Upon viral infection, assessing the host nasal epigenome

Amy Carpenter Aquino

August 2023—Analyzing the nasal epigenome can shed light on viral infections, strain differences, and potentially infection severity, and for influenza B in particular the results are striking.

The epigenome describes modifications to the genome that don’t affect the DNA sequence but determine whether genes are switched on or off where and when they are needed.

In a plenary presentation last November at the Association for Molecular Pathology meeting, Elin Grundberg, PhD, the Roberta D. Harding and William F. Bradley Jr. endowed chair in genomic research, Genomic Medicine Center, Children’s Mercy Research Institute, Children’s Mercy Kansas City, reported the results of her group’s recent efforts in understanding epigenome perturbation in infectious respiratory disease using DNA obtained from nasal swabs.

Dr. Grundberg and colleagues at Children’s Mercy use next-generation sequencing technologies to understand how environmental triggers and genetic predisposition affect the functional genome and disease risk.

While links are commonly made between genetic variation across populations and disease outcome, and a statistical link can be made between a genetic marker and disease risk, “it’s sometimes challenging to understand the molecular mechanism and biological consequences of this association,” she said. Epidemiology studies have also been able to link variables such as diet and smoking to disease outcome. “The challenge with all of these is we don’t have the molecular pathways,” said Dr. Grundberg, who is also associate professor of pediatrics, University of Missouri–Kansas City School of Medicine, and research associate professor of pathology, University of Kansas School of Medicine.

“What’s become clear and successful across multiple studies is that we can use an intermediate trait, such as a cellular phenotype, to link genetics to epigenomic function assessments to improve our understanding of the biological mechanism to the disease association,” and then find the cause of these diseases, she said.

DNA methylation, a chemical modification to the DNA that can be used to predict regulatory element presence and activity, is the most commonly used epigenetic trait. “It allows us to gain additional insight into biological pathways linked to our disease trait of interest,” Dr. Grundberg said. DNA methylation variation is region dependent. Promoter regions are larger, mostly invariable, unmethylated, and often close to the transcription start sites. Enhancer-like regulatory regions, on the other hand, are more variable when assessed across individuals and have intermediate cytosine methylation and low CpG density.

“My lab spent a fair amount of time assessing and trying to improve the way we measure DNA methylation genomewide,” Dr. Grundberg said. The two most common approaches to methylome investigations—microarray and whole genome bisulfite sequencing—are limited by biased content (microarray) and high cost (sequencing), she said. Her laboratory focused on how to retain the high resolution and single CpG resolution of next-generation sequencing.

“So we designed an approach,” methylC-capture sequencing, “where we simply filter out anything we don’t think is a variable and then enrich regions overlapping regulatory elements, like we do in exome sequencing, for instance,” Dr. Grundberg said. Her group at McGill University worked with Roche NimbleGen to design this capture approach using specific probes to target each epigenome of interest. “We designed probes and targets toward disease we’re interested in or the tissue we’re sampling with” (Allum F, et al. Nat Commun. 2015;​6:7211; Allum F, et al. Nat Commun. 2019;10[1]:1209).

Dr. Grundberg’s laboratory team at Children’s Mercy Research Institute hypothesized that since viral infections involve functional associations of the host-gene expression machinery, infection severity could also be linked to regulatory changes marked by epigenetic modifications.

“We set up a study where we leveraged the nasal mucosal samples” used clinically and kept for research, Dr. Grundberg said, noting their focus was children but they’ve done the same in adults. The appeal of nasal swabs was based on the ready availability of the samples and their being “at that time a relatively untouched biospecimen type in terms of understanding epigenome perturbations.”

They focused on genomewide assessments of respiratory viral infections and their link to infection status and severity. Their aim, she said—they’re not there yet—is to do epi­genome analysis in the host and link that to the deep clinical information they have from the samples and then perform sophisticated pathway and network analysis. Although their study samples were small in quantity and limited in terms of useful molecular and cellular phenotypes, Dr. Grundberg’s group was also able to perform protein and single-cell analysis on the salvage nasal mucosa samples.

In their first project, in the 2018–2019 viral season, Dr. Grundberg said her group was less interested in the interindividual variation within infections and more focused on viral type. They limited the sample group to infants under age six months to focus on the primary infections pre-vaccination.

They collected 10 samples across seven respiratory viruses and a noninfected cohort, pooled the samples, and performed high-resolution whole genome bisulfite sequencing per individual.

“We can use the methylation landscape to create footprints and inform about regulatory activity, so we were able to do the same here for the first time using the nasal samples and creating first a landscape or a map of regulatory elements in these nasal samples,” she said. They saw the same patterns seen in other tissue samples—“roughly 60,000 enhancer elements that we can capture and 20,000 promoters.”

Given this was a new tissue type they hadn’t worked with previously, they wanted to see the underlying cell types they were capturing. “So we were using high-throughput histone modification data that had been generated from various consortia to overlap that with our data,” Dr. Grundberg said. A fair amount—20 percent of their regulatory elements—appear to be immune specific, but, as expected, they identified epithelial-specific elements too.

How did the regulatory element activities differ based on infection type? They found that 42 percent are unique to a viral or nonviral pool. “The most commonly unique condition was those that were hypomethylated, an activation of a regulatory element, which made more sense than having a repression.”

The influenza B samples provided the first evidence that one of their viral types was an outlier. They “showed a striking number of unique regulatory elements compared with others,” Dr. Grundberg said, referring to the hypo- and hypermethylated regions. Of the 42 percent of regions that seemed to be specific to a viral or nonviral pool, 80 percent of those were seen just in influenza B. “So it was a little exciting that the first analysis of its kind showed a signature like this.”

They then looked at the single-site CpG levels and measured about 20 million of them across the 10 viral sample types. Next they assessed the correlation distances using hierarchical clustering. “Again, we noticed that the influenza B samples continued to be an outlier in terms of similarities of the epigenome landscape.”

Dr. Grundberg’s group addressed the challenge of how to validate the findings working with these salvage samples stored in freezers or refrigerators by connecting with Olink, a company performing high-resolution, highly sensitive protein analysis. “Because mRNAs are not intact, we could not use gene expression as a validation approach, so we explored protein measures instead. Olink was eager to work with us since the nasal swab was a new sample type for them.” Olink was able to use the very limited material it had of exactly the same samples her group had used for epigenome analysis. “We were using their NGS readout for about 1,600 proteins and did an unbiased protein analysis,” Dr. Grundberg said.