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

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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

1. Sander Granneman
(2020) Hfq CLASH uncovers sRNA-target interaction networks involved in adaptation to nutrient availability
NCBI Gene Expression Omnibus, GSE123050.

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE123050
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(2019) Hfq CLASH and TEX processed data
https://doi.org/10.7488/ds/2537.

https://datashare.is.ed.ac.uk/handle/10283/3313

The following previously published data sets were used

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(2020) Transcriptome wide mapping of Hfq mediated RNA-RNA interactions in E. coli (RIL-seq)
ArrayExpress, E-MTAB-3910.

https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3910/
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NCBI Gene Expression Omnibus, GSE80019.

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80019
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(2011) The base pairing RNA Spot 42 participates in a multi-output feedforward loop to help enact catabolite repression in Escherichia coli
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Article and author information

Author details

Ira Alexandra Iosub

SynthSys, University of Edinburgh, Edinburgh, United Kingdom

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-2924-2471
Rob Willem van Nues

ICB, University of Edinburgh, Edinburgh, United Kingdom

Competing interests
The authors declare that no competing interests exist.
Stuart William McKellar

IQB3, University of Edinburgh, Edinburgh, United Kingdom

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-0792-9878
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.
Marta Marchioretto

Institute of Biophysics, CNR, Trento, Italy

Competing interests
The authors declare that no competing interests exist.
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.
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.
Gabriella Viero

Institute of Biophysics, CNR Unit, Trento, Italy

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-6755-285X
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.

"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

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.