Biology subjects

Koelle, K.

Publications and source records attributed to Koelle, K..

6 recordsLinked to original sources

bioRxiv2018

Genetic signatures of human cytomegalovirus variants acquired by seronegative glycoprotein B vaccinees

Human cytomegalovirus (HCMV) is the most common congenital infection worldwide, and a frequent cause of hearing loss or debilitating neurologic disease in newborn infants. Thus, a vaccine to prevent HCMV-associated congenital disease is a public health priority. One potential strategy is vaccination of women of child-bearing age to prevent maternal HCMV acquisition during pregnancy. The glycoprotein B (gB) + MF59 adjuvant subunit vaccine is the most efficacious tested clinically to date, demonstrating approximately 50% protection against HCMV infection of seronegative women in multiple phase 2 trials. Yet, the impact of gB/MF59-elicited immune responses on the population of viruses acquired by trial participants has not been assessed. In this analysis, we employed quantitative PCR as well as multiple sequencing methodologies to interrogate the magnitude and genetic composition of HCMV populations infecting gB/MF59 vaccinees and placebo recipients. We identified several differences between the viral dynamics of acutely-infected vaccinees and placebo recipients. First, there was reduced magnitude viral shedding in the saliva of gB vaccinees. Additionally, employing a panel of tests for genetic compartmentalization, we noted tissue-specific gB haplotypes in the majority of vaccinees though only in a single placebo recipient. Finally, we observed reduced acquisition of genetically-related gB1, gB2, and gB4 genotype \"supergroup\" HCMV variants among vaccine recipients, suggesting that the gB1 genotype vaccine construct may have elicited partial protection against HCMV viruses with antigenically-similar gB sequences. These findings indicate that gB immunization may have had a measurable impact on viral intrahost population dynamics and support future analysis of a larger cohort.\n\nAuthor SummaryThough not a household name like Zika virus, human cytomegalovirus (HCMV) causes permanent neurologic disability in one newborn child every hour in the United States - more than Down syndrome, fetal alcohol syndrome, and neural tube defects combined. There are currently no established effective preventative measures to inhibit congenital HCMV transmission following acute or chronic HCMV infection of a pregnant mother. However, the glycoprotein B (gB) vaccine is the most effective HCMV vaccine tried clinically to date. Here, we utilized high-throughput, next-generation sequencing of viral DNA isolated from patients enrolled in a gB vaccine trial, and identified several impacts that this vaccine had on the size, distribution, and composition of the in vivo viral population. These results have increased our understanding of why the gB/MF59 vaccine was partially efficacious and will inform future rational design of a vaccine to prevent congenital HCMV.

microbiology↗

bioRxiv2018

Why Are CD8 T Cell Epitopes of Human Influenza A Virus Conserved?

The high-degree conservation of CD8 T cell epitopes of influenza A virus (IAV) may allow T cell-inducing vaccines effective across different strains and subtypes. This conservation is not fully explained by functional constraint, since additional mutation(s) can compensate the replicative fitness loss of IAV escape-variant. Here, we propose three additional mechanisms that contribute to the conservation of CD8 T cell epitopes of IAV. First, influenza-specific CD8 T cells may protect predominantly against severe pathology rather than infection and may only have a modest effect on transmission. Second, polymorphism of human MHC-I gene restricts the advantage of an escape-variant to only a small fraction of human population, who carry the relevant MHC-I alleles. Finally, infection with CD8 T cell-escapevariants may result in compensatory increase in the responses to other epitopes of IAV. A combination of population genetics and epidemiological models is used to examine how the interplay between these mechanisms affects the rate of invasion of IAV escape-variants. We conclude that the invasion of an escape-variant will be very slow with a timescale of decades or longer, even if the escape-variant does not have a replicative fitness loss. Our results suggest T cell-inducing vaccines may not engender the rapid evolution of IAV and serve as a foundation for future modeling works on the long-term effectiveness and impacts of T cell-inducing influenza vaccines. (Word count: 221)\n\nImportanceUniversal influenza vaccines against the conserved epitopes of influenza A virus have been proposed to minimize the burden of seasonal outbreaks and prepare for the pandemics. However, it is not clear to which extent the T cell-inducing vaccines will select for viruses that escape the T cell responses. Our mathematical models suggest how the nature of CD8 T cell protection contributes to the conservation of the CD8 T cell epitopes of influenza A virus. Also, it points out the essential biological parameters and questions that need addressing by future experimental works. (Word count: 91)

immunology↗

bioRxiv2018

Within-host infectious disease models accommodating cellular coinfection, with an application to influenza

Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (for example, cells that are refractory to infection and cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological macroparasite models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as hosts and viral particles as macroparasites, and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cells multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, that they can reproduce notable features of within-host viral dynamics, and that important in vivo quantities such as the mean multiplicity of cellular infection can be easily quantified with these models once parameterized. The within-host model structure we develop here provides an alternative approach for modeling within-host viral load dynamics and allows for a new class of questions to be addressed that consider the effects of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

epidemiology↗

bioRxiv2017

Selection on non-antigenic gene segments of seasonal influenza A virus and its impact on adaptive evolution

