The Effects of Statistical Multiplicity of Infection on Virus Quantification and Infectivity Assays.
ABSTRACT: Many biological assays are employed in virology to quantify parameters of interest. Two such classes of assays, virus quantification assays (VQAs) and infectivity assays (IAs), aim to estimate the number of viruses present in a solution and the ability of a viral strain to successfully infect a host cell, respectively. VQAs operate at extremely dilute concentrations, and results can be subject to stochastic variability in virus-cell interactions. At the other extreme, high viral-particle concentrations are used in IAs, resulting in large numbers of viruses infecting each cell, enough for measurable change in total transcription activity. Furthermore, host cells can be infected at any concentration regime by multiple particles, resulting in a statistical multiplicity of infection and yielding potentially significant variability in the assay signal and parameter estimates. We develop probabilistic models for statistical multiplicity of infection at low and high viral-particle-concentration limits and apply them to the plaque (VQA), endpoint dilution (VQA), and luciferase reporter (IA) assays. A web-based tool implementing our models and analysis is also developed and presented. We test our proposed new methods for inferring experimental parameters from data using numerical simulations and show improvement on existing procedures in all limits.
Project description:Transmission of multiple founder variants has been associated with faster HIV disease progression. Many studies have attempted to determine the number of founder variants, mainly by analysis of sequence diversity and/or tree topology from acutely HIV-infected individuals. We hypothesized that adding sequence data collected from source partners might improve resolution and characterization of transmission events. Blood plasma samples were collected from both the source and recipient in thirty epidemiologically- and phylogenetically linked transmission pairs. All were men who have sex with men, sampled on average 70 days (range 11-170) after the recipient's estimated date of infection. Next generation sequencing (454 FLX, Roche) of HIV-1 env (C2-V3) was performed for all samples. Inspection of sequence alignments, highlighter plots, phylogenetic tree topologies and sequence diversity were used to determine the multiplicity of founder viruses with and without the inclusion of source data. Using only recipient sequence data, we were able to resolve multiplicity in twenty-six of the thirty transmission pairs (87 percent). Among them, five presented with a high viral diversity at baseline (>0.10 subst/site), consistent with multiple founders. By incorporating sequence data collected from the source partner, we were able to characterize all thirty transmission pairs. Overall, sixteen transmission events (53.3 percent) involved multiple founders. Results obtained by combining sequence data from recipient and source were congruent for nineteen of the twenty-six (73 percent) cases where conclusions were made using only recipient sequence data. The multiplicity of founders was associated with significantly higher HIV RNA levels (P?=?0.04). To further evaluate the transmission bottleneck, we focused on single founder transmissions (fourteen of the thirty), and identified four recipients (28.6 percent) that had founder variants that were inferred to arise from minority viral populations in the source. These source clades ranged from 1.0 to 5.4 percent of the sampled population. Incorporating sequence data from the source increased of the ability to determine the multiplicity of founder variants, reduced misclassification, and allowed us to infer the transmission of minority variants.
Project description:Highly effective direct-acting antivirals against Hepatitis C virus (HCV) have created an opportunity to transplant organs from HCV-positive individuals into HCV-negative recipients, since de novo infection can be routinely cured. As this procedure is performed more widely, it becomes increasingly important to understand the biological underpinnings of virus transmission, especially the multiplicity of infection. Here, we used single genome sequencing of plasma virus in four genotype 1a HCV-positive organ donors and their seven organ recipients to assess the genetic bottleneck associated with HCV transmission following renal and cardiac transplantation. In all recipients, de novo infection was established by multiple genetically distinct viruses that reflect the full phylogenetic spectrum of replication-competent virus circulating in donor plasma. This was true in renal and cardiac transplantation and in recipients with peak viral loads ranging between 2.9 and 6.6 log10 IU/mL. The permissive transmission process characterized here contrasts sharply with sexual or injection-related transmission, which occurs less frequently per exposure and is generally associated with a stringent genetic bottleneck. These findings highlight the effectiveness of current anti-HCV regimens, while raising caution regarding the substantially higher multiplicity of infection seen in organ transplantation-associated HCV acquisition.
