Infections caused by foodborne bacterial pathogens continue to be a major public health issue around the world. During the past decade, pulsed-field gel electrophoresis (PFGE) has become the gold standard for molecular subtyping and source tracking of most foodborne bacteria. Owing to problems inherent in PFGE technology, new methods have been developed focusing on DNA sequence-based subtyping. This review discusses the feasibility of using multilocus sequence typing, multiple-locus variable-number tandem repeat analysis, single nucleotide polymorphisms, microarrays, whole genome sequencing and mass spectrometry for subtyping foodborne bacterial pathogens.

The PulseNet USA subtyping network recently established a standardized protocol for multiple-locus variable-number tandem repeat analysis (MLVA) to characterize Shiga toxin–producing Escherichia coli O157. To enable data comparisons from different laboratories in the same database, reproducibility and high quality of the data must be ensured. The aim of this study was to test the robustness and reproducibility of the proposed standardized protocol by subjecting it to a multilaboratory validation process and to address any discrepancies that may have arisen from the study. A set of 50 strains was tested in 10 PulseNet participating laboratories that used capillary electrophoresis instruments from two manufacturers. Six out of the 10 laboratories were able to generate correct MLVA types for 46 (92%) or more strains. The discrepancies in MLVA type assignment were caused mainly by difficulties in optimizing polymerase chain reactions that were attributed to technical inexperience of the staff and suboptimal quality of reagents and instrumentation. It was concluded that proper training of staff must be an integral part of technology transfer. The interlaboratory reproducibility of fragment sizing was excellent when the same capillary electrophoresis platform was used. However, sizing discrepancies of up to six base pairs for the same fragment were detected between the two platforms. These discrepancies were attributed to different dye and polymer chemistries employed by the manufacturers. A novel software script was developed to assign alleles based on two platform-specific (Beckman Coulter CEQ™8000 and Applied Biosystems Genetic Analyzer 3130xl) look-up tables containing fragment size ranges for all alleles. The new allele assignment method was validated at the PulseNet central laboratory using a diverse set of 502 Shiga toxin–producing Escherichia coli O157 isolates. The validation confirmed that the script reliably assigned the same allele for the same fragment regardless of the platform used to size the fragment.

Whole genome sequencing is replacing traditional laboratory surveillance methods as the primary tool to track and characterize clusters and outbreaks of the foodborne and zoonotic pathogen Salmonella enterica (S. enterica). In this study, 438 S. enterica isolates representing 35 serovars and 13 broad vehicle categories from one hundred epidemiologically confirmed outbreaks were evaluated for genetic variation to develop epidemiologically relevant interpretation guidelines for Salmonella disease cluster detection. The Illumina sequences were analyzed by core genome multi-locus sequence typing (cgMLST) and screened for antimicrobial resistance (AR) determinants and plasmids. Ninety-three of the one hundred outbreaks exhibited a close allele range (less than 10 allele differences with a subset closer than 5). The remaining seven outbreaks showed increased variation, of which three were considered polyclonal. A total of 16 and 28 outbreaks, respectively, showed variations in the AR and plasmid profiles. The serovars Newport and I 4,[5],12:i:-, as well as the zoonotic and poultry product vehicles, were overrepresented among the outbreaks, showing increased variation. A close allele range in cgMLST profiles can be considered a reliable proxy for epidemiological relatedness for the vast majority of S. enterica outbreak investigations. Variations associated with mobile elements happen relatively frequently during outbreaks and could be reflective of changing selective pressures.

Four enzymatic DNA library preparation kits were compared for sequencing Shiga toxin-producing E. coli. All kits produced high quality sequence data which performed equally well in the downstream analyses for surveillance and outbreak detection. Important differences were noted in the workflow user-friendliness and per sample cost.

Enzymatic library preparation kits are increasingly used for bacterial whole genome sequencing. While they offer a rapid workflow, the transposases used in the kits are recognized to be somewhat biased. The aim of this study was to optimize and validate a protocol for the Illumina DNA Prep kit (formerly Nextera DNA Flex) for sequencing enteric pathogens and compare its performance against the Nextera XT kit. One hundred forty-three strains of Campylobacter , Escherichia , Listeria , Salmonella , Shigella , and Vibrio were prepared with both methods and sequenced on the Illumina MiSeq using 300 and/or 500 cycle chemistries. Sequences were compared using core genome multilocus sequence typing (cgMLST), 7-gene multilocus sequence typing (MLST), and detection of markers encoding serotype, virulence, and antimicrobial resistance. Sequences for one Escherichia strain were downsampled to determine the minimum coverage required for the analyses. While organism-specific differences were observed, the Prep libraries generated longer average read lengths and less fragmented assemblies compared to the XT libraries. In downstream analysis, the most notable difference between the kits was observed for Escherichia , particularly for the 300 cycle sequences. The O group was not predicted in 32% and 4% of XT sequences when using blast and kmer algorithms, respectively, while the O group was predicted from all Prep sequences regardless of the algorithm. In addition, the ehxA gene was not detected in 6% of XT sequences and 34% were missing one or more of the type III secretion systems and/or plasmid-associated genes, which were detected in the Prep sequences. The coverage downsampling revealed that acceptable assembly quality and allele detection was achieved at 30 × coverage with the Prep libraries, whereas 40–50 × coverage was required for the XT libraries. The better performance of the Prep libraries was attributed to more even coverage, particularly in genome regions low in GC content.