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.

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.

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.

Assessment of the Feasibility of a Future Integrated Larger-Scale Epidemiological Study to Evaluate Health Risks of Air Pollution Episodes in Children.

Air pollution exposure can lead to exacerbation of respiratory disorders in children. Using sensitive biomarkers helps to assess the impact of air pollution on children's respiratory health and combining protein, genetic and epigenetic biomarkers gives insights on their interrelatedness. Most studies do not contain such an integrated approach and investigate these biomarkers individually in blood, although its collection in children is challenging. Our study aimed at assessing the feasibility of conducting future integrated larger-scale studies evaluating respiratory health risks of air pollution episodes in children, based on a qualitative analysis of the technical and logistic aspects of a small-scale field study involving 42 children. This included the preparation, collection and storage of non-invasive samples (urine, saliva), the measurement of general and respiratory health parameters and the measurement of specific biomarkers (genetic, protein, epigenetic) of respiratory health and air pollution exposure. Bottlenecks were identified and modifications were proposed to expand this integrated study to a higher number of children, time points and locations. This would allow for non-invasive assessment of the impact of air pollution exposure on the respiratory health of children in future larger-scale studies, which is critical for the development of policies or measures at the population level.

Strategy to Develop and Evaluate a Multiplex RT-ddPCR in Response to SARS-CoV-2 Genomic Evolution.

The worldwide emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since 2019 has highlighted the importance of rapid and reliable diagnostic testing to prevent and control the viral transmission. However, inaccurate results may occur due to false negatives (FN) caused by polymorphisms or point mutations related to the virus evolution and compromise the accuracy of the diagnostic tests. Therefore, PCR-based SARS-CoV-2 diagnostics should be evaluated and evolve together with the rapidly increasing number of new variants appearing around the world. However, even by using a large collection of samples, laboratories are not able to test a representative collection of samples that deals with the same level of diversity that is continuously evolving worldwide. In the present study, we proposed a methodology based on an in silico and in vitro analysis. First, we used all information offered by available whole-genome sequencing data for SARS-CoV-2 for the selection of the two PCR assays targeting two different regions in the genome, and to monitor the possible impact of virus evolution on the specificity of the primers and probes of the PCR assays during and after the development of the assays. Besides this first essential in silico evaluation, a minimal set of testing was proposed to generate experimental evidence on the method performance, such as specificity, sensitivity and applicability. Therefore, a duplex reverse-transcription droplet digital PCR (RT-ddPCR) method was evaluated in silico by using 154 489 whole-genome sequences of SARS-CoV-2 strains that were representative for the circulating strains around the world. The RT-ddPCR platform was selected as it presented several advantages to detect and quantify SARS-CoV-2 RNA in clinical samples and wastewater. Next, the assays were successfully experimentally evaluated for their sensitivity and specificity. A preliminary evaluation of the applicability of the developed method was performed using both clinical and wastewater samples.

Deepening of In Silico Evaluation of SARS-CoV-2 Detection RT-qPCR Assays in the Context of New Variants.

For 1 year now, the world is undergoing a coronavirus disease-2019 (COVID-19) pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The most widely used method for COVID-19 diagnosis is the detection of viral RNA by RT-qPCR with a specific set of primers and probe. It is important to frequently evaluate the performance of these tests and this can be done first by an in silico approach. Previously, we reported some mismatches between the oligonucleotides of publicly available RT-qPCR assays and SARS-CoV-2 genomes collected from GISAID and NCBI, potentially impacting proper detection of the virus. In the present study, 11 primers and probe sets investigated during the first study were evaluated again with 84,305 new SARS-CoV-2 unique genomes collected between June 2020 and January 2021. The lower inclusivity of the China CDC assay targeting the gene N has continued to decrease with new mismatches detected, whereas the other evaluated assays kept their inclusivity above 99%. Additionally, some mutations specific to new SARS-CoV-2 variants of concern were found to be located in oligonucleotide annealing sites. This might impact the strategy to be considered for future SARS-CoV-2 testing. Given the potential threat of the new variants, it is crucial to assess if they can still be correctly targeted by the primers and probes of the RT-qPCR assays. Our study highlights that considering the evolution of the virus and the emergence of new variants, an in silico (re-)evaluation should be performed on a regular basis. Ideally, this should be done for all the RT-qPCR assays employed for SARS-CoV-2 detection, including also commercial tests, although the primer and probe sequences used in these kits are rarely disclosed, which impedes independent performance evaluation.

Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection.

