ArticleG3 (Bethesda, Md.)2023
Growth condition-dependent differences in methylation imply transiently differentiated DNA methylation states in Escherichia coli.
Article in G3 (Bethesda, Md.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Growth Phase-Related DNA Methylation and Localized DNA Fragment Density Variation inEpigenomes · 2026Article
- Long-read methylome analysis of Oleidesulfovibrio alaskensis G20 biofilm under copper stress.Scientific reports · 2025Article
- Understanding prokaryotic adaptation through advanced DNA methylation detection techniques.The ISME journal · 2025Review
- Epigenome analysis of an algae-infecting giant virus reveals a unique methylation motif catalogue.PloS one · 2025Article
- Nanopore strand-specific mismatch enables de novo detection of bacterial DNA modifications.Genome research · 2024Article
- Article
- Synthetically-primed adaptation of Pseudomonas putida to a non-native substrate D-xylose.Nature communications · 2024Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA methylation in bacteria frequently serves as a simple immune system, allowing recognition of DNA from foreign sources, such as phages or selfish genetic elements. However, DNA methylation also affects other cell phenotypes in a heritable manner (i.e. epigenetically). While there are several examples of methylation affecting transcription in an epigenetic manner in highly localized contexts, it is not well-established how frequently methylation serves a more general epigenetic function over larger genomic scales. To address this question, here we use Oxford Nanopore sequencing to profile DNA modification marks in three natural isolates of Escherichia coli. We first identify the DNA sequence motifs targeted by the methyltransferases in each strain. We then quantify the frequency of methylation at each of these motifs across the entire genome in different growth conditions. We find that motifs in specific regions of the genome consistently exhibit high or low levels of methylation. Furthermore, we show that there are replicable and consistent differences in methylated regions across different growth conditions. This suggests that during growth, E. coli transiently differentiate into distinct methylation states that depend on the growth state, raising the possibility that measuring DNA methylation alone can be used to infer bacterial growth states without additional information such as transcriptome or proteome data. These results show the utility of using Oxford Nanopore sequencing as an economic means to infer DNA methylation status. They also provide new insights into the dynamics of methylation during bacterial growth and provide evidence of differentiated cell states, a transient analog to what is observed in the differentiation of cell types in multicellular organisms.
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