The important conformational plasticity of DsrA sRNA for adapting multiple target regulation

Wu, Pengzhi; Liu, Xiaodan; Yang, Lingna; Sun, Yitong; Gong, Qingguo; Wu, Jihui; Shi, Yunyu

doi:10.1093/nar/gkx570

Cited by 14 publications

(23 citation statements)

References 46 publications

(75 reference statements)

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“…SL3 is a Rho-independent transcription terminator, which consists of many G-C base-pairs followed by multiple uridine nucleotides. SL2 contains a dynamic conformational equilibrium, so it can participate in base-pairing with hns , mreB , or rbsD mRNAs with different conformational states [ 59 ]. The SL1 and Linker 1 promote efficient translation of rpoS mRNA, which encodes for the stress sigma factor σ S , by acting as an anti-antisense RNA [ 54 , 60 ].…”

Section: Introductionmentioning

confidence: 99%

“…The preferential Hfq-binding site of DsrA is Linker 1, while SL1 is partially destabilized by Hfq [ 62 ]. Meanwhile, recent NMR studies showed that SL1 has a very stable stem-loop structure, and cannot be significantly unfolded to base pair with the rpoS mRNA without Hfq at room temperature [ 59 ]. These results indicate that Hfq may play an important role in the unfolding of DsrA SL1.…”

Section: Introductionmentioning

confidence: 99%

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The Amyloid Region of Hfq Riboregulator Promotes DsrA:rpoS RNAs Annealing

Turbant

Wien

et al. 2021

Biology

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Hfq is a bacterial RNA chaperone which promotes the pairing of small noncoding RNAs to target mRNAs, allowing post-transcriptional regulation. This RNA annealing activity has been attributed for years to the N-terminal region of the protein that forms a toroidal structure with a typical Sm-fold. Nevertheless, many Hfqs, including that of Escherichia coli, have a C-terminal region with unclear functions. Here we use a biophysical approach, Synchrotron Radiation Circular Dichroism (SRCD), to probe the interaction of the E. coli Hfq C-terminal amyloid region with RNA and its effect on RNA annealing. This C-terminal region of Hfq, which has been described to be dispensable for sRNA:mRNA annealing, has an unexpected and significant effect on this activity. The functional consequences of this novel property of the amyloid region of Hfq in relation to physiological stress are discussed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Amyloid Region of Hfq Riboregulator Promotes DsrA:rpoS RNAs Annealing

Turbant

Wien

et al. 2021

Biology

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“…Using this automated procedure we have successfully built 50 different small-RNA structures and analyzed some of their basic properties calculated from their dynamics data. Comparison of our server derived model of DsrA and the NMR structure of the SL1 of the DsrA (pdb code: 5WQ1)46 shows high similarities (RMSD: 2.75Å) between the structures, indicating reliability of our 3D model (FigureS7in Supplementary Information File). However, the NMR structure covers only a short fraction of the DsrA sequence.PresRAT enables a user to search for probable target mRNAs of sRNA sequences from a given bacterial chromosome and further concentrate on identification of the probable sRNA-mRNA binding regions.…”

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confidence: 79%

“…As per the latest RCSB protein databank 45 statistics, there are 1528 experimentally solved 3D structures of RNA representing only ~0.01% of the whole deposited structures. So far there is only one experimentally solved 3D structures available for sRNA 46 (N-terminal SL1 part of DsrA from E.coli) other than few sRNA conjugated with chaperone proteins [47][48][49][50][51] . PresRAT uses RNA2D3D 42 program to generate an initial RNA model followed by extensive refinement of the structure using GROMACS v4.6.3 molecular dynamics simulation package 52 .…”

Section: Introductionmentioning

confidence: 99%

PresRAT: a server for identification of bacterial small-RNA sequences and their targets with probable binding region

2020

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Bacterial small-RNA (sRNA) sequences are functional RNAs, which play an important role in regulating the expression of a diverse class of genes. It is thus critical to identify such sRNA sequences and their probable mRNA targets. Here, we discuss new procedures to identify and characterize sRNA and their targets via the introduction of an integrated online platform named PresRAT (Prediction of sRNA and their Targets). PresRAT uses the primary and secondary structural attributes of sRNA sequences to predict sRNA from a given sequence or bacterial genome. PresRAT also finds probable target mRNAs of sRNA sequences from a given bacterial chromosome and further concentrates on identification of the probable sRNA-mRNA binding regions.Using PresRAT we have identified a total of 60,518 potential sRNA sequences from 54 bacterial genomes and 2447 potential targets from 13 bacterial genomes. We have also implemented a protocol to build and refine 3D models of sRNA and sRNA-mRNA duplex regions and generated 3D models of 50 known sRNAs and 81 sRNA-mRNA duplexes using this platform. Along with the server part, PresRAT also contains a database section, which enlists the predicted sRNA sequences, sRNA targets and their corresponding 3D models with structural dynamics information..

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“…Previous studies on sRNAs that recognize multiple targets have shown that interactions occur in different regions of the sRNA and that structural flexibility of the sRNA is required for interactions with different targets [ 38 , 39 ]. To analyze multiple interactions, we built density maps of the interactions.…”

Section: Discussionmentioning

confidence: 99%

Codon usage and modular interactions between messenger RNA coding regions and small RNAs in Escherichia coli

2018

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BackgroundSmall RNAs (sRNAs) are key regulators of gene expression in bacteria. In addition to modulating translation initiation, sRNAs can interact with mRNA coding regions to regulate mRNA stability and translation efficiency, enhancing or impeding progression of the ribosome along the mRNA. Since most amino acids are decoded by more than one codon (synonymous) we asked as to whether there is a codon bias in the interaction of sRNAs with coding regions of mRNAs. Therefore, we explored whether there are differences in codon usage or tRNA availability according to whether an mRNA is regulated by sRNAs or not. We also explored these parameters in the coding interaction regions in mRNAs. We focused our analysis on sRNAs that regulate multiple mRNAs.ResultsWe found differences in codon adaptation index and tRNA adaptation index between sRNA-regulated and non-sRNA-regulated mRNAs. Interestingly, the sRNA-mRNA interacting regions tended to be enriched in unpreferred codons decoded by scarce tRNAs. We also found that sRNAs with multiple targets often contained modular segments capable of recognizing conserved motifs among these mRNAs.ConclusionsOur results show that sRNAs in E. coli tend to recognize mRNA coding regions in which the ribosome is predicted to advance at low speeds. Identified motifs in interacting regions are conserved among mRNAs that are recognized by the same sRNA.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5038-6) contains supplementary material, which is available to authorized users.

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The important conformational plasticity of DsrA sRNA for adapting multiple target regulation

Cited by 14 publications

References 46 publications

The Amyloid Region of Hfq Riboregulator Promotes DsrA:rpoS RNAs Annealing

The Amyloid Region of Hfq Riboregulator Promotes DsrA:rpoS RNAs Annealing

PresRAT: a server for identification of bacterial small-RNA sequences and their targets with probable binding region

Codon usage and modular interactions between messenger RNA coding regions and small RNAs in Escherichia coli

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