analyses of genetic data from longitudinal studies of genetic variation in a lentivirus regulatory protein, Rev, over the course of disease in ponies experimentally infected with equine infectious anemia virus. As observed with other lentivirus data, the Rev variants exhibited a quasispecies character. Phylogenetic and partition analyses suggested that the Rev quasispecies comprised two distinct subpopulations that coexisted during infection. One subpopulation appeared to accumulate changes in a linear, time-dependent manner, while the other evolved radially from a common variant. Over time, the two subpopulations cycled in predominance coincident with changes in the disease state, suggesting that the two groups differed in selective advantage. Transient expression assays indicated the two populations differed significantly in Rev nuclear export activity. Chimeric proviral clones containing Rev genotypes representative of each population differed in rate and overall level of virus replication in vitro. The coexistence of genetically distinct viral subpopulations that differ in phenotype provides great adaptability to environmental changes within the infected host. A quasispecies model with multiple subpopulations may provide additional insight into the nature of lentivirus reservoirs and the evolution of antigenic and drug-resistant variants