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  1. MCM Regulatory Science

FDA and global partners to analyze coronavirus samples

Effort to help inform development of SARS-COV-2 diagnostics, vaccines, and therapeutics

Creative rendition of SARS-CoV-2 virus particles. (Note: not to scale.) Credit: NIAID
Creative rendition of SARS-CoV-2 virus particles. (Note: not to scale.) Credit: NIAID

Background | Project description | Project outcomes | Additional reading

Performer: University of Liverpool
Project leader: Julian Hiscox, PhD
Contract value: $5,402,198
Project dates: September 2020 – September 2023


The emergence of SARS-CoV-2 in 2019 and the associated COVID-19 pandemic, and prior SARS-CoV and MERS-CoV outbreaks, demonstrate the significant threat posed by coronaviruses. Since there are currently no licensed therapeutics or vaccines to prevent or treat infections from these specific viruses or coronaviruses in general, there is an urgent need to support development and evaluation of relevant medical countermeasures (MCMs).

Project description

In this Medical Countermeasures Initiative (MCMi) regulatory science project, the University of Liverpool (ULIV) and international partners will analyze SARS-CoV-2, SARS-CoV, and MERS-CoV clinical samples, collected through global partnerships, to better understand coronavirus evolution and virulence, characterize host-pathogen interactions and immunity, and identify biomarkers of disease progression and severity. Through the sequence analysis of current and ongoing collection of samples from humans and animals, this project will help inform the real-time performance of molecular-based diagnostics (e.g., genetic drift that may evade the current molecular diagnostic tests).

This project also has the potential to provide a better understanding of vaccine and therapeutic targets, including biomarkers of protection, potential development of antiviral resistance, and host-directed therapeutics for a broad range of coronaviruses. The pattern of severe disease in COVID-19 is similar to both MERS and SARS, particularly with regard to an enhanced and overt host inflammatory response. This will be investigated and compared in human and animal models. Identification of potentially common pathways would provide necessary information for development of host-directed MCMs.

The project will also examine in vitro models of coronavirus infection, including human organs-on-chips, to elucidate how these models compare to in vivo responses in animal models and humans. Ultimately, these in vitro models will result in enhanced MCM screening methods.

Collaborators include:

Project outcomes

During this project, the University of Liverpool and international partners listed above, will perform RNA sequencing and immunological analysis of samples from patients who were infected with SARS-CoV-2, SARS-CoV, and MERS-CoV during the 2019-20 pandemic and outbreaks in 2003-2004 (SARS-CoV) and MERS-CoV (since 2012). The project will use a biobank of diverse samples from humans with these infections and compare their response to relevant animal models and in vitro systems being used to develop MCMs.

Major objectives of this project include:

  • Characterizing viral genetics during infection and identifying whether sites targeted by diagnostics and therapeutics are under selection pressure. This will also assess whether the major drivers in evolution are mutation and/or recombination; the latter is a natural byproduct of coronavirus RNA synthesis.
  • Assessing the host response to mild and severe coronavirus infection and identifying any commonalities and differences. This will correlate observations in humans with findings from relevant animal models used in the development of MCMs. Here machine learning approaches will be used to interrogate the large datasets generated and identify patterns.
  • Further characterizing the properties of SARS-CoV-2 and MERS-CoV in cell culture with a specific focus on cell lines and systems used for screening candidate MCMs.
  • Developing and assessing organs-on-chips technology for investigating severe coronavirus infection and their application to MCM evaluation. This will use the data generated in the previous objectives for both human infections and animal models.

