István Csabai (ELTE Dept. of Physics of Complex Systems)

Mining genomic big data for the origin of COVID

Abstract: The COVID-19 pandemic has been going on for almost three years now and although many hypotheses have been put forward, its origin remain obscure.  We investigated whether the huge public sequencing data archives' samples collected earlier than the earliest known cases of the pandemic might contain traces of SARS-CoV-2. In the talk I will report the bioinformatic analysis of a metagenome sample set collected from soil on King George Island, Antarctica  between 2018-12-24 and 2019-01-13. Most probably as a result of contamination it contains sequence fragments matching the SARS-CoV-2 reference genome with altogether more than half million nucleotides, covering the complete genome on average 17x.
The sequence contains a unique combination of mutations, unseen in other samples and phylogeny analysis places the sample close to the earliest known lineages. We could also find likely genetic footprint of the hosts. With reasonable confidence we could identify genetic material from mitochondria of Homo sapiens, green monkey and Chinese hamster. These most likely originate from cell lines like Vero E6 and CHO, which are frequent laboratory culture media for studying viruses including SARS-CoV-2 and its closest relatives.
Depending on the currently unknown collection date of the alleged contaminating samples the recovered data can add important piece of information to the puzzle of the origin of the pandemic.

Links to the related preprints:

• https://www.researchsquare.com/article/rs-1177047/v1
• https://www.researchsquare.com/article/rs-1330800/v1

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