Genomic Surveillance

NGS can provide unbiased detection of pathogens from a variety of sample types without prior knowledge of the organism.

A key challenge in infectious disease surveillance is that many of the microbes, including viruses, that cause respiratory, digestive, and other diseases in humans, have not been researched and characterized and thus are not known or detected by targeted approaches such as PCR. Development of PCR assays requires knowledge of the pathogen genome. NGS plays a critical role in discovering these unknown, novel pathogens; the resulting genome sequence can then be used to develop routine tests such as PCR to help clinicians manage patients.

NGS can be used to track the evolution of the pathogen genome to help public health officials monitor the spread of infection and determine the best isolation plan at a population level. Sequencing pathogens from different patients, animals, and environments over time can determine the rate of evolution, and address whether the pathogen is changing in ways that could impact pathogenicity as well as diagnostic or therapeutic effectiveness. PCR is designed to detect the presence of specific regions of the pathogen genome and will not identify new mutations across rapidly evolving pathogen genomes. Furthermore, PCR performance can suffer if mutations occur in the primer or probe binding regions.

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NGS vs qPCR

A shotgun metagenomics workflow enables sequencing of both novel and known species. During an outbreak involving an unknown pathogen, multiple molecular diagnostic tests are often utilized; this may lead to unnecessary costs and delays in identifying the pathogen. Shotgun metagenomics can be used as a single comprehensive screening assay for identifying and characterizing pathogens. This research workflow can help accelerate outbreak investigations and support development of new lab tests for large-scale screening efforts.

Once a pathogen is identified, a hybrid capture workflow can provide the high sensitivity needed to detect the pathogen and provide information about its epidemiology and evolution. This information can help researchers optimize infection control strategies, including monitoring when it's acceptable to de-escalate isolation mechanisms and resume normal activities, and aid in the development of diagnostics, vaccines, and therapeutics.

These complementary workflows using Illumina sequencing can be performed alongside traditional testing methods and integrated into a comprehensive outbreak response model.

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Shotgun Metagenomic Sequencing

Hybrid Capture Sequencing

Hybrid capture is a resequencing method that captures genomic regions of interest by hybridization to target-specific biotinylated probes. Enrichment through hybrid–capture methods allows for highly sensitive detection and therefore does not require high read depth. Additionally, the hybrid capture NGS workflow allows for near-complete sequence data of targets and is more tolerant to mutations in the pathogen’s genome.

Alternatively, amplicon sequencing uses gene-specific primers to enrich known targets for ultradeep sequencing. Amplicon sequencing can produce near-complete sequence data of viruses or targeted regions of pathogen species with larger genomes (e.g., Mycobaterium tuberculosis). This method is less tolerant to mutations so it’s important to monitor the primer designs.

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Amplicon Sequencing

Hybrid Capture Sequencing

Amplicon sequencing is best utilized in situations when scientists know what they are looking for. This method does not require cultured isolates and can be used to detect specific, predefined genes associated with microbial identity, AMR mutations, or variants of concern.

For instances where certain pathogens are suspected to be present, or for surveillance of multiple known pathogens from a primary sample, hybrid capture enrichment solutions are ideal.

We recommend visiting our NGS for Beginners page.

Visit our sequencing platforms page to explore our portfolio, or see the workflows on our coronavirus sequencing page for recommendations on which sequencer is optimal for a particular method. The choice of sequencer depends on which method(s) you use most frequently.