Enriching Microbial Cell-Free DNA in Clinical Metagenomics Using Epigenetic Filters.

Authors

Tiepeng Liao, Spencer C Ding, Jingru Yu, Wei Gu

Published in

Clinical chemistry. Aug 05, 2026. Epub Aug 05, 2026.

Abstract

Noninvasive cell-free DNA (cfDNA) metagenomic sequencing enables hypothesis-free detection of microbial pathogens in patients with suspected infections. However, its clinical sensitivity is often limited by the overwhelming background of host-derived cfDNA, which can obscure low-abundance microbial signals. We developed an epigenetically guided enrichment strategy, termed Epigenetically filtered Metagenomic Sequencing (EpiMeta-seq), to selectively enrich microbial cfDNA based on fundamental differences in DNA methylation between microbial and human genomes.
EpiMeta-seq uses the methylation-sensitive restriction enzyme HpaII to selectively digest unmethylated CCGG sites, which are prevalent in microbial genomes but largely methylated in human DNA. Only fragments cleaved once at unmethylated sites are incorporated into sequencing libraries, thereby enriching microbial cfDNA prior to sequencing. We assessed plasma samples from patients with microbiologically confirmed infections. Metagenomics informatics involved alignment, removal of host DNA, and taxonomic classification of sequencing reads to a curated reference database.
In spike-in experiments at a 1:1000 dilution, EpiMeta-seq achieved a mean enrichment of 24.5-fold for fungal species and 11.4-fold for bacterial species compared with unenriched whole-genome sequencing. In 23 clinical plasma samples representing 12 pathogens, EpiMeta-seq produced an average 10.0-fold increase in microbial reads per million. Viral DNA showed the highest enrichment (mean 11.5-fold), while bacterial enrichment varied across species (1.2- to 30.8-fold).
By leveraging genome-wide methylation differences between host and microbial DNA, EpiMeta-seq is a proof-of-concept, orthogonal enrichment strategy for improving microbial cfDNA signal-to-background ratio across diverse pathogen types in metagenomic sequencing.

PMID:
42551913
Bibliographic data and abstract were imported from PubMed on 05 Aug 2026.

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