German coasts harbor non-O1/non-O139 Vibrio cholerae with clinical virulence gene profiles.

Non-O1/non-O139 Vibrio cholerae (NOVC) are ubiquitous in aquatic ecosystems. In rare cases, they can cause intestinal and extra-intestinal infections in human. This ability is associated with various virulence factors. The presence of NOVC in German North Sea and Baltic Sea was observed in previous studies. However, data on virulence characteristics are still scarce. Therefore, this work aimed to investigating the virulence potential of NOVC isolated in these two regions. In total, 31 NOVC strains were collected and subjected to whole genome sequencing. In silico analysis of the pathogenic potential was performed based on the detection of genes involved in colonization and virulence. Phenotypic assays, including biofilm formation, mobility and human serum resistance assays were applied for validation. Associated toxin genes (hlyA, rtxA, chxA and stn), pathogenicity islands (Vibrio pathogenicity island 2 (VPI-II) and Vibrio seventh pathogenicity island 2 (VSP-II)) and secretion systems (Type II, III and VI secretion system) were observed. A maximum likelihood analysis from shared core genes revealed a close relationship between clinical NOVCs published in NCBI and environmental strains from this study. NOVC strains are more mobile at 37 °C than at 25 °C, and 68% of the NOVC strains could form strong biofilms at both temperatures. All tested strains were able to lyse erythrocytes from both human and sheep blood. Additionally, one strain could survive up to 60% and seven strains up to 40% human serum at 37 °C. Overall, the genetic virulence profile as well as the phenotypic virulence characteristics of the investigated NOVC from the German North Sea and Baltic Sea suggest potential human pathogenicity.

Identification of knowledge gaps in whole-genome sequence analysis of multi-resistant thermotolerant Campylobacter spp.

BACKGROUND: Campylobacter spp. is the most frequent cause of bacterial food-borne gastroenteritis and a high priority antibiotic resistant bacterium according to the World Health Organization (WHO). European monitoring of thermotolerant Campylobacter spp. does not reflect the global burden of resistances already circulating within the bacterial population worldwide. METHODS: We systematically compared whole genome sequencing with comprehensive phenotypic antimicrobial susceptibility, analyzing 494 thermotolerant Campylobacter poultry isolates from Vietnam and Germany. Any discrepancy was checked by repeating the wet lab and improving the dry lab part. Selected isolates were additionally analyzed via long-read Oxford Nanopore technology, leading to closed chromosomes and plasmids. RESULTS: Overall, 22 different resistance genes and gene variants (e. g. erm(B), aph(3')-IIIa, aph(2'')-If, catA, lnu(C), blaOXA, sat4) and point mutations in three distinct genes (gyrA, 23S rRNA, rpsL) associated with AMR were present in the Campylobacter isolates. Two AMR genes were missing in the database and one falsely associated with resistance. Bioinformatic analysis based on short-read data partly failed to identify tet(O) and aadE, when the genes were present as duplicate or homologous gene variants. Intriguingly, isolates also contained different determinants, redundantly conferring resistance to chloramphenicol, gentamicin, kanamycin, lincomycin and streptomycin. We found a novel tet(W) in tetracycline sensitive strains, harboring point mutations. Furthermore, analysis based on assemblies from short-read data was impaired to identify full length phase variable aad9, due to variations of the poly-C tract within the gene. The genetic determinant responsible for gentamicin resistance of one isolate from Germany could not be identified. GyrT86I, presenting the main determinant for (fluoro-)quinolone resistance led to a rare atypical phenotype of ciprofloxacin resistance but nalidixic acid sensitivity. Long-read sequencing predicted AMR genes were mainly located on the chromosome, and rarely on plasmids. Predictions from long- and short-read sequencing, respectively, often differed. AMR genes were often organized in multidrug resistance islands (MDRI) and partially located in proximity to transposase genes, suggesting main mobilization of resistance determinants is via natural transformation and transposition in Campylobacter. CONCLUSIONS: The results of this study suggest that there is frequent resistance gene duplication, mosaicism, and mutation leading to gene variation and truncation in Campylobacter strains that have not been reported in previous studies and are missing from databases. Furthermore, there is a need for deciphering yet unknown resistance mechanisms and resistance spread in thermotolerant Campylobacter spp. that may pose a challenge to global food safety.

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.

Genetic and Phenotypic Virulence Potential of Non-O1/Non-O139 Vibrio cholerae Isolated from German Retail Seafood.

