Impact of wet-lab protocols on quality of whole-genome short-read sequences from foodborne microbial pathogens.

For successful elucidation of a food-borne infection chain, the availability of high-quality sequencing data from suspected microbial contaminants is a prerequisite. Commonly, those investigations are a joint effort undertaken by different laboratories and institutes. To analyze the extent of variability introduced by differing wet-lab procedures on the quality of the sequence data we conducted an interlaboratory study, involving four bacterial pathogens, which account for the majority of food-related bacterial infections: Campylobacter spp., Shiga toxin-producing Escherichia coli, Listeria monocytogenes, and Salmonella enterica. The participants, ranging from German federal research institutes, federal state laboratories to universities and companies, were asked to follow their routine in-house protocols for short-read sequencing of 10 cultures and one isolated bacterial DNA per species. Sequence and assembly quality were then analyzed centrally. Variations within isolate samples were detected with SNP and cgMLST calling. Overall, we found that the quality of Illumina raw sequence data was high with little overall variability, with one exception, attributed to a specific library preparation kit. The variability of Ion Torrent data was higher, independent of the investigated species. For cgMLST and SNP analysis results, we found that technological sequencing artefacts could be reduced by the use of filters, and that SNP analysis was more suited than cgMLST to compare data of different contributors. Regarding the four species, a minority of Campylobacter isolate data showed the in comparison highest divergence with regard to sequence type and cgMLST analysis. We additionally compared the assembler SPAdes and SKESA for their performance on the Illumina data sets of the different species and library preparation methods and found overall similar assembly quality metrics and cgMLST statistics.

Large Multicountry Outbreak of Invasive Listeriosis by a Listeria monocytogenes ST394 Clone Linked to Smoked Rainbow Trout, 2020 to 2021.

Whole-genome sequencing (WGS) has revolutionized surveillance of infectious diseases. Disease outbreaks can now be detected with high precision, and correct attribution of infection sources has been improved. Listeriosis, caused by the bacterium Listeria monocytogenes, is a foodborne disease with a high case fatality rate and a large proportion of outbreak-related cases. Timely recognition of listeriosis outbreaks and precise allocation of food sources are important to prevent further infections and to promote public health. We report the WGS-based identification of a large multinational listeriosis outbreak with 55 cases that affected Germany, Austria, Denmark, and Switzerland during 2020 and 2021. Clinical isolates formed a highly clonal cluster (called Ny9) based on core genome multilocus sequence typing (cgMLST). Routine and ad hoc investigations of food samples identified L. monocytogenes isolates from smoked rainbow trout filets from a Danish producer grouping with the Ny9 cluster. Patient interviews confirmed consumption of rainbow trout as the most likely infection source. The Ny9 cluster was caused by a MLST sequence type (ST) ST394 clone belonging to molecular serogroup IIa, forming a distinct clade within molecular serogroup IIa strains. Analysis of the Ny9 genome revealed clpY, dgcB, and recQ inactivating mutations, but phenotypic characterization of several virulence-associated traits of a representative Ny9 isolate showed that the outbreak strain had the same pathogenic potential as other serogroup IIa strains. Our report demonstrates that international food trade can cause multicountry outbreaks that necessitate cross-border outbreak collaboration. It also corroborates the relevance of ready-to-eat smoked fish products as causes for listeriosis. IMPORTANCE Listeriosis is a severe infectious disease in humans and characterized by an exceptionally high case fatality rate. The disease is transmitted through consumption of food contaminated by the bacterium Listeria monocytogenes. Outbreaks of listeriosis often occur but can be recognized and stopped through implementation of whole-genome sequencing-based pathogen surveillance systems. We here describe the detection and management of a large listeriosis outbreak in Germany and three neighboring countries. This outbreak was caused by rainbow trout filet, which was contaminated by a L. monocytogenes clone belonging to sequence type ST394. This work further expands our knowledge on the genetic diversity and transmission routes of an important foodborne pathogen.

Genetic Characterization of Listeria from Food of Non-Animal Origin Products and from Producing and Processing Companies in Bavaria, Germany.

