July 19, 2018
Research Highlight

Assessing Metabolic Pathways in Metagenome-Assembled Genomes

Metagenomics, the study of genetic material from environmental samples, has become a powerful tool in the biological sciences. It involves collecting genetic sequences from environmental samples and using them to reconstruct the genomes of organisms. This is particularly useful because DNA can be preserved for thousands of years under the right conditions, such as very cold and/or dry environments, and can thereby provide insight into Earth’s ancient biosphere.

Artist impression of a strand of DNA.
Artist impression of a strand of DNA.Image credit: GA Tech/CCE.

Over the years, metagenomics techniques have been adapted for use with a variety of sample types. To study life in Earth’s ancient past, some scientists have turned to genome-resolved metagenomics. This allows scientists to construct microbial genomes using short-read shotgun metagenomics. However, these short fragments of DNA, which are often degraded, are incomplete and can contain contaminant sequence. This affects the accuracy of the data acquired from samples, including insights in tot he metabolic pathways identified in metagenome-assembled genomes (MAGs).

Researchers at CalTech recently developed an algorithm, dubbed MetaPOAP, that could help assess samples for the presence or absence of metabolic pathways in MAGs. The algorithm has been made available as a Python script on GitHub, and is also directly available through the research group at CalTech.

The study, “MetaPOAP: Presence or Absence of Metabolic Pathways in Metagenome-Assembled Genomes,” was published in the journal Bioinformatics . The work was supported by NASA Astrobiology through the Exobiology Program.