By the bioMérieux Connection Editors
Whole genome sequencing (WGS), the process of determining the complete nucleotide or DNA/RNA sequence of a genome at one time, has made headlines recently for its potential to transform infectious disease management, particularly related to SARS-CoV-2, the virus responsible for the COVID-19 pandemic. The U.K. government launched a new initiative that aims to analyze the differences in the genetic code of viruses from different patients to map the spread of COVID-19 in real time. Better understanding of the genetic makeup of the virus could inform strategies for public health and patient care, while also facilitating the creation of therapies and vaccines.
In the same way that whole genome sequencing can provide value in understanding and managing SARS-CoV-2, it can also help in fighting antimicrobial resistance (AMR). AMR is always a concern, but it is even more of a problem during a pandemic, when healthcare systems can become overburdened. Whole genome sequencing can provide rich surveillance data for tracking pathogens and AMR worldwide. Advancements in sequencing technology, such as next-generation sequencing, expanded databases, and robust online tools, present opportunities to further shape how we manage antimicrobial resistance and infectious diseases.
Antimicrobial Susceptibility Testing and Infectious Disease Surveillance
Generally, whole genome sequencing studies have relied on high-throughput sequencers to minimize costs, which can have slow turnaround times. However, the introduction of rapid benchtop sequencers has sharply reduced the cost to generate data, which has helped support the study of machine learning capabilities for whole genome sequencing antimicrobial susceptibility testing (WG-AST). WGS-AST can identify all known resistance genotypes throughout the entire genome simultaneously, whereas phenotypic antimicrobial susceptibility results are often limited by the number and type of resistant mechanisms that can be detected using traditional culture based methods. This additional information from whole genome sequencing can provide insight for identifying and tracking infectious diseases.
For example, in 2013, a neonatal unit suffered an MRSA outbreak, but it was not possible to determine whether the cases were linked using traditional strain typing methods. Rapid whole genome sequencing confirmed that a member of the staff on the neonatal unit was an MRSA carrier and colonized with the outbreak strain. The staff member was relieved from clinical duties for treatment and successfully underwent decolonization, and no further MRSA isolates linked to the outbreak were observed in the unit.
In addition to individual hospitals, whole genome sequencing has also provided benefits to public health. In 2018, the National Antimicrobial Resistance Monitoring System (NARMS) utilized whole genome sequencing to distinguish between two Salmonella outbreaks. NARMS scientists were aware of one outbreak, but when they used whole genome sequencing to identify antibiotic resistance, they found differing susceptibility patterns between strains. This information led epidemiologists to believe that two outbreaks occurred simultaneously prompting a more thorough investigation, ultimately resulting in actionable data for both outbreaks.
The incident demonstrated how combining detailed genetic information with epidemiologic data helps scientists more precisely link illnesses to specific food or animal sources. Major food safety and public health organizations are adopting whole genome sequencing—in 2019, PulseNet, which is governed by the CDC, announced its laboratory network would transition to using whole genome sequencing to combat foodborne diseases more effectively.
The Future of Genomic Data
While whole genome sequencing can be a powerful addition to traditional AST methods, it also has the potential to contribute to other areas related to antimicrobial resistance. Genomic data can be stored digitally and queried for other purposes in the future, including drug development, infectious disease surveillance, and identification of emerging resistance trends. The accumulation of pathogen genomes in clinical laboratories also creates a data source that can be used to research the evolution of resistant pathogens.
Technological advancements will begin to provide more granular data from more sources, such as animals, food, and the environment, so that researchers and clinicians can more thoroughly and accurately track antimicrobial resistance. As these surveillance systems proliferate, expand, and mature, they will contribute the data that are needed to facilitate a One Health approach to managing antimicrobial resistance. Because microbes live everywhere and can develop resistance anywhere, this genomic data has the potential to help us truly grasp the extent of the microbiological ecosystems we live with, and effectively prevent or treat infectious diseases.
Opinions expressed in this article are not necessarily those of bioMérieux, Inc.