A highly pathogenic simian/human immunodeficiency virus effectively produces infectious virions compared with a less pathogenic virus in cell culture

The comparison of decay rates of infectious SARS-CoV-2 and viral RNA in environmental waters and wastewater

Understanding the decay characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater and ambient waters is important for multiple applications including assessment of risk of exposure associated with handling wastewater samples, public health risk associated with recreation in wastewater polluted ambient waters and better understanding and interpretation of wastewater-based epidemiology (WBE) results. We evaluated the decay rates of infectious SARS-CoV-2 and viral RNA in wastewater and ambient waters under temperature regimes representative of seasonal fluctuations. Infectious virus was seeded in autoclaved primary wastewater effluent, final dechlorinated wastewater effluent, lake water, and marine water at a final concentration of 6.26 ± 0.07 log10 plaque forming units per milliliter. Each suspension was incubated at either 4°, 25°, and 37 °C. Samples were initially collected on an hourly basis, then approximately every other day for 15 days. All samples were analyzed for infectious virus via a plaque assay using the Vero E6 cell line, and viral gene copy levels were quantified with the US CDC's N1 and N2 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assays. The infectious virus decayed significantly faster (p ≤ 0.0214) compared to viral RNA, which persisted for the duration of the study irrespective of the incubation conditions. The initial loss (within 15 min of seeding) as well as decay of infectious SARS-CoV-2 was significantly faster (p ≤ 0.0387) in primary treated wastewater compared to other water types, but viral RNA did not degrade appreciably in this matrix until day 15. Overall, temperature was the most important driver of decay, and after 24 h, no infectious SARS-CoV-2 was detected at 37 °C in any water type. Moreover, the CDC N2 gene assay target decayed significantly (p ≤ 0.0174) faster at elevated temperatures compared to CDC N1, which has important implications for RT-qPCR assay selection for WBE approach.

The reproduction number and its probability distribution for stochastic viral dynamics

We consider stochastic models of individual infected cells. The reproduction number, R, is understood as a random variable representing the number of new cells infected by one initial infected cell in an otherwise susceptible (target cell) population. Variability in R results partly from heterogeneity in the viral burst size (the number of viral progeny generated from an infected cell during its lifetime), which depends on the distribution of cellular lifetimes and on the mechanism of virion release. We analyse viral dynamics models with an eclipse phase: the period of time after a cell is infected but before it is capable of releasing virions. The duration of the eclipse, or the subsequent infectious, phase is non-exponential, but composed of stages. We derive the probability distribution of the reproduction number for these viral dynamics models, and show it is a negative binomial distribution in the case of constant viral release from infectious cells, and under the assumption of an excess of target cells. In a deterministic model, the ultimate in-host establishment or extinction of the viral infection depends entirely on whether the mean reproduction number is greater than, or less than, one, respectively. Here, the probability of extinction is determined by the probability distribution of R, not simply its mean value. In particular, we show that in some cases the probability of infection is not an increasing function of the mean reproduction number.

Systems biology analyses reveal enhanced chronic morphine distortion of gut-brain interrelationships in simian human immunodeficiency virus infected rhesus macaques

Background

Commonly used opioids, such as morphine have been implicated in augmented SIV/HIV persistence within the central nervous system (CNS). However, the extent of myeloid cell polarization and viral persistence in different brain regions remains unclear. Additionally, the additive effects of morphine on SIV/HIV dysregulation of gut-brain crosstalk remain underexplored. Therefore, studies focused on understanding how drugs of abuse such as morphine affect immune dynamics, viral persistence and gut-brain interrelationships are warranted.

Materials and methods

For a total of 9 weeks, rhesus macaques were ramped-up, and twice daily injections of either morphine (n = 4) or saline (n = 4) administered. This was later followed with infection with SHIVAD8EO variants. At necropsy, mononuclear cells were isolated from diverse brain [frontal lobe, cerebellum, medulla, putamen, hippocampus (HIP) and subventricular zone (SVZ)] and gut [lamina propria (LP) and muscularis (MUSC) of ascending colon, duodenum, and ileum] regions. Multiparametric flow cytometry was used to were profile for myeloid cell polarity/activation and results corroborated with indirect immunofluorescence assays. Simian human immunodeficiency virus (SHIV) DNA levels were measured with aid of the digital droplet polymerase chain reaction (PCR) assay. Luminex assays were then used to evaluate soluble plasma/CSF biomarker levels. Finally, changes in the fecal microbiome were evaluated using 16S rRNA on the Illumina NovaSeq platform.

