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Deep mutational scanning of a model picornavirus: understanding the effects of mutations across all viral proteins and their role in innate immunity

Authors: Velandia-Álvarez, Sebastian; Álvarez-Rodríguez, Beatriz; Geller, Ron;

Deep mutational scanning of a model picornavirus: understanding the effects of mutations across all viral proteins and their role in innate immunity

Abstract

RNA viruses have the highest mutation rate in nature. This, combined with the rapid replication and relatively large population sizes, has allowed RNA viruses to rapidly evolve and adapt to new environments, counteracting different selective pressures such as antivirals, host immunity, among others. However, while the high mutation rate is key to successful adaptation, it also plays an important role in the generation of non-viable viruses, as most mutations tend to be deleterious for protein functions. How the viruses and their proteins contend with this process and achieve adaptation under different selective pressures (e.g. antibody neutralization, antivirals, innate immunity) is unclear. The study of this phenomenon is useful for understanding viral and protein biology and developing new therapeutic approaches. Deep Mutational Scanning (DMS) is a powerful tool for studying the questions raised, as it assesses all possible single amino acid mutations in a given protein. This method, combined with the application of a selective pressure can shed light on the mutations that are crucial for counteracting the effects of that force. For instance, coupling DMS with antibodies could help map important sites for neutralization and elucidate how the antibody response to a given virus is developed. Answering this type of questions can help develop new therapeutic approaches and understand how viruses might mutate under different pressures. Furthermore, DMS is a potent system to identify mutations that have a specific phenotype when subjected to different environments. Picornaviruses are (+)ssRNA viruses that infect a broad range of hosts including humans. Significant pathogens like poliovirus, enterovirus A71 and coxsackievirus are part of this group. These viruses possess multiple mechanisms to neutralize both innate and adaptive immune response. Some of these include inhibition of cellular translation, modification of vesicle trafficking, blockage of signaling pathways and cleavage of innate immunity effector proteins. The inhibition of innate immune pathways leads to a successful infection and the development of disease. Over the years, several picornaviral proteins have been shown to combat the innate immunity pathways. Moreover, innate immune response is essential for activating adaptive immunity and developing a strong long-lasting immune memory. We used DMS populations to define single amino acid mutations across the full proteome of Coxsackievirus B3 (CVB3) that confer resistance or sensitivity to interferon. We infected HeLa H1 cells with the populations in presence and absence of IFN. The resulting populations were subjected to high fidelity-next generation sequencing to identify mutations that increased or decreased significantly upon IFN treatment, indicating resistance or sensitivity to this antiviral mechanism. We identified several mutations conferring resistance or sensitivity using this approach. Validation was carried out by individually constructing mutant viruses, revealing that the identified mutants might be affected by two different mechanisms of the interferon effector pathway. Further analyses are being carried out to develop a novel live-attenuated vaccine candidate based on the combination of different mutations that confer sensitivity to IFN.

Resumen del póster presentado a las III Jornadas Científicas PTI+ Salud Global, celebradas en el Centro de Ciencias Humanas y Sociales (CCHS), CSIC (Madrid) del 20 al 22 de noviembre de 2023.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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