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The extent to which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) break through infection- or vaccine-induced immunity is not well understood. We analyzed 28,578 sequenced SARS-CoV-2 samples from individuals with known immune status obtained through national community testing in the Netherlands from March to August 2021. We found evidence of an increased risk of infection by the Beta (B.1.351), Gamma (P.1), or Delta (B.1.617.2) variants compared with the Alpha (B.1.1.7) variant after vaccination. No clear differences were found between vaccines. However, the effect was larger in the first 14 to 59 days after complete vaccination compared with ≥60 days. In contrast to vaccine-induced immunity, there was no increased risk for reinfection with Beta, Gamma, or Delta variants relative to the Alpha variant in individuals with infection-induced immunity.

The extent to which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) break through infection- or vaccine-induced immunity is not well understood. Here, we analyze 28,578 sequenced SARS-CoV-2 samples from individuals with known immune status obtained through national community testing in the Netherlands from March to August 2021. We find evidence for an increased risk of infection by the Beta (B.1.351), Gamma (P.1), or Delta (B.1.617.2) variants compared to the Alpha (B.1.1.7) variant after vaccination. No clear differences were found between vaccines. However, the effect was larger in the first 14-59 days after complete vaccination compared to 60 days and longer. In contrast to vaccine-induced immunity, no increased risk for reinfection with Beta, Gamma or Delta variants relative to Alpha variant was found in individuals with infection-induced immunity.

Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories.MethodsMetagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analysed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analysed.ResultsOverall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection.ConclusionA wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.

Mumps cases continue to occur, also in countries with a relatively high vaccination rate. The last major outbreaks of mumps in the Netherlands were from 2009-2012 and thereafter, only small clusters and single cases were reported. Molecular epidemiology can provide insights in the circulation of mumps viruses. The aims of the present study were to analyze the molecular epidemiology of mumps viruses in the Netherlands in 2017-2019 and to elucidate whether complete genome sequencing adds to the molecular resolution of mumps viruses when compared to sequencing of the mumps SH gene and non-coding regions (SH+NCRs). To this end, Sanger sequence data from the SH+NCRs were analyzed from 82 mumps genotype G viruses. In addition, the complete genomes were obtained from 10 mumps virus isolates using next-generation sequencing. Analysis of SH+NCRs of mumps viruses revealed the presence of two major lineages in the Netherlands, which was confirmed by analysis of complete genomes. Comparison of molecular resolution obtained with SH+NCRs and complete genomes clearly indicated that additional molecular resolution can be obtained by analyzing complete genomes. In conclusion, analysis of SH + NCRs sequence data from recent mumps genotype G viruses indicate that mumps viruses continue to circulate in the Netherlands and surrounding countries. However, to understand exact transmission trees and to compare mumps viruses on a large geographic scale, analysis of complete genomes is a very useful approach.

As research next-generation sequencing (NGS) metagenomic pipelines transition to clinical diagnostics, the user-base changes from bioinformaticians to biologists, medical doctors, and lab-technicians. Besides the obvious need for benchmarking and assessment of diagnostic outcomes of the pipelines and tools, other focus points remain: reproducibility, data immutability, user-friendliness, portability/scalability, privacy, and a clear audit trail. We have a research metagenomics pipeline that takes raw fastq files and produces annotated contigs, but it is too complicated for non-bioinformaticians. Here, we present preliminary findings in adapting this pipeline for clinical diagnostics. We used information available on relevant fora (www.bioinfo-core.org) and experiences and publications from colleague bioinformaticians in other institutes (COMPARE, UBC, and LUMC). From this information, a robust and user-friendly storage and analysis workflow was designed for non-bioinformaticians in a clinical setting. Via Conda [https://conda.io] and Docker containers [http://www.docker.com], we made our disparate pipeline processes self-contained and reproducible. Furthermore, we moved all pipeline settings into a separate JSON file. After every analysis, the pipeline settings and virtual-environment recipes will be archived (immutably) under a persistent unique identifier. This allows long-term precise reproducibility. Likewise, after every run the raw data and final products will be automatically archived, complying with data retention laws/guidelines. All the disparate processes in the pipeline are parallelized and automated via Snakemake1 (i.e. end-users need no coding skills). In addition, interactive web-reports such as MultiQC [http://multiqc.info] and Krona2 are generated automatically. By combining Snakemake, Conda, and containers, our pipeline is highly portable and easily scaled up for outbreak situations, or scaled down to reduce costs. Since patient privacy is a concern, our pipeline automatically removes human genetic data. Moreover, all source code will be stored on an internal Gitlab server, and, combined with the archived data, ensures a clear audit trail. Nevertheless, challenges remain: (1) reproducible reference databases, e.g. being able to revert to an older version to reproduce old analyses. (2) A user-friendly GUI. (3) Connecting the pipeline and NGS data to in-house LIMS. (4) Efficient long-term storage, e.g. lossless compression algorithms. Nevertheless, this work represents a step forward in making user-friendly clinical diagnostic workflows.

