Bacterial Epigenomics: Coming of Age

Microbiome and epigenetic variation in wild fish with low genetic diversity

Non-genetic sources of phenotypic variation, such as the epigenome and the microbiome, could be important contributors to adaptive variation for species with low genetic diversity. However, little is known about the complex interaction between these factors and the genetic diversity of the host, particularly in wild populations. Here, we examine the skin microbiome composition of two closely-related mangrove killifish species with different mating systems (self-fertilising and outcrossing) under sympatric and allopatric conditions. This allows us to partition the influence of the genotype and the environment on their microbiome and (previously described) epigenetic profiles. We find the diversity and community composition of the skin microbiome are strongly shaped by the environment and, to a lesser extent, by species-specific influences. Heterozygosity and microbiome alpha diversity, but not epigenetic variation, are associated with the fluctuating asymmetry of traits related to performance (vision) and behaviour (aggression). Our study identifies that a proportion of the epigenetic diversity and microbiome differentiation is unrelated to genetic variation, and we find evidence for an associative relationship between microbiome and epigenetic diversity in these wild populations. This suggests that both mechanisms could potentially contribute to variation in species with low genetic diversity.

Bacmethy: A novel and convenient tool for investigating bacterial DNA methylation pattern and their transcriptional regulation effects

DNA methylation serves as the primary mode of epigenetic regulation in prokaryotes, particularly through transcriptional regulation. With the rapid implementation of third-generation sequencing technology, we are currently experiencing a golden age of bacterial epigenomics. However, there has been a lack of comprehensive research exploring the versatility and consequential impact of bacterial DNA methylome on cellular and physiological functions. There is a critical need for a user-friendly bioinformatics tool that can effectively characterize DNA methylation modification features and predict the regulation patterns. To address this gap, the current study introduces Bacmethy, an innovative tool that utilizes SMRT-seq data and offers a range of analytical modules. First, the tool classifies methylation sites in the genome, highlighting the distinct regulations present under varying modification fractions and location enrichment. Furthermore, this tool enables us to identify regulatory region methylation and potential cis and trans interactions between methylation sites and regulatory effectors. Using benchmark data sets and our data, we show that our tool facilitates the understanding of the distinctive traits of DNA methylation modifications and predicts transcriptional regulation effects on important physiological and pathological functions. Bacmethy code is freely available, and the Docker image is downloadable. Bacmethy has been made available as a user-friendly web server interface at https://bacmethy.med.sustech.edu.cn.

Cardiometabolic health, diet and the gut microbiome: a meta-omics perspective

Cardiometabolic diseases have become a leading cause of morbidity and mortality globally. They have been tightly linked to microbiome taxonomic and functional composition, with diet possibly mediating some of the associations described. Both the microbiome and diet are modifiable, which opens the way for novel therapeutic strategies. High-throughput omics techniques applied on microbiome samples (meta-omics) hold the unprecedented potential to shed light on the intricate links between diet, the microbiome, the metabolome and cardiometabolic health, with a top-down approach. However, effective integration of complementary meta-omic techniques is an open challenge and their application on large cohorts is still limited. Here we review meta-omics techniques and discuss their potential in this context, highlighting recent large-scale efforts and the novel insights they provided. Finally, we look to the next decade of meta-omics research and discuss various translational and clinical pathways to improving cardiometabolic health.

Growth condition-dependent differences in methylation imply transiently differentiated DNA methylation states in Escherichia coli

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.