By Shannon Mahoney, senior specialist, Advanced Molecular Detection, APHL
With the recent COVID-19 pandemic and mpox outbreak, public health laboratories have found themselves in the critical position of having to rapidly adapt to emergent situations impacting a global population. For that reason, the APHL ID Lab Con session “Metagenomic Approaches to Infectious Disease Surveillance and Diagnostics” proved to be very popular. The panel of bioinformaticians, moderated by Patricia Simner, PhD, D(ABMM), Johns Hopkins University School of Medicine, provided attendees with insight into how state laboratories, the US Centers for Disease Control and Prevention (CDC) and academia have been working to combat new and evolving challenges in public health.
Metagenomics in Emergent Public Health Scenarios
Jared Johnson, PhD, former APHL Fellow and currently with the Michigan Bureau of Laboratories opened the session detailing his work utilizing shotgun metagenomics to establish a genomic surveillance methodology during the 2022 mpox outbreak.
Per guidelines from CDC, biosafety protocols regarding mpox are largely dependent on their identified clade, as infections with phylogenetically distinct viral strains can greatly affect the rate of mortality during an outbreak. The mpox virus is composed of two clades: Clade I, which is identified as a Select Agent by CDC and has a fatality rate of around 10% and Clade II, which has two definitive subsets and is rarely fatal, with a 99% recovery rate. Identifying the clade of a mpox-positive specimen plays a large role in helping to ensure the safety of not only the testing laboratory’s laboratory staff, but the communities that could be widely impacted by the outbreak. These factors led the state’s virology section to take action, implementing a method that could help sequence the emergent virus.
The benefit of a metagenomic approach allowed them to rapidly develop a surveillance method that didn’t need to be continuously altered once implemented, permitting for them to sequence without the threat of a decrease in the taxonomic classification quality. By developing a shotgun metagenomics method, which was sequenced on the Illumina NextSeq 550 System and analyzed using open-source alignment and clustering tools Nextclade and Mash, Michigan hopes to promote a robust sequencing technique commonly used to help identify continuously evolving viruses.
Bioinformatics in Resource-Limited Environments
A critical component of public health is being able to identify emergent threats in any region or country. However, one might begin to wonder how a resource-limited laboratory can manage infectious disease outbreaks, where access to technology, computing or personnel often provide a major roadblock.
That was the topic addressed by Brian Merritt’s talk on a threat-agnostic sequencing software toolkit developed by Johns Hopkins University’s Applied Physical Laboratory. Built around open-source workflow and analysis programs nf-core and Basestack, the toolkit provides a myriad of benefits to organizations constrained by hardware accessibility and technical limitations of staff.
The toolkit supports both short-read and long-read sequencing operations, and features interactive quality metrics, real-time reporting and taxonomic filtering, and a CLIA-style report detailing organism identification. No command line knowledge is needed to utilize the toolkit and its ability to be deployed from Docker reduces the need for high-end computing—promoting it as an easily deployable and widely accessible platform.
The Hopkins team has already tested and deployed the toolkit in a variety of use cases, teaming up with health partners in Cambodia and the NIH’s Fogarty International Center to introduce the platform in over 25 countries so far. In the future, they hope to implement more improvements such as expanding integrated module management, enlarging cloud integration, adding additional bioinformatic modules, and more.
Using Culture-independent Metagenomics to Tackle Foodborne Illness
One of the key advantages of metagenomics stands with its ability to provide a more comprehensive view of microbial communities when compared to traditional culture-based methods, which tend to be significantly more time-consuming and biased toward specific types of organisms. Similarly, culture-independent diagnostic testing (CIDT) also fails to identify novel pathogens. When compared to culture-based testing and CIDT, metagenomics tends to serve as an improved methodology when working with outbreaks of unknown etiology.
The advantages of culture-independent metagenomics weren’t lost on Andrew Huang, PhD, of CDC’s Enteric Diseases Laboratory Branch (EDLB), who discussed his unit’s Undiagnosed Diarrheal Illness (UNDI) project, aimed at tackling the frequency of unknown agents that cause one in every four foodborne illness outbreaks.
The project sought to develop a pipeline to aid in pathogen discovery for organisms with strong epidemiological links, but negative or inconsistent CIDT results. This led the CDC EDLB team to establishment a two-tier pipeline. The first tier serves as a rapid, inexpensive triage step targeting markers of known diarrheal pathogens (such as Shigella, Campylobacter, and Salmonella) that weren’t initially defined by CIDT.
The second tier, which would be utilized for specimen rendered negative or indeterminate in the first tier, applies a pathogen-agnostic shotgun metagenomic approach designed to identify shared genomic material for a small number of outbreak samples. It utilizes both reference-based tools (such as MIDAS2) and reference-free tools (such as composition based tools like MetaBat and MaxBin) to attempt to differentiate potential known pathogens that can evade CIDTs from the identification of a novel pathogen fueling a foodborne illness outbreak.
To further develop the pipeline, the CDC EDLB team are currently looking for state public health partners to collaborate with in order to aid in the collection of foodborne outbreak stool samples.