Cereulide production capacities and genetic properties of 31 emetic Bacillus cereus group strains.

The highly potent toxin cereulide is a frequent cause of foodborne intoxications. This extremely resistant toxin is produced by Bacillus cereus group strains carrying the plasmid encoded cesHPTABCD gene cluster. It is known that the capacities to produce cereulide vary greatly between different strains but the genetic background of these variations is not clear. In this study, cereulide production capacities were associated with genetic characteristics. For this, cereulide levels in cultures of 31 strains were determined after incubation in tryptic soy broth for 24 h at 24 °C, 30 °C and 37 °C. Whole genome sequencing based data were used for an in-depth characterization of gene sequences related to cereulide production. The taxonomy, population structure and phylogenetic relationships of the strains were evaluated based on average nucleotide identity, multi-locus sequence typing (MLST), core genome MLST and single nucleotide polymorphism analyses. Despite a limited strain number, the approach of a genome wide association study (GWAS) was tested to link genetic variation with cereulide quantities. Our study confirms strain-dependent differences in cereulide production. For most strains, these differences were not explainable by sequence variations in the cesHPTABCD gene cluster or the regulatory genes abrB, spo0A, codY and pagRBc. Likewise, the population structure and phylogeny of the tested strains did not comprehensively reflect the cereulide production capacities. GWAS yielded first hints for associated proteins, while their possible effect on cereulide synthesis remains to be further investigated.

From farm to fork: Spread of a multidrug resistant Salmonella Infantis clone encoding blaCTX-M-1 on pESI-like plasmids in Central Italy.

Salmonella enterica subsp. enterica serovar Infantis (S. Infantis) is one of the "top five Salmonella serovars" of clinical significance in the European Union (EU). Antimicrobial resistant and extended spectrum ß-lactamase (ESBL) AmpC-producing S. Infantis have been described in food production systems and human clinical samples in Italy. Recently, an increase of MDR S. Infantis carrying blaCTX-M genes involved in 3rd generation cephalosporin resistance was noticed in the EU, including Italy, mainly due to the spread of S. Infantis harboring a pESI-like plasmid. The aim of this study was to investigate the occurrence of the S. Infantis pESI-like plasmid among antibiotic resistant S. Infantis strains isolated at different points of the food chain, and to provide a phylogenetic analysis to gain further insight on their transmission pathways from 'farm to fork'. MDR S. Infantis strains (n. 35) isolated from 2016 to 2021 at different stages of the food chain (animals, food, food-related environments, and humans) were investigated with in depth molecular characterization using real-time PCR, S1 nuclease pulsed-field gel electrophoresis (S1-PFGE) and whole genome sequencing (WGS). Our study reported the occurrence of S. Infantis strains harboring pESI-like plasmids, carrying blaCTX-M-1 genes, in Central Italy, at different sampling points along the food chain. Results confirmed the presence of a plasmid with a molecular size around 224-310 kb, thus consistent with the pESI-like, in 97 % of the 35 samples investigated. Two variants of S. Infantis pESI-like IncFIB(K)_1_Kpn3 were detected, one associated with the European clone carrying blaCTX-M-1 (21 isolates) and the other associated with U.S. isolates carrying blaCTX-M-65 (2 isolates, pESI-like U.S. variant). The majority was resistant to 3rd generation cephalosporins but none of the strains tested positive for the carbapenemase encoding genes. A total of 118 virulence genes were identified in isolates harboring the pESI-like plasmid. cgMLST and SNP-based analysis revealed the presence of one main cluster, composed by strains isolated from the environment, animals, food and humans. The results of this investigation underline the importance of phylogenetic studies to monitor and understand pathogen and AMR spread in a One Health approach.

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.

[Assessment of available and currently applied typing methods including genome-based methods for zoonotic pathogens with a focus on Salmonella enterica]. / Bestandsaufnahme der verfügbaren und aktuell eingesetzten Typisierungsmethoden einschließlich genombasierter Verfahren von Zoonoseerregern am Beispiel von Salmonella enterica.