Project description:Recombination, complementation and competition profoundly influence virus evolution and epidemiology. Since viruses are intracellular parasites, the basic parameter determining the potential for such interactions is the multiplicity of cellular infection (cellular MOI), i.e. the number of viral genome units that effectively infect a cell. The cellular MOI values that prevail in host organisms have rarely been investigated, and whether they remain constant or change widely during host invasion is totally unknown. Here, we fill this experimental gap by presenting the first detailed analysis of the dynamics of the cellular MOI during colonization of a host plant by a virus. Our results reveal ample variations between different leaf levels during the course of infection, with values starting close to 2 and increasing up to 13 before decreasing to initial levels in the latest infection stages. By revealing wide dynamic changes throughout a single infection, we here illustrate the existence of complex scenarios where the opportunity for recombination, complementation and competition among viral genomes changes greatly at different infection phases and at different locations within a multi-cellular host.
Project description:The multiplicity of infection (MOI), i.e., the number of viral genomes that infect a cell, is an important parameter in virus evolution, which for each virus and environment may have an optimum value that maximizes virus fitness. Thus, the MOI might be controlled by virus functions, an underexplored hypothesis in eukaryote-infecting viruses. To analyze if the MOI is controlled by virus functions, we estimated the MOI in plants coinfected by two genetic variants of Tomato bushy stunt virus (TBSV); by TBSV and a TBSV-derived defective interfering RNA (DI-RNA); or by TBSV and a second tombusvirus, Cymbidium ringspot virus (CymRSV). The MOI was significantly larger in TBSV-CymRSV coinfections (~4.0) than in TBSV-TBSV or TBSV-DI-RNA coinfections (~1.7 to 2.2). Coinfections by CymRSV or TBSV with chimeras in which an open reading frame (ORF) of one virus species was replaced by that of the other identified a role of viral proteins in determining the MOI, which ranged from 1.6 to 3.9 depending on the coinfecting genotypes. However, no virus-encoded protein or genomic region was the sole MOI determinant. Coinfections by CymRSV and TBSV mutants in which the expression of the gene-silencing suppressor protein p19 was abolished also showed a possible role of gene silencing in MOI determination. Taken together, these results demonstrate that the MOI is a quantitative trait showing continuous variation and that as such it has a complex determination involving different virus-encoded functions.The number of viral genomes infecting a cell, or the multiplicity of infection (MOI), is an important parameter in virus evolution affecting recombination rates, selection intensity on viral genes, evolution of multipartite genomes, or hyperparasitism by satellites or defective interfering particles. For each virus and environment, the MOI may have an optimum value that maximizes virus fitness, but little is known about MOI control in eukaryote-infecting viruses. We show here that in plants coinfected by two genotypes of Tomato bushy stunt virus (TBSV), the MOI was lower than in plants coinfected by TBSV and Cymbidium ringspot virus (CymRSV). Coinfections by CymRSV or TBSV with TBSV-CymRSV chimeras showed a role of viral proteins in MOI determination. Coinfections by CymRSV and TBSV mutants not expressing the gene-silencing suppressor protein also showed a role of gene silencing in MOI determination. The results demonstrate that the MOI is a quantitative trait with a complex determination involving different viral functions.
Project description:Molecular signatures are computational or mathematical models created to diagnose disease and other phenotypes and to predict clinical outcomes and response to treatment. It is widely recognized that molecular signatures constitute one of the most important translational and basic science developments enabled by recent high-throughput molecular assays. A perplexing phenomenon that characterizes high-throughput data analysis is the ubiquitous multiplicity of molecular signatures. Multiplicity is a special form of data analysis instability in which different analysis methods used on the same data, or different samples from the same population lead to different but apparently maximally predictive signatures. This phenomenon has far-reaching implications for biological discovery and development of next generation patient diagnostics and personalized treatments. Currently the causes and interpretation of signature multiplicity are unknown, and several, often contradictory, conjectures have been made to explain it. We present a formal characterization of signature multiplicity and a new efficient algorithm that offers theoretical guarantees for extracting the set of maximally predictive and non-redundant signatures independent of distribution. The new algorithm identifies exactly the set of optimal signatures in controlled experiments and yields signatures with significantly better predictivity and reproducibility than previous algorithms in human microarray gene expression datasets. Our results shed light on the causes of signature multiplicity, provide computational tools for studying it empirically and introduce a framework for in silico bioequivalence of this important new class of diagnostic and personalized medicine modalities.
