Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes.

Metagenomic sequencing is a promising method that has the potential to revolutionize the world of pathogen detection and antimicrobial resistance (AMR) surveillance in food-producing environments. However, the analysis of the huge amount of data obtained requires performant bioinformatics tools and databases, with intuitive and straightforward interpretation. In this study, based on long-read metagenomics data of chicken fecal samples with a spike-in mock community, we proposed confidence levels for taxonomic identification and AMR gene detection, with interpretation guidelines, to help with the analysis of the output data generated by KMA, a popular k-mer read alignment tool. Additionally, we demonstrated that the completeness and diversity of the genomes present in the reference databases are key parameters for accurate and easy interpretation of the sequencing data. Finally, we explored whether KMA, in a two-step procedure, can be used to link the detected AMR genes to their bacterial host chromosome, both detected within the same long-reads. The confidence levels were successfully tested on 28 metagenomics datasets which were obtained with sequencing of real and spiked samples from fecal (chicken, pig, and buffalo) or food (minced beef and food enzyme products) origin. The methodology proposed in this study will facilitate the analysis of metagenomics sequencing datasets for KMA users. Ultimately, this will contribute to improvements in the rapid diagnosis and surveillance of pathogens and AMR genes in food-producing environments, as prioritized by the EU.

Strain-level characterization of foodborne pathogens without culture enrichment for outbreak investigation using shotgun metagenomics facilitated with nanopore adaptive sampling.

Introduction: Shotgun metagenomics has previously proven effective in the investigation of foodborne outbreaks by providing rapid and comprehensive insights into the microbial contaminant. However, culture enrichment of the sample has remained a prerequisite, despite the potential impact on pathogen detection resulting from the growth competition. To circumvent the need for culture enrichment, we explored the use of adaptive sampling using various databases for a targeted nanopore sequencing, compared to shotgun metagenomics alone. Methods: The adaptive sampling method was first tested on DNA of mashed potatoes mixed with DNA of a Staphylococcus aureus strain previously associated with a foodborne outbreak. The selective sequencing was used to either deplete the potato sequencing reads or enrich for the pathogen sequencing reads, and compared to a shotgun sequencing. Then, living S. aureus were spiked at 105 CFU into 25 g of mashed potatoes. Three DNA extraction kits were tested, in combination with enrichment using adaptive sampling, following whole genome amplification. After data analysis, the possibility to characterize the contaminant with the different sequencing and extraction methods, without culture enrichment, was assessed. Results: Overall, the adaptive sampling outperformed the shotgun sequencing. While the use of a host removal DNA extraction kit and targeted sequencing using a database of foodborne pathogens allowed rapid detection of the pathogen, the most complete characterization was achieved when using solely a database of S. aureus combined with a conventional DNA extraction kit, enabling accurate placement of the strain on a phylogenetic tree alongside outbreak cases. Discussion: This method shows great potential for strain-level analysis of foodborne outbreaks without the need for culture enrichment, thereby enabling faster investigations and facilitating precise pathogen characterization. The integration of adaptive sampling with metagenomics presents a valuable strategy for more efficient and targeted analysis of microbial communities in foodborne outbreaks, contributing to improved food safety and public health.

Closing the gap: Oxford Nanopore Technologies R10 sequencing allows comparable results to Illumina sequencing for SNP-based outbreak investigation of bacterial pathogens.

