The universality of DNA methylation as an epigenetic regulatory mechanism belongs to all biological kingdoms. However, while eukaryotic systems have been the primary focus of DNA methylation studies, the molecular mechanisms in prokaryotes are less known. Nevertheless, DNA methylation in prokaryotes plays a pivotal role in many cellular processes such as defense systems against exogenous DNA, cell cycle dynamics, and gene expression, including virulence. Thanks to single-molecule DNA sequencing technologies, genome-wide identification of methylated DNA is becoming feasible on a large scale, providing the possibility to investigate more deeply the presence, variability, and roles of DNA methylation. Here, we present an overview of the multifaceted roles of DNA methylation in prokaryotes and suggest research directions and tools which can enable us to better understand the contribution of DNA methylation to prokaryotic genome evolution and adaptation. In particular, we emphasize the need to understand the presence and role of transgenerational inheritance, as well as the impact of epigenomic signatures on adaptation and genome evolution. Research directions and the importance of novel computational tools are underlined.

DNA methylation is one of the most observed epigenetic modifications. It is present in eukaryotes and prokaryotes and is related to several biological phenomena, including gene flow and adaptation to environmental conditions. The widespread use of third-generation sequencing technologies allows direct and easy detection of genome-wide methylation profiles, offering increasing opportunities to understand and exploit the epigenomic landscape of individuals and populations. Here, we present a pipeline named MeStudio, with the aim of analyzing and combining genome-wide methylation profiles with genomic features. Outputs report the presence of DNA methylation in coding sequences (CDSs) and noncoding sequences, including both intergenic sequences and sequences upstream of the CDS. We apply this novel tool, showing the usage and performance of MeStudio, on a set of single-molecule real-time sequencing outputs from strains of the bacterial species Sinorhizobium meliloti.

In prokaryotes, DNA methylation plays roles in DNA repair, gene expression, cell cycle progression, and immune recognition of foreign DNA. Genome-wide methylation patterns can vary between strains, influencing phenotype, and gene transfer. However, broader evolutionary studies on bacterial epigenomic variation remain limited. In this study, we conducted an epigenomic analysis using single-molecule real-time sequencing on 21 strains of Sinorhizobium meliloti, a facultative plant nitrogen-fixing alphaproteobacterium. This species is notable for its multipartite genome structure, consisting of a chromosome, chromid, and megaplasmid, leading to significant genomic and phenotypic diversity. We identified 16 palindromic and nonpalindromic methylated DNA motifs, including N4-methylcytosine and N6-methyladenine modifications, and analyzed their associated methyltransferases. Some motifs were methylated across all strains, forming a core set of epigenomic signatures, while others exhibited variable methylation frequencies, indicating a dispensable (shell) epigenome. Additionally, we observed differences in methylation frequency between replicons and within coding sequences versus regulatory regions, suggesting that methylation patterns may reflect multipartite genome evolution and influence gene regulation. Overall, our findings reveal extensive epigenomic diversity in S. meliloti, with complex epigenomic signatures varying across replicons and genomic regions. These results enhance our understanding of multipartite genome evolution and highlight the potential role of epigenomic diversity in phenotypic variation.

Interpreting a bacterial methylome is a multi-omics problem. It requires integrating modified-base calls with genome annotation, motif inventories, methyltransferase genotypes, transcript abundance, replichore position and, increasingly, chromosome conformation. These data types are commonly generated in incompatible formats, use inconsistent sequence and gene identifiers, and originate from different analytical workflows. Relevant algorithms are available but assembling them into a coherent and statistically defensible analysis remains a substantial data-integration and interface problem. We present MErlin (Methylation-driven Expression & Regulation Linkage in Interacting Nuclear-domains), a multi-omics toolkit comprising seventeen composable modules, from basecalled modBAM files to ranked gene-level evidence and a self-contained HTML report. MErlin is distributed both as a conventional Python package and as an agent skill: a structured, version-controlled layer of procedural knowledge that enables a compatible large language model (LLM) assistant to select and operate the audited package without generating a new analysis implementation for each request. This design treats natural language as an interface to fixed analytical operations rather than as a substitute for tested scientific software. The skill encodes module-selection rules, mandatory preflight checks, questions that require human input, design-to-inference constraints, and interpretation guidance. We describe MErlin’s architecture and statistics, validate it against a synthetic dataset with planted ground truth, and illustrate the conversational interface on a real methylome–transcriptome comparison in Pseudoalteromonas haloplanktis TAC125. MErlin is open source and available at https://github.com/IacopoPasseri/MErlin .

Motivation: DNA methylation is the most relevant epigenetic information, present in eukaryotes and prokaryotes, and is related to several biological phenomena, from cellular differentiation to control of gene flow, pathogenesis and virulence. The widespread use of third-generation sequencing technologies allows direct and easy detection of genome-wide methylation profiles, offering increasing opportunities to understand and exploit the epigenomics landscape. Results: We introduce MeStudio, a pipeline which allows to analyse and combine genome-wide methylation profiles with genomic features. Outputs report the presence of DNA methylation in coding sequences, noncoding sequences, intergenic sequences, and sequences upstream to CDS. We show the usage and performances of MeStudio on a set of single-molecule real time sequencing outputs from the bacterial species Sinorhizobium meliloti . Availability and Implementation: MeStudio is written in Python, Bash and C and is freely available under an open source GPLv3 license at https://github.com/combogenomics/MeStudio Supplementary information: Supplementary data are available at Bioinformatics online. Contact: combo.unifi@gmail.com

In prokaryotes, DNA methylation has been found to be involved in several mechanisms, such as DNA repair, DNA–protein interactions, gene expression, cell cycle progression and self-DNA recognition (the Restriction-Modification systems). Studies on representatives from the same bacterial species have found that genome-wide DNA methylation patterns can be highly variable and may affect phenotypic variation and gene transfer among closely related strains. However, broader evolutionary studies on such epigenomic variation in bacteria are still scarce. Here, we addressed this point by performing an epigenomic analysis on 21 strains of the facultative plant symbiotic nitrogen-fixing alphaproteobacterium Sinorhizobium meliloti . Strains of these species are characterized by a divided (multipartite) genome structure, including a chromosome, a chromid and a (more recently acquired) megaplasmid. Since these strains display extensive genomic and phenotypic variation, they are good models to test evolutionary hypotheses on the relationships among epigenomic signatures, genome structure evolution and phenotypic switches. Results showed the presence of a wide pan-epigenome with 16 DNA methylated motifs, including both 4mC and 6mA palindromic and nonpalindromic motifs. While 9 motifs have been found methylated by all strains, the remaining had differential methylation between S. meliloti strains, constituting a dispensable epigenome. Differences in frequency of methylation were found among replicons, with the megaplasmid and the additional plasmids displaying several motifs with different methylation frequency with respect to the chromosome and the chromid. Moreover, differences between coding, upstream and intergenic regions, were found, suggesting that DNA methylation at specific motifs may play a role in gene regulation and consequently in phenotypic variability among strains. Altogether, our data indicate the presence of a large epigenomic diversity in S. meliloti , with epigenome signatures differing between replicons, reflecting their timing of evolutionary acquisition in S. meliloti genomes and suggesting a role of DNA methylation in the variability of gene expression among strains.