RNA Modifications in Pathogenic Bacteria: Impact on Host Adaptation and Virulence
Abstract
:1. Introduction
2. Technological Advances: Detecting RNA Modifications
3. Impact of RNA Modifications on Pathogenic Bacterial Stress Responses and Host Adaptation
3.1. rRNA Modifications
3.2. tRNA Modifications
3.3. sRNA Modifications
3.4. mRNA Modifications
4. Conclusions and Perspectives
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Methods | Modifications Detected | Quantification | Genome Wide | Positional Information | Remarks (Pros/Cons) | ||
---|---|---|---|---|---|---|---|
Structure Determination | X-ray Cristallography | All modifications | ✕/✓ | ✕ | ✓ | Difficult to obtain crystals | |
Cryo Electron Microscopy | Heterogeneous resolution | ||||||
Nuclear Magnetic Resonance | Size limit | ||||||
LC/MSMS | Nucleoside analysis | DMRM [34] | Known modifications | ✓ | ✓ | ✕ | Fragmentation pattern and retention time of modifications must be known |
NLS [34] | Various modifications | ✓ | ✓ | ✕ | NLS is less suitable for quantification than DMRM | ||
Fragment analysis | With a reference (SILNAS/CARD/ SILCARD) [52,53] | Known modifications | ✓ | ✕ | ✓ | Relative quantification can be assessed with reference in vitro RNA | |
Without reference (RNase digests) [39] | Known modifications | ✕ | ✕ | ✓ | Determination of base composition and localization by comparing mass-spectrometry results with expected RNase fragments | ||
NGS-based methods | RNA deep-sequencing direct method | A-to-I [54] | ✓ | ✓ | ✓ | To be accompanied by DNA sequencing to distinguish editing events from SNPs | |
Methylations [55] | ✕ | ✕ | Based on RT stops or misincorporations | ||||
Nanopore RNA sequencing [56,57] | m6A, m5C, A-to-I, Ψ and others | ✓ | ✓ | Based on the use of systematic base-calling ‘errors’ caused by the presence of RNA modifications. Software is still in development | |||
Indirect methods: chemical treatments | ICE-Seq [58,59] | A-to-I | ✓ | ✓ | No need of DNA seq | ||
Bisulfite-Seq [60] | m5C | ||||||
Riboxi-Seq [61] | Nm | ||||||
RiboMethSeq [62,63] | |||||||
Pseudo-Seq [64] | Ψ | ||||||
Ψ-Seq | |||||||
PSI-Seq [65] | |||||||
HydraPsi-Seq [66] | |||||||
SLAM-Seq [67] | s4U | ||||||
ARM-Seq [68] | m1A, m3C, m1G | ||||||
TRAC-Seq [69] | m7G | ||||||
AlkAniline-Seq [70] | m7G, m3C, D | ||||||
Indirect methods: IP | miCLIP [71] | Methylation | ✓ | ✓ | |||
m6A-Seq [72] | m6A | ||||||
meRIP-Seq [73] | |||||||
m6A-LAIC-Seq [74] | |||||||
Nm-Seq / 2OMe-Seq [75] | Nm | ||||||
acRIP-Seq [76] | ac4C | ||||||
NAD capture-Seq [77] | 5’-NAD cap | ||||||
Affinity gel electrophoresis | Mercury-sulfur affinity [78] | s2U, s4U | ✕ | ✕ | ✕ | APM treatment (Acrylo-aminophenylmercuric chloride) | |
Boronate affinity [79] | NAD- or FAD-modified RNAs | ✓ | ✓ | ✕ | APB treatment (Acryloylaminophenyl boronic acid); fast screening (easy and quick); quantification possible as per intensity of bands |
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Antoine, L.; Bahena-Ceron, R.; Devi Bunwaree, H.; Gobry, M.; Loegler, V.; Romby, P.; Marzi, S. RNA Modifications in Pathogenic Bacteria: Impact on Host Adaptation and Virulence. Genes 2021, 12, 1125. https://doi.org/10.3390/genes12081125
Antoine L, Bahena-Ceron R, Devi Bunwaree H, Gobry M, Loegler V, Romby P, Marzi S. RNA Modifications in Pathogenic Bacteria: Impact on Host Adaptation and Virulence. Genes. 2021; 12(8):1125. https://doi.org/10.3390/genes12081125
Chicago/Turabian StyleAntoine, Laura, Roberto Bahena-Ceron, Heemee Devi Bunwaree, Martin Gobry, Victor Loegler, Pascale Romby, and Stefano Marzi. 2021. "RNA Modifications in Pathogenic Bacteria: Impact on Host Adaptation and Virulence" Genes 12, no. 8: 1125. https://doi.org/10.3390/genes12081125
APA StyleAntoine, L., Bahena-Ceron, R., Devi Bunwaree, H., Gobry, M., Loegler, V., Romby, P., & Marzi, S. (2021). RNA Modifications in Pathogenic Bacteria: Impact on Host Adaptation and Virulence. Genes, 12(8), 1125. https://doi.org/10.3390/genes12081125