Whole-genome sequencing has become the method of choice for bacterial outbreak investigation, with most clinical and public health laboratories currently routinely using short-read Illumina sequencing. Recently, long-read Oxford Nanopore Technologies (ONT) sequencing has gained prominence and may offer advantages over short-read sequencing, particularly with the recent introduction of the R10 chemistry, which promises much lower error rates than the R9 chemistry. However, limited information is available on its performance for bacterial single-nucleotide polymorphism (SNP)-based outbreak investigation. We present an open-source workflow, Prokaryotic Awesome variant Calling Utility (PACU) (https://github.com/BioinformaticsPlatformWIV-ISP/PACU), for constructing SNP phylogenies using Illumina and/or ONT R9/R10 sequencing data. The workflow was evaluated using outbreak data sets of Shiga toxin-producing Escherichia coli and Listeria monocytogenes by comparing ONT R9 and R10 with Illumina data. The performance of each sequencing technology was evaluated not only separately but also by integrating samples sequenced by different technologies/chemistries into the same phylogenomic analysis. Additionally, the minimum sequencing time required to obtain accurate phylogenetic results using nanopore sequencing was evaluated. PACU allowed accurate identification of outbreak clusters for both species using all technologies/chemistries, but ONT R9 results deviated slightly more from the Illumina results. ONT R10 results showed trends very similar to Illumina, and we found that integrating data sets sequenced by either Illumina or ONT R10 for different isolates into the same analysis produced stable and highly accurate phylogenomic results. The resulting phylogenies for these two outbreaks stabilized after ~20 hours of sequencing for ONT R9 and ~8 hours for ONT R10. This study provides a proof of concept for using ONT R10, either in isolation or in combination with Illumina, for rapid and accurate bacterial SNP-based outbreak investigation.

Pilot market surveillance of GMM contaminations in alpha-amylase food enzyme products: A detection strategy strengthened by a newly developed qPCR method targeting a GM Bacillus licheniformis producing alpha-amylase.

Using high-throughput metagenomics on commercial microbial fermentation products, DNA from a new unauthorized genetically modified microorganism (GMM), namely the GM B. licheniformis strain producing alpha-amylase (GMM alpha-amylase2), was recently discovered and characterized. On this basis, a new qPCR method targeting an unnatural association of sequences specific to the GMM alpha-amylase2 strain was designed and developed in this study, allowing to strengthen the current GMM detection strategy. The performance of the newly developed qPCR method was assessed for its specificity and sensitivity to comply with the minimum performance requirements established by the European Network of GMO Laboratories for GMO analysis. Moreover, the transferability of the in house validated qPCR method was demonstrated. Finally, its applicability was confirmed by a pilot market surveillance of GMM contaminations conducted for the first time on 40 alpha-amylase food enzyme products labelled as containing alpha-amylase. This pilot market surveillance allowed also to highlight numerous contaminations with GMM alpha-amylase2, including frequent cross-contaminations with other GMM strains previously characterized. In addition, the presence of full-length AMR genes, raising health concerns, was also reported.

Development of a portable on-site applicable metagenomic data generation workflow for enhanced pathogen and antimicrobial resistance surveillance.

Rapid, accurate and comprehensive diagnostics are essential for outbreak prevention and pathogen surveillance. Real-time, on-site metagenomics on miniaturized devices, such as Oxford Nanopore Technologies MinION sequencing, could provide a promising approach. However, current sample preparation protocols often require substantial equipment and dedicated laboratories, limiting their use. In this study, we developed a rapid on-site applicable DNA extraction and library preparation approach for nanopore sequencing, using portable devices. The optimized method consists of a portable mechanical lysis approach followed by magnetic bead-based DNA purification and automated sequencing library preparation, and resulted in a throughput comparable to a current optimal, laboratory-based protocol using enzymatic digestion to lyse cells. By using spike-in reference communities, we compared the on-site method with other workflows, and demonstrated reliable taxonomic profiling, despite method-specific biases. We also demonstrated the added value of long-read sequencing by recovering reads containing full-length antimicrobial resistance genes, and attributing them to a host species based on the additional genomic information they contain. Our method may provide a rapid, widely-applicable approach for microbial detection and surveillance in a variety of on-site settings.

Comparison of 6 DNA extraction methods for isolation of high yield of high molecular weight DNA suitable for shotgun metagenomics Nanopore sequencing to detect bacteria.

BACKGROUND: Oxford Nanopore Technologies (ONT) offers an accessible platform for long-read sequencing, which improves the reconstruction of genomes and helps to resolve complex genomic contexts, especially in the case of metagenome analysis. To take the best advantage of long-read sequencing, DNA extraction methods must be able to isolate pure high molecular weight (HMW) DNA from complex metagenomics samples, without introducing any bias. New methods released on the market, and protocols developed at the research level, were specifically designed for this application and need to be assessed. RESULTS: In this study, with different bacterial cocktail mixes, analyzed as pure or spiked in a synthetic fecal matrix, we evaluated the performances of 6 DNA extraction methods using various cells lysis and purification techniques, from quick and easy, to more time-consuming and gentle protocols, including a portable method for on-site application. In addition to the comparison of the quality, quantity and purity of the extracted DNA, the performance obtained when doing Nanopore sequencing on a MinION flow cell was also tested. From the obtained results, the Quick-DNA HMW MagBead Kit (Zymo Research) was selected as producing the best yield of pure HMW DNA. Furthermore, this kit allowed an accurate detection, by Nanopore sequencing, of almost all the bacterial species present in a complex mock community. CONCLUSION: Amongst the 6 tested methods, the Quick-DNA HMW MagBead Kit (Zymo Research) was considered as the most suitable for Nanopore sequencing and would be recommended for bacterial metagenomics studies using this technology.