Non-O1 and non-O139 Vibrio cholerae (NOVC) can cause gastrointestinal infections in humans. Contaminated food, especially seafood, is an important source of human infections. In this study, the virulence potential of 63 NOVC strains isolated from retail seafood were characterized at the genotypic and phenotypic levels. Although no strain encoded the cholera toxin (CTX) and the toxin-coregulated pilus (TCP), several virulence factors, including the HlyA hemolysin, the cholix toxin ChxA, the heat-stable enterotoxin Stn, and genes coding for the type 3 and type 6 secretion systems, were detected. All strains showed hemolytic activity against human and sheep erythrocytes: 90% (n = 57) formed a strong biofilm, 52% (n = 33) were highly motile at 37 °C, and only 8% (n = 5) and 14% (n = 9) could resist ≥60% and ≥40% human serum, respectively. Biofilm formation and toxin regulation genes were also detected. cgMLST analysis demonstrated that NOVC strains from seafood cluster with clinical NOVC strains. Antimicrobial susceptibility testing (AST) results in the identification of five strains that developed non-wildtype phenotypes (medium and resistant) against the substances of the classes of beta-lactams (including penicillin, carbapenem, and cephalosporin), polymyxins, and sulphonamides. The phenotypic resistance pattern could be partially attributed to the acquired resistance determinants identified via in silico analysis. Our results showed differences in the virulence potential of the analyzed NOVC isolated from retail seafood products, which may be considered for further pathogenicity evaluation and the risk assessment of NOVC isolates in future seafood monitoring.

Genetic characterization of a multidrug-resistant Salmonella enterica serovar Agona isolated from a dietary supplement in Germany.

Salmonella enterica subsp. enterica serovar Agona has a history of causing food-borne outbreaks and any emergence of multidrug-resistant (MDR) isolates in novel food products is of concern. Particularly, in food products frequently consumed without sufficient heating prior to consumption. Here, we report about the MDR isolate, 18-SA00377, which had been isolated from a dietary supplement in Germany in 2018 and submitted to the German National Reference Laboratory for Salmonella. WGS-based comparative genetic analyses were conducted to find a potential reservoir of the isolate itself or mobile genetic elements associated with MDR. As a phylogenetic analysis did not yield any closely related S. Agona isolates, either globally or from Germany, a detailed analysis of the largest plasmid (295,499 bp) was performed as it is the main carrier of resistances. A combined approach of long-read and short-read sequencing enabled the assembly of the isolate's chromosome and its four plasmids. Their characterization revealed the presence of 23 different antibiotic resistance genes (ARGs), conferring resistance to 12 different antibiotic drug classes, as well as genes conferring resistance to six different heavy metals. The largest plasmid, pSE18-SA00377-1, belongs to the IncHI2 plasmid family and carries 16 ARGs, that are organized as two distinct clusters, with each ARG associated with putative composite transposons. Through a two-pronged approach, highly similar plasmids to pSE18-SA00377-1 were identified in the NCBI database and a search for Salmonella isolates with a highly similar ARG resistance profile was conducted. Mapping and structural comparisons between pSE18-SA00377-1 and these plasmids and Salmonella isolates showed that both the plasmid backbone and identical or similar ARG clusters can be found not only in Salmonella isolates, originating mostly from a wide variety of livestock, but also in a diverse range of bacterial genera of varying geographical origins and isolation sources. Thus, it can be speculated that the host range of pSE18-SA00377-1 is not restricted to Salmonella and its spread already occurred in different bacterial populations. Overall, this hints at a complex history for pSE18-SA00377-1 and highlights the importance of surveilling multidrug-resistant S. enterica isolates, especially in novel food items that are not yet heavily regulated.

Exploring Long-Read Metagenomics for Full Characterization of Shiga Toxin-Producing Escherichia coli in Presence of Commensal E. coli.

