Initial findings reported by the Arizona COVID-19 Genomics Union (ACGU) suggest that following Arizona’s first reported case of COVID-19 in late January, the state experienced no subsequent cases that went undetected and was COVID-free until at least 11 distinct incursions occurred between mid-February and early April.
The published results appear in the scientific journal mBio.
Faculty at Northern Arizona University (NAU), the Translational Genomics Research Institute (TGen), an affiliate of City of Hope, University of Arizona (UArizona) and Arizona State University (ASU) launched the ACGU in early April with the express purpose of tracking the causative agent of COVID-19, SARS-CoV-2: how it evolves and how it spreads into, within and out of Arizona.
The ACGU sequenced the SARS-CoV-2 genomes in as many virus-positive patient samples in Arizona as possible, and working with Arizona’s public health officials, applied the results toward statewide efforts to test and track patients, as well as provide guidance for Arizona public policy makers.
Quick action by ASU and Maricopa County public health officials, ACGU scientists agree, likely kept the first identified COVID-19 patient in Arizona — a student who had just returned from Hubei, the Chinese province where the disease originated — from igniting an outbreak, and prevented Arizona from becoming an early epicenter for the contagion.
“This is a great example of how a rapid and thorough public health response can be successful in preventing the spread of this disease,” said Paul Keim, ACGU co-founder and director, NAU Regents’ Professor of Biological Sciences and Cowden Endowed Chair in Microbiology and Executive Director of NAU’s Pathogen and Microbiome Institute (PMI). Seven additional PMI scientists also contributed to this study as co-first authors or co-authors.
“Similar steps could be taken when shaping future efforts to reopen businesses and schools, even though the virus continues to circulate and people remain susceptible,” added Keim, who is also a Distinguished Professor and Co-Director of TGen’s Pathogen and Microbiome Division.
Michael Worobey, an ACGU co-founder and the head of University of Arizona’s Department of Ecology and Evolutionary Biology, agrees.
“It’s a combination of the patient doing the right things to isolate himself and be aware that he possibly had this disease, and public health officials doing all the right things. Stopping an incursion of COVID-19 was a victory for the state of Arizona,” Worobey said.
This bought Arizona valuable time for preparedness efforts. The first reported case of “community” transmission occurred in Arizona in early March descended from the Washington state outbreak that was discovered in February. More than 80 percent of the SARS-CoV-2 genome sequences from Arizona COVID-19 cases descended from at least 11 separate lineages that were initially circulating widely in Europe, and by travel have since dominated the outbreak throughout the U.S. None of the observed transmission clusters are epidemiologically linked to the original travel-related case in the Arizona, suggesting successful early isolation and quarantine.
The ACGU uses state-of-the-art sequencers, custom computational analysis workflows and supercomputers to determine the sequence of the virus’s RNA genome, which is just under 30,000 bases long. In contrast, there are nearly 3 billion bases in the human genome, which determine traits as simple as eye and hair color, and as complex as an individual’s propensity for cancer and other disease.
TGen has so far sequenced SARS-CoV-2 genomes from almost 3,000 COVID-19 positive samples for the ACGU, and additional sequencing was performed at ASU and UA, from among the more than 200,000 positive cases in Arizona, making it one of the most robust such efforts in the nation. ACGU receives Arizona samples collected by state, county, tribal and private healthcare systems.
With the massive amount of data generated through the genomic sequencing, even the most advanced computing resources would not be able to keep pace; custom software was developed to support the ACGU work. Greg Caporaso, NAU Associate Professor of Biology and Director of PMI’s Center for Applied Microbiome Science, observed, “Integrating the SARS-CoV-2 genomes sequenced from patients in Arizona with those sequenced around the world required us to work quickly to develop new software to support our work. Our new software allows us to identify a highly informative subset of the globally available genomes to analyze, which make the analysis more computationally tractable while retaining information that is essential for contextualizing the Arizona sequences.” Caporaso’s team has released the new software under an open source license, which is free for all use as a contribution to global coronavirus research; see this paper describing the software.