BACKGROUND: In recent years, whole genome sequencing (WGS) in combination with bioinformatic analyses has become state of the art in evaluating the pathogenicity/resistance potential and relatedness of bacteria. WGS analysis thus represents a central tool in the investigation of the resistance and virulence potential of pathogens, as well as their dissemination via outbreak clusters and transmission chains within the framework of molecular epidemiology. In order to gain an overview of the available genotypic and phenotypic methods used for pathogen typing of Salmonella and Shiga toxin-producing and enterohemorrhagic Escherichia coli (STEC/EHEC) in Germany at state and federal level, along with the availability of WGS-based typing and corresponding analytical methods, a survey of laboratories was conducted. METHODS: An electronic survey of laboratories working for public health protection and consumer health protection was conducted from February to June 2020. RESULTS AND CONCLUSION: The results of the survey showed that many of the participating laboratories provide a wide range of phenotypic and molecular methods. Molecular typing is most commonly used for species identification of Salmonella. In many cases, WGS-based methods have already been established at federal and state institutions or are in the process of being established. The Illumina sequencing technology is the most widely used technology. The survey confirms the importance of molecular biology and whole genome typing technologies for laboratories in the diagnosis of bacterial zoonotic pathogens.

What WGS Reveals about Salmonella enterica subsp. enterica in Wildlife in Germany.

The aim of this study was to gain an overview of the genetic diversity of Salmonella found in wildlife in Germany. We were particularly interested in exploring whether wildlife acts as a reservoir of certain serovars/subtypes or antimicrobial resistance (AMR) genes. Moreover, we wanted to explore the potential of Salmonella in spreading from wildlife to livestock and humans. To answer these questions, we sequenced 260 Salmonella enterica subsp. enterica isolates sampled between 2002 and 2020 from wildlife across Germany, using short-read whole genome sequencing. We found, consistent with previous findings, that some Salmonella sequence types are associated with certain animal species, such as S. Choleraesuis ST145 with wild boar and S. Enteritidis ST183 with hedgehogs. Antibiotic resistance was detected in 14.2% of all isolates, with resistance against important WATCH group antibiotics present in a small number of isolates. We further found that wildlife isolates do not form separate phylogenetic clusters distant to isolates from domestic animals and foodstuff, thus indicating frequent transmission events between these reservoirs. Overall, our study shows that Salmonella in German wildlife are diverse, with a low AMR burden and close links to Salmonella populations of farm and food-production environments.

Decentralized Investigation of Bacterial Outbreaks Based on Hashed cgMLST.

Whole-genome sequencing (WGS)-based outbreak investigation has proven to be a valuable method for the surveillance of bacterial pathogens. Its utility has been successfully demonstrated using both gene-by-gene (cgMLST or wgMLST) and single-nucleotide polymorphism (SNP)-based approaches. Among the obstacles of implementing a WGS-based routine surveillance is the need for an exchange of large volumes of sequencing data, as well as a widespread reluctance to share sequence and metadata in public repositories, together with a lacking standardization of suitable bioinformatic tools and workflows. To address these issues, we present chewieSnake, an intuitive and simple-to-use cgMLST workflow. ChewieSnake builds on the allele calling software chewBBACA and extends it by the concept of allele hashing. The resulting hashed allele profiles can be readily compared between laboratories without the need of a central allele nomenclature. The workflow fully automates the computation of the allele distance matrix, cluster membership, and phylogeny and summarizes all important findings in an interactive HTML report. Furthermore, chewieSnake can join allele profiles generated at different laboratories and identify shared clusters, including a stable and intercommunicable cluster nomenclature, thus facilitating a joint outbreak investigation. We demonstrate the feasibility of the proposed approach with a thorough method comparison using publically available sequencing data for Salmonella enterica. However, chewieSnake is readily applicable to all bacterial taxa, provided that a suitable cgMLST scheme is available. The workflow is freely available as an open-source tool and can be easily installed via conda or docker.

