Regulatory roles of 5′ UTR and ORF-internal RNAs detected by 3′ end mapping

Adams, Philip P.; Baniulyte, Gabriele; Esnault, Caroline; Chegireddy, Kavya; Singh, Navjot; Monge, Molly; Dale, Ryan; Storz, Gisela; Wade, Joseph T.

doi:10.1101/2020.07.18.207399

Cited by 6 publications

(8 citation statements)

References 101 publications

(169 reference statements)

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“…Here, we describe and discuss the set of informative features of sRNAs as well as a predictive algorithm utilizing them, provide a list of potential novel sRNAs and report the experimental verification of novel sRNAs encoded in intergenic regions within operons, in 5 and 3 UTRs and within the coding sequence. Our computational and experimental results support the expanding concept that there is a reservoir of sRNAs encoded within a variety of genomic entities and expressed under various conditions (Adams and Storz, 2020;Adams et al, 2021). The computational framework that we provide for analysis of Hfq RIL-seq data can be used to identify novel sRNAs in RIL-seq data generated for E. coli grown under additional cellular conditions and in RIL-seq data generated for other bacteria manifesting Hfq-mediated sRNA-target interactions.…”

Section: Introductionsupporting

confidence: 67%

“…Seven of the remaining nine putative sRNAs were verified experimentally by northern blotting, where expression was evident in wild type but not in the hfq strain (Figure 5 and Table 2B). While this paper was under revision, the expression of AceK-int was confirmed also in another publication (Adams et al, 2021). The expression of sRNAs encoded at the 3 UTRs of glpX and ykgH could not be verified by the northern blot experiments using two different probes for each of the candidates (Supplementary Table 3).…”

Section: Experimental Verification Of Srna Candidatesmentioning

confidence: 84%

“…enforcing their seemingly misclassification as a sRNAs, although with relatively low sRNA scores (Supplementary Table 1). Interestingly, a recent study identified a premature transcription termination site downstream to the transcription start site of ompF, suggesting that, in addition to being targeted by sRNAs in its 5 UTR, a yet unknown small RNA overlapping ompF 5 UTR might be generated (Adams et al, 2021). In general, sRNAs that function mainly as sponges of other sRNAs are not expected to be predicted by our algorithm as they usually have very few interactions (Supplementary Table 5).…”

Section: Contribution Of Individual Features To the Classificationmentioning

confidence: 93%

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Prediction of Novel Bacterial Small RNAs From RIL-Seq RNA–RNA Interaction Data

et al. 2021

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The genomic revolution and subsequent advances in large-scale genomic and transcriptomic technologies highlighted hidden genomic treasures. Among them stand out non-coding small RNAs (sRNAs), shown to play important roles in post-transcriptional regulation of gene expression in both pro- and eukaryotes. Bacterial sRNA-encoding genes were initially identified in intergenic regions, but recent evidence suggest that they can be encoded within other, well-defined, genomic elements. This notion was strongly supported by data generated by RIL-seq, a RNA-seq-based methodology we recently developed for deciphering chaperon-dependent sRNA-target networks in bacteria. Applying RIL-seq to Hfq-bound RNAs in Escherichia coli, we found that ∼64% of the detected RNA pairs involved known sRNAs, suggesting that yet unknown sRNAs may be included in the ∼36% remaining pairs. To determine the latter, we first tested and refined a set of quantitative features derived from RIL-seq data, which distinguish between Hfq-dependent sRNAs and “other RNAs”. We then incorporated these features in a machine learning-based algorithm that predicts novel sRNAs from RIL-seq data, and identified high-scoring candidates encoded in various genomic regions, mostly intergenic regions and 3′ untranslated regions, but also 5′ untranslated regions and coding sequences. Several candidates were further tested and verified by northern blot analysis as Hfq-dependent sRNAs. Our study reinforces the emerging concept that sRNAs are encoded within various genomic elements, and provides a computational framework for the detection of additional sRNAs in Hfq RIL-seq data of E. coli grown under different conditions and of other bacteria manifesting Hfq-mediated sRNA-target interactions.

