Prior bovine immunodeficiency virus infection does not inhibit subsequent superinfection by the acutely pathogenic Jembrana disease virus

The role of virulence in in vivo superinfection fitness of the vertebrate RNA virus infectious hematopoietic necrosis virus

We have developed a novel in vivo superinfection fitness assay to examine superinfection dynamics and the role of virulence in superinfection fitness. This assay involves controlled, sequential infections of a natural vertebrate host, Oncorhynchus mykiss (rainbow trout), with variants of a coevolved viral pathogen, infectious hematopoietic necrosis virus (IHNV). Intervals between infections ranged from 12 h to 7 days, and both frequency of superinfection and viral replication levels were examined. Using virus genotype pairs of equal and unequal virulence, we observed that superinfection generally occurred with decreasing frequency as the interval between exposures to each genotype increased. For both the equal-virulence and unequal-virulence genotype pairs, the frequency of superinfection in most cases was the same regardless of which genotype was used in the primary exposure. The ability to replicate in the context of superinfection also did not differ between the genotypes of equal or unequal virulence tested here. For both genotype pairs, the mean viral load of the secondary virus was significantly reduced in superinfection while primary virus replication was unaffected. Our results demonstrate, for the two genotype pairs examined, that superinfection restriction does occur for IHNV and that higher virulence did not correlate with a significant difference in superinfection fitness. To our knowledge, this is the first assay to examine the role of virulence of an RNA virus in determining superinfection fitness dynamics within a natural vertebrate host.

True versus false parasite interactions: a robust method to take risk factors into account and its application to feline viruses

Background

Multiple infections are common in natural host populations and interspecific parasite interactions are therefore likely within a host individual. As they may seriously impact the circulation of certain parasites and the emergence and management of infectious diseases, their study is essential. In the field, detecting parasite interactions is rendered difficult by the fact that a large number of co-infected individuals may also be observed when two parasites share common risk factors. To correct for these “false interactions”, methods accounting for parasite risk factors must be used.

Methodology/Principal Findings

In the present paper we propose such a method for presence-absence data (i.e., serology). Our method enables the calculation of the expected frequencies of single and double infected individuals under the independence hypothesis, before comparing them to the observed ones using the chi-square statistic. The method is termed “the corrected chi-square.” Its robustness was compared to a pre-existing method based on logistic regression and the corrected chi-square proved to be much more robust for small sample sizes. Since the logistic regression approach is easier to implement, we propose as a rule of thumb to use the latter when the ratio between the sample size and the number of parameters is above ten. Applied to serological data for four viruses infecting cats, the approach revealed pairwise interactions between the Feline Herpesvirus, Parvovirus and Calicivirus, whereas the infection by FIV, the feline equivalent of HIV, did not modify the risk of infection by any of these viruses.

Conclusions/Significance

This work therefore points out possible interactions that can be further investigated in experimental conditions and, by providing a user-friendly R program and a tutorial example, offers new opportunities for animal and human epidemiologists to detect interactions of interest in the field, a crucial step in the challenge of multiple infections.