Species-Specific Quality Control, Assembly and Contamination Detection in Microbial Isolate Sequences with AQUAMIS.

Sequencing of whole microbial genomes has become a standard procedure for cluster detection, source tracking, outbreak investigation and surveillance of many microorganisms. An increasing number of laboratories are currently in a transition phase from classical methods towards next generation sequencing, generating unprecedented amounts of data. Since the precision of downstream analyses depends significantly on the quality of raw data generated on the sequencing instrument, a comprehensive, meaningful primary quality control is indispensable. Here, we present AQUAMIS, a Snakemake workflow for an extensive quality control and assembly of raw Illumina sequencing data, allowing laboratories to automatize the initial analysis of their microbial whole-genome sequencing data. AQUAMIS performs all steps of primary sequence analysis, consisting of read trimming, read quality control (QC), taxonomic classification, de-novo assembly, reference identification, assembly QC and contamination detection, both on the read and assembly level. The results are visualized in an interactive HTML report including species-specific QC thresholds, allowing non-bioinformaticians to assess the quality of sequencing experiments at a glance. All results are also available as a standard-compliant JSON file, facilitating easy downstream analyses and data exchange. We have applied AQUAMIS to analyze ~13,000 microbial isolates as well as ~1000 in-silico contaminated datasets, proving the workflow's ability to perform in high throughput routine sequencing environments and reliably predict contaminations. We found that intergenus and intragenus contaminations can be detected most accurately using a combination of different QC metrics available within AQUAMIS.

Toward an Integrated Genome-Based Surveillance of Salmonella enterica in Germany.

Despite extensive monitoring programs and preventative measures, Salmonella spp. continue to cause tens of thousands human infections per year, as well as many regional and international food-borne outbreaks, that are of great importance for public health and cause significant socio-economic costs. In Germany, salmonellosis is the second most common cause of bacterial diarrhea in humans and is associated with high hospitalization rates. Whole-genome sequencing (WGS) combined with data analysis is a high throughput technology with an unprecedented discriminatory power, which is particularly well suited for targeted pathogen monitoring, rapid cluster detection and assignment of possible infection sources. However, an effective implementation of WGS methods for large-scale microbial pathogen detection and surveillance has been hampered by the lack of standardized methods, uniform quality criteria and strategies for data sharing, all of which are essential for a successful interpretation of sequencing data from different sources. To overcome these challenges, the national GenoSalmSurv project aims to establish a working model for an integrated genome-based surveillance system of Salmonella spp. in Germany, based on a decentralized data analysis. Backbone of the model is the harmonization of laboratory procedures and sequencing protocols, the implementation of open-source bioinformatics tools for data analysis at each institution and the establishment of routine practices for cross-sectoral data sharing for a uniform result interpretation. With this model, we present a working solution for cross-sector interpretation of sequencing data from different sources (such as human, veterinarian, food, feed and environmental) and outline how a decentralized data analysis can contribute to a uniform cluster detection and facilitate outbreak investigations.

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.

Complete Genome Sequence of Arcanobacterium sp. Strain 2701, Isolated from a Harbor Seal.

Arcanobacterium spp. are Gram-positive bacteria which can be found in a wide range of hosts and can be associated with disease in humans and animals. Here, we announce the complete genome sequence of Arcanobacterium sp. strain 2701, isolated from a harbor seal from the North Sea.

Complete Genome Sequence of Salmonella enterica subsp. diarizonae Serovar 61:k:1,5,(7) Strain 14-SA00836-0, Isolated from Human Urine.

Salmonella enterica subsp. diarizonae serovar 61:k:1,5,(7) is commonly associated with sheep. Occasionally, the serovar has been found to also infect humans. Here, we report the complete genome sequence of strain 14-SA00836-0, isolated from human urine. To our knowledge, this is the first reported complete genome sequence of this serovar isolated from a human clinical sample.

Typing methods based on whole genome sequencing data.

Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.

