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.

Smallpox was declared eradicated in 1980¹ thanks to the use of the vaccine initially developed by Edward Jenner in 1798.² Since that time, it has generally been assumed that the smallpox vaccine is based on cowpox virus, even though it has been known since the late 1930s that the virus that is used to immunize against smallpox, now referred to as vaccinia, differs from cowpox virus. The true origin of vaccinia virus is unknown, and it is usually described as a laboratory virus without a known natural host. Smallpox vaccines from many different sources were used until 1967, when the World Health Organization standardized four vaccinia strains that were widely used in the global smallpox eradication effort, although other vaccines were also used.¹

In food safety the detection of food contaminations with pathogenic microorganisms is a race against time and often outpaced by error-prone epidemiological approaches. For evidence-based outbreak investigations fast and reliable techniques and procedures are required to identify the source of infection. Metagenomics has the potential to become a powerful tool in the field of modern food safety, since it allows the detection, identification and characterization of a broad range of pathogens in a single experiment without pre-cultivation within a couple of days. Nevertheless, sample handling, sequencing and data analysis are challenging and can introduce errors and biases into the analysis. In order to evaluate the potential of metagenomics in food safety, we generated a mock community containing DNA of foodborne bacteria. Herewith, we compare the aptitude of the two prevalent approaches – 16S rDNA amplicon sequencing and whole genome shotgun sequencing – for the detection of foodborne bacteria using different parameters during sample preparation, sequencing and data analysis. 16S rDNA sequencing did not only result in high deviations from the expected sample composition on genus and species level, but more importantly lacked the detection of several pathogenic species. While shotgun sequencing is more suitable for species detection, abundance estimation, genome assembly and species characterization, the performance can vary depending on the library preparation kit, which was confirmed for a naturally Francisella tularensis contaminated game meat sample. The application of the Nextera XT DNA Library Preparation Kit for shotgun sequencing did not only result in lower reference genome recovery and coverage, but also in distortions of the mock community composition. For data analysis, we propose a publicly available workflow for pathogen detection and characterization and demonstrate its benefits on the usability of metagenomic sequencing in food safety by analyzing an authentic metagenomic sample.

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.

Background: The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. Results: As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. Conclusions: Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI’s BioSample database.

Rotaviruses infect humans and animals and are a main cause of diarrhea. They are non-enveloped viruses with a genome of 11 double-stranded RNA segments. Based on genome analysis and amino acid sequence identities of the capsid protein VP6, the rotavirus species A to J (RVA-RVJ) have been defined so far. In addition, rotaviruses putatively assigned to the novel rotavirus species K (RVK) and L (RVL) have been recently identified in common shrews (Sorex araneus), based on partial genome sequences. Here, the complete genome sequence of strain KS14/0241, a prototype strain of RVL, is presented. The deduced amino acid sequence for VP6 of this strain shows only up to 47% identity to that of RVA to RVJ reference strains. Phylogenetic analyses indicate a clustering separated from the established rotavirus species for all 11 genome segments of RVL, with the closest relationship to RVH and RVJ within the phylogenetic RVB-like clade. The non-coding genome segment termini of RVL showed conserved sequences at the 5′-end (positive-sense RNA strand), which are common to all rotaviruses, and those conserved among the RVB-like clade at the 3′-end. The results are consistent with a classification of the virus into a novel rotavirus species L.