Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes.

Journal: Nucleic acids research
Published Date: Feb 22, 2022

Abstract

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC-ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.

Authors

  • William B Andreopoulos
    Joint Genome Institute, US Department of Energy, LBNL Berkeley, CA, USA.
  • Alexander M Geller
    Department of Plant Pathology and Microbiology, The Institute of Environmental Science, The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot, Israel.
  • Miriam Lucke
    Department of Plant Pathology and Microbiology, The Institute of Environmental Science, The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot, Israel.
  • Jan Balewski
    National Energy Research Scientific Computing Center (NERSC), Berkeley, CA, USA.
  • Alicia Clum
    Joint Genome Institute, US Department of Energy, LBNL Berkeley, CA, USA.
  • Natalia N Ivanova
    Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, California, USA.
  • Asaf Levy
    Department of Plant Pathology and Microbiology, The Institute of Environmental Science, The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot, Israel.

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