TaxiBGC: a Taxonomy-Guided Approach for Profiling Experimentally Characterized Microbial Biosynthetic Gene Clusters and Secondary Metabolite Production Potential in Metagenomes

Author:

Gupta Vinod K.12,Bakshi Utpal3,Chang Daniel4,Lee Aileen R.56,Davis John M.7,Chandrasekaran Sriram8910,Jin Yong-Su1112,Freeman Michael F.56,Sung Jaeyun127

Affiliation:

1. Microbiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA

2. Division of Surgery Research, Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA

3. Institute of Health Sciences, Presidency University, Kolkata, West Bengal, India

4. Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA

5. Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota—Twin Cities, St. Paul, Minnesota, USA

6. BioTechnology Institute, University of Minnesota—Twin Cities, St. Paul, Minnesota, USA

7. Division of Rheumatology, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA

8. Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA

9. Program in Chemical Biology, University of Michigan, Ann Arbor, Michigan, USA

10. Center for Bioinformatics and Computational Medicine, University of Michigan, Ann Arbor, Michigan, USA

11. Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

12. Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

Abstract

Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source.

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

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