Virus samples in ancient glacier may help predict our future

Chris Burns - Jul 23, 2021, 10:43am CDT
Virus samples in ancient glacier may help predict our future

In what feels like the first chapter in an apocalyptic science fiction story, scientists reported this week that they’d discovered a set of ancient viruses in glacier ice. Using Guliya ice cap core samples first harvested back in 2015, these researchers have discovered genetic code for 33 viruses. Just 4 of those viruses were previously known by modern humans, the rest are “novel” – previously unknown to the scientific community.

This is just the third time in modern history that a virus has been discovered in a glacier. This is largely because the methods of harvesting, detecting, and analyzing glacier samples looking for microbes and phages is only very recently developed to the point where this data can be useful.

The viruses discovered in the Guliya ice cap were analyzed, their genes compared to known viruses, and cataloged as such. Per the research published this week, the previously-unknown viruses found in this study likely originated from soil or plants, between hundreds and thousands of years ago.

Of the 33 viruses analyzed, this study found “28 novel genera and not a single species shared with 225 environmentally diverse viromes.” This is important – discovering evidence of ancient microbiology allows researchers to fill in gaps in our understanding of history, and assist us in predicting change in the natural world in the future.

To be extra clear, here, this isn’t like a sci-fi end-of-world story, and the viruses these researchers are digging up aren’t going to infect us and end all life on earth. They’re finding evidence of viruses that are more in danger of being destroyed by the temperature of an examination lab than we are of being harmed by them.

For more information on this study, see the paper Glacier ice archives nearly 15,000-year-old microbes and phages as authored by Zhi-Ping Zhong et. al. This paper appear in Microbiome 9, Article number: 160 (2021). This research can be found with code DOI:10.1186/s40168-021-01106-w as of July 20, 2021.


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