Whole-Genome Sequencing-Based Screening of MRSA in Patients and Healthcare Workers in Public Hospitals in Benin.

Methicillin-resistant Staphylococcus aureus (MRSA) constitutes a serious public health concern, with a considerable impact on patients' health, and substantial healthcare costs. In this study, patients and healthcare workers (HCWs) from six public hospitals in Benin were screened for MRSA. Strains were identified as MRSA using conventional microbiological methods in Benin, and confirmed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry in Belgium. Whole-genome sequencing (WGS) was used on the confirmed MRSA isolates, to characterize their genomic content and study their relatedness. Amongst the 305 isolates (304 wound swabs and 61 nasal swabs) that were collected from patients and HCWs, we detected 32 and 15 cases of MRSA, respectively. From this collection, 27 high-quality WGS datasets were obtained, which carried numerous genes and mutations associated with antimicrobial resistance. The mecA gene was detected in all the sequenced isolates. These isolates were assigned to five sequence types (STs), with ST8 (55.56%, n = 15/27), ST152 (18.52%, n = 5/27), and ST121 (18.52%, n = 5/27) being the most common. These 27 isolates carried multiple virulence genes, including the genes encoding the Panton-Valentine leukocidin toxin (48.15%, n = 13/27), and the tst gene (29.63%, n = 8/27), associated with toxic shock syndrome. This study highlights the need to implement a multimodal strategy for reducing the risk of the cross-transmission of MRSA in hospitals.

Transforming Shiga toxin-producing Escherichia coli surveillance through whole genome sequencing in food safety practices.

Introduction: Shiga toxin-producing Escherichia coli (STEC) is a gastrointestinal pathogen causing foodborne outbreaks. Whole Genome Sequencing (WGS) in STEC surveillance holds promise in outbreak prevention and confinement, in broadening STEC epidemiology and in contributing to risk assessment and source attribution. However, despite international recommendations, WGS is often restricted to assist outbreak investigation and is not yet fully implemented in food safety surveillance across all European countries, in contrast to for example in the United States. Methods: In this study, WGS was retrospectively applied to isolates collected within the context of Belgian food safety surveillance and combined with data from clinical isolates to evaluate its benefits. A cross-sector WGS-based collection of 754 strains from 1998 to 2020 was analyzed. Results: We confirmed that WGS in food safety surveillance allows accurate detection of genomic relationships between human cases and strains isolated from food samples, including those dispersed over time and geographical locations. Identifying these links can reveal new insights into outbreaks and direct epidemiological investigations to facilitate outbreak management. Complete WGS-based isolate characterization enabled expanding epidemiological insights related to circulating serotypes, virulence genes and antimicrobial resistance across different reservoirs. Moreover, associations between virulence genes and severe disease were determined by incorporating human metadata into the data analysis. Gaps in the surveillance system were identified and suggestions for optimization related to sample centralization, harmonizing isolation methods, and expanding sampling strategies were formulated. Discussion: This study contributes to developing a representative WGS-based collection of circulating STEC strains and by illustrating its benefits, it aims to incite policymakers to support WGS uptake in food safety surveillance.

Retrospective surveillance of viable Bacillus cereus group contaminations in commercial food and feed vitamin B2 products sold on the Belgian market using whole-genome sequencing.

