INDUSTRY MATTERS
Leveraging Genomics and Automation to Address the Rise in Multi-Drug Resistant Bacteria Outbreaks
By Michael Balamotis , PhD , staff scientist , Clear Labs ; Andrew Lin , PhD , staff scientist , Clear Labs ; and Kristina Hsieh , DrPH , Scientific Affairs lead , Clear Labs
PulseNet utilize WGS to track pathogens that cause foodborne illness by leveraging their decentralized network of labs .
Currently , most drug-resistant bacteria are identified through a combination of lab culture work , PCR and antimicrobial susceptibility testing ( AST ). Pairing genomic data with these AST data creates linkage maps that can function as a powerful toolset for surveillance , intervention and treatment selection . The NCBI has a public database that contains genomic and phenotypic AST information . As more laboratories gain the capacity to upload sequence data along with AST data , the robustness and value of these databases will expand so that the entire scientific community can use the data in ways like what we have seen with the COVID-19 pandemic for detection , surveillance , and vaccine development .
Each year in the United States , more than 2.8 million antibiotic-resistant infections occur that can lead to death and longterm infection , taking psychological , physical and financial toll on patients and families .
1 Under selective pressure due to overuse of antibiotics , new “ superbugs ” such as
Methicillin Resistant Staphylococcus aureus , Carbapenemresistant Enterobacterales , and multi drug-resistant
Neisseria gonorrhoeae pose formidable challenges to our healthcare system . These bacteria evolve rapidly to thwart our current antibiotic lines of defense , making antimicrobial resistance ( AR ) a recognized public health threat by the
World Health Organization .
2 The steady increase of AR must be met by robust , rapid methods for detection and characterization .
Clear Labs is an APHL Gold Level Sustaining Member .
Giving the Data Its Due
The data obtained from whole genome sequencing ( WGS ) provides the scientific leverage needed to successfully combat AR . WGS reveals the unique genomic fingerprint of a bacterium , including virulence genes associated with a resistance phenotype . WGS sequencing information is valuable because it captures long stretches of DNA , such as complex mosaic gene mutation patterns that confer resistance and novel pathogenicity islands that may be missed by PCR methods alone . Genomic sequence data has been widely adopted as a common language across a network of government , academic and private industry laboratories and has shown to be an invaluable tool for characterizing pathogens to develop a more in-depth understanding of the organism . For example , the federal government programs such as GenomeTrakr and
Preparing WGS for Prime Time
While WGS is a powerful tool , manual WGS workflows are time-consuming , labor-intensive , and require specialized expertise for analysis 3 , which severely limit the practicality of WGS for routine use in clinical and public health laboratories . However , an automated system on which laboratory staff can be easily trained and one that requires minimal human touchpoints will accelerate the adoption of WGS . An ideal system would automate the entire WGS workflow , including sample lysis , nucleic acid extraction , quantitation , library preparation , sequencing , and bioinformatics analysis , thus leveraging the benefits of WGS with less labor and time at the bench .
In addition to the benchtop process , automation and standardization of the bioinformatics analysis is imperative to ensure that lab technicians who do not have an extensive background in
18 LAB MATTERS Summer 2022