The characterization of Shiga toxin-producing Escherichia coli (STEC) is necessary to assess their pathogenic potential, but isolation of the strain from complex matrices such as milk remains challenging. In previous work, we have shown the potential of long-read metagenomics to characterize eae-positive STEC from artificially contaminated raw milk without isolating the strain. The presence of multiple E. coli strains in the sample was shown to potentially hinder the correct characterization of the STEC strain. Here, we aimed at determining the STEC:commensal ratio that would prevent the characterization of the STEC. We artificially contaminated pasteurized milk with different ratios of an eae-positive STEC and a commensal E. coli and applied the method previously developed. Results showed that the STEC strain growth was better than the commensal E. coli after enrichment in acriflavine-supplemented BPW. The STEC was successfully characterized in all samples with at least 10 times more STEC post-enrichment compared to the commensal E. coli. However, the presence of equivalent proportions of STEC and commensal E. coli prevented the full characterization of the STEC strain. This study confirms the potential of long-read metagenomics for STEC characterization in an isolation-free manner while refining its limit regarding the presence of background E. coli strains.

Clonal relation between Salmonella enterica subspecies enterica serovar Dublin strains of bovine and food origin in Germany.

Salmonella enterica subspecies enterica serovar Dublin (S. Dublin) is a host-adapted serovar causing enteritis and/or systemic diseases in cattle. As the serovar is not host-restricted, it may cause infections in other animals, including humans with severe illness and higher mortality rates than other non-typhoidal serovars. As human infections are mainly caused by contaminated milk, milk products and beef, information on the genetic relationship of S. Dublin strains from cattle and food should be evaluated. Whole-genome sequencing (WGS) of 144 S. Dublin strains from cattle and 30 strains from food origin was performed. Multilocus sequence typing (MLST) revealed mostly sequence type ST-10 from both, cattle and food isolates. In total, 14 of 30 strains from food origin were clonally related to at least one strain from cattle, as detected by core-genome single nucleotide polymorphisms typing as well as core-genome MLST. The remaining 16 foodborne strains fit into the genome structure of S. Dublin in Germany without outliers. WGS proved to be a powerful tool not only to gain information on the epidemiology of Salmonella strains but also to detect clonal relations between organisms isolated from different stages of production. This study has shown a high genetic correlation between S. Dublin strains from cattle and food and, therefore, the potential to cause human infections. S. Dublin strains of both origins share an almost identical set of virulence factors, emphasizing their potential to cause severe clinical manifestations in animals, but also in humans and thus the need for effective control of S. Dublin in a farm-to-fork strategy.

Genomic Insights into the Mobilome and Resistome of Sentinel Microorganisms Originating from Farms of Two Different Swine Production Systems.

Antimicrobial resistance (AMR) is a threat to public health due to long-term antimicrobial use (AMU), which promotes the bacterial acquisition of antimicrobial resistance determinants (ARDs). Within food-producing animals, organic and extensive Iberian swine production is based on sustainable and eco-friendly management systems, providing an excellent opportunity to evaluate how sustained differences in AMU impact the development and spread of AMR. Here, through a whole-genome sequencing approach, we provide an in-depth characterization of the resistome and mobilome and their interaction in 466 sentinel bacteria, namely, Escherichia coli, Enterococcus spp., Campylobacter coli, and Staphylococcus spp., recovered from 37 intensive and organic-extensive pig farms. Both ARDs and mobile genetic elements (MGEs) were primarily taxon-associated, with higher similarities among bacteria which were closely phylogenetically related. E. coli exhibited the most diverse resistome and mobilome, with 85.4% mobilizable ARDs, 50.3% of which were plasmid-associated. Staphylococcus spp. exhibited a broad repertoire of ARDs and MGEs, with 52.3% of its resistome being mobilizable. Although Enterococcus spp. carried the highest number of ARDs per isolate and its plasmidome was similar in size to that of E. coli, 43.7% of its resistome was mobilizable. A narrow spectrum of ARDs constituted the C. coli resistome, with point mutations as its main AMR driver. A constrained AMU, as observed in organic-extensive herds, determined a reduction in the quantitative composition of the resistome and the complexity of the resistome-mobilome interaction. These results demonstrate taxon-associated AMR-MGE interactions and evidence that responsible AMU can contribute to reducing AMR pressure in the food chain. IMPORTANCE This study provides the first integral genomic characterization of the resistome and mobilome of sentinel microorganisms for antimicrobial resistance (AMR) surveillance from two different swine production systems. Relevant differences were observed among taxa in the resistomes and mobilomes they harbored, revealing their distinctive risk in AMR dissemination and spread. Thus, Escherichia coli and, to a lesser extent, Staphylococcus spp. constituted the main reservoirs of mobilizable antimicrobial resistance genes, which were predominantly plasmid-associated; in contrast to Campylobacter coli, whose resistome was mainly determined by point mutations. The reduced complexity of mobilome-resistome interaction in Enterococcus spp. suggested its limited role in AMR dissemination from swine farms. The significant differences in antimicrobial use among the studied farms allowed us to assess the suitability of whole-genome sequencing as a rapid and efficient technique for the assessment of mid- to long-term on-farm interventions for the reduction of antimicrobial use and the evaluation of AMR status.