The primary planned outcomes of this project are to:

  1. Identify viral evolution in longitudinal samples (nasal aspirates/blood/plasma) taken from patients with MERS-CoV and SARS-CoV-2 using Illumina, PacBio, and Oxford Nanopore-based technologies.
  2. Identify host biomarkers and immune responses through gene and protein expression patterns, using RNAseq, long read sequencing, proteomics, machine learning, digital cell quantification, cytometry, and multiplex tissue imaging in longitudinal samples taken from patients with SARS-CoV, MERS-CoV, and SARS-CoV-2 with metadata including clinical information on disease progression and outcomes.
  3. Characterization of in vitro host pathogen interactions and comparison to in vivo responses for SARS-CoV, MERS-CoV, and SARS-CoV-2. This will range from using traditional continuous cell culture models for benchmarked high-throughput analysis to three-dimensional culture from clinical samples to emerging technologies such as organs-on-chips and marrying with approaches including CODEX.

This project is funded through the MCMi Regulatory Science Extramural Research program, and is supported through partnership with the Office of Biodefense Research Resources, and Translational Research, Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH).

Additional reading

Moore SC, Penrice-Randal R, Alruwaili M, et al. Amplicon based MinION sequencing of SARS-CoV-2 and metagenomic characterisation of nasopharyngeal swabs from patients with COVID-19. MedRxiv [preprint]. 2020 Mar 8. DOI: 10.1101/2020.03.05.20032011 - full text (open access)

Davidson AD, Williamson MK, Lewis S, et al. Characterisation of the transcriptome and proteome of SARS-CoV-2 using direct RNA sequencing and tandem mass spectrometry reveals evidence for a cell passage induced in-frame deletion in the spike glycoprotein that removes the furin-like cleavage site. Genome Medicine. 2020 Mar 24. DOI: 10.1186/s13073-020-00763-0 - full text (open access)

Daly JL,  Simonetti B,  Antón-Plágaro C, et al. Neuropilin-1 is a host factor for SARS-CoV-2 infection. Dose-dependent response to infection with SARS-CoV-2 in the ferret model: evidence of protection to re-challenge BioRxiv [preprint]. 05 Jun 2020. DOI: 10.1101/2020.06.05.134114 - full text (open access)

Ryan KA, Bewley KR, Fotheringham SA, et al. Dose-dependent response to infection with SARS-CoV-2 in the ferret model: evidence of protection to re-challenge. BioRxiv [preprint]. 29 May 2020. DOI: 10.1101/2020.05.29.123810 - full text (open access)



  • Jordan J. Clark, Rebekah Penrice-Randal, Parul Sharma, Anja Kipar, Xiaofeng Dong, Andrew Davidson, Maia Kavanagh Williamson, David A. Matthews, Lance Turtle, Tessa Prince, Grant L. Hughes, Edward. Patterson, Ghada Shawli, Krishanthi Subramaniam, Jo Sharp, Lynn McLaughlin, En-Min Zhou, Joseph D. Turner, Amy E. Marriott, Stefano Colombo, Shaun H. Pennington, Giancarlo Biagini, Andrew Owen, Julian A. Hiscox, James P. Stewart. Sequential infection with influenza A virus followed by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to more severe disease and encephalitis in a mouse model of COVID-19. bioRxiv. [preprint] 2020 Oct 13 DOI: 10.1101/2020.10.13.334532 - full text (open access)
  • David A Dorward, Clark D Russell, In Hwa Um , Mustafa Elshani, Stuart D Armstrong, Rebekah Penrice-Randal, Tracey Millar, Chris Eb Lerpiniere, Giulia Tagliavini, Catherine S Hartley, Nadine P Randle, Naomi N Gachanja, Philippe Md Potey, Xiaofeng Dong, Alison M Anderson, Victoria L Campbell, Alasdair J Duguid, Wael Al Qsous, Ralph BouHaidar, J Kenneth Baillie, Kevin Dhaliwal, William A Wallace, Christopher Oc Bellamy, Sandrine Prost, Colin Smith, Julian A Hiscox, David J Harrison, Christopher D Lucas. Tissue-specific Immunopathology in Fatal COVID-19. PubMed. [preprint] 2020 Nov 20 DOI:  10.1164/rccm.202008-3265OC – full text (open access)

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