The current COronaVIrus Disease 2019 (COVID-19) pandemic started in December 2019. COVID-19 cases are confirmed by the detection of SARS-CoV-2 RNA in biological samples by RT-qPCR. However, limited numbers of SARS-CoV-2 genomes were available when the first RT-qPCR methods were developed in January 2020 for initial in silico specificity evaluation and to verify whether the targeted loci are highly conserved. Now that more whole genome data have become available, we used the bioinformatics tool SCREENED and a total of 4755 publicly available SARS-CoV-2 genomes, downloaded at two different time points, to evaluate the specificity of 12 RT-qPCR tests (consisting of a total of 30 primers and probe sets) used for SARS-CoV-2 detection and the impact of the virus' genetic evolution on four of them. The exclusivity of these methods was also assessed using the human reference genome and 2624 closely related other respiratory viral genomes. The specificity of the assays was generally good and stable over time. An exception is the first method developed by the China Center for Disease Control and prevention (CDC), which exhibits three primer mismatches present in 358 SARS-CoV-2 genomes sequenced mainly in Europe from February 2020 onwards. The best results were obtained for the assay of Chan et al. (2020) targeting the gene coding for the spiking protein (S). This demonstrates that our user-friendly strategy can be used for a first in silico specificity evaluation of future RT-qPCR tests, as well as verifying that the former methods are still capable of detecting circulating SARS-CoV-2 variants.

A genoserotyping system for a fast and objective identification of Salmonella serotypes commonly isolated from poultry and pork food sectors in Belgium.

Humans are mostly contaminated by Salmonella through the consumption of pork- and poultry-derived food products. Therefore, a strict monitoring of Salmonella serotypes in food-producing animals is needed to limit the transmission of the pathogen to humans. Additionally, Salmonella can lead to economic loss in the food sector. Previously, a genoserotyping method using the MOL-PCR and Luminex technology was developed for the identification of the 6 Salmonella serotypes, and their variants, subjected to an official control in the Belgian food sector. In this study, 3 additional assays using the same technology were developed for the rapid and cost-effective detection of 13 dangerous highly invasive serotypes or other serotypes frequently isolated from the Belgian poultry and pork sector, i.e. Agona, Anatum, Brandenburg, Choleraesuis, Derby, Enteritidis vaccine strains, Gallinarum var. Gallinarum/Pullorum, Livingstone, Mbandaka, Minnesota, Ohio, Rissen and Senftenberg. Moreover, the previously developed first MOL-PCR assay was improved for S. Paratyphi B and serogroup O:3 detection. Finally, a Decision Support System hosted by a web application was created for an automatic and objective interpretation of the Luminex raw data. The 3 new assays and the modifications of the first assay were validated with a 100% accuracy, using 553 Salmonella and non-Salmonella strains in total.

A multiplex oligonucleotide ligation-PCR method for the genoserotyping of common Salmonella using a liquid bead suspension assay.

Salmonella is a major pathogen having a public health and economic impact in both humans and animals. Six serotypes of the Salmonella genus are mentioned in the Belgian and European regulation as to be rapidly excluded from the food chain (EU regulation N°2160/2003, Belgian royal decree 27/04/2017). The reference method for Salmonella serotyping, including slide-agglutination and biochemical tests, is time-consuming, expensive, not always objective, and therefore does not match the fast identification criteria required by the legislation. In this study, a molecular method, using genetic markers detected by Multiplex Oligonucleotide Ligation - PCR and Luminex technology, was developed for the identification of the 6 Salmonella serotypes and their variants subjected to an official control. The resulting method was validated with the analysis of 971 Salmonella isolated from different matrixes (human, animal, food or environment) and 33 non-Salmonella strains. The results were compared with the reference identifications, achieving an accuracy of 99.7%. The cost-effective high-throughput genoserotyping assay is performed in 1 day and generates objective results, thanks to the automatic interpretation of raw data using a barcode system. In conclusion, it is fully adapted to the implementation in first line laboratories and meets the requirements of the regulation.

Development of a real-time PCR method for the genoserotyping of Salmonella Paratyphi B variant Java.

Discriminating between D-tartrate fermenting and non-fermenting strains of Salmonella enterica subsp. enterica serotype Paratyphi B is of major importance as these two variants have different pathogenic profiles. While D-tartrate non-fermenting S. Paratyphi B isolates are the causative agent of typhoid-like fever, D-tartrate fermenting isolates (also called variant Java) of the same serotype trigger the less dangerous gastroenteritis. The determination of S. Paratyphi B variants requires a time-consuming process and complex biochemical tests. Therefore, a quadruplex real-time PCR method, based on the allelic discrimination of molecular markers selected from the scientific literature and from whole genome sequencing data produced in-house, was developed in this study, to be applied to Salmonella isolates. This method was validated with the analysis of 178 S. Paratyphi B (D-tartrate fermenting and non-fermenting) and other serotypes reaching an accuracy, compared with the classical methods, of 98% for serotyping by slide agglutination and 100% for replacement of the biochemical test. The developed real-time PCR permits to save time and to obtain an accurate identification of a S. Paratyphi B serotype and its D-tartrate fermenting profile, which is needed in routine laboratories for fast and efficient diagnostics.