Project description:Type I interferons (IFNs) are induced upon viral infection and important mediators of innate immunity. While there is 1 beta interferon (IFN-?) protein, there are 12 different IFN-? subtypes. It has been reported extensively that different viruses induce distinct patterns of IFN subtypes, but it has not been previously shown how the viral multiplicity of infection (MOI) can affect IFN induction. In this study, we discovered the novel finding that human U937 cells infected with 2 different concentrations of Sendai virus (SeV) induce 2 distinct type I IFN subtype profiles. Cells infected at the lower MOI induced more subtypes than cells infected at the higher MOI. We found that this was due to the extent of signaling through the IFN receptor (IFNAR). The cells infected at the lower viral MOI induced the IFNAR2-dependent IFN-? subtypes 4, 6, 7, 10, and 17, which were not induced in cells infected at higher virus concentrations. IFN-? and IFN-?1, -2, and -8 were induced in an IFNAR-independent manner in cells infected at both virus concentrations. IFN-?5, -14, -16, and -21 were induced in an IFNAR-dependent manner in cells infected at lower virus concentrations and in an IFNAR-independent manner in cells infected at higher virus concentrations. These differences in IFN subtype profiles in the 2 virus concentrations also resulted in distinct interferon-stimulated gene induction. These results present the novel finding that different viral MOIs differentially activate JAK/STAT signaling through the IFNAR, which greatly affects the profile of IFN subtypes that are induced.Type I IFNs are pleiotropic cytokines that are instrumental in combating viral diseases. Understanding how the individual subtypes are induced is important in developing strategies to block viral replication. Many studies have reported that different viruses induce distinct type I IFN subtype profiles due to differences in the way viruses are sensed in different cell types. However, we report in our study the novel finding that the amount of virus used to infect a system can also affect which type I IFN subtypes are induced due to the extent of activation of certain signaling pathways. These distinct IFN subtype profiles in cells infected at different MOIs are correlated with differences in interferon-stimulated gene induction, indicating that the same virus can induce distinct antiviral responses depending on the MOI. Because type I IFNs are used as therapeutic agents to treat viral diseases, understanding their antiviral mechanisms can enhance clinical treatments.
Project description:Elucidating virus-host interactions responsible for HIV-1 transmission is important for advancing HIV-1 prevention strategies. To this end, single genome amplification (SGA) and sequencing of HIV-1 within the context of a model of random virus evolution has made possible for the first time an unambiguous identification of transmitted/founder viruses and a precise estimation of their numbers. Here, we applied this approach to HIV-1 env analyses in a cohort of acutely infected men who have sex with men (MSM) and found that a high proportion (10 of 28; 36%) had been productively infected by more than one virus. In subjects with multivariant transmission, the minimum number of transmitted viruses ranged from 2 to 10 with viral recombination leading to rapid and extensive genetic shuffling among virus lineages. A combined analysis of these results, together with recently published findings based on identical SGA methods in largely heterosexual (HSX) cohorts, revealed a significantly higher frequency of multivariant transmission in MSM than in HSX [19 of 50 subjects (38%) versus 34 of 175 subjects (19%); Fisher's exact p = 0.008]. To further evaluate the SGA strategy for identifying transmitted/founder viruses, we analyzed 239 overlapping 5' and 3' half genome or env-only sequences from plasma viral RNA (vRNA) and blood mononuclear cell DNA in an MSM subject who had a particularly well-documented virus exposure history 3-6 days before symptom onset and 14-17 days before peak plasma viremia (47,600,000 vRNA molecules/ml). All 239 sequences coalesced to a single transmitted/founder virus genome in a time frame consistent with the clinical history, and a molecular clone of this genome encoded replication competent virus in accord with model predictions. Higher multiplicity of HIV-1 infection in MSM compared with HSX is consistent with the demonstrably higher epidemiological risk of virus acquisition in MSM and could indicate a greater challenge for HIV-1 vaccines than previously recognized.
