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The biological relevance and dynamics of mRNA modifications have been extensively studied; however, whether rRNA modifications are dynamically regulated, and under which conditions, remains unclear. Here, we systematically characterize bacterial rRNA modifications upon exposure to diverse antibiotics using native RNA nanopore sequencing. To identify significant rRNA modification changes, we develop NanoConsensus, a novel pipeline that is robust across RNA modification types, stoichiometries and coverage, with very low false positive rates, outperforming all individual algorithms tested. We then apply NanoConsensus to characterize the rRNA modification landscape upon antibiotic exposure, finding that rRNA modification profiles are altered in the vicinity of A and P-sites of the ribosome, in an antibiotic-specific manner, possibly contributing to antibiotic resistance. Our work demonstrates that rRNA modification profiles can be rapidly altered in response to environmental exposures, and provides a robust workflow to study rRNA modification dynamics in any species, in a scalable and reproducible manner.
Sequence Analysis, RNA, Science, Q, Microbiology, Article, Computational biology and bioinformatics, Anti-Bacterial Agents, Nanopore Sequencing, RNA, Bacterial, Antibiotics, RNA, Ribosomal, Escherichia coli, RNA Processing, Post-Transcriptional, Ribosomes, Algorithms
Sequence Analysis, RNA, Science, Q, Microbiology, Article, Computational biology and bioinformatics, Anti-Bacterial Agents, Nanopore Sequencing, RNA, Bacterial, Antibiotics, RNA, Ribosomal, Escherichia coli, RNA Processing, Post-Transcriptional, Ribosomes, Algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 21 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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