The University of California, San Francisco (UCSF) Bakar Computational Health Sciences Institute capitalized on powerful cloud-based computing made possible by Amazon Web Services (AWS) to enable two projects involving the sequencing of genomes of the viruses infecting hundreds of COVID-19 patients in the San Francisco Bay Area using CRISPR gene-technology in a research study. Front and center in this innovative effort was the laboratory of Charles Chiu, MD, PhD.
As recently announced from the Bakar Institute, data and computation represent hallmarks of the newest paradigm of scientific research, especially in this time of COVID-19 where innovation drives discovery. Technology is absolutely key to helping researchers work more effectively with data in support of mission-critical COVID-19 studies. Amazon Web Services (AWS—the cloud computing division of Seattle-based Amazon) offered their support and donated service credits provided by the AWS Diagnostic Development Initiative for cutting edge COVID-19 research at the University of California, San Francisco (UCSF).
The COVID-19 Host Transcriptome Profiling Project—What is this?
The translational research laboratory team, led by Dr. Chiu, is performing transcriptome analysis of nasal swab and whole blood samples from patients with viral respiratory infection to identify specific biomarkers of the disease.
What have the accomplished thus far?
To date, the team have identified distinct signatures for influenza, RSV (respiratory syncytial virus), bacterial sepsis, Lyme disease, and babesiosis.
What is UCSF’s relevant hypothesis here?
They have formulated a hypothesis that COVID-19 infection may evoke a specific and distinct host response in infected patients that would be detectable by RNA sequencing, and that machine-learning based models can discriminate between respiratory viral infections on the basis of the host response. Hence, indirect diagnostic testing on the basis of the early host response may be critical to aiding rapid response efforts as recent data has suggested that SARS-CoV-2 is associated with asymptomatic infection and transmission.
How did AWS help Chui and team with the COVID-19 viral Genomic Sequencing Project?
The AWS infrastructure supported the development of a method (metagenomic sequencing with spiked primer enrichment, MSSPE) that will enrich metagenomic libraries for 2019-nCOV genome sequences. The method is complementary to other methods of viral genome sequence recovery, and is particularly useful for analysis of nasopharyngeal swab samples with low viral concentrations.
How has the UCSF team leveraged this new method?
The team used the new method, powered by AWS, to conduct a genomic survey of SARS-CoV-2 strains circulating in California. For example, the team was able to demonstrate that the strain of SARS-CoV-2 that infected people aboard the Grand Princess cruise ship clusters with the WA1 strain predominantly circulating in Washington State.
And now the team is collaborating with the US CDC, California Department of Public Health, and the Santa Clara Department of Public Health to conduct real-time, genomic surveillance of SARS-CoV-2 infection in California.
Why is this work so important?
Well this work, led by Chiu at his lab at UCSF’s Bakar Computational Health Sciences Institute along with the technology offered by AWS, helps health agencies track mutations and the spread of the infection—essential work for guiding public health interventions to minimize further spread of the virus while residents are told to “shelter in place.” Emphasizing the importance of the technology elements, Chiu noted, “In today’s rapid-changing environment around the COVID-19 pandemic, cloud computing resources will accelerate our efforts to design the next generation of diagnostic tests and provide real-time, actionable genomic data to inform the public health response.”
Charles Chiu, MD, PhD
Call to Action: Interested in learning more about how the UCSF Bakar Computational Health Sciences Institute developed this approach? We include Chiu’s contact details.Source: UCSF Bakar Computational Health Sciences Institute