Project description:Inorganic arsenic (iAs) is ubiquitous in the environment as arsenite (AsIII) and arsenate (AsV) compounds and biotransformation of these toxic chemicals leads to the extraordinary variety of organoarsenic species found in nature. Despite classification as a human carcinogen based on data from populations exposed through contaminated drinking water, only recently has a need for regulatory limits on iAs in food been recognized. The delay was due to the difficulty in risk assessment of dietary iAs, which critically relies on speciation analysis providing occurrence data for iAs in food - and not simply for total arsenic. In the present review the state of knowledge regarding arsenic speciation in food and diet is evaluated with focus on iAs and human exposure assessment through different dietary approaches including duplicate diet studies, market basket surveys, and total diet studies. The analytical requirements for obtaining reliable data for iAs in food are discussed and iAs levels in foods and beverages are summarized, along with information on other (potentially) toxic co-occurring organoarsenic compounds. Quantitative exposure assessment of iAs in food is addressed, focusing on the need of capturing variability and extent of exposure and identifying what dietary items drive very high exposure for certain population groups. Finally, gaps and uncertainties are discussed, including effect of processing and cooking, and iAs bioavailability.
Project description:A high particle to infectivity ratio is a feature common to many RNA viruses, with ~90-99% of particles unable to initiate a productive infection under low multiplicity conditions. A recent publication by Brooke et al. revealed that, for influenza A virus (IAV), a proportion of these seemingly non-infectious particles are in fact semi-infectious. Semi-infectious (SI) particles deliver an incomplete set of viral genes to the cell, and therefore cannot support a full cycle of replication unless complemented through co-infection. In addition to SI particles, IAV populations often contain defective-interfering (DI) particles, which actively interfere with production of infectious progeny. With the aim of understanding the significance to viral evolution of these incomplete particles, we tested the hypothesis that SI and DI particles promote diversification through reassortment. Our approach combined computational simulations with experimental determination of infection, co-infection and reassortment levels following co-inoculation of cultured cells with two distinct influenza A/Panama/2007/99 (H3N2)-based viruses. Computational results predicted enhanced reassortment at a given % infection or multiplicity of infection with increasing semi-infectious particle content. Comparison of experimental data to the model indicated that the likelihood that a given segment is missing varies among the segments and that most particles fail to deliver ?1 segment. To verify the prediction that SI particles augment reassortment, we performed co-infections using viruses exposed to low dose UV. As expected, the introduction of semi-infectious particles with UV-induced lesions enhanced reassortment. In contrast to SI particles, inclusion of DI particles in modeled virus populations could not account for observed reassortment outcomes. DI particles were furthermore found experimentally to suppress detectable reassortment, relative to that seen with standard virus stocks, most likely by interfering with production of infectious progeny from co-infected cells. These data indicate that semi-infectious particles increase the rate of reassortment and may therefore accelerate adaptive evolution of IAV.
Project description:Cell culture growth competition assays of human immunodeficiency virus type 1 (HIV-1) are used to estimate viral fitness and quantify the impact of mutations conferring drug resistance and immunological escape. A comprehensive study of growth competition assays was conducted and identified experimental parameters that can impact measurements of relative fitness including multiplicity of infection, viral input ratio, number, timing and interval of time points used to evaluate selective outgrowth, and the algorithm for calculating fitness values. An optimized protocol is developed here that is a multi-point growth competition assay that resolves reproducibly small differences in viral fitness. The optimized protocol uses an MOI of 0.005, a consistent ratio of mutant: parental viruses (70:30), and a multipoint [1+s 4,7] algorithm that uses data points within the logarithmic phase of viral growth for assessing fitness differences.