Results

Flow Cytometry-based semi-supervised analysis revealed that morphine exposure led to exacerbated M1 (CD14/CD16)/M2 (CD163/CD206) polarization in activated microglia that spanned across diverse brain regions. This was accompanied by elevated SHIV DNA within the sites of neurogenesis-HIP and SVZ. HIP/SVZ CD16+ activated microglia positively correlated with SHIV DNA levels in the brain (r = 0.548, p = 0.042). Simultaneously, morphine dependence depleted butyrate-producing bacteria, including Ruminococcus (p = 0.05), Lachnospira (p = 0.068) genera and Roseburia_sp_831b (p = 0.068). Finally, morphine also altered the regulation of CNS inflammation by reducing the levels of IL1 Receptor antagonist (IL1Ra).

Conclusion

These findings are suggestive that morphine promotes CNS inflammation by altering receptor modulation, increasing myeloid brain activation, distorting gut-brain crosstalk, and causing selective enhancement of SHIV persistence in sites of neurogenesis.

Incomplete antiviral treatment may induce longer durations of viral shedding during SARS-CoV-2 infection

The duration of viral shedding is determined by a balance between de novo infection and removal of infected cells. That is, if infection is completely blocked with antiviral drugs (100% inhibition), the duration of viral shedding is minimal and is determined by the length of virus production. However, some mathematical models predict that if infected individuals are treated with antiviral drugs with efficacy below 100%, viral shedding may last longer than without treatment because further de novo infections are driven by entry of the virus into partially protected, uninfected cells at a slower rate. Using a simple mathematical model, we quantified SARS-CoV-2 infection dynamics in non-human primates and characterized the kinetics of viral shedding. We counterintuitively found that treatments initiated early, such as 0.5 d after virus inoculation, with intermediate to relatively high efficacy (30-70% inhibition of virus replication) yield a prolonged duration of viral shedding (by about 6.0 d) compared with no treatment.

Quantifying mechanistic traits of influenza viral dynamics using in vitro data

When analysing in vitro data, growth kinetics of influenza virus strains are often compared by computing their growth rates, which are sometimes used as proxies for fitness. However, analogous to mathematical models for epidemics, the growth rate can be defined as a function of mechanistic traits: the basic reproduction number (the average number of cells each infected cell infects) and the mean generation time (the average length of a replication cycle). Fitting a model to previously published and newly generated data from experiments in human lung cells, we compared estimates of growth rate, reproduction number and generation time for six influenza A strains. Of four strains in previously published data, A/Canada/RV733/2003 (seasonal H1N1) had the lowest basic reproduction number, followed by A/Mexico/INDRE4487/2009 (pandemic H1N1), then A/Indonesia/05/2005 (spill-over H5N1) and A/Anhui/1/2013 (spill-over H7N9). This ordering of strains was preserved for both generation time and growth rate, suggesting a positive biological correlation between these quantities which have not been previously observed. We further investigated these potential correlations using data from reassortant viruses with different internal proteins (from A/England/195/2009 (pandemic H1N1) and A/Turkey/05/2005 (H5N1)), and the same surface proteins (from A/Puerto Rico/8/34 (lab-adapted H1N1)). Similar correlations between traits were observed for these viruses, confirming our initial findings and suggesting that these patterns were related to the degree of human adaptation of internal genes. Also, the model predicted that strains with a smaller basic reproduction number, shorter generation time and slower growth rate underwent more replication cycles by the time of peak viral load, potentially accumulating mutations more quickly. These results illustrate the utility of mathematical models in inferring traits driving observed differences in in vitro growth of influenza strains.

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.

