Deep learning revealed the distribution and evolution patterns for invertible promoters across bacterial lineages.

Journal: Nucleic acids research
PMID: 39460615

Abstract

Invertible promoters (invertons) are crucial regulatory elements in bacteria, facilitating gene expression changes under stress. Despite their importance, their prevalence and the range of regulated gene functions are largely unknown. We introduced DeepInverton, a deep learning model that identifies invertons across a broad phylogenetic spectrum without using sequencing reads. By analyzing 68 733 bacterial genomes and 9382 metagenomes, we have uncovered over 200 000 nonredundant invertons and have also highlighted their abundance in pathogens. Additionally, we identified a post-Cambrian Explosion increase of invertons, paralleling species diversification. Furthermore, we revealed that invertons regulate diverse functions, including antimicrobial resistance and biofilm formation, underscoring their role in environmental adaptation. Notably, the majority of inverton identifications by DeepInverton have been confirmed by the in vitro experiments. The comprehensive inverton profiles have deepened our understanding of invertons at pan-genome and pan-metagenome scales, enabling a broad spectrum of applications in microbial ecology and synthetic biology.

Authors

  • Jiejie Wen
    Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
  • Haobo Zhang
    Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
  • Dongliang Chu
    Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
  • Xiaoke Chen
    Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
  • Jingru Feng
    Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
  • Yucen Wang
    Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
  • Guanxi Liu
    Key Laboratory for Precision and Non-Traditional Machining Technology, Ministry of Education, Dalian University of Technology, Dalian, China.
  • Yuhao Zhang
    Biomedical Informatics Training Program, Stanford University, Stanford, CA, USA.
  • Yuxue Li
    Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
  • Kang Ning
    MOE Key Laboratory of Molecular Biophysics, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: ningkang@hust.edu.cn.

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