Emerging methylation-based approaches in microbiome engineering

Abstract

Bacterial epigenetics, particularly through DNA methylation, exerts significant influence over various biological processes such as DNA replication, uptake, and gene regulation in bacteria. In this review, we explore recent advances in characterizing bacterial epigenomes, accompanied by emerging strategies that harness bacterial epigenetics to elucidate and engineer diverse bacterial species with precision and effectiveness. Furthermore, we delve into the potential of epigenetic modifications to steer microbial functions and influence community dynamics, offering promising opportunities for understanding and modulating microbiomes. Additionally, we investigate the extensive diversity of DNA methyltransferases and emphasize their potential utility in the context of the human microbiome. In summary, this review highlights the potential of DNA methylation as a powerful toolkit for engineering microbiomes.

Keywords: Bacterial epigenetics; DNA methyltransferases; Methylome; Microbiome engineering; Restriction-modification (R-M) systems.

Fig. 1

Representative sequencing technologies for mapping DNA modifications. A Bisulfite sequencing begins with the treatment of genomic DNA (gDNA) with sodium bisulfite, a chemical that converts unmethylated cytosines (C) to uracils (U), while leaving methylated cytosines unchanged. PCR-amplified DNA fragments are then sequenced to determine the methylation status of cytosines across the genome. B Single-molecule real-time (SMRT) sequencing monitors the incorporation of fluorescently labeled nucleotides by a DNA polymerase in real time. Each nucleotide addition emits a fluorescent pulse as a signal. The DNA sequence is determined by the pattern of these signals, and interruptions in the pulse sequence indicate the presence of covalent modifications within the template DNA. C Nanopore sequencing utilizes the movement of a single DNA strand through a nanoscale pore (nanopore). As the DNA molecule passes through the pore, it causes disruptions in the electrical current, which are used to deduce the DNA sequence and detect DNA modifications such as 5mC, 4mC, and 6mA

Fig. 2

Potential applications of bacterial epigenetics in microbiome engineering. A Mimicking host DNA methylation patterns and recoding DNA sequences with synonymous nucleotide modifications or single-nucleotide polymorphisms (SNPs) have facilitated the evasion of R-M barrier in bacteria. B DNA MTases can serve as reporter systems for monitoring protein expression levels, achieved by their integration with methylation-sensitive restriction enzyme digestion and subsequent high-throughput sequencing. C Epigenetic regulatory systems utilizing DNA methyltransferases have been devised to sense targeted signals and maintain an epigenetic memory of cellular states. D Natural bacterial DNA methylation and methylation-sensitive Type II REases have been harnessed to selectively enrich genomes of specific bacterial subgroups within microbiomes. E Type IV secretion systems (T4SS), combined with DNA methylation patterns, could offer precision in gene transmission to specific microbes. The use of DNA methylation patterns ensures that gene delivery is confined to targeted microbial clusters, thereby enhancing target specificity. F A fusion protein of DCM (DNA cytosine methyltransferase) and the RNA polymerase subunit b, along with methylated DNA sequencing, has been employed to trace genome-wide gene transcription over time

Fig. 3

Diversity of DNA methyltransferases in the human microbiome. This figure classifies DNA methyltransferases from various bacterial species within the human microbiome using data from the REBASE database. A phylogenetic tree, color-coded by phylum, displays 150 bacterial species and is based on their 16S rRNA gene sequences. A A heat map details the distribution of Type I, II, III, IV, and orphan restriction-modification (R-M) systems across these species, while an adjacent bar plot shows the number of DNA methyltransferases per species, with Treponema succinifaciens registering the highest at 27. Donut charts (B) depict the prevalence of methylation types—5mC, 6mA, and unknown—across all methyltransferases and C the distribution of known versus unknown motifs within all R-M systems. D A bar plot enumerates the proportions of specific known methylation motifs for all R-M systems identified, with motifs appearing only once grouped as “Others”