Modeling Borna Disease Virus In Vitro Spread Reveals the Mode of Antiviral Effect Conferred by an Endogenous Bornavirus-Like Element

Endogenous retroviruses have demonstrated exaptation during long-term evolution with hosts, e.g., resulting in acquisition of antiviral effect on related extant viral infections. While empirical studies have found that an endogenous bornavirus-like element derived from viral nucleoprotein (itEBLN) in the ground squirrel genome shows antiviral effect on virus replication and de novo infection, the antiviral mechanism, dynamics, and quantitative effect of itEBLN remain unknown. In this study, we experimentally and theoretically investigated the dynamics of how an extant bornavirus, Borna disease virus 1 (BoDV-1), spreads and replicates in uninfected, BoDV-1-infected, and itEBLN-expressing cultured cells. Quantifying antiviral effect based on time course data sets, we found that the antiviral effects of itEBLN are estimated to be 75% and 34% on intercellular virus spread and intracellular virus replication, respectively. This discrepancy between intercellular virus spread and intracellular viral replication suggests that viral processes other than the replication of viral ribonucleoprotein complex (RNP) contributed to the suppression of virus spread in itEBLN-expressing cells. Because itEBLN binds to the BoDV-1 RNP, the suppression of viral RNP trafficking can be an attractive candidate explaining this discrepancy.IMPORTANCE Accumulating evidence suggests that some endogenous viral elements (EVEs), including endogenous retroviruses and endogenous nonretroviral virus elements, have acquired functions in the host as a result of long-term coevolution. Recently, an endogenous bornavirus-like element (itEBLN) found in the ground squirrel genome has been shown to have antiviral activity against exogenous bornavirus infection. In this study, we first quantified bornavirus spread in cultured cells and then calculated the antiviral activity of itEBLN on bornavirus infection. The calculated antiviral activity of itEBLN suggests its suppression of multiple processes in the viral life cycle. To our knowledge, this is the first study quantifying the antiviral activity of EVEs and speculating on a model of how some EVEs have acquired antiviral activity during host-virus arms races.

Modeling the efficiency of filovirus entry into cells in vitro: Effects of SNP mutations in the receptor molecule

Interaction between filovirus glycoprotein (GP) and the Niemann-Pick C1 (NPC1) protein is essential for membrane fusion during virus entry. Some single-nucleotide polymorphism (SNPs) in two surface-exposed loops of NPC1 are known to reduce viral infectivity. However, the dependence of differences in entry efficiency on SNPs remains unclear. Using vesicular stomatitis virus pseudotyped with Ebola and Marburg virus GPs, we investigated the cell-to-cell spread of viruses in cultured cells expressing NPC1 or SNP derivatives. Eclipse and virus-producing phases were assessed by in vitro infection experiments, and we developed a mathematical model describing spatial-temporal virus spread. This mathematical model fit the plaque radius data well from day 2 to day 6. Based on the estimated parameters, we found that SNPs causing the P424A and D508N substitutions in NPC1 most effectively reduced the entry efficiency of Ebola and Marburg viruses, respectively. Our novel approach could be broadly applied to other virus plaque assays.

Ebola (EBOV) and Marburg (MARV) viruses, which are included viruses of the family Filoviridae, cause severe hemorrhagic fever in humans. Filovirus particles is adsorbed to the cell through glycoprotein (GP), which is the only viral surface protein. Interaction between the filovirus sugar protein (GP) and the Niemann-Pick C1 (NPC1) protein plays a key role in membrane fusion during virus entry. Although some single-nucleotide polymorphism (SNPs) in two surface-exposed loops of NPC1 are known to reduce viral infectivity, the dependence of differences in entry efficiency on SNPs has not been studied. We therefore investigated the cell-to-cell spread of viruses in cultured cells expressing NPC1 or SNP derivatives. Using a mathematical model describing spatial-temporal virus spread, we quantitatively analyze viral entry efficiency and how this affected cell-to-cell spread. Our approach may be applied to not only understanding the roles of genetic polymorphisms in human susceptibility to filoviruses, but also other virus plaque assays.

Quantifying antiviral effects against simian/human immunodeficiency virus induced by host immune response

