The transmission of SARS-CoV-1 to humans in 2002, MERS-CoV from dromedary camels to humans in 2012, and SARS-CoV-2 from bats to human in 2019 resulted in widespread infections, numerous deaths, and economic impact. These strains belong to a common family of viruses called Coronaviridae, and have been repeatedly shown that the most troublesome health issue that we are facing concern encompasses not just humans, but the entire biosphere. We, in fact, all live in this global petri dish.

What it does

We developed this new toolbox that quantifies and visualizes the evolution of various coronaviruses across different species, increasing their host range, and becoming more infectious. We aim to use this information to understand coronavirus beyond its circulation in humans, and identify types of transmissions that are susceptible to allowing non-neutral mutations across major strains of the coronavirus and ultimately, help develop pandemic-prevention strategies that will incorporate the various risks of zoonotic disease transfer.

On the web page, users can select two animals (e.g. bats and human), and a corona virus variant (e.g. sars-cov-2) of interest for comparison. After hitting the "enter" button, users can view graphics pointing out locations of neutral/beneficial/harmful mutations on the virus's gnome sequence, and metrics such as the Tajima D score that identify whether or not the observed mutations are random or under selective pressure. Data sets for animal pairs that reveal a high degree of selective pressure indicate higher risks of zoonotic transfers producing novel strains of coronavirus.

These kinds of evolutionary statistics are not commonly used for viruses. In fact, it has only been used to study the evolutionary nature of human immunodeficiency virus in the past. Applying the same methodologies to the coronavirus could reveal new information that has not been elucidated yet.

How we built it

  • We gathered gnome sequence for MERS-CoV, SARS-CoV-1, SARS-CoV-2 across animals such as bats, camels, humans, mice, cows, and pigs.
  • We used the Tajima D's test in python to compute the similarity between the sequences and assess the variations they present. (Using the ClustalOmega Multiple Sequence Alignment Tool )

  • We developed a web page to showcase the results, with technologies such as Flask and Tableau.

    What's next for Next-Door Neighbor

  • Adding more features on the results page, such as a geographical distribution of the animals of interest, which allows users to visualize where the spread of the virus from one species to another is most susceptible. In addition, we hope to add more detailed visualizations of the differences between strains that are being compared, including mutation and phylogenetic analyses.

  • Pending further developments, our interactive tool will be fully functional on our website and will serve as a source of information for other researchers investigating similar ideas.

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