Complete Genome Sequence of a Salmonella enterica subsp. enterica Serovar Tennessee Strain from Tahini.

Salmonella sp. infections are associated with contaminated low-moisture foods (with high fat content) with increasing frequency. Here, we report the complete genome sequence of Salmonella enterica subsp. enterica serovar Tennessee, which was isolated from tahini (a paste made from ground sesame seeds) purchased at a local retailer in Berlin, Germany.

Complete Genome Sequence of an Aeromonas rivuli Strain Isolated from Ready-to-Eat Food.

Aeromonads can be associated with diseases in animals and humans. Knowledge regarding Aeromonas rivuli, a species recently discovered in creek water in Germany, is still fragmentary. Here, we announce the complete genome sequence of Aeromonas rivuli strain 20-VB00005, which was recovered from ready-to-eat food.

A step forward for Shiga toxin-producing Escherichia coli identification and characterization in raw milk using long-read metagenomics.

Shiga toxin-producing Escherichia coli (STEC) are a cause of severe human illness and are frequently associated with haemolytic uraemic syndrome (HUS) in children. It remains difficult to identify virulence factors for STEC that absolutely predict the potential to cause human disease. In addition to the Shiga-toxin (stx genes), many additional factors have been reported, such as intimin (eae gene), which is clearly an aggravating factor for developing HUS. Current STEC detection methods classically rely on real-time PCR (qPCR) to detect the presence of the key virulence markers (stx and eae). Although qPCR gives an insight into the presence of these virulence markers, it is not appropriate for confirming their presence in the same strain. Therefore, isolation steps are necessary to confirm STEC viability and characterize STEC genomes. While STEC isolation is laborious and time-consuming, metagenomics has the potential to accelerate the STEC characterization process in an isolation-free manner. Recently, short-read sequencing metagenomics have been applied for this purpose, but assembly quality and contiguity suffer from the high proportion of mobile genetic elements occurring in STEC strains. To circumvent this problem, we used long-read sequencing metagenomics for identifying eae-positive STEC strains using raw cow's milk as a causative matrix for STEC food-borne outbreaks. By comparing enrichment conditions, optimizing library preparation for MinION sequencing and generating an easy-to-use STEC characterization pipeline, the direct identification of an eae-positive STEC strain was successful after enrichment of artificially contaminated raw cow's milk samples at a contamination level as low as 5 c.f.u. ml-1. Our newly developed method combines optimized enrichment conditions of STEC in raw milk in combination with a complete STEC analysis pipeline from long-read sequencing metagenomics data. This study shows the potential of the innovative methodology for characterizing STEC strains from complex matrices. Further developments will nonetheless be necessary for this method to be applied in STEC surveillance.

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.

Phenotypic and Genotypic Properties of Fluoroquinolone-Resistant, qnr-Carrying Escherichia coli Isolated from the German Food Chain in 2017.

Fluoroquinolones are the highest priority, critically important antimicrobial agents. Resistance development can occur via different mechanisms, with plasmid-mediated quinolone resistance (PMQR) being prevalent in the livestock and food area. Especially, qnr genes, commonly located on mobile genetic elements, are major drivers for the spread of resistance determinants against fluoroquinolones. We investigated the prevalence and characteristics of qnr-positive Escherichia (E.) coli obtained from different monitoring programs in Germany in 2017. Furthermore, we aimed to evaluate commonalities of qnr-carrying plasmids in E. coli. We found qnr to be broadly spread over different livestock and food matrices, and to be present in various sequence types. The qnr-positive isolates were predominantly detected within selectively isolated ESBL (extended spectrum beta-lactamase)-producing E. coli, leading to a frequent association with other resistance genes, especially cephalosporin determinants. Furthermore, we found that qnr correlates with the presence of genes involved in resistance development against quaternary ammonium compounds (qac). The detection of additional point mutations in many isolates within the chromosomal QRDR region led to even higher MIC values against fluoroquinolones for the investigated E. coli. All of these attributes should be carefully taken into account in the risk assessment of qnr-carrying E. coli from livestock and food.

