1. Biochemistry and Chemical Biology
  2. Chromosomes and Gene Expression

Hfq CLASH uncovers sRNA-target interaction networks linked to nutrient availability adaptation

  1. Ira Alexandra Iosub
  2. Rob Willem van Nues
  3. Stuart William McKellar
  4. Karen Jule Nieken
  5. Marta Marchioretto
  6. Brandon Sy
  7. Jai J Tree
  8. Gabriella Viero
  9. Sander Granneman  Is a corresponding author
  1. University of Edinburgh, United Kingdom
  2. CNR, Italy
  3. University of New South Wales, Australia
  4. CNR Unit, Italy
https://doi.org/10.7554/eLife.54655
Share this article
Cite this article
  1. Ira Alexandra Iosub
  2. Rob Willem van Nues
  3. Stuart William McKellar
  4. Karen Jule Nieken
  5. Marta Marchioretto
  6. Brandon Sy
  7. Jai J Tree
  8. Gabriella Viero
  9. Sander Granneman
(2020)
Hfq CLASH uncovers sRNA-target interaction networks linked to nutrient availability adaptation
eLife 9:e54655.
https://doi.org/10.7554/eLife.54655
  2. Download BibTeX
  3. Download .RIS

Abstract

By shaping gene expression profiles, small RNAs (sRNAs) enable bacteria to efficiently adapt to changes in their environment. To better understand how Escherichia coli acclimatizes to nutrient availability, we performed UV cross-linking, ligation and sequencing of hybrids (CLASH) to uncover Hfq-associated RNA-RNA interactions at specific growth stages. We demonstrate that Hfq CLASH robustly captures bona fide RNA-RNA interactions identified hundreds of novel sRNA base-pairing interactions, including many sRNA-sRNA interactions and involving 3'UTR-derived sRNAs. We rediscovered known and identified novel sRNA seed sequences. The sRNA-mRNA interactions identified by CLASH have strong base-pairing potential and are highly enriched for complementary sequence motifs, even those supported by only a few reads. Yet, steady state levels of most mRNA targets were not significantly affected upon over-expression of the sRNA regulator. Our results reinforce the idea that the reproducibility of the interaction, not base-pairing potential, is a stronger predictor for a regulatory outcome.

Data availability

The next generation sequencing data have been deposited on the NCBI Gene Expression Omnibus (GEO) with accession number GSE123050. The python pyCRAC (Webb et al., 2014), kinetic-CRAC and GenomeBrowser software packages used for analysing the data are available from https://bitbucket.org/sgrann (pyCRAC up to version 1.4.3), https://git.ecdf.ed.ac.uk/sgrannem/ and pypi (https://pypi.org/user/g_ronimo/). The hyb pipeline for identifying chimeric reads is available from https://github.com/gkudla/hyb. The scripts for statistical analysis of hyb data is available from https://bitbucket.org/jaitree/hyb_stats/. The FLASH algorithm for merging paired reads is available from https://github.com/dstreett/FLASH2. Bedgraph and Gene Transfer Format (GTF) generated from the analysis of the Hfq CLASH, RNA-seq and TEX RNA-seq data (Thomason et al., 2015) are available from the Granneman lab DataShare repository (https://datashare.is.ed.ac.uk/handle/10283/2915).

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Ira Alexandra Iosub

    SynthSys, University of Edinburgh, Edinburgh, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2924-2471

  2. Rob Willem van Nues

    ICB, University of Edinburgh, Edinburgh, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  3. Stuart William McKellar

    IQB3, University of Edinburgh, Edinburgh, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0792-9878

  4. Karen Jule Nieken

    Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  5. Marta Marchioretto

    Institute of Biophysics, CNR, Trento, Italy
    Competing interests
    The authors declare that no competing interests exist.

  6. Brandon Sy

    School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.

  7. Jai J Tree

    School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.

  8. Gabriella Viero

    Institute of Biophysics, CNR Unit, Trento, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6755-285X

  9. Sander Granneman

    SynthSys, University of Edinburgh, Edinburgh, United Kingdom
    For correspondence
    sgrannem@ed.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4387-1271

Funding

Wellcome (102334)

  • Ira Alexandra Iosub

Wellcome (091549)

  • Sander Granneman

Medical Research Council (MR/R008205/1)

  • Sander Granneman

Australian National Health (GNT1067241)

  • Jai J Tree

Australian Medical Research Council (GNT1139313)

  • Jai J Tree

Axonomix (N/A)

  • Gabriella Viero

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Iosub et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,438
    views
  • 426
    downloads
  • 79
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Ira Alexandra Iosub
  2. Rob Willem van Nues
  3. Stuart William McKellar
  4. Karen Jule Nieken
  5. Marta Marchioretto
  6. Brandon Sy
  7. Jai J Tree
  8. Gabriella Viero
  9. Sander Granneman
(2020)
Hfq CLASH uncovers sRNA-target interaction networks linked to nutrient availability adaptation
eLife 9:e54655.
https://doi.org/10.7554/eLife.54655

