In this free webinar, the featured speaker will discuss new experimental workflows and technologies to enable safe handling of tissue from virally infected patients. Attendees will learn about the benefit of automated tissue dissociation into nuclei for single cell sequencing applications as well as the impact of COVID-19 in host gene transcription at single cell resolution and on host gene expression in a wide variety of organs.
The clinical manifestations of COVID-19 infections are highly variable between individuals and are not localized to the lungs and airway passages as seen with other respiratory viruses. In order to define appropriate therapeutic targets and mitigation strategies for COVID-19 infections, it is important to understand the impact of COVID-19 across a wide variety of organs at the cellular level.
To that end, we have conducted a survey of the effects of SARS-COV-2 infection on host gene expression, at the single cell level, across a wide array of tissues obtained from autopsies of confirmed COVID-19 patients. Tissues from nineteen COVID-19 autopsy patients, including seven from the US and twelve from Europe, were analyzed using single nuclei RNA sequencing (snRNA Seq), along with three non-COVID controls.
Six to eight different organs from each patient were analyzed, including heart, lung, liver, kidney, ileum, colon, spleen, prostate and testes. In all, gene expression analyses were performed on approximately 150 unique tissue specimens. The project required implementation of new experimental workflows and technologies to enable safe handling of the samples.
Join Bruce Wang, Assistant Professor in Residence, Div. of Gastroenterology, UCSF in a live webinar on Thursday, September 23, 2021 at 2pm EDT to hear a presentation of these methods along with the results obtained using tissue processing automation from S2 Genomics detailing the impact of COVID-19 on host gene expression.
For more information, or to register for this event, visit Impact of SARS-CoV-2 Infection on Host Gene Expression Across Multiple Tissues at Single Cell Resolution.
Source – PRWeb