Integrated DNA walking system to characterize a broad spectrum of GMOs in food/feed matrices

Background: In order to provide a system fully integrated with qPCR screening, usually used in GMO routine analysis, as well as being able to detect, characterize and identify a broad spectrum of GMOs in food/feed matrices, two bidirectional DNA walking methods targeting p35S or tNOS, the most common transgenic elements found in GM crops, were developed. These newly developed DNA walking methods are completing the previously implemented DNA walking method targeting the t35S pCAMBIA element. Results: First, the newly developed DNA walking methods, anchored on the sequences used for the p35S or tNOS qPCR screening, were tested on Bt rice that contains these two transgenic elements. Second, the methods were assessed on a maize sample containing a low amount of the GM MON863 event, representing a more complex matrix in terms of genome size and sensitivity. Finally, to illustrate its applicability in GMO routine analysis by enforcement laboratories, the entire workflow of the integrated strategy, including qPCR screening to detect the potential presence of GMOs and the subsequent DNA walking methods to characterize and identify the detected GMOs, was applied on a GeMMA Scheme Proficiency Test matrix. Via the characterization of the transgene flanking region between the transgenic cassette and the plant genome as well as of a part of the transgenic cassette, the presence of GMOs was properly confirmed or infirmed in all tested samples. Conclusion: Due to their simple procedure and their short time-frame to get results, the developed DNA walking methods proposed here can be easily implemented in GMO routine analysis by the enforcement laboratories. In providing crucial information about the transgene flanking regions and/or the transgenic cassettes, this DNA walking strategy is a key molecular tool to prove the presence of GMOs in any given food/feed matrix

Next-generation sequencing : an eye-opener for the surveillance of antiviral resistance in influenza

Next-generation sequencing (NGS) can enable a more effective response to a wide range of communicable disease threats, such as influenza, which is one of the leading causes of human morbidity and mortality worldwide. After vaccination, antivirals are the second line of defense against influenza. The use of currently available antivirals can lead to antiviral resistance mutations in the entire influenza genome. Therefore, the methods to detect these mutations should be developed and implemented. In this Opinion, we assess how NGS could be implemented to detect drug resistance mutations in clinical influenza virus isolates

Discrimination of three genetically close Aspergillus species by using high resolution melting analysis applied to indoor air as case study.

peer reviewedBACKGROUND: Indoor air pollution caused by fungal contamination is suspected to have a public health impact. Monitoring of the composition of the indoor airborne fungal contaminants is therefore important. To avoid problems linked to culture-dependent protocols, molecular methods are increasingly being proposed as an alternative. Among these molecular methods, the polymerase chain reaction (PCR) and the real-time PCR are the most frequently used tools for indoor fungal detection. However, even if these tools have demonstrated their appropriate performance, some of them are not able to discriminate between species which are genetically close. A solution to this could be the use of a post-qPCR high resolution melting (HRM) analysis, which would allow the discrimination of these species based on the highly accurate determination of the difference in melting temperature of the obtained amplicon. In this study, we provide a proof-of-concept for this approach, using a dye adapted version of our previously developed qPCR SYBR(R)Green method to detect Aspergillus versicolor in indoor air, an important airborne fungus in terms of occurrence and cause of health problems. Despite the good performance observed for that qPCR method, no discrimination could previously be made between A. versicolor, Aspergillus creber and Aspergillus sydowii. METHODS: In this study, we developed and evaluated an HRM assay for the discrimination between A. versicolor, Aspergillus creber and Aspergillus sydowii. RESULTS: Using HRM analysis, the discrimination of the 3 Aspergillus species could be made. No false positive, nor false negatives were observed during the performance assessment including 20 strains of Aspergillus. The limit of detection was determined for each species i.e., 0.5 pg of gDNA for A. creber and A. sydowii, and 0.1 pg of gDNA for A. versicolor. The HRM analysis was also successfully tested on environmental samples. CONCLUSION: We reported the development of HRM tools for the discrimination of A. versicolor, A. creber and A. sydowii. However, this study could be considered as a study case demonstrating that HRM based on existing qPCR assays, allows a more accurate identification of indoor air contaminants. This contributes to an improved insight in the diversity of indoor airborne fungi and hence, eventually in the causal link with health problems

Strategy for the identification of micro-organisms producing food and feed products : bacteria producing food enzymes as study case