Chimeric simian and human immunodeficiency viruses (SHIVs) are appropriate animal models for the human immunodeficiency virus (HIV) because HIV has quite a narrow host range. Additionally, SHIVs that encode the HIV-1 Env protein and are infectious to macaques have many strains that show different pathogenesis, such as the highly pathogenic SHIV-KS661 and the less pathogenic SHIV-#64. Therefore, we used SHIVs to understand different aspects of AIDS pathogenesis. In a previous study, we established a mathematical model of in vivo early SHIV infection dynamics, which revealed the expected uninfected and infected dynamics in Rhesus macaques. In concrete, the number of uninfected CD4⁺ T cells in SHIV-KS661-infected Rhesus macaques decreased more significantly and rapidly than that of SHIV-#64 Rhesus macaques, and these Rhesus macaques did not any induce host immune response. In contrast, the number of uninfected CD4⁺ T cells in SHIV-#64-infected Rhesus macaques is maintained, and host immune response developed. Although we considered that the peak viral load might determine whether systemic CD4⁺ T cell depletion occurs or host immune responses develop, we could not investigate this because our model quantified only SHIV infection prior to the development of the pathogenicity or host immune responses. Therefore, we developed a new mathematical model to investigate why SHIV-#64 and SHIV-KS661 showed different long-term viral dynamics. We fitted our new model considering antibody responses to our experimental datasets that included antibody titers, CD4⁺ T cells, and viral load data. We performed a maximum likelihood estimation using a non-linear mixed effect model. From the results, we derived the basic reproduction numbers of SHIV-#64 and SHIV-KS661 from intravenous infection (IV) and SHIV-KS661 from intrarectal infection (IR), as well as the antiviral effects of antibodies against SHIV-#64(IV) and SHIV-KS661(IR). We found significant differences between the basic reproduction number of SHIV-#64(IV) or -KS661(IR) and that of SHIV-KS661(IV). We found no clear difference between the antiviral effects of SHIV-#64(IV) and SHIV-KS661(IR), and revealed that an antiviral effect more than 90% of that of maximum antibody responses was induced from initial antibody responses (i.e., antibody response just after its inducement). In conclusion, we found that the basic reproduction number, rather than SHIV strains determines whether systemic CD4⁺ T cell depletion develops, and the subsequent antibody responses occurs.

Should a viral genome stay in the host cell or leave? A quantitative dynamics study of how hepatitis C virus deals with this dilemma

Virus proliferation involves gene replication inside infected cells and transmission to new target cells. Once positive-strand RNA virus has infected a cell, the viral genome serves as a template for copying (“stay-strategy”) or is packaged into a progeny virion that will be released extracellularly (“leave-strategy”). The balance between genome replication and virion release determines virus production and transmission efficacy. The ensuing trade-off has not yet been well characterized. In this study, we use hepatitis C virus (HCV) as a model system to study the balance of the two strategies. Combining viral infection cell culture assays with mathematical modeling, we characterize the dynamics of two different HCV strains (JFH-1, a clinical isolate, and Jc1-n, a laboratory strain), which have different viral release characteristics. We found that 0.63% and 1.70% of JFH-1 and Jc1-n intracellular viral RNAs, respectively, are used for producing and releasing progeny virions. Analysis of the Malthusian parameter of the HCV genome (i.e., initial proliferation rate) and the number of de novo infections (i.e., initial transmissibility) suggests that the leave-strategy provides a higher level of initial transmission for Jc1-n, whereas, in contrast, the stay-strategy provides a higher initial proliferation rate for JFH-1. Thus, theoretical-experimental analysis of viral dynamics enables us to better understand the proliferation strategies of viruses, which contributes to the efficient control of virus transmission. Ours is the first study to analyze the stay-leave trade-off during the viral life cycle and the significance of the replication-release switching mechanism for viral proliferation.

A theoretical-experimental analysis of viral dynamics reveals a stay/leave trade-off during the viral life cycle and demonstrates the significance for viral proliferation of a replication-release switching mechanism.

Revealing uninfected and infected target cell dynamics from peripheral blood data in highly and less pathogenic simian/human immunodeficiency virus infected Rhesus macaque

Since chimeric simian and human immunodeficiency viruses (SHIVs) used here, that is, SHIV-#64 and -KS661 utilize both CCR5 and CXCR4 chemokine receptors, they have broad target cell properties. A highly pathogenic SHIV strain, SHIV-KS661, causes an infection that systemically depletes the CD4⁺ T cells of Rhesus macaques, while a less pathogenic strain, SHIV-#64, does not cause severe symptoms in the macaques. In our previous studies, we established in vitro quantification system for virus infection dynamics, and concluded that SHIV-KS661 effectively produces infectious virions compared with SHIV-#64 in the HSC-F cell culture. However, in vivo dynamics of SHIV infection have not been well understood. To quantify SHIV-#64 and -KS661 infection dynamics in Rhesus macaques, we developed a novel approach and analyzed total CD4⁺ T cells and viral load in peripheral blood, and reproduced the expected dynamics for the uninfected and infected CD4⁺ T cells in silico. Using our previous cell culture experimental datasets, we revealed that an infection rate constant is different between SHIV-#64 and -KS661, but the viral production rate and the death rate are similar for the both strains. Thus, here, we assumed these relations in our in vivo data and carried out the data fitting. We performed Bayesian estimation for the whole dataset using MCMC sampling, and simultaneously fitted our novel model to total CD4⁺ T cells and viral load of SHIV-#64 and -KS661 infection. Our analyses explained that the Malthusian parameter (i.e., fitness of virus infection) and the basic reproduction number (i.e., potential of virus infection) for SHIV-KS661 are significantly higher than those of SHIV-#64. In addition, we demonstrated that the number of uninfected CD4⁺ T cells in SHIV-KS661 infected Rhesus macaques decreases to the significantly lower value than that before the inoculation several days earlier compared with SHIV-#64 infection. Taken together, the differences between SHIV-#64 and -KS661 infection before the peak viral load might determine the subsequent destiny, that is, whether the systemic CD4⁺ T cell depletion occurs or the host immune response develop.