Share this article

https://doi.org/10.7554/eLife.54655

Categories and tags

Research organism

Further reading

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics

    Genetic code expansion, click chemistry, and light-activated PI3K reveal details of membrane protein trafficking downstream of receptor tyrosine kinases

    Duk-Su Koh, Anastasiia Stratiievska ... Sharona E Gordon
    Tools and Resources

    Ligands such as insulin, epidermal growth factor, platelet-derived growth factor, and nerve growth factor (NGF) initiate signals at the cell membrane by binding to receptor tyrosine kinases (RTKs). Along with G-protein-coupled receptors, RTKs are the main platforms for transducing extracellular signals into intracellular signals. Studying RTK signaling has been a challenge, however, due to the multiple signaling pathways to which RTKs typically are coupled, including MAP/ERK, PLCγ, and Class 1A phosphoinositide 3-kinases (PI3K). The multi-pronged RTK signaling has been a barrier to isolating the effects of any one downstream pathway. Here, we used optogenetic activation of PI3K to decouple its activation from other RTK signaling pathways. In this context, we used genetic code expansion to introduce a click chemistry noncanonical amino acid into the extracellular side of membrane proteins. Applying a cell-impermeant click chemistry fluorophore allowed us to visualize delivery of membrane proteins to the plasma membrane in real time. Using these approaches, we demonstrate that activation of PI3K, without activating other pathways downstream of RTK signaling, is sufficient to traffic the TRPV1 ion channels and insulin receptors to the plasma membrane.

    1. Biochemistry and Chemical Biology

    Discovery of the 1-naphthylamine biodegradation pathway reveals a broad-substrate-spectrum enzyme catalyzing 1-naphthylamine glutamylation

    Shu-Ting Zhang, Shi-Kai Deng ... Ning-Yi Zhou
    Research Article

    1-Naphthylamine (1NA), which is harmful to human and aquatic animals, has been used widely in the manufacturing of dyes, pesticides, and rubber antioxidants. Nevertheless, little is known about its environmental behavior and no bacteria have been reported to use it as the growth substrate. Herein, we describe a pathway for 1NA degradation in the isolate Pseudomonas sp. strain JS3066, determine the structure and mechanism of the enzyme NpaA1 that catalyzes the initial reaction, and reveal how the pathway evolved. From genetic and enzymatic analysis, a five gene-cluster encoding a dioxygenase system was determined to be responsible for the initial steps in 1NA degradation through glutamylation of 1NA. The γ-glutamylated 1NA was subsequently oxidized to 1,2-dihydroxynaphthalene which was further degraded by the well-established pathway of naphthalene degradation via catechol. A glutamine synthetase-like (GS-like) enzyme (NpaA1) initiates 1NA glutamylation, and this enzyme exhibits a broad substrate selectivity toward a variety of anilines and naphthylamine derivatives. Structural analysis revealed that the aromatic residues in the 1NA entry tunnel and the V201 site in the large substrate-binding pocket significantly influence NpaA1’s substrate preferences. The findings enhance understanding of degrading polycyclic aromatic amines, and will also enable the application of bioremediation at naphthylamine contaminated sites.

    1. Biochemistry and Chemical Biology
    2. Microbiology and Infectious Disease

    Hyperglycemia induced cathepsin L maturation linked to diabetic comorbidities and COVID-19 mortality

    Qiong He, Miao-Miao Zhao ... Jin-Kui Yang
    Research Article

    Diabetes, a prevalent chronic condition, significantly increases the risk of mortality from COVID-19, yet the underlying mechanisms remain elusive. Emerging evidence implicates Cathepsin L (CTSL) in diabetic complications, including nephropathy and retinopathy. Our previous research identified CTSL as a pivotal protease promoting SARS-CoV-2 infection. Here, we demonstrate elevated blood CTSL levels in individuals with diabetes, facilitating SARS-CoV-2 infection. Chronic hyperglycemia correlates positively with CTSL concentration and activity in diabetic patients, while acute hyperglycemia augments CTSL activity in healthy individuals. In vitro studies reveal high glucose, but not insulin, promotes SARS-CoV-2 infection in wild-type cells, with CTSL knockout cells displaying reduced susceptibility. Utilizing lung tissue samples from diabetic and non-diabetic patients, alongside Leprdb/dbmice and Leprdb/+mice, we illustrate increased CTSL activity in both humans and mice under diabetic conditions. Mechanistically, high glucose levels promote CTSL maturation and translocation from the endoplasmic reticulum (ER) to the lysosome via the ER-Golgi-lysosome axis. Our findings underscore the pivotal role of hyperglycemia-induced CTSL maturation in diabetic comorbidities and complications.