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  • 1
    Online Resource
    Online Resource
    Validation strategy of a bioinformatics whole genome sequencing workflow for Shiga toxin-producing Escherichia coli using a reference collection extensively characterized with conventional methods
    Microbiology Society ; 2021
    In:  Microbial Genomics Vol. 7, No. 3 ( 2021-03-01)
    Details
    In: Microbial Genomics, Microbiology Society, Vol. 7, No. 3 ( 2021-03-01)
    Abstract: Whole genome sequencing (WGS) enables complete characterization of bacterial pathogenic isolates at single nucleotide resolution, making it the ultimate tool for routine surveillance and outbreak investigation. The lack of standardization, and the variation regarding bioinformatics workflows and parameters, however, complicates interoperability among (inter)national laboratories. We present a validation strategy applied to a bioinformatics workflow for Illumina data that performs complete characterization of Shiga toxin-producing Escherichia coli (STEC) isolates including antimicrobial resistance prediction, virulence gene detection, serotype prediction, plasmid replicon detection and sequence typing. The workflow supports three commonly used bioinformatics approaches for the detection of genes and alleles: alignment with blast +, kmer-based read mapping with KMA, and direct read mapping with SRST2. A collection of 131 STEC isolates collected from food and human sources, extensively characterized with conventional molecular methods, was used as a validation dataset. Using a validation strategy specifically adopted to WGS, we demonstrated high performance with repeatability, reproducibility, accuracy, precision, sensitivity and specificity above 95 % for the majority of all assays. The WGS workflow is publicly available as a ‘push-button’ pipeline at https://galaxy.sciensano.be. Our validation strategy and accompanying reference dataset consisting of both conventional and WGS data can be used for characterizing the performance of various bioinformatics workflows and assays, facilitating interoperability between laboratories with different WGS and bioinformatics set-ups.
    Type of Medium: Online Resource
    ISSN: 2057-5858
    URL: Article
    DOI: 10.1099/mgen.0.000531
    Language: English
    Publisher: Microbiology Society
    Publication Date: 2021
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  • 2
    Online Resource
    Online Resource
    Whole-genome-based phylogenomic analysis of the Belgian 2016–2017 influenza A(H3N2) outbreak season allows improved surveillance
    Microbiology Society ; 2021
    In:  Microbial Genomics Vol. 7, No. 9 ( 2021-09-03)
    Details
    In: Microbial Genomics, Microbiology Society, Vol. 7, No. 9 ( 2021-09-03)
    Abstract: Seasonal influenza epidemics are associated with high mortality and morbidity in the human population. Influenza surveillance is critical for providing information to national influenza programmes and for making vaccine composition predictions. Vaccination prevents viral infections, but rapid influenza evolution results in emerging mutants that differ antigenically from vaccine strains. Current influenza surveillance relies on Sanger sequencing of the haemagglutinin (HA) gene. Its classification according to World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC) guidelines is based on combining certain genotypic amino acid mutations and phylogenetic analysis. Next-generation sequencing technologies enable a shift to whole-genome sequencing (WGS) for influenza surveillance, but this requires laboratory workflow adaptations and advanced bioinformatics workflows. In this study, 253 influenza A(H3N2) positive clinical specimens from the 2016–2017 Belgian season underwent WGS using the Illumina MiSeq system. HA-based classification according to WHO/ECDC guidelines did not allow classification of all samples. A new approach, considering the whole genome, was investigated based on using powerful phylogenomic tools including beast and Nextstrain, which substantially improved phylogenetic classification. Moreover, Bayesian inference via beast facilitated reassortment detection by both manual inspection and computational methods, detecting intra-subtype reassortants at an estimated rate of 15 %. Real-time analysis (i.e. as an outbreak is ongoing) via Nextstrain allowed positioning of the Belgian isolates into the globally circulating context. Finally, integration of patient data with phylogenetic groups and reassortment status allowed detection of several associations that would have been missed when solely considering HA, such as hospitalized patients being more likely to be infected with A(H3N2) reassortants, and the possibility to link several phylogenetic groups to disease severity indicators could be relevant for epidemiological monitoring. Our study demonstrates that WGS offers multiple advantages for influenza monitoring in (inter)national influenza surveillance, and proposes an improved methodology. This allows leveraging all information contained in influenza genomes, and allows for more accurate genetic characterization and reassortment detection.