Direct identification and molecular characterization of zoonotic hazards in raw milk by metagenomics using Brucella as a model pathogen.

Metagenomics is a valuable diagnostic tool for enhancing microbial food safety because (i) it enables the untargeted detection of pathogens, (ii) it is fast since primary isolation of micro-organisms is not required, and (iii) it has high discriminatory power allowing for a detailed molecular characterization of pathogens. For shotgun metagenomics, total nucleic acids (NAs) are isolated from complex samples such as foodstuff. Along with microbial NAs, high amounts of matrix NAs are extracted that might outcompete microbial NAs during next-generation sequencing and compromise sensitivity for the detection of low abundance micro-organisms. Sensitive laboratory methods are indispensable for detecting highly pathogenic foodborne bacteria like Brucella spp., because a low infectious dose is sufficient to cause human disease through the consumption of contaminated dairy or meat products. In our study, we applied shotgun metagenomic sequencing for the identification and characterization of Brucella spp. in artificially and naturally contaminated raw milk from various ruminant species. With the depletion of eukaryotic cells prior to DNA extraction, Brucella was detectable at 10 bacterial cells ml-1, while at the same time microbiological culture and isolation of the fastidious bacteria commonly failed. Moreover, we were able to retrieve the genotype of a Brucella isolate from a metagenomic dataset, indicating the potential of metagenomics for outbreak investigations using SNPs and core-genome multilocus sequence typing (cgMLST). To improve diagnostic applications, we developed a new bioinformatics approach for strain prediction based on SNPs to identify the correct species and define a certain strain with only low numbers of genus-specific reads per sample. This pipeline turned out to be more sensitive and specific than Mash Screen. In raw milk samples, we simultaneously detected numerous other zoonotic pathogens, antimicrobial resistance genes and virulence factors. Our study showed that metagenomics is a highly sensitive tool for biological risk assessment of foodstuffs, particularly when pathogen isolation is hazardous or challenging.

Outcome of Different Sequencing and Assembly Approaches on the Detection of Plasmids and Localization of Antimicrobial Resistance Genes in Commensal Escherichia coli.

Antimicrobial resistance (AMR) is a major threat to public health worldwide. Currently, AMR typing changes from phenotypic testing to whole-genome sequence (WGS)-based detection of resistance determinants for a better understanding of the isolate diversity and elements involved in gene transmission (e.g., plasmids, bacteriophages, transposons). However, the use of WGS data in monitoring purposes requires suitable techniques, standardized parameters and approved guidelines for reliable AMR gene detection and prediction of their association with mobile genetic elements (plasmids). In this study, different sequencing and assembly strategies were tested for their suitability in AMR monitoring in Escherichia coli in the routines of the German National Reference Laboratory for Antimicrobial Resistances. To assess the outcomes of the different approaches, results from in silico predictions were compared with conventional phenotypic- and genotypic-typing data. With the focus on (fluoro)quinolone-resistant E.coli, five qnrS-positive isolates with multiple extrachromosomal elements were subjected to WGS with NextSeq (Illumina), PacBio (Pacific BioSciences) and ONT (Oxford Nanopore) for in depth characterization of the qnrS1-carrying plasmids. Raw reads from short- and long-read sequencing were assembled individually by Unicycler or Flye or a combination of both (hybrid assembly). The generated contigs were subjected to bioinformatics analysis. Based on the generated data, assembly of long-read sequences are error prone and can yield in a loss of small plasmid genomes. In contrast, short-read sequencing was shown to be insufficient for the prediction of a linkage of AMR genes (e.g., qnrS1) to specific plasmid sequences. Furthermore, short-read sequencing failed to detect certain duplications and was unsuitable for genome finishing. Overall, the hybrid assembly led to the most comprehensive typing results, especially in predicting associations of AMR genes and mobile genetic elements. Thus, the use of different sequencing technologies and hybrid assemblies currently represents the best approach for reliable AMR typing and risk assessment.

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.

Complete and Circularized Genome Assembly of a Human Isolate of Vibrio navarrensis Biotype pommerensis with MiSeq and MinION Sequence Data.

Vibrio navarrensis is a rare human pathogen. Strains of Vibrio navarrensis biotype pommerensis were isolated from seawater of the Baltic Sea. Recently, a strain of this biotype was recovered from a human patient. The isolate contains two circular chromosomes and a large plasmid with a size of 180 kb.