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Today's Topics:
1. 70k new RNA viruses identified using AI metagenomics
(Stephen Loosley)
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Date: Sat, 12 Oct 2024 22:46:44 +1030
From: Stephen Loosley <[email protected]>
To: "link" <[email protected]>
Subject: [LINK] 70k new RNA viruses identified using AI metagenomics
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AI scans RNA ?dark matter? and uncovers 70,000 new viruses
Many are bizarre and live in salt lakes, hydrothermal vents and other extreme
environments.
By Smriti Mallapaty 11 October 2024
https://www.nature.com/articles/d41586-024-03320-6
[Photo caption: Observation of the basaltic organs of the Panarea volcanic
island in the Aeolian islands archipelago, Mediterranean Sea.
Some of the newly discovered viruses live in hydrothermal vents and other
extreme environments. Credit: Alexis Rosenfeld/Getty]
Researchers have used artificial intelligence (AI) to uncover 70,500 viruses
previously unknown to science1, many of them weird and nothing like known
species.
The RNA viruses were identified using metagenomics, in which scientists sample
all the genomes present in the environment without having to culture individual
viruses.
The method shows the potential of AI to explore the ?dark matter? of the RNA
virus universe.
Viruses are ubiquitous microorganisms that infect animals, plants and even
bacteria, yet only a small fraction have been identified and described. There
is ?essentially a bottomless pit? of viruses to discover, says Artem Babaian, a
computational virologist at the University of Toronto in Canada. Some of these
viruses could cause diseases in people, which means that characterizing them
could help to explain mystery illnesses, he says.
Previous studies have used machine learning to find new viruses in sequencing
data.
https://www.nature.com/articles/d41586-018-03358-3
The latest study, published in Cell this week, takes that work a step further
and uses it to look at predicted protein structures1.
The AI model incorporates a protein-prediction tool, called ESMFold, that was
developed by researchers at Meta (formerly Facebook, headquartered in Menlo
Park, California). A similar AI system, AlphaFold, was developed by researchers
at Google DeepMind in London, who won the Nobel Prize in Chemistry this week.
Missed viruses
In 2022, Babaian and his colleagues searched 5.7 million genomic samples
archived in publicly available databases and identified almost 132,000 new RNA
viruses2. Other groups have led similar efforts3.
But RNA viruses evolve quickly, so existing methods for identifying RNA viruses
in genomic sequence data probably miss many. A common method is to look for a
section of the genome that encodes a key protein used in RNA replication,
called RNA-dependent RNA polymerase (RdRp). But if the sequence that encodes
this protein in a virus is vastly different from any known sequence,
researchers won?t recognize it.
Shi Mang, an evolutionary biologist at Sun Yat-sen University in Shenzhen,
China, and a co-author of the Cell study, and his colleagues went looking for
previously unrecognized viruses in publicly available genomic samples.
They developed a model, called LucaProt, using the ?transformer? architecture
that underpins ChatGPT, and fed it sequencing and ESMFold protein-prediction
data.
They then trained their model to recognize viral RdRps and used it to find
sequences that encoded these enzymes ? evidence that those sequences belonged
to a virus ? in the large tranche of genomic data. Using this method, they
identified some 160,000 RNA viruses, including some that were exceptionally
long and found in extreme environments such as hot springs, salt lakes and air.
Just under half of them had not been described before.
They found ?little pockets of RNA virus biodiversity that are really far off in
the boonies of evolutionary space?, says Babaian.
?It?s a really promising approach for expanding the virosphere,? says Jackie
Mahar, an evolutionary virologist at the CSIRO Australian Centre for Disease
Preparedness in Geelong.
Characterizing viruses will help researchers to understand the microbes?
origins and how they evolved in different hosts, she says.
And expanding the pool of known viruses makes it easier to find more viruses
that are similar, says Babaian.
?All of a sudden you can see things that you just weren?t seeing before.?
The team wasn?t able to determine the hosts of the viruses they identified,
which should be investigated further, says Mahar.
Researchers are particularly interested in knowing whether any of the new
viruses infect archaea, an entire branch of the tree of life for which no RNA
viruses have been clearly shown to infect.
Shi is now developing a model to predict the hosts of these newly identified
RNA viruses.
He hopes this will help researchers to understand the roles that viruses have
in their environmental niches.
doi: https://doi.org/10.1038/d41586-024-03320-6
References
Hou, X. et al. Cell https://doi.org/10.1016/j.cell.2024.09.027 (2024).
Article
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Edgar, R. C. et al. Nature 602, 142?147 (2022).
Article
PubMed
Google Scholar
Zayed, A. A. et al. Science 376,156?162 (2022).
Article
PubMed
Google Scholar
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