Performance and Accuracy of Four Open-Source Tools for In Silico Serotyping of Salmonella spp. Based on Whole-Genome Short-Read Sequencing Data.

We compared the performance of four open-source in silico Salmonella typing tools (SeqSero, SeqSero2, Salmonella In Silico Typing Resource [SISTR], and Metric Oriented Sequence Typer [MOST]) to assess their potential for replacing laboratory serological testing with serovar predictions from whole-genome sequencing data. We conducted a retrospective analysis of 1,624 Salmonella isolates of 72 serovars submitted to the German National Salmonella Reference Laboratory between 1999 and 2019. All isolates are derived from animal and foodstuff origins. We conducted Illumina short-read sequencing and compared the in silico serovar prediction results with the results of routine laboratory serotyping. We found the best-performing in silico serovar prediction tool to be SISTR, with 94% correctly typed isolates, followed by SeqSero2 (87%), SeqSero (81%), and MOST (79%). Furthermore, we found that mapping-based tools like SeqSero and SeqSero2 (allele mode) were more reliable for the prediction of monophasic variants, while sequence type and cluster-based methods like MOST and SISTR (core-genome multilocus sequence type [cgMLST]), showed greater resilience when confronted with GC-biased sequencing data. We showed that the choice of library preparation kit could substantially affect O antigen detection, due to the low GC content of the wzx and wzy genes. Although the accuracy of computational serovar predictions is still not quite on par with traditional serotyping by Salmonella reference laboratories, the command-line tools investigated in this study perform a rapid, efficient, inexpensive, and reproducible analysis, which can be integrated into in-house characterization pipelines. Based on our results, we find SISTR most suitable for automated, routine serotyping for public health surveillance of SalmonellaIMPORTANCESalmonella spp. are important foodborne pathogens. To reduce the number of infected patients, it is essential to understand which subtypes of the bacteria cause disease outbreaks. Traditionally, characterization of Salmonella requires serological testing, a laboratory method by which Salmonella isolates can be classified into over 2,600 distinct subtypes, called serovars. Due to recent advances in whole-genome sequencing, many tools have been developed to replace traditional testing methods with computational analysis of genome sequences. It is crucial to validate that these tools, many already in use for routine surveillance, deliver accurate and reliable serovar information. In this study, we set out to compare which of the currently available open-source command-line tools is most suitable to replace serological testing. A thorough evaluation of the differing computational approaches is highly important to ensure the backward compatibility of serotyping data and to maintain comparability between laboratories.

First complete genome sequence and comparative analysis of Salmonella enterica subsp. diarizonae serovar 61:k:1,5,(7) indicates host adaptation traits to sheep.

BACKGROUND: The Salmonella enterica subsp. diarizonae serovar 61:k:1,5,(7) (SASd) has been found to be host-adapted to sheep, with a high prevalence in sheep herds worldwide. Infections are usually sub-clinical, however the serovar has the potential to cause diarrhea, abortions and chronic proliferative rhinitis. Although occurrence and significance of SASd infections in sheep have been extensively studied, the genetic mechanism underlying this unusual host-adaptation have remained unknown, due to a lack of (a) available high-quality genome sequence(s). RESULTS: We utilized Nanopore and Illumina sequencing technologies to generate a de novo assembly of the 4.88-Mbp complete genome sequence of the SASd strain 16-SA00356, isolated from the organs of a deceased sheep in 2016. We annotated and analyzed the genome sequence with the aim to gain a deeper understanding of the genome characteristics associated with its pathogenicity and host adaptation to sheep. Overall, we found a number of interesting genomic features such as several prophage regions, a VirB4/D4 plasmid and novel genomic islands. By comparing the genome of 16-SA00356 to other S. enterica serovars we found that SASd features an increased number of pseudogenes as well as a high level of genomic rearrangements, both known indicators of host-adaptation. CONCLUSIONS: With this sequence, we provide the first complete and closed genome sequence of a SASd strain. With this study, we provide an important basis for an understanding of the genetic mechanism that underlie pathogenicity and host adaptation of SASd to sheep.