Recent European regulations require safety assessments of food enzymes (FE) before their commercialization. FE are mainly produced by micro-organisms, whose viable strains nor associated DNA can be present in the final products. Currently, no strategy targeting such impurities exists in enforcement laboratories. Therefore, a generic strategy of first line screening was developed to detect and identify, through PCR amplification and sequencing of the 16S-rRNA gene, the potential presence of FE producing bacteria in FE preparations. First, the specificity was verified using all microbial species reported to produce FE. Second, an in-house database, with 16S reference sequences from bacteria producing FE, was constructed for their fast identification through blast analysis. Third, the sensitivity was assessed on a spiked FE preparation. Finally, the applicability was verified using commercial FE preparations. Using straightforward PCR amplifications, Sanger sequencing and blast analysis, the proposed strategy was demonstrated to be convenient for implementation in enforcement laboratories

Current and new approaches in GMO detection: challenges and solutions

In many countries, genetically modified organisms (GMO) legislations have been established in order to guarantee the traceability of food/feed products on the market as well as to protect the consumer freedom of choice. Therefore, several GMO detection strategies, mainly based on DNA, have been developed to implement these legislations. Due to its numerous advantages, the quantitative PCR (qPCR) is the method of choice for the enforcement laboratories in GMO routine analysis. However, given the increasing number and diversity of GMO developed and put on the market around the world, some technical hurdles could be encountered with the qPCR technology, mainly owed to its inherent properties. To address these challenges, alternative GMO detection methods have been developed, allowing faster detections of single GM target (e.g. Loop-mediated isothermal amplification), simultaneous detections of multiple GM targets (e.g. PCR capillary gel electrophoresis, microarray and Luminex®), more accurate quantification of GM targets (e.g. digital PCR) or characterization of partially known (e.g. DNA walking and Next Generation Sequencing (NGS)) or unknown (e.g. NGS) GMO. The benefits and drawbacks of these methods are discussed in this review

Isolation of Burkholderia pseudomallei from a pet green iguana, Belgium

We isolated Burkholderia pseudomallei, the causative agent of melioidosis, from liver granulomas of a pet green iguana (Iguana iguana) in Belgium. This case highlights a risk for imported green iguanas acting as a reservoir for introduction of this high-threat, zoonotic pathogen into nonendemic regions

Strain-level metagenomic data analysis of enriched in vitro and in silico spiked food samples : paving the way towards a culture-free foodborne outbreak investigation using STEC as a case study

Culture-independent diagnostics, such as metagenomic shotgun sequencing of food samples, could not only reduce the turnaround time of samples in an outbreak investigation, but also allow the detection of multi-species and multi-strain outbreaks. For successful foodborne outbreak investigation using a metagenomic approach, it is, however, necessary to bioinformatically separate the genomes of individual strains, including strains belonging to the same species, present in a microbial community, which has up until now not been demonstrated for this application. The current work shows the feasibility of strain-level metagenomics of enriched food matrix samples making use of data analysis tools that classify reads against a sequence database. It includes a brief comparison of two database-based read classification tools, Sigma and Sparse, using a mock community obtained by in vitro spiking minced meat with a Shiga toxin-producing Escherichia coli (STEC) isolate originating from a described outbreak. The more optimal tool Sigma was further evaluated using in silico simulated metagenomic data to explore the possibilities and limitations of this data analysis approach. The performed analysis allowed us to link the pathogenic strains from food samples to human isolates previously collected during the same outbreak, demonstrating that the metagenomic approach could be applied for the rapid source tracking of foodborne outbreaks. To our knowledge, this is the first study demonstrating a data analysis approach for detailed characterization and phylogenetic placement of multiple bacterial strains of one species from shotgun metagenomic WGS data of an enriched food sample

First detection of a plasmid located carbapenem resistant bla(VIM-1) gene in E. coli isolated from meat products at retail in Belgium in 2015