ACGU scientists take advantage of small changes or mutations in the virus’ genome, which naturally occur over time as the virus reproduces, to track the spread of the virus. By comparing mutations observed in Arizona to those present in strains circulating across the globe, they can determine when and from where the virus has been introduced to Arizona.
Crystal Hepp, NAU Assistant Professor in the School of Informatics, Computing, and Cyber Systems and Assistant Director of PMI, noted, “The rate that mutations accumulate in the virus or viral population can be used as a ‘molecular clock’ to understand when it arrived in Arizona and to further estimate the magnitude of the outbreak.” The ACGU researchers found that the majority of Arizona sequences are represented by two lineages — and several sub-lineages — most of which were likely introduced through domestic travel, but with some evidence for international importation.
Jason Ladner, NAU Assistant Professor of Biology and Assistant Director of PMI, used similar analysis on the Ebola outbreak in West Africa. He said, “evolutionary analysis of disease outbreaks is one of the most important tools for understanding the origins of new viruses, like this novel coronavirus. Applying this technology to Arizona gives us local insights into how the disease has been spreading and what interventions will likely be most beneficial to control the spread of the virus.”
“Through the ACGU, we are harnessing expertise in virology, genomics, evolution and bioinformatics from throughout Arizona in order to rapidly distill these genomic data into actionable insights that can complement the state’s public health response,” Keim said. “These results demonstrate the power of public health contact tracing and self-isolation following a positive test for stemming the tide of infections moving forward.”
David Engelthaler, Director of TGen North in Flagstaff, which includes the institute’s infectious disease branch, said the initial ACGU findings show how each community, each state is writing its own story for what is happening in the COVID-19 pandemic.
“We need to understand all of those plot lines that have led to where we are now,” said Engelthaler, an ACGU co-founder. “Once this disease was detected in Arizona on Jan. 26, public health immediately jumped in to make sure that all contacts were identified, samples were collected and the patient was watched very closely for the next couple of weeks to make sure there were not any more cases.”
In the coming months, he said, it will be necessary to track COVID-19 outbreaks and build epidemiological walls around each case, especially for those most at risk: persons older than 65, those in long-term care facilities, prisons and those with pre-existing health problems.
“When you don’t have eyes on this, when you don’t have contact tracing, then it can really easily move from person-to-person,” Engelthaler said. “It’s really useful for public policy makers to be making locally-informed decisions.”
Efrem Lim, a virologist who leads the ASU team, said the SARS-CoV-2 genome sequence data can give health care providers and public policy makers an edge in fighting the pandemic.
“Tracking the transmission of the virus and its mutations ensures that therapeutics and vaccines being developed are on the right course,” said Lim, an assistant professor at ASU’s Biodesign Institute. “We now have a handle on what the SARS-CoV-2 virus in our communities looks like at the sequence level.”
This study — An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona — was supported by The NARBHA Institute, Flinn Foundation, The Virginia G. Piper Charitable Trust, Blue Cross and Blue Shield of Arizona, the National Institutes of Health, the David and Lucile Packard Foundation, the University of Arizona College of Science and Office of Research Innovation and Impact and BIO5 Institute.
The authors acknowledge the critical role the Arizona Department of Health Services and multiple county and tribal health departments play in directing samples to the ACGU to be sequenced. Computational analyses were run on Northern Arizona University’s Monsoon high-performance computing cluster, funded by Arizona’s Technology and Research Initiative Fund. Software development efforts were funded in part by the Chan-Zuckerberg Initiative and the Alfred P. Sloan Foundation. Additional analysis effort was funded under the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through NAU. The Cowden Endowment for Microbiology provided funds to support salaries.
Steve Yozwiak, TGen and
Kerry Bennett, Office of the Vice President for Research
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