Our Favorite Publications of 2023¶

2023 has been an incredible year for sequencing in diagnostic and public health labs. Thanks to the innovation and drive of molecular scientists, microbiologists, epidemiologists and laboratory technologists, major progress was made to bring sequencing closer to routine use.

As we look forward to all of the advances that 2024 is sure to bring, we took the opportunity to look back at our favorites from 2023. This list includes a mix of metagenomics, infection control and antimicrobial resistance; each of which is sure to have substantial impact on human health in the year to come and beyond.

Our Favorites¶

WGS of a cluster of MDR Shigella sonnei utilizing Oxford Nanopore R10.4.1 long-read sequencing¶

WGS of a cluster of MDR Shigella sonnei utilizing Oxford Nanopore R10.4.1 long-read sequencing from the Providence Health Care diagnostic lab represents the fourth publication from this team showcasing the power of BugSeq. The automated combination of organism identification, antimicrobial resistance prediction and outbreak analysis by BugSeq enabled a holistic understanding of the Shigella sonnei cluster.

Through their analysis, the team found strong evidence of a clonal strain causing infections:

Near-identical strain typing by MLST, genotype, cgMLST and refMLST
A highly conserved set of 10 plasmids across isolates
Identical genotypic and phenotypic antimicrobial resistance profiles for four important antimicrobials

Ritchie et al:

“BugSeq’s predicted phenotype matched the observed phenotype for all isolates”

Beyond confirmation and characterization of the S. sonnei cluster, Ritchie et al. demonstrated loss of phenotypic tetracycline resistance over time with loss of a plasmid carrying tet(A). Collectively, these analyses further validate BugSeq’s outbreak analysis, plasmid profiling and antimicrobial resistance prediction.

Figure 1 from Ritchie et al. Cluster isolates demonstrate highly similar strain types, plasmid profiles and antimicrobial resistance.

Agnostic Sequencing for Detection of Viral Pathogens¶

Agnostic Sequencing for Detection of Viral Pathogens from our team and collaborators on a BARDA-supported project, presents a broad overview of metagenomic sequencing for detection of viruses. Viruses have unique characteristics, including RNA, short and segmented genomes; rapid mutation rates; and complex biology; these characteristics require unique sample preparation and analysis. Like SARS-CoV-2, RNA viruses are the most likely class of agent to cause the next pandemic - and we need to be prepared. Our team and other collaborators have previously written how routine agnostic testing has the potential to detect and avert the next pandemic. While bioinformatics has traditionally been one of the largest barriers for routine implementation of agnostic sequencing, BugSeq’s platform has catalyzed faster and wider adoption.

Table 1 from Gauthier et al. Challenges to translation of agnostic sequencing for routine viral diagnosis and potential solutions to each challenge. BugSeq is pioneering the bottom half of solutions to move routine clinical metagenomics closer to reality.

Oxford nanopore next generation sequencing in a front-line clinical microbiology laboratory without on-site bioinformaticians¶

Oxford nanopore next generation sequencing in a front-line clinical microbiology laboratory without on-site bioinformaticians from New Zealand’s Wellington Southern Community Laboratories and ESR Consortium, applied next generation sequencing for routine and rapid infection control. The lab had “no experience with NGS, nor molecular testing of hospital-associated bacteria”, yet developed a robust program to sequence and strain-type organisms onsite. The authors compared BugSeq with manual analysis and found “excellent concordance” between BugSeq and the manual analysis, “with over 60 organisms showing concordant MLSTs on an initial validation”.

The work by Bloomfield et al. highlights the value of real-time, routine genomic surveillance for infection control along with rapid and simple bioinformatics:

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“We can report that a significant outbreak of ST2 C. difficile was detected on a hospital ward, which would not have been detected otherwise, and has since been contained via enhanced cleaning”