Long-reads and powerful algorithms identify “invisible” microbes

Jan. 18, 2022

Researchers at the University of California San Diego Department of Computer Science and Engineering, the U.S. Department of Agriculture, the biotechnology company Pacific Biosciences and labs in Russia, Israel, and the Netherlands have shown that HiFi, combined with advanced algorithms, can differentiate between nearly identical organisms, allowing researchers to catalogue microbial communities more completely, according to a news release from UCSD.

The study was published in Nature Biotechnology.

HiFi is a so-called ‘long-reads’ technology developed by Pacific Bioscience. Explains Pavel Pevzner, Professor of Computer Science at UC San Diego and co-senior author on the paper. “Here, we provide complete or nearly complete bacterial genomes, distinguishing very similar bacterial strains from a single sample. This is no small thing: Some E. coli strains are harmless, others are deadly.”

The paper builds on findings that show long-reads can shine a light on previously invisible organisms. Short-reads, the most common genomic sequencing technique, analyze brief DNA fragments (100 to 300 base pairs) and have trouble assembling complete genomes and differentiating between genomically similar microbes.

HiFi recently helped sequence a complete human genome, a feat that had evaded scientists since the Human Genome Project produced an incomplete version 20 years ago, the university contends.

Long-read technologies, such as HiFi, generate much larger DNA fragments (greater than 15,000 base pairs) and have emerged as a potential solution. As long-read accuracy has increased, the technology has revealed hidden genomic features in amazing detail. In this case, HiFi easily differentiated microbes with only minor genomic variations.

“Rather than combining similar organisms into one bucket, we can now differentiate them and get a true metagenomic picture of complex bacterial communities,” said Pevzner. “Like complete genomics, which is already being applied to rare disease diagnostics, complete metagenomics may soon make its way into medicine and many other disciplines.”

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