Growth rate dependent DNA methylation patterns along bacterial chromosomes
DNA methylation plays critical roles in gene regulation in bacteria, from regulating essential processes like the cell cycle to phenotypes of practical interest like pathogenicity and motility. Synthetic manipulation of global methylation levels has broad impacts on cellular physiology, changing expression patterns of hundreds of genes. However, whether or how environmental variation in natural settings similarly impacts DNA methylation patterns has been unclear. In this work, using the alphaproteobacteria Methylobacterium extorquens and Caulobacter crescentus as model systems, we discover the methylome is highly fluid in response to environmental variation, with different environments leading to distinct patterns of increased or decreased methylation levels along the chromosome. Despite a heterogeneous effect of different environments on methylation patterns, we find a general principle where the dependence of methylation states on position in the genome decreases in proportion to growth rate. A simple model that considers the methylation state through different phases of the cell cycle as a function of distance from an origin provides a framework to interpret the effects of different stressors upon the observed environmental responsiveness of the methylation patterns. Our work highlights how sequencing data alone can shed light on important aspects of microbial physiology. Significance StatementDNA methylation is known to profoundly impact gene regulation in prokaryotes, with both distinct methylation states at specific loci and global levels of DNA methylation modulating critical cellular phenotypes. Yet whether or how DNA methylation patterns depend on environmental variation remains unclear. Using Methylobacterium and Caulobacter as model systems, we combine experiments and theory to uncover general principles of how global patterns of DNA methylation are shaped by the environment. In particular, we discover a positive relationship between growth rate and the magnitude of the genomic position-dependent methylation level, highlighting how sequencing data can provide a culture-independent approach to estimating microbial traits like growth rate in natural settings. Our results resolve an open question, highlighting that DNA methylation patterns in bacteria can rapidly change in response to environmental shifts and revealing rules by which methylation patterns can help understand cellular phenotypes.