Bacillus cereus is a spore-forming bacterium that occurs as a contaminant in food and feed, occasionally resulting in food poisoning through the production of various toxins. In this study, we retrospectively characterized viable B. cereus sensu lato (s.l.) isolates originating from commercial vitamin B2 feed and food additives collected between 2016 and 2022 by the Belgian Federal Agency for the Safety of the Food Chain from products sold on the Belgian market. In total, 75 collected product samples were cultured on a general medium and, in case of bacterial growth, two isolates per product sample were collected and characterized using whole-genome sequencing (WGS) and subsequently characterized in terms of sequence type (ST), virulence gene profile, antimicrobial resistance (AMR) gene profile, plasmid content, and phylogenomic relationships. Viable B. cereus was identified in 18 of the 75 (24%) tested products, resulting in 36 WGS datasets, which were classified into eleven different STs, with ST165 (n = 10) and ST32 (n = 8) being the most common. All isolates carried multiple genes encoding virulence factors, including cytotoxin K-2 (52.78%) and cereulide (22.22%). Most isolates were predicted to be resistant to beta-lactam antibiotics (100%) and fosfomycin (88.89%), and a subset was predicted to be resistant to streptothricin (30.56%). Phylogenomic analysis revealed that some isolates obtained from different products were closely related or even identical indicating a likely common origin, whereas for some products the two isolates obtained did not show any close relationship to each other or other isolates found in other products. This study reveals that potentially pathogenic and drug-resistant B. cereus s.l. can be present in food and feed vitamin B2 additives that are commercially available, and that more research is warranted to assess whether their presence in these types of products poses a threat to consumers.

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.

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.

Targeted High-Throughput Sequencing Enables the Detection of Single Nucleotide Variations in CRISPR/Cas9 Gene-Edited Organisms.

Similar to genetically modified organisms (GMOs) produced by classical genetic engineering, gene-edited (GE) organisms and their derived food/feed products commercialized on the European Union market fall within the scope of European Union Directive 2001/18/EC. Consequently, their control in the food/feed chain by GMO enforcement laboratories is required by the competent authorities to guarantee food/feed safety and traceability (2003/1829/EC; 2003/1830/EC). However, their detection is potentially challenging at both the analytical and interpretation levels since this requires methodological approaches that can target and detect a specific single nucleotide variation (SNV) introduced into a GE organism. In this study, we propose a targeted high-throughput sequencing approach, including (i) a prior PCR-based enrichment step to amplify regions of interest, (ii) a sequencing step, and (iii) a data analysis methodology to identify SNVs of interest. To investigate if the performance of this targeted high-throughput sequencing approach is compatible with the performance criteria used in the GMO detection field, several samples containing different percentages of a GE rice line carrying a single adenosine insertion in OsMADS26 were prepared and analyzed. The SNV of interest in samples containing the GE rice line could successfully be detected, both at high and low percentages. No impact related to food processing or to the presence of other crop species was observed. The present proof-of-concept study has allowed us to deliver the first experimental-based evidence indicating that the proposed targeted high-throughput sequencing approach may constitute, in the future, a specific and sensitive tool to support the safety and traceability of the food/feed chain regarding GE plants carrying SNVs.

Metagenomic Characterization of Multiple Genetically Modified Bacillus Contaminations in Commercial Microbial Fermentation Products.

Genetically modified microorganisms (GMM) are frequently employed for manufacturing microbial fermentation products such as food enzymes or vitamins. Although the fermentation product is required to be pure, GMM contaminations have repeatedly been reported in numerous commercial microbial fermentation produce types, leading to several rapid alerts at the European level. The aim of this study was to investigate the added value of shotgun metagenomic high-throughput sequencing to confirm and extend the results of classical analysis methods for the genomic characterization of unauthorized GMM. By combining short- and long-read metagenomic sequencing, two transgenic constructs were characterized, with insertions of alpha-amylase genes originating from B. amyloliquefaciens and B. licheniformis, respectively, and a transgenic construct with a protease gene insertion originating from B. velezensis, which were all present in all four investigated samples. Additionally, the samples were contaminated with up to three unculturable Bacillus strains, carrying genetic modifications that may hamper their ability to sporulate. Moreover, several samples contained viable Bacillus strains. Altogether these contaminations constitute a considerable load of antimicrobial resistance genes, that may represent a potential public health risk. In conclusion, our study showcases the added value of metagenomics to investigate the quality and safety of complex commercial microbial fermentation products.