Identification of influential proteins in the classical retinoic acid signaling pathway

Background

In the classical pathway of retinoic acid (RA) mediated gene transcription, RA binds to a nuclear hormone receptor dimer composed of retinoic acid receptor (RAR) and retinoid X receptor (RXR), to induce the expression of its downstream target genes. In addition to nuclear receptors, there are other intracellular RA binding proteins such as cellular retinoic acid binding proteins (CRABP1 and CRABP2) and cytochrome P450 (CYP) enzymes, whose contributions to the RA signaling pathway have not been fully understood. The objective of this study was to compare the significance of various RA binding receptors, i.e. CRABP1, CRABP2, CYP and RAR in the RA signaling pathway. In this regard, we developed a mathematical model of the RA pathway, which is one of the few models, if not the only one, that includes all main intracellular RA binding receptors. We then performed a global sensitivity analysis (GSA) to investigate the contribution of the RA receptors to RA-induced mRNA production, when the cells were treated with a wide range of RA levels, from physiological to pharmacological concentrations.

Results

Our results show that CRABP2 and RAR are the most and the least important proteins, respectively, in controlling the model performance at physiological concentrations of RA (1–10 nM). However, at higher concentrations of RA, CYP and RAR are the most sensitive parameters of the system. Furthermore, we found that depending on the concentrations of all RA binding proteins, the rate of metabolism of RA can either change or remain constant following RA therapy. The cellular levels of CRABP1 are more important than that of CRABP2 in controlling RA metabolite formation at pharmacological conditions (RA = 0.1–1 μM). Finally, our results indicate a significant negative correlation between total mRNA production and total RA metabolite formation at pharmacological levels of RA.

Conclusions

Our simulations indicate that the significance of the RA binding proteins in the RA pathway of gene expression strongly depends on intracellular concentration of RA. This study not only can explain why various cell types respond to RA therapy differently, but also can potentially help develop pharmacological methods to increase the efficacy of the drug.

Electronic supplementary material

The online version of this article (10.1186/s12976-018-0088-7) contains supplementary material, which is available to authorized users.

A PDE multiscale model of hepatitis C virus infection can be transformed to a system of ODEs

Direct-acting antivirals (DAAs) treat hepatitis C virus (HCV) by targeting its intracellular viral replication. DAAs are effective and deliver high clinical performance against HCV infection, but optimization of the DAA treatment regimen is ongoing. Different classes of DAAs are currently under development, and HCV treatments that combine two or three DAAs with different action mechanisms are being improved. To accurately quantify the antiviral effect of these DAA treatments and optimize multi-drug combinations, we must describe the intracellular viral replication processes corresponding to the action mechanisms by multiscale mathematical models. Previous multiscale models of HCV treatment have been formulated by partial differential equations (PDEs). However, estimating the parameters from clinical datasets requires comprehensive numerical PDE computations that are time consuming and often converge poorly. Here, we propose a user-friendly approach that transforms a standard PDE multiscale model of HCV infection (Guedj J et al., Proc. Natl. Acad. Sci. USA 2013; 110(10):3991-6) to mathematically identical ordinary differential equations (ODEs) without any assumptions. We also confirm consistency between the numerical solutions of our transformed ODE model and the original PDE model. This relationship between a detailed structured model and a simple model is called ``model aggregation problem'' and a fundamental important in theoretical biology. In particular, as the parameters of ODEs can be estimated by already established methods, our transformed ODE model and its modified version avoid the time-consuming computations and are broadly available for further data analysis.