PlasmidHunter: accurate and fast prediction of plasmid sequences using gene content profile and machine learning

Author:

Tian Renmao1ORCID,Zhou Jizhong23,Imanian Behzad14ORCID

Affiliation:

1. Institute for Food Safety and Health, Illinois Institute of Technology , 6502 S Archer Rd, Bedford Park, IL 60501, United States

2. Institute for Environmental Genomics , Department of Microbiology and Plant Biology, , 101 David L Boren Blvd, Norman, OK 73019, United States

3. University of Oklahoma , Department of Microbiology and Plant Biology, , 101 David L Boren Blvd, Norman, OK 73019, United States

4. Food Science and Nutrition Department, Illinois Institute of Technology , 10 West 35th Street, Chicago, IL 60616, United States

Abstract

Abstract Plasmids are extrachromosomal DNA found in microorganisms. They often carry beneficial genes that help bacteria adapt to harsh conditions. Plasmids are also important tools in genetic engineering, gene therapy, and drug production. However, it can be difficult to identify plasmid sequences from chromosomal sequences in genomic and metagenomic data. Here, we have developed a new tool called PlasmidHunter, which uses machine learning to predict plasmid sequences based on gene content profile. PlasmidHunter can achieve high accuracies (up to 97.6%) and high speeds in benchmark tests including both simulated contigs and real metagenomic plasmidome data, outperforming other existing tools.

Funder

Food and Drug Administration

U.S. Department of Health and Human Services

Publisher

Oxford University Press (OUP)

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