Metagenomics to Detect and Characterize Viruses in Food Samples at Genome Level? Lessons Learnt from a Norovirus Study.

In this proof-of-concept study on food contaminated with norovirus, we investigated the feasibility of metagenomics as a new method to obtain the whole genome sequence of the virus and perform strain level characterization but also relate to human cases in order to resolve foodborne outbreaks. We tested several preparation methods to determine if a more open sequencing approach, i.e., shotgun metagenomics, or a more targeted approach, including hybrid capture, was the most appropriate. The genetic material was sequenced using Oxford Nanopore technologies with or without adaptive sampling, and the data were analyzed with an in-house bioinformatics workflow. We showed that a viral genome sequence could be obtained for phylogenetic analysis with shotgun metagenomics if the contamination load was sufficiently high or after hybrid capture for lower contamination. Relatedness to human cases goes well beyond the results obtained with the current qPCR methods. This workflow was also tested on a publicly available dataset of food spiked with norovirus and hepatitis A virus. This allowed us to prove that we could detect even fewer genome copies and two viruses present in a sample using shotgun metagenomics. We share the lessons learnt on the satisfactory and unsatisfactory results in an attempt to advance the field.

A general approach to identify low-frequency variants within influenza samples collected during routine surveillance.

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.

Whole-Genome Sequence Approach and Phylogenomic Stratification Improve the Association Analysis of Mutations With Patient Data in Influenza Surveillance.

Each year, seasonal influenza results in high mortality and morbidity. The current classification of circulating influenza viruses is mainly focused on the hemagglutinin gene. Whole-genome sequencing (WGS) enables tracking mutations across all influenza segments allowing a better understanding of the epidemiological effects of intra- and inter-seasonal evolutionary dynamics, and exploring potential associations between mutations across the viral genome and patient's clinical data. In this study, mutations were identified in 253 Influenza A (H3N2) clinical isolates from the 2016-2017 influenza season in Belgium. As a proof of concept, available patient data were integrated with this genomic data, resulting in statistically significant associations that could be relevant to improve the vaccine and clinical management of infected patients. Several mutations were significantly associated with the sampling period. A new approach was proposed for exploring mutational effects in highly diverse Influenza A (H3N2) strains through considering the viral genetic background by using phylogenetic classification to stratify the samples. This resulted in several mutations that were significantly associated with patients suffering from renal insufficiency. This study demonstrates the usefulness of using WGS data for tracking mutations across the complete genome and linking these to patient data, and illustrates the importance of accounting for the viral genetic background in association studies. A limitation of this association study, especially when analyzing stratified groups, relates to the number of samples, especially in the context of national surveillance of small countries. Therefore, we investigated if international databases like GISAID may help to verify whether observed associations in the Belgium A (H3N2) samples, could be extrapolated to a global level. This work highlights the need to construct international databases with both information of viral genome sequences and patient data.

Detection and identification of authorized and unauthorized GMOs using high-throughput sequencing with the support of a sequence-based GMO database.

The increasing number and diversity of genetically modified organisms (GMOs) for the food and feed market calls for the development of advanced methods for their detection and identification. This issue can be addressed by next generation sequencing (NGS). However, the efficiency of NGS-based strategies depends on the availability of bioinformatic methods to find sequences of the transgenic insert and junction regions, which is a challenging topic. To facilitate this task, we have developed Nexplorer, a sequence-based database in which annotated sequences of GM events are stored in a structured, searchable and extractable format. As a proof of concept, we have developed a methodology for the analysis of sequencing data of DNA walking libraries of samples containing GMOs using the database. The efficiency of the method has been tested on datasets representing various scenarios that can be encountered in routine GMO analysis. Database-guided analysis allowed obtaining detailed and reliable information with limited hands-on time. As the database allows for efficient analysis of NGS data, it paves the way for the use of NGS sequencing technology to aid routine detection and identification of GMO.

Population Analysis of O26 Shiga Toxin-Producing Escherichia coli Causing Hemolytic Uremic Syndrome in Italy, 1989-2020, Through Whole Genome Sequencing.