    Type of Medium: Online Resource
    ISSN: 2057-5858
    URL: Article
    DOI: 10.1099/mgen.0.000643
    Language: English
    Publisher: Microbiology Society
    Publication Date: 2021
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  • 3
    Online Resource
    Online Resource
    A general approach to identify low-frequency variants within influenza samples collected during routine surveillance
    Microbiology Society ; 2022
    In:  Microbial Genomics Vol. 8, No. 9 ( 2022-09-28)
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    In: Microbial Genomics, Microbiology Society, Vol. 8, No. 9 ( 2022-09-28)
    Abstract: Influenza viruses exhibit considerable diversity between hosts. Additionally, different quasispecies can be found within the same host. High-throughput sequencing technologies can be used to sequence a patient-derived virus population at sufficient depths to identify low-frequency variants (LFV) present in a quasispecies, but many challenges remain for reliable LFV detection because of experimental errors introduced during sample preparation and sequencing. High genomic copy numbers and extensive sequencing depths are required to differentiate false positive from real LFV, especially at low allelic frequencies (AFs). This study proposes a general approach for identifying LFV in patient-derived samples obtained during routine surveillance. Firstly, validated thresholds were determined for LFV detection, whilst balancing both the cost and feasibility of reliable LFV detection in clinical samples. Using a genetically well-defined population of influenza A viruses, thresholds of at least 10 4 genomes per microlitre and AF of ≥5 % were established as detection limits. Secondly, a subset of 59 retained influenza A (H3N2) samples from the 2016–2017 Belgian influenza season was composed. Thirdly, as a proof of concept for the added value of LFV for routine influenza monitoring, potential associations between patient data and whole genome sequencing data were investigated. A significant association was found between a high prevalence of LFV and disease severity. This study provides a general methodology for influenza LFV detection, which can also be adopted by other national influenza reference centres and for other viruses such as SARS-CoV-2. Additionally, this study suggests that the current relevance of LFV for routine influenza surveillance programmes might be undervalued.
    Type of Medium: Online Resource
    ISSN: 2057-5858
    URL: Article
    DOI: 10.1099/mgen.0.000867
    Language: English
    Publisher: Microbiology Society
    Publication Date: 2022
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  • 4
    Online Resource
    Online Resource
    Using a combination of short- and long-read sequencing to investigate the diversity in plasmid- and chromosomally encoded extended-spectrum beta-lactamases (ESBLs) in clinical Shigella and Salmonella isolates in Belgium
    Microbiology Society ; 2023
    In:  Microbial Genomics Vol. 9, No. 1 ( 2023-01-23)
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    In: Microbial Genomics, Microbiology Society, Vol. 9, No. 1 ( 2023-01-23)
    Abstract: For antimicrobial resistance (AMR) surveillance, it is important not only to detect AMR genes, but also to determine their plasmidic or chromosomal location, as this will impact their spread differently. Whole-genome sequencing (WGS) is increasingly used for AMR surveillance. However, determining the genetic context of AMR genes using only short-read sequencing is complicated. The combination with long-read sequencing offers a potential solution, as it allows hybrid assemblies. Nevertheless, its use in surveillance has so far been limited. This study aimed to demonstrate its added value for AMR surveillance based on a case study of extended-spectrum beta-lactamases (ESBLs). ESBL genes have been reported to occur also on plasmids. To gain insight into the diversity and genetic context of ESBL genes detected in clinical isolates received by the Belgian National Reference Center between 2013 and 2018, 100 ESBL-producing Shigella and 31 ESBL-producing Salmonella were sequenced with MiSeq and a representative selection of 20 Shigella and six Salmonella isolates additionally with MinION technology, allowing hybrid assembly. The bla CTX-M-15 gene was found to be responsible for a rapid rise in the ESBL Shigella phenotype from 2017. This gene was mostly detected on multi-resistance-carrying IncFII plasmids. Based on clustering, these plasmids were determined to be distinct from the circulating plasmids before 2017. They were spread to different Shigella species and within Shigella sonnei between multiple genotypes. Another similar IncFII plasmid was detected after 2017 containing bla CTX-M-27 for which only clonal expansion occurred. Matches of up to 99 % to plasmids of various bacterial hosts from all over the world were found, but global alignments indicated that direct or recent ESBL-plasmid transfers did not occur. It is most likely that travellers introduced these in Belgium and subsequently spread them domestically. However, a clear link to a specific country could not be made. Moreover, integration of bla CTX-M in the chromosome of two Shigella isolates was determined for the first time, and shown to be related to ISEcp1. In contrast, in Salmonella , ESBL genes were only found on plasmids, of which bla CTX-M-55 and IncHI2 were the most prevalent, respectively. No matching ESBL plasmids or cassettes were detected between clinical Shigella and Salmonella isolates. The hybrid assembly data allowed us to check the accuracy of plasmid prediction tools. MOB-suite showed the highest accuracy. However, these tools cannot replace the accuracy of long-read and hybrid assemblies. This study illustrates the added value of hybrid assemblies for AMR surveillance and shows that a strategy where even just representative isolates of a collection used for hybrid assemblies could improve international AMR surveillance as it allows plasmid tracking.
