Multiple viral infections in Agaricus bisporus - characterisation of 18 unique RNA viruses and 8 ORFans identified by deep sequencing

Thirty unique non-host RNAs were sequenced in the cultivated fungus, Agaricus bisporus, comprising 18 viruses each encoding an RdRp domain with an additional 8 ORFans (non-host RNAs with no similarity to known sequences). Two viruses were multipartite with component RNAs showing correlative abundances and common 3′ motifs. The viruses, all positive sense single-stranded, were classified into diverse orders/families. Multiple infections of Agaricus may represent a diverse, dynamic and interactive viral ecosystem with sequence variability ranging over 2 orders of magnitude and evidence of recombination, horizontal gene transfer and variable fragment numbers. Large numbers of viral RNAs were detected in multiple Agaricus samples; up to 24 in samples symptomatic for disease and 8–17 in asymptomatic samples, suggesting adaptive strategies for co-existence. The viral composition of growing cultures was dynamic, with evidence of gains and losses depending on the environment and included new hypothetical viruses when compared with the current transcriptome and EST databases. As the non-cellular transmission of mycoviruses is rare, the founding infections may be ancient, preserved in wild Agaricus populations, which act as reservoirs for subsequent cell-to-cell infection when host populations are expanded massively through fungiculture

Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling

International audienceEvidence is mounting that influenza virus interacts with other pathogens colonising or infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. This is particularly true for mathematical modelling studies, which have become critical in public health decision-making. Yet models usually focus on influenza virus acquisition and infection alone, thereby making broad oversimplifications of pathogen ecology. Herein, we report evidence of influenza virus interactions with bacteria and viruses and systematically review the modelling studies that have incorporated interactions. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitidis, respiratory syncytial virus (RSV), human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. The notable exception is the pneumococcus-influenza interaction, for which several recent modelling studies demonstrate the power of dynamic modelling as an approach to test biological hypotheses on interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and possible misinterpretation, and we illustrate the impact of interactions on public health surveillance using simple transmission models. We demonstrate that the development of multipathogen models is essential to assessing the true public health burden of influenza and that it is needed to help improve planning and evaluation of control measures. Finally, we identify the public health, surveillance, modelling, and biological challenges and propose avenues of research for the coming years