Quality management and independent assessment of high-throughput sequencing-based virus diagnostics have not yet been established as a mandatory approach for ensuring comparable results. The sensitivity and specificity of viral high-throughput sequence data analysis are highly affected by bioinformatics processing using publicly available and custom tools and databases and thus differ widely between individuals and institutions., Quality management and independent assessment of high-throughput sequencing-based virus diagnostics have not yet been established as a mandatory approach for ensuring comparable results. The sensitivity and specificity of viral high-throughput sequence data analysis are highly affected by bioinformatics processing using publicly available and custom tools and databases and thus differ widely between individuals and institutions. Here we present the results of the COMPARE [Collaborative Management Platform for Detection and Analyses of (Re-)emerging and Foodborne Outbreaks in Europe] in silico virus proficiency test. An artificial, simulated in silico data set of Illumina HiSeq sequences was provided to 13 different European institutes for bioinformatics analysis to identify viral pathogens in high-throughput sequence data. Comparison of the participants’ analyses shows that the use of different tools, programs, and databases for bioinformatics analyses can impact the correct identification of viral sequences from a simple data set. The identification of slightly mutated and highly divergent virus genomes has been shown to be most challenging. Furthermore, the interpretation of the results, together with a fictitious case report, by the participants showed that in addition to the bioinformatics analysis, the virological evaluation of the results can be important in clinical settings. External quality assessment and proficiency testing should become an important part of validating high-throughput sequencing-based virus diagnostics and could improve the harmonization, comparability, and reproducibility of results. There is a need for the establishment of international proficiency testing, like that established for conventional laboratory tests such as PCR, for bioinformatics pipelines and the interpretation of such results.

Data sharing enables research communities to exchange findings and build upon the knowledge that arises from their discoveries. Areas of public and animal health as well as food safety would benefit from rapid data sharing when it comes to emergencies. However, ethical, regulatory and institutional challenges, as well as lack of suitable platforms which provide an infrastructure for data sharing in structured formats, often lead to data not being shared or at most shared in form of supplementary materials in journal publications. Here, we describe an informatics platform that includes workflows for structured data storage, managing and pre-publication sharing of pathogen sequencing data and its analysis interpretations with relevant stakeholders.

The development of domain specific models requires appropriate tool support for modeling and execution. Meta-modeling facilitates solutions for the generation of modeling tools from abstract language specifications. The Rmt approach (Renew Meta-Modeling and Transformation) applies transformational semantics using Petri net formalisms as target languages in order to produce quick results for the development of modeling techniques. The problem with transformational approaches is that the inspection of the system during execution is not possible in the original representation.

The Curry-coloured Petri net (CCPN) simulation combines Petri nets with the purely functional logic programming language Curry. The most notable aspects of the CCPN simulator are the absence of side effects, the use of logic program evaluation for the transition binding search and a concurrent simulation. Furthermore, the inscribed programs can be non-deterministic.

Mumps cases continue to occur, also in countries with a relatively high vaccination rate. The last major outbreaks of mumps in the Netherlands were in 2009–2012 and thereafter, only small clusters and single cases were reported. Molecular epidemiology can provide insights in the circulation of mumps viruses. The aims of the present study were to analyze the molecular epidemiology of mumps viruses in the Netherlands in 2017–2019 and to compare the phylogenetic trees built from sequence data of near complete mumps virus genomes or from the SH gene and non-coding regions (SH+NCRs). To this end, Sanger sequence data from SH+NCRs were analyzed from 82 mumps genotype G viruses. In addition, near complete genomes were obtained from 10 mumps virus isolates using next-generation sequencing. Analysis of SH+NCRs sequences of mumps genotype G viruses revealed the presence of two major genetic lineages in the Netherlands, which was confirmed by analysis of near complete genomes. Comparison of phylogenetic trees built with SH+NCRs or near complete genomes indicated that the topology was similar, while somewhat longer branches were present in the phylogenetic tree with near complete genomes. These results confirm that analysis of SH + NCRs sequence data is a useful approach for molecular surveillance. Furthermore, data from recent mumps genotype G viruses might indicate (intermittent) circulation of mumps genotype G viruses in the Netherlands in 2017–2019.

Nowadays, modeling complex systems requires a combination of techniques to facilitate multiple perspectives and adequate modeling. Therefore, UML and other formalisms are used in combination with Petri nets. Often the different models are transformed into a single formalism to simulate the resulting models within a homogeneous execution environment. For UML, the mapping is usually done via the transformation to some programming language.

Brick-and-mortar retailers are nowadays confronted with increased customer expectations and competitive pressure from online pure players. While omni-channel retailing may present exceptional growth opportunities, accompanying significant invest- ments and further complexity in channel integration pose unprecedented challenges. This article 1 is the first to promote a comprehensive framework on the multi-dimensionality of omni-channel integration. Moreover, we propose an objectified measurement scale to as- sess a retailer’s omni-channel capability as prevailing measures solely feature a macro view or are externally-focused. We find growing revenues and meeting customer expectations to be drivers of omni-channel engagement. Consolidating the IT infrastructure alongside overcoming organizational issues are discovered as dominant impediments. Furthermore, the study takes a micro view on the multiple dimensions of omni-channel integration that are clustered into organization, data and infrastructure, processes, and marketing strategy. The findings enable managers to prioritize investment decisions, define a complementary retailing strategy and assess their competitive positioning.

Modelling with agents focusses on the structure of a software system, while modelling with workflows focusses on the behaviour. Our research aims to combine and integrate the strengths of each of these concepts in a unified modelling approach. This current paper presents a technical implementation and proof-of-concept of that approach in the so-called Paffin (Processes and Agents for a Full Integration) system. An application scenario is also discussed.

Teaching the application of Petri nets to software development is a major challenge for the Petri net community. We face this during our practical courses in that we teach the Paose-approach. Students need to get acquainted with the development tools. At the beginning of each course, we start with an introduction phase, which is followed by an intensification phase. In order to support the teachers as well as the students, we use explicated process models to restructure and augment the worksheets. The resulting worksheets enable the students to follow the structure of the processes step by step. In the last two projects, we already applied the restructured and augmented worksheets. We noticed that the students were able to process the worksheets more independently and were less confused and frustrated. In general this lead to a more relaxed teaching atmosphere. In this contribution we provide detailed insights into the teaching approach. We demonstrate our current best practices for teaching Petri nets in practical settings. In this regard, we describe how Petri nets can be utilized to improve learning materials (e.g. worksheets) and to this end, the effects of our restructured and augmented learning materials are evaluated.