The RNA rhinoviruses (RV) encode 2A proteases (2A pro ) that contribute essential polyprotein processing and host cell shutoff functions during infection, including the cleavage of Phe/Gly-containing nucleoporin proteins (Nups) within nuclear pore complexes (NPC). Within the 3 RV species, multiple divergent genotypes encode diverse 2A pro sequences that act differentially on specific Nups. Since only subsets of Phe/Gly motifs, particularly those within Nup62, Nup98, and Nup153, are recognized by transport receptors (karyopherins) when trafficking large molecular cargos through the NPC, the processing preferences of individual 2A pro predict RV genotype-specific targeting of NPC pathways and cargos. To test this idea, transformed HeLa cell lines were created with fluorescent cargos (mCherry) for the importin ␣/␤, transportin 1, and transportin 3 import pathways and the Crm1-mediated export pathway. Live-cell imaging of single cells expressing recombinant RV 2A pro (A16, A45, B04, B14, B52, C02, and C15) showed disruption of each pathway with measurably different efficiencies and reaction rates. The B04 and B52 proteases preferentially targeted Nups in the import pathways, while B04 and C15 proteases were more effective against the export pathway. Virus-type-specific trends were also observed during infection of cells with A16, B04, B14, and B52 viruses or their chimeras, as measured by NF-B (p65/Rel) translocation into the nucleus and the rates of virus-associated cytopathic effects. This study provides new tools for evaluating the host cell response to RV infections in real time and suggests that differential 2A pro activities explain, in part, strain-dependent host responses and diverse RV disease phenotypes.IMPORTANCE Genetic variation among human rhinovirus types includes unexpected diversity in the genes encoding viral proteases (2A pro ) that help these viruses achieve antihost responses. When the enzyme activities of 7 different 2A pro were measured comparatively in transformed cells programed with fluorescent reporter systems and by quantitative cell imaging, the cellular substrates, particularly in the nuclear pore complex, used by these proteases were indeed attacked at different rates and with different affinities. The importance of this finding is that it provides a mechanistic explanation for how different types (strains) of rhinoviruses may elicit different cell responses that directly or indirectly lead to distinct disease phenotypes.KEYWORDS 2A, live-cell imaging, nuclear export, nuclear localization, nuclear trafficking, protease, rhinovirus T he controlled trafficking of protein and RNA across the nuclear membrane is essential for many eukaryotic cellular processes. Nuclear pore complexes (NPC) are large proteinaceous channels embedded in the nuclear envelope that restrict and

Although virus release from host cells and tissues propels the spread of many infectious diseases, most virus particles are not infectious; many are defective, lacking essential genetic information needed for replication. When defective and viable particles enter the same cell, the defective particles can multiply while interfering with viable particle production. Defective interfering particles (DIPs) occur in nature, but their role in disease pathogenesis and spread is not known. Here, we engineered an RNA virus and its DIPs to express different fluorescent reporters, and we observed how DIPs impact viral gene expression and infection spread. Across thousands of host cells, co-infected with infectious virus and DIPs, gene expression was highly variable, but average levels of viral reporter expression fell at higher DIP doses. In cell populations spatial patterns of infection spread provided the first direct evidence for the co-transmission of DIPs with infectious virus. Patterns of spread were highly sensitive to the behavior of initial or early co-infected cells, with slower overall spread stemming from higher early DIP doses. Under such conditions striking patterns of patchy gene expression reflected localized regions of DIP or virus enrichment. From a broader perspective, these results suggest DIPs contribute to the ecological and evolutionary persistence of viruses in nature.

When viruses infect their host cells, they can make defective virus-like particles along with intact virus. Cells coinfected with virus and defective particles often exhibit interference with virus growth caused by the competition for resources by defective genomes. Recent reports of the coexistence and cotransmission of such defective interfering particles (DIPs) in vivo, across epidemiological length and time scales, suggest a role in viral pathogenesis, but it is not known how DIPs impact infection spread, even under controlled culture conditions. Using fluorescence microscopy, we quantified coinfections of vesicular stomatitis virus (VSV) expressing a fluorescent reporter protein and its DIPs on BHK-21 host cell monolayers. We found that viral gene expression was more delayed, infections spread more slowly, and patterns of spread became more “patchy” with higher DIP inputs to the initial cell. To examine how infection spread might depend on the behavior of the initial coinfected cell, we built a computational model, adapting a cellular automaton (CA) approach to incorporate kinetic data on virus growth for the first time. Specifically, changes in observed patterns of infection spread could be directly linked to previous high-throughput single-cell measures of virus-DIP coinfection. The CA model also provided testable hypotheses on the spatial-temporal distribution of the DIPs, which remain governed by their predator-prey interaction. More generally, this work offers a data-driven computational modeling approach for better understanding of how single infected cells impact the multiround spread of virus infections across cell populations. IMPORTANCE Defective interfering particles (DIPs) compete with intact virus, depleting host cell resources that are essential for virus growth and infection spread. However, it is not known how such competition, strong or weak, ultimately affects the way in which infections spread and cause disease. In this study, we address this unmet need by developing an integrated experimental-computational approach, which sheds new light on how infections spread. We anticipate that our approach will also be useful in the development of DIPs as therapeutic agents to manage the spread of viral infections.