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A reporter system coupled with high-throughput sequencing unveils key bacterial transcription and translation determinants

Author

Listed:
  • Eva Yus

    (The Barcelona Institute for Science and Technology
    Universitat Pompeu Fabra (UPF))

  • Jae-Seong Yang

    (The Barcelona Institute for Science and Technology
    Universitat Pompeu Fabra (UPF))

  • Adrià Sogues

    (The Barcelona Institute for Science and Technology
    Universitat Pompeu Fabra (UPF)
    Unité de Microbiologie Structurale (CNRS) UMR 3528, Université Paris Diderot)

  • Luis Serrano

    (The Barcelona Institute for Science and Technology
    Universitat Pompeu Fabra (UPF)
    Institució Catalana de Recerca i Estudis Avançats (ICREA))

Abstract

Quantitative analysis of the sequence determinants of transcription and translation regulation is relevant for systems and synthetic biology. To identify these determinants, researchers have developed different methods of screening random libraries using fluorescent reporters or antibiotic resistance genes. Here, we have implemented a generic approach called ELM-seq (expression level monitoring by DNA methylation) that overcomes the technical limitations of such classic reporters. ELM-seq uses DamID (Escherichia coli DNA adenine methylase as a reporter coupled with methylation-sensitive restriction enzyme digestion and high-throughput sequencing) to enable in vivo quantitative analyses of upstream regulatory sequences. Using the genome-reduced bacterium Mycoplasma pneumoniae, we show that ELM-seq has a large dynamic range and causes minimal toxicity. We use ELM-seq to determine key sequences (known and putatively novel) of promoter and untranslated regions that influence transcription and translation efficiency. Applying ELM-seq to other organisms will help us to further understand gene expression and guide synthetic biology.

Suggested Citation

  • Eva Yus & Jae-Seong Yang & Adrià Sogues & Luis Serrano, 2017. "A reporter system coupled with high-throughput sequencing unveils key bacterial transcription and translation determinants," Nature Communications, Nature, vol. 8(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-00239-7
    DOI: 10.1038/s41467-017-00239-7
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    Cited by:

    1. Alicia Broto & Erika Gaspari & Samuel Miravet-Verde & Vitor A. P. Martins Santos & Mark Isalan, 2022. "A genetic toolkit and gene switches to limit Mycoplasma growth for biosafety applications," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Samuel Miravet-Verde & Rocco Mazzolini & Carolina Segura-Morales & Alicia Broto & Maria Lluch-Senar & Luis Serrano, 2024. "ProTInSeq: transposon insertion tracking by ultra-deep DNA sequencing to identify translated large and small ORFs," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    3. Simon Höllerer & Laetitia Papaxanthos & Anja Cathrin Gumpinger & Katrin Fischer & Christian Beisel & Karsten Borgwardt & Yaakov Benenson & Markus Jeschek, 2020. "Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
    4. Evangelos-Marios Nikolados & Arin Wongprommoon & Oisin Mac Aodha & Guillaume Cambray & Diego A. Oyarzún, 2022. "Accuracy and data efficiency in deep learning models of protein expression," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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