A Faster Way to Characterize Pathogenic Bacteria

Bacterial typing is considered the “forensics” of bacterial identification, providing a specific molecular fingerprint of potentially lethal microbes. Typing can identify different types of bacteria within the same species and helps us understand the source and transmission route of harmful bacteria. It can also determine bacterial antibiotic resistance and monitor genes that encode for vaccine antigens. But while speed, affordability and accuracy are of the essence, traditional typing techniques such as MLST (multi-locus sequence typing)and PFGE (pulse field gel electrophoresis) lack sufficient strain resolving power or are labor-intensive and difficult to standardize across different laboratories.

Hospital and public health microbiology labs of the future may instead rely on rapid typing based on whole-genome sequencing (WGS) called core-genome multi-locus sequence typing (MLST+). Compared with traditional MLST that involves sequencing of 5-7 common genes, MLST+ leverages the entire genome and uses hundreds to thousands of genes for bacterial typing. Additionally, MLST+, instead of using a SNP-based analysis, employs a gene-by-gene (allelic) approach, that better accounts for recombination events and the genetic diversity of many bacterial species. Research using the Ion PGM™ System can conduct rapid WGS, and when combined with the typing of microbes using Ridom® SeqSphere+ Software program, results in an MLST+ method that may in the future help facilitate global bacterial surveillance and the early-warning outbreak detection needed for an increasingly connected world.

Using Neisseria meningitidis, one of the agents responsible for bacterial meningitis, researchers examined three bacterial strains using the Ion PGM™ System and Ridom® SeqSphere+ Software. The MLST+ sequence typing consisted of 1,241 targets, which improved discrimination among strains compared to traditional typing methods using 26 targets (Figure 1). Traditional Sanger sequencing-based typing methods showed just one allelic difference among the three strains, while sequencing information from MLST+ resulted in improved strain resolution with separation by 12 alleles between the first and second strain, and 22 alleles between the first and third strain.

What’s more, bacterial strain typing research with the Ion PGM™ and Ridon® SeqSphere+ analysis was carried out in less than 24 hours. In the future, it may be possible to shift bacterial forensics from a retrospective, historical investigation to real-time outbreak identification.

You can learn more about this and other bacterial typing studies from our Bacterial Research Typing Application Note.

Figure 1. Minimum spanning trees for sequence targets obtained from de novo assembled WGS data of three Neisseria meningitidis community outbreak strains. (A) Sequence information from 26 targets (comprising MLST/eMLST/AST/4CMenB/AR) resulted in a single allelic discrimination between strains DE9622 and DE9686/DE9938, with strains DE9686 and DE9938 indistinguishable. (B) Sequence information from 1,101 targets better resolves the three strains, with DE9686 separated by 13 and 22 alleles from DE9938 and DE9622, respectively.