Shiga toxin-producing Escherichia coli (STEC) belonging to the O26 serogroup represent an important cause of Hemolitic Uremic Syndrome (HUS) in children worldwide. The localization of STEC virulence genes on mobile genetic elements allowed the emergence of clones showing different assets of this accessory genomic fraction. A novel O26 STEC clone belonging to Sequence Type (ST) 29 and harboring stx2a, ehxA and etpD plasmid-borne genes has emerged and spread in Europe since the mid-1990s, while another ST29 clone positive for stx2d and lacking plasmid-borne virulence genes was recently described as emerging in France. In Italy, O26 has been the most frequently detected STEC serogroup from HUS cases since the late 1990s. In this study we describe the genomic characterization and population structure of 144 O26 STEC strains isolated from human sources in Italy in the period 1989-2020. A total of 89 strains belonged to ST21, 52 to ST29, two to ST396 and one to ST4944. ST29 strains started to be isolated from 1999. 24 strains were shown to harbour stx1a, alone (n=20) or in combination with stx2a (n=4). The majority of the strains (n=118) harbored stx2a genes only and the two ST396 strains harbored stx2d. A Hierarchical Clustering on Principal Components (HCPC) analysis, based on the detection of accessory virulence genes, antimicrobial resistance (AMR) genes and plasmid replicons, classified the strains in seven clusters identified with numbers from 1 to 7, containing two, 13, 39, 63, 16, 10 and one strain, respectively. The majority of the genetic features defining the clusters corresponded to plasmid-borne virulence genes, AMR genes and plasmid replicons, highlighting specific assets of plasmid-borne features associated with different clusters. Core genome Multi Locus Sequence Typing grouped ST21 and ST29 strains in three clades each, with each ST29 clade exactly corresponding to one HCPC cluster. Our results showed high conservation of either the core or the accessory genomic fraction in populations of ST29 O26 STEC, differently from what observed in ST21 strains, suggesting that a different selective pressure could drive the evolution of different populations of these pathogens possibly involving different ecological niches.

Retrospective evaluation of routine whole genome sequencing of Mycobacterium tuberculosis at the Belgian National Reference Center, 2019.

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.

Whole-Genome Sequencing-Based Antimicrobial Resistance Characterization and Phylogenomic Investigation of 19 Multidrug-Resistant and Extended-Spectrum Beta-Lactamase-Positive Escherichia coli Strains Collected From Hospital Patients in Benin in 2019.

The increasing worldwide prevalence of extended-spectrum beta-lactamase (ESBL) producing Escherichia coli constitutes a serious threat to global public health. Surgical site infections are associated with high morbidity and mortality rates in developing countries, fueled by the limited availability of effective antibiotics. We used whole-genome sequencing (WGS) to evaluate antimicrobial resistance and the phylogenomic relationships of 19 ESBL-positive E. coli isolates collected from surgical site infections in patients across public hospitals in Benin in 2019. Isolates were identified by MALDI-TOF mass spectrometry and phenotypically tested for susceptibility to 16 antibiotics. Core-genome multi-locus sequence typing and single-nucleotide polymorphism-based phylogenomic methods were used to investigate the relatedness between samples. The broader phylogenetic context was characterized through the inclusion of publicly available genome data. Among the 19 isolates, 13 different sequence types (STs) were observed, including ST131 (n = 2), ST38 (n = 2), ST410 (n = 2), ST405 (n = 2), ST617 (n = 2), and ST1193 (n = 2). The bla CTX-M-15 gene encoding ESBL resistance was found in 15 isolates (78.9%), as well as other genes associated with ESBL, such as bla OXA-1 (n = 14) and bla TEM-1 (n = 9). Additionally, we frequently observed genes encoding resistance against aminoglycosides [aac-(6')-Ib-cr, n = 14], quinolones (qnrS1 , n = 4), tetracyclines [tet(B), n = 14], sulfonamides (sul2, n = 14), and trimethoprim (dfrA17, n = 13). Nonsynonymous chromosomal mutations in the housekeeping genes parC and gyrA associated with resistance to fluoroquinolones were also detected in multiple isolates. Although the phylogenomic investigation did not reveal evidence of hospital-acquired transmissions, we observed two very similar strains collected from patients in different hospitals. By characterizing a set of multidrug-resistant isolates collected from a largely unexplored environment, this study highlights the added value for WGS as an effective early warning system for emerging pathogens and antimicrobial resistance.