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Section: Introductionsupporting

confidence: 67%

Section: Experimental Verification Of Srna Candidatesmentioning

confidence: 84%

Section: Contribution Of Individual Features To the Classificationmentioning

confidence: 93%

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Prediction of Novel Bacterial Small RNAs From RIL-Seq RNA–RNA Interaction Data

et al. 2021

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“…In addition to an expanding context of genomic regulatory RNA sources, there is also emerging evidence for high complexity in bacterial post-transcriptional networks involving not only cross-talk with transcriptional control, but also RNAs that can sequester and modulate RNA-binding proteins (Romeo & Babitzke, 2018;Wassarman, 2018) or even regulate stability or function of other RNAs as so-called competing endogenous RNAs (ceRNAs), RNA decoys/predators, or sponge RNAs (Figueroa-Bossi & Bossi, 2018;Grüll & Massé, 2019;Kavita et al, 2018). Such RNA sponges can be derived from diverse cellular transcripts, including mRNAs (Miyakoshi et al, 2015b;Adams et al, 2021;Figueroa-Bossi et al, 2009) and tRNAs (Lalaouna et al, 2015), or can be stand-alone sRNAs encoded in the core genome or in prophages (Melamed et al, 2020;Tree et al, 2014;Bronesky et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

RNase III-mediated processing of atrans-acting bacterial sRNA and itscis-encoded antagonist

Svensson

Sharma

2021

Preprint

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Small RNAs (sRNAs) are emerging as important and diverse post-transcriptional gene expression regulators in bacterial stress responses and virulence. While originally identified mainly in intergenic regions, genome-wide approaches have revealed sRNAs encoded in diverse contexts, such as processed from parental transcripts by RNase E. Despite its well-known roles in rRNA processing, RNA decay, cleavage of sRNA-mRNA duplexes, the role of RNase III in sRNA biogenesis is less well understood. Here, we show that a pair of cis-encoded sRNAs (CJnc190 and CJnc180) are processed by RNase III in the foodborne pathogen Campylobacter jejuni. While CJnc180 processing requires CJnc190, RNase III cleaves an intramolecular duplex in CJnc190, independent of CJnc180. Moreover, we demonstrate that CJnc190 directly represses translation of the colonization factor PtmG by binding its G-rich ribosome binding site, and show that CJnc180 is a cis-acting antagonist of CJnc190, thereby indirectly affecting ptmG regulation. Our results expand the diversity of known genomic locations of bacterial sRNA sponges and highlight a role for bacterial RNase III that parallels miRNA processing by related eukaryotic Dicer and Drosha.

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“…Some of them are encoded as intergenic regions in polycistronic transcripts, e. g. SroC targeting GcvB sRNA is excised from prematurely terminated gltIJKL mRNA [13], while chbBC depleting ChiX comes from chbB – chbC spacer [14]. On the other hand, ChiZ, which also sequesters ChiX, is derived from 5’-UTR of chiP mRNA [15]. Other sponges are processed from the internal or external transcribed spacers (ITS or ETS, respectively) of tRNA operons.…”

Section: Introductionmentioning

confidence: 99%

Bacterial chaperone protein Hfq facilitates the annealing of sponge RNAs to small regulatory RNAs

Małecka

Sobańska

Olejniczak

2021

Preprint

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Bacterial small RNAs (sRNAs) in association with the chaperone protein Hfq regulate the expression of many target mRNAs. Since sRNAs’ action is crucial to engender a response to changing environmental conditions, their activity needs to be regulated. One such mechanism occurs at posttranscriptional level and involves sponge RNAs (or anti-sRNAs) which sequester sRNAs affecting their regulatory output. Both types of RNAs were identified on Hfq, but it is not known how Hfq interacts with RNA sponges and stimulates their base-pairing with sRNAs. Here, we used biochemical methods to demonstrate that anti-sRNAs resemble sRNAs by their structure and their modes of Hfq binding. Hfq facilitates sponge RNA annealing to sRNA, and each surface of the protein plays a particular role in the process. Moreover, we found that the efficiency of sponge RNA interactions with sRNAs can be improved, therefore, we propose that natural RNA sponges might not sequester sRNAs optimally.

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Regulatory roles of 5′ UTR and ORF-internal RNAs detected by 3′ end mapping

Cited by 6 publications

References 101 publications

Prediction of Novel Bacterial Small RNAs From RIL-Seq RNA–RNA Interaction Data

Prediction of Novel Bacterial Small RNAs From RIL-Seq RNA–RNA Interaction Data

RNase III-mediated processing of atrans-acting bacterial sRNA and itscis-encoded antagonist

Bacterial chaperone protein Hfq facilitates the annealing of sponge RNAs to small regulatory RNAs

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