Search

Objectives Since January 2019, the Belgian National Reference Center for Mycobacteria (NRC) has switched from conventional typing to prospective whole-genome sequencing (WGS) of all submitted Mycobacterium tuberculosis complex (MTB) isolates. The ISO17025 validated procedure starts with semi-automated extraction and purification of gDNA directly from the submitted MGIT tubes, without preceding subculturing. All samples are then sequenced on an Illumina MiSeq sequencer and analyzed using an in-house developed and validated bioinformatics workflow to determine the species and antimicrobial resistance. In this study, we retrospectively compare results obtained via WGS to conventional phenotypic and genotypic testing, for all Belgian MTB strains analyzed in 2019 (n = 306). Results In all cases, the WGS-based procedure was able to identify correctly the MTB species. Compared to MGIT drug susceptibility testing (DST), the sensitivity and specificity of genetic prediction of resistance to first-line antibiotics were respectively 100 and 99% (rifampicin, RIF), 90.5 and 100% (isoniazid, INH), 100 and 98% (ethambutol, EMB) and 61.1 and 100% (pyrazinamide, PZA). The negative predictive value was above 95% for these four first-line drugs. A positive predictive value of 100% was calculated for INH and PZA, 80% for RIF and 45% for EMB. Conclusions Our study confirms the effectiveness of WGS for the rapid detection of M. tuberculosis complex and its drug resistance profiles for first-line drugs even when working directly on MGIT tubes, and supports the introduction of this test into the routine workflow of laboratories performing tuberculosis diagnosis.

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 104 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.

Since January 2019, the Belgian National Reference Center for Mycobacteria (NRC) has switched from conventional typing to prospective whole-genome sequencing (WGS) of all submittedIn all cases, the WGS-based procedure was able to identify correctly the MTB species. Compared to MGIT drug susceptibility testing (DST), the sensitivity and specificity of genetic prediction of resistance to first-line antibiotics were respectively 100 and 99% (rifampicin, RIF), 90.5 and 100% (isoniazid, INH), 100 and 98% (ethambutol, EMB) and 61.1 and 100% (pyrazinamide, PZA). The negative predictive value was above 95% for these four first-line drugs. A positive predictive value of 100% was calculated for INH and PZA, 80% for RIF and 45% for EMB.Our study confirms the effectiveness of WGS for the rapid detection of

The ongoing COVID-19 pandemic, caused by SARS-CoV-2, constitutes a tremendous global health issue. Continuous monitoring of the virus has become a cornerstone to make rational decisions on implementing societal and sanitary measures to curtail the virus spread. Additionally, emerging SARS-CoV-2 variants have increased the need for genomic surveillance to detect particular strains because of their potentially increased transmissibility, pathogenicity and immune escape. Targeted SARS-CoV-2 sequencing of wastewater has been explored as an epidemiological surveillance method for the competent authorities. Few quality criteria are however available when sequencing wastewater samples, and those available typically only pertain to constructing the consensus genome sequence. Multiple variants circulating in the population can however be simultaneously present in wastewater samples. The performance, including detection and quantification of low-abundant variants, of whole genome sequencing (WGS) of SARS-CoV-2 in wastewater samples remains largely unknown. Here, we evaluated the detection and quantification of mutations present at low abundances using the SARS-CoV-2 lineage B.1.1.7 (alpha variant) defining mutations as a case study. Real sequencing data were in silico modified by introducing mutations of interest into raw wild-type sequencing data, or by mixing wild-type and mutant raw sequencing data, to mimic wastewater samples subjected to WGS using a tiling amplicon-based targeted metagenomics approach and Illumina sequencing. As anticipated, higher variation, lower sensitivity and more false negatives, were observed at lower coverages and allelic frequencies. We found that detection of all low-frequency variants at an abundance of 10%, 5%, 3% and 1%, requires at least a sequencing coverage of 250X, 500X, 1500X and 10,000X, respectively. Although increasing variability of estimated allelic frequencies at decreasing coverages and lower allelic frequencies was observed, its impact on reliable quantification was limited. This study provides a highly sensitive low-frequency variant detection approach, which is publicly available at https://galaxy.sciensano.be, and specific recommendations for minimum sequencing coverages to detect clade-defining mutations at specific allelic frequencies.

The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of similar to 99% for all assays, except for spoligotyping, where sensitivity dropped to >90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and non-profit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.

Next-generation sequencing (NGS) is being integrated into routine clinical practice in the field of (hemato-) oncology to search for variants with diagnostic, prognostic, or therapeutic value at potentially low allelic frequencies. The complex sequencing workflows used require careful validation and continuous quality control. Participation in external quality assessments (EQA) helps laboratories evaluate their performance and guarantee the validity of tests results with the ultimate goal of ensuring high-quality patient care. Here, we describe three benchmarking trials performed during the period 2017&ndash, 2018 aiming firstly at establishing the state-of-the-art and secondly setting up a NGS-specific EQA program at the national level in the field of clinical (hemato-) oncology in Belgium. DNA samples derived from cell line mixes and artificially mutated cell lines, designed to carry variants of clinical relevance occurring in solid tumors, hematological malignancies, and BRCA1/BRCA2 genes, were sent to Belgian human genetics, anatomic pathology, and clinical biology laboratories, to be processed following routine practices, together with surveys covering technical aspects of the NGS workflows. Despite the wide variety of platforms and workflows currently applied in routine clinical practice, performance was satisfactory, since participating laboratories identified the targeted variants with success rates ranging between 93.06% and 97.63% depending on the benchmark, and few false negative or repeatability issues were identified. However, variant reporting and interpretation varied, underlining the need for further standardization. Our approach showcases the feasibility of developing and implementing EQA for routine clinical practice in the field of (hemato-) oncology, while highlighting the challenges faced.