Reported cases of listeriosis from food of non-animal origin (FNAO) are increasing. In order to assess the risk of exposure to Listeria monocytogenes from FNAO, the genetic characterization of the pathogen in FNAO products and in primary production and processing plants needs to be investigated. For this, 123 samples of fresh and frozen soft fruit and 407 samples of 39 plants in Bavaria, Germany that produce and process FNAO were investigated for Listeria contamination. As a result, 64 Listeria spp. isolates were detected using ISO 11290-1:2017. Environmental swabs and water and food samples were investigated. L. seeligeri (36/64, 56.25%) was the most frequently identified species, followed by L. monocytogenes (8/64, 12.50%), L. innocua (8/64, 12.50%), L. ivanovii (6/64, 9.38%), L. newyorkensis (5/64, 7.81%), and L. grayi (1/64, 1.56%). Those isolates were subsequently sequenced by whole-genome sequencing and subjected to pangenome analysis to retrieve data on the genotype, serotype, antimicrobial resistance (AMR), and virulence markers. Eight out of sixty-four Listeria spp. isolates were identified as L. monocytogenes. The serogroup analysis detected that 62.5% of the L. monocytogenes isolates belonged to serogroup IIa (1/2a and 3a) and 37.5% to serogroup IVb (4b, 4d, and 4e). Furthermore, the MLST (multilocus sequence typing) analysis of the eight detected L. monocytogenes isolates identified seven different sequence types (STs) and clonal complexes (CCs), i.e., ST1/CC1, ST2/CC2, ST6/CC6, ST7/CC7, ST21/CC21, ST504/CC475, and ST1413/CC739. The core genome MLST analysis also showed high allelic differences and suggests plant-specific isolates. Regarding the AMR, we detected phenotypic resistance against benzylpenicillin, fosfomycin, and moxifloxacin in all eight L. monocytogenes isolates. Moreover, virulence factors, such as prfA, hly, plcA, plcB, hpt, actA, inlA, inlB, and mpl, were identified in pathogenic and nonpathogenic Listeria species. The significance of L. monocytogenes in FNAO is growing and should receive increasing levels of attention.

Whole-Genome Sequence Comparisons of Listeria monocytogenes Isolated from Meat and Fish Reveal High Inter- and Intra-Sample Diversity.

Interpretation of whole-genome sequencing (WGS) data for foodborne outbreak investigations is complex, as the genetic diversity within processing plants and transmission events need to be considered. In this study, we analyzed 92 food-associated Listeria monocytogenes isolates by WGS-based methods. We aimed to examine the genetic diversity within meat and fish production chains and to assess the applicability of suggested thresholds for clustering of potentially related isolates. Therefore, meat-associated isolates originating from the same samples or processing plants as well as fish-associated isolates were analyzed as distinct sets. In silico serogrouping, multilocus sequence typing (MLST), core genome MLST (cgMLST), and pangenome analysis were combined with screenings for prophages and genetic traits. Isolates of the same subtypes (cgMLST types (CTs) or MLST sequence types (STs)) were additionally compared by SNP calling. This revealed the occurrence of more than one CT within all three investigated plants and within two samples. Analysis of the fish set resulted in predominant assignment of isolates from pangasius catfish and salmon to ST2 and ST121, respectively, potentially indicating persistence within the respective production chains. The approach not only allowed the detection of distinct subtypes but also the determination of differences between closely related isolates, which need to be considered when interpreting WGS data for surveillance.

German-Wide Interlaboratory Study Compares Consistency, Accuracy and Reproducibility of Whole-Genome Short Read Sequencing.

We compared the consistency, accuracy and reproducibility of next-generation short read sequencing between ten laboratories involved in food safety (research institutes, state laboratories, universities and companies) from Germany and Austria. Participants were asked to sequence six DNA samples of three bacterial species (Campylobacter jejuni, Listeria monocytogenes and Salmonella enterica) in duplicate, according to their routine in-house sequencing protocol. Four different types of Illumina sequencing platforms (MiSeq, NextSeq, iSeq, NovaSeq) and one Ion Torrent sequencing instrument (S5) were involved in the study. Sequence quality parameters were determined for all data sets and centrally compared between laboratories. SNP and cgMLST calling were performed to assess the reproducibility of sequence data collected for individual samples. Overall, we found Illumina short read data to be more accurate (higher base calling accuracy, fewer miss-assemblies) and consistent (little variability between independent sequencing runs within a laboratory) than Ion Torrent sequence data, with little variation between the different Illumina instruments. Two laboratories with Illumina instruments submitted sequence data with lower quality, probably due to the use of a library preparation kit, which shows difficulty in sequencing low GC genome regions. Differences in data quality were more evident after assembling short reads into genome assemblies, with Ion Torrent assemblies featuring a great number of allele differences to Illumina assemblies. Clonality of samples was confirmed through SNP calling, which proved to be a more suitable method for an integrated data analysis of Illumina and Ion Torrent data sets in this study.