This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: A handful of soil holds a crowded world of bacteria, fungi and other organisms. Scientists can collect their DNA, but much of it remains difficult to identify.
Now, researchers at the Hebrew University of Jerusalem and partner institutions have developed an artificial intelligence tool that helps make sense of this genetic puzzle. Called BBERT, the tool learns patterns in bacterial DNA, allowing it to recognize bacterial fragments just 100 DNA "letters" long. In tests, it helped researchers distinguish bacterial DNA from other genetic material and piece bacterial genomes together faster and with fewer errors.
The study, published in Nucleic Acids Research, was led by Dr. Amir Erez of the Hebrew University's Racah Institute of Physics and Dr. Finkel of its Department of Plant and Environmental Sciences.
Tomer Sidi contributed equally to the work, alongside colleagues from the University of Haifa and the Agricultural Research Organization's Volcani Institute. To study life in soil, scientists can extract and sequence DNA from an entire sample at once. This produces millions of short genetic fragments from many different organisms.
The challenge is figuring out which fragments belong to bacteria and what information they contain. It is like sorting a huge pile of puzzle pieces from many different puzzles, often without knowing what the finished pictures should look like. Existing tools commonly identify fragments by comparing them with DNA sequences stored in reference databases.
But many soil organisms are missing from those databases. Without a suitable match, their DNA can remain unidentified or be labeled incorrectly. Researchers often call this unexplained genetic material microbial "dark matter." BBERT approaches the problem differently.
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