Unknown,Transcriptomics,Genomics,Proteomics

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Transcriptional responses of Middle East respiratory syndrome coronavirus (MERS-CoV) in marmosets

ABSTRACT: The absence of a robust disease model currently hinders the evaluation of countermeasures for Middle East respiratory syndrome coronavirus (MERS-CoV). While a rhesus macaque model of MERS-CoV that results in mild-to-moderate disease has been utilized to describe the pathogenesis of this virus and for the evaluation of therapeutics, the inability to produce uniform disease with substantial virus replication complicates analysis in countermeasure studies. In an attempt to identify a more robust disease model, DPP4 sequences of various non-human primates were aligned. Modeling of the interactions between the receptor binding domain of MERS-CoV and its cognate receptor DPP4 predicted a "good fit" with complete conservation of all of the critical residues. To determine the feasibility of the marmoset as a MERS-CoV disease model, common marmosets were inoculated with MERS-CoV via combined intratracheal, intranasal, oral and ocular routes. Marmosets developed signs of moderate to severe illness with progressive serious to severe pneumonia. Progressive gross lesions were evident in animals necropsied at 3, 4 and 6 days post inoculation and two animals were euthanized during the study due to disease severity. This is the first description of a moderate-to-severe, with potentially lethality, disease model of MERS-CoV and as such will have utility for vaccine and other countermeasure efficacy evaluations in addition to further pathogenesis studies. Lung tissue samples were isolated and sequenced at 3, 4 and 6 days post inoculation. Two animals were euthanized during the study due to disease severity.

ORGANISM(S): Callithrix jacchus

SUBMITTER: Michael Katze

PROVIDER: E-GEOD-55023 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Human coronaviruses have become an increasing threat to global health; three highly pathogenic strains have emerged since the early 2000s, including most recently SARS-CoV-2, the cause of COVID-19. A better understanding of the molecular mechanisms of coronavirus pathogenesis is needed, including how these highly virulent strains differ from those that cause milder, common-cold like disease. While significant progress has been made in understanding how SARS-CoV-2 proteins interact with the host cell, non-structural protein 3 (nsp3) has largely been omitted from the analyses. Nsp3 is a viral protease with important roles in viral protein biogenesis, replication complex formation, and modulation of host ubiquitinylation and ISGylation. Herein, we use affinity purification-mass spectrometry to study the host-viral protein-protein interactome of nsp3 from five coronavirus strains: pathogenic strains SARS-CoV-2, SARS-CoV, and MERS-CoV, and endemic common-cold strains hCoV-229E and hCoV-OC43. We divide each nsp3 into three fragments and use tandem mass tag technology to directly compare the interactors across the five strains for each fragment. We find that that few interactors are common across all variants for a particular fragment, but we identify shared patterns between select variants, such as ribosomal proteins enriched in the N-terminal fragment (nsp3.1) analysis for SARS-CoV-2 and SARS-CoV. We also identify unique biological processes enriched for individual homologs, for instance nuclear protein important for the middle fragment of hCoV-229E, as well as ribosome biogenesis of the MERS nsp3.1 homolog. Lastly, we further investigate the interaction of the SARS-CoV-2 nsp3.1 N-terminal fragment with ATF6, a regulator of the unfolded protein response. We show that SARS-CoV-2 nsp3.1 directly binds to ATF6 and can suppress the ATF6 stress response. Characterizing the host interactions of nsp3 widens our understanding of how coronaviruses co-opt cellular pathways and presents new avenues for host-targeted antiviral therapeutics.

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Transcriptional responses of Middle East respiratory syndrome coronavirus (MERS-CoV) in marmosets

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