What is Genomic Surveillance?
Decreasing DNA sequencing costs and new user-friendly bioinformatics platforms have made genomic surveillance a powerful tool for preventing infectious diseases. This post explains what it is, who benefits, and what to consider before implementing genomic surveillance.
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What is genomic surveillance?
Genomic surveillance means tracking genetic changes in pathogens over time and integrating this information with epidemiological data. By sequencing multiple samples of the same pathogen, like SARS-CoV-2, you can monitor their evolution.
Benefits of genomic surveillance
Early outbreak detection
Genomic methods can detect outbreaks, with automated early warnings and show the transmission of plasmids across species.
High discrimination
Genomic data has high discriminatory power, showing the relatedness of samples on a granular level. This approach can disprove suspected transmission events, where the basic demographics may look identical, but the pathogen’s origin is separate.
Real-time visibility into evolutionary changes
Real-time visibility into the evolution, such as newly acquired antimicrobial resistance, helps stay ahead of outbreaks.
Enhanced preparedness, collaboration, and response
New information about circulating pathogens will affect health guidelines, hygiene, antimicrobial use, and product recalls. These interventions are costly and long-lasting, and genomic data supports these decisions.
Backwards compatibility
Pathogens move geographically and come in waves. Genomes can be compared against a vast historical database to understand what drives sudden increases of certain pathogens.
Methods Used in Genomic Surveillance
Sampling, preparation, and sequencing
Samples are usually pre-screened against criteria before sequencing. Common screening criteria are multi-drug resistance, patient risk factors, specific species, or previous outbreaks in a location.
Samples can be taken from infected or non-infected clinical patients, food, or environmental sources like surfaces, equipment, and wastewater. After sampling, the pathogens are prepared for sequencing. The most popular sequencing method is whole genome sequencing (WGS), but metagenomic and shotgun approaches are also used.
Bioinformatics
Surveillance programs use bioinformatics for species identification, subtyping, genomic characterization (e.g. antimicrobial resistance), tracking evolution, and reconstructing transmission dynamics.
Real-time data sharing
Genomic data is integrated with epidemiological information, such as patient movement data or structured interviews. It may be shared with other researchers, global pathogen databases, other local healthcare systems, and public health officials. Early warnings are crucial for emerging and dangerous species.
Applications of Genomic Surveillance
Hospital Infection Prevention and Control
Genomic surveillance helps in clustering and identifying related samples. The clusters represent possible transmission, and may lead to further discoveries of unknown pathogen reservoirs, such as medical equipment or drains. Detailed pathogen information informs interventions, e.g. discovering quaternary ammonium resistance affects disinfecting agent choices. Disproving suspected transmission avoids unnecessary interventions.
Public health
Genomic surveillance in public health tracks infectious disease risk, predicts disease trends, and improves treatments. By combining genetic sequencing with epidemiological data, we better understand disease spread and detect new pathogens early. This approach supports targeted outbreak responses, global health cooperation, and policies on antimicrobial use.
Food safety
Routine sequencing of food samples establishes pathogen baseline and development trends. Heavy antibiotic use in food production is known to increase antimicrobial resistance, which can now be monitored in real time.
What kind of hospital would benefit from genomic surveillance?
While any hospital can benefit from genomic surveillance, the biggest gains typically come from these factors:
High-risk pathogens in the community
Genomic surveillance is a preventative, risk-reducing method, and therefore its value is greater in high-incidence communities.
High-risk patients
Some patients are at higher risk of contracting and suffering from infectious diseases. Genomic surveillance is a targeted risk reduction strategy for immunocompromised patients, ICU patients, burn victims, and similar groups.
High standards for patient safety
Even if hospitals have low infection rates, genomic surveillance provides concrete evidence of outbreaks' presence or absence. Being able to demonstrate the absence of outbreaks helps hospitals justify the investment into patient safety.
Persistent outbreaks
Hospitals facing ongoing outbreaks can use genomic surveillance to understand the cause. High-resolution genomic subtyping will help determine if new cases are part of a persistent outbreak or unrelated.
Suspected healthcare-associated infections
Hospitals with high infection rates can benefit from genomic surveillance. By studying the genetic makeup of the germs causing these infections, hospitals can find root causes more effectively and protect their patients.
What to consider when starting genomic surveillance?
Define goals for genomic surveillance. Focus on priority pathogens or locations first and expand gradually.
Involve multiple functions to maximize the value of surveillance. Involve microbiology, infection prevention, clinical, and antibiotic stewardship teams in the process.
Insourcing vs. outsourcing genomic surveillance involves considering cost, turnaround time, quality, and data security. Consider what works best for your organization.
Challenges of Genomic Surveillance
- Investments: sequencing equipment, infrastructure, and training can be a barrier for hospitals starting genomic surveillance.
- Turnaround time: The various steps should be seamlessly coordinated to get the results as quickly as possible
- Data volume: Sequencing creates massive amounts of data, and managing and storing it can be overwhelming without proper infrastructure.
- Data integration: Combining genomic and epidemiological data involves manual work, slowing down the analysis.
- Sample quality is essential for valid conclusions from genomic analyses.
- Physical space: Many hospitals lack space for sequencing devices and reagents.
- Expertise: Result interpretation requires knowledge of genomics and bioinformatics.
- Workload: Implementing genomic surveillance programs can add healthcare staff’s workload
How to choose the right sequencing methods for genomic surveillance?
Short reads – most popular
Short-read sequencing, like Illumina, is widely used for bacterial and viral sequencing due to its availability, cost, and timelines. However, short-read assemblies may not accurately represent the chromosome and plasmids.
Long reads – best for plasmids
Long-read sequencing provides more contiguous assemblies than short-read methods and preserves plasmids better in the data. Long-read data traditionally has a higher error rate than short-read sequencing, causing some false negatives for sample clustering and subtyping. New chemistry kits and basecalling methods are improving this.
Hybrid - most accurate
Hybrid sequencing combines short- and long-read sequencing, resulting in polished, reference-quality assemblies, more reliable than either method alone. The downsides are high costs and longer timelines.
Metagenomics – best for wastewater
Environmental reservoirs contain multiple microbes, and metagenomic sequencing is a good way to determine the sample’s contents. It has simpler sample preparation steps but lacks the resolution of whole genome sequencing.
Why is quality important for genomic surveillance?
Errors in the system reduce the sensitivity and specificity of the results, and erode trust in the surveillance. A good system should check for contamination, DNA quantity and quality, sequencing read quality, assembly quality, and annotation results.
Databases and tools should be validated updated regularly to keep up with evolving knowledge of emerging pathogens and AMR mechanisms.
Findings should be validated with epidemiological methods to maintain awareness of the surveillance program’s effectiveness.
How much does genomic surveillance cost?
Genomic surveillance costs include sequencing, infrastructure, data analysis, labor, and overhead and capital expenditures. Cost-effectiveness analyses of genomic surveillance programs usually report a cost from 50 to 300 USD per sample.
Some companies, like Solu, offer integrated genomic surveillance at a fixed price.
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