Direct methylation detection with nanopore sequencing enables new view of multiple sclerosis

According to global estimates, nearly two million people have multiple sclerosis (MS) — a neurodegenerative, autoimmune disorder that affects the brain, spinal cord, and optic nerves¹. MS is a chronic disease that can be debilitating. It typically manifests in younger adults, between the ages of 20 and 40, and is more common in women². In some cases, symptoms are milder — such as fatigue or muscular tremors — while other cases progress to increasing levels of disability, with some losing the ability to walk.

Even with so many people affected and decades of research centered on MS, the specific biological mechanisms of the disorder have remained a mystery. Studies have identified that DNA methylation patterns may be associated with the pathogenesis of MS, and there is hope that medications targeting epigenetic factors could one day provide a new pathway for treating the disease. However, it has not been easy to characterise the epigenetic changes that may be associated with MS. Most methods for detecting methylation require a conversion step, such as bisulfite conversion, that provides an added layer of complexity and cost to workflows, as well as the opportunity to introduce errors that could affect experimental results when inappropriate conversion occurs.

Si et al. from the City University of Hong Kong, China, deployed nanopore sequencing from Oxford Nanopore Technologies to perform direct detection of methylation in an animal model of MS³. Their study underscores the value of ultra-rich data generated by nanopore sequencing for elucidating mechanisms of disease, and shows that direct methylation detection provides high-quality information about how epigenetics may influence the onset of MS.

Methylation in the mouse brain

The researchers turned to nanopore sequencing because of its track record in advancing epigenetic studies, noting that it 'has been applied as a robust tool for investigating genomes, epigenomes, transcriptomes, and epitranscriptomes due to its rapid advances in detecting full-length transcript and base [modifications]'³. With high sensitivity, nanopore technology can detect methylation directly from native DNA — without the need for a conversion step. This capability means that DNA methylation and canonical base sequence data can be produced simultaneously with no additional cost.

For this project, the team used an animal model of MS: mice induced with experimental autoimmune encephalomyelitis (EAE). To pinpoint genes that were differentially expressed in EAE mice, the researchers also analysed a group of healthy control mice. For both groups, mouse brain samples were collected for sequencing and methylation detection. The team prepared four libraries with the PCR-free Ligation Sequencing Kit, sequencing them on a MinION device with an R10.4 MinION Flow Cell.

By comparing the nanopore methylation data from the brain samples of EAE and control mice, the team identified hundreds of epigenetic differences. They found 490 differentially methylated promoters; of those, 163 genes were hypomethylated and 327 genes were hypermethylated.

Next, the team aimed to associate function with those methylation changes. Pathway analysis revealed 215 upregulated functions, including enhanced T cell activation and axon guidance, and 133 downregulated functions, of which reduced vitamin binding and downregulated prolactin were among the major findings. The most hypermethylated gene identified in the comparison was CEND3, which has been detected at increased levels in white blood cells collected for other human studies of MS in identical twins. The study also indicated that EAE mice could have increased lipid metabolism occurring in the brain.

Overall, the researchers reported that the genomic alterations they found 'were linked to changes in metabolism, immune responses, neuronal functions, and mitochondrial activities, which play important pathophysiological roles during the course of EAE'. While a number of the genes that emerged from the comparative analysis have been flagged as relevant in previous MS studies, the authors noted that DNA methylation data for these genes has not been available before. By elucidating methylation patterns with nanopore sequencing and conducting additional metabolomic analyses, they were able to identify 'a potential link between the dysregulation of promoter methylation and metabolome in the brain of EAE mice'.