Carbapenemase-producing Enterobacteriaceae (CPE) confer resistance to antibiotics that are of critical importance to human medicine. There have only been a few reported cases of CPEs in the European food chain. We report the first detection of a carbapenemase-producing Escherichia coli (ST 5869) in the Belgian food chain. Our aim was to characterize the origin of the carbapenem resistance in the E. coli isolate. The isolate was detected during the screening of 178 minced pork samples and was shown to contain the carbapenemase gene bla(VIM-1) by PCR and Sanger sequencing. Whole genome short and long read sequencing (MiSeq and MinION) was performed to characterize the isolate. With a hybrid assembly we reconstructed a 190,205 bp IncA/C2 plasmid containing bla(VIM-1) (S15FP06257_p), in addition to other critically important resistance genes. This plasmid showed only low similarity to plasmids containing bla(VIM-1) previously reported in Germany. Moreover, no sequences existed in the NCBI nucleotide database that completely covered S15FP06257_p. Analysis of the bla(VIM-1) gene cassette demonstrated that it likely originated from an integron of a Klebsiella plasmid reported previously in a clinical isolate in Europe, suggesting that the meat could have been contaminated by human handling in one of the steps of the food chain. This study shows the relevance of fully reconstructing plasmids to characterize their genetic content and to allow source attribution. This is especially important in view of the potential risk of antimicrobial resistance gene transmission through mobile elements as was reported here for the of public health concern bla(VIM-1)

Perceived utility and feasibility of pathogen genomics for public health practice : a survey among public health professionals working in the field of infectious diseases, Belgium, 2019

Background Pathogen genomics is increasingly being translated from the research setting into the activities of public health professionals operating at different levels. This survey aims to appraise the literacy level and gather the opinions of public health experts and allied professionals working in the field of infectious diseases in Belgium concerning the implementation of next-generation sequencing (NGS) in public health practice. Methods In May 2019, Belgian public health and healthcare professionals were invited to complete an online survey containing eight main topics including background questions, general attitude towards pathogen genomics for public health practice and main concerns, genomic literacy, current and planned NGS activities, place of NGS in diagnostic microbiology pathways, data sharing obstacles, end-user requirements, and key drivers for the implementation of NGS. Descriptive statistics were used to report on the frequency distribution of multiple choice responses whereas thematic analysis was used to analyze free text responses. A multivariable logistic regression model was constructed to identify important predictors for a positive attitude towards the implementation of pathogen genomics in public health practice. Results 146 out of the 753 invited public health professionals completed the survey. 63% of respondents indicated that public health agencies should be using genomics to understand and control infectious diseases. Having a high level of expertise in the field of pathogen genomics was the strongest predictor of a positive attitude (OR = 4.04, 95% CI = 1.11 – 17.23). A significantly higher proportion of data providers indicated to have followed training in the field of pathogen genomics compared to data end-users (p < 0.001). Overall, 79% of participants expressed interest in receiving further training. Main concerns were related to the cost of sequencing technologies, data sharing, data integration, interdisciplinary working, and bioinformatics expertise. Conclusions Belgian health professionals expressed favorable views about implementation of pathogen genomics in their work activities related to infectious disease surveillance and control. They expressed the need for suitable training initiatives to strengthen their competences in the field. Their perception of the utility and feasibility of pathogen genomics for public health purposes will be a key driver for its further implementation

A practical method to implement strain-level metagenomics-based foodborne outbreak investigation and source tracking in routine

The management of a foodborne outbreak depends on the rapid and accurate identification of the responsible food source. Conventional methods based on isolation of the pathogen from the food matrix and target-specific real-time polymerase chain reactions (qPCRs) are used in routine. In recent years, the use of whole genome sequencing (WGS) of bacterial isolates has proven its value to collect relevant information for strain characterization as well as tracing the origin of the contamination by linking the food isolate with the patient’s isolate with high resolution. However, the isolation of a bacterial pathogen from food matrices is often time-consuming and not always successful. Therefore, we aimed to improve outbreak investigation by developing a method that can be implemented in reference laboratories to characterize the pathogen in the food vehicle without its prior isolation and link it back to human cases. We tested and validated a shotgun metagenomics approach by spiking food pathogens in specific food matrices using the Shiga toxin-producing Escherichia coli (STEC) as a case study. Different DNA extraction kits and enrichment procedures were investigated to obtain the most practical workflow. We demonstrated the feasibility of shotgun metagenomics to obtain the same information as in ISO/TS 13136:2012 and WGS of the isolate in parallel by inferring the genome of the contaminant and characterizing it in a shorter timeframe. This was achieved in food samples containing different E. coli strains, including a combination of different STEC strains. For the first time, we also managed to link individual strains from a food product to isolates from human cases, demonstrating the power of shotgun metagenomics for rapid outbreak investigation and source tracking