Most studies on seasonal influenza A/H3N2 virus adaptation have focused on the main antigenic gene, haemagglutinin. However, there is increasing evidence that the genome-wide genetic background of novel antigenic variants can influence these variants emergence probabilities and impact their patterns of dominance in the population. This suggests that non-antigenic genes may be important in shaping the viral evolutionary dynamics. To better understand the role of selection on non-antigenic genes in the adaptive evolution of seasonal influenza viruses, we here develop a simple population genetic model that considers a virus with one antigenic and one non-antigenic gene segment. By simulating this model under different regimes of selection and reassortment, we find that the empirical patterns of lineage turnover for the antigenic and non-antigenic gene segments are best captured when there is both limited viral coinfection and selection operating on both gene segments. In contrast, under a scenario of only neutral evolution in the non-antigenic gene segment, we see persistence of multiple lineages for long periods of time in that segment, which is not compatible with the observed molecular evolutionary patterns. Further, we find that reassortment, occurring in coinfected individuals, can increase the speed of viral adaptive evolution by primarily reducing selective interference and genetic linkage effects mediated by the non-antigenic gene segment. Together, these findings suggest that, for influenza, with 6 internal or non-antigenic gene segments, the evolutionary dynamics of novel antigenic variants are likely to be influenced by the genome-wide genetic background as a result of linked selection among both beneficial and deleterious mutations.

evolutionary biology↗

bioRxiv2017

Preexisting antibodies can protect against congenital cytomegalovirus infection in monkeys

Human cytomegalovirus (HCMV) is the most common congenital infection and a known cause of microcephaly, sensorineural hearing loss, and cognitive impairment among newborns worldwide. Natural maternal HCMV immunity reduces the incidence of congenital infection, but does not prevent the disease altogether. We employed a nonhuman primate model of congenital CMV infection to investigate the ability of preexisting antibodies to protect against placental CMV transmission. Pregnant, CD4+ T cell-depleted, rhesus CMV (RhCMV)-seronegative rhesus monkeys were treated with either standardly-produced hyperimmune globulin (HIG) from RhCMV-seropositive macaques or dose-optimized, potently RhCMV-neutralizing HIG prior to intravenous challenge with an RhCMV swarm. HIG passive infusion provided complete protection against fetal loss in both groups, and the potently-neutralizing HIG additionally inhibited placental transmission of RhCMV. Our findings suggest that antibody alone at the time of primary infection can prevent congenital CMV and therefore could be a primary target of vaccines to eliminate this neonatal infection.

immunology↗

bioRxiv2017

Transmission Bottleneck Size Estimation from Pathogen Deep-Sequencing Data, with an Application to Human Influenza A Virus

The bottleneck governing infectious disease transmission describes the size of the pathogen population transferred from a donor to a recipient host. Accurate quantification of the bottleneck size is of particular importance for rapidly evolving pathogens such as influenza virus, as narrow bottlenecks would limit the extent of transferred viral genetic diversity and, thus, have the potential to slow the rate of viral adaptation. Previous studies have estimated the transmission bottleneck size governing viral transmission through statistical analyses of variants identified in pathogen sequencing data. The methods used by these studies, however, did not account for variant calling thresholds and stochastic dynamics of the viral population within recipient hosts. Because these factors can skew bottleneck size estimates, we here introduce a new method for inferring transmission bottleneck sizes that explicitly takes these factors into account. We compare our method, based on beta-binomial sampling, with existing methods in the literature for their ability to recover the transmission bottleneck size of a simulated dataset. This comparison demonstrates that the beta-binomial sampling method is best able to accurately infer the simulated bottleneck size. We then apply our method to a recently published dataset of influenza A H1N1p and H3N2 infections, for which viral deep sequencing data from inferred donor-recipient transmission pairs are available. Our results indicate that transmission bottleneck sizes across transmission pairs are variable, yet that there is no significant difference in the overall bottleneck sizes inferred for H1N1p and H3N2. The mean bottleneck size for influenza virus in this study, considering all transmission pairs, was Nb = 196 (95% confidence interval 66-392) virions. While this estimate is consistent with previous bottleneck size estimates for this dataset, it is considerably higher than the bottleneck sizes estimated for influenza from other datasets.\n\nAuthor SummaryThe transmission bottleneck size describes the size of the pathogen population transferred from the donor to recipient host at the onset of infection and is a key factor in determining the rate at which a pathogen can adapt within a host population. Recent advances in sequencing technology have enabled the bottleneck size to be estimated from pathogen sequence data, though there is not yet a consensus on the statistical method to use. In this study, we introduce a new approach for inferring the transmission bottleneck size from sequencing data that accounts for the criteria used to identify sequence variants and stochasticity in pathogen replication dynamics. We show that the failure to account for these factors may lead to underestimation of the transmission bottleneck size. We apply this method to a previous dataset of human influenza A infections, showing that transmission is governed by a loose transmission bottleneck and that the bottleneck size is highly variable across transmission events. This work advances our understanding of the bottleneck size governing influenza infection and introduces a method for estimating the bottleneck size that can be applied to other rapidly evolving RNA viruses, such as norovirus and RSV.

microbiology↗