    Type of Medium: Online Resource
    ISSN: 2057-5858
    URL: Article
    DOI: 10.1099/mgen.0.000925
    Language: English
    Publisher: Microbiology Society
    Publication Date: 2023
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  • 5
    Online Resource
    Online Resource
    Evaluation of WGS performance for bacterial pathogen characterization with the Illumina technology optimized for time-critical situations
    Microbiology Society ; 2021
    In:  Microbial Genomics Vol. 7, No. 11 ( 2021-11-05)
    Details
    In: Microbial Genomics, Microbiology Society, Vol. 7, No. 11 ( 2021-11-05)
    Abstract: Whole genome sequencing (WGS) has become the reference standard for bacterial outbreak investigation and pathogen typing, providing a resolution unattainable with conventional molecular methods. Data generated with Illumina sequencers can however only be analysed after the sequencing run has finished, thereby losing valuable time during emergency situations. We evaluated both the effect of decreasing overall run time, and also a protocol to transfer and convert intermediary files generated by Illumina sequencers enabling real-time data analysis for multiple samples part of the same ongoing sequencing run, as soon as the forward reads have been sequenced. To facilitate implementation for laboratories operating under strict quality systems, extensive validation of several bioinformatics assays (16S rRNA species confirmation, gene detection against virulence factor and antimicrobial resistance databases, SNP-based antimicrobial resistance detection, serotype determination, and core genome multilocus sequence typing) for three bacterial pathogens ( Mycobacterium tuberculosis , Neisseria meningitidis , and Shiga-toxin producing Escherichia coli ) was performed by evaluating performance in function of the two most critical sequencing parameters, i.e. read length and coverage. For the majority of evaluated bioinformatics assays, actionable results could be obtained between 14 and 22 h of sequencing, decreasing the overall sequencing-to-results time by more than half. This study aids in reducing the turn-around time of WGS analysis by facilitating a faster response in time-critical scenarios and provides recommendations for time-optimized WGS with respect to required read length and coverage to achieve a minimum level of performance for the considered bioinformatics assay(s), which can also be used to maximize the cost-effectiveness of routine surveillance sequencing when response time is not essential.
    Type of Medium: Online Resource
    ISSN: 2057-5858
    URL: Article
    DOI: 10.1099/mgen.0.000699
    Language: English
    Publisher: Microbiology Society
    Publication Date: 2021
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  • 6
    Online Resource
    Online Resource
    Application of a strain-level shotgun metagenomics approach on food samples: resolution of the source of a Salmonella food-borne outbreak
    Microbiology Society ; 2021
    In:  Microbial Genomics Vol. 7, No. 4 ( 2021-04-07)
    Details
    In: Microbial Genomics, Microbiology Society, Vol. 7, No. 4 ( 2021-04-07)
    Abstract: Food-borne outbreak investigation currently relies on the time-consuming and challenging bacterial isolation from food, to be able to link food-derived strains to more easily obtained isolates from infected people. When no food isolate can be obtained, the source of the outbreak cannot be unambiguously determined. Shotgun metagenomics approaches applied to the food samples could circumvent this need for isolation from the suspected source, but require downstream strain-level data analysis to be able to accurately link to the human isolate. Until now, this approach has not yet been applied outside research settings to analyse real food-borne outbreak samples. In September 2019, a Salmonella outbreak occurred in a hotel school in Bruges, Belgium, affecting over 200 students and teachers. Following standard procedures, the Belgian National Reference Center for human salmonellosis and the National Reference Laboratory for Salmonella in food and feed used conventional analysis based on isolation, serotyping and MLVA (multilocus variable number tandem repeat analysis) comparison, followed by whole-genome sequencing, to confirm the source of the contamination over 2 weeks after receipt of the sample, which was freshly prepared tartar sauce in a meal cooked at the school. Our team used this outbreak as a case study to deliver a proof of concept for a short-read strain-level shotgun metagenomics approach for source tracking. We received two suspect food samples: the full meal and some freshly made tartar sauce served with this meal, requiring the use of raw eggs. After analysis, we could prove, without isolation, that Salmonella was present in both samples, and we obtained an inferred genome of a Salmonella enterica subsp. enterica serovar Enteritidis that could be linked back to the human isolates of the outbreak in a phylogenetic tree. These metagenomics-derived outbreak strains were separated from sporadic cases as well as from another outbreak circulating in Europe at the same time period. This is, to our knowledge, the first Salmonella food-borne outbreak investigation uniquely linking the food source using a metagenomics approach and this in a fast time frame.
    Type of Medium: Online Resource
    ISSN: 2057-5858
    URL: Article
    DOI: 10.1099/mgen.0.000547
    Language: English
    Publisher: Microbiology Society
    Publication Date: 2021
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