Exclusive: Secret gain-of-function research on novel coronavirus in Wuhan uncovered from mining genomic datasets with Steve Massey
Last week, Adrian Jones, Daoyu Zhang, Steven Massey, Yuri Deigin, Louis Nemzer, and Steven Quay reported out on an ingenious analysis of genomic datasets from NCBI that indicate a lab in Wuhan was performing potentially risky genetic engineering manipulations on a novel coronavirus that was previously unreported. The manipulation? Inserting a MERS spike protein into a previously unreported coronavirus. MERS has a case fatality rate of over 30%. What is clear from the analysis is that at least one lab in Wuhan was performing risky gain-of-function research on unreported coronaviruses before the pandemic started, the kind that could have created SARS-CoV-2. It also shows that risky GOF research is being conducted in Wuhan that has no identifiable medical benefit, but has the potential to create a pandemic level pathogen. Today I interview Steven Massey, a professor of bioinformatics that has been actively researching the origin of SARS-CoV-2 since the pandemic began and one of the authors of this significant discovery. We discuss the paper, how his team discovered this novel engineered coronavirus from Wuhan, and what it means in the search for the origin of COVID-19...
About Our Guest
Steve Massey is a professor of bioinformatics at the University of Puerto Rico. Steve has studied topics including the origin of life and the self-organization of the genetic code, the emergence of robustness in complex systems, social network analysis of biblical texts, and the deceptive signaling strategies of molecules, organisms and humans. The latter led him to study the deceptive strategies used by SARS-CoV-2 to manipulate the human host and promote its transmission through the population, which then led to his current interest in the origin of the virus itself. Steve has been conducting decentralized investigation with members of the DRASTIC group and others, in order to glean information from genomic datasets that may help shed light on whether SARS-CoV-2 emerged via zoonosis or a research related accident.