The use of 16S rRNA gene metagenetic monitoring of refrigerated food products for understanding the kinetics of microbial subpopulations at different storage temperatures: the example of white pudding.

In order to control food losses and wastage, monitoring the microbial diversity of food products, during processing and storage is important, as studies have highlighted the metabolic activities of some microorganisms which can lead to spoilage. Knowledge of this diversity can be greatly improved by using a metagenetic approach based on high throughput 16S rRNA gene sequencing, which enables a much higher resolution than culture-based methods. Moreover, the Jameson effect, a phenomenon described by Jameson in 1962, is often used to classify bacterial strains within an ecosystem. According to this, we have studied the bacterial microbiota of Belgian white pudding during storage at different temperatures using culture-dependent and independent methods. The product was inoculated with a mix of dominant strains previously isolated from this foodstuff at the end of its shelf life (Carnobacterium maltaromaticum, Lactobacillus fuchuensis, Lactobacillus graminis, Lactobacillus oligofermentans, Lactococcus lactis, Leuconostoc mesenteroides, Raoultella terrigena and Serratia sp.). Daily during 16days, the absolute abundance of inoculated strain was monitored by combining total count on plate agar and metagenetic analysis. The results were confirmed by qPCR analysis. The growth of each species was modelled for each temperature conditions, representative of good or bad storage practices. These data allowed the bacterial strains subdivision into three classes based on criteria of growth parameters for the studied temperature: the "dominant", the "subdominant" and the "inhibited" bacterial species, according to their maximal concentration (Nmax, log CFU/g), growth rate (µmax, 1/h) and time to reach the stationary phase (TRSP, days). Thereby, depending on the storage conditions, these data have permitted to follow intrinsically the evolution of each strain on the bacterial ecosystem of Belgian white pudding. Interestingly, it has shown that the reliability of the Jameson effect can be discussed. For example, at 4°C when Lactococcus lactis and Serratia sp. stopped growth at day 12, at the same time Carnobacterium maltaromaticum reached its maximal concentration and entered its stationary phase. In opposition to this, it can be noticed that in the same condition, the "sub-dominant" organisms continued their growth independently of the "dominant" species behaviour. In this case, the Jameson effect was not illustrated. This pattern is described for all storage conditions with the same strain classifications. These results highlighted the importance of combining metagenetic analysis and classical methods, with modelling, to offer a new tool for studying the evolution of microorganisms present in perishable food within different environmental conditions.

Cdc42 and Rac1 activity is reduced in human pheochromocytoma and correlates with FARP1 and ARHGEF1 expression.

Among small GTPases from the Rho family, Cdc42, RAC, and Rho are well known to mediate a large variety of cellular processes linked with cancer biology through their ability to cycle between an inactive (GDP-bound) and an active (GTP-bound) state. Guanine nucleotide exchange factors (GEFs) stimulate the exchange of GDP for GTP to generate the activated form, whereas the GTPase-activating proteins (GAPs) catalyze GTP hydrolysis, leading to the inactivated form. Modulation of Rho GTPase activity following altered expression of RHO-GEFs and/or RHO-GAPs has already been reported in various human tumors. However, nothing is known about the Rho GTPase activity or the expression of their regulators in human pheochromocytomas, a neuroendocrine tumor (NET) arising from chromaffin cells of the adrenal medulla. In this study, we demonstrate, through an ELISA-based activity assay, that Rac1 and Cdc42 activities decrease in human pheochromocytomas (PCCs) compared with the matched adjacent non-tumor tissue. Furthermore, through quantitative mass spectrometry (MS) approaches, we show that the expression of two RHO-GEF proteins, namely ARHGEF1 and FARP1, is significantly reduced in tumors compared with matched non-tumor tissue, whereas ARHGAP36 expression is increased. Moreover, siRNA-based knockdown of ARHGEF1 and FARP1 in PC12 cells leads to a significant inhibition of Rac1 and Cdc42 activities, respectively. Finally, a principal component analysis (PCA) of our dataset was able to discriminate PCC from non-tumor tissue and indicates a close correlation between Cdc42/Rac1 activity and FARP1/ARHGEF1 expression. Altogether, our findings reveal for the first time the importance of modulation of Rho GTPase activities and expression of their regulators in human PCCs.